phyml-20120412/ 0000755 0001750 0001750 00000000000 11741362657 010115 5 0000000 0000000 phyml-20120412/configure.ac 0000755 0001750 0001750 00000010504 11741256215 012316 0000000 0000000 # -*- Autoconf -*-
# Process this file with autoconf to produce a configure script.
dnl AC_PREREQ(2.61)
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AC_DEFINE([UNIX],[1],[Unix tag on])
AC_DEFINE([DEBUG],[1],[Debug tag on])
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phyml-20120412/depcomp 0000755 0001750 0001750 00000044267 11331674343 011420 0000000 0000000 #! /bin/sh
# depcomp - compile a program generating dependencies as side-effects
scriptversion=2009-04-28.21; # UTC
# Copyright (C) 1999, 2000, 2003, 2004, 2005, 2006, 2007, 2009 Free
# Software Foundation, Inc.
# This program is free software; you can redistribute it and/or modify
# it under the terms of the GNU General Public License as published by
# the Free Software Foundation; either version 2, or (at your option)
# any later version.
# This program is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
# GNU General Public License for more details.
# You should have received a copy of the GNU General Public License
# along with this program. If not, see .
# As a special exception to the GNU General Public License, if you
# distribute this file as part of a program that contains a
# configuration script generated by Autoconf, you may include it under
# the same distribution terms that you use for the rest of that program.
# Originally written by Alexandre Oliva .
case $1 in
'')
echo "$0: No command. Try \`$0 --help' for more information." 1>&2
exit 1;
;;
-h | --h*)
cat <<\EOF
Usage: depcomp [--help] [--version] PROGRAM [ARGS]
Run PROGRAMS ARGS to compile a file, generating dependencies
as side-effects.
Environment variables:
depmode Dependency tracking mode.
source Source file read by `PROGRAMS ARGS'.
object Object file output by `PROGRAMS ARGS'.
DEPDIR directory where to store dependencies.
depfile Dependency file to output.
tmpdepfile Temporary file to use when outputing dependencies.
libtool Whether libtool is used (yes/no).
Report bugs to .
EOF
exit $?
;;
-v | --v*)
echo "depcomp $scriptversion"
exit $?
;;
esac
if test -z "$depmode" || test -z "$source" || test -z "$object"; then
echo "depcomp: Variables source, object and depmode must be set" 1>&2
exit 1
fi
# Dependencies for sub/bar.o or sub/bar.obj go into sub/.deps/bar.Po.
depfile=${depfile-`echo "$object" |
sed 's|[^\\/]*$|'${DEPDIR-.deps}'/&|;s|\.\([^.]*\)$|.P\1|;s|Pobj$|Po|'`}
tmpdepfile=${tmpdepfile-`echo "$depfile" | sed 's/\.\([^.]*\)$/.T\1/'`}
rm -f "$tmpdepfile"
# Some modes work just like other modes, but use different flags. We
# parameterize here, but still list the modes in the big case below,
# to make depend.m4 easier to write. Note that we *cannot* use a case
# here, because this file can only contain one case statement.
if test "$depmode" = hp; then
# HP compiler uses -M and no extra arg.
gccflag=-M
depmode=gcc
fi
if test "$depmode" = dashXmstdout; then
# This is just like dashmstdout with a different argument.
dashmflag=-xM
depmode=dashmstdout
fi
cygpath_u="cygpath -u -f -"
if test "$depmode" = msvcmsys; then
# This is just like msvisualcpp but w/o cygpath translation.
# Just convert the backslash-escaped backslashes to single forward
# slashes to satisfy depend.m4
cygpath_u="sed s,\\\\\\\\,/,g"
depmode=msvisualcpp
fi
case "$depmode" in
gcc3)
## gcc 3 implements dependency tracking that does exactly what
## we want. Yay! Note: for some reason libtool 1.4 doesn't like
## it if -MD -MP comes after the -MF stuff. Hmm.
## Unfortunately, FreeBSD c89 acceptance of flags depends upon
## the command line argument order; so add the flags where they
## appear in depend2.am. Note that the slowdown incurred here
## affects only configure: in makefiles, %FASTDEP% shortcuts this.
for arg
do
case $arg in
-c) set fnord "$@" -MT "$object" -MD -MP -MF "$tmpdepfile" "$arg" ;;
*) set fnord "$@" "$arg" ;;
esac
shift # fnord
shift # $arg
done
"$@"
stat=$?
if test $stat -eq 0; then :
else
rm -f "$tmpdepfile"
exit $stat
fi
mv "$tmpdepfile" "$depfile"
;;
gcc)
## There are various ways to get dependency output from gcc. Here's
## why we pick this rather obscure method:
## - Don't want to use -MD because we'd like the dependencies to end
## up in a subdir. Having to rename by hand is ugly.
## (We might end up doing this anyway to support other compilers.)
## - The DEPENDENCIES_OUTPUT environment variable makes gcc act like
## -MM, not -M (despite what the docs say).
## - Using -M directly means running the compiler twice (even worse
## than renaming).
if test -z "$gccflag"; then
gccflag=-MD,
fi
"$@" -Wp,"$gccflag$tmpdepfile"
stat=$?
if test $stat -eq 0; then :
else
rm -f "$tmpdepfile"
exit $stat
fi
rm -f "$depfile"
echo "$object : \\" > "$depfile"
alpha=ABCDEFGHIJKLMNOPQRSTUVWXYZabcdefghijklmnopqrstuvwxyz
## The second -e expression handles DOS-style file names with drive letters.
sed -e 's/^[^:]*: / /' \
-e 's/^['$alpha']:\/[^:]*: / /' < "$tmpdepfile" >> "$depfile"
## This next piece of magic avoids the `deleted header file' problem.
## The problem is that when a header file which appears in a .P file
## is deleted, the dependency causes make to die (because there is
## typically no way to rebuild the header). We avoid this by adding
## dummy dependencies for each header file. Too bad gcc doesn't do
## this for us directly.
tr ' ' '
' < "$tmpdepfile" |
## Some versions of gcc put a space before the `:'. On the theory
## that the space means something, we add a space to the output as
## well.
## Some versions of the HPUX 10.20 sed can't process this invocation
## correctly. Breaking it into two sed invocations is a workaround.
sed -e 's/^\\$//' -e '/^$/d' -e '/:$/d' | sed -e 's/$/ :/' >> "$depfile"
rm -f "$tmpdepfile"
;;
hp)
# This case exists only to let depend.m4 do its work. It works by
# looking at the text of this script. This case will never be run,
# since it is checked for above.
exit 1
;;
sgi)
if test "$libtool" = yes; then
"$@" "-Wp,-MDupdate,$tmpdepfile"
else
"$@" -MDupdate "$tmpdepfile"
fi
stat=$?
if test $stat -eq 0; then :
else
rm -f "$tmpdepfile"
exit $stat
fi
rm -f "$depfile"
if test -f "$tmpdepfile"; then # yes, the sourcefile depend on other files
echo "$object : \\" > "$depfile"
# Clip off the initial element (the dependent). Don't try to be
# clever and replace this with sed code, as IRIX sed won't handle
# lines with more than a fixed number of characters (4096 in
# IRIX 6.2 sed, 8192 in IRIX 6.5). We also remove comment lines;
# the IRIX cc adds comments like `#:fec' to the end of the
# dependency line.
tr ' ' '
' < "$tmpdepfile" \
| sed -e 's/^.*\.o://' -e 's/#.*$//' -e '/^$/ d' | \
tr '
' ' ' >> "$depfile"
echo >> "$depfile"
# The second pass generates a dummy entry for each header file.
tr ' ' '
' < "$tmpdepfile" \
| sed -e 's/^.*\.o://' -e 's/#.*$//' -e '/^$/ d' -e 's/$/:/' \
>> "$depfile"
else
# The sourcefile does not contain any dependencies, so just
# store a dummy comment line, to avoid errors with the Makefile
# "include basename.Plo" scheme.
echo "#dummy" > "$depfile"
fi
rm -f "$tmpdepfile"
;;
aix)
# The C for AIX Compiler uses -M and outputs the dependencies
# in a .u file. In older versions, this file always lives in the
# current directory. Also, the AIX compiler puts `$object:' at the
# start of each line; $object doesn't have directory information.
# Version 6 uses the directory in both cases.
dir=`echo "$object" | sed -e 's|/[^/]*$|/|'`
test "x$dir" = "x$object" && dir=
base=`echo "$object" | sed -e 's|^.*/||' -e 's/\.o$//' -e 's/\.lo$//'`
if test "$libtool" = yes; then
tmpdepfile1=$dir$base.u
tmpdepfile2=$base.u
tmpdepfile3=$dir.libs/$base.u
"$@" -Wc,-M
else
tmpdepfile1=$dir$base.u
tmpdepfile2=$dir$base.u
tmpdepfile3=$dir$base.u
"$@" -M
fi
stat=$?
if test $stat -eq 0; then :
else
rm -f "$tmpdepfile1" "$tmpdepfile2" "$tmpdepfile3"
exit $stat
fi
for tmpdepfile in "$tmpdepfile1" "$tmpdepfile2" "$tmpdepfile3"
do
test -f "$tmpdepfile" && break
done
if test -f "$tmpdepfile"; then
# Each line is of the form `foo.o: dependent.h'.
# Do two passes, one to just change these to
# `$object: dependent.h' and one to simply `dependent.h:'.
sed -e "s,^.*\.[a-z]*:,$object:," < "$tmpdepfile" > "$depfile"
# That's a tab and a space in the [].
sed -e 's,^.*\.[a-z]*:[ ]*,,' -e 's,$,:,' < "$tmpdepfile" >> "$depfile"
else
# The sourcefile does not contain any dependencies, so just
# store a dummy comment line, to avoid errors with the Makefile
# "include basename.Plo" scheme.
echo "#dummy" > "$depfile"
fi
rm -f "$tmpdepfile"
;;
icc)
# Intel's C compiler understands `-MD -MF file'. However on
# icc -MD -MF foo.d -c -o sub/foo.o sub/foo.c
# ICC 7.0 will fill foo.d with something like
# foo.o: sub/foo.c
# foo.o: sub/foo.h
# which is wrong. We want:
# sub/foo.o: sub/foo.c
# sub/foo.o: sub/foo.h
# sub/foo.c:
# sub/foo.h:
# ICC 7.1 will output
# foo.o: sub/foo.c sub/foo.h
# and will wrap long lines using \ :
# foo.o: sub/foo.c ... \
# sub/foo.h ... \
# ...
"$@" -MD -MF "$tmpdepfile"
stat=$?
if test $stat -eq 0; then :
else
rm -f "$tmpdepfile"
exit $stat
fi
rm -f "$depfile"
# Each line is of the form `foo.o: dependent.h',
# or `foo.o: dep1.h dep2.h \', or ` dep3.h dep4.h \'.
# Do two passes, one to just change these to
# `$object: dependent.h' and one to simply `dependent.h:'.
sed "s,^[^:]*:,$object :," < "$tmpdepfile" > "$depfile"
# Some versions of the HPUX 10.20 sed can't process this invocation
# correctly. Breaking it into two sed invocations is a workaround.
sed 's,^[^:]*: \(.*\)$,\1,;s/^\\$//;/^$/d;/:$/d' < "$tmpdepfile" |
sed -e 's/$/ :/' >> "$depfile"
rm -f "$tmpdepfile"
;;
hp2)
# The "hp" stanza above does not work with aCC (C++) and HP's ia64
# compilers, which have integrated preprocessors. The correct option
# to use with these is +Maked; it writes dependencies to a file named
# 'foo.d', which lands next to the object file, wherever that
# happens to be.
# Much of this is similar to the tru64 case; see comments there.
dir=`echo "$object" | sed -e 's|/[^/]*$|/|'`
test "x$dir" = "x$object" && dir=
base=`echo "$object" | sed -e 's|^.*/||' -e 's/\.o$//' -e 's/\.lo$//'`
if test "$libtool" = yes; then
tmpdepfile1=$dir$base.d
tmpdepfile2=$dir.libs/$base.d
"$@" -Wc,+Maked
else
tmpdepfile1=$dir$base.d
tmpdepfile2=$dir$base.d
"$@" +Maked
fi
stat=$?
if test $stat -eq 0; then :
else
rm -f "$tmpdepfile1" "$tmpdepfile2"
exit $stat
fi
for tmpdepfile in "$tmpdepfile1" "$tmpdepfile2"
do
test -f "$tmpdepfile" && break
done
if test -f "$tmpdepfile"; then
sed -e "s,^.*\.[a-z]*:,$object:," "$tmpdepfile" > "$depfile"
# Add `dependent.h:' lines.
sed -ne '2,${
s/^ *//
s/ \\*$//
s/$/:/
p
}' "$tmpdepfile" >> "$depfile"
else
echo "#dummy" > "$depfile"
fi
rm -f "$tmpdepfile" "$tmpdepfile2"
;;
tru64)
# The Tru64 compiler uses -MD to generate dependencies as a side
# effect. `cc -MD -o foo.o ...' puts the dependencies into `foo.o.d'.
# At least on Alpha/Redhat 6.1, Compaq CCC V6.2-504 seems to put
# dependencies in `foo.d' instead, so we check for that too.
# Subdirectories are respected.
dir=`echo "$object" | sed -e 's|/[^/]*$|/|'`
test "x$dir" = "x$object" && dir=
base=`echo "$object" | sed -e 's|^.*/||' -e 's/\.o$//' -e 's/\.lo$//'`
if test "$libtool" = yes; then
# With Tru64 cc, shared objects can also be used to make a
# static library. This mechanism is used in libtool 1.4 series to
# handle both shared and static libraries in a single compilation.
# With libtool 1.4, dependencies were output in $dir.libs/$base.lo.d.
#
# With libtool 1.5 this exception was removed, and libtool now
# generates 2 separate objects for the 2 libraries. These two
# compilations output dependencies in $dir.libs/$base.o.d and
# in $dir$base.o.d. We have to check for both files, because
# one of the two compilations can be disabled. We should prefer
# $dir$base.o.d over $dir.libs/$base.o.d because the latter is
# automatically cleaned when .libs/ is deleted, while ignoring
# the former would cause a distcleancheck panic.
tmpdepfile1=$dir.libs/$base.lo.d # libtool 1.4
tmpdepfile2=$dir$base.o.d # libtool 1.5
tmpdepfile3=$dir.libs/$base.o.d # libtool 1.5
tmpdepfile4=$dir.libs/$base.d # Compaq CCC V6.2-504
"$@" -Wc,-MD
else
tmpdepfile1=$dir$base.o.d
tmpdepfile2=$dir$base.d
tmpdepfile3=$dir$base.d
tmpdepfile4=$dir$base.d
"$@" -MD
fi
stat=$?
if test $stat -eq 0; then :
else
rm -f "$tmpdepfile1" "$tmpdepfile2" "$tmpdepfile3" "$tmpdepfile4"
exit $stat
fi
for tmpdepfile in "$tmpdepfile1" "$tmpdepfile2" "$tmpdepfile3" "$tmpdepfile4"
do
test -f "$tmpdepfile" && break
done
if test -f "$tmpdepfile"; then
sed -e "s,^.*\.[a-z]*:,$object:," < "$tmpdepfile" > "$depfile"
# That's a tab and a space in the [].
sed -e 's,^.*\.[a-z]*:[ ]*,,' -e 's,$,:,' < "$tmpdepfile" >> "$depfile"
else
echo "#dummy" > "$depfile"
fi
rm -f "$tmpdepfile"
;;
#nosideeffect)
# This comment above is used by automake to tell side-effect
# dependency tracking mechanisms from slower ones.
dashmstdout)
# Important note: in order to support this mode, a compiler *must*
# always write the preprocessed file to stdout, regardless of -o.
"$@" || exit $?
# Remove the call to Libtool.
if test "$libtool" = yes; then
while test "X$1" != 'X--mode=compile'; do
shift
done
shift
fi
# Remove `-o $object'.
IFS=" "
for arg
do
case $arg in
-o)
shift
;;
$object)
shift
;;
*)
set fnord "$@" "$arg"
shift # fnord
shift # $arg
;;
esac
done
test -z "$dashmflag" && dashmflag=-M
# Require at least two characters before searching for `:'
# in the target name. This is to cope with DOS-style filenames:
# a dependency such as `c:/foo/bar' could be seen as target `c' otherwise.
"$@" $dashmflag |
sed 's:^[ ]*[^: ][^:][^:]*\:[ ]*:'"$object"'\: :' > "$tmpdepfile"
rm -f "$depfile"
cat < "$tmpdepfile" > "$depfile"
tr ' ' '
' < "$tmpdepfile" | \
## Some versions of the HPUX 10.20 sed can't process this invocation
## correctly. Breaking it into two sed invocations is a workaround.
sed -e 's/^\\$//' -e '/^$/d' -e '/:$/d' | sed -e 's/$/ :/' >> "$depfile"
rm -f "$tmpdepfile"
;;
dashXmstdout)
# This case only exists to satisfy depend.m4. It is never actually
# run, as this mode is specially recognized in the preamble.
exit 1
;;
makedepend)
"$@" || exit $?
# Remove any Libtool call
if test "$libtool" = yes; then
while test "X$1" != 'X--mode=compile'; do
shift
done
shift
fi
# X makedepend
shift
cleared=no eat=no
for arg
do
case $cleared in
no)
set ""; shift
cleared=yes ;;
esac
if test $eat = yes; then
eat=no
continue
fi
case "$arg" in
-D*|-I*)
set fnord "$@" "$arg"; shift ;;
# Strip any option that makedepend may not understand. Remove
# the object too, otherwise makedepend will parse it as a source file.
-arch)
eat=yes ;;
-*|$object)
;;
*)
set fnord "$@" "$arg"; shift ;;
esac
done
obj_suffix=`echo "$object" | sed 's/^.*\././'`
touch "$tmpdepfile"
${MAKEDEPEND-makedepend} -o"$obj_suffix" -f"$tmpdepfile" "$@"
rm -f "$depfile"
cat < "$tmpdepfile" > "$depfile"
sed '1,2d' "$tmpdepfile" | tr ' ' '
' | \
## Some versions of the HPUX 10.20 sed can't process this invocation
## correctly. Breaking it into two sed invocations is a workaround.
sed -e 's/^\\$//' -e '/^$/d' -e '/:$/d' | sed -e 's/$/ :/' >> "$depfile"
rm -f "$tmpdepfile" "$tmpdepfile".bak
;;
cpp)
# Important note: in order to support this mode, a compiler *must*
# always write the preprocessed file to stdout.
"$@" || exit $?
# Remove the call to Libtool.
if test "$libtool" = yes; then
while test "X$1" != 'X--mode=compile'; do
shift
done
shift
fi
# Remove `-o $object'.
IFS=" "
for arg
do
case $arg in
-o)
shift
;;
$object)
shift
;;
*)
set fnord "$@" "$arg"
shift # fnord
shift # $arg
;;
esac
done
"$@" -E |
sed -n -e '/^# [0-9][0-9]* "\([^"]*\)".*/ s:: \1 \\:p' \
-e '/^#line [0-9][0-9]* "\([^"]*\)".*/ s:: \1 \\:p' |
sed '$ s: \\$::' > "$tmpdepfile"
rm -f "$depfile"
echo "$object : \\" > "$depfile"
cat < "$tmpdepfile" >> "$depfile"
sed < "$tmpdepfile" '/^$/d;s/^ //;s/ \\$//;s/$/ :/' >> "$depfile"
rm -f "$tmpdepfile"
;;
msvisualcpp)
# Important note: in order to support this mode, a compiler *must*
# always write the preprocessed file to stdout.
"$@" || exit $?
# Remove the call to Libtool.
if test "$libtool" = yes; then
while test "X$1" != 'X--mode=compile'; do
shift
done
shift
fi
IFS=" "
for arg
do
case "$arg" in
-o)
shift
;;
$object)
shift
;;
"-Gm"|"/Gm"|"-Gi"|"/Gi"|"-ZI"|"/ZI")
set fnord "$@"
shift
shift
;;
*)
set fnord "$@" "$arg"
shift
shift
;;
esac
done
"$@" -E 2>/dev/null |
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phyml-20120412/config.guess 0000755 0001750 0001750 00000131054 11274160642 012350 0000000 0000000 #! /bin/sh
# Attempt to guess a canonical system name.
# Copyright (C) 1992, 1993, 1994, 1995, 1996, 1997, 1998, 1999,
# 2000, 2001, 2002, 2003, 2004, 2005, 2006, 2007, 2008, 2009
# Free Software Foundation, Inc.
timestamp='2009-06-10'
# This file is free software; you can redistribute it and/or modify it
# under the terms of the GNU General Public License as published by
# the Free Software Foundation; either version 2 of the License, or
# (at your option) any later version.
#
# This program is distributed in the hope that it will be useful, but
# WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU
# General Public License for more details.
#
# You should have received a copy of the GNU General Public License
# along with this program; if not, write to the Free Software
# Foundation, Inc., 51 Franklin Street - Fifth Floor, Boston, MA
# 02110-1301, USA.
#
# As a special exception to the GNU General Public License, if you
# distribute this file as part of a program that contains a
# configuration script generated by Autoconf, you may include it under
# the same distribution terms that you use for the rest of that program.
# Originally written by Per Bothner .
# Please send patches to . Submit a context
# diff and a properly formatted ChangeLog entry.
#
# This script attempts to guess a canonical system name similar to
# config.sub. If it succeeds, it prints the system name on stdout, and
# exits with 0. Otherwise, it exits with 1.
#
# The plan is that this can be called by configure scripts if you
# don't specify an explicit build system type.
me=`echo "$0" | sed -e 's,.*/,,'`
usage="\
Usage: $0 [OPTION]
Output the configuration name of the system \`$me' is run on.
Operation modes:
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-t, --time-stamp print date of last modification, then exit
-v, --version print version number, then exit
Report bugs and patches to ."
version="\
GNU config.guess ($timestamp)
Originally written by Per Bothner.
Copyright (C) 1992, 1993, 1994, 1995, 1996, 1997, 1998, 1999, 2000, 2001,
2002, 2003, 2004, 2005, 2006, 2007, 2008 Free Software Foundation, Inc.
This is free software; see the source for copying conditions. There is NO
warranty; not even for MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE."
help="
Try \`$me --help' for more information."
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--time-stamp | --time* | -t )
echo "$timestamp" ; exit ;;
--version | -v )
echo "$version" ; exit ;;
--help | --h* | -h )
echo "$usage"; exit ;;
-- ) # Stop option processing
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break ;;
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echo "$me: invalid option $1$help" >&2
exit 1 ;;
* )
break ;;
esac
done
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set_cc_for_build='
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trap "rm -f \$tmpfiles 2>/dev/null; rmdir \$tmp 2>/dev/null; exit 1" 1 2 13 15 ;
: ${TMPDIR=/tmp} ;
{ tmp=`(umask 077 && mktemp -d "$TMPDIR/cgXXXXXX") 2>/dev/null` && test -n "$tmp" && test -d "$tmp" ; } ||
{ test -n "$RANDOM" && tmp=$TMPDIR/cg$$-$RANDOM && (umask 077 && mkdir $tmp) ; } ||
{ tmp=$TMPDIR/cg-$$ && (umask 077 && mkdir $tmp) && echo "Warning: creating insecure temp directory" >&2 ; } ||
{ echo "$me: cannot create a temporary directory in $TMPDIR" >&2 ; exit 1 ; } ;
dummy=$tmp/dummy ;
tmpfiles="$dummy.c $dummy.o $dummy.rel $dummy" ;
case $CC_FOR_BUILD,$HOST_CC,$CC in
,,) echo "int x;" > $dummy.c ;
for c in cc gcc c89 c99 ; do
if ($c -c -o $dummy.o $dummy.c) >/dev/null 2>&1 ; then
CC_FOR_BUILD="$c"; break ;
fi ;
done ;
if test x"$CC_FOR_BUILD" = x ; then
CC_FOR_BUILD=no_compiler_found ;
fi
;;
,,*) CC_FOR_BUILD=$CC ;;
,*,*) CC_FOR_BUILD=$HOST_CC ;;
esac ; set_cc_for_build= ;'
# This is needed to find uname on a Pyramid OSx when run in the BSD universe.
# (ghazi@noc.rutgers.edu 1994-08-24)
if (test -f /.attbin/uname) >/dev/null 2>&1 ; then
PATH=$PATH:/.attbin ; export PATH
fi
UNAME_MACHINE=`(uname -m) 2>/dev/null` || UNAME_MACHINE=unknown
UNAME_RELEASE=`(uname -r) 2>/dev/null` || UNAME_RELEASE=unknown
UNAME_SYSTEM=`(uname -s) 2>/dev/null` || UNAME_SYSTEM=unknown
UNAME_VERSION=`(uname -v) 2>/dev/null` || UNAME_VERSION=unknown
# Note: order is significant - the case branches are not exclusive.
case "${UNAME_MACHINE}:${UNAME_SYSTEM}:${UNAME_RELEASE}:${UNAME_VERSION}" in
*:NetBSD:*:*)
# NetBSD (nbsd) targets should (where applicable) match one or
# more of the tupples: *-*-netbsdelf*, *-*-netbsdaout*,
# *-*-netbsdecoff* and *-*-netbsd*. For targets that recently
# switched to ELF, *-*-netbsd* would select the old
# object file format. This provides both forward
# compatibility and a consistent mechanism for selecting the
# object file format.
#
# Note: NetBSD doesn't particularly care about the vendor
# portion of the name. We always set it to "unknown".
sysctl="sysctl -n hw.machine_arch"
UNAME_MACHINE_ARCH=`(/sbin/$sysctl 2>/dev/null || \
/usr/sbin/$sysctl 2>/dev/null || echo unknown)`
case "${UNAME_MACHINE_ARCH}" in
armeb) machine=armeb-unknown ;;
arm*) machine=arm-unknown ;;
sh3el) machine=shl-unknown ;;
sh3eb) machine=sh-unknown ;;
sh5el) machine=sh5le-unknown ;;
*) machine=${UNAME_MACHINE_ARCH}-unknown ;;
esac
# The Operating System including object format, if it has switched
# to ELF recently, or will in the future.
case "${UNAME_MACHINE_ARCH}" in
arm*|i386|m68k|ns32k|sh3*|sparc|vax)
eval $set_cc_for_build
if echo __ELF__ | $CC_FOR_BUILD -E - 2>/dev/null \
| grep -q __ELF__
then
# Once all utilities can be ECOFF (netbsdecoff) or a.out (netbsdaout).
# Return netbsd for either. FIX?
os=netbsd
else
os=netbsdelf
fi
;;
*)
os=netbsd
;;
esac
# The OS release
# Debian GNU/NetBSD machines have a different userland, and
# thus, need a distinct triplet. However, they do not need
# kernel version information, so it can be replaced with a
# suitable tag, in the style of linux-gnu.
case "${UNAME_VERSION}" in
Debian*)
release='-gnu'
;;
*)
release=`echo ${UNAME_RELEASE}|sed -e 's/[-_].*/\./'`
;;
esac
# Since CPU_TYPE-MANUFACTURER-KERNEL-OPERATING_SYSTEM:
# contains redundant information, the shorter form:
# CPU_TYPE-MANUFACTURER-OPERATING_SYSTEM is used.
echo "${machine}-${os}${release}"
exit ;;
*:OpenBSD:*:*)
UNAME_MACHINE_ARCH=`arch | sed 's/OpenBSD.//'`
echo ${UNAME_MACHINE_ARCH}-unknown-openbsd${UNAME_RELEASE}
exit ;;
*:ekkoBSD:*:*)
echo ${UNAME_MACHINE}-unknown-ekkobsd${UNAME_RELEASE}
exit ;;
*:SolidBSD:*:*)
echo ${UNAME_MACHINE}-unknown-solidbsd${UNAME_RELEASE}
exit ;;
macppc:MirBSD:*:*)
echo powerpc-unknown-mirbsd${UNAME_RELEASE}
exit ;;
*:MirBSD:*:*)
echo ${UNAME_MACHINE}-unknown-mirbsd${UNAME_RELEASE}
exit ;;
alpha:OSF1:*:*)
case $UNAME_RELEASE in
*4.0)
UNAME_RELEASE=`/usr/sbin/sizer -v | awk '{print $3}'`
;;
*5.*)
UNAME_RELEASE=`/usr/sbin/sizer -v | awk '{print $4}'`
;;
esac
# According to Compaq, /usr/sbin/psrinfo has been available on
# OSF/1 and Tru64 systems produced since 1995. I hope that
# covers most systems running today. This code pipes the CPU
# types through head -n 1, so we only detect the type of CPU 0.
ALPHA_CPU_TYPE=`/usr/sbin/psrinfo -v | sed -n -e 's/^ The alpha \(.*\) processor.*$/\1/p' | head -n 1`
case "$ALPHA_CPU_TYPE" in
"EV4 (21064)")
UNAME_MACHINE="alpha" ;;
"EV4.5 (21064)")
UNAME_MACHINE="alpha" ;;
"LCA4 (21066/21068)")
UNAME_MACHINE="alpha" ;;
"EV5 (21164)")
UNAME_MACHINE="alphaev5" ;;
"EV5.6 (21164A)")
UNAME_MACHINE="alphaev56" ;;
"EV5.6 (21164PC)")
UNAME_MACHINE="alphapca56" ;;
"EV5.7 (21164PC)")
UNAME_MACHINE="alphapca57" ;;
"EV6 (21264)")
UNAME_MACHINE="alphaev6" ;;
"EV6.7 (21264A)")
UNAME_MACHINE="alphaev67" ;;
"EV6.8CB (21264C)")
UNAME_MACHINE="alphaev68" ;;
"EV6.8AL (21264B)")
UNAME_MACHINE="alphaev68" ;;
"EV6.8CX (21264D)")
UNAME_MACHINE="alphaev68" ;;
"EV6.9A (21264/EV69A)")
UNAME_MACHINE="alphaev69" ;;
"EV7 (21364)")
UNAME_MACHINE="alphaev7" ;;
"EV7.9 (21364A)")
UNAME_MACHINE="alphaev79" ;;
esac
# A Pn.n version is a patched version.
# A Vn.n version is a released version.
# A Tn.n version is a released field test version.
# A Xn.n version is an unreleased experimental baselevel.
# 1.2 uses "1.2" for uname -r.
echo ${UNAME_MACHINE}-dec-osf`echo ${UNAME_RELEASE} | sed -e 's/^[PVTX]//' | tr 'ABCDEFGHIJKLMNOPQRSTUVWXYZ' 'abcdefghijklmnopqrstuvwxyz'`
exit ;;
Alpha\ *:Windows_NT*:*)
# How do we know it's Interix rather than the generic POSIX subsystem?
# Should we change UNAME_MACHINE based on the output of uname instead
# of the specific Alpha model?
echo alpha-pc-interix
exit ;;
21064:Windows_NT:50:3)
echo alpha-dec-winnt3.5
exit ;;
Amiga*:UNIX_System_V:4.0:*)
echo m68k-unknown-sysv4
exit ;;
*:[Aa]miga[Oo][Ss]:*:*)
echo ${UNAME_MACHINE}-unknown-amigaos
exit ;;
*:[Mm]orph[Oo][Ss]:*:*)
echo ${UNAME_MACHINE}-unknown-morphos
exit ;;
*:OS/390:*:*)
echo i370-ibm-openedition
exit ;;
*:z/VM:*:*)
echo s390-ibm-zvmoe
exit ;;
*:OS400:*:*)
echo powerpc-ibm-os400
exit ;;
arm:RISC*:1.[012]*:*|arm:riscix:1.[012]*:*)
echo arm-acorn-riscix${UNAME_RELEASE}
exit ;;
arm:riscos:*:*|arm:RISCOS:*:*)
echo arm-unknown-riscos
exit ;;
SR2?01:HI-UX/MPP:*:* | SR8000:HI-UX/MPP:*:*)
echo hppa1.1-hitachi-hiuxmpp
exit ;;
Pyramid*:OSx*:*:* | MIS*:OSx*:*:* | MIS*:SMP_DC-OSx*:*:*)
# akee@wpdis03.wpafb.af.mil (Earle F. Ake) contributed MIS and NILE.
if test "`(/bin/universe) 2>/dev/null`" = att ; then
echo pyramid-pyramid-sysv3
else
echo pyramid-pyramid-bsd
fi
exit ;;
NILE*:*:*:dcosx)
echo pyramid-pyramid-svr4
exit ;;
DRS?6000:unix:4.0:6*)
echo sparc-icl-nx6
exit ;;
DRS?6000:UNIX_SV:4.2*:7* | DRS?6000:isis:4.2*:7*)
case `/usr/bin/uname -p` in
sparc) echo sparc-icl-nx7; exit ;;
esac ;;
s390x:SunOS:*:*)
echo ${UNAME_MACHINE}-ibm-solaris2`echo ${UNAME_RELEASE}|sed -e 's/[^.]*//'`
exit ;;
sun4H:SunOS:5.*:*)
echo sparc-hal-solaris2`echo ${UNAME_RELEASE}|sed -e 's/[^.]*//'`
exit ;;
sun4*:SunOS:5.*:* | tadpole*:SunOS:5.*:*)
echo sparc-sun-solaris2`echo ${UNAME_RELEASE}|sed -e 's/[^.]*//'`
exit ;;
i86pc:SunOS:5.*:* | i86xen:SunOS:5.*:*)
eval $set_cc_for_build
SUN_ARCH="i386"
# If there is a compiler, see if it is configured for 64-bit objects.
# Note that the Sun cc does not turn __LP64__ into 1 like gcc does.
# This test works for both compilers.
if [ "$CC_FOR_BUILD" != 'no_compiler_found' ]; then
if (echo '#ifdef __amd64'; echo IS_64BIT_ARCH; echo '#endif') | \
(CCOPTS= $CC_FOR_BUILD -E - 2>/dev/null) | \
grep IS_64BIT_ARCH >/dev/null
then
SUN_ARCH="x86_64"
fi
fi
echo ${SUN_ARCH}-pc-solaris2`echo ${UNAME_RELEASE}|sed -e 's/[^.]*//'`
exit ;;
sun4*:SunOS:6*:*)
# According to config.sub, this is the proper way to canonicalize
# SunOS6. Hard to guess exactly what SunOS6 will be like, but
# it's likely to be more like Solaris than SunOS4.
echo sparc-sun-solaris3`echo ${UNAME_RELEASE}|sed -e 's/[^.]*//'`
exit ;;
sun4*:SunOS:*:*)
case "`/usr/bin/arch -k`" in
Series*|S4*)
UNAME_RELEASE=`uname -v`
;;
esac
# Japanese Language versions have a version number like `4.1.3-JL'.
echo sparc-sun-sunos`echo ${UNAME_RELEASE}|sed -e 's/-/_/'`
exit ;;
sun3*:SunOS:*:*)
echo m68k-sun-sunos${UNAME_RELEASE}
exit ;;
sun*:*:4.2BSD:*)
UNAME_RELEASE=`(sed 1q /etc/motd | awk '{print substr($5,1,3)}') 2>/dev/null`
test "x${UNAME_RELEASE}" = "x" && UNAME_RELEASE=3
case "`/bin/arch`" in
sun3)
echo m68k-sun-sunos${UNAME_RELEASE}
;;
sun4)
echo sparc-sun-sunos${UNAME_RELEASE}
;;
esac
exit ;;
aushp:SunOS:*:*)
echo sparc-auspex-sunos${UNAME_RELEASE}
exit ;;
# The situation for MiNT is a little confusing. The machine name
# can be virtually everything (everything which is not
# "atarist" or "atariste" at least should have a processor
# > m68000). The system name ranges from "MiNT" over "FreeMiNT"
# to the lowercase version "mint" (or "freemint"). Finally
# the system name "TOS" denotes a system which is actually not
# MiNT. But MiNT is downward compatible to TOS, so this should
# be no problem.
atarist[e]:*MiNT:*:* | atarist[e]:*mint:*:* | atarist[e]:*TOS:*:*)
echo m68k-atari-mint${UNAME_RELEASE}
exit ;;
atari*:*MiNT:*:* | atari*:*mint:*:* | atarist[e]:*TOS:*:*)
echo m68k-atari-mint${UNAME_RELEASE}
exit ;;
*falcon*:*MiNT:*:* | *falcon*:*mint:*:* | *falcon*:*TOS:*:*)
echo m68k-atari-mint${UNAME_RELEASE}
exit ;;
milan*:*MiNT:*:* | milan*:*mint:*:* | *milan*:*TOS:*:*)
echo m68k-milan-mint${UNAME_RELEASE}
exit ;;
hades*:*MiNT:*:* | hades*:*mint:*:* | *hades*:*TOS:*:*)
echo m68k-hades-mint${UNAME_RELEASE}
exit ;;
*:*MiNT:*:* | *:*mint:*:* | *:*TOS:*:*)
echo m68k-unknown-mint${UNAME_RELEASE}
exit ;;
m68k:machten:*:*)
echo m68k-apple-machten${UNAME_RELEASE}
exit ;;
powerpc:machten:*:*)
echo powerpc-apple-machten${UNAME_RELEASE}
exit ;;
RISC*:Mach:*:*)
echo mips-dec-mach_bsd4.3
exit ;;
RISC*:ULTRIX:*:*)
echo mips-dec-ultrix${UNAME_RELEASE}
exit ;;
VAX*:ULTRIX*:*:*)
echo vax-dec-ultrix${UNAME_RELEASE}
exit ;;
2020:CLIX:*:* | 2430:CLIX:*:*)
echo clipper-intergraph-clix${UNAME_RELEASE}
exit ;;
mips:*:*:UMIPS | mips:*:*:RISCos)
eval $set_cc_for_build
sed 's/^ //' << EOF >$dummy.c
#ifdef __cplusplus
#include /* for printf() prototype */
int main (int argc, char *argv[]) {
#else
int main (argc, argv) int argc; char *argv[]; {
#endif
#if defined (host_mips) && defined (MIPSEB)
#if defined (SYSTYPE_SYSV)
printf ("mips-mips-riscos%ssysv\n", argv[1]); exit (0);
#endif
#if defined (SYSTYPE_SVR4)
printf ("mips-mips-riscos%ssvr4\n", argv[1]); exit (0);
#endif
#if defined (SYSTYPE_BSD43) || defined(SYSTYPE_BSD)
printf ("mips-mips-riscos%sbsd\n", argv[1]); exit (0);
#endif
#endif
exit (-1);
}
EOF
$CC_FOR_BUILD -o $dummy $dummy.c &&
dummyarg=`echo "${UNAME_RELEASE}" | sed -n 's/\([0-9]*\).*/\1/p'` &&
SYSTEM_NAME=`$dummy $dummyarg` &&
{ echo "$SYSTEM_NAME"; exit; }
echo mips-mips-riscos${UNAME_RELEASE}
exit ;;
Motorola:PowerMAX_OS:*:*)
echo powerpc-motorola-powermax
exit ;;
Motorola:*:4.3:PL8-*)
echo powerpc-harris-powermax
exit ;;
Night_Hawk:*:*:PowerMAX_OS | Synergy:PowerMAX_OS:*:*)
echo powerpc-harris-powermax
exit ;;
Night_Hawk:Power_UNIX:*:*)
echo powerpc-harris-powerunix
exit ;;
m88k:CX/UX:7*:*)
echo m88k-harris-cxux7
exit ;;
m88k:*:4*:R4*)
echo m88k-motorola-sysv4
exit ;;
m88k:*:3*:R3*)
echo m88k-motorola-sysv3
exit ;;
AViiON:dgux:*:*)
# DG/UX returns AViiON for all architectures
UNAME_PROCESSOR=`/usr/bin/uname -p`
if [ $UNAME_PROCESSOR = mc88100 ] || [ $UNAME_PROCESSOR = mc88110 ]
then
if [ ${TARGET_BINARY_INTERFACE}x = m88kdguxelfx ] || \
[ ${TARGET_BINARY_INTERFACE}x = x ]
then
echo m88k-dg-dgux${UNAME_RELEASE}
else
echo m88k-dg-dguxbcs${UNAME_RELEASE}
fi
else
echo i586-dg-dgux${UNAME_RELEASE}
fi
exit ;;
M88*:DolphinOS:*:*) # DolphinOS (SVR3)
echo m88k-dolphin-sysv3
exit ;;
M88*:*:R3*:*)
# Delta 88k system running SVR3
echo m88k-motorola-sysv3
exit ;;
XD88*:*:*:*) # Tektronix XD88 system running UTekV (SVR3)
echo m88k-tektronix-sysv3
exit ;;
Tek43[0-9][0-9]:UTek:*:*) # Tektronix 4300 system running UTek (BSD)
echo m68k-tektronix-bsd
exit ;;
*:IRIX*:*:*)
echo mips-sgi-irix`echo ${UNAME_RELEASE}|sed -e 's/-/_/g'`
exit ;;
????????:AIX?:[12].1:2) # AIX 2.2.1 or AIX 2.1.1 is RT/PC AIX.
echo romp-ibm-aix # uname -m gives an 8 hex-code CPU id
exit ;; # Note that: echo "'`uname -s`'" gives 'AIX '
i*86:AIX:*:*)
echo i386-ibm-aix
exit ;;
ia64:AIX:*:*)
if [ -x /usr/bin/oslevel ] ; then
IBM_REV=`/usr/bin/oslevel`
else
IBM_REV=${UNAME_VERSION}.${UNAME_RELEASE}
fi
echo ${UNAME_MACHINE}-ibm-aix${IBM_REV}
exit ;;
*:AIX:2:3)
if grep bos325 /usr/include/stdio.h >/dev/null 2>&1; then
eval $set_cc_for_build
sed 's/^ //' << EOF >$dummy.c
#include
main()
{
if (!__power_pc())
exit(1);
puts("powerpc-ibm-aix3.2.5");
exit(0);
}
EOF
if $CC_FOR_BUILD -o $dummy $dummy.c && SYSTEM_NAME=`$dummy`
then
echo "$SYSTEM_NAME"
else
echo rs6000-ibm-aix3.2.5
fi
elif grep bos324 /usr/include/stdio.h >/dev/null 2>&1; then
echo rs6000-ibm-aix3.2.4
else
echo rs6000-ibm-aix3.2
fi
exit ;;
*:AIX:*:[456])
IBM_CPU_ID=`/usr/sbin/lsdev -C -c processor -S available | sed 1q | awk '{ print $1 }'`
if /usr/sbin/lsattr -El ${IBM_CPU_ID} | grep ' POWER' >/dev/null 2>&1; then
IBM_ARCH=rs6000
else
IBM_ARCH=powerpc
fi
if [ -x /usr/bin/oslevel ] ; then
IBM_REV=`/usr/bin/oslevel`
else
IBM_REV=${UNAME_VERSION}.${UNAME_RELEASE}
fi
echo ${IBM_ARCH}-ibm-aix${IBM_REV}
exit ;;
*:AIX:*:*)
echo rs6000-ibm-aix
exit ;;
ibmrt:4.4BSD:*|romp-ibm:BSD:*)
echo romp-ibm-bsd4.4
exit ;;
ibmrt:*BSD:*|romp-ibm:BSD:*) # covers RT/PC BSD and
echo romp-ibm-bsd${UNAME_RELEASE} # 4.3 with uname added to
exit ;; # report: romp-ibm BSD 4.3
*:BOSX:*:*)
echo rs6000-bull-bosx
exit ;;
DPX/2?00:B.O.S.:*:*)
echo m68k-bull-sysv3
exit ;;
9000/[34]??:4.3bsd:1.*:*)
echo m68k-hp-bsd
exit ;;
hp300:4.4BSD:*:* | 9000/[34]??:4.3bsd:2.*:*)
echo m68k-hp-bsd4.4
exit ;;
9000/[34678]??:HP-UX:*:*)
HPUX_REV=`echo ${UNAME_RELEASE}|sed -e 's/[^.]*.[0B]*//'`
case "${UNAME_MACHINE}" in
9000/31? ) HP_ARCH=m68000 ;;
9000/[34]?? ) HP_ARCH=m68k ;;
9000/[678][0-9][0-9])
if [ -x /usr/bin/getconf ]; then
sc_cpu_version=`/usr/bin/getconf SC_CPU_VERSION 2>/dev/null`
sc_kernel_bits=`/usr/bin/getconf SC_KERNEL_BITS 2>/dev/null`
case "${sc_cpu_version}" in
523) HP_ARCH="hppa1.0" ;; # CPU_PA_RISC1_0
528) HP_ARCH="hppa1.1" ;; # CPU_PA_RISC1_1
532) # CPU_PA_RISC2_0
case "${sc_kernel_bits}" in
32) HP_ARCH="hppa2.0n" ;;
64) HP_ARCH="hppa2.0w" ;;
'') HP_ARCH="hppa2.0" ;; # HP-UX 10.20
esac ;;
esac
fi
if [ "${HP_ARCH}" = "" ]; then
eval $set_cc_for_build
sed 's/^ //' << EOF >$dummy.c
#define _HPUX_SOURCE
#include
#include
int main ()
{
#if defined(_SC_KERNEL_BITS)
long bits = sysconf(_SC_KERNEL_BITS);
#endif
long cpu = sysconf (_SC_CPU_VERSION);
switch (cpu)
{
case CPU_PA_RISC1_0: puts ("hppa1.0"); break;
case CPU_PA_RISC1_1: puts ("hppa1.1"); break;
case CPU_PA_RISC2_0:
#if defined(_SC_KERNEL_BITS)
switch (bits)
{
case 64: puts ("hppa2.0w"); break;
case 32: puts ("hppa2.0n"); break;
default: puts ("hppa2.0"); break;
} break;
#else /* !defined(_SC_KERNEL_BITS) */
puts ("hppa2.0"); break;
#endif
default: puts ("hppa1.0"); break;
}
exit (0);
}
EOF
(CCOPTS= $CC_FOR_BUILD -o $dummy $dummy.c 2>/dev/null) && HP_ARCH=`$dummy`
test -z "$HP_ARCH" && HP_ARCH=hppa
fi ;;
esac
if [ ${HP_ARCH} = "hppa2.0w" ]
then
eval $set_cc_for_build
# hppa2.0w-hp-hpux* has a 64-bit kernel and a compiler generating
# 32-bit code. hppa64-hp-hpux* has the same kernel and a compiler
# generating 64-bit code. GNU and HP use different nomenclature:
#
# $ CC_FOR_BUILD=cc ./config.guess
# => hppa2.0w-hp-hpux11.23
# $ CC_FOR_BUILD="cc +DA2.0w" ./config.guess
# => hppa64-hp-hpux11.23
if echo __LP64__ | (CCOPTS= $CC_FOR_BUILD -E - 2>/dev/null) |
grep -q __LP64__
then
HP_ARCH="hppa2.0w"
else
HP_ARCH="hppa64"
fi
fi
echo ${HP_ARCH}-hp-hpux${HPUX_REV}
exit ;;
ia64:HP-UX:*:*)
HPUX_REV=`echo ${UNAME_RELEASE}|sed -e 's/[^.]*.[0B]*//'`
echo ia64-hp-hpux${HPUX_REV}
exit ;;
3050*:HI-UX:*:*)
eval $set_cc_for_build
sed 's/^ //' << EOF >$dummy.c
#include
int
main ()
{
long cpu = sysconf (_SC_CPU_VERSION);
/* The order matters, because CPU_IS_HP_MC68K erroneously returns
true for CPU_PA_RISC1_0. CPU_IS_PA_RISC returns correct
results, however. */
if (CPU_IS_PA_RISC (cpu))
{
switch (cpu)
{
case CPU_PA_RISC1_0: puts ("hppa1.0-hitachi-hiuxwe2"); break;
case CPU_PA_RISC1_1: puts ("hppa1.1-hitachi-hiuxwe2"); break;
case CPU_PA_RISC2_0: puts ("hppa2.0-hitachi-hiuxwe2"); break;
default: puts ("hppa-hitachi-hiuxwe2"); break;
}
}
else if (CPU_IS_HP_MC68K (cpu))
puts ("m68k-hitachi-hiuxwe2");
else puts ("unknown-hitachi-hiuxwe2");
exit (0);
}
EOF
$CC_FOR_BUILD -o $dummy $dummy.c && SYSTEM_NAME=`$dummy` &&
{ echo "$SYSTEM_NAME"; exit; }
echo unknown-hitachi-hiuxwe2
exit ;;
9000/7??:4.3bsd:*:* | 9000/8?[79]:4.3bsd:*:* )
echo hppa1.1-hp-bsd
exit ;;
9000/8??:4.3bsd:*:*)
echo hppa1.0-hp-bsd
exit ;;
*9??*:MPE/iX:*:* | *3000*:MPE/iX:*:*)
echo hppa1.0-hp-mpeix
exit ;;
hp7??:OSF1:*:* | hp8?[79]:OSF1:*:* )
echo hppa1.1-hp-osf
exit ;;
hp8??:OSF1:*:*)
echo hppa1.0-hp-osf
exit ;;
i*86:OSF1:*:*)
if [ -x /usr/sbin/sysversion ] ; then
echo ${UNAME_MACHINE}-unknown-osf1mk
else
echo ${UNAME_MACHINE}-unknown-osf1
fi
exit ;;
parisc*:Lites*:*:*)
echo hppa1.1-hp-lites
exit ;;
C1*:ConvexOS:*:* | convex:ConvexOS:C1*:*)
echo c1-convex-bsd
exit ;;
C2*:ConvexOS:*:* | convex:ConvexOS:C2*:*)
if getsysinfo -f scalar_acc
then echo c32-convex-bsd
else echo c2-convex-bsd
fi
exit ;;
C34*:ConvexOS:*:* | convex:ConvexOS:C34*:*)
echo c34-convex-bsd
exit ;;
C38*:ConvexOS:*:* | convex:ConvexOS:C38*:*)
echo c38-convex-bsd
exit ;;
C4*:ConvexOS:*:* | convex:ConvexOS:C4*:*)
echo c4-convex-bsd
exit ;;
CRAY*Y-MP:*:*:*)
echo ymp-cray-unicos${UNAME_RELEASE} | sed -e 's/\.[^.]*$/.X/'
exit ;;
CRAY*[A-Z]90:*:*:*)
echo ${UNAME_MACHINE}-cray-unicos${UNAME_RELEASE} \
| sed -e 's/CRAY.*\([A-Z]90\)/\1/' \
-e y/ABCDEFGHIJKLMNOPQRSTUVWXYZ/abcdefghijklmnopqrstuvwxyz/ \
-e 's/\.[^.]*$/.X/'
exit ;;
CRAY*TS:*:*:*)
echo t90-cray-unicos${UNAME_RELEASE} | sed -e 's/\.[^.]*$/.X/'
exit ;;
CRAY*T3E:*:*:*)
echo alphaev5-cray-unicosmk${UNAME_RELEASE} | sed -e 's/\.[^.]*$/.X/'
exit ;;
CRAY*SV1:*:*:*)
echo sv1-cray-unicos${UNAME_RELEASE} | sed -e 's/\.[^.]*$/.X/'
exit ;;
*:UNICOS/mp:*:*)
echo craynv-cray-unicosmp${UNAME_RELEASE} | sed -e 's/\.[^.]*$/.X/'
exit ;;
F30[01]:UNIX_System_V:*:* | F700:UNIX_System_V:*:*)
FUJITSU_PROC=`uname -m | tr 'ABCDEFGHIJKLMNOPQRSTUVWXYZ' 'abcdefghijklmnopqrstuvwxyz'`
FUJITSU_SYS=`uname -p | tr 'ABCDEFGHIJKLMNOPQRSTUVWXYZ' 'abcdefghijklmnopqrstuvwxyz' | sed -e 's/\///'`
FUJITSU_REL=`echo ${UNAME_RELEASE} | sed -e 's/ /_/'`
echo "${FUJITSU_PROC}-fujitsu-${FUJITSU_SYS}${FUJITSU_REL}"
exit ;;
5000:UNIX_System_V:4.*:*)
FUJITSU_SYS=`uname -p | tr 'ABCDEFGHIJKLMNOPQRSTUVWXYZ' 'abcdefghijklmnopqrstuvwxyz' | sed -e 's/\///'`
FUJITSU_REL=`echo ${UNAME_RELEASE} | tr 'ABCDEFGHIJKLMNOPQRSTUVWXYZ' 'abcdefghijklmnopqrstuvwxyz' | sed -e 's/ /_/'`
echo "sparc-fujitsu-${FUJITSU_SYS}${FUJITSU_REL}"
exit ;;
i*86:BSD/386:*:* | i*86:BSD/OS:*:* | *:Ascend\ Embedded/OS:*:*)
echo ${UNAME_MACHINE}-pc-bsdi${UNAME_RELEASE}
exit ;;
sparc*:BSD/OS:*:*)
echo sparc-unknown-bsdi${UNAME_RELEASE}
exit ;;
*:BSD/OS:*:*)
echo ${UNAME_MACHINE}-unknown-bsdi${UNAME_RELEASE}
exit ;;
*:FreeBSD:*:*)
case ${UNAME_MACHINE} in
pc98)
echo i386-unknown-freebsd`echo ${UNAME_RELEASE}|sed -e 's/[-(].*//'` ;;
amd64)
echo x86_64-unknown-freebsd`echo ${UNAME_RELEASE}|sed -e 's/[-(].*//'` ;;
*)
echo ${UNAME_MACHINE}-unknown-freebsd`echo ${UNAME_RELEASE}|sed -e 's/[-(].*//'` ;;
esac
exit ;;
i*:CYGWIN*:*)
echo ${UNAME_MACHINE}-pc-cygwin
exit ;;
*:MINGW*:*)
echo ${UNAME_MACHINE}-pc-mingw32
exit ;;
i*:windows32*:*)
# uname -m includes "-pc" on this system.
echo ${UNAME_MACHINE}-mingw32
exit ;;
i*:PW*:*)
echo ${UNAME_MACHINE}-pc-pw32
exit ;;
*:Interix*:[3456]*)
case ${UNAME_MACHINE} in
x86)
echo i586-pc-interix${UNAME_RELEASE}
exit ;;
EM64T | authenticamd | genuineintel)
echo x86_64-unknown-interix${UNAME_RELEASE}
exit ;;
IA64)
echo ia64-unknown-interix${UNAME_RELEASE}
exit ;;
esac ;;
[345]86:Windows_95:* | [345]86:Windows_98:* | [345]86:Windows_NT:*)
echo i${UNAME_MACHINE}-pc-mks
exit ;;
8664:Windows_NT:*)
echo x86_64-pc-mks
exit ;;
i*:Windows_NT*:* | Pentium*:Windows_NT*:*)
# How do we know it's Interix rather than the generic POSIX subsystem?
# It also conflicts with pre-2.0 versions of AT&T UWIN. Should we
# UNAME_MACHINE based on the output of uname instead of i386?
echo i586-pc-interix
exit ;;
i*:UWIN*:*)
echo ${UNAME_MACHINE}-pc-uwin
exit ;;
amd64:CYGWIN*:*:* | x86_64:CYGWIN*:*:*)
echo x86_64-unknown-cygwin
exit ;;
p*:CYGWIN*:*)
echo powerpcle-unknown-cygwin
exit ;;
prep*:SunOS:5.*:*)
echo powerpcle-unknown-solaris2`echo ${UNAME_RELEASE}|sed -e 's/[^.]*//'`
exit ;;
*:GNU:*:*)
# the GNU system
echo `echo ${UNAME_MACHINE}|sed -e 's,[-/].*$,,'`-unknown-gnu`echo ${UNAME_RELEASE}|sed -e 's,/.*$,,'`
exit ;;
*:GNU/*:*:*)
# other systems with GNU libc and userland
echo ${UNAME_MACHINE}-unknown-`echo ${UNAME_SYSTEM} | sed 's,^[^/]*/,,' | tr '[A-Z]' '[a-z]'``echo ${UNAME_RELEASE}|sed -e 's/[-(].*//'`-gnu
exit ;;
i*86:Minix:*:*)
echo ${UNAME_MACHINE}-pc-minix
exit ;;
arm*:Linux:*:*)
eval $set_cc_for_build
if echo __ARM_EABI__ | $CC_FOR_BUILD -E - 2>/dev/null \
| grep -q __ARM_EABI__
then
echo ${UNAME_MACHINE}-unknown-linux-gnu
else
echo ${UNAME_MACHINE}-unknown-linux-gnueabi
fi
exit ;;
avr32*:Linux:*:*)
echo ${UNAME_MACHINE}-unknown-linux-gnu
exit ;;
cris:Linux:*:*)
echo cris-axis-linux-gnu
exit ;;
crisv32:Linux:*:*)
echo crisv32-axis-linux-gnu
exit ;;
frv:Linux:*:*)
echo frv-unknown-linux-gnu
exit ;;
ia64:Linux:*:*)
echo ${UNAME_MACHINE}-unknown-linux-gnu
exit ;;
m32r*:Linux:*:*)
echo ${UNAME_MACHINE}-unknown-linux-gnu
exit ;;
m68*:Linux:*:*)
echo ${UNAME_MACHINE}-unknown-linux-gnu
exit ;;
mips:Linux:*:* | mips64:Linux:*:*)
eval $set_cc_for_build
sed 's/^ //' << EOF >$dummy.c
#undef CPU
#undef ${UNAME_MACHINE}
#undef ${UNAME_MACHINE}el
#if defined(__MIPSEL__) || defined(__MIPSEL) || defined(_MIPSEL) || defined(MIPSEL)
CPU=${UNAME_MACHINE}el
#else
#if defined(__MIPSEB__) || defined(__MIPSEB) || defined(_MIPSEB) || defined(MIPSEB)
CPU=${UNAME_MACHINE}
#else
CPU=
#endif
#endif
EOF
eval "`$CC_FOR_BUILD -E $dummy.c 2>/dev/null | sed -n '
/^CPU/{
s: ::g
p
}'`"
test x"${CPU}" != x && { echo "${CPU}-unknown-linux-gnu"; exit; }
;;
or32:Linux:*:*)
echo or32-unknown-linux-gnu
exit ;;
ppc:Linux:*:*)
echo powerpc-unknown-linux-gnu
exit ;;
ppc64:Linux:*:*)
echo powerpc64-unknown-linux-gnu
exit ;;
alpha:Linux:*:*)
case `sed -n '/^cpu model/s/^.*: \(.*\)/\1/p' < /proc/cpuinfo` in
EV5) UNAME_MACHINE=alphaev5 ;;
EV56) UNAME_MACHINE=alphaev56 ;;
PCA56) UNAME_MACHINE=alphapca56 ;;
PCA57) UNAME_MACHINE=alphapca56 ;;
EV6) UNAME_MACHINE=alphaev6 ;;
EV67) UNAME_MACHINE=alphaev67 ;;
EV68*) UNAME_MACHINE=alphaev68 ;;
esac
objdump --private-headers /bin/sh | grep -q ld.so.1
if test "$?" = 0 ; then LIBC="libc1" ; else LIBC="" ; fi
echo ${UNAME_MACHINE}-unknown-linux-gnu${LIBC}
exit ;;
padre:Linux:*:*)
echo sparc-unknown-linux-gnu
exit ;;
parisc:Linux:*:* | hppa:Linux:*:*)
# Look for CPU level
case `grep '^cpu[^a-z]*:' /proc/cpuinfo 2>/dev/null | cut -d' ' -f2` in
PA7*) echo hppa1.1-unknown-linux-gnu ;;
PA8*) echo hppa2.0-unknown-linux-gnu ;;
*) echo hppa-unknown-linux-gnu ;;
esac
exit ;;
parisc64:Linux:*:* | hppa64:Linux:*:*)
echo hppa64-unknown-linux-gnu
exit ;;
s390:Linux:*:* | s390x:Linux:*:*)
echo ${UNAME_MACHINE}-ibm-linux
exit ;;
sh64*:Linux:*:*)
echo ${UNAME_MACHINE}-unknown-linux-gnu
exit ;;
sh*:Linux:*:*)
echo ${UNAME_MACHINE}-unknown-linux-gnu
exit ;;
sparc:Linux:*:* | sparc64:Linux:*:*)
echo ${UNAME_MACHINE}-unknown-linux-gnu
exit ;;
vax:Linux:*:*)
echo ${UNAME_MACHINE}-dec-linux-gnu
exit ;;
x86_64:Linux:*:*)
echo x86_64-unknown-linux-gnu
exit ;;
xtensa*:Linux:*:*)
echo ${UNAME_MACHINE}-unknown-linux-gnu
exit ;;
i*86:Linux:*:*)
# The BFD linker knows what the default object file format is, so
# first see if it will tell us. cd to the root directory to prevent
# problems with other programs or directories called `ld' in the path.
# Set LC_ALL=C to ensure ld outputs messages in English.
ld_supported_targets=`cd /; LC_ALL=C ld --help 2>&1 \
| sed -ne '/supported targets:/!d
s/[ ][ ]*/ /g
s/.*supported targets: *//
s/ .*//
p'`
case "$ld_supported_targets" in
elf32-i386)
TENTATIVE="${UNAME_MACHINE}-pc-linux-gnu"
;;
esac
# Determine whether the default compiler is a.out or elf
eval $set_cc_for_build
sed 's/^ //' << EOF >$dummy.c
#include
#ifdef __ELF__
# ifdef __GLIBC__
# if __GLIBC__ >= 2
LIBC=gnu
# else
LIBC=gnulibc1
# endif
# else
LIBC=gnulibc1
# endif
#else
#if defined(__INTEL_COMPILER) || defined(__PGI) || defined(__SUNPRO_C) || defined(__SUNPRO_CC)
LIBC=gnu
#else
LIBC=gnuaout
#endif
#endif
#ifdef __dietlibc__
LIBC=dietlibc
#endif
EOF
eval "`$CC_FOR_BUILD -E $dummy.c 2>/dev/null | sed -n '
/^LIBC/{
s: ::g
p
}'`"
test x"${LIBC}" != x && {
echo "${UNAME_MACHINE}-pc-linux-${LIBC}"
exit
}
test x"${TENTATIVE}" != x && { echo "${TENTATIVE}"; exit; }
;;
i*86:DYNIX/ptx:4*:*)
# ptx 4.0 does uname -s correctly, with DYNIX/ptx in there.
# earlier versions are messed up and put the nodename in both
# sysname and nodename.
echo i386-sequent-sysv4
exit ;;
i*86:UNIX_SV:4.2MP:2.*)
# Unixware is an offshoot of SVR4, but it has its own version
# number series starting with 2...
# I am not positive that other SVR4 systems won't match this,
# I just have to hope. -- rms.
# Use sysv4.2uw... so that sysv4* matches it.
echo ${UNAME_MACHINE}-pc-sysv4.2uw${UNAME_VERSION}
exit ;;
i*86:OS/2:*:*)
# If we were able to find `uname', then EMX Unix compatibility
# is probably installed.
echo ${UNAME_MACHINE}-pc-os2-emx
exit ;;
i*86:XTS-300:*:STOP)
echo ${UNAME_MACHINE}-unknown-stop
exit ;;
i*86:atheos:*:*)
echo ${UNAME_MACHINE}-unknown-atheos
exit ;;
i*86:syllable:*:*)
echo ${UNAME_MACHINE}-pc-syllable
exit ;;
i*86:LynxOS:2.*:* | i*86:LynxOS:3.[01]*:* | i*86:LynxOS:4.[02]*:*)
echo i386-unknown-lynxos${UNAME_RELEASE}
exit ;;
i*86:*DOS:*:*)
echo ${UNAME_MACHINE}-pc-msdosdjgpp
exit ;;
i*86:*:4.*:* | i*86:SYSTEM_V:4.*:*)
UNAME_REL=`echo ${UNAME_RELEASE} | sed 's/\/MP$//'`
if grep Novell /usr/include/link.h >/dev/null 2>/dev/null; then
echo ${UNAME_MACHINE}-univel-sysv${UNAME_REL}
else
echo ${UNAME_MACHINE}-pc-sysv${UNAME_REL}
fi
exit ;;
i*86:*:5:[678]*)
# UnixWare 7.x, OpenUNIX and OpenServer 6.
case `/bin/uname -X | grep "^Machine"` in
*486*) UNAME_MACHINE=i486 ;;
*Pentium) UNAME_MACHINE=i586 ;;
*Pent*|*Celeron) UNAME_MACHINE=i686 ;;
esac
echo ${UNAME_MACHINE}-unknown-sysv${UNAME_RELEASE}${UNAME_SYSTEM}${UNAME_VERSION}
exit ;;
i*86:*:3.2:*)
if test -f /usr/options/cb.name; then
UNAME_REL=`sed -n 's/.*Version //p' /dev/null >/dev/null ; then
UNAME_REL=`(/bin/uname -X|grep Release|sed -e 's/.*= //')`
(/bin/uname -X|grep i80486 >/dev/null) && UNAME_MACHINE=i486
(/bin/uname -X|grep '^Machine.*Pentium' >/dev/null) \
&& UNAME_MACHINE=i586
(/bin/uname -X|grep '^Machine.*Pent *II' >/dev/null) \
&& UNAME_MACHINE=i686
(/bin/uname -X|grep '^Machine.*Pentium Pro' >/dev/null) \
&& UNAME_MACHINE=i686
echo ${UNAME_MACHINE}-pc-sco$UNAME_REL
else
echo ${UNAME_MACHINE}-pc-sysv32
fi
exit ;;
pc:*:*:*)
# Left here for compatibility:
# uname -m prints for DJGPP always 'pc', but it prints nothing about
# the processor, so we play safe by assuming i586.
# Note: whatever this is, it MUST be the same as what config.sub
# prints for the "djgpp" host, or else GDB configury will decide that
# this is a cross-build.
echo i586-pc-msdosdjgpp
exit ;;
Intel:Mach:3*:*)
echo i386-pc-mach3
exit ;;
paragon:*:*:*)
echo i860-intel-osf1
exit ;;
i860:*:4.*:*) # i860-SVR4
if grep Stardent /usr/include/sys/uadmin.h >/dev/null 2>&1 ; then
echo i860-stardent-sysv${UNAME_RELEASE} # Stardent Vistra i860-SVR4
else # Add other i860-SVR4 vendors below as they are discovered.
echo i860-unknown-sysv${UNAME_RELEASE} # Unknown i860-SVR4
fi
exit ;;
mini*:CTIX:SYS*5:*)
# "miniframe"
echo m68010-convergent-sysv
exit ;;
mc68k:UNIX:SYSTEM5:3.51m)
echo m68k-convergent-sysv
exit ;;
M680?0:D-NIX:5.3:*)
echo m68k-diab-dnix
exit ;;
M68*:*:R3V[5678]*:*)
test -r /sysV68 && { echo 'm68k-motorola-sysv'; exit; } ;;
3[345]??:*:4.0:3.0 | 3[34]??A:*:4.0:3.0 | 3[34]??,*:*:4.0:3.0 | 3[34]??/*:*:4.0:3.0 | 4400:*:4.0:3.0 | 4850:*:4.0:3.0 | SKA40:*:4.0:3.0 | SDS2:*:4.0:3.0 | SHG2:*:4.0:3.0 | S7501*:*:4.0:3.0)
OS_REL=''
test -r /etc/.relid \
&& OS_REL=.`sed -n 's/[^ ]* [^ ]* \([0-9][0-9]\).*/\1/p' < /etc/.relid`
/bin/uname -p 2>/dev/null | grep 86 >/dev/null \
&& { echo i486-ncr-sysv4.3${OS_REL}; exit; }
/bin/uname -p 2>/dev/null | /bin/grep entium >/dev/null \
&& { echo i586-ncr-sysv4.3${OS_REL}; exit; } ;;
3[34]??:*:4.0:* | 3[34]??,*:*:4.0:*)
/bin/uname -p 2>/dev/null | grep 86 >/dev/null \
&& { echo i486-ncr-sysv4; exit; } ;;
NCR*:*:4.2:* | MPRAS*:*:4.2:*)
OS_REL='.3'
test -r /etc/.relid \
&& OS_REL=.`sed -n 's/[^ ]* [^ ]* \([0-9][0-9]\).*/\1/p' < /etc/.relid`
/bin/uname -p 2>/dev/null | grep 86 >/dev/null \
&& { echo i486-ncr-sysv4.3${OS_REL}; exit; }
/bin/uname -p 2>/dev/null | /bin/grep entium >/dev/null \
&& { echo i586-ncr-sysv4.3${OS_REL}; exit; }
/bin/uname -p 2>/dev/null | /bin/grep pteron >/dev/null \
&& { echo i586-ncr-sysv4.3${OS_REL}; exit; } ;;
m68*:LynxOS:2.*:* | m68*:LynxOS:3.0*:*)
echo m68k-unknown-lynxos${UNAME_RELEASE}
exit ;;
mc68030:UNIX_System_V:4.*:*)
echo m68k-atari-sysv4
exit ;;
TSUNAMI:LynxOS:2.*:*)
echo sparc-unknown-lynxos${UNAME_RELEASE}
exit ;;
rs6000:LynxOS:2.*:*)
echo rs6000-unknown-lynxos${UNAME_RELEASE}
exit ;;
PowerPC:LynxOS:2.*:* | PowerPC:LynxOS:3.[01]*:* | PowerPC:LynxOS:4.[02]*:*)
echo powerpc-unknown-lynxos${UNAME_RELEASE}
exit ;;
SM[BE]S:UNIX_SV:*:*)
echo mips-dde-sysv${UNAME_RELEASE}
exit ;;
RM*:ReliantUNIX-*:*:*)
echo mips-sni-sysv4
exit ;;
RM*:SINIX-*:*:*)
echo mips-sni-sysv4
exit ;;
*:SINIX-*:*:*)
if uname -p 2>/dev/null >/dev/null ; then
UNAME_MACHINE=`(uname -p) 2>/dev/null`
echo ${UNAME_MACHINE}-sni-sysv4
else
echo ns32k-sni-sysv
fi
exit ;;
PENTIUM:*:4.0*:*) # Unisys `ClearPath HMP IX 4000' SVR4/MP effort
# says
echo i586-unisys-sysv4
exit ;;
*:UNIX_System_V:4*:FTX*)
# From Gerald Hewes .
# How about differentiating between stratus architectures? -djm
echo hppa1.1-stratus-sysv4
exit ;;
*:*:*:FTX*)
# From seanf@swdc.stratus.com.
echo i860-stratus-sysv4
exit ;;
i*86:VOS:*:*)
# From Paul.Green@stratus.com.
echo ${UNAME_MACHINE}-stratus-vos
exit ;;
*:VOS:*:*)
# From Paul.Green@stratus.com.
echo hppa1.1-stratus-vos
exit ;;
mc68*:A/UX:*:*)
echo m68k-apple-aux${UNAME_RELEASE}
exit ;;
news*:NEWS-OS:6*:*)
echo mips-sony-newsos6
exit ;;
R[34]000:*System_V*:*:* | R4000:UNIX_SYSV:*:* | R*000:UNIX_SV:*:*)
if [ -d /usr/nec ]; then
echo mips-nec-sysv${UNAME_RELEASE}
else
echo mips-unknown-sysv${UNAME_RELEASE}
fi
exit ;;
BeBox:BeOS:*:*) # BeOS running on hardware made by Be, PPC only.
echo powerpc-be-beos
exit ;;
BeMac:BeOS:*:*) # BeOS running on Mac or Mac clone, PPC only.
echo powerpc-apple-beos
exit ;;
BePC:BeOS:*:*) # BeOS running on Intel PC compatible.
echo i586-pc-beos
exit ;;
BePC:Haiku:*:*) # Haiku running on Intel PC compatible.
echo i586-pc-haiku
exit ;;
SX-4:SUPER-UX:*:*)
echo sx4-nec-superux${UNAME_RELEASE}
exit ;;
SX-5:SUPER-UX:*:*)
echo sx5-nec-superux${UNAME_RELEASE}
exit ;;
SX-6:SUPER-UX:*:*)
echo sx6-nec-superux${UNAME_RELEASE}
exit ;;
SX-7:SUPER-UX:*:*)
echo sx7-nec-superux${UNAME_RELEASE}
exit ;;
SX-8:SUPER-UX:*:*)
echo sx8-nec-superux${UNAME_RELEASE}
exit ;;
SX-8R:SUPER-UX:*:*)
echo sx8r-nec-superux${UNAME_RELEASE}
exit ;;
Power*:Rhapsody:*:*)
echo powerpc-apple-rhapsody${UNAME_RELEASE}
exit ;;
*:Rhapsody:*:*)
echo ${UNAME_MACHINE}-apple-rhapsody${UNAME_RELEASE}
exit ;;
*:Darwin:*:*)
UNAME_PROCESSOR=`uname -p` || UNAME_PROCESSOR=unknown
case $UNAME_PROCESSOR in
unknown) UNAME_PROCESSOR=powerpc ;;
esac
echo ${UNAME_PROCESSOR}-apple-darwin${UNAME_RELEASE}
exit ;;
*:procnto*:*:* | *:QNX:[0123456789]*:*)
UNAME_PROCESSOR=`uname -p`
if test "$UNAME_PROCESSOR" = "x86"; then
UNAME_PROCESSOR=i386
UNAME_MACHINE=pc
fi
echo ${UNAME_PROCESSOR}-${UNAME_MACHINE}-nto-qnx${UNAME_RELEASE}
exit ;;
*:QNX:*:4*)
echo i386-pc-qnx
exit ;;
NSE-?:NONSTOP_KERNEL:*:*)
echo nse-tandem-nsk${UNAME_RELEASE}
exit ;;
NSR-?:NONSTOP_KERNEL:*:*)
echo nsr-tandem-nsk${UNAME_RELEASE}
exit ;;
*:NonStop-UX:*:*)
echo mips-compaq-nonstopux
exit ;;
BS2000:POSIX*:*:*)
echo bs2000-siemens-sysv
exit ;;
DS/*:UNIX_System_V:*:*)
echo ${UNAME_MACHINE}-${UNAME_SYSTEM}-${UNAME_RELEASE}
exit ;;
*:Plan9:*:*)
# "uname -m" is not consistent, so use $cputype instead. 386
# is converted to i386 for consistency with other x86
# operating systems.
if test "$cputype" = "386"; then
UNAME_MACHINE=i386
else
UNAME_MACHINE="$cputype"
fi
echo ${UNAME_MACHINE}-unknown-plan9
exit ;;
*:TOPS-10:*:*)
echo pdp10-unknown-tops10
exit ;;
*:TENEX:*:*)
echo pdp10-unknown-tenex
exit ;;
KS10:TOPS-20:*:* | KL10:TOPS-20:*:* | TYPE4:TOPS-20:*:*)
echo pdp10-dec-tops20
exit ;;
XKL-1:TOPS-20:*:* | TYPE5:TOPS-20:*:*)
echo pdp10-xkl-tops20
exit ;;
*:TOPS-20:*:*)
echo pdp10-unknown-tops20
exit ;;
*:ITS:*:*)
echo pdp10-unknown-its
exit ;;
SEI:*:*:SEIUX)
echo mips-sei-seiux${UNAME_RELEASE}
exit ;;
*:DragonFly:*:*)
echo ${UNAME_MACHINE}-unknown-dragonfly`echo ${UNAME_RELEASE}|sed -e 's/[-(].*//'`
exit ;;
*:*VMS:*:*)
UNAME_MACHINE=`(uname -p) 2>/dev/null`
case "${UNAME_MACHINE}" in
A*) echo alpha-dec-vms ; exit ;;
I*) echo ia64-dec-vms ; exit ;;
V*) echo vax-dec-vms ; exit ;;
esac ;;
*:XENIX:*:SysV)
echo i386-pc-xenix
exit ;;
i*86:skyos:*:*)
echo ${UNAME_MACHINE}-pc-skyos`echo ${UNAME_RELEASE}` | sed -e 's/ .*$//'
exit ;;
i*86:rdos:*:*)
echo ${UNAME_MACHINE}-pc-rdos
exit ;;
i*86:AROS:*:*)
echo ${UNAME_MACHINE}-pc-aros
exit ;;
esac
#echo '(No uname command or uname output not recognized.)' 1>&2
#echo "${UNAME_MACHINE}:${UNAME_SYSTEM}:${UNAME_RELEASE}:${UNAME_VERSION}" 1>&2
eval $set_cc_for_build
cat >$dummy.c <
# include
#endif
main ()
{
#if defined (sony)
#if defined (MIPSEB)
/* BFD wants "bsd" instead of "newsos". Perhaps BFD should be changed,
I don't know.... */
printf ("mips-sony-bsd\n"); exit (0);
#else
#include
printf ("m68k-sony-newsos%s\n",
#ifdef NEWSOS4
"4"
#else
""
#endif
); exit (0);
#endif
#endif
#if defined (__arm) && defined (__acorn) && defined (__unix)
printf ("arm-acorn-riscix\n"); exit (0);
#endif
#if defined (hp300) && !defined (hpux)
printf ("m68k-hp-bsd\n"); exit (0);
#endif
#if defined (NeXT)
#if !defined (__ARCHITECTURE__)
#define __ARCHITECTURE__ "m68k"
#endif
int version;
version=`(hostinfo | sed -n 's/.*NeXT Mach \([0-9]*\).*/\1/p') 2>/dev/null`;
if (version < 4)
printf ("%s-next-nextstep%d\n", __ARCHITECTURE__, version);
else
printf ("%s-next-openstep%d\n", __ARCHITECTURE__, version);
exit (0);
#endif
#if defined (MULTIMAX) || defined (n16)
#if defined (UMAXV)
printf ("ns32k-encore-sysv\n"); exit (0);
#else
#if defined (CMU)
printf ("ns32k-encore-mach\n"); exit (0);
#else
printf ("ns32k-encore-bsd\n"); exit (0);
#endif
#endif
#endif
#if defined (__386BSD__)
printf ("i386-pc-bsd\n"); exit (0);
#endif
#if defined (sequent)
#if defined (i386)
printf ("i386-sequent-dynix\n"); exit (0);
#endif
#if defined (ns32000)
printf ("ns32k-sequent-dynix\n"); exit (0);
#endif
#endif
#if defined (_SEQUENT_)
struct utsname un;
uname(&un);
if (strncmp(un.version, "V2", 2) == 0) {
printf ("i386-sequent-ptx2\n"); exit (0);
}
if (strncmp(un.version, "V1", 2) == 0) { /* XXX is V1 correct? */
printf ("i386-sequent-ptx1\n"); exit (0);
}
printf ("i386-sequent-ptx\n"); exit (0);
#endif
#if defined (vax)
# if !defined (ultrix)
# include
# if defined (BSD)
# if BSD == 43
printf ("vax-dec-bsd4.3\n"); exit (0);
# else
# if BSD == 199006
printf ("vax-dec-bsd4.3reno\n"); exit (0);
# else
printf ("vax-dec-bsd\n"); exit (0);
# endif
# endif
# else
printf ("vax-dec-bsd\n"); exit (0);
# endif
# else
printf ("vax-dec-ultrix\n"); exit (0);
# endif
#endif
#if defined (alliant) && defined (i860)
printf ("i860-alliant-bsd\n"); exit (0);
#endif
exit (1);
}
EOF
$CC_FOR_BUILD -o $dummy $dummy.c 2>/dev/null && SYSTEM_NAME=`$dummy` &&
{ echo "$SYSTEM_NAME"; exit; }
# Apollos put the system type in the environment.
test -d /usr/apollo && { echo ${ISP}-apollo-${SYSTYPE}; exit; }
# Convex versions that predate uname can use getsysinfo(1)
if [ -x /usr/convex/getsysinfo ]
then
case `getsysinfo -f cpu_type` in
c1*)
echo c1-convex-bsd
exit ;;
c2*)
if getsysinfo -f scalar_acc
then echo c32-convex-bsd
else echo c2-convex-bsd
fi
exit ;;
c34*)
echo c34-convex-bsd
exit ;;
c38*)
echo c38-convex-bsd
exit ;;
c4*)
echo c4-convex-bsd
exit ;;
esac
fi
cat >&2 < in order to provide the needed
information to handle your system.
config.guess timestamp = $timestamp
uname -m = `(uname -m) 2>/dev/null || echo unknown`
uname -r = `(uname -r) 2>/dev/null || echo unknown`
uname -s = `(uname -s) 2>/dev/null || echo unknown`
uname -v = `(uname -v) 2>/dev/null || echo unknown`
/usr/bin/uname -p = `(/usr/bin/uname -p) 2>/dev/null`
/bin/uname -X = `(/bin/uname -X) 2>/dev/null`
hostinfo = `(hostinfo) 2>/dev/null`
/bin/universe = `(/bin/universe) 2>/dev/null`
/usr/bin/arch -k = `(/usr/bin/arch -k) 2>/dev/null`
/bin/arch = `(/bin/arch) 2>/dev/null`
/usr/bin/oslevel = `(/usr/bin/oslevel) 2>/dev/null`
/usr/convex/getsysinfo = `(/usr/convex/getsysinfo) 2>/dev/null`
UNAME_MACHINE = ${UNAME_MACHINE}
UNAME_RELEASE = ${UNAME_RELEASE}
UNAME_SYSTEM = ${UNAME_SYSTEM}
UNAME_VERSION = ${UNAME_VERSION}
EOF
exit 1
# Local variables:
# eval: (add-hook 'write-file-hooks 'time-stamp)
# time-stamp-start: "timestamp='"
# time-stamp-format: "%:y-%02m-%02d"
# time-stamp-end: "'"
# End:
phyml-20120412/bin/ 0000755 0001750 0001750 00000000000 11321753770 010657 5 0000000 0000000 phyml-20120412/bin/phyml.bat 0000755 0001750 0001750 00000000430 11321753770 012420 0000000 0000000 @echo off
cls
color 1B
mode con:cols=98
mode con:lines=50
if not exist phyml.exe goto error
if exist phyml.exe then goto launch
echo on
:launch
phyml
goto end
:error
echo Error - can't find `phyml.exe'
pause
goto end
:end
echo Execution finished
pause
phyml-20120412/bin/.svn/ 0000755 0001750 0001750 00000000000 11741256231 011537 5 0000000 0000000 phyml-20120412/bin/.svn/prop-base/ 0000755 0001750 0001750 00000000000 11321753767 013441 5 0000000 0000000 phyml-20120412/bin/.svn/prop-base/phyml.bat.svn-base 0000555 0001750 0001750 00000000036 11321753767 016717 0000000 0000000 K 14
svn:executable
V 1
*
END
phyml-20120412/bin/.svn/props/ 0000755 0001750 0001750 00000000000 11321753767 012714 5 0000000 0000000 phyml-20120412/bin/.svn/all-wcprops 0000555 0001750 0001750 00000000234 11321753767 013657 0000000 0000000 K 25
svn:wc:ra_dav:version-url
V 27
/svn/!svn/ver/236/trunk/bin
END
phyml.bat
K 25
svn:wc:ra_dav:version-url
V 37
/svn/!svn/ver/236/trunk/bin/phyml.bat
END
phyml-20120412/bin/.svn/entries 0000444 0001750 0001750 00000000463 11424121257 013051 0000000 0000000 10
dir
557
https://phyml.googlecode.com/svn/trunk/bin
https://phyml.googlecode.com/svn
2009-05-06T09:32:26.424212Z
236
stephane.guindon
phyml.bat
file
2010-01-09T01:12:24.000000Z
17bdc7c3feabb576a87264db2749bdb4
2009-05-06T09:32:26.424212Z
236
stephane.guindon
has-props
280
phyml-20120412/bin/.svn/tmp/ 0000755 0001750 0001750 00000000000 11424121257 012334 5 0000000 0000000 phyml-20120412/bin/.svn/tmp/prop-base/ 0000755 0001750 0001750 00000000000 11321753770 014233 5 0000000 0000000 phyml-20120412/bin/.svn/tmp/props/ 0000755 0001750 0001750 00000000000 11321753770 013506 5 0000000 0000000 phyml-20120412/bin/.svn/tmp/text-base/ 0000755 0001750 0001750 00000000000 11321753770 014237 5 0000000 0000000 phyml-20120412/bin/.svn/text-base/ 0000755 0001750 0001750 00000000000 11321753770 013437 5 0000000 0000000 phyml-20120412/bin/.svn/text-base/phyml.bat.svn-base 0000555 0001750 0001750 00000000430 11321753770 016713 0000000 0000000 @echo off
cls
color 1B
mode con:cols=98
mode con:lines=50
if not exist phyml.exe goto error
if exist phyml.exe then goto launch
echo on
:launch
phyml
goto end
:error
echo Error - can't find `phyml.exe'
pause
goto end
:end
echo Execution finished
pause
phyml-20120412/ChangeLog 0000755 0001750 0001750 00000032607 11321753770 011614 0000000 0000000
Version date what has been changed
5.0 26.08.2000 - changes to manual, Makefile.in
- cpREV hidden by -DCPREV flag
- chi2test, quartio included into source code files
- generic scr/Makefile.generic
- src/makefile.com for VAX
- AUTHORS, README, ChangeLog updated
- INSTALL checked
27.08.2000 - test code excluded
- '-randseed#' added for debugging purposes
- ./align added to autoconf/automake
- warning output if cmdline parameter unknown
11.10.2000 - fixed output of rate categories of sites before
computing them
- check whether rate categories were computed by
1st user tree or NJ tree fixed in the output
12.10.2000 - invariant site model normalization fixed
CODE FREEZE
===========
5.0.a33 15.08.2000 - changes for autoconf/automake
5.0.a32 01.08.2000 - a FPE error fixed (badq == 0)
- small error in -bestq fixed
- fflush's added at several places
5.0.a31 01.08.2000 - comments added to tree structure sorting puzzle2.c
- changes in configure.in, Makefile.in
5.0.a30 23.07.2000 - some debugging in checkquart
- changed to autoconf
5.0.a29 13.07.2000 - some debugging in checkquart
5.0.a28 13.07.2000 - use best quartet topology option (-bestq) implemented
5.0.a27 13.07.2000 - further developement to checkquart
- ascii/binary quartet values (-wqla/-wqlb)
- typo correction
5.0.a26 11.07.2000 - fflush at all checktimer
- further developement at checkquart
- possibility to write quartet values to file (-wqlh)
5.0.a25 06.07.2000 - fflush at checktimer
5.0.a24 02.07.2000 - further debugging of checkquart
5.0.a23 02.07.2000 - further developement to checkquart
5.0.a22 29.06.2000 - checkquart added to makefile
- bad quartet stats added after reading in *.allquarts
5.0.a21 27.06.2000 - site pattern statistics implemented and added to
SEQUENCE ALIGNMENT section in puzzle report
5.0.a20 26.06.2000 - cpREV45 implemented
5.0.a19 26.06.2000 - for debugging purposes: typo "MPE" changed to "FPE"
- fflush(stdout) added in chi2test
5.0.a18 20.06.2000 - checkquart implemented
5.0.a17 19.06.2000 - FPRINTF(STDOUTFILE and STDOUT definition changed
and moved; fputid/fputid10 writes to STDOUT instead
of stdout
- ppuzzle checks slaves enough slave-processes
- numquarts, num2quart, quart2num moved from ppuzzle.c
to puzzle1.c
- read/writeallquart implemented (undocumented feature)
to be used by -wqf/-rqf at comandline
-wqf = write quartet file (infilename.allquart) after
quartet evaluation
-rqf = read quartet file (infilename.allquart), no
quartet evaluation, unless -wqf is used as
well, then quartets are written and read in
- '-h' option at comandline -> printusage
5.0.a16 31.05.2000 - chi2test bug fixed
- WAG matrix added, model choice adopted
13.06.2000 - date set to June 2000
- author order changed to Schmidt, Strimmer, Vingron,
v.Haeseler
- CPU time output stopped, due to overflow errors
16.06.2000 - sequence composition chi2test moved before
parameter output.
- output of chi2test and bad quartet statistics split,
to do the chi2test output earlier.
5.0.a15 02.05.2000 - Names changed back from TREE-PUZZLE to PUZZLE
09.05.2000 - and to TREE-PUZZLE again ;-)
5.0.a14 13.03.2000 - Changes to the manual.
- Executable names changed to (p)treepuzzle.
(changes in the makefiles)
15.03.2000 - Output of parameters after estimation added.
5.0.a13 18.02.2000 - ALPHA version number removed from the code
5.0.a12 18.02.2000 - CPU time measurement problems fixed for case where
clock_t is an unsigned type.
5.0.a11 17.02.2000 - time measure problems (CPU/wallclock) fixed
not all features in addtimes are used at the moment.
- unnecessary and unused routines removed fron source
code.
5.0.a10 20.01.2000 - Name changes from PUZZLE to TREE-PUZZLE
- Chi2-fit model guessing for VT model added
- little model printing bug fixed
5.0.a9 22.12.1999 - VT Model incorporated (Mueller, Vingron (2000)
JCB, to appear).
- TODO: Chi2-fit model guessing for VT model
5.0.a8 21.12.1999 - 'sys/times.h' and 'sys/types.h' removed from
puzzle.h. They were neither ANSI conform nor
necessary, but occured in the SUN man pages.
- Definition and call of writetimesstat eliminated
from the sequention version by compiler switched,
and not just the function body as before.
- '-O4' canged to '-O' to be more generic.
5.0.a7 21.12.1999 - Macro constants introduced for data_optn
(NUCLEOTIDE, AMINOACID, BINARY)
- round robbing of datatype and AA model option changed
in menu to make adjustment of the model possible by a
determined sequence of letters:
'd': Auto -> Nucleotides
-> Amino acids
-> Binary states
-> Auto
('m' && data_optn == AMINOACID):
Auto -> Dayhoff
-> JTT
-> mtREV24
-> BLOSUM62
-> Auto
- manual.html adjusted
5.0.a6 20.12.1999 - new manual.html added
5.0.a5 07.12.1999 - output bug fixed (bestrates were written before they
were computed)
5.0.a4 02.12.1999 - header file inclusion ajusted:
added: #include
changed from: #include "ppuzzle.h"
to: #ifdef PARALLEL
# include "ppuzzle.h"
#endif
5.0.a3 27.11.1999 - '-h' comandline option removed, because of problems
with MPICH under LINUX
- new memory leaks of 5.0.a2 closed in PP_Finalize
5.0.a2 27.11.1999 - Cleanup of the source code
- Measurement of CPU time added
- Parallel load statistics added (quartets, trees, time)
to puzzle report.
- Cleanup debug messages
- Comments "[...]" are removed from usertrees now.
- single quotes will only be printed arount species
names if -DUSEQUOTES is set at compiletime.
- tree likelihood is printed infront of a tree as a
comment, [ lh=-xx.xxxxx ](...);
5.0.a1 26.11.1999 - Cleanup of the directories
- Copyright changes
- Version changes
VERSION CHANGE
==============
4.1.a26 25.11.1999 - Makefile made universal for pauzzle and ppuzzle
- lines not needed removed from puzzle.h
4.1.a25 19.11.1999 - Output file prefixes for distances, trees, and
puzzlereport changed in user trees analysis case
to user tree file name
- Temporary output of likelihood to treefile added
4.1.a24 11.11.1999 - Output of puzzling step trees changed
ptorder: [ orderno # % ID #UniqTopos #Steps ]PHYLIP
pstep: chunk #InChunk sum ID #UniqTopos #Steps
- preliminary leap frog RNG implemented, i.e. uses
the rand4 in the usual way in the sequential case.
If run in parallel all rand4 are initialized with
the same seed and started with PP_Myid-th random
number. after that each process uses the every
PP_NumProcs-th random number to make sure that these
unique.
4.1.a23 08.11.1999 - output of sequential and parallel version to *.pstep
made identical
4.1.a22 05.11.1999 - two different puzzle step tree outputs intruduced
and added to the menu ("[ 1. 35 ](...);":
- ordered unique tree list -> *.ptorder
Format: "[ 1. 35 ]" (Ordernumber, Amount)
- chronological tree list -> *.pstep
Format: "[ 1. 35 ]" (Chunknumber, Amount in chunk)
(the last is a problem in parallel, because the come
in chunks, as scheduled)
- debugged the output
4.1.a21 04.11.1999 - Makefile adjustments for other Plattforms
- pstep tree output changed. unique treestructures
printed to *.pstep file with a leading comment
containing an order number and the ammount padded
with blanks (e.g. "[ 1. 356 ]('mouse'...").
output is done right before writing the puzzle file.
- controlled MPI finish to the Quit menu option added
4.1.a20 03.11.1999 - some garbage collection (free) added
- makefile adjusted, OFLAGS for optimization added
(ppuzzle/MPICH has problems with -O, so the
ppuzzle is created without optimization)
Some minor changes in the makefiles
- still to do: garbage collection from 'internalnode'
in master process
4.1.a19 13.10.1999 - adding the output of standardized (i.e. sorted)
puzzling step trees. Those are printed to the
standard output at the moment. (Routines to sort
and print the trees implemented)
14.10.1999 - routines for printing the sorted trees to a string.
needed to send them between Master and Worker, and
to have a unique key to sort and count the trees.
21.10.1999 - counting of sorted trees implemented by doubly linked
list, sort routine, print to stdout
25.10.1999 - change place of writing distances to file right after
distances have been computed.
- output of puzzling step trees now with true name,
not numbers
02.11.1999 - parallel counting and sending of puzzling step trees
- some parallel sending bugs fixed
4.1.a18 14.09.1999 - adding possibility to specify input file at
command line, this specifies also the output
filenames (puzzle output: *.puzzle; treefile:
*.tree; distances: *.dist; Triangel EPS: *.eps;
unresolved: *.qlist; puzzling step trees: *.pstep)
If an unexisting name is given, one has to reenter
the right name, but the wrong one is used as prefix.
15.09.1999 - sending back of bad quartets from slaves added
- bug in quart2num fixed (not used before; was shifted
by 1)
- first version of a README added ;-)
4.1.a17 03.08.1999 - Recv-Error in receiving DoPuzzleBlock fixed
- double freeing of same MPI_Datatype fixed
- changing of scheduling algorithm to smaller chunks
in gss -> sgss
13.09.1999 - bug fixed in optimization routine in ml2.c:
boundary check added
4.1.a16 12.07.1999 - slight changes in verbosity levels
- changed all printf to FPRINTF(STDOUTFILE to
change easily from stdout to a file.
4.1.a15 08.07.1999 - scheduler for both parallel parts
- several small changes
4.1.a14 25.06.1999 - computation of tree parallel, scheduler dependent,
sending all biparts in one message instead of one
by one
- several small changes since a13 in sched.c, et al.
4.1.a13 10.06.1999 - computation of tree parallel (chunk = #trees/#slaves)
- scheduling schemes implemented for minimum chunk sizes
4.1.a12 07.06.1999 - computation of quartets properly parallel
- scheduling implemented
- counting of quartets by slave ajusted
- TODO: sending of bad quartets (array + list)
- distinction between '1st user tree' and 'NJ tree'
in result output removed again
4.1.a11 28.05.1999 - PP_SendDoQuartBlock, PP_RecvDoQuartBlock,
PP_SendQuartBlock, PP_RecvQuartBlock
- mallocquartets() changed from global to local
variables to be more flexible
- Quartet computation moved to slave (badquartet
handling missing: output, badquartet vector);
- distinction between '1st user tree' and 'NJ tree'
added in result output (puzzle1.c around l.1756)
4.1.a10 20.05.1999 - num2quart, numquarts, quart2num introduced
- parallel init/finalize, quartets computed on
master and slave, compared -> equal -> all necessary
parameter exported
4.1.a9 19.05.1999 - 'dvector forg' removed from onepamratematrix
cmdline, because it's not used in the function.
4.1.a8 18.05.1999 - add _GAMMA_ (not necessary) to gamma.h and _PUZZLE_
to puzzle.h to avoid dublicate includes, possible
due to ppuzzle.h
- ppuzzle added to makefile and to check
- 1st parallel version but no slave computations
only sending parameters and done signals.
4.1.a7 18.05.1999 - export reevaluation of tree and evaluation of
usertrees to evaluatetree.
4.1.a6 17.05.1999 - -DNEWFORLOOP added to fixed.src, because the changed
for loop structure changes the sequence of randomized
quartets during likelihood mapping
- change 'int main()' to 'int main(argc, argv)'
- export more functionalities from main:
memcleanup(), inputandinit(&argc, &argv)
- grouping if's (excluding eachother) together in
switch()
- split treereavaluation and 1st usertree,
evaluate all usertrees together (TODO: both,
treereavaluation and usertrees in one loop)
- MAKE CHECK added to ./makefile
4.1.a5 16.05.1999 - adding ´dvector Brnlength´ to lslength cmdline to
reduce globality of Brnlength. (Later better to *Tree)
4.1.a4 11.05.1999 - structure of for loops changed in computeallquartets
and recon_tree, so that the quarted addresses are in
one contigous sequence (for a
#ifndef RATES_H
#define RATES_H
#include "utilities.h"
#include "spr.h"
#include "lk.h"
#include "optimiz.h"
#include "bionj.h"
#include "models.h"
#include "free.h"
#include "help.h"
#include "simu.h"
#include "eigen.h"
#include "pars.h"
#include "alrt.h"
#include "time.h"
#include "m4.h"
#include "draw.h"
#include "mcmc.h"
#include "stats.h"
void RATES_Monte_Carlo_Mean_Rates(t_tree *tree);
void RATES_Monte_Carlo_Mean_Rates_Pre(t_node *a, t_node *d, t_edge *b, phydbl curr_rate, t_tree *tree);
void RATES_Print_Rates(t_tree *tree);
void RATES_Print_Rates_Pre(t_node *a, t_node *d, t_edge *b, t_tree *tree);
t_rate *RATES_Make_Rate_Struct(int n_otu);
void RATES_Init_Rate_Struct(t_rate *rates, t_rate *existing_rates, int n_otu);
void RATES_Classify_Branches(t_tree *tree);
void RATES_Adjust_Rates(t_tree *tree);
void RATES_Adjust_Rates_Local_Pre(t_node *a, t_node *d, t_edge *b, t_tree *tree);
void RATES_Adjust_Rates_Local(t_node *a, t_node *d, t_edge *b1, t_tree *tree);
void RATES_Record_T(t_tree *tree);
void RATES_Restore_T(t_tree *tree);
void RATES_Monte_Carlo_Mean_Rates_Core(phydbl t_lim_sup, phydbl t_lim_inf, phydbl *curr_rate, phydbl *mean_rate, phydbl lexp, phydbl alpha);
phydbl RATES_Lk_Rates(t_tree *tree);
void RATES_Lk_Rates_Pre(t_node *a, t_node *d, t_edge *b, t_tree *tree);
void RATES_Fill_Node_Rates_Pre(t_node *a, t_node *d, t_edge *b, phydbl *node_r, t_tree *tree);
void RATES_Fill_Node_Rates(phydbl *node_r, t_tree *tree);
void RATES_Optimize_Node_Times_Serie_Fixed_Br_Len(t_node *a, t_node *d, t_tree *tree);
void RATES_Optimize_Lexp(t_tree *tree);
void RATES_Round_Optimize(t_tree *tree);
void RATES_Optimize_Lexp(t_tree *tree);
void RATES_Optimize_Alpha(t_tree *tree);
phydbl RATES_Dmu(phydbl mu, int n_jumps, phydbl dt, phydbl a, phydbl b, phydbl lexp, int min_n, int jps_dens);
phydbl RATES_Dr_X_Dx(phydbl r, phydbl mu, phydbl y, phydbl dt, phydbl a, phydbl b, phydbl lexp);
phydbl RATES_Dmu_Given_Y_Trpzd(phydbl mu, phydbl y, phydbl dt, phydbl a, phydbl b, phydbl lexp,
int nsteps, phydbl beg, phydbl end, phydbl prevs);
phydbl RATES_Dmu_Given_Y_Std(phydbl mu, phydbl y, phydbl dt, phydbl a, phydbl b, phydbl lexp);
phydbl RATES_Dmu_Given_Y_Romb(phydbl mu, phydbl y, phydbl dt, phydbl a, phydbl b, phydbl lexp);
phydbl RATES_Dmu_Given_Y(phydbl mu, phydbl y, phydbl dt, phydbl a, phydbl b, phydbl lexp);
phydbl RATES_Dy_Given_Mu(phydbl mu, phydbl y, phydbl dt, phydbl a, phydbl b, phydbl lexp);
phydbl RATES_Dmu2_Given_Y_X_Dy_Given_Mu1(phydbl mu1, phydbl mu2, phydbl y, phydbl dt1, phydbl dt2, phydbl a, phydbl b, phydbl lexp);
phydbl RATES_Dmu2_Given_Mu1_Trpz(phydbl mu1, phydbl mu2, phydbl dt1, phydbl dt2, phydbl a, phydbl b, phydbl lexp,
int nsteps, phydbl beg, phydbl end, phydbl prevs);
phydbl RATES_Dmu2_And_Mu1(phydbl mu1, phydbl mu2, phydbl dt1, phydbl dt2, phydbl a, phydbl b, phydbl lexp);
phydbl RATES_Dmu2_Given_Mu1(phydbl mu1, phydbl mu2, phydbl dt1, phydbl dt2, phydbl a, phydbl b, phydbl lexp);
phydbl RATES_Dmu2_Given_Mu1_Romb(phydbl mu1, phydbl mu2, phydbl dt1, phydbl dt2, phydbl a, phydbl b, phydbl lexp);
void RATES_Random_Branch_Lengths(t_tree *tree);
void RATES_Bracket_N_Jumps(int *up, int *down, phydbl param);
void RATES_Set_Node_Times(t_tree *tree);
void RATES_Set_Node_Times_Pre(t_node *a, t_node *d, t_tree *tree);
void RATES_Optimize_Node_Times(t_tree *tree);
phydbl RATES_Exp_Y(phydbl mu1, phydbl mu2, phydbl dt1, phydbl lexp);
phydbl RATES_Dmu2_Given_Mu1_Bis(phydbl mu1, phydbl mu2, phydbl dt1, phydbl dt2, phydbl alpha, phydbl beta, phydbl lexp);
void RATES_Replace_Br_Lengths_By_Rates_Pre(t_node *a, t_node *d, t_edge *b, t_tree *tree);
void RATES_Replace_Br_Lengths_By_Rates(t_tree *tree);
void RATES_Get_Mean_Rates(t_tree *tree);
void RATES_Get_Mean_Rates_Pre(t_node *a, t_node *d, t_edge *b, phydbl r_a, t_tree *tree);
void RATES_Expect_Number_Subst(phydbl t_beg, phydbl t_end, phydbl r_beg, int *n_jumps, phydbl *mean_r, phydbl *r_end, t_rate *rates, t_tree *tree);
void RATES_Optimize_Clock_Rate(t_tree *tree);
phydbl RATES_Dmu1_Given_Lbda_And_Mu2(phydbl lbda, phydbl mu1, phydbl mu2, phydbl alpha, phydbl beta);
phydbl RATES_Dmu1_And_Mu2_One_Jump_Trpz(phydbl mu1, phydbl mu2, phydbl a, phydbl b,
int nsteps, phydbl beg, phydbl end, phydbl prevs);
phydbl RATES_Dmu1_And_Mu2_One_Jump_One_Interval(phydbl mu1, phydbl mu2, phydbl a, phydbl b);
phydbl RATES_Dmu1_And_Mu2_One_Jump_Two_Intervals(phydbl dt1, phydbl dt2, phydbl mu1, phydbl mu2, phydbl a, phydbl b);
phydbl RATES_Dmu1_And_Mu2_One_Jump_Old(phydbl mu1, phydbl mu2, phydbl a, phydbl b);
phydbl RATES_Dmu2_And_Min_N_Given_Mu1(phydbl mu1, phydbl mu2, phydbl dt1, phydbl dt2, int n_min, phydbl a, phydbl b, phydbl lexp);
phydbl RATES_Dmu2_And_Mu1_Given_N(phydbl mu1, phydbl mu2, phydbl dt1, phydbl dt2, int n, phydbl a, phydbl b, phydbl lexp);
phydbl RATES_Lk_Rates_Core(phydbl br_r_a, phydbl br_r_d, phydbl nd_r_a, phydbl nd_r_d, int n_a, int n_d, phydbl dt_a, phydbl dt_d, t_tree *tree);
void RATES_Init_Triplets(t_tree *tree);
phydbl RATES_Lk_Change_One_Time(t_node *n, phydbl new_t, t_tree *tree);
void RATES_Update_Triplet(t_node *n, t_tree *tree);
void RATES_Print_Triplets(t_tree *tree);
phydbl RATES_Lk_Change_One_Rate(t_node *d, phydbl new_rate, t_tree *tree);
phydbl RATES_Dmu2_And_Mu1_Given_Min_N(phydbl mu1, phydbl mu2, phydbl dt1, phydbl dt2, int n_min, phydbl a, phydbl b, phydbl lexp);
phydbl RATES_Dmu2_And_Mu1_Given_N_Normal(phydbl mu1, phydbl mu2, phydbl dt1, phydbl dt2, int n, phydbl a, phydbl b, phydbl lexp);
phydbl RATES_Coeff_Corr(phydbl alpha, phydbl beta, int n1, int n2);
phydbl RATES_Dmu2_And_Mu1_Given_N_Full(phydbl mu1, phydbl mu2, phydbl dt1, phydbl dt2, int n, phydbl a, phydbl b, phydbl lexp);
phydbl RATES_Dmu1_Given_V_And_N(phydbl mu1, phydbl v, int n, phydbl dt1, phydbl a, phydbl b);
phydbl RATES_Yule(t_tree *tree);
phydbl RATES_Check_Mean_Rates(t_tree *tree);
void RATES_Check_Mean_Rates_Pre(t_node *a, t_node *d, t_edge *b, phydbl *sum, t_tree *tree);
void RATES_Discretize_Rates(t_tree *tree);
void RATES_Discretize_Rates_Pre(t_node *a, t_node *d, t_edge *b, t_tree *tree);
phydbl RATES_Dmu_Given_V_And_MinN(phydbl mu, phydbl dt, phydbl v, int minn, phydbl a, phydbl b, phydbl lexp);
phydbl RATES_Dmu_One(phydbl mu, phydbl dt, phydbl a, phydbl b, phydbl lexp);
phydbl RATES_Compound_Core(phydbl mu1, phydbl mu2, int n1, int n2, phydbl dt1, phydbl dt2, phydbl alpha, phydbl beta, phydbl lexp, phydbl eps, int approx);
void RATES_Record_Rates(t_tree *tree);
void RATES_Reset_Rates(t_tree *tree);
void RATES_Record_Times(t_tree *tree);
void RATES_Reset_Times(t_tree *tree);
void RATES_Update_T_Rates_Pre(t_node *a, t_node *d, t_tree *tree);
void RATES_Update_T_Rates(t_tree *tree);
void RATES_Get_Rates_From_Bl(t_tree *tree);
phydbl RATES_Compound_Core_Joint(phydbl mu1, phydbl mu2, int n1, int n2, phydbl dt1, phydbl dt2,
phydbl alpha, phydbl beta, phydbl lexp, phydbl eps, int approx);
phydbl RATES_Dmu_Joint(phydbl mu, int n, phydbl dt, phydbl a, phydbl b, phydbl lexp, int min_n);
phydbl RATES_Compound_Core_Marginal(phydbl mu1, phydbl mu2, phydbl dt1, phydbl dt2, phydbl alpha,
phydbl beta, phydbl lexp, phydbl eps, int approx);
phydbl RATES_Lk_Jumps(t_tree *tree);
void RATES_Posterior_Rates(t_tree *tree);
void RATES_Posterior_One_Rate(t_node *a, t_node *d, int traversal, t_tree *tree);
void RATES_Free_Rates(t_rate *rates);
void RATES_Initialize_True_Rates(t_tree *tree);
void RATES_Posterior_Times(t_tree *tree);
void RATES_Posterior_One_Time(t_node *a, t_node *d, int traversal, t_tree *tree);
void RATES_Update_Cur_Bl(t_tree *tree);
void RATES_Update_Cur_Bl_Pre(t_node *a, t_node *d, t_edge *b, t_tree *tree);
void RATES_Get_Cov_Matrix_Rooted(phydbl *unroot_cov, t_tree *tree);
void RATES_Get_Cov_Matrix_Rooted_Pre(t_node *a, t_node *d, t_edge *b, phydbl *cov, t_tree *tree);
void RATES_Bl_To_Ml(t_tree *tree);
void RATES_Bl_To_Ml_Pre(t_node *a, t_node *d, t_edge *b, t_tree *tree);
int RATES_Check_Node_Times(t_tree *tree);
void RATES_Check_Node_Times_Pre(t_node *a, t_node *d, int *err, t_tree *tree);
void RATES_Covariance_Mu(t_tree *tree);
void RATES_Variance_Mu_Pre(t_node *a, t_node *d, t_tree *tree);
void RATES_Fill_Lca_Table(t_tree *tree);
void RATES_Posterior_Clock_Rate(t_tree *tree);
void RATES_Get_Conditional_Variances(t_tree *tree);
void RATES_Get_All_Reg_Coeff(t_tree *tree);
void RATES_Posterior_Time_Root(t_tree *tree);
void RATES_Get_Trip_Conditional_Variances(t_tree *tree);
void RATES_Get_All_Trip_Reg_Coeff(t_tree *tree);
void RATES_Check_Lk_Rates(t_tree *tree, int *err);
phydbl RATES_Expected_Tree_Length(t_tree *tree);
void RATES_Expected_Tree_Length_Pre(t_node *a, t_node *d, phydbl eranc, phydbl *mean, int *n, t_tree *tree);
void RATES_Normalise_Rates(t_tree *tree);
phydbl RATES_Check_Mean_Rates_True(t_tree *tree);
phydbl RATES_Find_Min_Dt_Bisec(phydbl r0, phydbl r1, phydbl t0, phydbl t1, phydbl nu, phydbl threshp, int inf);
phydbl RATES_Find_Max_Dt_Bisec(phydbl r0, phydbl r1, phydbl t0, phydbl t1, phydbl nu, phydbl threshp, int inf);
void RATES_Min_Max_Interval(phydbl u0, phydbl u1, phydbl u2, phydbl u3, phydbl t0, phydbl t2, phydbl t3,
phydbl *t_min, phydbl *t_max, phydbl nu, phydbl p_thresh, t_tree *tree);
phydbl RATES_Get_Correction_Factor(phydbl mode, phydbl sd, int *err, t_tree *tree);
phydbl RATES_Average_Substitution_Rate(t_tree *tree);
void RATES_Update_Norm_Fact(t_tree *tree);
void RATES_Update_Mean_Br_Len(int iter, t_tree *tree);
void RATES_Update_Cov_Br_Len(int iter, t_tree *tree);
void RATES_Set_Mean_L(t_tree *tree);
void RATES_Fill_All_Param(t_rate *rate, t_tree *tree);
void RATES_Record_Rates(t_tree *tree);
void RATES_Reset_Rates(t_tree *tree);
phydbl RATES_Average_Rate(t_tree *tree);
void RATES_Set_Clock_And_Nu_Max(t_tree *tree);
void RATES_Write_Mean_R_On_Edge_Label(t_node *a, t_node *d, t_edge *b, t_tree *tree);
phydbl RATES_Lk_Linreg(t_tree *tree);
phydbl RATES_Get_Mean_Rate_In_Subtree(t_node *root, t_tree *tree);
void RATES_Get_Mean_Rate_In_Subtree_Pre(t_node *a, t_node *d, phydbl *sum, int *n, t_tree *tree);
char *RATES_Get_Model_Name(int model);
void RATES_Get_Survival_Ranks(t_tree *tree);
void RATES_Bl_To_Bl(t_tree *tree);
void RATES_Bl_To_Bl_Pre(t_node *a, t_node *d, t_edge *b, t_tree *tree);
void RATES_Set_Birth_Rate_Boundaries(t_tree *tree);
#endif
phyml-20120412/src/eigen.h 0000644 0001750 0001750 00000002711 11637265513 012062 0000000 0000000 #include
#ifndef EIGEN_H
#define EIGEN_H
#include "utilities.h"
#include "free.h"
#ifdef RWRAPPER
#include
#endif
int ludcmp_1D(phydbl *a, int n, phydbl *d);
void det_1D(phydbl *a, int n, phydbl *d);
int Eigen(int job, phydbl *A, int n, phydbl *rr, phydbl *ri,
phydbl *vr, phydbl *vi, phydbl *w);
void balance(phydbl *mat, int n, int *low, int *hi, phydbl *scale);
void unbalance(int n, phydbl *vr, phydbl *vi, int low, int hi,
phydbl *scale);
int realeig(int job, phydbl *mat, int n,int low, int hi, phydbl *valr,
phydbl *vali, phydbl *vr, phydbl *vi);
void elemhess(int job, phydbl *mat, int n, int low, int hi,
phydbl *vr, phydbl *vi, int *work);
int ludcmp(phydbl **a, int n, phydbl *d);
void det(phydbl **a, int n, phydbl *d);
/* complex functions */
typedef struct { phydbl re, im; } complex;
#define csize(a) (FABS(a.re)+FABS(a.im))
complex compl (phydbl re,phydbl im);
complex _conj (complex a);
complex cplus (complex a, complex b);
complex cminus (complex a, complex b);
complex cby (complex a, complex b);
complex cdiv (complex a,complex b);
/* complex local_cexp (complex a); */
complex cfactor (complex x, phydbl a);
int cxtoy (complex *x, complex *y, int n);
int cmatby (complex *a, complex *b, complex *c, int n,int m,int k);
int cmatout (FILE * fout, complex *x, int n, int m);
int cmatinv( complex *x, int n, int m, phydbl *space);
phydbl *Cholesky_Decomp(phydbl *A, int dim);
#endif
phyml-20120412/src/models.h 0000644 0001750 0001750 00000004175 11637265607 012270 0000000 0000000 /*
PHYML : a program that computes maximum likelihood phylogenies from
DNA or AA homologous sequences
Copyright (C) Stephane Guindon. Oct 2003 onward
All parts of the source except where indicated are distributed under
the GNU public licence. See http://www.opensource.org for details.
*/
#include
#ifndef MODELS_H
#define MODELS_H
#include "utilities.h"
#include "eigen.h"
#include "free.h"
#include "stats.h"
void PMat(phydbl l, model *mod, int pos, phydbl *Pij);
void PMat_K80(phydbl l,phydbl kappa, int pos, phydbl *Pij);
void PMat_TN93(phydbl l, model *mod, int pos, phydbl *Pij);
void PMat_Empirical(phydbl l, model *mod, int pos, phydbl *Pij);
void PMat_Zero_Br_Len(model *mod, int pos, phydbl *Pij);
void PMat_Gamma(phydbl l, model *mod, int pos, phydbl *Pij);
int GetDaa (phydbl *daa, phydbl *pi, char *file_name);
void Init_Model(calign *data, model *mod, option *io);
void Update_Qmat_GTR(phydbl *rr, phydbl *rr_val, int *rr_num, phydbl *pi, phydbl *qmat);
void Update_Qmat_HKY(phydbl kappa, phydbl *pi, phydbl *qmat);
void Update_Qmat_Generic(phydbl *rr, phydbl *pi, int ns, phydbl *qmat);
void Translate_Custom_Mod_String(model *mod);
void Set_Model_Parameters(model *mod);
phydbl GTR_Dist(phydbl *F, phydbl alpha, eigen *eigen_struct);
phydbl General_Dist(phydbl *F, model *mod, eigen *eigen_struct);
int Init_Qmat_WAG(phydbl *daa, phydbl *pi);
int Init_Qmat_Dayhoff(phydbl *daa, phydbl *pi);
int Init_Qmat_JTT(phydbl *daa, phydbl *pi);
int Init_Qmat_RtREV(phydbl *daa, phydbl *pi);
int Init_Qmat_CpREV(phydbl *daa, phydbl *pi);
int Init_Qmat_VT(phydbl *daa, phydbl *pi);
int Init_Qmat_Blosum62(phydbl *daa, phydbl *pi);
int Init_Qmat_MtMam(phydbl *daa, phydbl *pi);
int Init_Qmat_MtArt(phydbl *daa, phydbl *pi); // Added by Federico Abascal
int Init_Qmat_HIVb(phydbl *daa, phydbl *pi); // Added by Federico Abascal
int Init_Qmat_HIVw(phydbl *daa, phydbl *pi); // Added by Federico Abascal
void Switch_From_Mod_To_M4mod(model *mod);
void Switch_From_M4mod_To_Mod(model *mod);
void PMat_JC69(phydbl l, int pos, phydbl *Pij, model *mod);
phydbl Get_Lambda_F84(phydbl *pi, phydbl *kappa);
void Update_Eigen(model *mod);
#endif
phyml-20120412/src/m4.h 0000644 0001750 0001750 00000003400 11637265564 011315 0000000 0000000 /*
PhyML: a program that computes maximum likelihood phylogenies from
DNA or AA homologous sequences.
Copyright (C) Stephane Guindon. Oct 2003 onward.
All parts of the source except where indicated are distributed under
the GNU public licence. See http://www.opensource.org for details.
*/
#include
#ifndef M4_H
#define M4_H
#include "spr.h"
#include "utilities.h"
#include "lk.h"
#include "optimiz.h"
#include "bionj.h"
#include "models.h"
#include "free.h"
#include "help.h"
#include "simu.h"
#include "eigen.h"
#include "pars.h"
#include "alrt.h"
#include "time.h"
#include "draw.h"
#ifdef PART
#include "mg.h"
#endif
int M4_main(int argc, char **argv);
void M4_Make_Complete(int n_h, int n_o, m4 *m4mod);
m4 *M4_Make_Light();
void M4_Free_M4_Model(m4 *m4mod);
void M4_Init_Qmat(m4 *m4mod, calign *data, model *mod);
void M4_Update_Qmat(m4 *m4mod, model *mod);
void M4_Init_Model(m4 *m4mod, calign *data, model *mod);
void M4_Init_P_Lk_Tips_Double(t_tree *tree);
void M4_Init_P_Lk_Tips_Int(t_tree *tree);
void M4_Post_Prob_H_Class_Edge_Site(t_edge *b, phydbl ****integral, phydbl *postprob, t_tree *tree);
phydbl ****M4_Integral_Term_On_One_Edge(t_edge *b, t_tree *tree);
phydbl ***M4_Compute_Proba_Hidden_States_On_Edges(t_tree *tree);
void M4_Free_Integral_Term_On_One_Edge(phydbl ****integral, t_tree *tree);
void M4_Compute_Posterior_Mean_Rates(phydbl ***post_probs, t_tree *tree);
void M4_Scale_Br_Len(t_tree *tree);
void M4_Detect_Site_Switches_Experiment(t_tree *tree);
m4 *M4_Copy_M4_Model(model *ori_mod, m4 *ori_m4mod);
void M4_Posterior_Prediction_Experiment(t_tree *tree);
void M4_Set_M4mod_Default(m4 *m4mod);
phydbl **M4_Site_Branch_Classification(phydbl ***post_probs, t_tree *tree);
void M4_Site_Branch_Classification_Experiment(t_tree *tree);
#endif
phyml-20120412/src/draw.c 0000644 0001750 0001750 00000041017 11644731704 011723 0000000 0000000 /*
PHYML : a program that computes maximum likelihood phyLOGenies from
DNA or AA homoLOGous sequences
Copyright (C) Stephane Guindon. Oct 2003 onward
All parts of the source except where indicated are distributed under
the GNU public licence. See http://www.opensource.org for details.
*/
#include "draw.h"
void DR_Draw_Tree(char *file_name, t_tree *tree)
{
FILE *ps_tree;
ps_tree = (FILE *)fopen(file_name,"w");
DR_Print_Postscript_Header(1,ps_tree);
tree->ps_tree = DR_Make_Tdraw_Struct(tree);
DR_Init_Tdraw_Struct(tree->ps_tree);
DR_Get_Tree_Box_Width(tree->ps_tree,tree);
Dist_To_Root(tree->n_root,tree);
tree->ps_tree->max_dist_to_root = DR_Get_Max_Dist_To_Root(tree);
DR_Get_X_Coord(NO,tree->ps_tree,tree);
DR_Get_Y_Coord(NO,tree->ps_tree,tree);
DR_Print_Tree_Postscript(1,NO,ps_tree,tree);
DR_Print_Postscript_EOF(ps_tree);
fclose(ps_tree);
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void DR_Get_Tree_Coord(t_tree *tree)
{
DR_Init_Tdraw_Struct(tree->ps_tree);
DR_Get_Tree_Box_Width(tree->ps_tree,tree);
if(!tree->n_root)
{
PhyML_Printf("\n. Adding root before rendering the tree.");
Add_Root(tree->t_edges[0],tree);
}
Dist_To_Root(tree->n_root,tree);
tree->ps_tree->max_dist_to_root = DR_Get_Max_Dist_To_Root(tree);
DR_Get_X_Coord(NO,tree->ps_tree,tree);
DR_Get_Y_Coord(NO,tree->ps_tree,tree);
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void DR_Print_Postscript_Header(int n_pages, FILE *fp)
{
if(!fp)
{
PhyML_Printf("\n. Failed to open the postscript file.");
PhyML_Printf("\n. Did you forget the '--ps' option ?.");
Warn_And_Exit("\n");
}
PhyML_Fprintf(fp,"%%!PS-Adobe-3.0\n");
PhyML_Fprintf(fp,"%%%%BoundingBox: 40 40 560 820\n");
PhyML_Fprintf(fp,"%%%%DocumentFonts: Times-Roman Times-Roman\n");
PhyML_Fprintf(fp,"%%%%Creator: Stephane Guindon\n");
PhyML_Fprintf(fp,"%%%%Title: tree\n");
PhyML_Fprintf(fp,"%%%%BeginFeature: *PageSize\n");
PhyML_Fprintf(fp,"a4\n");
PhyML_Fprintf(fp,"%%%%EndFeature\n");
PhyML_Fprintf(fp,"%%%%EndComments\n");
PhyML_Fprintf(fp,"%%%%Pages: %d\n",n_pages);
PhyML_Fprintf(fp,"/lt {lineto} bind def\n");
PhyML_Fprintf(fp,"/mt {moveto} bind def\n");
PhyML_Fprintf(fp,"/sc {setrgbcolor} bind def\n");
PhyML_Fprintf(fp,"/ct {curveto} bind def\n");
PhyML_Fprintf(fp,"/np {newpath} bind def\n");
PhyML_Fprintf(fp,"/cp {closepath} bind def\n");
PhyML_Fprintf(fp,"/gs {gsave} bind def\n");
PhyML_Fprintf(fp,"/gr {grestore} bind def\n");
PhyML_Fprintf(fp,"/Times-Roman findfont\n");
PhyML_Fprintf(fp,"14 scalefont\n");
PhyML_Fprintf(fp,"setfont\n");
PhyML_Fprintf(fp,"/clipbox\n");
PhyML_Fprintf(fp,"{\n");
PhyML_Fprintf(fp,"newpath\n");
PhyML_Fprintf(fp,"40 40 mt\n");
PhyML_Fprintf(fp,"560 40 lt\n");
PhyML_Fprintf(fp,"560 820 lt\n");
PhyML_Fprintf(fp,"40 820 lt\n");
PhyML_Fprintf(fp,"40 40 lt\n");
PhyML_Fprintf(fp,"closepath\n");
PhyML_Fprintf(fp,"clip\n");
PhyML_Fprintf(fp,"} bind def\n");
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void DR_Print_Postscript_EOF(FILE *fp)
{
PhyML_Fprintf(fp,"%%%%Trailer\n");
PhyML_Fprintf(fp,"%%%%EOF\n");
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void DR_Print_Tree_Postscript(int page_num, int render_name, FILE *fp, t_tree *tree)
{
tdraw *draw;
t_node *n_root;
draw = tree->ps_tree;
/* DR_Get_Tree_Coord(tree); */
n_root = tree->n_root;
/* PhyML_Fprintf(fp,"%%%%Page: %d %d\n",page_num,page_num); */
PhyML_Fprintf(fp,"0.001 setlinewidth\n");
/* PhyML_Fprintf(fp,"0.5 0.5 0.4 sc\n"); */
PhyML_Fprintf(fp,"0 0 0 sc\n");
/* PhyML_Fprintf(fp,"clipbox\n"); */
/* PhyML_Fprintf(fp,"stroke\n"); */
PhyML_Fprintf(fp,"0 0 translate\n");
PhyML_Fprintf(fp,"newpath\n");
draw->ycoord[n_root->num] = (draw->ycoord[n_root->v[0]->num] + draw->ycoord[n_root->v[1]->num])/2.;
draw->xcoord[n_root->num] = 0.0;
DR_Print_Tree_Postscript_Pre(n_root,n_root->v[0],render_name,fp,draw,tree);
DR_Print_Tree_Postscript_Pre(n_root,n_root->v[1],render_name,fp,draw,tree);
PhyML_Fprintf(fp,"closepath\n");
PhyML_Fprintf(fp,"0 0 translate\n");
PhyML_Fprintf(fp,"stroke\n");
PhyML_Fprintf(fp,"showpage\n");
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void DR_Print_Tree_Postscript_Pre(t_node *a, t_node *d, int render_name, FILE *fp, tdraw *w, t_tree *tree)
{
int i;
phydbl R, G, B;
R = G = B = 0.0;
PhyML_Fprintf(fp,"gs\n");
PhyML_Fprintf(fp,"%.1f %.1f mt\n",w->xcoord[a->num],w->ycoord[a->num]);
/* PhyML_Fprintf(fp,"%.1f %.1f lt\n",w->xcoord[a->num],w->ycoord[d->num]); */
/* PhyML_Fprintf(fp,"%.1f %.1f lt\n",w->xcoord[d->num],w->ycoord[d->num]); */
phydbl min,max,step,val;
min = 0.0;
max = 4.;
step = (max-min)/13.;
/* val = tree->rates->mean_r[d->num] / (phydbl)(tree->mcmc->run/tree->mcmc->sample_interval+1.); */
val = tree->rates->mean_r[d->num];
/* val = tree->rates->has_survived[d->num]; */
/* if(val > 0.5) {R=1.; G=.0; B=0.;} */
if(val <= min+1.*step)
{R=.0; G=1.; B=1.;}
else if(val > min+1.*step && val <= min+2.*step)
{R=.0; G=1.; B=.8;}
else if(val > min+2.*step && val <= min+3.*step)
{R=.0; G=1.; B=.5;}
else if(val > min+3.*step && val <= min+4.*step)
{R=.0; G=1.; B=.3;}
else if(val > min+4.*step && val <= min+5.*step)
{R=.0; G=1.; B=.0;}
else if(val > min+5.*step && val <= min+6.*step)
{R=.25; G=1.; B=0.;}
else if(val > min+6.*step && val <= min+7.*step)
{R=.5; G=1.; B=0.;}
else if(val > min+7.*step && val <= min+8.*step)
{R=.75; G=1.; B=.0;}
else if(val > min+8.*step && val <= min+9.*step)
{R=1.; G=1.; B=.0;}
else if(val > min+9.*step && val <= min+10.*step)
{R=1.; G=.75; B=.0;}
else if(val > min+10.*step && val <= min+11.*step)
{R=1.; G=.5; B=.0;}
else if(val > min+11.*step && val <= min+12.*step)
{R=1.; G=.25; B=.0;}
else if(val > min+12.*step)
{R=1.; G=.0; B=0.;}
PhyML_Fprintf(fp,"%.1f %.1f lt\n",w->xcoord[a->num],w->ycoord[d->num]);
PhyML_Fprintf(fp,"%.1f %.1f lt\n",w->xcoord[d->num],w->ycoord[d->num]);
/* PhyML_Fprintf(fp,"%.1f %.1f %.1f %.1f %.1f %.1f ct\n", */
/* w->xcoord[a->num], */
/* w->ycoord[d->num], */
/* w->xcoord[d->num], */
/* w->ycoord[d->num], */
/* w->xcoord[d->num], */
/* w->ycoord[d->num]); */
if(tree->rates->has_survived[d->num] == YES)
{
PhyML_Fprintf(fp," /Helvetica findfont 16 scalefont\n");
PhyML_Fprintf(fp,"setfont\n");
PhyML_Fprintf(fp,"%.1f %.1f mt\n",w->xcoord[d->num]-5,w->ycoord[d->num]);
PhyML_Fprintf(fp,"0 0 0 sc\n");
PhyML_Fprintf(fp,"(*) show \n");
}
PhyML_Fprintf(fp,"%f %f %f sc\n",R,G,B);
if(d->tax)
{
PhyML_Fprintf(fp,"stroke\n");
PhyML_Fprintf(fp,"0 setgray\n");
PhyML_Fprintf(fp,"0.1 setlinewidth\n");
PhyML_Fprintf(fp,"np %.1f %.1f 3 0 360 arc cp\n",w->xcoord[d->num],w->ycoord[d->num]);
PhyML_Fprintf(fp,"%.1f %.1f %.1f sc fill\n",R,G,B);
/* PhyML_Fprintf(fp,"%f setgray fill\n",greylevel); */
PhyML_Fprintf(fp,"0 0 0 sc\n");
PhyML_Fprintf(fp," /Helvetica findfont 8 scalefont\n");
PhyML_Fprintf(fp,"setfont\n");
PhyML_Fprintf(fp,"%.1f %.1f mt\n",w->xcoord[d->num]+2,w->ycoord[d->num]);
PhyML_Fprintf(fp,"(%d) show \n",d->num);
PhyML_Fprintf(fp," /Helvetica findfont 14 scalefont\n");
PhyML_Fprintf(fp,"setfont\n");
/* PhyML_Fprintf(fp,"%.1f %.1f mt\n",w->xcoord[d->num]+5,w->ycoord[d->num]); */
/* PhyML_Fprintf(fp,"(%.10s) show \n",d->name); */
/* if(render_name) */
/* { */
/* if(tree->io->long_tax_names) */
/* PhyML_Fprintf(fp,"(%s) show \n",tree->io->long_tax_names[d->num]); */
/* else */
/* PhyML_Fprintf(fp,"(%s) show \n",d->name); */
/* } */
PhyML_Fprintf(fp,"stroke\n");
PhyML_Fprintf(fp,"gr\n");
PhyML_Fprintf(fp,"0 0 0 sc\n");
return;
}
else
{
PhyML_Fprintf(fp," /Helvetica findfont 8 scalefont\n");
PhyML_Fprintf(fp,"setfont\n");
PhyML_Fprintf(fp,"%.1f %.1f mt\n",w->xcoord[d->num]+2,w->ycoord[d->num]);
PhyML_Fprintf(fp,"(%d) show \n",d->num);
PhyML_Fprintf(fp,"%.1f %.1f mt\n",w->xcoord[d->num],w->ycoord[d->num]);
PhyML_Fprintf(fp," /Helvetica findfont 14 scalefont\n");
PhyML_Fprintf(fp,"setfont\n");
PhyML_Fprintf(fp,"stroke\n");
PhyML_Fprintf(fp,"gr\n");
PhyML_Fprintf(fp,"0 0 0 sc\n");
For(i,3)
if(d->v[i] != a && d->b[i] != tree->e_root) DR_Print_Tree_Postscript_Pre(d,d->v[i],render_name,fp,w,tree);
}
return;
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void DR_Get_X_Coord_Pre(t_node *a, t_node *d, t_edge *b, tdraw *w, int fixed_tips, t_tree *tree)
{
int i;
if(!(d->tax && fixed_tips == YES)) w->xcoord[d->num] = d->dist_to_root * (phydbl)w->tree_box_width/w->max_dist_to_root;
if(d->tax) return;
else
{
For(i,3)
if((d->v[i] != a) && (d->b[i] != tree->e_root))
DR_Get_X_Coord_Pre(d,d->v[i],d->b[i],w,fixed_tips,tree);
}
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void DR_Get_X_Coord(int fixed_tips, tdraw *w, t_tree *tree)
{
if(!(tree->n_root->v[0]->tax && fixed_tips == YES)) w->xcoord[tree->n_root->v[0]->num] = tree->n_root->v[0]->dist_to_root * (phydbl)w->tree_box_width/w->max_dist_to_root;
if(!(tree->n_root->v[1]->tax && fixed_tips == YES)) w->xcoord[tree->n_root->v[1]->num] = tree->n_root->v[1]->dist_to_root * (phydbl)w->tree_box_width/w->max_dist_to_root;
DR_Get_X_Coord_Pre(tree->n_root,tree->n_root->v[0],NULL,w,fixed_tips,tree);
DR_Get_X_Coord_Pre(tree->n_root,tree->n_root->v[1],NULL,w,fixed_tips,tree);
w->xcoord[tree->n_root->num] = 0;
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void DR_Get_Y_Coord(int fixed_tips, tdraw *w, t_tree *tree)
{
phydbl next_y_slot;
next_y_slot = .0;
DR_Get_Y_Coord_Post(tree->n_root,tree->n_root->v[0],NULL,&next_y_slot,fixed_tips,w,tree);
DR_Get_Y_Coord_Post(tree->n_root,tree->n_root->v[1],NULL,&next_y_slot,fixed_tips,w,tree);
w->ycoord[tree->n_root->num] = (int)((w->ycoord[tree->n_root->v[0]->num] + w->ycoord[tree->n_root->v[0]->num]) / 2.);
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void DR_Get_Y_Coord_Post(t_node *a, t_node *d, t_edge *b, phydbl *next_y_slot, int fixed_tips, tdraw *w, t_tree *tree)
{
int i;
if(d->tax)
{
if(!fixed_tips)
{
/* w->ycoord[d->num] = *next_y_slot + (int)(w->page_height / (2.*tree->n_otu)); */
w->ycoord[d->num] = *next_y_slot;
(*next_y_slot) += ((phydbl)w->page_height / (phydbl)tree->n_otu);
}
}
else
{
int d1, d2;
d1 = d2 = -1;
For(i,3)
{
if(d->v[i] != a && d->b[i] != tree->e_root)
{
DR_Get_Y_Coord_Post(d,d->v[i],d->b[i],next_y_slot,fixed_tips,w,tree);
if(d1<0) d1 = i;
else d2 = i;
}
}
w->ycoord[d->num] = (w->ycoord[d->v[d1]->num] + w->ycoord[d->v[d2]->num])/2.;
}
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
tdraw *DR_Make_Tdraw_Struct(t_tree *tree)
{
tdraw *w;
w = (tdraw *)mCalloc(1,sizeof(tdraw));
w->xcoord = (phydbl *)mCalloc(2*tree->n_otu-1,sizeof(phydbl));
w->ycoord = (phydbl *)mCalloc(2*tree->n_otu-1,sizeof(phydbl));
w->xcoord_s = (phydbl *)mCalloc(2*tree->n_otu-1,sizeof(phydbl));
w->ycoord_s = (phydbl *)mCalloc(2*tree->n_otu-1,sizeof(phydbl));
w->cdf_mat = (int *)mCalloc((2*tree->n_otu-2)*(2*tree->n_otu-2),sizeof(int));
w->cdf_mat_x = (phydbl *)mCalloc(2*tree->n_otu-1,sizeof(phydbl));
w->cdf_mat_y = (phydbl *)mCalloc(2*tree->n_otu-1,sizeof(phydbl));
return w;
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void DR_Init_Tdraw_Struct(tdraw *w)
{
w->page_width = 510;
w->page_height = 760;
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void DR_Get_Tree_Box_Width(tdraw *w, t_tree *tree)
{
int i;
int max_name_len, curr_len;
max_name_len = curr_len = 0;
For(i,tree->n_otu)
{
curr_len = (int)strlen(tree->t_nodes[i]->name);
if(curr_len > max_name_len) max_name_len = curr_len;
}
w->tree_box_width = w->page_width - max_name_len * 8.66667;
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
phydbl DR_Get_Max_Dist_To_Root(t_tree *tree)
{
phydbl mx;
int i;
mx = .0;
For(i,tree->n_otu)
{
if(tree->t_nodes[i]->dist_to_root > mx)
{
mx = tree->t_nodes[i]->dist_to_root;
}
}
return mx;
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void DR_Get_Tree_Coord_Scaled(tdraw *w, t_tree *tree)
{
int i;
int max_x,min_x;
int max_y,min_y;
max_x = -INT_MAX;
min_x = INT_MAX;
For(i,2*tree->n_otu-1)
{
if(w->xcoord[i] > max_x) max_x = w->xcoord[i];
if(w->xcoord[i] < min_x) min_x = w->xcoord[i];
}
max_y = -INT_MAX;
min_y = INT_MAX;
For(i,2*tree->n_otu-1)
{
if(w->ycoord[i] > max_y) max_y = w->ycoord[i];
if(w->ycoord[i] < min_y) min_y = w->ycoord[i];
}
For(i,2*tree->n_otu-1)
{
w->xcoord_s[i] = (phydbl)(w->xcoord[i] - min_x) / (max_x - min_x);
w->ycoord_s[i] = (phydbl)(w->ycoord[i] - min_y) / (max_y - min_y);
}
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void DR_Get_Cdf_Mat(t_tree *tree)
{
int i,j,k;
phydbl min_x,max_x,y;
phydbl x_mat,y_mat;
t_node *d, *a;
phydbl eps;
eps = 1.E-6;
For(i,2*tree->n_otu-1) tree->ps_tree->cdf_mat_x[i] = tree->ps_tree->xcoord_s[i];
For(i,2*tree->n_otu-1) tree->ps_tree->cdf_mat_y[i] = tree->ps_tree->ycoord_s[i];
Qksort(tree->ps_tree->cdf_mat_x,NULL,0,2*tree->n_otu-2);
Qksort(tree->ps_tree->cdf_mat_y,NULL,0,2*tree->n_otu-2);
For(i,2*tree->n_otu-2) /* x coordinates */
{
For(j,2*tree->n_otu-2) /* y coordinates */
{
For(k,2*tree->n_otu-2) /* all nodes in the tree */
{
d = tree->t_nodes[k];
a = tree->t_nodes[k]->anc;
min_x = tree->ps_tree->xcoord_s[a->num];
max_x = tree->ps_tree->xcoord_s[d->num];
y = tree->ps_tree->ycoord_s[d->num];
x_mat = tree->ps_tree->cdf_mat_x[i];
y_mat = tree->ps_tree->cdf_mat_y[j];
/* printf("\n. x_mat=%.1f ymat=%.1f min=%.1f max=%.1f y=%.1f", */
/* x_mat,y_mat,min_x,max_x,y); */
if((min_x < x_mat + eps) && (max_x > x_mat) && (y > y_mat))
{
tree->ps_tree->cdf_mat[j*(2*tree->n_otu-2)+i] += 1;
/* PhyML_Printf("\n. Add 1 to [%.1f,%.1f]", */
/* tree->ps_tree->cdf_mat_x[i], */
/* tree->ps_tree->cdf_mat_y[j]); */
}
}
}
}
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
phyml-20120412/src/interface.c 0000644 0001750 0001750 00000137417 11654733405 012741 0000000 0000000 /*
PhyML: a program that computes maximum likelihood phyLOGenies from
DNA or AA homoLOGous sequences.
Copyright (C) Stephane Guindon. Oct 2003 onward.
All parts of the source except where indicated are distributed under
the GNU public licence. See http://www.opensource.org for details.
*/
#include "interface.h"
#include "mg.h"
void Launch_Interface(option *io)
{
Launch_Interface_Input(io);
io->ready_to_go = 0;
do
{
switch(io->curr_interface)
{
case INTERFACE_DATA_TYPE :
{
Launch_Interface_Data_Type(io);
break;
}
case INTERFACE_MULTIGENE :
{
Launch_Interface_Multigene(io);
break;
}
case INTERFACE_MODEL :
{
Launch_Interface_Model(io);
break;
}
case INTERFACE_TOPO_SEARCH :
{
Launch_Interface_Topo_Search(io);
break;
}
case INTERFACE_BRANCH_SUPPORT :
{
Launch_Interface_Branch_Support(io);
break;
}
default :
{
PhyML_Printf("\n. Err in file %s at line %d\n\n",__FILE__,__LINE__);
Exit("");
break;
}
}
}while(!io->ready_to_go);
if(io->in_tree == 2)
{
PhyML_Printf("\n. Enter the name of the input tree file > ");
Getstring_Stdin(io->in_tree_file);
io->fp_in_tree = Openfile(io->in_tree_file,0);
}
if((io->mod->whichmodel == CUSTOMAA) && (io->datatype == AA))
{
char *filename;
filename = (char *)mCalloc(T_MAX_NAME,sizeof(char));
fflush(NULL);
PhyML_Printf("\n");
PhyML_Printf("\n. Enter the rate matrix file name > "); fflush(NULL);
Getstring_Stdin(filename);
io->fp_aa_rate_mat = Openfile(filename,0);
strcpy(io->aa_rate_mat_file,filename);
PhyML_Printf("\n");
Free(filename);
fflush(NULL);
}
if((io->mod->s_opt->n_rand_starts) &&
(io->mod->s_opt->topo_search == NNI_MOVE) &&
(io->mod->s_opt->random_input_tree))
{
Warn_And_Exit("\n. The random starting tree option is only compatible with SPR based search options.\n");
}
if ((io->datatype == NT) && (io->mod->whichmodel > 10))
{
char choix;
PhyML_Printf("\n. Err: model incompatible with the data type. Please use JC69, K80, F81, HKY, F84, TN93 or GTR\n");
PhyML_Printf("\n. Type any key to exit.\n");
if(!scanf("%c",&choix)) Exit("\n");
Warn_And_Exit("\n");
}
else if ((io->datatype == AA) && (io->mod->whichmodel < 11))
{
char choix;
PhyML_Printf("\n. Err: model incompatible with the data type. Please use LG, Dayhoff, JTT, MtREV, WAG, DCMut, RtREV, CpREV, VT, Blosum62, MtMam, MtArt, HIVw or HIVb.\n");
PhyML_Printf("\n. Type any key to exit.\n");
if(!scanf("%c",&choix)) Exit("\n");
Exit("\n");
}
if(io->m4_model == YES)
{
#ifdef M4
io->mod->ns *= io->mod->m4mod->n_h;
io->mod->use_m4mod = 1;
M4_Make_Complete(io->mod->m4mod->n_h,
io->mod->m4mod->n_o,
io->mod->m4mod);
#endif
}
else
{
io->mod->s_opt->opt_cov_delta = 0;
io->mod->s_opt->opt_cov_alpha = 0;
io->mod->s_opt->opt_cov_free_rates = 0;
}
if((io->mod->s_opt->opt_cov_free_rates) && (io->mod->s_opt->opt_cov_alpha))
{
io->mod->s_opt->opt_cov_free_rates = 0;
io->mod->m4mod->use_cov_alpha = 0;
io->mod->m4mod->use_cov_free = 1;
}
if(io->print_site_lnl)
{
strcpy(io->out_lk_file,io->in_align_file);
strcat(io->out_lk_file, "_phyml_lk");
if(io->appebr_run_ID) { strcat(io->out_lk_file,"_"); strcat(io->out_lk_file,io->run_id_string); }
strcat(io->out_lk_file, ".txt");
io->fp_out_lk = Openfile(io->out_lk_file,1);
}
if(io->print_trace)
{
strcpy(io->out_trace_file,io->in_align_file);
strcat(io->out_trace_file,"_phyml_trace");
if(io->appebr_run_ID) { strcat(io->out_trace_file,"_"); strcat(io->out_trace_file,io->run_id_string); }
strcat(io->out_trace_file,".txt");
io->fp_out_trace = Openfile(io->out_trace_file,1);
}
if(io->mod->s_opt->random_input_tree)
{
strcpy(io->out_trees_file,io->in_align_file);
strcat(io->out_trees_file,"_phyml_trees");
if(io->appebr_run_ID) { strcat(io->out_trees_file,"_"); strcat(io->out_trees_file,io->run_id_string); }
strcat(io->out_trees_file,".txt");
io->fp_out_trees = Openfile(io->out_trees_file,1);
}
if((io->print_boot_trees) && (io->mod->bootstrap > 0))
{
strcpy(io->out_boot_tree_file,io->in_align_file);
strcat(io->out_boot_tree_file,"_phyml_boot_trees");
if(io->appebr_run_ID) { strcat(io->out_boot_tree_file,"_"); strcat(io->out_boot_tree_file,io->run_id_string); }
strcat(io->out_boot_tree_file,".txt");
io->fp_out_boot_tree = Openfile(io->out_boot_tree_file,1);
strcpy(io->out_boot_stats_file,io->in_align_file);
strcat(io->out_boot_stats_file,"_phyml_boot_stats");
if(io->appebr_run_ID) { strcat(io->out_boot_stats_file,"_"); strcat(io->out_boot_stats_file,io->run_id_string); }
strcat(io->out_boot_stats_file,".txt");
io->fp_out_boot_stats = Openfile(io->out_boot_stats_file,1);
}
if(io->appebr_run_ID)
{
strcat(io->out_tree_file,"_");
strcat(io->out_stats_file,"_");
strcat(io->out_tree_file,io->run_id_string);
strcat(io->out_stats_file,io->run_id_string);
strcat(io->out_tree_file,".txt");
strcat(io->out_stats_file,".txt");
}
if(io->mod->n_catg == 1) io->mod->s_opt->opt_alpha = 0;
if(io->mod->whichmodel != K80 &&
io->mod->whichmodel != HKY85 &&
io->mod->whichmodel != F84 &&
io->mod->whichmodel != TN93)
{
io->mod->s_opt->opt_kappa = 0;
}
io->fp_out_tree = Openfile(io->out_tree_file,1);
io->fp_out_stats = Openfile(io->out_stats_file,1);
if(io->mod->whichmodel == GTR)
{
Make_Custom_Model(io->mod);
io->mod->s_opt->opt_rr = 1;
}
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void Clear()
{
#ifdef WIN32
system("cls");
#elif UNIX
PhyML_Printf("\033[2J\033[H");
#endif
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void Launch_Interface_Input(option *io)
{
char choix;
int n_trial;
Clear();
Print_Banner(stdout);
#ifdef EVOLVE
char *n_data_sets;
PhyML_Printf("\n\n");
PhyML_Printf("\n. Enter the tree file name > "); fflush(NULL);
Getstring_Stdin(io->in_tree_file);
io->fp_in_tree = Openfile(io->in_tree_file,0);
PhyML_Printf("\n");
PhyML_Printf("\n. Enter the reference sequence file name > "); fflush(NULL);
Getstring_Stdin(io->in_align_file);
io->fp_in_align = Openfile(io->in_align_file,0);
PhyML_Printf("\n");
PhyML_Printf("\n. Number of data sets > ");
n_data_sets = (char *)mCalloc(10000,sizeof(char));
Getstring_Stdin(n_data_sets);
n_trial = 0;
while((!atoi(n_data_sets)) || (atoi(n_data_sets) < 0))
{
if(++n_trial > 10) Exit("\n. Err : the number of sets must be a positive integer");
PhyML_Printf("\n. The number of sets must be a positive integer");
PhyML_Printf("\n. Enter a new value > ");
Getstring_Stdin(n_data_sets);
}
io->n_data_set_asked = atoi(n_data_sets);
Free(n_data_sets);
#elif OPTIMIZ
PhyML_Printf("\n. Enter the tree file name > "); fflush(NULL);
Getstring_Stdin(io->in_tree_file);
io->fp_in_tree = Openfile(io->in_tree_file,0);
PhyML_Printf("\n");
PhyML_Printf("\n. Enter the reference sequence file name > "); fflush(NULL);
Getstring_Stdin(io->in_align_file);
io->fp_in_align = Openfile(io->in_align_file,0);
PhyML_Printf("\n");
#elif defined(PHYML) || defined(PART) || defined(PHYML_INSERT)
PhyML_Printf("\n. Enter the sequence file name > "); fflush(NULL);
Getstring_Stdin(io->in_align_file);
io->fp_in_align = Openfile(io->in_align_file,0);
#endif
#if defined(PHYML) || defined(PART) || defined(PHYML_INSERT)
strcpy(io->out_stats_file,io->in_align_file);
strcat(io->out_stats_file,"_phyml_stats.txt");
strcpy(io->out_tree_file,io->in_align_file);
strcat(io->out_tree_file,"_phyml_tree.txt");
strcpy(io->out_lk_file,io->in_align_file);
strcat(io->out_lk_file,"_phyml_lk.txt");
#endif
#ifdef WIN32
#ifdef EVOLVE
if(Filexists("evolve_out.txt"));
#elif OPTIMIZ
if(Filexists("optimiz_out.txt"))
#elif defined(PHYML) || defined(PART) || defined(PHYML_INSERT)
if(Filexists(io->out_stats_file))
#endif
#elif UNIX
#ifdef EVOLVE
if(Filexists("evolve_out"));
#elif OPTIMIZ
if(Filexists("optimiz_out"))
#elif defined(PHYML) || defined(PART) || defined(PHYML_INSERT)
if(Filexists(io->out_stats_file))
#endif
#endif
{
PhyML_Printf("\n");
#ifdef EVOLVE
PhyML_Printf("\n. A file 'evolve_out' already exists");
#elif OPTIMIZ
PhyML_Printf("\n. A file 'optimiz_out' already exists");
#elif defined(PHYML) || defined(PART) || defined(PHYML_INSERT)
PhyML_Printf("\n. A file '%s' already exists",io->out_stats_file);
#endif
PhyML_Printf("\n. Do you want to Replace it or Append to it ? ");
n_trial = 0;
do
{
PhyML_Printf("\n. Please type R or A > ");
if(!scanf("%c",&choix)) Exit("\n");
if(choix == '\n') choix = 'r';
else getchar();
if(++n_trial>10) Exit("\n");
Uppercase(&choix);
}
while((choix != 'R') && (choix != 'A'));
if(choix == 'R') io->out_stats_file_open_mode = 1;
else io->out_stats_file_open_mode = 2;
}
printf("\n. MODE = %d",io->out_stats_file_open_mode);
io->fp_out_stats = Openfile(io->out_stats_file,io->out_stats_file_open_mode);
#ifdef WIN32
#ifdef EVOLVE
if(Filexists("evolve_seq.txt"))
#elif OPTIMIZ
if(Filexists("optimiz_tree.txt"))
#elif defined(PHYML) || defined(PART) || defined(PHYML_INSERT)
if(Filexists(io->out_tree_file))
#endif
#elif UNIX
#ifdef EVOLVE
if(Filexists("evolve_seq"))
#elif OPTIMIZ
if(Filexists("optimiz_tree"))
#elif defined(PHYML) || defined(PART) || defined(PHYML_INSERT)
if(Filexists(io->out_tree_file))
#endif
#endif
{
PhyML_Printf("\n");
#ifdef EVOLVE
PhyML_Printf("\n. A file 'evolve_seq' already exists");
#elif OPTIMIZ
PhyML_Printf("\n. A file 'optimiz_tree' already exists");
#elif defined(PHYML) || defined(PART) || defined(PHYML_INSERT)
PhyML_Printf("\n. A file '%s' already exists",io->out_tree_file);
#endif
PhyML_Printf("\n. Do you want to Replace it or Append to it ? ");
n_trial = 0;
do
{
PhyML_Printf("\n. Please type R or A > ");
if(!scanf("%c",&choix)) Exit("\n");
if(choix == '\n') choix = 'r';
else getchar();
Uppercase(&choix);
if(++n_trial>10) Exit("\n");
}
while((choix != 'R') && (choix != 'A'));
if(choix == 'R') io->out_tree_file_open_mode = 1;
else io->out_tree_file_open_mode = 2;
}
io->fp_out_tree = Openfile(io->out_tree_file,io->out_tree_file_open_mode);
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void Launch_Interface_Data_Type(option *io)
{
char choix;
char *s;
char *buff;
Clear();
Print_Banner(stdout);
if(io->config_multigene) Print_Data_Set_Number(io,stdout);
s = (char *)mCalloc(100,sizeof(char));
buff = (char *)mCalloc(100,sizeof(char));
PhyML_Printf("\n\n");
PhyML_Printf(" ................... \n");
PhyML_Printf(" Menu : Input Data \n");
PhyML_Printf(" ......................... \n");
PhyML_Printf("\n\n");
PhyML_Printf(" [+] "
".................................... Next sub-menu\n");
PhyML_Printf(" [-] "
"................................ Previous sub-menu\n");
PhyML_Printf(" [Y] "
".............................. Launch the analysis\n");
PhyML_Printf("\n");
if(io->datatype == NT) strcpy(s,"DNA");
else if(io->datatype == AA) strcpy(s,"AA");
else strcpy(s,"Generic");
PhyML_Printf(" [D] "
"....................... Data type (DNA/AA/Generic) "
" %-15s \n",s);
PhyML_Printf(" [I] "
"...... Input sequences interleaved (or sequential) "
" %-15s \n",
(io->interleaved)?("interleaved"):("sequential"));
strcpy(s,"");
sprintf(s," (%d sets)",io->n_data_sets);
strcpy(buff,(io->n_data_sets > 1)?("yes"):("no"));
buff=strcat(buff,(io->n_data_sets > 1)?(s):("\0"));
PhyML_Printf(" [M] "
"....................... Analyze multiple data sets "
" %-15s \n",buff);
if(!io->appebr_run_ID) strcpy(s,"none");
else strcpy(s,io->run_id_string);
PhyML_Printf(" [R] "
"........................................... Run ID "
" %-15s \n",s);
PhyML_Printf("\n\n. Are these settings correct ? "
"(type '+', '-', 'Y' or other letter for one to change) ");
if(!scanf("%c",&choix)) Exit("\n");
if(choix != '\n') getchar(); /* \n */
fflush(NULL);
Uppercase(&choix);
switch(choix)
{
/* case '\n': */
/* { */
/* io->curr_interface++; */
/* break; */
/* } */
case 'R' :
{
io->appebr_run_ID = (io->appebr_run_ID)?(0):(1);
PhyML_Printf("\n. Enter a run ID (any string of characters) > ");
Getstring_Stdin(io->run_id_string);
break;
}
case 'M' :
{
char *c;
int n_trial;
PhyML_Printf("\n. How many data sets > ");
c = (char *)mCalloc(100,sizeof(char));
Getstring_Stdin(c);
n_trial = 0;
while((!atoi(c)) || (atoi(c) < 0))
{
if(++n_trial > 10) Exit("\n. Err : The number of data sets must be a positive integer");
PhyML_Printf("\n. The number of data sets must be a positive integer");
PhyML_Printf("\n. Enter a new value > ");
Getstring_Stdin(c);
}
io->n_data_sets = atoi(c);
#ifdef PART
if(io->n_data_sets > 1)
{
io->multigene = 1;
}
#endif
if((io->mod->bootstrap > 1) && (io->n_data_sets > 1))
{
PhyML_Printf("\n. Bootstrap option is not allowed with multiple data sets !\n");
PhyML_Printf("\n. Type any key to exit.");
if(!scanf("%c",&choix)) Exit("\n");
Exit("\n");
}
Free(c);
break;
}
case 'I' :
{
if(io->interleaved)
io->interleaved = 0;
else io->interleaved = 1;
break;
}
case 'D' :
{
if(io->datatype == NT)
{
io->datatype = AA;
io->mod->state_len = 1;
io->mod->ns = 20;
io->mod->s_opt->opt_kappa = 0;
io->mod->whichmodel = LG;
strcpy(io->mod->modelname,"LG");
}
else if(io->datatype == AA)
{
io->datatype = GENERIC;
io->mod->whichmodel = JC69;
strcpy(io->mod->modelname,"JC69");
strcpy(io->nt_or_cd,"natural numbers");
}
else if(io->datatype == GENERIC)
{
io->datatype = NT;
io->mod->state_len = 1;
io->mod->ns = 4;
io->mod->whichmodel = HKY85;
strcpy(io->mod->modelname,"HKY85");
strcpy(io->nt_or_cd,"nucleotides");
}
break;
}
case '-' :
{
io->curr_interface = (io->config_multigene)?(INTERFACE_MODEL):(INTERFACE_BRANCH_SUPPORT);
break;
}
case '+' :
{
io->curr_interface = (io->multigene)?(INTERFACE_MULTIGENE):(INTERFACE_MODEL);
break;
}
case 'Y' :
{
io->ready_to_go = 1;
break;
}
default :
{
break;
}
}
Free(s);
Free(buff);
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void Launch_Interface_Model(option *io)
{
char choix;
char *s;
s = (char *)mCalloc(100,sizeof(char));
Clear();
Print_Banner(stdout);
if(io->config_multigene) Print_Data_Set_Number(io,stdout);
PhyML_Printf("\n\n");
PhyML_Printf(" ........................... \n");
PhyML_Printf(" Menu : Substitution Model \n");
PhyML_Printf(" ................................. \n");
PhyML_Printf("\n\n");
PhyML_Printf(" [+] "
".................................... Next sub-menu\n");
PhyML_Printf(" [-] "
"................................ Previous sub-menu\n");
PhyML_Printf(" [Y] "
".............................. Launch the analysis\n");
PhyML_Printf("\n");
if (io->datatype == NT)
{
if(!strcmp(io->nt_or_cd,"nucleotides"))
{
PhyML_Printf(" [M] "
"................. Model of nucleotide substitution "
" %-15s \n", io->mod->modelname);
if((io->mod->whichmodel == F81) ||
(io->mod->whichmodel == HKY85) ||
(io->mod->whichmodel == F84) ||
(io->mod->whichmodel == TN93) ||
(io->mod->whichmodel == GTR) ||
(io->mod->whichmodel == CUSTOM))
{
/* PhyML_Printf(" [F] " */
/* ".......... Base frequency estimates (empirical/ML) " */
/* " %-15s \n", */
/* (io->mod->s_opt->opt_state_freq)?("ML"):("empirical")); */
/* } */
/* else if(io->mod->whichmodel == CUSTOM) */
/* { */
PhyML_Printf(" [F] "
"................. Optimise equilibrium frequencies "
" %-15s \n",
(io->mod->s_opt->opt_state_freq)?("yes"):("no"));
}
if(io->mod->whichmodel == CUSTOM)
{
if(!io->mod->s_opt->opt_state_freq)
{
PhyML_Printf(" [E] "
"......... Equilibrium frequencies (empirical/user) "
" %-15s \n",
(io->mod->s_opt->user_state_freq)?("user defined"):("empirical"));
}
PhyML_Printf(" [K] "
"............................. Current custom model "
" %-15s \n", io->mod->custom_mod_string);
PhyML_Printf(" [O] "
"................ Optimise relative rate parameters "
" %-15s \n",(io->mod->s_opt->opt_rr)?("yes"):("no"));
}
}
}
else if(io->datatype == AA)
{
PhyML_Printf(" [M] "
"................ Model of amino-acids substitution "
" %-15s \n", io->mod->modelname);
PhyML_Printf(" [F] "
". Amino acid frequencies (empirical/model defined) "
" %-15s \n",
(io->mod->s_opt->opt_state_freq)?("empirical"):("model"));
}
else if(io->datatype == GENERIC)
{
PhyML_Printf(" [M] "
"................. Model of nucleotide substitution "
" %-15s \n", io->mod->modelname);
}
if ((io->datatype == NT) &&
((io->mod->whichmodel == K80) ||
(io->mod->whichmodel == HKY85)||
(io->mod->whichmodel == F84) ||
(io->mod->whichmodel == TN93)))
{
strcpy(s,(io->mod->s_opt->opt_kappa)?("estimated"):("fixed"));
(io->mod->s_opt->opt_kappa)?((char *)strcat(s,"")):((char *)strcat(s," (ts/tv = "));
/* (io->mod->s_opt->opt_kappa)?((char *)strcat(s,"")):((char *)sprintf(s+(int)strlen((char *)s),"%3.2f)",io->mod->kappa->v)); */
if(io->mod->s_opt->opt_kappa)
{
strcat((char *)s,"");
}
else
{
sprintf((char *)(s+(int)strlen(s)),"%3.2f)",io->mod->kappa->v);
}
PhyML_Printf(" [T] "
".................... Ts/tv ratio (fixed/estimated) "
" %-15s \n",s);
}
(io->mod->s_opt->opt_pinvar)?(strcpy(s,"estimated")):(strcpy(s,"fixed"));
(io->mod->s_opt->opt_pinvar)?((char *)strcat(s,"")):((char *)strcat(s," (p-invar = "));
if(io->mod->s_opt->opt_pinvar)
{
strcat(s,"");
}
else
{
sprintf((char *)(s+strlen((char *)s)),"%3.2f)",io->mod->pinvar->v);
}
PhyML_Printf(" [V] "
". Proportion of invariable sites (fixed/estimated)"
" %-15s \n",s);
PhyML_Printf(" [R] "
"....... One category of substitution rate (yes/no) "
" %-15s \n",
(io->mod->n_catg > 1)?("no"):("yes"));
if(io->mod->n_catg > 1)
{
PhyML_Printf(" [C] "
"........... Number of substitution rate categories "
" %-15d \n",
io->mod->n_catg);
}
if(io->mod->n_catg > 1)
{
PhyML_Printf(" [G] "
"............. Gamma distributed rates across sites "
" %-15s \n",(io->mod->free_mixt_rates)?("no"):("yes"));
}
if((io->mod->n_catg > 1) && (io->mod->free_mixt_rates == NO))
{
strcpy(s,(io->mod->s_opt->opt_alpha)?("estimated"):("fixed"));
(io->mod->s_opt->opt_alpha)?(strcat(s, "")):(strcat(s," (alpha = "));
if(io->mod->s_opt->opt_alpha)
{
strcat(s, "");
}
else
{
sprintf(s+strlen(s),"%3.2f)",io->mod->alpha->v);
}
PhyML_Printf(" [A] "
"... Gamma distribution parameter (fixed/estimated) "
" %-15s \n",s);
/* strcpy(s,(io->mod->gamma_median)?("median"):("mean")); */
/* PhyML_Printf(" [G] " */
/* ".........'Middle' of each rate class (mean/median) " */
/* " %-15s \n",s); */
}
PhyML_Printf("\n\n. Are these settings correct ? "
"(type '+', '-', 'Y' or other letter for one to change) ");
if(!scanf("%c",&choix)) Exit("\n");
if(choix != '\n') getchar(); /* \n */
Uppercase(&choix);
switch(choix)
{
/* case '\n': */
/* { */
/* io->curr_interface++; */
/* break; */
/* } */
case 'G' :
{
io->mod->free_mixt_rates = (io->mod->free_mixt_rates)?(NO):(YES);
break;
}
case 'O' :
{
io->mod->s_opt->opt_rr = (io->mod->s_opt->opt_rr)?(0):(1);
break;
}
case 'K' :
{
int i,j;
char **rr_param,*rr;
model *mod;
int curr_param;
int n_trial;
if(io->mod->whichmodel == CUSTOM)
{
rr_param = (char **)mCalloc(6,sizeof(char *));
For(i,6) rr_param[i] = (char *)mCalloc(10,sizeof(char));
rr = (char *)mCalloc(50,sizeof(char));
mod = io->mod;
mod->s_opt->opt_rr = 1;
n_trial = 0;
do
{
PhyML_Printf("\n. Enter a new custom model > ");
Getstring_Stdin(io->mod->custom_mod_string);
if(strlen(io->mod->custom_mod_string) == 6)
{
For(i,6)
{
while(!isdigit((int)io->mod->custom_mod_string[i]))
{
if(++n_trial > 10) Exit("\n. Err : this string is not valid !\n");
PhyML_Printf("\n. This string is not valid\n");
PhyML_Printf("\n. Enter a new model > ");
Getstring_Stdin(io->mod->custom_mod_string);
}
}
if(i == 6) break;
}
else
{
PhyML_Printf("\n. The string should be of length 6\n");
n_trial++;
}
}while(n_trial < 10);
if(n_trial == 10) Exit("");
if(!mod->rr->v) Make_Custom_Model(mod);
Translate_Custom_Mod_String(io->mod);
strcpy(rr_param[0],"A<->C");
strcpy(rr_param[1],"A<->G");
strcpy(rr_param[2],"A<->T");
strcpy(rr_param[3],"C<->G");
strcpy(rr_param[4],"C<->T");
strcpy(rr_param[5],"G<->T");
PhyML_Printf("\n. Set the relative rate values\n");
curr_param = 0;
For(i,mod->n_diff_rr)
{
sprintf(rr,"\n. [");
For(j,6)
{
if(mod->rr_num->v[j] == i)
{
sprintf(rr+strlen(rr),"%s = ",rr_param[j]);
}
}
sprintf(rr+strlen(rr)-3,"]");
PhyML_Printf("%s",rr);
PhyML_Printf(" (current=%.2f) > ",mod->rr_val->v[i]);
Getstring_Stdin(rr);
if(rr[0] != '\0')
{
n_trial = 0;
while((atof(rr) < .0))
{
if(++n_trial > 10)
Exit("\n. Err : the value of this parameter must be a positive number\n");
PhyML_Printf("\n. The value of this parameter must be a positive number\n");
PhyML_Printf("\n. Enter a new value > ");
Getstring_Stdin(rr);
}
io->mod->rr_val->v[i] = (phydbl)atof(rr);
}
}
For(i,5) Free(rr_param[i]);
Free(rr_param);
Free(rr);
}
break;
}
case 'E' :
{
int i;
if(io->mod->whichmodel == CUSTOM)
{
io->mod->s_opt->user_state_freq = (io->mod->s_opt->user_state_freq)?(0):(1);
if(io->mod->s_opt->user_state_freq)
{
if(!io->mod->s_opt->opt_state_freq)
{
char **bases;
char *bs;
phydbl sum;
int n_trial;
bases = (char **)mCalloc(4,sizeof(char *));
For(i,4) bases[i] = (char *)mCalloc(50,sizeof(char));
bs = (char *)mCalloc(100,sizeof(char));
strcpy(bases[0],". f(A)> ");
strcpy(bases[1],". f(C)> ");
strcpy(bases[2],". f(G)> ");
strcpy(bases[3],". f(T)> ");
PhyML_Printf("\n. Set nucleotide frequencies \n");
sum = .0;
For(i,4)
{
PhyML_Printf("%s",bases[i]);
Getstring_Stdin(bs);
n_trial = 0;
while((atof(bs) < .0001) || (bs[0] == '\0'))
{
if(++n_trial > 10)
Exit("\n. Err : the value of this parameter must be a positive number\n");
PhyML_Printf("\n. The value of this parameter must be a positive number\n");
PhyML_Printf("\n. Enter a new value > ");
Getstring_Stdin(bs);
}
io->mod->user_b_freq->v[i] = (phydbl)atof(bs);
sum += io->mod->user_b_freq->v[i];
}
For(i,4) io->mod->user_b_freq->v[i] /= sum;
if(sum > 1.0 || sum < 1.0)
{
PhyML_Printf("\n. The nucleotide frequencies have to be normalised in order to sum to 1.0.\n");
PhyML_Printf("\n. The frequencies are now : f(A)=%f, f(C)=%f, f(G)=%f, f(T)=%f.\n",
io->mod->user_b_freq->v[0],
io->mod->user_b_freq->v[1],
io->mod->user_b_freq->v[2],
io->mod->user_b_freq->v[3]);
PhyML_Printf("\n. Enter any key to continue.\n");
if(!scanf("%c",bs)) Exit("\n");
}
For(i,4) Free(bases[i]);
Free(bases);
Free(bs);
}
else
{
Warn_And_Exit("\n. 'E' is not a valid option with these model settings.\n");
}
}
}
break;
}
case 'A' :
{
char answer;
int n_trial;
switch(io->mod->s_opt->opt_alpha)
{
case 0 :
{
PhyML_Printf("\n. Optimise alpha ? [Y/n] ");
if(!scanf("%c",&answer)) Exit("\n");
if(answer == '\n') answer = 'Y';
else getchar();
break;
}
case 1 :
{
PhyML_Printf("\n. Optimise alpha ? [N/y] ");
if(!scanf("%c",&answer)) Exit("\n");
if(answer == '\n') answer = 'N';
else getchar();
break;
}
default : Exit("\n");
}
n_trial = 0;
while((answer != 'Y') && (answer != 'y') &&
(answer != 'N') && (answer != 'n'))
{
if(++n_trial > 10) Exit("\n. Err : wrong answers !");
PhyML_Printf("\n. Optimise alpha ? [N/y] ");
if(!scanf("%c",&answer)) Exit("\n");
if(answer == '\n') answer = 'N';
else getchar();
}
switch(answer)
{
case 'Y' : case 'y' :
{
io->mod->s_opt->opt_alpha = 1;
io->mod->s_opt->opt_subst_param = 1;
break;
}
case 'N' : case 'n' :
{
char *a;
a = (char *)mCalloc(100,sizeof(char));
io->mod->alpha->v = 10.0;
io->mod->s_opt->opt_alpha = 0;
PhyML_Printf("\n. Enter your value of alpha > ");
Getstring_Stdin(a);
n_trial = 0;
while(atof(a) < 1.E-10)
{
if(++n_trial > 10) Exit("\n. Err : alpha must be > 1.E-10\n");
PhyML_Printf("\n. Alpha must be 1.E-10\n");
PhyML_Printf("\n. Enter a new value > ");
Getstring_Stdin(a);
}
io->mod->alpha->v = (phydbl)atof(a);
Free(a);
io->mod->s_opt->opt_alpha = 0;
break;
}
}
break;
}
case 'C' :
{
char *c;
int n_trial;
PhyML_Printf("\n. Enter your number of categories > ");
c = (char *)mCalloc(100,sizeof(char));
Getstring_Stdin(c);
n_trial = 0;
while((!atoi(c)) || (atoi(c) < 0))
{
if(++n_trial > 10) Exit("\n. Err : the number of categories must be a positive integer\n");
PhyML_Printf("\n. The number of categories must be a positive integer\n");
PhyML_Printf("\n. Enter a new value > ");
Getstring_Stdin(c);
}
io->mod->n_catg = atoi(c);
Free(c);
break;
}
case 'R' :
{
(io->mod->n_catg == 1)?(io->mod->n_catg = 4):(io->mod->n_catg = 1);
break;
}
case 'V' :
{
char answer;
int n_trial;
switch(io->mod->s_opt->opt_pinvar)
{
case 0 :
{
PhyML_Printf("\n. Optimise p-invar ? [Y/n] ");
if(!scanf("%c", &answer)) Exit("\n");
if(answer == '\n') answer = 'Y';
else getchar();
break;
}
case 1 :
{
PhyML_Printf("\n. Optimise p-invar ? [N/y] ");
if(!scanf("%c", &answer)) Exit("\n");
if(answer == '\n') answer = 'N';
else getchar();
break;
}
default : Exit("\n");
}
n_trial = 0;
while((answer != 'Y') && (answer != 'y') &&
(answer != 'N') && (answer != 'n'))
{
if(++n_trial > 10) Exit("\n. Err : wrong answers !");
PhyML_Printf("\n. Optimise p-invar ? [N/y] ");
if(!scanf("%c", &answer)) Exit("\n");
if(answer == '\n') answer = 'N';
else getchar();
}
switch(answer)
{
case 'Y' : case 'y' :
{
io->mod->s_opt->opt_subst_param = 1;
io->mod->s_opt->opt_pinvar = 1;
io->mod->pinvar->v = 0.2;
io->mod->invar = 1;
break;
}
case 'N' : case 'n' :
{
char *p;
p = (char *)mCalloc(100,sizeof(char));
PhyML_Printf("\n. Enter your value of p-invar > ");
Getstring_Stdin(p);
n_trial = 0;
while((atof(p) < 0.0) || (atof(p) > 1.0))
{
if(++n_trial > 10)
Exit("\n. Err : the proportion of invariable sites must be a positive number between 0.0 and 1.0");
PhyML_Printf("\n. The proportion must be a positive number between 0.0 and 1.0\n");
PhyML_Printf("\n. Enter a new value > ");
Getstring_Stdin(p);
}
io->mod->pinvar->v = (phydbl)atof(p);
if(io->mod->pinvar->v > 0.0+SMALL) io->mod->invar = 1;
else io->mod->invar = 0;
Free(p);
io->mod->s_opt->opt_pinvar = 0;
break;
}
}
break;
}
case 'T' :
{
char answer;
int n_trial;
if((io->datatype == AA) ||
(io->mod->whichmodel == JC69)||
(io->mod->whichmodel == F81) ||
(io->mod->whichmodel == GTR) ||
(io->mod->whichmodel == CUSTOM))
{
PhyML_Printf("\n. 'K' is not a valid choice for this model\n");
PhyML_Printf("\n. Type any key to exit.\n");
if(!scanf("%c",&choix)) Exit("\n");
Exit("\n");
}
switch(io->mod->s_opt->opt_kappa)
{
case 0 :
{
PhyML_Printf("\n. Optimise ts/tv ratio ? [Y/n] ");
if(!scanf("%c", &answer)) Exit("\n");
if(answer == '\n') answer = 'Y';
else getchar();
break;
}
case 1 :
{
PhyML_Printf("\n. Optimise ts/tv ratio ? [N/y] ");
if(!scanf("%c", &answer)) Exit("\n");
if(answer == '\n') answer = 'N';
else getchar();
break;
}
default : Exit("\n");
}
n_trial = 0;
while((answer != 'Y') && (answer != 'y') &&
(answer != 'N') && (answer != 'n'))
{
if(++n_trial > 10) Exit("\n. Err : wrong answers !");
PhyML_Printf("\n. Optimise ts/tv ratio ? [N/y] ");
if(!scanf("%c", &answer)) Exit("\n");
if(answer == '\n') answer = 'N';
else getchar();
}
switch(answer)
{
case 'Y' : case 'y' :
{
io->mod->kappa->v = 4.0;
io->mod->s_opt->opt_subst_param = 1;
io->mod->s_opt->opt_kappa = 1;
if(io->mod->whichmodel == TN93)
io->mod->s_opt->opt_lambda = 1;
break;
}
case 'N' : case 'n' :
{
char *t;
t = (char *)mCalloc(100,sizeof(char));
io->mod->s_opt->opt_kappa = 0;
PhyML_Printf("\n. Enter your value of the ts/tv ratio > ");
Getstring_Stdin(t);
n_trial = 0;
while(atof(t) < .0)
{
if(++n_trial > 10) Exit("\n. Err : the ts/tv ratio must be a positive number\n");
PhyML_Printf("\n. The ratio must be a positive number");
PhyML_Printf("\n. Enter a new value > ");
Getstring_Stdin(t);
}
io->mod->kappa->v = (phydbl)atof(t);
io->mod->s_opt->opt_kappa = 0;
io->mod->s_opt->opt_lambda = 0;
Free(t);
break;
}
}
break;
}
case 'F' :
{
if((io->mod->whichmodel == JC69) ||
(io->mod->whichmodel == K80))
{
Warn_And_Exit("\n. 'F' is not a valid choice with these model settings.\n");
}
io->mod->s_opt->opt_state_freq = (io->mod->s_opt->opt_state_freq)?(0):(1);
break;
}
case 'M' :
{
if(io->datatype == NT)
{
if(!strcmp(io->nt_or_cd,"nucleotides"))
{
if(io->mod->whichmodel == JC69)
{
io->mod->whichmodel = K80;
}
else if(io->mod->whichmodel == K80)
{
io->mod->whichmodel = F81;
}
else if(io->mod->whichmodel == F81)
{
io->mod->whichmodel = HKY85;
}
else if(io->mod->whichmodel == HKY85)
{
io->mod->whichmodel = F84;
}
else if(io->mod->whichmodel == F84)
{
io->mod->whichmodel = TN93;
}
else if(io->mod->whichmodel == TN93)
{
io->mod->whichmodel = GTR;
}
else if(io->mod->whichmodel == GTR)
{
io->mod->whichmodel = CUSTOM;
}
else if(io->mod->whichmodel == CUSTOM)
{
io->mod->whichmodel = JC69;
}
}
}
else if(io->datatype == AA)
{
if(io->mod->whichmodel == LG)
{
io->mod->whichmodel = WAG;
}
else if(io->mod->whichmodel == WAG)
{
io->mod->whichmodel = DAYHOFF;
}
else if(io->mod->whichmodel == DAYHOFF)
{
io->mod->whichmodel = JTT;
}
else if(io->mod->whichmodel == JTT)
{
io->mod->whichmodel = BLOSUM62;
}
else if(io->mod->whichmodel == BLOSUM62)
{
io->mod->whichmodel = MTREV;
}
else if(io->mod->whichmodel == MTREV)
{
io->mod->whichmodel = RTREV;
}
else if(io->mod->whichmodel == RTREV)
{
io->mod->whichmodel = CPREV;
}
else if(io->mod->whichmodel == CPREV)
{
io->mod->whichmodel = DCMUT;
}
else if(io->mod->whichmodel == DCMUT)
{
io->mod->whichmodel = VT;
}
else if(io->mod->whichmodel == VT)
{
io->mod->whichmodel = MTMAM;
}
else if(io->mod->whichmodel == MTMAM)
{
io->mod->whichmodel = MTART;
}
else if(io->mod->whichmodel == MTART)
{
io->mod->whichmodel = HIVW;
}
else if(io->mod->whichmodel == HIVW)
{
io->mod->whichmodel = HIVB;
}
else if(io->mod->whichmodel == HIVB)
{
io->mod->whichmodel = CUSTOMAA;
}
else if(io->mod->whichmodel == CUSTOMAA)
{
io->mod->whichmodel = LG;
}
}
else if(io->datatype == GENERIC)
{
io->mod->whichmodel = JC69;
}
Set_Model_Name(io->mod);
break;
}
case '-' :
{
io->curr_interface = INTERFACE_DATA_TYPE;
break;
}
case '+' :
{
io->curr_interface = (io->config_multigene)?(INTERFACE_DATA_TYPE):(INTERFACE_TOPO_SEARCH);
break;
}
case 'Y' :
{
io->ready_to_go = 1;
break;
}
default :
{
break;
}
}
if(io->mod->s_opt->opt_alpha ||
io->mod->s_opt->opt_kappa ||
io->mod->s_opt->opt_lambda ||
io->mod->s_opt->opt_pinvar ||
io->mod->s_opt->opt_rr) io->mod->s_opt->opt_subst_param = 1;
else io->mod->s_opt->opt_subst_param = 0;
Free(s);
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void Launch_Interface_Topo_Search(option *io)
{
char choix;
char *s;
s = (char *)mCalloc(100,sizeof(char));
Clear();
Print_Banner(stdout);
PhyML_Printf("\n\n");
PhyML_Printf(" ....................... \n");
PhyML_Printf(" Menu : Tree Searching \n");
PhyML_Printf(" ............................. \n");
PhyML_Printf("\n\n");
PhyML_Printf(" [+] "
".................................... Next sub-menu\n");
PhyML_Printf(" [-] "
"................................ Previous sub-menu\n");
PhyML_Printf(" [Y] "
".............................. Launch the analysis\n");
PhyML_Printf("\n");
PhyML_Printf(" [O] "
"........................... Optimise tree topoLOGy "
" %-15s \n",
(io->mod->s_opt->opt_topo)?("yes"):("no"));
if(io->mod->s_opt->opt_topo)
{
switch(io->in_tree)
{
case 0: { strcpy(s,"BioNJ"); break; }
case 1: { strcpy(s,"parsimony"); break; }
case 2: { strcpy(s,"user tree"); break; }
}
PhyML_Printf(" [U] "
"........ Starting tree (BioNJ/parsimony/user tree) "
" %-15s \n",s);
}
else
{
switch(io->in_tree)
{
case 0: { strcpy(s,"BioNJ"); break; }
case 2: { strcpy(s,"user tree"); break; }
}
PhyML_Printf(" [U] "
"..................... Input tree (BioNJ/user tree) "
" %-15s \n",s);
}
if(io->mod->s_opt->opt_topo)
{
char *s;
s = (char *)mCalloc(T_MAX_OPTION,sizeof(char));
if(io->mod->s_opt->topo_search == NNI_MOVE)
{
strcpy(s,"NNI moves (fast, approximate)\0");
}
else if(io->mod->s_opt->topo_search == SPR_MOVE)
{
strcpy(s,"SPR moves (slow, accurate)\0");
}
else if(io->mod->s_opt->topo_search == BEST_OF_NNI_AND_SPR)
{
strcpy(s,"Best of NNI and SPR \0");
}
PhyML_Printf(" [S] "
".................. Tree topoLOGy search operations "
" %-15s \n",s);
Free(s);
if(io->mod->s_opt->topo_search != NNI_MOVE)
{
PhyML_Printf(" [R] "
"........................ Add random starting trees "
" %-15s \n",
(io->mod->s_opt->random_input_tree)?("yes"):("no"));
if(io->mod->s_opt->random_input_tree)
{
PhyML_Printf(" [N] "
".................. Number of random starting trees "
" %-15d \n",io->mod->s_opt->n_rand_starts);
}
}
}
else
{
PhyML_Printf(" [L] "
".......................... Optimise branch lengths "
" %-15s \n",
(io->mod->s_opt->opt_bl)?("yes"):("no"));
}
PhyML_Printf("\n\n. Are these settings correct ? "
"(type '+', '-', 'Y' or other letter for one to change) ");
if(!scanf("%c",&choix)) Exit("\n");
if(choix != '\n') getchar(); /* \n */
Free(s);
Uppercase(&choix);
switch(choix)
{
case '-' :
{
io->curr_interface = INTERFACE_MODEL;
break;
}
case '+' :
{
io->curr_interface = INTERFACE_BRANCH_SUPPORT;
break;
}
case 'Y' :
{
io->ready_to_go = 1;
break;
}
case 'U' :
{
io->in_tree++;
if(!io->mod->s_opt->opt_topo)
{
if(io->in_tree == 1) io->in_tree = 2;
}
if(io->in_tree == 3) io->in_tree = 0;
break;
}
case 'N' :
{
char *n;
int n_trial;
PhyML_Printf("\n. Enter your number of starting trees > ");
n = (char *)mCalloc(100,sizeof(char));
Getstring_Stdin(n);
n_trial = 0;
while(atoi(n) < 1)
{
if(++n_trial > 10) Exit("\n. Err : the number of starting trees must be a positive integer\n");
PhyML_Printf("\n. The number of starting trees must be a positive integer\n");
PhyML_Printf("\n. Enter a new value > ");
Getstring_Stdin(n);
}
io->mod->s_opt->n_rand_starts = atoi(n);
io->n_trees = 1;
Free(n);
break;
}
case 'O' :
{
io->mod->s_opt->opt_topo = (io->mod->s_opt->opt_topo)?(0):(1);
break;
}
case 'L' :
{
if(!io->mod->s_opt->opt_topo)
{
io->mod->s_opt->opt_bl = (io->mod->s_opt->opt_bl)?(0):(1);
}
break;
}
case 'S' :
{
if(io->mod->s_opt->topo_search == NNI_MOVE)
{
io->mod->s_opt->topo_search = SPR_MOVE;
io->mod->s_opt->n_rand_starts = 1;
io->mod->s_opt->random_input_tree = 0;
io->mod->s_opt->greedy = 0;
}
else if(io->mod->s_opt->topo_search == SPR_MOVE)
{
io->mod->s_opt->topo_search = BEST_OF_NNI_AND_SPR;
io->mod->s_opt->n_rand_starts = 1;
io->mod->s_opt->random_input_tree = 0;
io->mod->s_opt->greedy = 0;
}
else if(io->mod->s_opt->topo_search == BEST_OF_NNI_AND_SPR)
{
io->mod->s_opt->topo_search = NNI_MOVE;
io->mod->s_opt->n_rand_starts = 1;
io->mod->s_opt->random_input_tree = 0;
io->mod->s_opt->greedy = 0;
}
break;
}
case 'R' :
{
io->mod->s_opt->random_input_tree = (io->mod->s_opt->random_input_tree)?(0):(1);
if(io->mod->s_opt->random_input_tree)
{
if(io->fp_in_tree) fclose(io->fp_in_tree);
/* io->in_tree = 0; */
io->n_trees = 1;
io->mod->s_opt->n_rand_starts = 5;
strcpy(io->out_trees_file,io->in_align_file);
strcat(io->out_trees_file,"_phyml_trees.txt");
}
break;
}
default :
{
break;
}
}
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void Launch_Interface_Branch_Support(option *io)
{
char choix;
char *s;
s = (char *)mCalloc(100,sizeof(char));
Clear();
Print_Banner(stdout);
PhyML_Printf("\n\n");
PhyML_Printf(" ....................... \n");
PhyML_Printf(" Menu : Branch Support \n");
PhyML_Printf(" ............................. \n");
PhyML_Printf("\n\n");
PhyML_Printf(" [+] "
".................................... Next sub-menu\n");
PhyML_Printf(" [-] "
"................................ Previous sub-menu\n");
PhyML_Printf(" [Y] "
".............................. Launch the analysis\n");
PhyML_Printf("\n");
strcpy(s,(io->mod->bootstrap > 0)?("yes"):("no"));
if(io->mod->bootstrap > 0) sprintf(s+strlen(s)," (%d replicate%s)",
io->mod->bootstrap,
(io->mod->bootstrap>1)?("s"):(""));
/* PhyML_Printf(" [+] " */
PhyML_Printf(" [B] "
"................ Non parametric bootstrap analysis "
" %-15s \n",s);
if(io->ratio_test == 0)
{
strcpy(s,"no");
}
else if(io->ratio_test == 1)
{
strcpy(s,"yes / aLRT statistics");
}
else if(io->ratio_test == 2)
{
strcpy(s,"yes / Chi2-based supports");
}
else if(io->ratio_test == 3)
{
strcpy(s,"yes / min of SH-like & Chi2-based supports");
}
else if(io->ratio_test == 4)
{
strcpy(s,"yes / SH-like supports");
}
else if(io->ratio_test == 5)
{
strcpy(s,"yes / aBayes supports");
}
/* PhyML_Printf(" [+] " */
PhyML_Printf(" [A] "
"................ Approximate likelihood ratio test "
" %-15s \n",s);
PhyML_Printf("\n. Are these settings correct ? "
"(type '+', '-', 'Y' or other letter for one to change) ");
if(!scanf("%c",&choix)) Exit("\n");
if(choix != '\n') getchar(); /* \n */
Uppercase(&choix);
Free(s);
switch(choix)
{
/* case '\n': */
/* { */
/* io->curr_interface++; */
/* break; */
/* } */
case 'B' :
{
if(io->mod->bootstrap > 0) io->mod->bootstrap = 0;
else
{
char *r;
char answer;
int n_trial;
io->ratio_test = 0;
if(io->n_data_sets > 1)
{
PhyML_Printf("\n. Bootstrap option is not allowed with multiple data sets.\n");
PhyML_Printf("\n. Type any key to exit.\n");
if(!scanf("%c",&choix)) Exit("\n");
Exit("\n");
}
PhyML_Printf("\n. Number of replicates > ");
r = (char *)mCalloc(T_MAX_OPTION,sizeof(char));
Getstring_Stdin(r);
n_trial = 0;
while((!atoi(r)) || (atoi(r) < 0))
{
if(++n_trial > 10) Exit("\n. Err : the number of replicates must be a positive integer\n");
PhyML_Printf("\n. The number of replicates must be a positive integer");
PhyML_Printf("\n. Enter a new value > ");
Getstring_Stdin(r);
}
io->mod->bootstrap = atoi(r);
PhyML_Printf("\n. Print bootstrap trees (and statistics) ? (%s) > ",
(io->print_boot_trees)?("Y/n"):("y/N"));
if(!scanf("%c",&answer)) Exit("\n");
if(answer == '\n') answer = (io->print_boot_trees)?('Y'):('N');
else getchar();
switch(answer)
{
case 'Y' : case 'y' :
{
io->print_boot_trees = 1;
strcpy(io->out_boot_tree_file,io->in_align_file);
strcat(io->out_boot_tree_file,"_phyml_boot_trees.txt");
io->fp_out_boot_tree = Openfile(io->out_boot_tree_file,1);
strcpy(io->out_boot_stats_file,io->in_align_file);
strcat(io->out_boot_stats_file,"_phyml_boot_stats.txt");
io->fp_out_boot_stats = Openfile(io->out_boot_stats_file,1);
break;
}
case 'N' : case 'n' :
{
io->print_boot_trees = 0;
io->fp_out_boot_tree = NULL;
io->fp_out_boot_stats = NULL;
break;
}
}
Free(r);
}
break;
}
case 'A' :
{
io->mod->bootstrap = 0;
switch(io->ratio_test)
{
case 0 :
{
io->ratio_test = 1;
break;
}
case 1 :
{
io->ratio_test = 2;
break;
}
case 2 :
{
/* io->ratio_test = 3; */
io->ratio_test = 4;
break;
}
case 3 :
{
io->ratio_test = 4;
break;
}
case 4 :
{
io->ratio_test = 5;
break;
}
case 5 :
{
io->ratio_test = 0;
break;
}
}
break;
}
case '-' :
{
io->curr_interface = INTERFACE_TOPO_SEARCH;
break;
}
case '+' :
{
io->curr_interface = INTERFACE_DATA_TYPE;
break;
}
case 'Y' :
{
io->ready_to_go = 1;
break;
}
default : break;
}
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void Launch_Interface_Multigene(option *io)
{
#ifdef PART
if((io->n_data_sets > 1) && (io->multigene))
{
int set, n_trial;
char choix;
io->n_part = io->n_data_sets;
io->st = (supert_tree *)PART_Make_Supert_tree_Light(io);
io->st->n_part = io->n_data_sets;
For(set,io->n_part)
{
io->st->optionlist[set] = Make_Input();
Set_Defaults_Input(io->st->optionlist[set]);
Set_Defaults_Model(io->st->optionlist[set]->mod);
Set_Defaults_Optimiz(io->st->optionlist[set]->mod->s_opt);
io->st->optionlist[set]->curr_gt = set;
PhyML_Printf("\n. Enter the sequence file name [data set %2d] > ",set+1); fflush(NULL);
Getstring_Stdin(io->st->optionlist[set]->in_align_file);
io->st->optionlist[set]->fp_in_align = Openfile(io->st->optionlist[set]->in_align_file,0);
}
PhyML_Printf("\n. Do you want to use your own initial tree ? [N/y] ");
if(!scanf("%c", &choix)) Exit("\n");
if(choix != '\n') getchar();
n_trial = 0;
while((choix != 'Y') && (choix != 'y') &&
(choix != 'N') && (choix != 'n'))
{
if(++n_trial > 10) Exit("\n. Err : wrong answers !");
PhyML_Printf("\n. Do you want to use your own initial tree ? [N/y] ? ");
if(!scanf("%c", &choix)) Exit("\n");
if(choix == '\n') choix = 'N';
else getchar();
}
switch(choix)
{
case '\n' : break;
case 'Y' : case 'y' :
{
io->in_tree = 2;
PhyML_Printf("\n. Enter the name of the tree file > ");
Getstring_Stdin(io->in_tree_file);
io->fp_in_tree = Openfile(io->in_tree_file,0);
break;
}
case 'N' : case 'n' :
{
io->in_tree = 0;
break;
}
default : break;
}
io->curr_gt = 0;
do
{
io->st->optionlist[io->curr_gt]->config_multigene = 1;
do
{
switch(io->st->optionlist[io->curr_gt]->curr_interface)
{
case INTERFACE_DATA_TYPE :
{
Launch_Interface_Data_Type(io->st->optionlist[io->curr_gt]);
break;
}
case INTERFACE_MODEL :
{
Launch_Interface_Model(io->st->optionlist[io->curr_gt]);
break;
}
default :
{
PhyML_Printf("\n. Err in file %s at line %d\n\n",__FILE__,__LINE__);
Exit("");
break;
}
}
}while(!io->st->optionlist[io->curr_gt]->ready_to_go);
io->curr_gt++;
}while(io->curr_gt < io->n_part);
}
io->ready_to_go = 1;
PART_Fill_Model_Partitions_Table(io->st);
#endif
}
phyml-20120412/src/main.c 0000644 0001750 0001750 00000031267 11741131042 011703 0000000 0000000 /*
PhyML: a program that computes maximum likelihood phyLOGenies from
DNA or AA homoLOGous sequences.
Copyright (C) Stephane Guindon. Oct 2003 onward.
All parts of the source except where indicated are distributed under
the GNU public licence. See http://www.opensource.org for details.
*/
#include "spr.h"
#include "utilities.h"
#include "lk.h"
#include "optimiz.h"
#include "bionj.h"
#include "models.h"
#include "free.h"
#include "help.h"
#include "simu.h"
#include "eigen.h"
#include "pars.h"
#include "alrt.h"
#ifdef MPI
#include "mpi_boot.h"
#endif
#ifdef PHYML
int main(int argc, char **argv)
{
calign *cdata;
option *io;
t_tree *tree;
int n_otu, num_data_set;
int num_tree,tree_line_number,num_rand_tree;
matrix *mat;
model *mod;
time_t t_beg,t_end;
phydbl best_lnL,most_likely_size,tree_size;
int r_seed;
char *most_likely_tree=NULL;
#ifdef MPI
int rc;
rc = MPI_Init(&argc,&argv);
if (rc != MPI_SUCCESS) {
PhyML_Printf("\n. Error starting MPI program. Terminating.\n");
MPI_Abort(MPI_COMM_WORLD, rc);
}
MPI_Comm_size(MPI_COMM_WORLD,&Global_numTask);
MPI_Comm_rank(MPI_COMM_WORLD,&Global_myRank);
#endif
#ifdef QUIET
setvbuf(stdout,NULL,_IOFBF,2048);
#endif
tree = NULL;
mod = NULL;
best_lnL = UNLIKELY;
most_likely_size = -1.0;
tree_size = -1.0;
io = (option *)Get_Input(argc,argv);
r_seed = (io->r_seed < 0)?(time(NULL)):(io->r_seed);
srand(r_seed);
io->r_seed = r_seed;
if(io->in_tree == 2) Test_Multiple_Data_Set_Format(io);
else io->n_trees = 1;
if(io->n_trees == 0 && io->in_tree == 2)
{
PhyML_Printf("\n. The input tree file does not provide a tree in valid format.");
Exit("\n");
}
mat = NULL;
tree_line_number = 0;
if((io->n_data_sets > 1) && (io->n_trees > 1))
{
io->n_data_sets = MIN(io->n_trees,io->n_data_sets);
io->n_trees = MIN(io->n_trees,io->n_data_sets);
}
For(num_data_set,io->n_data_sets)
{
n_otu = 0;
best_lnL = UNLIKELY;
Get_Seq(io);
Make_Model_Complete(io->mod);
Set_Model_Name(io->mod);
Print_Settings(io);
mod = io->mod;
if(io->data)
{
if(io->n_data_sets > 1) PhyML_Printf("\n. Data set [#%d]\n",num_data_set+1);
cdata = Compact_Data(io->data,io);
Free_Seq(io->data,cdata->n_otu);
if(cdata) Check_Ambiguities(cdata,io->datatype,io->mod->state_len);
else
{
PhyML_Printf("\n. Err in file %s at line %d\n",__FILE__,__LINE__);
Warn_And_Exit("");
}
for(num_tree=(io->n_trees == 1)?(0):(num_data_set);num_tree < io->n_trees;num_tree++)
{
if(!io->mod->s_opt->random_input_tree) io->mod->s_opt->n_rand_starts = 1;
For(num_rand_tree,io->mod->s_opt->n_rand_starts)
{
if((io->mod->s_opt->random_input_tree) && (io->mod->s_opt->topo_search != NNI_MOVE))
if(!io->quiet) PhyML_Printf("\n. [Random start %3d/%3d]\n",num_rand_tree+1,io->mod->s_opt->n_rand_starts);
Init_Model(cdata,mod,io);
if(io->mod->use_m4mod) M4_Init_Model(mod->m4mod,cdata,mod);
switch(io->in_tree)
{
case 0 : case 1 : { tree = Dist_And_BioNJ(cdata,mod,io); break; }
case 2 : { tree = Read_User_Tree(cdata,mod,io); break; }
}
if(io->fp_in_constraint_tree != NULL)
{
char *s;
io->cstr_tree = Read_Tree_File_Phylip(io->fp_in_constraint_tree);
s = Add_Taxa_To_Constraint_Tree(io->fp_in_constraint_tree,cdata);
fflush(NULL);
if(tree->mat) Free_Mat(tree->mat);
Free_Tree(tree);
tree = Read_Tree(&s);
io->in_tree = 2;
Free(s);
Check_Constraint_Tree_Taxa_Names(io->cstr_tree,cdata);
Alloc_Bip(io->cstr_tree);
Get_Bip(io->cstr_tree->t_nodes[0],
io->cstr_tree->t_nodes[0]->v[0],
io->cstr_tree);
if(!tree->has_branch_lengths) Add_BioNJ_Branch_Lengths(tree,cdata,mod);
}
if(!tree) continue;
time(&t_beg);
time(&(tree->t_beg));
tree->mod = mod;
tree->io = io;
tree->data = cdata;
tree->both_sides = YES;
tree->n_pattern = tree->data->crunch_len;
if(mod->s_opt->random_input_tree) Random_Tree(tree);
if((!num_data_set) && (!num_tree) && (!num_rand_tree)) Check_Memory_Amount(tree);
if(io->cstr_tree && !Check_Topo_Constraints(tree,io->cstr_tree))
{
PhyML_Printf("\n\n. The initial tree does not satisfy the topological constraint.");
PhyML_Printf("\n. Please use the user input tree option with an adequate tree topology.");
Exit("\n");
}
Prepare_Tree_For_Lk(tree);
/* ///////////////////////////////////////// */
/* Make_Mixtmod(3,tree); */
if(io->in_tree == 1) Spr_Pars(tree);
if(io->do_alias_subpatt)
{
tree->update_alias_subpatt = YES;
Lk(tree);
tree->update_alias_subpatt = NO;
}
if(tree->mod->s_opt->opt_topo)
{
if(tree->mod->s_opt->topo_search == NNI_MOVE) Simu_Loop(tree);
else if(tree->mod->s_opt->topo_search == SPR_MOVE) Speed_Spr_Loop(tree);
else Best_Of_NNI_And_SPR(tree);
if(tree->n_root) Add_Root(tree->t_edges[0],tree);
}
else
{
if(tree->mod->s_opt->opt_subst_param ||
tree->mod->s_opt->opt_bl) Round_Optimize(tree,tree->data,ROUND_MAX);
else Lk(tree);
}
tree->both_sides = 1;
Lk(tree);
Pars(tree);
Get_Tree_Size(tree);
PhyML_Printf("\n\n. Log likelihood of the current tree: %f.\n",tree->c_lnL);
Br_Len_Involving_Invar(tree);
Rescale_Br_Len_Multiplier_Tree(tree);
if(!tree->n_root) Get_Best_Root_Position(tree);
/* Print the tree estimated using the current random (or BioNJ) starting tree */
if(io->mod->s_opt->n_rand_starts > 1)
{
Print_Tree(io->fp_out_trees,tree);
fflush(NULL);
}
/* Record the most likely tree in a string of characters */
if(tree->c_lnL > best_lnL)
{
best_lnL = tree->c_lnL;
if(most_likely_tree) Free(most_likely_tree);
most_likely_tree = Write_Tree(tree,NO);
most_likely_size = Get_Tree_Size(tree);
}
/* JF(tree); */
time(&t_end);
Print_Fp_Out(io->fp_out_stats,t_beg,t_end,tree,
io,num_data_set+1,
(tree->mod->s_opt->n_rand_starts > 1)?
(num_rand_tree):(num_tree));
if(tree->io->print_site_lnl) Print_Site_Lk(tree,io->fp_out_lk);
/* Start from BioNJ tree */
if((num_rand_tree == io->mod->s_opt->n_rand_starts-1) && (tree->mod->s_opt->random_input_tree))
{
/* Do one more iteration in the loop, but don't randomize the tree */
num_rand_tree--;
tree->mod->s_opt->random_input_tree = 0;
}
if(io->fp_in_constraint_tree != NULL) Free_Tree(io->cstr_tree);
Free_Spr_List(tree);
Free_One_Spr(tree->best_spr);
if(tree->mat) Free_Mat(tree->mat);
Free_Triplet(tree->triplet_struct);
Free_Tree_Pars(tree);
Free_Tree_Lk(tree);
Free_Tree(tree);
}
/* Launch bootstrap analysis */
if(mod->bootstrap)
{
if(!io->quiet) PhyML_Printf("\n. Launch bootstrap analysis on the most likely tree...\n");
#ifdef MPI
MPI_Bcast (most_likely_tree, strlen(most_likely_tree)+1, MPI_CHAR, 0, MPI_COMM_WORLD);
if(!io->quiet) PhyML_Printf("\n. The bootstrap analysis will use %d CPUs.\n",Global_numTask);
#endif
most_likely_tree = Bootstrap_From_String(most_likely_tree,cdata,mod,io);
}
else if(io->ratio_test)
{
/* Launch aLRT */
if(!io->quiet) PhyML_Printf("\n. Compute fast branch supports on the most likely tree...\n");
most_likely_tree = aLRT_From_String(most_likely_tree,cdata,mod,io);
}
/* Print the most likely tree in the output file */
if(!io->quiet) PhyML_Printf("\n. Printing the most likely tree in file '%s'...\n", Basename(io->out_tree_file));
if(io->n_data_sets == 1) rewind(io->fp_out_tree);
PhyML_Fprintf(io->fp_out_tree,"%s\n",most_likely_tree);
if(io->n_trees > 1 && io->n_data_sets > 1) break;
}
Free_Cseq(cdata);
}
else
{
PhyML_Printf("\n. No data was found.\n");
PhyML_Printf("\n. Err in file %s at line %d\n",__FILE__,__LINE__);
Warn_And_Exit("");
}
Free_Model_Complete(mod);
}
if(most_likely_tree) Free(most_likely_tree);
if(mod->s_opt->n_rand_starts > 1) PhyML_Printf("\n. Best log likelihood: %f\n",best_lnL);
Free_Optimiz(mod->s_opt);
Free_Custom_Model(mod);
Free_Model_Basic(mod);
M4_Free_M4_Model(mod->m4mod);
Free(mod);
if(io->fp_in_constraint_tree) fclose(io->fp_in_constraint_tree);
if(io->fp_in_align) fclose(io->fp_in_align);
if(io->fp_in_tree) fclose(io->fp_in_tree);
if(io->fp_out_lk) fclose(io->fp_out_lk);
if(io->fp_out_tree) fclose(io->fp_out_tree);
if(io->fp_out_trees) fclose(io->fp_out_trees);
if(io->fp_out_stats) fclose(io->fp_out_stats);
Free_Input(io);
time(&t_end);
Print_Time_Info(t_beg,t_end);
#ifdef MPI
MPI_Finalize();
#endif
return 0;
}
#elif(M4)
#include "m4.h"
int main(int argc, char **argv)
{
M4_main(argc, argv);
return 1;
}
#elif(PART)
#include "mg.h"
int main(int argc, char **argv)
{
PART_main(argc, argv);
return 1;
}
#elif(PHYTIME)
#include "times.h"
int main(int argc, char **argv)
{
TIMES_main(argc, argv);
return 1;
}
#elif(PHYCONT)
#include "continuous.h"
int main(int argc, char **argv)
{
CONT_main(argc, argv);
return 1;
}
#elif(RF)
int main(int argc, char **argv)
{
t_tree *tree1, *tree2;
FILE *fp_tree1, *fp_tree2;
int i,j;
fp_tree1 = (FILE *)fopen(argv[1],"r");
fp_tree2 = (FILE *)fopen(argv[2],"r");
tree1 = Read_Tree_File_Phylip(fp_tree1);
tree2 = Read_Tree_File_Phylip(fp_tree2);
Match_Nodes_In_Small_Tree(tree1,tree2);
For(i,2*tree1->n_otu-2)
{
printf("\n. Node %d in tree1 matches node %d in tree2",i,(tree1->noeud[i]->match_node)?(tree1->noeud[i]->match_node->num):(-1));
}
/* t_tree *tree1, *tree2; */
/* FILE *fp_tree1, *fp_tree2; */
/* int i,j,rf,n_edges,n_common,bip_size; */
/* phydbl thresh; */
/* t_edge *b; */
/* fp_tree1 = (FILE *)fopen(argv[1],"r"); */
/* fp_tree2 = (FILE *)fopen(argv[2],"r"); */
/* thresh = (phydbl)atof(argv[3]); */
/* tree1 = Read_Tree_File(fp_tree1); */
/* tree2 = Read_Tree_File(fp_tree2); */
/* Get_Rid_Of_Prefix('_',tree1); */
/* /\* Find_Common_Tips(tree1,tree2); *\/ */
/* Alloc_Bip(tree1); */
/* Alloc_Bip(tree2); */
/* Get_Bip(tree1->noeud[0],tree1->noeud[0]->v[0],tree1); */
/* Get_Bip(tree2->noeud[0],tree2->noeud[0]->v[0],tree2); */
/* /\* PhyML_Printf("\n. rf=%f\n",Compare_Bip_On_Existing_Edges(thresh,tree1,tree2)); *\/ */
/* For(i,2*tree1->n_otu-3) tree1->t_edges[i]->bip_score = 0; */
/* For(i,2*tree2->n_otu-3) tree2->t_edges[i]->bip_score = 0; */
/* rf = 0; */
/* n_edges = 0; */
/* /\* First tree *\/ */
/* For(i,2*tree1->n_otu-3) */
/* { */
/* /\* Consider the branch only if the corresponding bipartition has size > 1 *\/ */
/* b = tree1->t_edges[i]; */
/* bip_size = MIN(b->left->bip_size[b->l_r],b->rght->bip_size[b->r_l]); */
/* if(bip_size > 1) */
/* { */
/* /\* with non-zero length *\/ */
/* if(tree1->t_edges[i]->l > thresh) */
/* { */
/* n_edges++; */
/* /\* This t_edge is not found in tree2 *\/ */
/* if(!tree1->t_edges[i]->bip_score) rf++; ; */
/* } */
/* } */
/* } */
/* /\* Second tree *\/ */
/* For(i,2*tree2->n_otu-3) */
/* { */
/* b = tree2->t_edges[i]; */
/* bip_size = MIN(b->left->bip_size[b->l_r],b->rght->bip_size[b->r_l]); */
/* if(bip_size > 1) */
/* { */
/* if(tree2->t_edges[i]->l > thresh) */
/* { */
/* n_edges++; */
/* /\* This t_edge is not found in tree1 *\/ */
/* if(!tree2->t_edges[i]->bip_score) rf++; ; */
/* } */
/* } */
/* } */
/* if(!n_edges) */
/* { */
/* Exit("\n. No comparable internal edges were found.\n"); */
/* } */
/* else */
/* { */
/* PhyML_Printf("\n. Robinson and Foulds distance: %f.",(double)rf/(n_edges)); */
/* /\* PhyML_Printf("\n. %d internal edges were processed (%d in the first tree, %d in the second).\n",n_edges,n_edges_t1,n_edges-n_edges_t1); *\/ */
/* PhyML_Printf("\n"); */
/* } */
return 1;
}
#elif(TIPORDER)
#include "tiporder.h"
int main(int argc, char **argv)
{
TIPO_main(argc, argv);
return 1;
}
#elif(TEST)
#include "xml.h"
int main(int argc, char **argv)
{
FILE *fp;
xml_node *root;
root = XML_New_Node(NULL,NULL);
fp = fopen(argv[1],"r");
XML_Load_File(fp,root);
return 1;
}
#endif
phyml-20120412/src/bionj.c 0000644 0001750 0001750 00000024530 11721311653 012061 0000000 0000000 /*
PHYML : a program that computes maximum likelihood phyLOGenies from
DNA or AA homoLOGous sequences
Copyright (C) Stephane Guindon. Oct 2003 onward
All parts of the source except where indicated are distributed under
the GNU public licence. See http://www.opensource.org for details.
*/
/*
The code below is an implementation of the building tree algorithm
described in "BIONJ: an improved version of the NJ algorithm based
on a simple model of sequence data." (1997) O. Gascuel. Mol Biol Evol.
14:685-95.
*/
#include "bionj.h"
void Bionj(matrix *mat)
{
int x,y,i;
phydbl vxy,lx,ly,lamda,score;
Clean_Tree_Connections(mat->tree);
For(i,mat->tree->n_otu) mat->tip_node[i] = mat->tree->t_nodes[i];
mat->tree->num_curr_branch_available = 0;
while(mat->r > 3)
{
x = y = 0;
vxy = .0;
score = .0;
Compute_Sx(mat);
Best_Pair(mat,&x,&y,&score);
vxy=Variance(mat,x,y);
lx=Br_Length(mat,x,y);
ly=Br_Length(mat,y,x);
lamda=Lamda(mat,x,y,vxy);
Update_Mat(mat,x,y,lx,ly,vxy,lamda);
Update_Tree(mat,x,y,lx,ly,score);
}
Finish(mat);
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void Finish(matrix *mat)
{
phydbl dxy,dxz,dyz;
int x,y,z;
t_node *nx,*ny,*nz,*new;
int i;
dxy = dxz = dyz = -1.;
x = y = z = -1;
For(i,mat->n_otu)
{
if(mat->on_off[i])
{
if(x < 0) x=i;
else if(y < 0) y = i;
else if(z < 0) z = i;
}
}
dxy = Dist(mat,x,y);
dxz = Dist(mat,x,z);
dyz = Dist(mat,y,z);
nx = mat->tip_node[x];
ny = mat->tip_node[y];
nz = mat->tip_node[z];
new = mat->tree->t_nodes[mat->curr_int];
new->num = mat->curr_int;
new->v[0] = nx;
new->v[1] = ny;
new->v[2] = nz;
nx->v[0] = new;
ny->v[0] = new;
nz->v[0] = new;
Connect_One_Edge_To_Two_Nodes(new,nx,mat->tree->t_edges[mat->tree->num_curr_branch_available],mat->tree);
mat->tree->num_curr_branch_available++;
Connect_One_Edge_To_Two_Nodes(new,ny,mat->tree->t_edges[mat->tree->num_curr_branch_available],mat->tree);
mat->tree->num_curr_branch_available++;
Connect_One_Edge_To_Two_Nodes(new,nz,mat->tree->t_edges[mat->tree->num_curr_branch_available],mat->tree);
mat->tree->num_curr_branch_available++;
nx->b[0]->l = .5*(dxy-dyz+dxz);
ny->b[0]->l = .5*(dyz-dxz+dxy);
nz->b[0]->l = .5*(dxz-dxy+dyz);
new->b[0]->l = nx->b[0]->l;
new->b[1]->l = ny->b[0]->l;
new->b[2]->l = nz->b[0]->l;
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void Update_Mat(matrix *mat, int x, int y, phydbl lx, phydbl ly, phydbl vxy, phydbl lamda)
{
int i;
int a,b;
a = b = -1;
For(i,mat->n_otu)
{
if((mat->on_off[i]) && (i != x) && (i != y))
{
if(x > i)
{
a=x;
b=i;
}
else
{
a=i;
b=x;
}
mat->dist[a][b]=Dist_Red(mat,x,lx,y,ly,i,lamda);
mat->dist[b][a]=Var_Red(mat,x,y,i,lamda,vxy);
}
}
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void Update_Tree(matrix *mat, int x, int y, phydbl lx, phydbl ly, phydbl score)
{
t_node *new, *nx, *ny;
nx = mat->tip_node[x];
ny = mat->tip_node[y];
new = mat->tree->t_nodes[mat->curr_int];
nx->v[0] = new;
ny->v[0] = new;
new->v[1] = nx;
new->v[2] = ny;
new->num = mat->curr_int;
Connect_One_Edge_To_Two_Nodes(new,nx,mat->tree->t_edges[mat->tree->num_curr_branch_available],mat->tree);
mat->tree->num_curr_branch_available++;
Connect_One_Edge_To_Two_Nodes(new,ny,mat->tree->t_edges[mat->tree->num_curr_branch_available],mat->tree);
mat->tree->num_curr_branch_available++;
nx->b[0]->l = lx;
ny->b[0]->l = ly;
new->b[1]->l = lx;
new->b[2]->l = ly;
new->score[0] = score;
nx->l[0] = lx;
ny->l[0] = ly;
new->l[1] = lx;
new->l[2] = ly;
mat->tip_node[x] = new;
mat->on_off[y] = 0;
mat->curr_int++;
mat->r--;
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void Best_Pair(matrix *mat, int *x, int *y,phydbl *score)
{
int i,j/* ,n_ties */;
phydbl Qmin,Qmin2;
phydbl *t_Qij;
/* int *ties; */
t_Qij = (phydbl *)mCalloc(mat->n_otu * mat->n_otu,sizeof(phydbl ));
/* ties = (int *)mCalloc(mat->n_otu * mat->n_otu,sizeof(int )); */
Qmin = 1.e+10;
For(i,mat->n_otu)
{
if(mat->on_off[i])
{
for(j=0;jon_off[j])
{
t_Qij[mat->n_otu*i+j] = Q_Agglo(mat,i,j);
if(t_Qij[mat->n_otu*i+j] < Qmin - 1.E-05)
{
*x = i;
*y = j;
Qmin = t_Qij[mat->n_otu*i+j];
}
}
}
}
}
/* n_ties = 0; */
/* For(i,mat->n_otu) */
/* { */
/* if(mat->on_off[i]) */
/* { */
/* for(j=0;jon_off[j]) */
/* { */
/* if((t_Qij[mat->n_otu*i+j] < Qmin + 1.E-05) && (t_Qij[mat->n_otu*i+j] > Qmin - 1.E-05)) */
/* { */
/* ties[n_ties] = mat->n_otu*i+j; */
/* n_ties++; */
/* } */
/* } */
/* } */
/* } */
/* } */
/* if(!n_ties) */
/* { */
/* PhyML_Printf("\n. Err in file %s at line %d\n\n",__FILE__,__LINE__); */
/* Warn_And_Exit(""); */
/* } */
/* /\* Useful if some pairwise distances are null *\/ */
/* if(n_ties > 1) */
/* { */
/* int cand; */
/* *x = *y = -1; */
/* cand = (int)RINT(rand()/(phydbl)(RAND_MAX) * (n_ties-1)); */
/* *x = (int)(ties[cand] / mat->n_otu); */
/* *y = (int)(ties[cand] % mat->n_otu); */
/* } */
Qmin2 = 1e+10;
For(i,mat->n_otu)
{
if((i != *y) && (i != *x) && (t_Qij[mat->n_otu*(*x)+i] < Qmin2)) Qmin2 = t_Qij[mat->n_otu*(*x)+i];
}
For(i,mat->n_otu)
{
if((i != *y) && (i != *x) && (t_Qij[mat->n_otu*i+(*y)] < Qmin2)) Qmin2 = t_Qij[mat->n_otu*i+(*y)];
}
*score = FABS(Qmin2 - Qmin)/FABS(Qmin);
Free(t_Qij);
/* Free(ties); */
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void Compute_Sx(matrix *mat)
{
int i,j;
For(i,mat->n_otu)
{
mat->dist[i][i] = .0;
if(mat->on_off[i])
{
For(j,mat->n_otu)
{
if((i != j) && (mat->on_off[j]))
{
mat->dist[i][i] += Dist(mat,i,j);
}
}
}
}
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
phydbl Sum_S(matrix *mat, int i)
{
return mat->dist[i][i];
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
phydbl Dist(matrix *mat, int x, int y)
{
if(x > y)
return(mat->dist[x][y]);
else
return(mat->dist[y][x]);
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
phydbl Variance(matrix *mat, int x, int y)
{
if(x > y)
{
return(mat->dist[y][x]);
}
else
{
return(mat->dist[x][y]);
}
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
phydbl Br_Length(matrix *mat, int x, int y)
{
return .5*(Dist(mat,x,y)+
(Sum_S(mat,x)-Sum_S(mat,y))/(phydbl)(mat->r-2.));
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
phydbl Dist_Red(matrix *mat, int x, phydbl lx, int y, phydbl ly, int i, phydbl lamda)
{
phydbl Dui;
Dui=lamda*(Dist(mat,x,i)-lx)
+(1.-lamda)*(Dist(mat,y,i)-ly);
return(Dui);
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
phydbl Var_Red(matrix *mat, int x, int y, int i, phydbl lamda, phydbl vxy)
{
phydbl Vui;
Vui=lamda*(Variance(mat,x,i))
+(1.-lamda)*(Variance(mat,y,i))
-lamda*(1.-lamda)*vxy;
return(Vui);
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
phydbl Lamda(matrix *mat, int x, int y, phydbl vxy)
{
phydbl lamda=0.0;
int i;
if(mat->method == 0) /* NJ (Saitou & Nei, 1987) */
lamda = 0.5;
else /* BioNJ (Gascuel, 1997) */
{
if(vxy < SMALL && vxy > -SMALL)
lamda=0.5;
else
{
For(i,mat->n_otu)
{
if((x != i) && (y != i) && (mat->on_off[i]))
lamda = lamda + Variance(mat,y,i) - Variance(mat,x,i);
}
lamda = 0.5 + lamda/(2.*(mat->r-2)*vxy);
}
if(lamda > 1.0)
lamda = 0.5;/*1.0;*/
else if(lamda < 0.0)
lamda = 0.5;/*0.0;*/
}
return(lamda);
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
phydbl Q_Agglo(matrix *mat, int x, int y)
{
phydbl Qxy;
Qxy = .0;
Qxy=(mat->r-2.)*Dist(mat,x,y)-Sum_S(mat,x)-Sum_S(mat,y);
return(Qxy);
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void Bionj_Br_Length(matrix *mat)
{
int x;
x = Bionj_Br_Length_Post(mat->tree->t_nodes[0],
mat->tree->t_nodes[0]->v[0],
mat);
mat->tree->t_nodes[0]->b[0]->l = Dist(mat,0,x);
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
int Bionj_Br_Length_Post(t_node *a, t_node *d, matrix *mat)
{
int i;
if(d->tax)
{
return d->num;
}
else
{
int d_v1, d_v2;
phydbl lx, ly, vxy,lamda;
int x,y;
d_v1 = d_v2 = -1;
For(i,3)
if(d->v[i] != a) {(d_v1 < 0)?(d_v1 = i):(d_v2 = i);}
x = Bionj_Br_Length_Post(d,d->v[d_v1],mat);
y = Bionj_Br_Length_Post(d,d->v[d_v2],mat);
vxy = .0;
Compute_Sx(mat);
vxy=Variance(mat,(x),(y));
lx=Br_Length(mat,(x),(y));
ly=Br_Length(mat,(y),(x));
lamda=Lamda(mat,(x),(y),vxy);
Update_Mat(mat,(x),(y),lx,ly,vxy,lamda);
d->b[d_v1]->l = lx;
d->b[d_v2]->l = ly;
mat->on_off[y] = 0;
mat->r--;
return x;
}
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
phyml-20120412/src/help.c 0000644 0001750 0001750 00000035714 11636521315 011721 0000000 0000000 /*
PhyML: a program that computes maximum likelihood phylogenies from
DNA or AA homologous sequences.
Copyright (C) Stephane Guindon. Oct 2003 onward.
All parts of the source except where indicated are distributed under
the GNU public licence. See http://www.opensource.org for details.
*/
#include "help.h"
/* int T_MAX_FILE; */
/* phydbl SMALL; */
/* phydbl UNLIKELY; */
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void Usage()
{
char *BOLD=(char *)mCalloc(10,sizeof(char));
char *FLAT=(char *)mCalloc(10,sizeof(char));
char *LINE=(char *)mCalloc(10,sizeof(char));
char *cha;
cha =getenv("OS");
if(cha!=NULL)
{
strcpy(BOLD, "");
strcpy(FLAT, "");
strcpy(LINE, "");
}
else
{
strcpy(BOLD, "\033[00;01m");
strcpy(FLAT, "\033[00;00m");
strcpy(LINE, "\033[00;04m");
}
#ifdef PHYML
PhyML_Printf("%sNAME\n"
"%s\t- PhyML %s - \n\n"
"%s\t\''A simple, fast, and accurate algorithm to estimate\n"
"%s\tlarge phylogenies by maximum likelihood\''\n\n"
"%s\tStephane Guindon and Olivier Gascuel,\n"
"%s\tSystematic Biology 52(5):696-704, 2003.\n\n"
"%s\tPlease cite this paper if you use this software in your publications.\n",BOLD,FLAT,VERSION,FLAT,FLAT,FLAT,FLAT,FLAT);
#endif
#ifdef PHYTIME
PhyML_Printf("%sNAME\n"
"%s\t- PhyTime %s - \n\n"
"%s\t'Bayesian estimation of divergence times from large sequence alignments.'\n"
"%s\tStephane Guindon,\n"
"%s\tMolecular Biology and Evolution 27(8):1768-81, 2010.\n\n"
"%s\tPlease cite this paper if you use this software in your publications.\n",BOLD,FLAT,VERSION,FLAT,FLAT,FLAT,FLAT,FLAT);
#endif
#ifdef PHYML
PhyML_Printf("%s\nSYNOPSIS:\n\n"
"%s\tphyml %s[command args]\n",BOLD,BOLD,BOLD);
#endif
#ifdef PHYTIME
PhyML_Printf("%s\nSYNOPSIS:\n\n"
"%s\tphytime %s[command args]\n",BOLD,BOLD,BOLD);
#endif
#ifdef PHYML
PhyML_Printf("%s\n\tAll the options below are optional (except '%s-i%s' if you want to use the command-line interface).\n\n",FLAT,BOLD,FLAT);
#endif
#ifdef PHYTIME
PhyML_Printf("%s\n\tAll the options below are optional except '%s-i%s','%s-u%s' and '%s--calibration%s'.\n\n",FLAT,BOLD,FLAT,BOLD,FLAT,BOLD,FLAT);
#endif
PhyML_Printf("%s\nCommand options:\n%s",BOLD,FLAT);
PhyML_Printf("\n\t%s-i (or --input) %sseq_file_name%s\n",BOLD,LINE,FLAT);
PhyML_Printf("\t\t%sseq_file_name%s is the name of the nucleotide or amino-acid sequence file in PHYLIP format.\n",LINE,FLAT);
PhyML_Printf("\n");
PhyML_Printf("%s\n\t-d (or --datatype) ""%sdata_type%s\n",BOLD,LINE,FLAT);
PhyML_Printf("\t\t%sdata_type%s is 'nt' for nucleotide (default), 'aa' for amino-acid sequences, or 'generic',\n",LINE,FLAT);
PhyML_Printf("\t\t(use NEXUS file format and the 'symbols' parameter here).\n");
PhyML_Printf("\n");
PhyML_Printf("%s\n\t-q (or --sequential)\n",BOLD);
PhyML_Printf("%s\t\tChanges interleaved format (default) to sequential format.\n",FLAT);
PhyML_Printf("\n");
#ifndef PHYTIME
PhyML_Printf("%s\n\t-n (or --multiple) ""%snb_data_sets%s\n",BOLD,LINE,FLAT);
PhyML_Printf("\t\t%snb_data_sets%s is an integer corresponding to the number of data sets to analyse.\n",LINE,FLAT);
PhyML_Printf("\n");
#endif
#ifndef PHYTIME
PhyML_Printf("%s\n\t-p (or --pars)%s\n",BOLD,FLAT);
PhyML_Printf("%s\t\tUse a minimum parsimony starting tree. This option is taken into account when the '-u' option\n",FLAT);
PhyML_Printf("%s\t\tis absent and when tree topology modifications are to be done.\n",FLAT);
PhyML_Printf("\n");
#endif
#ifndef PHYTIME
PhyML_Printf("%s\n\t-b (or --bootstrap) %sint%s\n",BOLD,LINE,FLAT);
PhyML_Printf("\t\t%sint%s > 0: %sint%s is the number of bootstrap replicates.\n",LINE,FLAT,LINE,FLAT);
PhyML_Printf("\t\t%sint%s = 0: neither approximate likelihood ratio test nor bootstrap values are computed.\n",LINE,FLAT);
PhyML_Printf("\t\t%sint%s = -1: approximate likelihood ratio test returning aLRT statistics.\n",LINE,FLAT);
PhyML_Printf("\t\t%sint%s = -2: approximate likelihood ratio test returning Chi2-based parametric branch supports.\n",LINE,FLAT);
/* PhyML_Printf("\t\t%sint%s = -3 : minimum of Chi2-based parametric and SH-like branch supports.\n",LINE,FLAT); */
PhyML_Printf("\t\t%sint%s = -4: (default) SH-like branch supports alone.\n",LINE,FLAT);
PhyML_Printf("\t\t%sint%s = -5: approximate Bayes branch supports.\n",LINE,FLAT);
PhyML_Printf("\n");
#endif
PhyML_Printf("%s\n\t-m (or --model) %smodel%s\n",BOLD,LINE,FLAT);
PhyML_Printf("\t\tmodel%s : substitution model name.\n",FLAT);
PhyML_Printf("\t\t%s- %sNucleotide%s-based models : %sHKY85%s (default) | %sJC69%s | %sK80%s | %sF81%s | %sF84%s | %sTN93%s | %sGTR%s | %scustom (*)%s\n",
FLAT,LINE,FLAT,LINE,FLAT,LINE,FLAT,LINE,FLAT,LINE,FLAT,LINE,FLAT,LINE,FLAT,LINE,FLAT,LINE,FLAT);
PhyML_Printf("\t\t(*) : for the custom option, a string of six digits identifies the model. For instance, 000000\n");
PhyML_Printf("\t\t corresponds to F81 (or JC69 provided the distribution of nucleotide frequencies is uniform).\n");
PhyML_Printf("\t\t 012345 corresponds to GTR. This option can be used for encoding any model that is a nested within GTR.\n");
PhyML_Printf("\n");
PhyML_Printf("\t\t%s- %sAmino-acid%s based models : %sLG%s (default) | %sWAG%s | %sJTT%s | %sMtREV%s | %sDayhoff%s | %sDCMut%s | %sRtREV%s | %sCpREV%s | %sVT%s\n",
FLAT,LINE,FLAT,
LINE,FLAT,
LINE,FLAT,
LINE,FLAT,
LINE,FLAT,
LINE,FLAT,
LINE,FLAT,
LINE,FLAT,
LINE,FLAT,
LINE,FLAT);
PhyML_Printf("\t\t %sBlosum62%s | %sMtMam%s | %sMtArt%s | %sHIVw%s | %sHIVb%s | %scustom%s\n",
LINE,FLAT,
LINE,FLAT,
LINE,FLAT,
LINE,FLAT,
LINE,FLAT,
LINE,FLAT);
PhyML_Printf("\n");
PhyML_Printf("%s\n\t--aa_rate_file %sfilename%s\n",BOLD,LINE,FLAT);
PhyML_Printf("\t\t%sfilename%s is the name of the file that provides the amino acid substitution rate matrix in PAML format.\n",LINE,FLAT);
PhyML_Printf("\t\tIt is compulsory to use this option when analysing amino acid sequences with the `custom' model.\n");
PhyML_Printf("\n");
#ifndef PHYTIME
PhyML_Printf("%s\n\t-f %se%s, %sm%s, or %sfA,fC,fG,fT%s\n",BOLD,LINE,BOLD,LINE,BOLD,LINE,FLAT);
PhyML_Printf("\t\t%se%s : the character frequencies are determined as follows : \n",LINE,FLAT);
PhyML_Printf("%s\t\t- %sNucleotide%s sequences: (Empirical) the equilibrium base frequencies are estimated by counting\n"
"\t\t the occurence of the different bases in the alignment.\n",FLAT,LINE,FLAT);
PhyML_Printf("%s\t\t- %sAmino-acid%s sequences: (Empirical) the equilibrium amino-acid frequencies are estimated by counting\n"
"\t\t the occurence of the different amino-acids in the alignment.\n",FLAT,LINE,FLAT);
PhyML_Printf("\n");
PhyML_Printf("\t\t%sm%s : the character frequencies are determined as follows : \n",LINE,FLAT);
PhyML_Printf("%s\t\t- %sNucleotide%s sequences: (ML) the equilibrium base frequencies are estimated using maximum likelihood \n",FLAT,LINE,FLAT);
PhyML_Printf("%s\t\t- %sAmino-acid%s sequences: (Model) the equilibrium amino-acid frequencies are estimated using\n"
"\t\t the frequencies defined by the substitution model.\n",FLAT,LINE,FLAT);
PhyML_Printf("\n");
PhyML_Printf("\t\t%s\"fA,fC,fG,fT\"%s : only valid for nucleotide-based models. fA, fC, fG and fT are floating numbers that \n",LINE,FLAT);
PhyML_Printf("\t\t correspond to the frequencies of A, C, G and T respectively (WARNING: do not use any blank space between\n");
PhyML_Printf("\t\t your values of nucleotide frequencies, only commas!)\n");
PhyML_Printf("\n");
#endif
#ifdef PHYTIME
PhyML_Printf("%s\n\t--calibration %sfilename%s\n",BOLD,LINE,FLAT);
PhyML_Printf("\t\t%sfilename%s is the name of the calibration file that provides a priori defined boundaries for node ages.\n",LINE,FLAT);
PhyML_Printf("\t\tPlease read the manual for more information about the format of this file.\n");
PhyML_Printf("\n");
#endif
PhyML_Printf("%s\n\t-t (or --ts/tv) %sts/tv_ratio%s\n",BOLD,LINE,FLAT);
PhyML_Printf("\t\tts/tv_ratio%s : transition/transversion ratio. DNA sequences only.\n",FLAT);
PhyML_Printf("\t\tCan be a fixed positive value (ex:4.0) or %se%s to get the maximum likelihood estimate.\n",LINE,FLAT);
PhyML_Printf("\n");
PhyML_Printf("%s\n\t-v (or --pinv) %sprop_invar%s\n",BOLD,LINE,FLAT);
PhyML_Printf("\t\tprop_invar%s : proportion of invariable sites.\n",FLAT);
PhyML_Printf("\t\tCan be a fixed value in the [0,1] range or %se%s to get the maximum likelihood estimate.\n",LINE,FLAT);
PhyML_Printf("\n");
PhyML_Printf("%s\n\t-c (or --nclasses) %snb_subst_cat%s\n",BOLD,LINE,FLAT);
PhyML_Printf("\t\tnb_subst_cat%s : number of relative substitution rate categories. Default : %snb_subst_cat%s=4.\n",
FLAT,LINE,FLAT);
PhyML_Printf("\t\tMust be a positive integer.\n");
PhyML_Printf("\n");
PhyML_Printf("%s\n\t-a (or --alpha) %sgamma%s\n",BOLD,LINE,FLAT);
PhyML_Printf("\t\tgamma%s : distribution of the gamma distribution shape parameter.\n",FLAT);
PhyML_Printf("\t\tCan be a fixed positive value or %se%s to get the maximum likelihood estimate.\n",LINE,FLAT);
PhyML_Printf("\n");
#ifndef PHYTIME
PhyML_Printf("%s\n\t-s (or --search) %smove%s\n",BOLD,LINE,FLAT);
PhyML_Printf("\t\tTree topology search operation option.\n");
PhyML_Printf("\t\tCan be either %sNNI%s (default, fast) or %sSPR%s (a bit slower than NNI) or %sBEST%s (best of NNI and SPR search).\n",LINE,FLAT,LINE,FLAT,LINE,FLAT);
PhyML_Printf("\n");
#endif
PhyML_Printf("%s\n\t-u (or --inputtree) %suser_tree_file%s\n",BOLD,LINE,FLAT);
PhyML_Printf("\t\tuser_tree_file%s : starting tree filename. The tree must be in Newick format.\n",FLAT);
PhyML_Printf("\n");
#ifndef PHYTIME
PhyML_Printf("%s\n\t-o %sparams%s\n",BOLD,LINE,FLAT);
PhyML_Printf("\t\tThis option focuses on specific parameter optimisation.\n");
PhyML_Printf("\t\t%sparams%s=tlr : tree topology (t), branch length (l) and rate parameters (r) are optimised.\n",LINE,FLAT);
PhyML_Printf("\t\t%sparams%s=tl : tree topology and branch length are optimised.\n",LINE,FLAT);
PhyML_Printf("\t\t%sparams%s=lr : branch length and rate parameters are optimised.\n",LINE,FLAT);
PhyML_Printf("\t\t%sparams%s=l : branch length are optimised.\n",LINE,FLAT);
PhyML_Printf("\t\t%sparams%s=r : rate parameters are optimised.\n",LINE,FLAT);
PhyML_Printf("\t\t%sparams%s=n : no parameter is optimised.\n",LINE,FLAT);
PhyML_Printf("\n");
#endif
#ifndef PHYTIME
PhyML_Printf("%s\n\t--rand_start%s\n",BOLD,FLAT);
PhyML_Printf("\t\tThis option sets the initial tree to random.\n");
PhyML_Printf("\t\tIt is only valid if SPR searches are to be performed.\n");
PhyML_Printf("\n");
#endif
#ifndef PHYTIME
PhyML_Printf("%s\n\t--n_rand_starts %snum%s\n",BOLD,LINE,FLAT);
PhyML_Printf("\t\tnum%s is the number of initial random trees to be used.\n",FLAT);
PhyML_Printf("\t\tIt is only valid if SPR searches are to be performed.\n");
PhyML_Printf("\n");
#endif
PhyML_Printf("%s\n\t--r_seed %snum%s\n",BOLD,LINE,FLAT);
PhyML_Printf("\t\tnum%s is the seed used to initiate the random number generator.\n",FLAT);
PhyML_Printf("\t\tMust be an integer.\n");
PhyML_Printf("\n");
#ifndef PHYTIME
PhyML_Printf("%s\n\t--print_site_lnl%s\n",BOLD,FLAT);
PhyML_Printf("\t\t%sPrint the likelihood for each site in file *_phyml_lk.txt.\n",FLAT);
PhyML_Printf("\n");
#endif
#ifndef PHYTIME
PhyML_Printf("%s\n\t--print_trace%s\n",BOLD,FLAT);
PhyML_Printf("\t\t%sPrint each phylogeny explored during the tree search process\n",FLAT);
PhyML_Printf("\t\t%sin file *_phyml_trace.txt.\n",FLAT);
PhyML_Printf("\n");
#endif
PhyML_Printf("%s\n\t--run_id %sID_string%s\n",BOLD,LINE,FLAT);
PhyML_Printf("\t\t%sAppend the string %sID_string%s at the end of each PhyML output file.\n",FLAT,LINE,FLAT);
PhyML_Printf("\t\t%sThis option may be useful when running simulations involving PhyML.\n",FLAT);
PhyML_Printf("\n");
PhyML_Printf("%s\n\t--quiet%s\n",BOLD,FLAT);
PhyML_Printf("\t\t%sNo interactive question (for running in batch mode) and quiet output.\n",FLAT);
PhyML_Printf("\n");
PhyML_Printf("%s\n\t--no_memory_check%s\n",BOLD,FLAT);
PhyML_Printf("\t\t%sNo interactive question for memory usage (for running in batch mode). Normal ouput otherwise.\n",FLAT);
PhyML_Printf("\n");
#ifndef PHYTIME
PhyML_Printf("%s\n\t--alias_subpatt%s\n",BOLD,FLAT);
PhyML_Printf("\t\t%sSite aliasing is generalized at the subtree level. Sometimes lead to faster calculations.\n",FLAT);
PhyML_Printf("\t\t%sSee Kosakovsky Pond SL, Muse SV, Sytematic Biology (2004) for an example.\n",FLAT);
PhyML_Printf("\n");
#endif
#ifndef PHYTIME
PhyML_Printf("%s\n\t--boot_progress_display %snum%s (default=20)\n",BOLD,LINE,FLAT);
PhyML_Printf("\t\t%snum%s is the frequency at which the bootstrap progress bar will be updated.\n",LINE,FLAT);
PhyML_Printf("\t\tMust be an integer.\n");
PhyML_Printf("\n");
#endif
#ifdef PHYTIME
PhyML_Printf("%s\n\t--chain_len %snum%s\n",BOLD,LINE,FLAT);
PhyML_Printf("\t\t%snum%s is the number of generations or runs of the Markov Chain Monte Carlo. Set to 1E+6 by default. \n",LINE,FLAT);
PhyML_Printf("\t\tMust be an integer.\n");
PhyML_Printf("\n");
#endif
/* #ifdef PHYTIME */
/* PhyML_Printf("%s\n\t--burnin %snum%s\n",BOLD,LINE,FLAT); */
/* PhyML_Printf("\t\t%snum%s is the number of generations of runs of the Markov Chain Monte Carlo during the 'burnin' period.\n",LINE,FLAT); */
/* PhyML_Printf("\t\t%sSet to 1E+5 by default. Must be an integer. \n",FLAT); */
/* PhyML_Printf("\n"); */
/* #endif */
#ifdef PHYTIME
PhyML_Printf("%s\n\t--sample_freq %snum%s\n",BOLD,LINE,FLAT);
PhyML_Printf("\t\tThe chain is sampled every %snum%s generations. Set to 1E+3 by default. \n",LINE,FLAT);
PhyML_Printf("\t\tMust be an integer.\n");
PhyML_Printf("\n");
#endif
#ifdef PHYTIME
PhyML_Printf("%s\n\t--no_data%s\n",BOLD,FLAT);
PhyML_Printf("\t\tUse this option to sample from the priors only (rather from the posterior joint density\n");
PhyML_Printf("\t\tof the model parameters).\n");
PhyML_Printf("\n");
#endif
#ifdef PHYTIME
PhyML_Printf("%s\n\t--fastlk%s\n",BOLD,FLAT);
PhyML_Printf("\t\tUse the multivariate normal approximation to the likelihood and speed up calculations\n");
PhyML_Printf("\n");
#endif
#ifdef PHYML
PhyML_Printf("%sPHYLIP-LIKE INTERFACE\n""%s\n\tYou can also use PhyML with no argument, in this case change the value of\n",BOLD,FLAT);
PhyML_Printf("%s\ta parameter by typing its corresponding character as shown on screen.\n\n",FLAT);
#endif
#ifdef PHYML
PhyML_Printf("%sEXAMPLES\n\n"
"%s\tDNA interleaved sequence file, default parameters : ""%s ./phyml -i seqs1"
"%s\n\tAA interleaved sequence file, default parameters : ""%s ./phyml -i seqs2 -d aa"
"%s\n\tAA sequential sequence file, with customization : ""%s ./phyml -i seqs3 -q -d aa -m JTT -c 4 -a e%s\n",BOLD,FLAT,BOLD,FLAT,BOLD,FLAT,BOLD,FLAT);
#endif
Exit("");
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
phyml-20120412/src/alrt.h 0000644 0001750 0001750 00000001663 11637265457 011751 0000000 0000000 /*
PHYML : a program that computes maximum likelihood phylogenies from
DNA or AA homologous sequences
Copyright (C) Stephane Guindon. Oct 2003 onward
All parts of the source except where indicated are distributed under
the GNU public licence. See http://www.opensource.org for details.
*/
#include
#ifndef ALRT_H
#define ALRT_H
#include "utilities.h"
#include "lk.h"
#include "optimiz.h"
#include "models.h"
#include "free.h"
#include "simu.h"
void aLRT(t_tree *tree);
int Check_NNI_Five_Branches(t_tree *tree);
int Compute_Likelihood_Ratio_Test(t_edge *tested_edge, t_tree *tree);
int NNI_Neigh_BL(t_edge *b_fcus, t_tree *tree);
void Make_Target_Swap(t_tree *tree, t_edge *b_fcus, int swaptodo);
phydbl Statistics_To_Probabilities(phydbl in);
phydbl Statistics_To_RELL(t_tree *tree);
phydbl Statistics_To_SH(t_tree *tree);
phydbl Update_Lk_At_Given_Edge_Excluding(t_edge *b_fcus, t_tree *tree, t_node *exclude);
#endif
phyml-20120412/src/stats.h 0000644 0001750 0001750 00000011565 11637265675 012151 0000000 0000000 /*
PhyML: a program that computes maximum likelihood phylogenies from
DNA or AA homologous sequences.
Copyright (C) Stephane Guindon. Oct 2003 onward.
All parts of the source except where indicated are distributed under
the GNU public licence. See http://www.opensource.org for details.
*/
#include
#ifndef STATS_H
#define STATS_H
#include "utilities.h"
#include "free.h"
#include "lk.h"
#include "optimiz.h"
#include "models.h"
#include "eigen.h"
phydbl *Covariance_Matrix(t_tree *tree);
phydbl *Hessian(t_tree *tree);
void Recurr_Hessian(t_node *a, t_node *b, int plus_minus, phydbl *inc, phydbl *res, int *is_ok, t_tree *tree);
phydbl stdnormal_inv(phydbl p);
phydbl Uni();
int Rand_Int(int min, int max);
phydbl Ahrensdietergamma(phydbl alpha);
phydbl Rgamma(phydbl shape, phydbl scale);
phydbl Rexp(phydbl lambda);
phydbl Bico(int n, int k);
phydbl Factln(int n);
phydbl Gammln(phydbl xx);
phydbl Pbinom(int N, int ni, phydbl p);
phydbl LnGamma (phydbl alpha);
phydbl IncompleteGamma(phydbl x, phydbl alpha, phydbl ln_gamma_alpha);
phydbl PointChi2 (phydbl prob, phydbl v);
phydbl Bivariate_Normal_Density(phydbl x, phydbl y, phydbl mux, phydbl muy, phydbl sdx, phydbl sdy, phydbl rho);
phydbl PointNormal (phydbl prob);
int DiscreteGamma (phydbl freqK[], phydbl rK[],phydbl alfa, phydbl beta, int K, int median);
phydbl Pnorm(phydbl x, phydbl mean, phydbl var);
phydbl Dnorm_Moments(phydbl x, phydbl mean, phydbl var);
phydbl Dnorm(phydbl x, phydbl mean, phydbl sd);
phydbl Pgamma(phydbl x, phydbl shape, phydbl scale);
phydbl Dgamma_Moments(phydbl x, phydbl mean, phydbl var);
phydbl Dgamma(phydbl x, phydbl shape, phydbl scale);
phydbl LnFact(int n);
int Choose(int n, int k);
phydbl Ppois(phydbl x, phydbl param);
phydbl Dexp(phydbl x, phydbl param);
phydbl Dpois(phydbl x, phydbl param);
phydbl Rand_Normal_Deviate(phydbl mean, phydbl sd);
phydbl Rnorm(phydbl mean, phydbl sd);
phydbl *Rnorm_Multid(phydbl *mu, phydbl *cov, int dim);
phydbl Rnorm_Trunc(phydbl mean, phydbl sd, phydbl min, phydbl max, int *err);
phydbl *Rnorm_Multid_Trunc(phydbl *mean, phydbl *cov, phydbl *min, phydbl *max, int dim);
phydbl *Hessian_Log(t_tree *tree);
void Recurr_Hessian_Log(t_node *a, t_node *d, int plus_minus, phydbl *inc, phydbl *res, int *is_ok, t_tree *tree);
phydbl Log_Det(int *is_ok, t_tree *tree);
phydbl Dnorm_Trunc(phydbl x, phydbl mean, phydbl sd, phydbl lo, phydbl up);
phydbl Normal_Trunc_Mean(phydbl mu, phydbl sd, phydbl min, phydbl max);
phydbl Constraint_Normal_Trunc_Mean(phydbl wanted_mu, phydbl sd, phydbl min, phydbl max);
phydbl Dnorm_Multi(phydbl *x, phydbl *mu, phydbl *cov, int size, int _log);
phydbl Dnorm_Multi_Given_InvCov_Det(phydbl *x, phydbl *mu, phydbl *invcov, phydbl det, int size, int _log);
phydbl Prop_Log_Dnorm_Multi_Given_InvCov_Det(phydbl *x, phydbl *mu, phydbl *invcov, phydbl det, int size);
phydbl Log_Dnorm(phydbl x, phydbl mean, phydbl sd, int *err);
phydbl tt800();
phydbl Pnorm_Ihaka_Derived_From_Cody(phydbl x);
int Matinv(phydbl *x, int n, int m, int verbose);
phydbl *Matrix_Mult(phydbl *A, phydbl *B, int nra, int nca, int nrb, int ncb);
phydbl *Matrix_Transpose(phydbl *A, int dim);
void Normal_Conditional(phydbl *mu, phydbl *cov, phydbl *a, int n, short int *is_1, int n1, phydbl *cond_mu, phydbl *cond_var);
void Normal_Conditional_Unsorted(phydbl *mu, phydbl *cov, phydbl *a, int n, short int *is_1, int n1, phydbl *cond_mu, phydbl *cond_cov);
phydbl Matrix_Det(phydbl *A, int size, int _log);
void Get_Reg_Coeff(phydbl *mu, phydbl *cov, phydbl *a, int n, short int *is_1, int n1, phydbl *reg_coeff);
phydbl Rnorm_Trunc_Inverse(phydbl mean, phydbl sd, phydbl min, phydbl max, int *error);
phydbl Norm_Trunc_Sd(phydbl mu, phydbl sd, phydbl a, phydbl b);
phydbl Norm_Trunc_Mean(phydbl mu, phydbl sd, phydbl a, phydbl b);
int Norm_Trunc_Mean_Sd(phydbl mu, phydbl sd, phydbl a, phydbl b, phydbl *trunc_mu, phydbl *trunc_sd);
phydbl Log_Dnorm_Trunc(phydbl x, phydbl mean, phydbl sd, phydbl lo, phydbl up, int *err);
phydbl Pnorm_Marsaglia(phydbl x);
int Iter_Matinv(phydbl *x, int n, int m, int verbose);
phydbl Dorder_Unif(phydbl x, int r, int n, phydbl min, phydbl max);
phydbl Covariance(phydbl *x, phydbl *y, int n);
phydbl *Rnorm_Multid_Trunc_Constraint(phydbl *mu, phydbl *cov, phydbl *min, phydbl *max, phydbl *lambda, phydbl k, phydbl *res, int len);
phydbl *Gradient(t_tree *tree);
phydbl *Hessian_Seo(t_tree *tree);
void Integrated_Brownian_Bridge_Moments(phydbl x_beg, phydbl x_end,
phydbl y_beg, phydbl y_end,
phydbl sd, phydbl *mean, phydbl *var);
void PMat_MGF_Gamma(phydbl *Pij, phydbl shape, phydbl scale, phydbl scaling_fact, model *mod);
void Integrated_Geometric_Brownian_Bridge_Moments(phydbl T, phydbl A, phydbl B, phydbl u, phydbl *mean, phydbl *var);
void Integrated_Geometric_Brownian_Bridge_Mean(phydbl T, phydbl A, phydbl B, phydbl u, phydbl *mean);
void Integrated_Geometric_Brownian_Bridge_Var(phydbl T, phydbl A, phydbl B, phydbl u, phydbl *mean);
#endif
phyml-20120412/src/spr.c 0000644 0001750 0001750 00000340523 11737136654 011604 0000000 0000000 /*
PhyML: a program that computes maximum likelihood phyLOGenies from
DNA or AA homoLOGous sequences.
Copyright (C) Stephane Guindon. Oct 2003 onward.
All parts of the source except where indicated are distributed under
the GNU public licence. See http://www.opensource.org for details.
*/
/*
** spr.c: Routines for performing SPR moves on the tree.
**
** Wim Hordijk Last modified: 28 August 2006
** Stephane Guindon 2007
*/
#include "spr.h"
/*
** BIG: Some big number.
*/
/* #define BIG 1e05 */
/*
** Global vars.
**
** - cur_lk: The current likelihood of the tree.
** - subtree_dist: The average subtree distances matrix.
** - seq_dist: The sequence distance matrix.
** - optim_cand: Array for holding candidate moves for local and global branch
** length optimization.
** - rgrft_cand: Array for holding candidate regraft positions.
** - v_tmp: The central t_node of the temporary regraft structure for
** estimating changes in likelihood.
** - path: The path through the tree during the recursive tree length
** calculation.
** - sum_scale_tmp Array for temporarily storing scaling factors.
** - p_lk_tmp: Temporary partial likelihood storage.
** - e_brent: A temporary t_edge to use for estimating distances using Brent.
** - tree->mod->s_opt->wim_n_rgrft: Number of promising regraft positions to consider when
performing all improving SPR moves.
** - tree->mod->s_opt->wim_n_optim: Number of candidate moves on which to perform local branch
length optimization.
** - tree->mod->s_opt->wim_max_dist: Maximum regraft distance to consider.
** - tree->mod->s_opt->wim_n_globl: Number of candidates moves on which to perform global branch
length optimization.
** - tree->mod->s_opt->wim_n_best: Number of promising regraft positions to consider when
performing only the best SPR move.
** - nr_d_l: Total number of change in tree length calculations done.
** - nr_d_lk: Total number of change in likelihood calculations done.
** - nr_loc: Total number of local branch length optimizations done.
** - nr_glb: Total number of global branch length optimizations done.
*/
phydbl cur_lk, **subtree_dist, *sum_scale_tmp, *p_lk_tmp;
matrix *seq_dist;
_move_ **optim_cand, **rgrft_cand;
t_node *v_tmp=NULL, **path;
t_edge *e_brent=NULL;
int nr_d_L, nr_d_lk, nr_loc, nr_glb;
/*
** Init_SPR: Initialize the SPR algorithm: allocate memory and set variables.
**
** Parameters:
** - tree: The current tree to use for initialization.
*/
void Init_SPR (t_tree *tree)
{
int i, nr_nodes, nr_edges;
t_node *u_0, *u_1, *u_2;
/*
** Get the SPR parameter values.
*/
nr_edges = 2*tree->n_otu-3;
if(tree->mod->s_opt->wim_n_rgrft < 0) tree->mod->s_opt->wim_n_rgrft = 1 + nr_edges / 5;
if(tree->mod->s_opt->wim_n_globl < 0) tree->mod->s_opt->wim_n_globl = 1 + nr_edges / 10;
if(tree->mod->s_opt->wim_max_dist < 0) tree->mod->s_opt->wim_max_dist = 1 + nr_edges / 10;
if(tree->mod->s_opt->wim_n_optim < 0) tree->mod->s_opt->wim_n_optim = 100;
if(tree->mod->s_opt->wim_n_best < 0) tree->mod->s_opt->wim_n_best = tree->mod->s_opt->wim_n_rgrft; /* can't
* be
* anything else
*/
/*
** If it doesn't exist yet, create the temporary regraft structure:
** a central t_node with three edges and tip nodes adjacent to it.
*/
if (v_tmp == NULL)
{
v_tmp=Make_Node_Light(0);
v_tmp->tax = 0;
u_0=Make_Node_Light(1);
u_0->tax = 1;
u_1=Make_Node_Light(2);
u_1->tax = 1;
u_2=Make_Node_Light(3);
u_2->tax = 1;
v_tmp->v[0] = u_0;
v_tmp->v[1] = u_1;
v_tmp->v[2] = u_2;
u_0->v[0] = v_tmp;
u_1->v[0] = v_tmp;
u_2->v[0] = v_tmp;
t_edge *edge_0 = Make_Edge_Light (v_tmp, u_0, 0);
Make_Edge_Lk (edge_0, tree);
t_edge *edge_1 = Make_Edge_Light (v_tmp, u_1,1);
Make_Edge_Lk (edge_1, tree);
t_edge *edge_2 = Make_Edge_Light (v_tmp, u_2,2);
Make_Edge_Lk (edge_2, tree);
/* For(i,tree->data->crunch_len) */
/* { */
/* For(j,tree->mod->n_catg) */
/* { */
/* Free(edge_0->p_lk_rght[i][j]); */
/* } */
/* Free(edge_0->p_lk_rght[i]); */
/* } */
Free(edge_0->p_lk_rght);
if(!edge_0->rght->tax) Free(edge_0->sum_scale_rght);
/* For(i,tree->data->crunch_len) */
/* { */
/* For(j,tree->mod->n_catg) */
/* { */
/* Free(edge_1->p_lk_rght[i][j]); */
/* } */
/* Free(edge_1->p_lk_rght[i]); */
/* } */
Free(edge_1->p_lk_rght);
if(!edge_1->rght->tax) Free(edge_1->sum_scale_rght);
/* For(i,tree->data->crunch_len) */
/* { */
/* For(j,tree->mod->n_catg) */
/* { */
/* Free(edge_2->p_lk_rght[i][j]); */
/* } */
/* Free(edge_2->p_lk_rght[i]); */
/* } */
Free(edge_2->p_lk_rght);
if(!edge_2->rght->tax) Free(edge_2->sum_scale_rght);
}
/*
** If it doesn't exist yet, create the temporary edge.
*/
if (e_brent == NULL)
{
u_1=Make_Node_Light(4);
u_1->tax = 1;
u_2=Make_Node_Light(5);
u_2->tax = 1;
u_1->v[0] = u_2;
u_2->v[0] = u_1;
t_edge *edge_4 = Make_Edge_Light (u_1, u_2, 3);
Make_Edge_Lk (edge_4, tree);
e_brent = u_1->b[0];
/* For(i,tree->data->crunch_len) */
/* { */
/* For(j,tree->mod->n_catg) */
/* { */
/* Free(edge_4->p_lk_rght[i][j]); */
/* } */
/* Free(edge_4->p_lk_rght[i]); */
/* } */
Free(edge_4->p_lk_rght);
if(!edge_4->rght->tax) Free(edge_4->sum_scale_rght);
/* For(i,tree->data->crunch_len) */
/* { */
/* For(j,tree->mod->n_catg) */
/* { */
/* Free(edge_4->p_lk_left[i][j]); */
/* } */
/* Free(edge_4->p_lk_left[i]); */
/* } */
Free(edge_4->p_lk_left);
if(!edge_4->left->tax) Free(edge_4->sum_scale_left);
}
/*
** Allocate memory for temporarily storing partial likelihoods and
** scaling factors.
*/
p_lk_tmp = (phydbl *)mCalloc (tree->n_pattern*tree->mod->n_catg*tree->mod->ns, sizeof (phydbl));
/* p_lk_tmp = (phydbl ***)mCalloc (tree->n_pattern, sizeof (phydbl **)); */
/* for (i = 0; i < tree->n_pattern; i++) */
/* { */
/* p_lk_tmp[i] = (phydbl **)mCalloc (tree->mod->n_catg, sizeof (phydbl *)); */
/* for (j = 0; j < tree->mod->n_catg; j++) */
/* { */
/* p_lk_tmp[i][j] = (phydbl *)mCalloc (tree->mod->ns, sizeof (phydbl)); */
/* } */
/* } */
sum_scale_tmp = (phydbl *)mCalloc (tree->n_pattern, sizeof (phydbl));
/*
** Allocate memory for storing the average subtree distances.
*/
nr_nodes = 2*tree->n_otu-2;
subtree_dist = (phydbl **)malloc (nr_nodes * sizeof (phydbl *));
for (i = 0; i < nr_nodes; i++)
{
subtree_dist[i] = (phydbl *)malloc (nr_nodes * sizeof (phydbl));
}
/*
** Allocate memory for storing the candidate regraft positions and
** t_edge length optimization moves.
*/
rgrft_cand = (_move_ **)malloc (MAX(tree->mod->s_opt->wim_n_rgrft,tree->mod->s_opt->wim_n_best) * sizeof (_move_ *));
for (i = 0; i < MAX(tree->mod->s_opt->wim_n_rgrft,tree->mod->s_opt->wim_n_best); i++)
{
rgrft_cand[i] = (_move_ *)malloc (sizeof (_move_));
rgrft_cand[i]->path = (t_node **)malloc ((tree->mod->s_opt->wim_max_dist+2) * sizeof (t_node *));
}
optim_cand = (_move_ **)malloc (tree->mod->s_opt->wim_n_optim * sizeof (_move_ *));
for (i = 0; i < tree->mod->s_opt->wim_n_optim; i++)
{
optim_cand[i] = (_move_ *)malloc (sizeof (_move_));
optim_cand[i]->path = (t_node **)malloc ((tree->mod->s_opt->wim_max_dist+2) * sizeof (t_node *));
}
path = (t_node **)malloc ((tree->mod->s_opt->wim_max_dist+2) * sizeof (t_node *));
if(!tree->mat)
{
seq_dist = ML_Dist (tree->data, tree->mod);
tree->mat = seq_dist;
}
else
seq_dist = tree->mat;
/*
** Set variables.
*/
nr_d_L = 0;
nr_d_lk = 0;
nr_loc = 0;
nr_glb = 0;
}
/*
** Clean_SPR: Free up the used memory.
**
** Parameters:
** - tree: The current tree.
*/
void Clean_SPR (t_tree *tree)
{
int i;
/*
** Clean up the temporary regraft structure.
*/
Free_Node (v_tmp->v[0]);
Free_Node (v_tmp->v[1]);
Free_Node (v_tmp->v[2]);
v_tmp->b[0]->p_lk_rght = NULL;
Free_Edge_Lk (tree, v_tmp->b[0]);
Free_Edge (v_tmp->b[0]);
v_tmp->b[1]->p_lk_rght = NULL;
Free_Edge_Lk(tree, v_tmp->b[1]);
Free_Edge(v_tmp->b[1]);
v_tmp->b[2]->p_lk_rght = NULL;
Free_Edge_Lk (tree, v_tmp->b[2]);
Free_Edge (v_tmp->b[2]);
Free_Node (v_tmp);
v_tmp = NULL;
/*
** Clean up the temporary edge.
*/
Free_Node (e_brent->left);
Free_Node (e_brent->rght);
e_brent->p_lk_left = NULL;
e_brent->p_lk_rght = NULL;
Free_Edge_Lk (tree, e_brent);
Free_Edge (e_brent);
e_brent = NULL;
/*
** Free the temporary partial likelihood and scaling memory.
*/
/* for (i = 0; i < tree->n_pattern; i++) */
/* { */
/* for (j = 0; j < tree->mod->n_catg; j++) */
/* { */
/* free (p_lk_tmp[i][j]); */
/* } */
/* free (p_lk_tmp[i]); */
/* } */
free (p_lk_tmp);
free (sum_scale_tmp);
/*
** Free the subtree distance matrix.
*/
for (i = 0; i < 2*tree->n_otu - 2; i++)
{
free (subtree_dist[i]);
}
free (subtree_dist);
/*
** Free the arrays for storing the candidate regrafting positions and
** t_edge length optimization moves.
*/
for (i = 0; i < MAX(tree->mod->s_opt->wim_n_rgrft,tree->mod->s_opt->wim_n_best); i++)
{
free (rgrft_cand[i]->path);
free (rgrft_cand[i]);
}
free (rgrft_cand);
for (i = 0; i < tree->mod->s_opt->wim_n_optim; i++)
{
free (optim_cand[i]->path);
free (optim_cand[i]);
}
free (optim_cand);
free (path);
/*
** Print some statistics (for "research" purposes only).
*/
/* PhyML_Printf ("nr_d_L: %d\n", nr_d_L); */
/* PhyML_Printf ("nr_d_lk: %d\n", nr_d_lk); */
/* PhyML_Printf ("nr_loc: %d\n", nr_loc); */
/* PhyML_Printf ("nr_glb: %d\n", nr_glb); */
}
/*
** Optim_SPR: Optimize the tree using SPR moves.
**
** Parameters:
** - tree: The tree to optimize.
** - max_size: The maximum size (= number of taxa) of the subtrees to be
** pruned. If m=0 or m>ntax, all possible prunings will be
** considered.
** - method: The optimization method to use ("ALL" or "BEST").
*/
void Optim_SPR (t_tree *tree, int max_size, int method)
{
int nr_moves, improvement;
t_node *root;
if(tree->mod->s_opt->print) PhyML_Printf("\n\n. Starting SPR moves...\n");
/*
** Calculate the current likelihood value.
*/
tree->both_sides = 1;
cur_lk = Lk (tree);
time(&(tree->t_current));
if(tree->mod->s_opt->print) Print_Lk(tree,"topology");
/*
** Optimize all t_edge lengths and calculate the new likelihood value.
*/
/* PhyML_Printf("\n. Optimizing t_edge lengths."); */
root = tree->t_nodes[0];
Optimize_Br_Len_Serie (root, root->v[0], root->b[0], tree, tree->data);
tree->both_sides = 1;
cur_lk = Lk (tree);
time(&(tree->t_current));
if(tree->mod->s_opt->print) Print_Lk(tree,"topology");
/*
** While improvements were found, perform another round of SPR moves.
*/
nr_moves = 0;
improvement = 1;
while (improvement)
{
/*
** Perform one round of SPR moves.
*/
if (method == ALL)
{
improvement = Perform_SPR_Moves (tree, max_size);
}
else if (method == BEST)
{
improvement = Perform_Best_SPR (tree, max_size);
}
else if (method == ONE)
{
improvement = Perform_One_SPR (tree, max_size);
}
else
{
PhyML_Printf ("\n. Unknown SPR optimization method, bailing out...\n");
exit (1);
}
/* If an improvement was found, update statistics. */
if(improvement)
{
nr_moves++;
if((nr_moves == 1) || (nr_moves % 4 == 1))
{
/*
** Optimize model parameters.
*/
Optimiz_All_Free_Param (tree,(tree->io->quiet)?(0):(tree->mod->s_opt->print));
tree->both_sides = 1;
Lk(tree);
}
}
/* Beg SG 28 May 2007 */
if(method == BEST || method == ONE) break;
/* Beg SG 28 May 2007 */
}
if(tree->mod->s_opt->print) PhyML_Printf ("\n\n. Number of SPR moves: %d\n", nr_moves);
/*
** Perform a last round of optimization steps (for t_edge lengths).
*/
Round_Optimize(tree,tree->data,ROUND_MAX);
Check_NNI_Five_Branches(tree);
}
/*
** Perform_SPR_Moves: Perform a round of SPR moves on the tree. Prune each subtree in
** turn and calculate the change in tree length for each candidate
** regraft position. Estimate change in likelihood for the most
** promising moves, and perform all moves that result in an
** improvement. If no improvements were found at all, try local edge
** length optimization. If still no improvement, try global edge
** length optimization.
**
** Parameters:
** - tree: The tree to perform the SPR moves on.
** - max_size: The maximum size (= number of taxa) of the subtrees to be
** pruned. If m=0 or m>ntax, all possible prunings will be
** considered.
**
** Returns:
** If the current tree could be improved: 1.
** Otherwise: 0.
*/
int Perform_SPR_Moves (t_tree *tree, int max_size)
{
int nr_edges, i, j, candidate, improvement;
t_node *root, *v_prune;
t_edge *e_prune;
/*
** Calculate the average subtree distances.
*/
root = tree->t_nodes[0];
PostOrder_v (tree, root->v[0], root->b[0]);
/*
** Initialize the array of optimization candidates.
*/
for (i = 0; i < tree->mod->s_opt->wim_n_optim; i++)
{
optim_cand[i]->delta_lk = -1.0*BIG;
optim_cand[i]->d_L = -1.0*BIG;
}
/*
** Try all possible SPR moves and perform the ones that give an improvement.
*/
nr_edges = 2*tree->n_otu - 3;
cur_lk = tree->c_lnL;
improvement = 0;
/* PhyML_Printf("\n >>>>>>>>>>>>>>>>>>"); */
/* PhyML_Printf("\n. cur_lk = %f %f",cur_lk,Lk(tree)); */
/* PhyML_Printf ("\n. Trying SPR moves"); */
/* PhyML_Printf ("\n. - calculating tree distances and estimating likelihoods"); */
for(i = 0; i < nr_edges; i++)
{
/*
** Get the next prune edge.
*/
e_prune = tree->t_edges[i];
/*
** Try right subtree if appropriate.
*/
if (!e_prune->left->tax)
{
/*
** Clear the regraft candidate list.
*/
for (j = 0; j < tree->mod->s_opt->wim_n_rgrft; j++)
{
rgrft_cand[j]->d_L = -1.0*BIG;
}
v_prune = e_prune->left;
/* if ((max_size == 0) || (e_prune->num_tax_rght <= max_size)) */
{
/*
** Calculate changes in tree length, and estimate changes in likelihood for
** the most promising candidates. Perform moves that give an improvement.
*/
Calc_Tree_Length (e_prune, v_prune, tree);
if ((candidate = Est_Lk_Change (e_prune, v_prune, tree)) >= 0)
{
improvement = 1;
Make_Move (rgrft_cand[candidate],0,tree);
/* PhyML_Printf("\n. Make simple move"); */
/* PhyML_Printf("\n. lk after simple move = %f",Lk(tree)); */
}
}
}
/*
** Try left subtree if appropriate.
*/
if (!e_prune->rght->tax)
{
/*
** Clear the regraft candidate list.
*/
for (j = 0; j < tree->mod->s_opt->wim_n_rgrft; j++)
{
rgrft_cand[j]->d_L = -1.0*BIG;
}
v_prune = e_prune->rght;
/* if ((max_size == 0) || (e_prune->num_tax_left <= max_size)) */
{
/*
** Calculate changes in tree length, and estimate changes in likelihood for
** the most promising candidates. Perform moves that give an improvement.
*/
Calc_Tree_Length (e_prune, v_prune, tree);
if ((candidate = Est_Lk_Change (e_prune, v_prune, tree)) >= 0)
{
improvement = 1;
Make_Move (rgrft_cand[candidate],0,tree);
/* PhyML_Printf("\n. Make simple move"); */
/* PhyML_Printf("\n. lk after simple move = %f",Lk(tree)); */
}
}
}
}
/*
** If there was no improvement at all, try local t_edge length optimization at the
** regraft position.
*/
/* PhyML_Printf("\n. before local = %f %f",tree->c_lnL,Lk(tree)); */
if (!improvement)
{
/* PhyML_Printf ("\n. - performing local t_edge length optimizations"); */
if ((candidate = Find_Optim_Local (tree)) >= 0)
{
/* PhyML_Printf("\n. make local move"); */
improvement = 1;
Make_Move (optim_cand[candidate],1,tree);
/* PhyML_Printf("\n. lk after local move = %f",Lk(tree)); */
}
}
/*
** If there was still no improvement, try global t_edge length optimization.
*/
/* PhyML_Printf("\n. before global = %f %f",tree->c_lnL,Lk(tree)); */
if (!improvement)
{
/* PhyML_Printf ("\n. - performing global t_edge length optimization"); */
if ((candidate = Find_Optim_Globl (tree)) >= 0)
{
/* PhyML_Printf("\n. make global move"); */
improvement = 1;
Make_Move (optim_cand[candidate],2,tree);
/* PhyML_Printf("\n. lk after global move = %f",Lk(tree)); */
}
}
/* PhyML_Printf("\n. after all = %f %f",tree->c_lnL,Lk(tree)); */
/*
** Optimize all t_edge lengths again to make sure we got an updated
** likelihood value.
*/
tree->both_sides = 1;
cur_lk = Lk (tree);
root = tree->t_nodes[0];
Optimize_Br_Len_Serie (root, root->v[0], root->b[0], tree, tree->data);
tree->both_sides = 1;
cur_lk = Lk (tree);
time(&(tree->t_current));
if(tree->mod->s_opt->print) Print_Lk(tree,"topoLOGy");
/*
** Return the result.
*/
return (improvement);
}
/*
** Perform_Best_SPR: Perform the best SPR move on the tree. Prune each subtree in
** turn and calculate the change in tree length for each candidate
** regraft position. Estimate change in likelihood for the most
** promising regraft positions, and store the best one. Then choose
** the best candidate over all moves. If no improving move can be
** found, try local t_edge length optimization, and if necessary
** global t_edge length optimization.
**
** Parameters:
** - tree: The tree to perform the SPR moves on.
** - max_size: The maximum size (= number of taxa) of the subtrees to be
** pruned. If m=0 or m>ntax, all possible prunings will be
** considered.
**
** Returns:
** If an improving move could be performed: 1.
** Otherwise: 0.
*/
int Perform_Best_SPR (t_tree *tree, int max_size)
{
int nr_edges, i, j, candidate, improvement;
t_node *root, *v_prune;
t_edge *e_prune;
/*
** Calculate the average subtree distances.
*/
root = tree->t_nodes[0];
PostOrder_v (tree, root->v[0], root->b[0]);
/*
** Initialize the array of optimization candidates.
*/
for (i = 0; i < tree->mod->s_opt->wim_n_optim; i++)
{
optim_cand[i]->delta_lk = -1.0*BIG;
optim_cand[i]->d_L = -1.0*BIG;
}
/*
** Try all possible SPR moves and perform the best one.
*/
nr_edges = 2*tree->n_otu - 3;
cur_lk = tree->c_lnL;
improvement = 0;
/* PhyML_Printf ("\n. Trying SPR moves"); */
/* PhyML_Printf ("\n. -calculating tree distances and estimating likelihoods"); */
for (i = 0; i < nr_edges; i++)
{
/*
** Get the next prune edge.
*/
e_prune = tree->t_edges[i];
/*
** Try right subtree if appropriate.
*/
if (!e_prune->left->tax)
{
/*
** Clear the regraft candidate list.
*/
for (j = 0; j < tree->mod->s_opt->wim_n_best; j++)
{
rgrft_cand[j]->d_L = -1.0*BIG;
}
v_prune = e_prune->left;
/* if ((max_size == 0) || (e_prune->num_tax_rght <= max_size)) */
{
/*
** Calculate changes in tree length, and estimate changes in likelihood for
** the most promising candidates. Store the best one in the optimization list.
*/
Calc_Tree_Length (e_prune, v_prune, tree);
candidate = Best_Lk_Change (e_prune, v_prune, tree);
}
}
/*
** Try left subtree if appropriate.
*/
if (!e_prune->rght->tax)
{
/*
** Clear the regraft candidate list.
*/
for (j = 0; j < tree->mod->s_opt->wim_n_rgrft; j++)
{
rgrft_cand[j]->d_L = -1.0*BIG;
}
v_prune = e_prune->rght;
/* if ((max_size == 0) || (e_prune->num_tax_left <= max_size)) */
{
/*
** Calculate changes in tree length, and estimate changes in likelihood for
** the most promising candidates. Perform moves that give an improvement.
*/
Calc_Tree_Length (e_prune, v_prune, tree);
candidate = Best_Lk_Change (e_prune, v_prune, tree);
}
}
}
/* If the best candidate has a positive estimated change in
** likelihood, perform that move.
*/
if (optim_cand[0]->delta_lk > 1.0/BIG)
{
improvement = 1;
Make_Move (optim_cand[0],0,tree);
}
/*
** If there was no improvement at all, try local t_edge length optimization at the
** regraft position.
*/
if (!improvement)
{
/* PhyML_Printf ("\n. - performing local t_edge length optimizations"); */
if ((candidate = Find_Optim_Local (tree)) >= 0)
{
improvement = 1;
Make_Move (optim_cand[candidate],1,tree);
}
}
/*
** If there was still no improvement, try global t_edge length optimization.
*/
if (!improvement)
{
/* PhyML_Printf ("\n. - performing global t_edge length optimization"); */
if ((candidate = Find_Optim_Globl (tree)) >= 0)
{
improvement = 1;
Make_Move (optim_cand[candidate],2,tree);
}
}
/*
** Optimize all t_edge lengths again to make sure we got an updated
** likelihood value.
*/
tree->both_sides = 1;
cur_lk = Lk (tree);
root = tree->t_nodes[0];
Optimize_Br_Len_Serie (root, root->v[0], root->b[0], tree, tree->data);
tree->both_sides = 1;
cur_lk = Lk (tree);
time(&(tree->t_current));
if(tree->mod->s_opt->print) Print_Lk(tree,"topoLOGy");
/*
** Return the result.
*/
return (improvement);
}
/*
** Perform_One_Moves: Perform a round of SPR moves on the tree. Prune each subtree in
** turn and calculate the change in tree length for each candidate
** regraft position. Estimate change in likelihood for the most
** promising moves, and perform the first move that results in an
** improvement. If no improvements were found at all, try local edge
** length optimization. If still no improvement, try global edge
** length optimization.
**
** Parameters:
** - tree: The tree to perform the SPR moves on.
** - max_size: The maximum size (= number of taxa) of the subtrees to be
** pruned. If m=0 or m>ntax, all possible prunings will be
** considered.
**
** Returns:
** If the current tree could be improved: 1.
** Otherwise: 0.
*/
int Perform_One_SPR(t_tree *tree, int max_size)
{
int nr_edges, i, j, candidate, improvement;
t_node *root, *v_prune;
t_edge *e_prune;
/*
** Calculate the average subtree distances.
*/
root = tree->t_nodes[0];
PostOrder_v (tree, root->v[0], root->b[0]);
/*
** Initialize the array of optimization candidates.
*/
for (i = 0; i < tree->mod->s_opt->wim_n_optim; i++)
{
optim_cand[i]->delta_lk = -1.0*BIG;
optim_cand[i]->d_L = -1.0*BIG;
}
/*
** Try all possible SPR moves and perform the ones that give an improvement.
*/
nr_edges = 2*tree->n_otu - 3;
cur_lk = tree->c_lnL;
improvement = 0;
/* PhyML_Printf("\n >>>>>>>>>>>>>>>>>>"); */
/* PhyML_Printf("\n. cur_lk = %f %f",cur_lk,Lk(tree)); */
/* PhyML_Printf ("\n. Trying SPR moves"); */
/* PhyML_Printf ("\n. - calculating tree distances and estimating likelihoods"); */
for(i = 0; i < nr_edges; i++)
{
/*
** Get the next prune edge.
*/
e_prune = tree->t_edges[i];
/*
** Try right subtree if appropriate.
*/
if (!e_prune->left->tax)
{
/*
** Clear the regraft candidate list.
*/
for (j = 0; j < tree->mod->s_opt->wim_n_rgrft; j++)
{
rgrft_cand[j]->d_L = -1.0*BIG;
}
v_prune = e_prune->left;
/* if ((max_size == 0) || (e_prune->num_tax_rght <= max_size)) */
{
/*
** Calculate changes in tree length, and estimate changes in likelihood for
** the most promising candidates. Perform moves that give an improvement.
*/
Calc_Tree_Length (e_prune, v_prune, tree);
if ((candidate = Est_Lk_Change (e_prune, v_prune, tree)) >= 0)
{
improvement = 1;
Make_Move (rgrft_cand[candidate],0,tree);
}
}
}
/*
** Try left subtree if appropriate.
*/
if (!e_prune->rght->tax && !improvement)
{
/*
** Clear the regraft candidate list.
*/
for (j = 0; j < tree->mod->s_opt->wim_n_rgrft; j++)
{
rgrft_cand[j]->d_L = -1.0*BIG;
}
v_prune = e_prune->rght;
/* if ((max_size == 0) || (e_prune->num_tax_left <= max_size)) */
{
/*
** Calculate changes in tree length, and estimate changes in likelihood for
** the most promising candidates. Perform moves that give an improvement.
*/
Calc_Tree_Length (e_prune, v_prune, tree);
if ((candidate = Est_Lk_Change (e_prune, v_prune, tree)) >= 0)
{
improvement = 1;
Make_Move (rgrft_cand[candidate],0,tree);
/* PhyML_Printf("\n. Make simple move"); */
/* PhyML_Printf("\n. lk after simple move = %f",Lk(tree)); */
}
}
}
if(improvement) break;
}
/*
** If there was no improvement at all, try local t_edge length optimization at the
** regraft position.
*/
/* PhyML_Printf("\n. before local = %f %f",tree->c_lnL,Lk(tree)); */
if (!improvement)
{
/* PhyML_Printf ("\n. - performing local t_edge length optimizations"); */
if ((candidate = Find_Optim_Local (tree)) >= 0)
{
/* PhyML_Printf("\n. make local move"); */
improvement = 1;
Make_Move (optim_cand[candidate],1,tree);
/* PhyML_Printf("\n. lk after local move = %f",Lk(tree)); */
}
}
/*
** If there was still no improvement, try global t_edge length optimization.
*/
/* PhyML_Printf("\n. before global = %f %f",tree->c_lnL,Lk(tree)); */
if (!improvement)
{
/* PhyML_Printf ("\n. - performing global t_edge length optimization"); */
if ((candidate = Find_Optim_Globl (tree)) >= 0)
{
/* PhyML_Printf("\n. make global move"); */
improvement = 1;
Make_Move (optim_cand[candidate],2,tree);
/* PhyML_Printf("\n. lk after global move = %f",Lk(tree)); */
}
}
/* PhyML_Printf("\n. after all = %f %f",tree->c_lnL,Lk(tree)); */
/*
** Optimize all t_edge lengths again to make sure we got an updated
** likelihood value.
*/
tree->both_sides = 1;
cur_lk = Lk (tree);
root = tree->t_nodes[0];
Optimize_Br_Len_Serie (root, root->v[0], root->b[0], tree, tree->data);
tree->both_sides = 1;
cur_lk = Lk (tree);
time(&(tree->t_current));
if(tree->mod->s_opt->print) Print_Lk(tree,"topology");
/*
** Return the result.
*/
return (improvement);
}
/*
** Calc_Tree_Length: Calculate the change in tree length, given a pruned subtree,
** for each possible regraft position.
**
** Parameters:
** - e_prune: The t_edge at which the subtree is pruned.
** - v_prune: The root of the pruned subtree.
*/
void Calc_Tree_Length (t_edge *e_prune, t_node *v_prune, t_tree *tree)
{
int i, d0, d1, d2;
phydbl d_uu;
t_node *u_prune, *u1, *u2;
/*
** Get the directions from t_node v_prune.
*/
d0 = -1;
u_prune = NULL;
for (i = 0; i < 3; i++)
{
if (v_prune->b[i] == e_prune)
{
d0 = i;
u_prune = v_prune->v[i];
break;
}
}
d1 = (d0 + 1) % 3;
d2 = 3 - d0 - d1;
/*
** Get the relevant average subtree distance within the pruned subtree.
*/
if (!u_prune->tax)
{
u1 = u2 = NULL;
for (i = 0; i < 3; i++)
{
if (u_prune->b[i] != e_prune)
{
if (u1 == NULL)
{
u1 = u_prune->v[i];
}
else
{
u2 = u_prune->v[i];
}
}
}
d_uu = subtree_dist[u1->num][u2->num];
}
else
{
d_uu = 0.0;
}
/*
** Recursively calculate the change in tree length for each
** possible regraft position.
**
** First recurse into direction d1.
*/
if (!v_prune->v[d1]->tax)
{
u1 = u2 = NULL;
for (i = 0; i < 3; i++)
{
if (v_prune->v[d1]->b[i] != v_prune->b[d1])
{
if (u1 == NULL)
{
u1 = v_prune->v[d1]->v[i];
}
else
{
u2 = v_prune->v[d1]->v[i];
}
}
}
Tree_Length(v_prune, u_prune, v_prune->v[d1], v_prune->v[d2], u1, v_prune->v[d2],
u2, subtree_dist[u_prune->num][v_prune->v[d2]->num], d_uu, 0.0, 1, tree);
Tree_Length(v_prune, u_prune, v_prune->v[d1], v_prune->v[d2], u2, v_prune->v[d2],
u1, subtree_dist[u_prune->num][v_prune->v[d2]->num], d_uu, 0.0, 1, tree);
}
/*
** Next recurse into direction d2.
*/
if (!v_prune->v[d2]->tax)
{
u1 = u2 = NULL;
for (i = 0; i < 3; i++)
{
if (v_prune->v[d2]->b[i] != v_prune->b[d2])
{
if (u1 == NULL)
{
u1 = v_prune->v[d2]->v[i];
}
else
{
u2 = v_prune->v[d2]->v[i];
}
}
}
Tree_Length(v_prune, u_prune, v_prune->v[d2], v_prune->v[d1], u1, v_prune->v[d1],
u2, subtree_dist[u_prune->num][v_prune->v[d1]->num], d_uu, 0.0, 1, tree);
Tree_Length(v_prune, u_prune, v_prune->v[d2], v_prune->v[d1], u2, v_prune->v[d1],
u1, subtree_dist[u_prune->num][v_prune->v[d1]->num], d_uu, 0.0, 1, tree);
}
}
/*
** Tree_Length: Recursively calculate the change in tree length for a given pruned
** subtree and regraft position.
**
** Parameters:
** - v_prune: The root of the pruned subtree.
** - u_prune: The t_node adjacent to v_p along the pruned edge.
** - v_n: The t_node adjacent to the regraft t_edge in the "backward" direction.
** - v_n_1: The previous v_n.
** - v_nx1: The t_node adjacent to the regrafting t_edge in the "forward" direction.
** - v_0: The other t_node originally adjacent to v_p;
** - u_n: The other t_node adjecent to v_n (besides v_n_1 and v_nx1);
** - d_uv_1: The distance between u_p and v_n_1;
** - d_uu: The subtree distance between descendants of u_prune.
** - d_L_1: The previous change in tree length.
** - n: The current distance from the prune position.
*/
void Tree_Length (t_node *v_prune, t_node *u_prune, t_node *v_n, t_node *v_n_1, t_node *v_nx1,
t_node *v_0, t_node *u_n, phydbl d_up_v_1, phydbl d_L_1, phydbl d_uu,
int n, t_tree *tree)
{
int i, j;
phydbl d_un_v, d_up_v, d_L;
t_node *u1, *u2;
t_edge *e_prune, *e_regraft;
_move_ *tmp_cand;
/*
** Update the path and number of calculations.
*/
path[n] = v_n;
nr_d_L++;
e_prune = NULL;
e_regraft = NULL;
/*
** Calculate the change in tree length for the current pruned subtree and regraft
** position.
*/
if (n == 1)
{
d_un_v = subtree_dist[u_n->num][v_0->num];
}
else
{
d_un_v = subtree_dist[u_n->num][v_n_1->num] -
(pow (0.5, n) * subtree_dist[u_n->num][u_prune->num]) +
(pow (0.5, n) * subtree_dist[u_n->num][v_0->num]);
}
d_up_v = 0.5 * (d_up_v_1 + subtree_dist[u_prune->num][u_n->num]);
/*
** Alternative method for calculating d_up_v. Just kept it around for reference...
**
d_up_v = subtree_dist[u_prune->num][u_n->num] - (0.5 * d_uu);
if (!u_n->tax)
{
u1 = u2 = NULL;
for (i = 0; i < 3; i++)
{
if (u_n->v[i] != v_n)
{
if (u1 == NULL)
{
u1 = u_n->v[i];
}
else
{
u2 = u_n->v[i];
}
}
}
d_up_v -= 0.5 * subtree_dist[u1->num][u2->num];
}
for (i = 0; i < 3; i++)
{
if (u_n->v[i] == v_n)
{
d_up_v -= u_n->b[i]->l;
break;
}
}
*/
d_L = d_L_1 + 0.25*((d_up_v_1 + subtree_dist[u_n->num][v_nx1->num]) -
(d_un_v + subtree_dist[u_prune->num][v_nx1->num]));
/*
** If the change is within the tree->mod->s_opt->wim_n_rgrft best ones so far, save it.
*/
if (d_L > rgrft_cand[tree->mod->s_opt->wim_n_rgrft-1]->d_L)
{
for (i = 0; i < 3; i++)
{
if (v_prune->v[i] == u_prune)
{
e_prune = v_prune->b[i];
}
if (v_n->v[i] == v_nx1)
{
e_regraft = v_n->b[i];
}
}
i = tree->mod->s_opt->wim_n_rgrft-1;
rgrft_cand[i]->v_prune = v_prune;
rgrft_cand[i]->u_prune = u_prune;
rgrft_cand[i]->v_n = v_n;
rgrft_cand[i]->v_nx1 = v_nx1;
rgrft_cand[i]->u_n = u_n;
rgrft_cand[i]->e_prune = e_prune;
rgrft_cand[i]->e_regraft = e_regraft;
rgrft_cand[i]->d_L = d_L;
rgrft_cand[i]->d_up_v = d_up_v;
rgrft_cand[i]->d_un_v = d_un_v;
rgrft_cand[i]->dist = n;
for (j = 1; j <= n; j++)
{
rgrft_cand[i]->path[j] = path[j];
}
rgrft_cand[i]->path[n+1] = v_nx1;
/*
** Move the candidate to the appropriate position in the list, so the list
** remains sorted in decreasing d_L value.
*/
while ((i > 0) && (rgrft_cand[i]->d_L > rgrft_cand[i-1]->d_L))
{
tmp_cand = rgrft_cand[i];
rgrft_cand[i] = rgrft_cand[i-1];
rgrft_cand[i-1] = tmp_cand;
i--;
}
}
/*
** Recurse.
*/
if (n < tree->mod->s_opt->wim_max_dist)
{
if (!v_nx1->tax)
{
u1 = u2 = NULL;
for (i = 0; i < 3; i++)
{
if (v_nx1->v[i] != v_n)
{
if (u1 == NULL)
{
u1 = v_nx1->v[i];
}
else
{
u2 = v_nx1->v[i];
}
}
}
Tree_Length (v_prune, u_prune, v_nx1, v_n, u1, v_0, u2, d_up_v, d_uu, d_L, n+1, tree);
Tree_Length (v_prune, u_prune, v_nx1, v_n, u2, v_0, u1, d_up_v, d_uu, d_L, n+1, tree);
}
}
}
/*
** Est_Lk_Change: Estimate the changes in likelihood for the most promising candidate
** regraft positions given a pruned subtree.
**
** Parameters:
** - e_prune: The t_edge at which the subtree was pruned.
** - v_prune: The root of the pruned subtree.
** - tree: The tree on which to do the calculations.
**
** Returns:
** If an improvement as found: The candidate which gives the improvement (which
** will be the first one found).
** Otherwise: -1.
*/
int Est_Lk_Change (t_edge *e_prune, t_node *v_prune, t_tree *tree)
{
int i, j, cand, best_cand, d0, d1, d2, n, pat, cat, ste;
phydbl d_uu, best_d_lk, l_connect, l_01, l_02, l_12, l_est[3], new_lk,
l_simple[3], l_dist[3];
phydbl *p_lk1_tmp, *p_lk2_tmp, *p_lk;
int *p_sum;
t_node *u_prune, *v_n, *v_nx1, *u_n, *u1, *u2;
t_edge *e_regraft, *e_tmp;
_move_ *tmp_cand;
int dim1, dim2;
dim1 = tree->mod->ns * tree->mod->n_catg;
dim2 = tree->mod->n_catg;
/*
** Get the directions from t_node v_prune.
*/
d0 = -1;
u_prune = NULL;
for (i = 0; i < 3; i++)
{
if (v_prune->b[i] == e_prune)
{
d0 = i;
u_prune = v_prune->v[i];
break;
}
}
d1 = (d0 + 1) % 3;
d2 = 3 - d0 - d1;
/*
** Copy the relevant partial likelihoods to the temporary regraft structure.
** We can point to the original matrices, cos they won't be changed anyway.
*/
if (v_prune == e_prune->left)
{
v_tmp->b[0]->p_lk_rght = e_prune->p_lk_rght;
v_tmp->b[0]->sum_scale_rght = e_prune->sum_scale_rght;
}
else
{
v_tmp->b[0]->p_lk_rght = e_prune->p_lk_left;
v_tmp->b[0]->sum_scale_rght = e_prune->sum_scale_left;
}
v_tmp->num = v_prune->num;
v_tmp->v[0]->num = u_prune->num;
v_tmp->b[0]->num = e_prune->num;
/*
** Estimate the length of the t_edge that will connect the two "detached" nodes
** after pruning. (The average of the sum of the lengths of the original two
** edges and the average subtree distance based estimate.)
*/
l_connect = subtree_dist[v_prune->v[d1]->num][v_prune->v[d2]->num];
if (!v_prune->v[d1]->tax)
{
u1 = u2 = NULL;
for (i = 0; i < 3; i++)
{
if (v_prune->v[d1]->b[i] != v_prune->b[d1])
{
if (u1 == NULL)
{
u1 = v_prune->v[d1]->v[i];
}
else
{
u2 = v_prune->v[d1]->v[i];
}
}
}
l_connect -= 0.5 * subtree_dist[u1->num][u2->num];
}
if (!v_prune->v[d2]->tax)
{
u1 = u2 = NULL;
for (i = 0; i < 3; i++)
{
if (v_prune->v[d2]->b[i] != v_prune->b[d2])
{
if (u1 == NULL)
{
u1 = v_prune->v[d2]->v[i];
}
else
{
u2 = v_prune->v[d2]->v[i];
}
}
}
l_connect -= 0.5 * subtree_dist[u1->num][u2->num];
}
l_connect += (v_prune->b[d1]->l + v_prune->b[d2]->l);
l_connect /= 2.0;
/*
** Temporarily swap the relevant partial likelihoods at the prune site.
**
** Direction d1.
*/
if (v_prune == v_prune->b[d1]->left)
{
p_lk1_tmp = v_prune->b[d1]->p_lk_left;
if (v_prune == v_prune->b[d2]->left)
{
v_prune->b[d1]->p_lk_left = v_prune->b[d2]->p_lk_rght;
}
else
{
v_prune->b[d1]->p_lk_left = v_prune->b[d2]->p_lk_left;
}
}
else
{
p_lk1_tmp = v_prune->b[d1]->p_lk_rght;
if (v_prune == v_prune->b[d2]->left)
{
v_prune->b[d1]->p_lk_rght = v_prune->b[d2]->p_lk_rght;
}
else
{
v_prune->b[d1]->p_lk_rght = v_prune->b[d2]->p_lk_left;
}
}
/*
** Direction d2.
*/
if (v_prune == v_prune->b[d2]->left)
{
p_lk2_tmp = v_prune->b[d2]->p_lk_left;
if (v_prune == v_prune->b[d1]->left)
{
v_prune->b[d2]->p_lk_left = v_prune->b[d1]->p_lk_rght;
}
else
{
v_prune->b[d2]->p_lk_left = v_prune->b[d1]->p_lk_left;
}
}
else
{
p_lk2_tmp = v_prune->b[d2]->p_lk_rght;
if (v_prune == v_prune->b[d1]->left)
{
v_prune->b[d2]->p_lk_rght = v_prune->b[d1]->p_lk_rght;
}
else
{
v_prune->b[d2]->p_lk_rght = v_prune->b[d1]->p_lk_left;
}
}
/*
** Temporarily set the t_edge lengths and update transition prob's at the
** prune site.
*/
v_prune->b[d1]->l_old = v_prune->b[d1]->l;
v_prune->b[d2]->l_old = v_prune->b[d2]->l;
v_prune->b[d1]->l = l_connect;
v_prune->b[d2]->l = l_connect;
Update_PMat_At_Given_Edge (v_prune->b[d1], tree);
Update_PMat_At_Given_Edge (v_prune->b[d2], tree);
/*
** Get the relevant average subtree distance within the pruned subtree.
*/
if (!u_prune->tax)
{
u1 = u2 = NULL;
for (i = 0; i < 3; i++)
{
if (u_prune->b[i] != e_prune)
{
if (u1 == NULL)
{
u1 = u_prune->v[i];
}
else
{
u2 = u_prune->v[i];
}
}
}
d_uu = subtree_dist[u1->num][u2->num];
}
else
{
d_uu = 0.0;
}
/*
** Try each candidate SPR and estimate the change in likelihood.
*/
best_d_lk = 1.0/BIG;
best_cand = -1;
for (cand = 0; cand < tree->mod->s_opt->wim_n_rgrft; cand++)
{
/*
** If there are no more candidates, bail out...
*/
if (FABS(rgrft_cand[cand]->d_L - 1.0*BIG) < SMALL)
{
break;
}
else
{
nr_d_lk++;
}
/*
** Get the relevant nodes and edges.
*/
v_n = rgrft_cand[cand]->v_n;
v_nx1 = rgrft_cand[cand]->v_nx1;
u_n = rgrft_cand[cand]->u_n;
e_regraft = rgrft_cand[cand]->e_regraft;
/*
** Update the relevant partial likelihoods along the path between the prune
** and regraft positions (temporarily save the first one).
*/
n = rgrft_cand[cand]->dist;
e_tmp = NULL;
p_lk = NULL;
p_sum = NULL;
for (i = 1; i <= n; i++)
{
/*
** Get the next t_edge along the path.
*/
for (j = 0; j < 3; j++)
{
if (rgrft_cand[cand]->path[i]->v[j] == rgrft_cand[cand]->path[i+1])
{
e_tmp = rgrft_cand[cand]->path[i]->b[j];
break;
}
}
if (i == 1)
{
/*
** Save the first partial likelihood along the path.
*/
if (rgrft_cand[cand]->path[i] == e_tmp->left)
{
p_lk = e_tmp->p_lk_left;
p_sum = e_tmp->sum_scale_left;
}
else
{
p_lk = e_tmp->p_lk_rght;
p_sum = e_tmp->sum_scale_rght;
}
for (pat = 0; pat < tree->n_pattern; pat++)
{
sum_scale_tmp[pat] = p_sum[pat];
for (cat = 0; cat < tree->mod->n_catg; cat++)
{
for (ste = 0; ste < tree->mod->ns; ste++)
{
p_lk_tmp[pat*dim1+cat*dim2+ste] = p_lk[pat*dim1+cat*dim2+ste];
}
}
}
}
Update_P_Lk (tree, e_tmp, rgrft_cand[cand]->path[i]);
}
if (v_n == e_regraft->left)
{
v_tmp->b[1]->p_lk_rght = e_regraft->p_lk_left;
v_tmp->b[2]->p_lk_rght = e_regraft->p_lk_rght;
v_tmp->b[1]->sum_scale_rght = e_regraft->sum_scale_left;
v_tmp->b[2]->sum_scale_rght = e_regraft->sum_scale_rght;
}
else
{
v_tmp->b[1]->p_lk_rght = e_regraft->p_lk_rght;
v_tmp->b[2]->p_lk_rght = e_regraft->p_lk_left;
v_tmp->b[1]->sum_scale_rght = e_regraft->sum_scale_rght;
v_tmp->b[2]->sum_scale_rght = e_regraft->sum_scale_left;
}
/*
** Estimate t_edge lengths of the three relevant regraft edges based on
** average subtree distances.
**
** l_01
*/
/*
** Alternative method of estimating l_01. Kept it around for reference...
**
l_01 = subtree_dist[u_prune->num][u_n->num] - (0.5 * d_uu);
if (!u_n->tax)
{
u1 = u2 = NULL;
for (i = 0; i < 3; i++)
{
if (u_n->v[i] != v_n)
{
if (u1 == NULL)
{
u1 = u_n->v[i];
}
else
{
u2 = u_n->v[i];
}
}
}
l_01 -= 0.5 * subtree_dist[u1->num][u2->num];
}
for (i = 0; i < 3; i++)
{
if (u_n->v[i] == v_n)
{
l_01 -= u_n->b[i]->l;
break;
}
}
*/
l_01 = rgrft_cand[cand]->d_up_v - (0.5 * rgrft_cand[cand]->d_un_v) -
(0.5 * d_uu);
/*
** l_02
*/
l_02 = subtree_dist[u_prune->num][v_nx1->num] - (0.5 * d_uu);
if (!v_nx1->tax)
{
u1 = u2 = NULL;
for (i = 0; i < 3; i++)
{
if (v_nx1->v[i] != v_n)
{
if (u1 == NULL)
{
u1 = v_nx1->v[i];
}
else
{
u2 = v_nx1->v[i];
}
}
}
l_02 -= (0.5 * subtree_dist[u1->num][u2->num]);
}
/*
** l_12
*/
l_12 = e_regraft->l;
/*
** Simple estimates.
*/
l_simple[0] = l_02 - (0.5*e_regraft->l);
l_simple[1] = 0.5 * e_regraft->l;
l_simple[2] = 0.5 * e_regraft->l;
/*
** Average subtree distance based estimates.
*/
l_dist[0] = 0.5 * ( l_01 + l_02 - l_12);
l_dist[1] = 0.5 * ( l_01 - l_02 + l_12);
l_dist[2] = 0.5 * (-l_01 + l_02 + l_12);
/*
** Take the average of the two estimates.
*/
l_est[0] = (l_simple[0] + l_dist[0]) / 2.0;
l_est[1] = (l_simple[1] + l_dist[1]) / 2.0;
l_est[2] = (l_simple[2] + l_dist[2]) / 2.0;
/*
** Set the t_edge lengths and update the relevant transition prob's and
** partial likelihoods in the temporary regraft structure.
*/
for (i = 0; i < 3; i++)
{
v_tmp->b[i]->l = l_est[i]; /* TO DO */
Update_PMat_At_Given_Edge (v_tmp->b[i], tree);
}
/* Beg SG 18 May 2007 */
if(tree->mod->s_opt->wim_inside_opt)
{
Triple_Dist(v_tmp,tree,0);
For(i,3) l_est[i] = v_tmp->b[i]->l;
}
/* End SG 18 May 2007 */
/*
** Calculate the change in likelihood locally. Save it and the estimated edge
** lengths in the current candidate in the list.
*/
Update_P_Lk (tree, v_tmp->b[0], v_tmp);
new_lk = Lk_At_Given_Edge (v_tmp->b[0],tree);
/* PhyML_Printf("\n. new_lk = %f",new_lk); */
rgrft_cand[cand]->delta_lk = new_lk - cur_lk;
rgrft_cand[cand]->rgrft_rank = cand;
rgrft_cand[cand]->optim_rank = -1;
rgrft_cand[cand]->globl_rank = -1;
rgrft_cand[cand]->l_connect = l_connect;
for (i = 0; i < 3; i++)
{
rgrft_cand[cand]->l_est[i] = v_tmp->b[i]->l;
}
if (rgrft_cand[cand]->delta_lk > best_d_lk)
{
best_d_lk = rgrft_cand[cand]->delta_lk;
best_cand = cand;
}
/*
** If the change is within the tree->mod->s_opt->wim_n_optim best ones, save it in the list of
** optimization candidates.
*/
if (rgrft_cand[cand]->delta_lk > optim_cand[tree->mod->s_opt->wim_n_optim-1]->delta_lk)
{
i = tree->mod->s_opt->wim_n_optim-1;
optim_cand[i]->v_prune = rgrft_cand[cand]->v_prune;
optim_cand[i]->u_prune = rgrft_cand[cand]->u_prune;
optim_cand[i]->v_n = rgrft_cand[cand]->v_n;
optim_cand[i]->v_nx1 = rgrft_cand[cand]->v_nx1;
optim_cand[i]->u_n = rgrft_cand[cand]->u_n;
optim_cand[i]->e_prune = rgrft_cand[cand]->e_prune;
optim_cand[i]->e_regraft = rgrft_cand[cand]->e_regraft;
optim_cand[i]->d_L = rgrft_cand[cand]->d_L;
optim_cand[i]->dist = rgrft_cand[cand]->dist;
optim_cand[i]->rgrft_rank = rgrft_cand[cand]->rgrft_rank;
optim_cand[i]->optim_rank = rgrft_cand[cand]->optim_rank;
optim_cand[i]->globl_rank = rgrft_cand[cand]->globl_rank;
optim_cand[i]->l_connect = rgrft_cand[cand]->l_connect;
for (j = 0; j < 3; j++)
{
optim_cand[i]->l_est[j] = rgrft_cand[cand]->l_est[j];
}
optim_cand[i]->delta_lk = rgrft_cand[cand]->delta_lk;
/*
** Move the candidate to the appropriate position in the list, so the list
** remains sorted in decreasing delta_Lk value.
*/
while ((i > 0) && (optim_cand[i]->delta_lk > optim_cand[i-1]->delta_lk))
{
tmp_cand = optim_cand[i];
optim_cand[i] = optim_cand[i-1];
optim_cand[i-1] = tmp_cand;
i--;
}
}
/*
** Reset the partial likelihoods along the path.
*/
for (pat = 0; pat < tree->n_pattern; pat++)
{
p_sum[pat] = sum_scale_tmp[pat];
for (cat = 0; cat < tree->mod->n_catg; cat++)
{
for (ste = 0; ste < tree->mod->ns; ste++)
{
p_lk[pat*dim1+cat*dim2+ste] = p_lk_tmp[pat*dim1+cat*dim2+ste];
}
}
}
n = rgrft_cand[cand]->dist;
for (i = 2; i <= n; i++)
{
for (j = 0; j < 3; j++)
{
if (rgrft_cand[cand]->path[i]->v[j] == rgrft_cand[cand]->path[i+1])
{
e_tmp = rgrft_cand[cand]->path[i]->b[j];
break;
}
}
Update_P_Lk (tree, e_tmp, rgrft_cand[cand]->path[i]);
}
/*
** If an improvement was found, forget the other candidates...
*/
if (best_cand >= 0)
{
break;
}
}
/*
** Swap back the relevant partial likelihoods at the prune site.
*/
if (v_prune == v_prune->b[d1]->left)
{
v_prune->b[d1]->p_lk_left = p_lk1_tmp;
}
else
{
v_prune->b[d1]->p_lk_rght = p_lk1_tmp;
}
if (v_prune == v_prune->b[d2]->left)
{
v_prune->b[d2]->p_lk_left = p_lk2_tmp;
}
else
{
v_prune->b[d2]->p_lk_rght = p_lk2_tmp;
}
/*
** Reset the relevant t_edge lengths and transition prob's at the prune site.
*/
v_prune->b[d1]->l = v_prune->b[d1]->l_old;
v_prune->b[d2]->l = v_prune->b[d2]->l_old;
Update_PMat_At_Given_Edge (v_prune->b[d1], tree);
Update_PMat_At_Given_Edge (v_prune->b[d2], tree);
/*
** Return the best candidate.
*/
return (best_cand);
}
/*
** Best_Lk_Change: Estimate the changes in likelihood for the most promising candidate
** regraft positions given a pruned subtree and save the best one.
**
** Parameters:
** - e_prune: The t_edge at which the subtree was pruned.
** - v_prune: The root of the pruned subtree.
** - tree: The tree on which to do the calculations.
**
** Returns:
** The candidate which gives the best (possibly negative) improvement.
*/
int Best_Lk_Change (t_edge *e_prune, t_node *v_prune, t_tree *tree)
{
int i, j, cand, best_cand, d0, d1, d2, n, pat, cat, ste;
phydbl d_uu, best_d_lk, l_connect, l_01, l_02, l_12, l_est[3], new_lk,
l_simple[3], l_dist[3];
phydbl *p_lk1_tmp, *p_lk2_tmp, *p_lk;
int *p_sum;
t_node *u_prune, *v_n, *v_nx1, *u_n, *u1, *u2;
t_edge *e_regraft, *e_tmp;
_move_ *tmp_cand;
int dim1, dim2;
dim1 = tree->mod->ns * tree->mod->n_catg;
dim2 = tree->mod->ns ;
/*
** Get the directions from t_node v_prune.
*/
d0 = -1;
u_prune = NULL;
for (i = 0; i < 3; i++)
{
if (v_prune->b[i] == e_prune)
{
d0 = i;
u_prune = v_prune->v[i];
break;
}
}
d1 = (d0 + 1) % 3;
d2 = 3 - d0 - d1;
/*
** Copy the relevant partial likelihoods to the temporary regraft structure.
** We can point to the original matrices, cos they won't be changed anyway.
*/
if (v_prune == e_prune->left)
{
v_tmp->b[0]->p_lk_rght = e_prune->p_lk_rght;
v_tmp->b[0]->sum_scale_rght = e_prune->sum_scale_rght;
}
else
{
v_tmp->b[0]->p_lk_rght = e_prune->p_lk_left;
v_tmp->b[0]->sum_scale_rght = e_prune->sum_scale_left;
}
v_tmp->num = v_prune->num;
v_tmp->v[0]->num = u_prune->num;
v_tmp->b[0]->num = e_prune->num;
/*
** Estimate the length of the t_edge that will connect the two "detached" nodes
** after pruning. (The average of the sum of the lengths of the original two
** edges and the average subtree distance based estimate.)
*/
l_connect = subtree_dist[v_prune->v[d1]->num][v_prune->v[d2]->num];
if (!v_prune->v[d1]->tax)
{
u1 = u2 = NULL;
for (i = 0; i < 3; i++)
{
if (v_prune->v[d1]->b[i] != v_prune->b[d1])
{
if (u1 == NULL)
{
u1 = v_prune->v[d1]->v[i];
}
else
{
u2 = v_prune->v[d1]->v[i];
}
}
}
l_connect -= 0.5 * subtree_dist[u1->num][u2->num];
}
if (!v_prune->v[d2]->tax)
{
u1 = u2 = NULL;
for (i = 0; i < 3; i++)
{
if (v_prune->v[d2]->b[i] != v_prune->b[d2])
{
if (u1 == NULL)
{
u1 = v_prune->v[d2]->v[i];
}
else
{
u2 = v_prune->v[d2]->v[i];
}
}
}
l_connect -= 0.5 * subtree_dist[u1->num][u2->num];
}
l_connect += (v_prune->b[d1]->l + v_prune->b[d2]->l);
l_connect /= 2.0;
/*
** Temporarily swap the relevant partial likelihoods at the prune site.
**
** Direction d1.
*/
if (v_prune == v_prune->b[d1]->left)
{
p_lk1_tmp = v_prune->b[d1]->p_lk_left;
if (v_prune == v_prune->b[d2]->left)
{
v_prune->b[d1]->p_lk_left = v_prune->b[d2]->p_lk_rght;
}
else
{
v_prune->b[d1]->p_lk_left = v_prune->b[d2]->p_lk_left;
}
}
else
{
p_lk1_tmp = v_prune->b[d1]->p_lk_rght;
if (v_prune == v_prune->b[d2]->left)
{
v_prune->b[d1]->p_lk_rght = v_prune->b[d2]->p_lk_rght;
}
else
{
v_prune->b[d1]->p_lk_rght = v_prune->b[d2]->p_lk_left;
}
}
/*
** Direction d2.
*/
if (v_prune == v_prune->b[d2]->left)
{
p_lk2_tmp = v_prune->b[d2]->p_lk_left;
if (v_prune == v_prune->b[d1]->left)
{
v_prune->b[d2]->p_lk_left = v_prune->b[d1]->p_lk_rght;
}
else
{
v_prune->b[d2]->p_lk_left = v_prune->b[d1]->p_lk_left;
}
}
else
{
p_lk2_tmp = v_prune->b[d2]->p_lk_rght;
if (v_prune == v_prune->b[d1]->left)
{
v_prune->b[d2]->p_lk_rght = v_prune->b[d1]->p_lk_rght;
}
else
{
v_prune->b[d2]->p_lk_rght = v_prune->b[d1]->p_lk_left;
}
}
/*
** Temporarily set the t_edge lengths and update transition prob's at the
** prune site.
*/
v_prune->b[d1]->l_old = v_prune->b[d1]->l;
v_prune->b[d2]->l_old = v_prune->b[d2]->l;
v_prune->b[d1]->l = l_connect;
v_prune->b[d2]->l = l_connect;
Update_PMat_At_Given_Edge (v_prune->b[d1], tree);
Update_PMat_At_Given_Edge (v_prune->b[d2], tree);
/*
** Get the relevant average subtree distance within the pruned subtree.
*/
if (!u_prune->tax)
{
u1 = u2 = NULL;
for (i = 0; i < 3; i++)
{
if (u_prune->b[i] != e_prune)
{
if (u1 == NULL)
{
u1 = u_prune->v[i];
}
else
{
u2 = u_prune->v[i];
}
}
}
d_uu = subtree_dist[u1->num][u2->num];
}
else
{
d_uu = 0.0;
}
/*
** Try the best candidate SPRs and estimate the change in likelihood.
*/
best_d_lk = -1.0*BIG;
best_cand = 0;
for (cand = 0; cand < tree->mod->s_opt->wim_n_best; cand++)
{
/*
** If there are no more candidates, bail out...
*/
if (FABS(rgrft_cand[cand]->d_L - 1.0*BIG) < SMALL)
{
break;
}
else
{
nr_d_lk++;
}
/*
** Get the relevant nodes and edges.
*/
v_n = rgrft_cand[cand]->v_n;
v_nx1 = rgrft_cand[cand]->v_nx1;
u_n = rgrft_cand[cand]->u_n;
e_regraft = rgrft_cand[cand]->e_regraft;
/*
** Update the relevant partial likelihoods along the path between the prune
** and regraft positions (temporarily save the first one).
*/
n = rgrft_cand[cand]->dist;
e_tmp = NULL;
p_lk = NULL;
p_sum = NULL;
for (i = 1; i <= n; i++)
{
/*
** Get the next t_edge along the path.
*/
for (j = 0; j < 3; j++)
{
if (rgrft_cand[cand]->path[i]->v[j] == rgrft_cand[cand]->path[i+1])
{
e_tmp = rgrft_cand[cand]->path[i]->b[j];
break;
}
}
if (i == 1)
{
/*
** Save the first partial likelihood along the path.
*/
if (rgrft_cand[cand]->path[i] == e_tmp->left)
{
p_lk = e_tmp->p_lk_left;
p_sum = e_tmp->sum_scale_left;
}
else
{
p_lk = e_tmp->p_lk_rght;
p_sum = e_tmp->sum_scale_rght;
}
for (pat = 0; pat < tree->n_pattern; pat++)
{
sum_scale_tmp[pat] = p_sum[pat];
for (cat = 0; cat < tree->mod->n_catg; cat++)
{
for (ste = 0; ste < tree->mod->ns; ste++)
{
p_lk_tmp[pat*dim1+cat*dim2+ste] = p_lk[pat*dim1+cat*dim2+ste];
}
}
}
}
Update_P_Lk (tree, e_tmp, rgrft_cand[cand]->path[i]);
}
if (v_n == e_regraft->left)
{
v_tmp->b[1]->p_lk_rght = e_regraft->p_lk_left;
v_tmp->b[2]->p_lk_rght = e_regraft->p_lk_rght;
v_tmp->b[1]->sum_scale_rght = e_regraft->sum_scale_left;
v_tmp->b[2]->sum_scale_rght = e_regraft->sum_scale_rght;
}
else
{
v_tmp->b[1]->p_lk_rght = e_regraft->p_lk_rght;
v_tmp->b[2]->p_lk_rght = e_regraft->p_lk_left;
v_tmp->b[1]->sum_scale_rght = e_regraft->sum_scale_rght;
v_tmp->b[2]->sum_scale_rght = e_regraft->sum_scale_left;
}
/*
** Estimate t_edge lengths of the three relevant regraft edges based on
** average subtree distances.
**
** l_01
*/
/*
** Alternative method of estimating l_01. Kept it around for reference...
**
l_01 = subtree_dist[u_prune->num][u_n->num] - (0.5 * d_uu);
if (!u_n->tax)
{
u1 = u2 = NULL;
for (i = 0; i < 3; i++)
{
if (u_n->v[i] != v_n)
{
if (u1 == NULL)
{
u1 = u_n->v[i];
}
else
{
u2 = u_n->v[i];
}
}
}
l_01 -= 0.5 * subtree_dist[u1->num][u2->num];
}
for (i = 0; i < 3; i++)
{
if (u_n->v[i] == v_n)
{
l_01 -= u_n->b[i]->l;
break;
}
}
*/
l_01 = rgrft_cand[cand]->d_up_v - (0.5 * rgrft_cand[cand]->d_un_v) -
(0.5 * d_uu);
/*
** l_02
*/
l_02 = subtree_dist[u_prune->num][v_nx1->num] - (0.5 * d_uu);
if (!v_nx1->tax)
{
u1 = u2 = NULL;
for (i = 0; i < 3; i++)
{
if (v_nx1->v[i] != v_n)
{
if (u1 == NULL)
{
u1 = v_nx1->v[i];
}
else
{
u2 = v_nx1->v[i];
}
}
}
l_02 -= (0.5 * subtree_dist[u1->num][u2->num]);
}
/*
** l_12
*/
l_12 = e_regraft->l;
/*
** Simple estimates.
*/
l_simple[0] = l_02 - (0.5*e_regraft->l);
l_simple[1] = 0.5 * e_regraft->l;
l_simple[2] = 0.5 * e_regraft->l;
/*
** Average subtree distance based estimates.
*/
l_dist[0] = 0.5 * ( l_01 + l_02 - l_12);
l_dist[1] = 0.5 * ( l_01 - l_02 + l_12);
l_dist[2] = 0.5 * (-l_01 + l_02 + l_12);
/*
** Take the average of the two estimates.
*/
l_est[0] = (l_simple[0] + l_dist[0]) / 2.0;
l_est[1] = (l_simple[1] + l_dist[1]) / 2.0;
l_est[2] = (l_simple[2] + l_dist[2]) / 2.0;
/*
** Set the t_edge lengths and update the relevant transition prob's and
** partial likelihoods in the temporary regraft structure.
*/
for (i = 0; i < 3; i++)
{
v_tmp->b[i]->l = l_est[i];
Update_PMat_At_Given_Edge (v_tmp->b[i], tree);
}
Update_P_Lk (tree, v_tmp->b[0], v_tmp);
/*
** Calculate the change in likelihood locally. Save it and the estimated edge
** lengths in the current candidate in the list.
*/
new_lk = Lk_At_Given_Edge (v_tmp->b[0],tree);
rgrft_cand[cand]->delta_lk = new_lk - cur_lk;
rgrft_cand[cand]->rgrft_rank = cand;
rgrft_cand[cand]->optim_rank = -1;
rgrft_cand[cand]->globl_rank = -1;
rgrft_cand[cand]->l_connect = l_connect;
for (i = 0; i < 3; i++)
{
rgrft_cand[cand]->l_est[i] = v_tmp->b[i]->l;
}
if (rgrft_cand[cand]->delta_lk > best_d_lk)
{
best_d_lk = rgrft_cand[cand]->delta_lk;
best_cand = cand;
}
/*
** Reset the partial likelihoods along the path.
*/
for (pat = 0; pat < tree->n_pattern; pat++)
{
p_sum[pat] = sum_scale_tmp[pat];
for (cat = 0; cat < tree->mod->n_catg; cat++)
{
for (ste = 0; ste < tree->mod->ns; ste++)
{
p_lk[pat*dim1+cat*dim2+ste] = p_lk_tmp[pat*dim1+cat*dim2+ste];
}
}
}
n = rgrft_cand[cand]->dist;
for (i = 2; i <= n; i++)
{
for (j = 0; j < 3; j++)
{
if (rgrft_cand[cand]->path[i]->v[j] == rgrft_cand[cand]->path[i+1])
{
e_tmp = rgrft_cand[cand]->path[i]->b[j];
break;
}
}
Update_P_Lk (tree, e_tmp, rgrft_cand[cand]->path[i]);
}
}
/*
** If the best candidate is within the tree->mod->s_opt->wim_n_optim best ones, save it in the list of
** optimization candidates.
*/
if (rgrft_cand[best_cand]->delta_lk > optim_cand[tree->mod->s_opt->wim_n_optim-1]->delta_lk)
{
i = tree->mod->s_opt->wim_n_optim-1;
optim_cand[i]->v_prune = rgrft_cand[best_cand]->v_prune;
optim_cand[i]->u_prune = rgrft_cand[best_cand]->u_prune;
optim_cand[i]->v_n = rgrft_cand[best_cand]->v_n;
optim_cand[i]->v_nx1 = rgrft_cand[best_cand]->v_nx1;
optim_cand[i]->u_n = rgrft_cand[best_cand]->u_n;
optim_cand[i]->e_prune = rgrft_cand[best_cand]->e_prune;
optim_cand[i]->e_regraft = rgrft_cand[best_cand]->e_regraft;
optim_cand[i]->d_L = rgrft_cand[best_cand]->d_L;
optim_cand[i]->dist = rgrft_cand[best_cand]->dist;
optim_cand[i]->rgrft_rank = rgrft_cand[best_cand]->rgrft_rank;
optim_cand[i]->optim_rank = rgrft_cand[best_cand]->optim_rank;
optim_cand[i]->globl_rank = rgrft_cand[best_cand]->globl_rank;
optim_cand[i]->l_connect = rgrft_cand[best_cand]->l_connect;
for (j = 0; j < 3; j++)
{
optim_cand[i]->l_est[j] = rgrft_cand[best_cand]->l_est[j];
}
optim_cand[i]->delta_lk = rgrft_cand[best_cand]->delta_lk;
/*
** Move the candidate to the appropriate position in the list, so the list
** remains sorted in decreasing delta_Lk value.
*/
while ((i > 0) && (optim_cand[i]->delta_lk > optim_cand[i-1]->delta_lk))
{
tmp_cand = optim_cand[i];
optim_cand[i] = optim_cand[i-1];
optim_cand[i-1] = tmp_cand;
i--;
}
}
/*
** Swap back the relevant partial likelihoods at the prune site.
*/
if (v_prune == v_prune->b[d1]->left)
{
v_prune->b[d1]->p_lk_left = p_lk1_tmp;
}
else
{
v_prune->b[d1]->p_lk_rght = p_lk1_tmp;
}
if (v_prune == v_prune->b[d2]->left)
{
v_prune->b[d2]->p_lk_left = p_lk2_tmp;
}
else
{
v_prune->b[d2]->p_lk_rght = p_lk2_tmp;
}
/*
** Reset the relevant t_edge lengths and transition prob's at the prune site.
*/
v_prune->b[d1]->l = v_prune->b[d1]->l_old;
v_prune->b[d2]->l = v_prune->b[d2]->l_old;
Update_PMat_At_Given_Edge (v_prune->b[d1], tree);
Update_PMat_At_Given_Edge (v_prune->b[d2], tree);
/*
** Return the best candidate.
*/
return (best_cand);
}
/*
** Make_Move: Perform an actual SPR move and calculate the new likelihood.
**
** Parameters:
** - candidate: The candidate move to perform.
** - tree: The tree on which to perform the move.
**
*/
void Make_Move (_move_ *move, int type, t_tree *tree)
{
int i;
t_node *v_prune, *u_prune, *v_n, *root;
t_edge *e_prune, *e_regraft, *e_connect, *e_avail;
phydbl new_lk;
/*
** Get the relevant nodes and edges.
*/
v_prune = move->v_prune;
u_prune = move->u_prune;
v_n = move->v_n;
e_prune = move->e_prune;
e_regraft = move->e_regraft;
/* PhyML_Printf (" making move: %d -> %d (%f)\n", e_prune->num, e_regraft->num, move->delta_lk); */
/*
** Perform the move and set t_edge lengths.
*/
Prune (e_prune, v_prune, &(e_connect), &(e_avail), tree);
Regraft (e_regraft, v_prune, e_avail, tree);
e_connect->l = move->l_connect;
for (i = 0; i < 3; i++)
{
if (v_prune->v[i] == u_prune)
{
v_prune->b[i]->l = move->l_est[0];
}
else if (v_prune->v[i] == v_n)
{
v_prune->b[i]->l = move->l_est[1];
}
else
{
v_prune->b[i]->l = move->l_est[2];
}
}
if(type > 0) /* local or global move */
{
Restore_Br_Len(tree);
}
/*
** Calculate the new likelihood.
*/
tree->both_sides = 1;
new_lk = Lk (tree);
if(tree->c_lnL < cur_lk-tree->mod->s_opt->min_diff_lk_local)
{
PhyML_Printf("\n. tree->c_lnL = %f cur_lk = %f",tree->c_lnL,cur_lk);
PhyML_Printf("\n. Err in file %s at line %d\n",__FILE__,__LINE__);
Warn_And_Exit("");
}
cur_lk = new_lk;
/*
** Recalculate the average distances between all (non-overlapping) subtrees.
*/
root = tree->t_nodes[0];
PostOrder_v (tree, root->v[0], root->b[0]);
}
/*
** Find_Optim_Local: Perform local t_edge length optimization on the candidates in the
** optimization list, and return the first one that gives an
** improvement in likelihood.
**
** Parameters:
** - tree: The tree on which to check the moves.
**
** Returns:
** If an improvement was found: The candidate that gives the improvement.
** Otherwise: -1.
*/
int Find_Optim_Local (t_tree *tree)
{
int best_cand, cand, i;
t_node *v_prune, *u_prune, *v_n;
t_edge *e_prune, *e_regraft, *e_connect, *e_avail;
phydbl max_change, new_lk;
_move_ *move, *tmp_cand;
/*
** Try all candidate moves starting from the first one.
*/
best_cand = -1;
max_change = 1.0/BIG;
for(cand = 0; cand < tree->mod->s_opt->wim_n_optim; cand++)
{
move = optim_cand[cand];
if(move->delta_lk > -1.0*BIG)
{
/*
** Get the relevant nodes and edges.
*/
v_prune = move->v_prune;
u_prune = move->u_prune;
v_n = move->v_n;
e_prune = move->e_prune;
e_regraft = move->e_regraft;
/*
** Perform the move and set t_edge lengths.
*/
Prune (e_prune, v_prune, &(e_connect), &(e_avail), tree);
Regraft (e_regraft, v_prune, e_avail, tree);
e_connect->l_old = e_connect->l;
e_connect->l = move->l_connect;
for (i = 0; i < 3; i++)
{
v_prune->b[i]->l_old = v_prune->b[i]->l;
if (v_prune->v[i] == u_prune)
{
v_prune->b[i]->l = move->l_est[0];
}
else if (v_prune->v[i] == v_n)
{
v_prune->b[i]->l = move->l_est[1];
}
else
{
v_prune->b[i]->l = move->l_est[2];
}
}
tree->both_sides = 1;
Lk(tree); // Not sure anymore whether this is required...
/*
** Use Brent optimization on the relevant edges at the regraft position
** and calculate the new likelihood value.
*/
Br_Len_Brent (10.*(v_prune->b[0]->l), v_prune->b[0]->l, tree->mod->l_min, 1.e-10,
v_prune->b[0], tree, 250, 0);
Br_Len_Brent (10.*(v_prune->b[1]->l), v_prune->b[1]->l, tree->mod->l_min, 1.e-10,
v_prune->b[1], tree, 250, 0);
Br_Len_Brent (10.*(v_prune->b[2]->l), v_prune->b[2]->l, tree->mod->l_min, 1.e-10,
v_prune->b[2], tree, 250, 0);
/* Update_PMat_At_Given_Edge (v_prune->b[0], tree); */
/* Update_PMat_At_Given_Edge (v_prune->b[1], tree); */
/* Update_PMat_At_Given_Edge (v_prune->b[2], tree); */
Update_P_Lk (tree, v_prune->b[0], v_prune);
new_lk = Lk_At_Given_Edge (v_prune->b[0],tree);
/* PhyML_Printf("\n. local new_lk = %f",new_lk); */
/*
** Save the change in likelihood and move the current candidate to the
** appropriate place in the list.
*/
move->delta_lk = new_lk - cur_lk;
move->optim_rank = cand;
i = cand;
while ((i > 0) && (optim_cand[i]->delta_lk > optim_cand[i-1]->delta_lk))
{
tmp_cand = optim_cand[i];
optim_cand[i] = optim_cand[i-1];
optim_cand[i-1] = tmp_cand;
i--;
}
if (move->delta_lk > max_change)
{
best_cand = i;
max_change = move->delta_lk;
Record_Br_Len(tree);
}
/*
** Undo the move again.
*/
Prune (e_prune, v_prune, &(e_regraft), &(e_avail), tree);
Regraft (e_connect, v_prune, e_avail, tree);
e_regraft->l = e_regraft->l_old;
for (i = 0; i < 3; i++)
{
v_prune->b[i]->l = v_prune->b[i]->l_old;
}
tree->both_sides = 1;
Lk(tree);
nr_loc++;
/* PhyML_Printf("\n. local back to = %f",tree->c_lnL); */
}
else
{
break;
}
/*
** If an improvement was found, forget the other candidates...
*/
if (best_cand >= 0)
{
break;
}
}
/*
** Return the best candidate.
*/
return (best_cand);
}
/*
** Find_Optim_Globl: Perform global t_edge length optimization on the candidates in the
** optimization list, and return the first one that gives an
** improvement in likelihood.
**
** Parameters:
** - tree: The tree on which to check the moves.
**
** Returns:
** If an improvement is found: The candidate that gives the improvement.
** Otherwise: -1.
*/
int Find_Optim_Globl (t_tree *tree)
{
int best_cand, cand, i;
t_node *v_prune, *u_prune, *v_n, *root;
t_edge *e_prune, *e_regraft, *e_connect, *e_avail;
phydbl max_change, new_lk;
_move_ *move;
/*
** Try all moves.
*/
best_cand = -1;
max_change = 1.0/BIG;
for (cand = 0; cand < tree->mod->s_opt->wim_n_globl; cand++)
{
move = optim_cand[cand];
if (move->delta_lk > -1.0*BIG)
{
Record_Br_Len(tree);
/*
** Get the relevant nodes and edges.
*/
v_prune = move->v_prune;
u_prune = move->u_prune;
v_n = move->v_n;
e_prune = move->e_prune;
e_regraft = move->e_regraft;
/*
** Perform the move and optimize all t_edge lengths.
*/
Prune (e_prune, v_prune, &(e_connect), &(e_avail), tree);
Regraft (e_regraft, v_prune, e_avail, tree);
e_connect->l_old = e_connect->l;
e_connect->l = move->l_connect;
for (i = 0; i < 3; i++)
{
v_prune->b[i]->l_old = v_prune->b[i]->l;
if (v_prune->v[i] == u_prune)
{
v_prune->b[i]->l = move->l_est[0];
}
else if (v_prune->v[i] == v_n)
{
v_prune->b[i]->l = move->l_est[1];
}
else
{
v_prune->b[i]->l = move->l_est[2];
}
}
tree->both_sides = 1;
Lk(tree);
root = tree->t_nodes[0];
Optimize_Br_Len_Serie (root, root->v[0], root->b[0], tree, tree->data);
tree->both_sides = 1;
new_lk = Lk (tree);
/* PhyML_Printf("\n. global new_lk = %f\n",tree->c_lnL); */
/*
** Save the change in likelihood and undo the move.
*/
move->delta_lk = new_lk - cur_lk;
move->globl_rank = cand;
if (move->delta_lk > max_change)
{
best_cand = cand;
max_change = move->delta_lk;
Record_Br_Len(tree);
}
Prune (e_prune, v_prune, &(e_regraft), &(e_avail), tree);
Regraft (e_connect, v_prune, e_avail, tree);
e_regraft->l = e_regraft->l_old;
for (i = 0; i < 3; i++)
{
v_prune->b[i]->l = v_prune->b[i]->l_old;
}
tree->both_sides = 1;
Restore_Br_Len(tree);
Lk(tree);
nr_glb++;
/* PhyML_Printf("\n. global back to = %f",tree->c_lnL); */
}
else break;
/*
** If an improvement was found, forget the other candidates...
*/
if (best_cand >= 0) break;
}
/*
** Return the best candidate.
*/
return (best_cand);
}
/*
** Prune: Prune the subtree at a certain t_edge and node. Note that edge
** lengths are not set and partial likelihoods are not updated.
**
** Parameters:
** - e: The t_edge at which to prune the subtree.
** - v: The t_node adjacent to t_edge e which forms the root of the subtree.
** - e_connect: An t_edge pointer which will point to the t_edge that was left
** after pruning.
** - e_avail: The t_edge that is "left over" and should be used in the
** regrafting step.
** - tree: The tree on which the pruning is done.
**
**
**
** \ /
** o
** |
** | e --> subtree to be pruned
** |
** o v
** / \
** e1/ \e2
** / \
** o o
** u1 u2 --> such that u1->num < u2->num
*/
void Prune (t_edge *e, t_node *v, t_edge **e_connect, t_edge **e_avail, t_tree *tree)
{
int dir0, dir1, dir2, v0, v1, v2, tmp_dir, i, j, k;
t_node *u1, *u2, *tmp_node;
t_edge *e1, *e2;
int *sum_scale_f;
phydbl *p_lk;
int dim1, dim2;
dim1 = tree->mod->ns * tree->mod->n_catg;
dim2 = tree->mod->ns;
/*
** Get the relevant directions, nodes and edges.
** Make sure that t_node u1 is the t_node with the smaller number.
*/
dir0 = -1;
for (i = 0; i < 3; i++)
{
if (v->b[i] == e)
{
dir0 = i;
break;
}
}
dir1 = (dir0 + 1) % 3;
dir2 = 3 - dir0 - dir1;
u1 = v->v[dir1];
u2 = v->v[dir2];
if (u1->num > u2->num)
{
tmp_node = u1;
u1 = u2;
u2 = tmp_node;
tmp_dir = dir1;
dir1 = dir2;
dir2 = tmp_dir;
}
e1 = v->b[dir1];
e2 = v->b[dir2];
/*
** Detach t_node v from the tree.
*/
v->v[dir1] = NULL;
v->v[dir2] = NULL;
v->b[dir1] = NULL;
v->b[dir2] = NULL;
/*
** Connect nodes u1 and u2 via t_edge e1 and copy relevant partial likelihoods.
*/
if (u2 == e2->left)
{
v0 = e2->l_r;
v1 = e2->l_v1;
v2 = e2->l_v2;
sum_scale_f = e2->sum_scale_left;
p_lk = e2->p_lk_left;
}
else
{
v0 = e2->r_l;
v1 = e2->r_v1;
v2 = e2->r_v2;
sum_scale_f = e2->sum_scale_rght;
p_lk = e2->p_lk_rght;
}
if (u1 == e1->left)
{
e1->rght = u2;
e1->r_l = v0;
e1->r_v1 = v1;
e1->r_v2 = v2;
for (i = 0; i < tree->n_pattern; i++)
{
e1->sum_scale_rght[i] = sum_scale_f[i];
for (j = 0; j < tree->mod->n_catg; j++)
{
for (k = 0; k < tree->mod->ns; k++)
{
e1->p_lk_rght[i*dim1+j*dim2+k] = p_lk[i*dim1+j*dim2+k];
}
}
}
}
else
{
e1->left = u2;
e1->l_r = v0;
e1->l_v1 = v1;
e1->l_v2 = v2;
for (i = 0; i < tree->n_pattern; i++)
{
e1->sum_scale_left[i] = sum_scale_f[i];
for (j = 0; j < tree->mod->n_catg; j++)
{
for (k = 0; k < tree->mod->ns; k++)
{
e1->p_lk_left[i*dim1+j*dim2+k] = p_lk[i*dim1+j*dim2+k];
}
}
}
}
for (i = 0; i < 3; i++)
{
if (u1->v[i] == v)
{
u1->v[i] = u2;
}
if (u2->v[i] == v)
{
u2->v[i] = u1;
u2->b[i] = e1;
u2->l[i] = e1->l;
}
}
/*
** Make sure that a possible tip t_node is still on the right side.
*/
if (e1->left->tax)
{
/*
** Swap left and right.
*/
tmp_node = e1->left;
e1->left = e1->rght;
e1->rght = tmp_node;
tmp_dir = e1->l_r;
e1->l_r = e1->r_l;
e1->r_l = tmp_dir;
tmp_dir = e1->l_v1;
e1->l_v1 = e1->r_v1;
e1->r_v1 = tmp_dir;
tmp_dir = e1->l_v2;
e1->l_v2 = e1->r_v2;
e1->r_v2 = tmp_dir;
p_lk = e1->p_lk_left;
e1->p_lk_left = e1->p_lk_rght;
e1->p_lk_rght = p_lk;
sum_scale_f = e1->sum_scale_left;
e1->sum_scale_left = e1->sum_scale_rght;
e1->sum_scale_rght = sum_scale_f;
}
/*
** Set the connecting and available edges.
*/
*(e_connect) = e1;
*(e_avail) = e2;
}
/*
** Regraft: Regraft a subtree at a certain edge. Note that t_edge lengths
** are not set and partial likelihoods are not updated.
**
** Parameters:
** - e: The t_edge to regraft the subtree on.
** - v: The root of the subtree to regraft.
** - avail: A previously deleted t_edge now available for insertion again.
** - tree: The tree on which the regrafting is done.
**
**
** \ /
** o
** |
** | --> subtree to regraft
** |
** o v
**
** o--------o
** u1 e u2 --> such that u1->num < u2->num
*/
void Regraft (t_edge *e, t_node *v, t_edge *avail, t_tree *tree)
{
int dir0, dir1, dir2, i, j, k;
int *sum_scale_f;
phydbl *p_lk;
t_node *u1, *u2;
int dim1, dim2;
dim1 = tree->mod->ns * tree->mod->n_catg;
dim2 = tree->mod->ns ;
/*
** Get the relevant directions and nodes.
*/
dir0 = -1;
for (i = 0; i < 3; i++)
{
if (v->b[i] != NULL)
{
dir0 = i;
break;
}
}
dir1 = (dir0 + 1) % 3;
dir2 = 3 - dir0 - dir1;
if (e->left->num < e->rght->num)
{
u1 = e->left;
u2 = e->rght;
sum_scale_f = e->sum_scale_rght;
p_lk = e->p_lk_rght;
}
else
{
u1 = e->rght;
u2 = e->left;
sum_scale_f = e->sum_scale_left;
p_lk = e->p_lk_left;
}
/*
** Connect nodes v and u2 via the available t_edge 'avail' and copy the
** relevant partial likelihood.
** (We want to do this first, cos we need some of the values of edge
** e before changing them below).
*/
avail->left = v;
avail->rght = u2;
avail->l_r = dir2;
avail->l_v1 = dir0;
avail->l_v2 = dir1;
v->v[dir2] = u2;
v->b[dir2] = avail;
for (i = 0; i < 3; i++)
{
if (e == u2->b[i])
{
u2->v[i] = v;
u2->b[i] = avail;
avail->r_l = i;
avail->r_v1 = (i + 1) % 3;
avail->r_v2 = 3 - i - avail->r_v1;
break;
}
}
for (i = 0; i < tree->n_pattern; i++)
{
avail->sum_scale_rght[i] = sum_scale_f[i];
for (j = 0; j < tree->mod->n_catg; j++)
{
for (k = 0; k < tree->mod->ns; k++)
{
avail->p_lk_rght[i*dim1+j*dim2+k] = p_lk[i*dim1+j*dim2+k];
}
}
}
/*
** Connect nodes v and u1 via t_edge e.
*/
if (u1 == e->left)
{
e->rght = v;
e->r_l = dir1;
e->r_v1 = dir0;
e->r_v2 = dir2;
}
else
{
e->left = v;
e->l_r = dir1;
e->l_v1 = dir0;
e->l_v2 = dir2;
}
v->v[dir1] = u1;
v->b[dir1] = e;
for (i = 0; i < 3; i++)
{
if (u1->v[i] == u2)
{
u1->v[i] = v;
break;
}
}
}
/*
** PostOrder_v: Recursively visit all nodes v in postorder to calculate
** the average distance between subtrees.
**
** Parameters:
** - tree: The tree for which to calculate the average distances.
** - v: The current node.
** - e: The t_edge we came from.
*/
void PostOrder_v (t_tree *tree, t_node *v, t_edge *e)
{
int i;
t_node *w;
/*
** If v is not a taxon, recurse.
*/
if (!v->tax)
{
for (i = 0; i < 3; i++)
{
if (v->b[i] != e)
{
PostOrder_v (tree, v->v[i], v->b[i]);
}
}
}
/*
** Recurse over all nodes w not in the current subtree and calculate
** the average distance between the current subtree and all others.
*/
if (v == e->left)
{
w = e->rght;
}
else
{
w = e->left;
}
PostOrder_w (tree, v, e, w, e);
}
/*
** PostOrder_w: Recursively visit all nodes w not in the subtree of v in
** postorder and calculate the average distance between the
** subtree of v and all others.
**
** Parameters:
** - tree: The tree for which to calculate the average distances.
** - v: The root t_node of the first subtree.
** - v_e: The t_edge adjacent to the first subtree.
** - w: The current node.
** - e: The t_edge we came from.
*/
void PostOrder_w (t_tree *tree, t_node *v, t_edge *v_e, t_node *w, t_edge *e)
{
int i;
t_node *w1, *w2, *v1, *v2;
/*
** If w is not a taxon, recurse.
*/
if (!w->tax)
{
for (i = 0; i < 3; i++)
{
if (w->b[i] != e)
{
PostOrder_w (tree, v, v_e, w->v[i], w->b[i]);
}
}
}
/*
** Calculate the average distance between the subtrees defined by
** nodes v and w.
*/
if (v->tax && w->tax)
{
subtree_dist[v->num][w->num] = seq_dist->dist[v->num][w->num];
}
else if (!v->tax)
{
v1 = v2 = NULL;
for (i = 0; i < 3; i++)
{
if (v->b[i] != v_e)
{
if (v1 == NULL)
{
v1 = v->v[i];
}
else
{
v2 = v->v[i];
}
}
}
subtree_dist[v->num][w->num] = 0.5*(subtree_dist[v1->num][w->num] +
subtree_dist[v2->num][w->num]);
}
else
{
w1 = w2 = NULL;
for (i = 0; i < 3; i++)
{
if (w->b[i] != e)
{
if (w1 == NULL)
{
w1 = w->v[i];
}
else
{
w2 = w->v[i];
}
}
}
subtree_dist[v->num][w->num] = 0.5*(subtree_dist[v->num][w1->num] +
subtree_dist[v->num][w2->num]);
}
subtree_dist[w->num][v->num] = subtree_dist[v->num][w->num];
}
/*********************************************************/
/*********************************************************/
/*********************************************************/
/* Below are my functions for SPR search (Stephane Guindon, 2007) */
void Randomize_Spr_List(t_tree *tree)
{
int i,j;
spr *buff;
For(i,tree->size_spr_list)
{
j = (int)FLOOR(rand()/(RAND_MAX+1.)*tree->size_spr_list);
buff = tree->spr_list[i];
tree->spr_list[i] = tree->spr_list[j];
tree->spr_list[j] = buff;
}
}
/*********************************************************/
int Spr(phydbl init_lnL, t_tree *tree)
{
int br;
int pars_diff, max_pars_diff, new_pars, old_pars;
t_edge *b;
tree->both_sides = 1;
pars_diff = -1;
max_pars_diff = -1;
new_pars = -1;
old_pars = -1;
Reset_Spr_List(tree);
For(br,2*tree->n_otu-3)
{
b = tree->t_edges[br];
old_pars = tree->c_pars;
Spr_Subtree(b,b->left,tree);
new_pars = tree->c_pars;
pars_diff = new_pars - old_pars;
if(pars_diff > max_pars_diff) max_pars_diff = pars_diff;
old_pars = tree->c_pars;
Spr_Subtree(b,b->rght,tree);
new_pars = tree->c_pars;
pars_diff = new_pars - old_pars;
if(pars_diff > max_pars_diff) max_pars_diff = pars_diff;
}
/* tree->mod->s_opt->pars_thresh = MAX(5,max_pars_diff); */
return 1;
}
/*********************************************************/
void Spr_Subtree(t_edge *b, t_node *link, t_tree *tree)
{
int i;
int n_moves_pars, n_moves, curr_pars, min_pars, best_move;
spr *best_pars_move;
t_edge *target, *residual;
int ret_val;
best_move = -1;
tree->n_moves = 0;
curr_pars = tree->c_pars;
ret_val = 0;
if((link != b->left) && (link != b->rght))
{
PhyML_Printf("\n. Err in file %s at line %d\n",__FILE__,__LINE__);
Warn_And_Exit("");
}
else
{
/* printf("\n. -1"); fflush(NULL); */
/* if(!Check_Lk_At_Given_Edge(tree)) Exit("\n"); */
if(!link->tax) Test_All_Spr_Targets(b,link,tree);
/* printf("\n. 0"); fflush(NULL); */
/* if(!Check_Lk_At_Given_Edge(tree)) Exit("\n"); */
if(tree->n_moves)
{
n_moves_pars = 0;
n_moves = 0;
For(i,tree->n_moves)
if(curr_pars - tree->spr_list[i]->pars >= -tree->mod->s_opt->pars_thresh)
n_moves_pars++;
For(i,tree->n_moves)
{
n_moves++;
/* if(n_moves > 15) break; */
if(n_moves > 5) break;
if(tree->spr_list[i]->lnL < tree->best_lnL - 2. * tree->mod->s_opt->max_delta_lnL_spr) break;
}
if(!tree->mod->s_opt->spr_lnL) n_moves = n_moves_pars;
if(!tree->io->fp_in_constraint_tree) n_moves = MAX(1,n_moves);
n_moves = MIN(n_moves,2*tree->n_otu-3);
if(tree->mod->s_opt->spr_pars)
{
if(tree->io->fp_in_constraint_tree)
{
PhyML_Printf("\n. Err in file %s at line %d\n",__FILE__,__LINE__);
Warn_And_Exit("");
}
min_pars = 1E+8;
best_pars_move = NULL;
For(i,n_moves)
if(tree->spr_list[i]->pars < min_pars)
{
best_pars_move = tree->spr_list[i];
min_pars = tree->spr_list[i]->pars;
}
if(best_pars_move->pars < tree->best_pars)
{
Prune_Subtree(best_pars_move->n_link,best_pars_move->n_opp_to_link,&target,&residual,tree);
Graft_Subtree(best_pars_move->b_target,best_pars_move->n_link,residual,tree);
tree->both_sides = 1;
Pars(tree);
tree->best_pars = tree->c_pars;
if(tree->best_pars != best_pars_move->pars)
{
PhyML_Printf("\n. best_pars = %d move_pars = %d",tree->best_pars,best_pars_move->pars);
PhyML_Printf("\n. Err in file %s at line %d\n",__FILE__,__LINE__);
Warn_And_Exit("");
}
tree->n_improvements++;
}
else
Pars(tree);
}
else
{
/* tree->both_sides = YES; */
/* Lk(tree); */
/* tree->both_sides = NO; */
/* printf("\n. 1"); fflush(NULL); */
/* if(!Check_Lk_At_Given_Edge(tree)) Exit("\n"); */
best_move = Evaluate_List_Of_Regraft_Pos_Triple(tree->spr_list,n_moves,tree);
/* printf("\n. 2"); fflush(NULL); */
/* if(!Check_Lk_At_Given_Edge(tree)) Exit("\n"); */
if((best_move > -1) && (tree->spr_list[best_move]->lnL > tree->best_lnL + tree->mod->s_opt->min_diff_lk_move))
/* if((best_move > -1) && (tree->spr_list[best_move]->lnL > tree->best_lnL - tree->mod->s_opt->max_delta_lnL_spr)) */
{
Try_One_Spr_Move_Triple(tree->spr_list[best_move],tree);
ret_val = 1;
}
else
{
Pars(tree);
/* tree->both_sides = YES; */
/* Lk(tree); */
/* tree->both_sides = NO; */
}
/* printf("\n. 3"); fflush(NULL); */
/* if(!Check_Lk_At_Given_Edge(tree)) Exit("\n"); */
}
}
Reset_Spr_List(tree);
}
}
/*********************************************************/
int Test_All_Spr_Targets(t_edge *b_pulled, t_node *n_link, t_tree *tree)
{
t_node *n_opp_to_link,*n_v1,*n_v2,*n_up;
t_edge *b_target,*b_residual;
int i,dir1,dir2;
phydbl init_len_v1, init_len_v2, init_len_pulled;
int best_found,approx;
phydbl init_lnL;
init_lnL = tree->c_lnL;
n_up = NULL;
b_target = b_residual = NULL;
n_opp_to_link = (n_link == b_pulled->rght)?(b_pulled->left):(b_pulled->rght);
approx = 1;
init_len_pulled = b_pulled->l;
dir1 = dir2 = -1;
For(i,3)
if(n_link->v[i] != n_opp_to_link)
{
if(dir1<0) dir1 = i;
else dir2 = i;
}
if(n_link->v[dir1]->num < n_link->v[dir2]->num)
{
n_v1 = n_link->v[dir1];
n_v2 = n_link->v[dir2];
init_len_v1 = n_link->b[dir1]->l;
init_len_v2 = n_link->b[dir2]->l;
}
else
{
n_v1 = n_link->v[dir2];
n_v2 = n_link->v[dir1];
init_len_v1 = n_link->b[dir2]->l;
init_len_v2 = n_link->b[dir1]->l;
}
if(!(n_v1->tax && n_v2->tax)) /* Pruning is meaningless otherwise */
{
Prune_Subtree(n_link,n_opp_to_link,&b_target,&b_residual,tree);
if(tree->mod->s_opt->spr_lnL)
{
Fast_Br_Len(b_target,tree,0);
/* Update_PMat_At_Given_Edge(b_target,tree); */
}
best_found = 0;
tree->depth_curr_path = 0;
tree->curr_path[0] = b_target->left;
Test_One_Spr_Target_Recur(b_target->rght,
b_target->left,
b_pulled,n_link,b_residual,&best_found,tree);
tree->depth_curr_path = 0;
tree->curr_path[0] = b_target->rght;
Test_One_Spr_Target_Recur(b_target->left,
b_target->rght,
b_pulled,n_link,b_residual,&best_found,tree);
Graft_Subtree(b_target,n_link,b_residual,tree);
if((n_link->v[dir1] != n_v1) || (n_link->v[dir2] != n_v2))
PhyML_Printf("\n. Warning : -- SWITCH NEEDED -- ! \n");
n_link->b[dir1]->l = init_len_v1;
n_link->b[dir2]->l = init_len_v2;
b_pulled->l = init_len_pulled;
Update_PMat_At_Given_Edge(n_link->b[dir1],tree);
Update_PMat_At_Given_Edge(n_link->b[dir2],tree);
Update_PMat_At_Given_Edge(b_pulled,tree);
/* if(tree->mod->s_opt->spr_lnL) */
/* { */
/* I don't understand why this is required when spr_lnL = NO, but it is... */
tree->update_alias_subpatt = YES;
Update_P_Lk(tree,b_pulled, n_link);
Update_P_Lk(tree,b_target, n_link);
Update_P_Lk(tree,b_residual,n_link);
tree->update_alias_subpatt = NO;
/* } */
/* else */
/* { */
Update_P_Pars(tree,b_pulled, n_link);
Update_P_Pars(tree,b_target, n_link);
Update_P_Pars(tree,b_residual,n_link);
/* } */
For(i,3)
if(n_link->v[i] != n_opp_to_link)
{
if(tree->mod->s_opt->spr_lnL)
{
tree->update_alias_subpatt = YES;
Pre_Order_Lk(n_link,n_link->v[i],tree);
tree->update_alias_subpatt = NO;
}
else
Pre_Order_Pars(n_link,n_link->v[i],tree);
}
}
tree->c_lnL = init_lnL;
return 0;
}
/*********************************************************/
void Test_One_Spr_Target_Recur(t_node *a, t_node *d, t_edge *pulled, t_node *link, t_edge *residual, int *best_found, t_tree *tree)
{
int i;
if(*best_found) return;
if(d->tax) return;
else
{
phydbl move_lnL;
For(i,3)
{
if(d->v[i] != a)
{
if(tree->mod->s_opt->spr_lnL)
{
tree->update_alias_subpatt = YES;
Update_P_Lk(tree,d->b[i],d);
tree->update_alias_subpatt = NO;
}
else
Update_P_Pars(tree,d->b[i],d);
tree->depth_curr_path++;
tree->curr_path[tree->depth_curr_path] = d->v[i];
if((tree->depth_curr_path <= tree->mod->s_opt->max_depth_path) &&
(tree->depth_curr_path >= tree->mod->s_opt->min_depth_path))
{
move_lnL = Test_One_Spr_Target(d->b[i],pulled,link,residual,tree);
if(move_lnL > tree->best_lnL + tree->mod->s_opt->min_diff_lk_move)
{
*best_found = 1;
}
}
if(tree->depth_curr_path < tree->mod->s_opt->max_depth_path)
Test_One_Spr_Target_Recur(d,d->v[i],pulled,link,residual,best_found,tree);
tree->depth_curr_path--;
}
}
}
}
/*********************************************************/
phydbl Test_One_Spr_Target(t_edge *b_target, t_edge *b_arrow, t_node *n_link, t_edge *b_residual, t_tree *tree)
{
phydbl init_target_len, init_arrow_len, init_residual_len;
int i,dir_v0,dir_v1,dir_v2;
phydbl l0,l1,l2;
t_node *v1, *v2;
phydbl init_lnL, move_lnL;
int init_pars,move_pars;
int approx;
tree->n_moves++;
approx = 1;
move_lnL = UNLIKELY;
init_lnL = tree->c_lnL;
init_pars = tree->c_pars;
Graft_Subtree(b_target,n_link,b_residual,tree);
init_target_len = b_target->l;
init_arrow_len = b_arrow->l;
init_residual_len = b_residual->l;
if(tree->mod->s_opt->spr_lnL)
{
tree->update_alias_subpatt = YES;
/* move_lnL = Triple_Dist(n_link,tree,1); */
Update_PMat_At_Given_Edge(b_target,tree);
Update_PMat_At_Given_Edge(b_arrow,tree);
Update_P_Lk(tree,b_residual,n_link);
move_lnL = Lk_At_Given_Edge(b_residual,tree);
tree->update_alias_subpatt = NO;
}
else
{
Update_P_Pars(tree,b_residual,n_link);
move_pars = Pars_At_Given_Edge(b_residual,tree);
}
v1 = (b_residual->left == n_link)?(b_residual->rght):(b_residual->left);
v2 = (b_target->left == n_link)?(b_target->rght):(b_target->left);
dir_v1 = dir_v2 = dir_v0 = -1;
For(i,3)
{
if(n_link->v[i] == v1) dir_v1 = i;
else if(n_link->v[i] == v2) dir_v2 = i;
else dir_v0 = i;
}
l0 = n_link->b[dir_v0]->l;
if(n_link->v[dir_v1]->num > n_link->v[dir_v2]->num)
{
l1 = n_link->b[dir_v2]->l;
l2 = n_link->b[dir_v1]->l;
}
else
{
l1 = n_link->b[dir_v1]->l;
l2 = n_link->b[dir_v2]->l;
}
For(i,tree->depth_curr_path+1) tree->spr_list[tree->size_spr_list]->path[i] = tree->curr_path[i];
tree->spr_list[tree->size_spr_list]->depth_path = tree->depth_curr_path;
tree->spr_list[tree->size_spr_list]->pars = tree->c_pars;
tree->spr_list[tree->size_spr_list]->lnL = tree->c_lnL;
tree->spr_list[tree->size_spr_list]->b_target = b_target;
tree->spr_list[tree->size_spr_list]->n_link = n_link;
tree->spr_list[tree->size_spr_list]->n_opp_to_link = (n_link==b_arrow->left)?(b_arrow->rght):(b_arrow->left);
tree->spr_list[tree->size_spr_list]->b_opp_to_link = b_arrow;
tree->spr_list[tree->size_spr_list]->l0 = l0;
tree->spr_list[tree->size_spr_list]->l1 = l1;
tree->spr_list[tree->size_spr_list]->l2 = l2;
tree->spr_list[tree->size_spr_list]->dist = b_target->topo_dist_btw_edges;
Include_One_Spr_To_List_Of_Spr(tree->spr_list[tree->size_spr_list],tree);
b_target->l = init_target_len;
b_arrow->l = init_arrow_len;
b_residual->l = init_residual_len;
Prune_Subtree(n_link,
(n_link==b_arrow->left)?(b_arrow->rght):(b_arrow->left),
&b_target,
&b_residual,
tree);
if(tree->mod->s_opt->spr_lnL) Update_PMat_At_Given_Edge(b_target,tree);
tree->c_lnL = init_lnL;
tree->c_pars = init_pars;
return move_lnL;
}
/*********************************************************/
void Speed_Spr_Loop(t_tree *tree)
{
phydbl lk_old;
int init_thresh;
init_thresh = tree->mod->s_opt->pars_thresh;
tree->best_pars = 1E+8;
tree->mod->s_opt->spr_lnL = 0;
tree->mod->s_opt->spr_pars = 0;
tree->mod->s_opt->quickdirty = 0;
if((tree->mod->s_opt->print) && (!tree->io->quiet)) PhyML_Printf("\n\n. Maximizing likelihood (using SPR moves)...\n");
SPR_Shuffle(tree);
Optimiz_All_Free_Param(tree,(tree->io->quiet)?(0):(tree->mod->s_opt->print));
tree->best_lnL = tree->c_lnL;
/*****************************/
lk_old = UNLIKELY;
tree->mod->s_opt->br_len_in_spr = 10;
/* tree->mod->s_opt->max_delta_lnL_spr = (tree->io->datatype == NT)?(50.):(0.); */
tree->mod->s_opt->max_depth_path = 2*tree->n_otu-3;
tree->mod->s_opt->max_delta_lnL_spr = (tree->io->datatype == NT)?(10.):(0.);
/* tree->mod->s_opt->max_depth_path = 5; */
tree->mod->s_opt->spr_lnL = NO;
do
{
lk_old = tree->c_lnL;
Speed_Spr(tree,1);
if(tree->n_improvements) Optimiz_All_Free_Param(tree,(tree->io->quiet)?(0):(tree->mod->s_opt->print));
if((tree->io->datatype == NT) && ((tree->max_spr_depth < 4 && tree->n_improvements < 10) || (FABS(lk_old-tree->c_lnL) < 1.))) break;
if((tree->io->datatype == AA) && ((tree->max_spr_depth < 4 && tree->n_improvements < 1) || (FABS(lk_old-tree->c_lnL) < 1.))) break;
/* if((tree->io->datatype == NT) & (tree->n_improvements < 10) || (FABS(lk_old-tree->c_lnL) < 1.)) break; */
/* if((tree->io->datatype == AA) & (tree->n_improvements < 1) || (FABS(lk_old-tree->c_lnL) < 1.)) break; */
}
while(1);
/*****************************/
/*****************************/
if(tree->io->datatype == NT)
{
lk_old = UNLIKELY;
tree->mod->s_opt->max_delta_lnL_spr = 20.;
tree->mod->s_opt->max_depth_path = 10;
tree->mod->s_opt->br_len_in_spr = 1;
tree->mod->s_opt->spr_lnL = YES;
do
{
lk_old = tree->c_lnL;
Speed_Spr(tree,1);
if(tree->n_improvements) Optimiz_All_Free_Param(tree,(tree->io->quiet)?(0):(tree->mod->s_opt->print));
if((!tree->n_improvements) || (FABS(lk_old-tree->c_lnL) < 1.)) break;
}
while(1);
}
/*****************************/
/*****************************/
lk_old = UNLIKELY;
do
{
lk_old = tree->c_lnL;
if(!Simu(tree,10)) break;
Optimiz_All_Free_Param(tree,(tree->io->quiet)?(0):(tree->mod->s_opt->print));
}
while(FABS(lk_old - tree->c_lnL) > tree->mod->s_opt->min_diff_lk_global);
/*****************************/
/*****************************/
do
{
Round_Optimize(tree,tree->data,ROUND_MAX);
if(!Check_NNI_Five_Branches(tree)) break;
}while(1);
/*****************************/
/* if((tree->mod->s_opt->print) && (!tree->io->quiet)) PhyML_Printf("\n"); */
}
/*********************************************************/
void Speed_Spr(t_tree *tree, int max_cycles)
{
int step,old_pars;
phydbl old_lnL;
if(tree->lock_topo)
{
PhyML_Printf("\n. The tree topoLlogy is locked.");
PhyML_Printf("\n. Err in file %s at line %d\n",__FILE__,__LINE__);
Warn_And_Exit("");
}
tree->both_sides = 1;
Pars(tree);
Lk(tree);
Record_Br_Len(tree);
tree->mod->s_opt->deepest_path = 0;
tree->best_pars = tree->c_pars;
tree->best_lnL = tree->c_lnL;
old_lnL = tree->c_lnL;
old_pars = tree->c_pars;
step = 0;
do
{
++step;
old_lnL = tree->c_lnL;
old_pars = tree->c_pars;
tree->max_spr_depth = 0;
tree->n_improvements = 0;
tree->perform_spr_right_away = 1;
Spr(UNLIKELY,tree);
if(!tree->mod->s_opt->spr_pars)
{
/* Optimise branch lengths */
Optimize_Br_Len_Serie(tree->t_nodes[0],
tree->t_nodes[0]->v[0],
tree->t_nodes[0]->b[0],
tree,
tree->data);
/* Update partial likelihoods */
tree->both_sides = 1;
Lk(tree);
/* Print log-likelihood and parsimony scores */
if((tree->mod->s_opt->print) && (!tree->io->quiet)) Print_Lk(tree,"[Branch lengths ]");
}
else
{
if((tree->mod->s_opt->print) && (!tree->io->quiet)) Print_Pars(tree);
}
Pars(tree);
if(tree->io->print_trace)
{
PhyML_Fprintf(tree->io->fp_out_trace,"[%f]%s\n",tree->c_lnL,Write_Tree(tree,NO)); fflush(tree->io->fp_out_trace);
if((tree->io->print_site_lnl) && (!tree->mod->s_opt->spr_pars)) Print_Site_Lk(tree,tree->io->fp_out_lk); fflush(tree->io->fp_out_lk);
}
/* Record the current best LOG-likelihood and parsimony */
tree->best_lnL = tree->c_lnL;
tree->best_pars = tree->c_pars;
if(!tree->mod->s_opt->spr_pars)
{
if(tree->c_lnL < old_lnL-tree->mod->s_opt->min_diff_lk_local)
{
PhyML_Printf("\n. old_lnL = %f c_lnL = %f",old_lnL,tree->c_lnL);
PhyML_Printf("\n. Err in file %s at line %d\n",__FILE__,__LINE__);
Warn_And_Exit("");
}
}
else
{
if(tree->c_pars > old_pars)
{
PhyML_Printf("\n. old_pars = %d c_pars = %d",old_pars,tree->c_pars);
PhyML_Printf("\n. Err in file %s at line %d\n",__FILE__,__LINE__);
Warn_And_Exit("");
}
}
/* Record the current best branch lengths */
Record_Br_Len(tree);
/* Exit if no improvements after complete optimization */
if(step+1 > max_cycles) break;
if((!tree->mod->s_opt->spr_pars) && (FABS(old_lnL-tree->c_lnL) < tree->mod->s_opt->min_diff_lk_global)) break;
/* if(( tree->mod->s_opt->spr_pars) && (FABS(old_pars-tree->c_pars) < 1.)) break; */
if(!tree->n_improvements) break;
}while(1);
}
/*********************************************************/
int Evaluate_List_Of_Regraft_Pos_Triple(spr **spr_list, int list_size, t_tree *tree)
{
spr *move;
t_edge *init_target, *b_residual;
int i,j,best_move;
int dir_v0, dir_v1, dir_v2;
phydbl recorded_l;
phydbl best_lnL,init_lnL;
best_lnL = UNLIKELY;
init_target = b_residual = NULL;
best_move = -1;
init_lnL = tree->c_lnL;
if(!list_size && !tree->io->fp_in_constraint_tree)
{
PhyML_Printf("\n. List size is 0 !");
PhyML_Printf("\n. Err in file %s at line %d\n",__FILE__,__LINE__);
Warn_And_Exit("");
}
recorded_l = -1.0;
For(i,list_size)
{
move = spr_list[i];
if(!move)
{
PhyML_Printf("\n. move is NULL\n");
PhyML_Printf("\n. Err in file %s at line %d\n",__FILE__,__LINE__);
Warn_And_Exit("");
}
if(move->b_target)
{
/* Record t_edge lengths */
Record_Br_Len(tree);
/* Prune subtree */
Prune_Subtree(move->n_link,move->n_opp_to_link,&init_target,&b_residual,tree);
if(recorded_l < 0.0)
{
/* Rough optimisation of the branch length at prune site
* We only need to perform this optimisation for the first
* element of spr_list because the pruned subtree is the
* same across all the elements of spr_list. It would not
* be true in the general case
*/
Fast_Br_Len(init_target,tree,0);
/* Record branch length at prune site */
move->init_target_l = init_target->l;
recorded_l = init_target->l;
}
else
{
init_target->l = recorded_l;
move->init_target_l = recorded_l;
}
/* Update the change proba matrix at prune position */
Update_PMat_At_Given_Edge(init_target,tree);
/* Update conditional likelihoods along the path from the prune to
the regraft position */
tree->update_alias_subpatt = YES;
Update_P_Lk_Along_A_Path(move->path,move->depth_path+1,tree);
tree->update_alias_subpatt = NO;
/* Regraft subtree */
Graft_Subtree(move->b_target,move->n_link,b_residual,tree);
dir_v1 = dir_v2 = dir_v0 = -1;
For(j,3)
{
if(move->n_link->v[j] == move->n_opp_to_link) dir_v0 = j;
else if(dir_v1 < 0) dir_v1 = j;
else dir_v2 = j;
}
move->n_link->b[dir_v0]->l = move->l0;
if(move->n_link->v[dir_v1]->num > move->n_link->v[dir_v2]->num)
{
move->n_link->b[dir_v2]->l = move->l1;
move->n_link->b[dir_v1]->l = move->l2;
}
else
{
move->n_link->b[dir_v1]->l = move->l1;
move->n_link->b[dir_v2]->l = move->l2;
}
/* Update_PMat_At_Given_Edge(move->b_target,tree); */
/* Update_PMat_At_Given_Edge(b_residual,tree); */
/* tree->update_alias_subpatt = YES; */
/* Update_P_Lk(tree,move->b_opp_to_link,move->n_link); */
/* tree->update_alias_subpatt = NO; */
/* move->lnL = Lk_At_Given_Edge(move->b_opp_to_link,tree); */
tree->update_alias_subpatt = YES;
move->lnL = Triple_Dist(move->n_link,tree,1);
tree->update_alias_subpatt = NO;
/* printf("\n. move->n_link=%d move=%f %f %f", */
/* move->n_link->num, */
/* move->lnL, */
/* move->l1,move->l2); */
/* Exit("\n"); */
if((move->lnL < best_lnL) && (move->lnL > best_lnL - tree->mod->s_opt->max_delta_lnL_spr))
{
/* Estimate the three t_edge lengths at the regraft site */
move->lnL = Triple_Dist(move->n_link,tree,0);
}
/* Record updated branch lengths for this move */
move->l0 = move->n_link->b[dir_v0]->l;
if(move->n_link->v[dir_v1]->num > move->n_link->v[dir_v2]->num)
{
move->l1 = move->n_link->b[dir_v2]->l;
move->l2 = move->n_link->b[dir_v1]->l;
}
else
{
move->l1 = move->n_link->b[dir_v1]->l;
move->l2 = move->n_link->b[dir_v2]->l;
}
if(move->lnL > best_lnL + tree->mod->s_opt->min_diff_lk_move)
{
best_lnL = move->lnL;
best_move = i;
}
/* Regraft the subtree at its original position */
Prune_Subtree(move->n_link,
move->n_opp_to_link,
&move->b_target,
&b_residual,
tree);
Graft_Subtree(init_target,
move->n_link,
b_residual,
tree);
/* Restore branch lengths */
Restore_Br_Len(tree);
/* Update relevant change proba matrices */
/* Update_PMat_At_Given_Edge(move->n_link->b[0],tree); */
/* Update_PMat_At_Given_Edge(move->n_link->b[1],tree); */
/* Update_PMat_At_Given_Edge(move->n_link->b[2],tree); */
Update_PMat_At_Given_Edge(move->b_target,tree);
/* Update_P_Lk(tree,move->n_link->b[0],move->n_link); */
/* Update_P_Lk(tree,move->n_link->b[1],move->n_link); */
/* Update_P_Lk(tree,move->n_link->b[2],move->n_link); */
/* Update conditional likelihoods along the path from the prune to
the regraft position */
/* Update_P_Lk_Along_A_Path(move->path,move->depth_path+1,tree); */
tree->c_lnL = init_lnL;
}
/* Bail out as soon as you've found a true improvement */
if(move->lnL > tree->best_lnL + tree->mod->s_opt->min_diff_lk_move) break;
}
/* PhyML_Printf("\n. [ %4d/%4d ]",i,list_size); */
/* PhyML_Printf("\n. max_improv = %f",max_improv); */
tree->update_alias_subpatt = YES;
For(i,list_size)
{
move = spr_list[i];
if(move->b_target)
{
For(j,3) Update_PMat_At_Given_Edge(move->n_link->b[j],tree);
For(j,3) Update_P_Lk(tree,move->n_link->b[j],move->n_link);
/* TO DO : we don't need to update all these partial likelihoods here.
Would need to record only those that were along the paths examined
above */
For(j,3)
if(move->n_link->v[j] != move->n_opp_to_link)
Pre_Order_Lk(move->n_link,move->n_link->v[j],tree);
break;
}
}
tree->update_alias_subpatt = NO;
#ifdef DEBUG
if(best_move < 0 && list_size > 0)
{
PhyML_Printf("\n\n. Best_move < 0 !");
PhyML_Printf("\n. List size = %d",list_size);
For(i,list_size)
{
move = spr_list[i];
PhyML_Printf("\n. %p %p",move,move->b_target);
}
PhyML_Printf("\n. Err in file %s at line %d\n",__FILE__,__LINE__);
Warn_And_Exit("");
}
#endif
return best_move;
}
/*********************************************************/
int Try_One_Spr_Move_Triple(spr *move, t_tree *tree)
{
t_edge *init_target, *b_residual;
int j;
int dir_v0, dir_v1, dir_v2;
int accept;
phydbl u;
Record_Br_Len(tree);
Prune_Subtree(move->n_link,
move->n_opp_to_link,
&init_target,
&b_residual,
tree);
init_target->l = move->init_target_l;
Graft_Subtree(move->b_target,move->n_link,b_residual,tree);
dir_v1 = dir_v2 = dir_v0 = -1;
For(j,3)
{
if(move->n_link->v[j] == move->n_opp_to_link) dir_v0 = j;
else if(dir_v1 < 0) dir_v1 = j;
else dir_v2 = j;
}
move->n_link->b[dir_v0]->l = move->l0;
if(move->n_link->v[dir_v1]->num > move->n_link->v[dir_v2]->num)
{
move->n_link->b[dir_v2]->l = move->l1;
move->n_link->b[dir_v1]->l = move->l2;
}
else
{
move->n_link->b[dir_v1]->l = move->l1;
move->n_link->b[dir_v2]->l = move->l2;
}
accept = YES;
if(!Check_Topo_Constraints(tree,tree->io->cstr_tree)) accept = NO;
if(accept)
{
u = Uni();
if(!(u < EXP((move->lnL - tree->best_lnL)/tree->temp)))
accept = NO;
if(FABS(move->lnL -tree->best_lnL) < tree->mod->s_opt->min_diff_lk_move)
accept = NO;
}
/* printf("\n. %d %15f %15f",accept,move->lnL - tree->best_lnL,tree->temp); */
if(accept == YES) /* Apply the move */
{
time(&(tree->t_current));
Pars(tree);
tree->both_sides = YES;
tree->update_alias_subpatt = YES;
Lk(tree);
tree->update_alias_subpatt = NO;
if(FABS(tree->c_lnL - move->lnL) > tree->mod->s_opt->min_diff_lk_move)
{
PhyML_Printf("\n. c_lnL = %f move_lnL = %f\n",
tree->c_lnL,move->lnL);
PhyML_Printf("\n. Err in file %s at line %d\n",__FILE__,__LINE__);
Warn_And_Exit("");
}
//
/* if(!(tree->n_improvements % tree->mod->s_opt->br_len_in_spr)) */
/* { */
/* tree->mod->s_opt->brent_it_max = 10; */
/* Optimize_Br_Len_Serie(tree->t_nodes[0], */
/* tree->t_nodes[0]->v[0], */
/* tree->t_nodes[0]->b[0], */
/* tree, */
/* tree->data); */
/* tree->mod->s_opt->brent_it_max = 500; */
/* tree->both_sides = 1; */
/* Lk(tree); */
/* } */
//
if((tree->mod->s_opt->print) && (!tree->io->quiet))
{
Print_Lk_And_Pars(tree);
PhyML_Printf(" [depth=%5d]",move->depth_path); fflush(NULL);
}
if(move->depth_path > tree->max_spr_depth) tree->max_spr_depth = move->depth_path;
tree->n_improvements++;
tree->best_lnL = tree->c_lnL;
Record_Br_Len(tree);
if(move->depth_path > tree->mod->s_opt->deepest_path)
tree->mod->s_opt->deepest_path = move->depth_path;
return 1;
}
Prune_Subtree(move->n_link,
move->n_opp_to_link,
&move->b_target,
&b_residual,
tree);
Graft_Subtree(init_target,
move->n_link,
b_residual,
tree);
Restore_Br_Len(tree);
tree->both_sides = YES;
tree->update_alias_subpatt = YES;
Lk(tree);
tree->update_alias_subpatt = NO;
Pars(tree);
return 0;
}
/*********************************************************/
int Try_One_Spr_Move_Full(spr *move, t_tree *tree)
{
t_edge *init_target, *b_residual;
Record_Br_Len(tree);
Prune_Subtree(move->n_link,
move->n_opp_to_link,
&init_target,
&b_residual,
tree);
Graft_Subtree(move->b_target,move->n_link,b_residual,tree);
tree->update_alias_subpatt = YES;
tree->both_sides = 1;
Lk(tree);
tree->update_alias_subpatt = NO;
Optimize_Br_Len_Serie(tree->t_nodes[0],
tree->t_nodes[0]->v[0],
tree->t_nodes[0]->b[0],
tree,
tree->data);
tree->both_sides = 1;
Lk(tree);
if(tree->c_lnL > tree->best_lnL + tree->mod->s_opt->min_diff_lk_move)
{
Pars(tree);
if((tree->mod->s_opt->print) && (!tree->io->quiet)) Print_Lk(tree,"[Topology ]");
tree->n_improvements++;
tree->best_lnL = tree->c_lnL;
Record_Br_Len(tree);
return 1;
}
else
{
Prune_Subtree(move->n_link,
move->n_opp_to_link,
&move->b_target,
&b_residual,
tree);
Graft_Subtree(init_target,
move->n_link,
b_residual,
tree);
Restore_Br_Len(tree);
tree->both_sides = 1;
tree->update_alias_subpatt = YES;
Lk(tree);
tree->update_alias_subpatt = NO;
Pars(tree);
return 0;
}
return -1;
}
/*********************************************************/
void Include_One_Spr_To_List_Of_Spr(spr *move, t_tree *tree)
{
int i;
spr *buff_spr;
if((( tree->mod->s_opt->spr_lnL) && (move->lnL > tree->spr_list[tree->size_spr_list-1]->lnL)) ||
((!tree->mod->s_opt->spr_lnL) && (move->pars <= tree->spr_list[tree->size_spr_list-1]->pars)))
{
tree->spr_list[tree->size_spr_list-1]->depth_path = move->depth_path;
tree->spr_list[tree->size_spr_list-1]->pars = move->pars;
tree->spr_list[tree->size_spr_list-1]->lnL = move->lnL;
tree->spr_list[tree->size_spr_list-1]->b_target = move->b_target;
tree->spr_list[tree->size_spr_list-1]->n_link = move->n_link;
tree->spr_list[tree->size_spr_list-1]->n_opp_to_link = move->n_opp_to_link;
tree->spr_list[tree->size_spr_list-1]->b_opp_to_link = move->b_opp_to_link;
tree->spr_list[tree->size_spr_list-1]->l0 = move->l0;
tree->spr_list[tree->size_spr_list-1]->l1 = move->l1;
tree->spr_list[tree->size_spr_list-1]->l2 = move->l2;
tree->spr_list[tree->size_spr_list-1]->dist = move->dist;
For(i,tree->spr_list[tree->size_spr_list-1]->depth_path+1)
tree->spr_list[tree->size_spr_list-1]->path[i] = move->path[i];
for(i=tree->size_spr_list-1;i>0;i--)
{
if((( tree->mod->s_opt->spr_lnL) && (tree->spr_list[i]->lnL > tree->spr_list[i-1]->lnL)) ||
((!tree->mod->s_opt->spr_lnL) && (tree->spr_list[i]->pars <= tree->spr_list[i-1]->pars)))
{
buff_spr = tree->spr_list[i-1];
tree->spr_list[i-1] = tree->spr_list[i];
tree->spr_list[i] = buff_spr;
}
else break;
}
}
}
/*********************************************************/
void Random_Spr(int n_moves, t_tree *tree)
{
int i;
int br_pulled, br_target;
spr *spr_struct;
t_edge *target, *residual;
spr_struct = Make_One_Spr(tree);
Init_One_Spr(spr_struct);
target = residual = NULL;
For(i,n_moves)
{
br_pulled = (int)((phydbl)rand()/RAND_MAX * (2*tree->n_otu-3-1));
do
{
br_target = (int)((phydbl)rand()/RAND_MAX * (2*tree->n_otu-3-1));
}while(br_target == br_pulled);
spr_struct->n_link = tree->t_edges[br_pulled]->left;
spr_struct->n_opp_to_link = tree->t_edges[br_pulled]->rght;
spr_struct->b_opp_to_link = tree->t_edges[br_pulled];
spr_struct->b_target = tree->t_edges[br_target];
spr_struct->b_init_target = NULL;
if(!Check_Spr_Move_Validity(spr_struct,tree))
{
spr_struct->n_link = tree->t_edges[br_pulled]->rght;
spr_struct->n_opp_to_link = tree->t_edges[br_pulled]->left;
}
#ifdef DEBUG
if(!Check_Spr_Move_Validity(spr_struct,tree))
{
Warn_And_Exit("\n. Could not find a valid move...\n");
}
#endif
Prune_Subtree(spr_struct->n_link,
spr_struct->n_opp_to_link,
&target,
&residual,
tree);
Graft_Subtree(spr_struct->b_target,
spr_struct->n_link,
residual,tree);
}
Free(spr_struct);
}
/*********************************************************/
void Reset_Spr_List(t_tree *tree)
{
int i;
For(i,tree->size_spr_list)
{
tree->spr_list[i]->depth_path = 0;
tree->spr_list[i]->pars = MAX_PARS;
tree->spr_list[i]->lnL = UNLIKELY;
tree->spr_list[i]->n_link = NULL;
tree->spr_list[i]->n_opp_to_link = NULL;
tree->spr_list[i]->b_target = NULL;
}
}
/*********************************************************/
int Check_Spr_Move_Validity(spr *this_spr_move, t_tree *tree)
{
int match;
match = 0;
Found_In_Subtree(this_spr_move->n_link,
this_spr_move->n_opp_to_link,
this_spr_move->b_target->left,
&match,
tree);
if(match) return 0;
else return 1;
}
/*********************************************************/
void Make_Best_Spr(t_tree *tree)
{
tree->best_spr = Make_One_Spr(tree);
Init_One_Spr(tree->best_spr);
}
/*********************************************************/
void Make_Spr_List(t_tree *tree)
{
int i;
tree->size_spr_list = 2*tree->n_otu-3;
tree->spr_list = (spr **)mCalloc(2*tree->n_otu-2,sizeof(spr *));
For(i,2*tree->n_otu-2)
{
tree->spr_list[i] = Make_One_Spr(tree);
Init_One_Spr(tree->spr_list[i]);
}
tree->perform_spr_right_away = 0;
}
/*********************************************************/
void Init_One_Spr(spr *a_spr)
{
a_spr->lnL = UNLIKELY;
a_spr->pars = 1E+5;
a_spr->depth_path = 0;
a_spr->dist = 0;
a_spr->init_target_l = -1.;
a_spr->l0 = -1.;
a_spr->l1 = -1.;
a_spr->l2 = -1.;
a_spr->n_link = NULL;
a_spr->n_opp_to_link = NULL;
a_spr->b_opp_to_link = NULL;
a_spr->b_target = NULL;
a_spr->b_init_target = NULL;
}
/*********************************************************/
spr *Make_One_Spr(t_tree *tree)
{
spr *a_spr;
a_spr = (spr *)mCalloc(1,sizeof(spr));
a_spr->path = (t_node **)mCalloc(tree->n_otu,sizeof(t_node *));
return a_spr;
}
/*********************************************************/
void Spr_Pars(t_tree *tree)
{
PhyML_Printf("\n. Minimizing parsimony...\n");
tree->best_pars = 1E+8;
tree->best_lnL = UNLIKELY;
tree->mod->s_opt->spr_lnL = 0;
tree->mod->s_opt->spr_pars = 1;
do
{
Speed_Spr(tree,1);
}while(tree->n_improvements);
tree->mod->s_opt->spr_pars = 0;
PhyML_Printf("\n");
}
/*********************************************************/
int Check_Lk_At_Given_Edge(t_tree *tree)
{
int res;
int i;
phydbl *lk;
lk = (phydbl *)mCalloc(2*tree->n_otu-3,sizeof(phydbl));
res = 0;
For(i,2*tree->n_otu-3)
{
lk[i] = Lk_At_Given_Edge(tree->t_edges[i],tree);
}
res=1;
for(i=1;i<2*tree->n_otu-3;i++)
{
if(FABS(lk[i]-lk[i-1]) > 1.E-2) res=0;
}
Free(lk);
return res;
}
/*********************************************************/
void SPR_Shuffle(t_tree *tree)
{
int n_rand_cycles = 0;
phydbl best_lnL = UNLIKELY;
t_tree *best_tree = Make_Tree_From_Scratch(tree->n_otu,tree->data);
t_tree *start_tree = Make_Tree_From_Scratch(tree->n_otu,tree->data);
int ori_catg = tree->mod->n_catg;
phydbl lk_old;
start_tree->mod = tree->mod;
start_tree->io = tree->io;
start_tree->data = tree->data;
start_tree->both_sides = YES;
start_tree->mod->s_opt->print = tree->mod->s_opt->print;
/* start_tree->mod->s_opt->print = YES; */
start_tree->n_pattern = tree->data->crunch_len;
start_tree->t_beg = tree->t_beg;
start_tree->mod->n_catg = MIN(2,ori_catg);
if(tree->mod->s_opt->print) PhyML_Printf("\n. Refining the tree...\n");
do
{
n_rand_cycles++;
/* Random_Tree(start_tree); */
Copy_Tree(tree,start_tree);
Share_Lk_Struct(tree,start_tree);
Share_Spr_Struct(tree,start_tree);
Share_Pars_Struct(tree,start_tree);
Fill_Dir_Table(start_tree);
Update_Dirs(start_tree);
Init_P_Lk_Tips_Int(start_tree);
Init_Ui_Tips(start_tree);
Init_P_Pars_Tips(start_tree);
Br_Len_Not_Involving_Invar(start_tree);
start_tree->best_pars = start_tree->c_pars;
start_tree->best_lnL = start_tree->c_lnL;
start_tree->mod->s_opt->max_delta_lnL_spr = 0.;
start_tree->mod->s_opt->br_len_in_spr = 1;
start_tree->mod->s_opt->max_depth_path = 2*tree->n_otu-3;
start_tree->mod->s_opt->spr_lnL = NO;
/* start_tree->temp = 6.; */
start_tree->temp = 0.;
do
{
start_tree->both_sides = YES;
Lk(start_tree);
Pars(start_tree);
Record_Br_Len(start_tree);
start_tree->n_improvements = 0;
start_tree->max_spr_depth = 0;
start_tree->best_pars = start_tree->c_pars;
start_tree->best_lnL = start_tree->c_lnL;
lk_old = tree->c_lnL;
Spr(UNLIKELY,start_tree);
start_tree->temp -= 3.;
if(start_tree->temp < .0) start_tree->temp = .0;
/* printf("\n. temp=%f n_improv=%d max_depth=%d",start_tree->temp,start_tree->n_improvements,start_tree->max_spr_depth); */
Optimiz_All_Free_Param(start_tree,(start_tree->io->quiet)?(0):(start_tree->mod->s_opt->print));
Optimize_Br_Len_Serie(start_tree->t_nodes[0],
start_tree->t_nodes[0]->v[0],
start_tree->t_nodes[0]->b[0],
start_tree,
start_tree->data);
if(start_tree->n_improvements < 20 || start_tree->max_spr_depth < 5 ||
(FABS(lk_old-start_tree->c_lnL) < 1.)) break;
}while(1);
if(start_tree->c_lnL > best_lnL)
{
best_lnL = start_tree->c_lnL;
Copy_Tree(start_tree,best_tree);
}
}while(n_rand_cycles < 1);
Copy_Tree(best_tree,tree);
Share_Lk_Struct(start_tree,tree);
Fill_Dir_Table(tree);
Update_Dirs(tree);
Init_P_Lk_Tips_Int(tree);
Init_Ui_Tips(tree);
Init_P_Pars_Tips(tree);
Free_Tree(start_tree);
Free_Tree(best_tree);
tree->mod->n_catg = ori_catg;
}
/*
** EOF: spr.c
*/
phyml-20120412/src/lk.h 0000644 0001750 0001750 00000010540 11654376266 011407 0000000 0000000 /*
PHYML : a program that computes maximum likelihood phylogenies from
DNA or AA homologous sequences
Copyright (C) Stephane Guindon. Oct 2003 onward
All parts of the source except where indicated are distributed under
the GNU public licence. See http://www.opensource.org for details.
*/
#include
#ifndef LK_H
#define LK_H
#include "utilities.h"
#include "optimiz.h"
#include "models.h"
#include "free.h"
#include "times.h"
void Init_Tips_At_One_Site_Nucleotides_Float(char state, int pos, phydbl *p_lk);
void Init_Tips_At_One_Site_AA_Float(char aa, int pos, phydbl *p_lk);
void Get_All_Partial_Lk(t_tree *tree,t_edge *b_fcus,t_node *a,t_node *d);
void Get_All_Partial_Lk_Scale(t_tree *tree,t_edge *b_fcus,t_node *a,t_node *d);
void Post_Order_Lk(t_node *pere, t_node *fils, t_tree *tree);
void Pre_Order_Lk(t_node *pere, t_node *fils, t_tree *tree);
phydbl Lk(t_tree *tree);
void Site_Lk(t_tree *tree);
phydbl Lk_At_Given_Edge(t_edge *b_fcus,t_tree *tree);
phydbl Return_Abs_Lk(t_tree *tree);
matrix *ML_Dist(calign *data, model *mod);
phydbl Lk_Given_Two_Seq(calign *data, int numseq1, int numseq2, phydbl dist, model *mod, phydbl *loglk);
void Unconstraint_Lk(t_tree *tree);
void Update_P_Lk(t_tree *tree,t_edge *b_fcus,t_node *n);
void Update_P_Lk_Generic(t_tree *tree,t_edge *b_fcus,t_node *n);
void Update_P_Lk_AA(t_tree *tree,t_edge *b_fcus,t_node *n);
void Update_P_Lk_Nucl(t_tree *tree,t_edge *b_fcus,t_node *n);
void Make_Tree_4_Lk(t_tree *tree,calign *cdata,int n_site);
void Init_P_Lk_Tips_Double(t_tree *tree);
void Init_P_Lk_Tips_Int(t_tree *tree);
void Init_P_Lk_At_One_Node(t_node *a, t_tree *tree);
void Update_PMat_At_Given_Edge(t_edge *b_fcus, t_tree *tree);
void Sort_Sites_Based_On_Lk(t_tree *tree);
void Get_Partial_Lk_Scale(t_tree *tree, t_edge *b_fcus, t_node *a, t_node *d);
void Get_Partial_Lk(t_tree *tree, t_edge *b_fcus, t_node *a, t_node *d);
void Init_Tips_At_One_Site_Nucleotides_Int(char state, int pos, short int *p_pars);
void Init_Tips_At_One_Site_AA_Int(char aa, int pos, short int *p_pars);
void Update_P_Lk_Along_A_Path(t_node **path, int path_length, t_tree *tree);
phydbl Lk_Dist(phydbl *F, phydbl dist, model *mod);
phydbl Update_Lk_At_Given_Edge(t_edge *b_fcus, t_tree *tree);
void Update_P_Lk_Greedy(t_tree *tree, t_edge *b_fcus, t_node *n);
void Get_All_Partial_Lk_Scale_Greedy(t_tree *tree, t_edge *b_fcus, t_node *a, t_node *d);
phydbl Lk_Core(t_edge *b, t_tree *tree);
phydbl Lk_Triplet(t_node *a, t_node *d, t_tree *tree);
void Print_Lk_Given_Edge_Recurr(t_node *a, t_node *d, t_edge *b, t_tree *tree);
phydbl *Post_Prob_Rates_At_Given_Edge(t_edge *b, phydbl *post_prob, t_tree *tree);
phydbl Lk_With_MAP_Branch_Rates(t_tree *tree);
void Init_Tips_At_One_Site_Generic_Int(char *state, int ns, int state_len, int pos, short int *p_pars);
void Init_Tips_At_One_Site_Generic_Float(char *state, int ns, int state_len, int pos, phydbl *p_lk);
void Alias_Subpatt(t_tree *tree);
void Alias_One_Subpatt(t_node *a, t_node *d, t_tree *tree);
void Alias_Subpatt_Post(t_node *a, t_node *d, t_tree *tree);
void Alias_Subpatt_Pre(t_node *a, t_node *d, t_tree *tree);
void Copy_P_Lk(phydbl *p_lk, int site_from, int site_to, t_tree *tree);
void Copy_Scale(int *scale, int site_from, int site_to, t_tree *tree);
void Init_P_Lk_Loc(t_tree *tree);
phydbl Lk_Normal_Approx(t_tree *tree);
phydbl Wrap_Lk(t_edge *b, t_tree *tree, supert_tree *stree);
phydbl Wrap_Lk_At_Given_Edge(t_edge *b, t_tree *tree, supert_tree *stree);
phydbl Wrap_Part_Lk_At_Given_Edge(t_edge *b, t_tree *tree, supert_tree *stree);
phydbl Wrap_Part_Lk(t_edge *b, t_tree *tree, supert_tree *stree);
phydbl Wrap_Geo_Lk(t_edge *b, t_tree *tree, supert_tree *stree);
phydbl Wrap_Diff_Lk_Norm_At_Given_Edge(t_edge *b, t_tree *tree, supert_tree *stree);
phydbl Wrap_Lk_Rates(t_edge *b, t_tree *tree, supert_tree *stree);
phydbl Wrap_Lk_Linreg(t_edge *b, t_tree *tree, supert_tree *stree);
void Sample_Ancestral_Seq(int mutmap, int fromprior, t_tree *tree);
void Map_Mutations(t_node *a, t_node *d, int sa, int sd, t_edge *b, int site, int rate_cat, int *muttype, phydbl *muttime, int *n_mut, t_tree *tree);
void Sample_Ancestral_Seq_Pre(t_node *a, t_node *d, t_edge *b,
int site, int rate_cat,
int *muttype, phydbl *muttime, int *n_mut,
int mutmap, int fromprior, t_tree *tree);
phydbl Wrap_Lk_Times(t_edge *b, t_tree *tree, supert_tree *stree);
phydbl Lk_LastFirst(t_tree *tree);
#endif
phyml-20120412/src/simu.h 0000644 0001750 0001750 00000002314 11637265652 011753 0000000 0000000 /*
PHYML : a program that computes maximum likelihood phylogenies from
DNA or AA homologous sequences
Copyright (C) Stephane Guindon. Oct 2003 onward
All parts of the source except where indicated are distributed under
the GNU public licence. See http://www.opensource.org for details.
*/
#include
#ifndef CURR_H
#define CURR_H
#include "utilities.h"
#include "lk.h"
#include "optimiz.h"
#include "models.h"
#include "free.h"
#include "spr.h"
#include "pars.h"
#include "alrt.h"
void Simu_Loop(t_tree *tree);
int Simu(t_tree *tree,int n_step_max);
void Select_Edges_To_Swap(t_tree *tree,t_edge **sorted_b,int *n_neg);
void Update_Bl(t_tree *tree,phydbl fact);
void Make_N_Swap(t_tree *tree,t_edge **b,int beg,int end);
int Make_Best_Swap(t_tree *tree);
int Mov_Backward_Topo_Bl(t_tree *tree,phydbl lk_old,t_edge **tested_b,int n_tested);
void Unswap_N_Branch(t_tree *tree,t_edge **b,int beg,int end);
void Swap_N_Branch(t_tree *tree,t_edge **b,int beg,int end);
void Check_NNI_Scores_Around(t_node *a, t_node *d, t_edge *b, phydbl *best_score, t_tree *tree);
int Mov_Backward_Topo_Pars(t_tree *tree, int pars_old, t_edge **tested_b, int n_tested);
void Simu_Pars(t_tree *tree, int n_step_max);
#endif
phyml-20120412/src/mg.c 0000644 0001750 0001750 00000234535 11644731736 011407 0000000 0000000 /*
PHYML : a program that computes maximum likelihood phylogenies from
DNA or AA homologous sequences
Copyright (C) Stephane Guindon. Oct 2003 onward
All parts of the source except where indicated are distributed under
the GNU public licence. See http://www.opensource.org for details.
*/
#include
#include "mg.h"
#include "free.h"
#include "help.h"
#include "utilities.h"
#include "optimiz.h"
#include "models.h"
#include "simu.h"
#include "lk.h"
#include "pars.h"
#include "interface.h"
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
int PART_main(int argc, char **argv)
{
option *io;
char *s_tree;
FILE *fp_phyml_tree,*fp_phyml_stats,*fp_phyml_lk;
int part;
time_t t_beg,t_end;
div_t hour,min;
int r_seed;
int i;
fflush(NULL);
io = (option *)Get_Input(argc,argv);
r_seed = (io->r_seed < 0)?(time(NULL)):(io->r_seed);
srand(r_seed);
fp_phyml_stats = Openfile(io->out_stats_file,io->out_stats_file_open_mode);
PhyML_Fprintf(fp_phyml_stats,"\n- PHYML %s -\n\n", VERSION);
fp_phyml_tree = Openfile(io->out_tree_file,io->out_tree_file_open_mode);
fp_phyml_lk = fopen(io->out_lk_file,"w");
time(&t_beg);
if(io->multigene)
{
align ***data;
calign **cdata;
model **mod;
matrix **mat;
t_treelist *treelist;
supert_tree *st;
data = (align ***) mCalloc(io->n_part,sizeof(align **));
cdata = (calign **)mCalloc(io->n_part,sizeof(calign *));
mod = (model **) mCalloc(io->n_part,sizeof(model *));
mat = (matrix **)mCalloc(io->n_part,sizeof(matrix *));
/* Read the sequences (for each partition) */
For(part,io->n_part)
{
Make_Model_Complete(io->st->optionlist[part]->mod); /* Complete model for each data part */
data[part] = Get_Seq(io->st->optionlist[part]);
Make_Model_Complete(io->st->optionlist[part]->mod);
Set_Model_Name(io->st->optionlist[part]->mod);
mod[part] = io->st->optionlist[part]->mod;
PhyML_Printf("\n. Data part [#%d]\n",part+1);
PhyML_Printf("\n. Compressing sequences...\n");
cdata[part] = Compact_Data(data[part],io->st->optionlist[part]);
fclose(io->st->optionlist[part]->fp_in_align);
Free_Seq(data[part],cdata[part]->n_otu);
Init_Model(cdata[part],mod[part],io->st->optionlist[part]);
Check_Ambiguities(cdata[part],
io->st->optionlist[part]->mod->io->datatype,
io->st->optionlist[part]->mod->state_len);
}
PART_Make_Supert_tree_Full(io->st,io,cdata);
st = io->st;
treelist = st->treelist;
Fill_Dir_Table(st->tree);
Update_Dirs(st->tree);
For(part,io->n_part)
{
st->curr_cdata = cdata[part];
if(!PART_Get_Species_Found_In_St(st,cdata[part])) break;
treelist->tree[part] = Make_Tree_From_Scratch(st->tree->n_otu,NULL);
Copy_Tree_Topology_With_Labels(st->tree,treelist->tree[part]);
treelist->tree[part]->num_curr_branch_available = 0;
Connect_Edges_To_Nodes_Recur(treelist->tree[part]->t_nodes[0],
treelist->tree[part]->t_nodes[0]->v[0],
treelist->tree[part]);
PART_Prune_St_Topo(treelist->tree[part],cdata[part],st);
if(treelist->tree[part]->n_otu != cdata[part]->n_otu)
{
PhyML_Printf("\n. Problem with sequence file '%s'\n",io->st->optionlist[part]->in_align_file);
PhyML_Printf("\n. # taxa found in supertree restricted to '%s' taxa = %d\n",
io->st->optionlist[part]->in_align_file,
treelist->tree[part]->n_otu);
PhyML_Printf("\n. # sequences in '%s' = %d\n",
io->st->optionlist[part]->in_align_file,
cdata[part]->n_otu);
Exit("\n");
}
treelist->tree[part]->dp = part;
treelist->tree[part]->n_otu = cdata[part]->n_otu;
treelist->tree[part]->mod = mod[part];
treelist->tree[part]->io = io->st->optionlist[part];
treelist->tree[part]->data = cdata[part];
treelist->tree[part]->both_sides = 1;
treelist->tree[part]->n_pattern = treelist->tree[part]->data->crunch_len/
treelist->tree[part]->io->mod->state_len;
Order_Tree_CSeq(treelist->tree[part],cdata[part]);
Fill_Dir_Table(treelist->tree[part]);
Update_Dirs(treelist->tree[part]);
Make_Tree_4_Lk(treelist->tree[part],cdata[part],cdata[part]->init_len);
Make_Tree_4_Pars(treelist->tree[part],cdata[part],cdata[part]->init_len);
treelist->tree[part]->triplet_struct = Make_Triplet_Struct(treelist->tree[part]->mod);
}
if(part != io->n_part)
{
PhyML_Printf("\n. Sequence data part found in '%s' has one or more taxa not found in the '%s' tree file\n",
io->st->optionlist[part]->in_align_file,
io->in_tree_file);
Exit("\n");
}
PART_Check_Extra_Taxa(st);
st->tree->c_lnL = .0;
For(part,io->n_part)
{
Lk(treelist->tree[part]);
/* Get_List_Of_Reachable_Tips(treelist->tree[part]); */
PART_Match_St_Nodes_In_Gt(treelist->tree[part],st);
PART_Match_St_Edges_In_Gt(treelist->tree[part],st);
PART_Map_St_Nodes_In_Gt(treelist->tree[part],st);
PART_Map_St_Edges_In_Gt(treelist->tree[part],st);
PART_Map_Gt_Edges_In_St(treelist->tree[part],st);
st->tree->c_lnL += treelist->tree[part]->c_lnL;
}
PART_Initialise_Bl_Partition(st);
PART_Set_Bl(st->bl,st);
time(&(st->tree->t_beg));
time(&(st->tree->t_current));
PhyML_Printf("\n. (%5d sec) [00] [%10.2f] [%5d]\n",
(int)(st->tree->t_current-st->tree->t_beg),
PART_Lk(st),
PART_Pars(st));
int n_iter=0;
do
{
PART_Optimize_Br_Len_Serie(st->tree->t_nodes[0],
st->tree->t_nodes[0]->v[0],
st->tree->t_nodes[0]->b[0],
st);
st->tree->both_sides = 1;
PART_Lk(st);
PhyML_Printf("\n. %f",st->tree->c_lnL);
/* For(part,st->n_part) PhyML_Printf("\n. %s",Write_Tree(st->treelist->tree[part],NO)); */
n_iter++;
}while(n_iter < 5);
/* Exit("\n"); */
/* PART_Lk(st); */
/* PhyML_Printf("\n> %f",st->tree->c_lnL); */
/* For(i,2*st->tree->n_otu-3) */
/* { */
/* if((!st->tree->t_edges[i]->left->tax) && (!st->tree->t_edges[i]->rght->tax)) */
/* { */
/* PART_NNI(st->tree->t_edges[i],st); */
/* } */
/* } */
/* if(io->mod->s_opt->topo_search == NNI_MOVE) */
PART_Simu(st);
/* else */
/* PART_Speed_Spr(st); */
time(&t_end);
hour = div(t_end-t_beg,3600);
min = div(t_end-t_beg,60 );
min.quot -= hour.quot*60;
PhyML_Fprintf(fp_phyml_stats,"\n%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%\n\n");
PhyML_Fprintf(fp_phyml_stats,"\n. Number of partitions = %d\n\n",st->n_part);
PhyML_Fprintf(fp_phyml_stats,"\n. Full data set -- lnL = %f\n\n",st->tree->c_lnL);
PhyML_Fprintf(fp_phyml_stats,"\n. Tree search algorithm : %s\n\n",(io->mod->s_opt->topo_search == NNI_MOVE)?("NNIs"):("SPRs"));
PhyML_Fprintf(fp_phyml_stats,"\n%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%\n\n\n");
For(part,io->n_part)
{
Print_Fp_Out(fp_phyml_stats,t_beg,t_end,st->treelist->tree[part],
io->st->optionlist[part],1,1);
}
PhyML_Printf("\n\n. Time used %dh%dm%ds\n", hour.quot,min.quot,(int)(t_end-t_beg)%60);
PhyML_Printf("\n%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%\n\n");
For(i,2*st->tree->n_otu-3) st->tree->t_edges[i]->l = 0.1;
s_tree = Write_Tree(st->tree,NO);
PhyML_Fprintf(fp_phyml_tree,"Supertree\n");
PhyML_Fprintf(fp_phyml_tree,"%s\n",s_tree);
Free(s_tree);
For(part,st->n_part)
{
PhyML_Fprintf(fp_phyml_tree,"Gene tree number %d\n",part+1);
s_tree = Write_Tree(st->treelist->tree[part],NO);
PhyML_Fprintf(fp_phyml_tree,"%s\n",s_tree);
Free(s_tree);
}
For(part,st->n_part)
{
if(io->mod->s_opt->topo_search == SPR_MOVE) Free_Spr_List(treelist->tree[part]);
Free_Tree_Lk(treelist->tree[part]);
Free_Tree_Pars(treelist->tree[part]);
Free_Triplet(treelist->tree[part]->triplet_struct);
Free_Tree(treelist->tree[part]);
Free_Cseq(cdata[part]);
Free_Model(mod[part]);
Free_Input(io->st->optionlist[part]);
}
if(io->mod->s_opt->topo_search == SPR_MOVE) Free_Spr_List(st->tree);
Free(mat);
Free(mod);
Free(data);
Free(cdata);
Free(treelist->tree);
Free(treelist);
Free_St(st);
}
if(io->fp_in_align ) fclose(io->fp_in_align);
if(io->fp_in_tree) fclose(io->fp_in_tree);
Free_Model(io->mod);
Free_Input(io);
fclose(fp_phyml_lk);
fclose(fp_phyml_tree);
fclose(fp_phyml_stats);
return 0;
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void PART_Print_Nodes(t_node *a, t_node *d, supert_tree *st)
{
int i;
PhyML_Printf(">>>>>>>>>>>>>>>>>>>>\n");
PhyML_Printf("num t_node = %d\n",d->num);
if(d->tax) PhyML_Printf("name='%s'\n",d->name);
else
{
PhyML_Printf("n_of_reachable_tips : \n");
For(i,3)
{
/* PhyML_Printf("dir%d=%d; ",i,st->n_of_reachable_tips[st->num_data_of_interest][d->num][i]); */
/* For(j,st->n_of_reachable_tips[st->num_data_of_interest][d->num][i]) */
/* { */
/* PhyML_Printf("%s ", */
/* st->list_of_reachable_tips[st->num_data_of_interest][d->num][i][j]->name); */
/* } */
PhyML_Printf("\n");
}
}
PhyML_Printf("<<<<<<<<<<<<<<<<<<<\n\n");
if(d->tax) return;
else
{
For(i,3) if(d->v[i] != a) PART_Print_Nodes(d,d->v[i],st);
}
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
supert_tree *PART_Make_Supert_tree_Light(option *input)
{
supert_tree *st;
st = (supert_tree *)mCalloc(1,sizeof(supert_tree));
st->optionlist = (option **)mCalloc(input->n_part,sizeof(option *));
st->bl_partition = (int *)mCalloc(input->n_part,sizeof(int ));
return st;
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void PART_Make_Supert_tree_Full(supert_tree *st, option *io, calign **data)
{
int i,j,k;
if(io->in_tree == 2)
{
PhyML_Printf("\n. Reading user tree...\n");
rewind(io->fp_in_tree);
st->tree = Read_Tree_File_Phylip(io->fp_in_tree);
if(!st->tree->has_branch_lengths)
{
PhyML_Printf("\n. Branch lengths are all set to 0.1...\n");
For(i,2*st->tree->n_otu-3) st->tree->t_edges[i]->l = 0.1;
}
}
else
{
Warn_And_Exit("\n. A user-defined input tree is needed\n");
}
st->tree->io = io;
st->treelist = (t_treelist *)Make_Treelist(io->n_part);
st->n_part = io->n_part;
st->tree->mod = io->mod;
st->lock_br_len = 0;
st->map_st_node_in_gt = (t_node *****)mCalloc(st->n_part,sizeof(t_node ****));
For(i,st->n_part)
{
st->map_st_node_in_gt[i] = (t_node ****)mCalloc(2*st->tree->n_otu-2,sizeof(t_node ***));
For(j,2*st->tree->n_otu-2)
{
st->map_st_node_in_gt[i][j] = (t_node ***)mCalloc(3,sizeof(t_node **));
For(k,3) st->map_st_node_in_gt[i][j][k] = (t_node **)mCalloc(2,sizeof(t_node *));
}
}
st->map_st_edge_in_gt = (t_edge ***)mCalloc(st->n_part,sizeof(t_edge **));
For(i,st->n_part) st->map_st_edge_in_gt[i] = (t_edge **)mCalloc(2*st->tree->n_otu-3,sizeof(t_edge *));
st->map_gt_edge_in_st = (t_edge ****)mCalloc(st->n_part,sizeof(t_edge ***));
For(i,st->n_part)
{
st->map_gt_edge_in_st[i] = (t_edge ***)mCalloc(2*st->tree->n_otu-3,sizeof(t_edge **));
For(j,2*st->tree->n_otu-3) st->map_gt_edge_in_st[i][j] = (t_edge **)mCalloc(2*st->tree->n_otu-3,sizeof(t_edge *));
}
st->size_map_gt_edge_in_st = (int **)mCalloc(st->n_part,sizeof(int *));
For(i,st->n_part) st->size_map_gt_edge_in_st[i] = (int *)mCalloc(2*st->tree->n_otu-3,sizeof(int));
st->match_st_edge_in_gt = (t_edge ***)mCalloc(st->n_part,sizeof(t_edge **));
For(i,st->n_part) st->match_st_edge_in_gt[i] = (t_edge **)mCalloc(2*st->tree->n_otu-3,sizeof(t_edge *));
st->match_gt_edge_in_st = (t_edge ***)mCalloc(st->n_part,sizeof(t_edge **));
For(i,st->n_part) st->match_gt_edge_in_st[i] = (t_edge **)mCalloc(2*st->tree->n_otu-3,sizeof(t_edge *));
st->bl = (phydbl **)mCalloc(st->n_part,sizeof(phydbl *));
For(i,st->n_part) st->bl[i] = (phydbl *)mCalloc(2*st->tree->n_otu-3,sizeof(phydbl));
st->bl_cpy = (phydbl **)mCalloc(st->n_part,sizeof(phydbl *));
For(i,st->n_part) st->bl_cpy[i] = (phydbl *)mCalloc(2*st->tree->n_otu-3,sizeof(phydbl));
st->bl0 = (phydbl **)mCalloc(st->n_part,sizeof(phydbl *));
For(i,st->n_part) st->bl0[i] = (phydbl *)mCalloc(2*st->tree->n_otu-3,sizeof(phydbl));
st->bl1 = (phydbl **)mCalloc(st->n_part,sizeof(phydbl *));
For(i,st->n_part) st->bl1[i] = (phydbl *)mCalloc(2*st->tree->n_otu-3,sizeof(phydbl));
st->bl2 = (phydbl **)mCalloc(st->n_part,sizeof(phydbl *));
For(i,st->n_part) st->bl2[i] = (phydbl *)mCalloc(2*st->tree->n_otu-3,sizeof(phydbl));
st->s_mod = (model **)mCalloc(st->n_part,sizeof(model *));
For(i,2*st->tree->n_otu-3) Make_Edge_NNI(st->tree->t_edges[i]);
st->match_st_node_in_gt = (t_node ***)mCalloc(io->n_part,sizeof(t_node **));
For(i,io->n_part) st->match_st_node_in_gt[i] = (t_node **)mCalloc(2*st->tree->n_otu-2,sizeof(t_node *));
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void PART_Prune_St_Topo(t_tree *tree, calign *data, supert_tree *st)
{
int i,j,not_found;
int curr_ext_node, curr_int_node, curr_br, n_pruned_nodes;;
t_node **pruned_nodes;
t_edge **residual_edges;
pruned_nodes = (t_node **)mCalloc(st->tree->n_otu,sizeof(t_node *));
residual_edges = (t_edge **)mCalloc(st->tree->n_otu,sizeof(t_edge *));
n_pruned_nodes = 0;
For(i,st->tree->n_otu)
{
For(j,data->n_otu)
{
if(!strcmp(data->c_seq[j]->name,st->tree->t_nodes[i]->name))
break;
}
not_found = 1;
if(j == data->n_otu)
{
For(j,tree->n_otu)
{
if(!strcmp(tree->t_nodes[j]->name,st->tree->t_nodes[i]->name))
{
Prune_Subtree(tree->t_nodes[j]->v[0],
tree->t_nodes[j],
NULL,&(residual_edges[n_pruned_nodes]),
tree);
pruned_nodes[n_pruned_nodes] = tree->t_nodes[j];
n_pruned_nodes++;
not_found = 0;
break;
}
}
if(not_found)
{
PhyML_Printf("\n. Taxon '%s'",st->tree->t_nodes[i]->name);
PhyML_Printf("\n. Err in file %s at line %d\n\n",__FILE__,__LINE__);
Warn_And_Exit("");
}
}
}
Free(tree->t_dir);
tree->n_otu -= n_pruned_nodes;
curr_ext_node = 0;
curr_int_node = tree->n_otu;
curr_br = 0;
For(i,st->tree->n_otu)
{
For(j,n_pruned_nodes)
{
if(!strcmp(pruned_nodes[j]->name,st->tree->t_nodes[i]->name))
break;
}
if(j == n_pruned_nodes) /* That t_node still belongs to the tree */
{
Reassign_Node_Nums(tree->t_nodes[i],tree->t_nodes[i]->v[0],
&curr_ext_node, &curr_int_node,tree);
break;
}
}
Reassign_Edge_Nums(tree->t_nodes[0],tree->t_nodes[0]->v[0],&curr_br,tree);
tree->t_dir = (short int *)mCalloc((2*tree->n_otu-2)*(2*tree->n_otu-2),sizeof(short int));
For(i,n_pruned_nodes)
{
Free_Edge(residual_edges[i]);
Free_Edge(pruned_nodes[i]->b[0]);
Free_Node(pruned_nodes[i]->v[0]);
Free_Node(pruned_nodes[i]);
}
Free(pruned_nodes);
Free(residual_edges);
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void PART_Match_St_Nodes_In_Gt(t_tree *gt, supert_tree *st)
{
int i,j;
For(i,2*st->tree->n_otu-2) st->match_st_node_in_gt[gt->dp][i] = NULL; /* don't forget that step ! */
/* Map tips */
For(i,st->tree->n_otu)
{
For(j,gt->n_otu)
{
if(!strcmp(st->tree->t_nodes[i]->name,gt->t_nodes[j]->name))
{
st->match_st_node_in_gt[gt->dp][st->tree->t_nodes[i]->num] = gt->t_nodes[j];
break;
}
}
}
#ifdef DEBUG
/* Checking that the results are correct so far */
int n_matches;
n_matches = 0;
For(i,2*st->tree->n_otu-2)
if(st->match_st_node_in_gt[gt->dp][i])
n_matches++;
if(n_matches != gt->n_otu)
{
PhyML_Printf("\n");
PhyML_Printf("\n. n_matches = %d 2*gt->n_otu-2 = %d\n",n_matches,2*gt->n_otu-2);
PhyML_Printf("\n. Err in file %s at line %d\n\n",__FILE__,__LINE__);
Warn_And_Exit("");
}
#endif
/* Map internal nodes */
For(i,st->tree->n_otu)
{
if(st->match_st_node_in_gt[gt->dp][st->tree->t_nodes[i]->num])
{
PART_Match_St_Nodes_In_Gt_Recurr(st->match_st_node_in_gt[gt->dp][st->tree->t_nodes[i]->num],
st->match_st_node_in_gt[gt->dp][st->tree->t_nodes[i]->num]->v[0],
st->tree->t_nodes[i],
st->tree->t_nodes[i]->v[0],
gt,
st);
break;
}
}
#ifdef DEBUG
/* Checking that the results are correct */
n_matches = 0;
For(i,2*st->tree->n_otu-2)
if(st->match_st_node_in_gt[gt->dp][st->tree->t_nodes[i]->num])
n_matches++;
if(n_matches != 2*gt->n_otu-2)
{
int j;
PhyML_Printf("\n");
PhyML_Printf("\n. n_matches = %d 2*gt->n_otu-2 = %d\n",n_matches,2*gt->n_otu-2);
For(j,2*gt->n_otu-2)
{
For(i,2*st->tree->n_otu-2)
if(st->match_st_node_in_gt[gt->dp][i] == gt->t_nodes[j])
break;
if(i == 2*st->tree->n_otu-2)
{
PhyML_Printf("\n. Gt %3d t_node %3d (%3d %3d %3d) (%s %s %s) (%f %f %f) does not match\n",
gt->dp,
gt->t_nodes[j]->num,
gt->t_nodes[j]->v[0] ? gt->t_nodes[j]->v[0]->num : -1,
gt->t_nodes[j]->v[1] ? gt->t_nodes[j]->v[1]->num : -1,
gt->t_nodes[j]->v[2] ? gt->t_nodes[j]->v[2]->num : -1,
gt->t_nodes[j]->v[0]->tax ? gt->t_nodes[j]->v[0]->name : NULL,
gt->t_nodes[j]->v[1]->tax ? gt->t_nodes[j]->v[1]->name : NULL,
gt->t_nodes[j]->v[2]->tax ? gt->t_nodes[j]->v[2]->name : NULL,
gt->t_nodes[j]->v[0] ? gt->t_nodes[j]->b[0]->l : -1.,
gt->t_nodes[j]->v[1] ? gt->t_nodes[j]->b[1]->l : -1.,
gt->t_nodes[j]->v[2] ? gt->t_nodes[j]->b[2]->l : -1.);
}
}
PhyML_Printf("oooooooo\n");
Print_Node(st->tree->t_nodes[0],
st->tree->t_nodes[0]->v[0],
st->tree);
PhyML_Printf(">>>>>>>\n");
For(i,st->n_part)
{
Print_Node(st->treelist->tree[i]->t_nodes[0],
st->treelist->tree[i]->t_nodes[0]->v[0],
st->treelist->tree[i]);
PhyML_Printf("<<<<<<<\n");
}
PhyML_Printf("\n. Err in file %s at line %d\n\n",__FILE__,__LINE__);
Warn_And_Exit("");
}
#endif
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void PART_Match_St_Nodes_In_Gt_Recurr(t_node *a_gt, t_node *d_gt, t_node *a_st, t_node *d_st, t_tree *gt, supert_tree *st)
{
int i,j,k;
int *score_d_st;
if((d_gt->tax) || (d_st->tax)) return;
else
{
score_d_st = (int *)mCalloc(3,sizeof(int));
/* Might be wrong. Check function Match_Nodes_In_Small_Tree */
For(i,3)
{
For(j,3)
{
For(k,d_st->bip_size[j])
{
if(!strcmp(d_gt->bip_node[i][0]->name,d_st->bip_node[j][k]->name))
{
score_d_st[j] += 1;
break;
}
}
}
}
if((score_d_st[0] == 2) && (score_d_st[1] == 2) && (score_d_st[2] == 2))
{
st->match_st_node_in_gt[gt->dp][d_st->num] = d_gt;
For(i,3)
{
if(d_gt->v[i] != a_gt)
{
For(j,3)
{
if(score_d_st[j] != 3)
{
PART_Match_St_Nodes_In_Gt_Recurr(d_gt,d_gt->v[i],d_st,d_st->v[j],gt,st);
break;
}
/* For(k,d_st->n_of_reachable_tips[j]) */
/* if(!strcmp(d_gt->list_of_reachable_tips[i][0]->name, */
/* d_st->list_of_reachable_tips[j][k]->name)) */
/* { */
/* PART_Match_St_Nodes_In_Gt_Recurr(d_gt,d_gt->v[i],d_st,d_st->v[j],gt,st); */
/* break; */
/* } */
/* if(k != d_st->n_of_reachable_tips[j]) break; */
}
}
}
}
else
{
For(i,3)
if(d_st->v[i] != a_st)
PART_Match_St_Nodes_In_Gt_Recurr(a_gt,d_gt,d_st,d_st->v[i],gt,st);
}
Free(score_d_st);
}
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void PART_Match_St_Edges_In_Gt(t_tree *gt, supert_tree *st)
{
int i;
For(i,2*st->tree->n_otu-3)
{
st->match_st_edge_in_gt[gt->dp][i] = NULL;
st->match_gt_edge_in_st[gt->dp][i] = NULL;
}
For(i,st->tree->n_otu)
if(st->match_st_node_in_gt[gt->dp][i])
{
PART_Match_St_Edges_In_Gt_Recurr(st->match_st_node_in_gt[gt->dp][i],
st->match_st_node_in_gt[gt->dp][i]->v[0],
st->tree->t_nodes[i],
st->tree->t_nodes[i]->v[0],
gt,st);
break;
}
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void PART_Match_St_Edges_In_Gt_Recurr(t_node *a_gt, t_node *d_gt, t_node *a_st, t_node *d_st, t_tree *gt, supert_tree *st)
{
t_edge *b_gt, *b_st;
int i,j;
b_gt = b_st = NULL;
if((st->match_st_node_in_gt[gt->dp][a_st->num] == a_gt) &&
(st->match_st_node_in_gt[gt->dp][d_st->num] == d_gt))
{
For(i,3) if((a_st->v[i]) && (a_st->v[i] == d_st)) {b_st = a_st->b[i]; break;}
For(i,3) if((a_gt->v[i]) && (a_gt->v[i] == d_gt)) {b_gt = a_gt->b[i]; break;}
st->match_st_edge_in_gt[gt->dp][b_st->num] = b_gt;
st->match_gt_edge_in_st[gt->dp][b_gt->num] = b_st;
}
if(!d_gt)
{
PhyML_Printf("\n");
PhyML_Printf("\n. a_gt->num = %d\n",a_gt->num);
PhyML_Printf("\n. Err in file %s at line %d\n\n",__FILE__,__LINE__);
Warn_And_Exit("");
}
if(d_gt->tax || d_st->tax) return;
else
{
if(st->match_st_node_in_gt[gt->dp][d_st->num] == d_gt)
{
For(i,3)
{
if(d_gt->v[i] != a_gt)
{
For(j,3)
{
/* For(k,d_st->n_of_reachable_tips[j]) */
/* if(!strcmp(d_gt->list_of_reachable_tips[i][0]->name,d_st->list_of_reachable_tips[j][k]->name)) */
{
PART_Match_St_Edges_In_Gt_Recurr(d_gt,d_gt->v[i],d_st,d_st->v[j],gt,st);
break;
}
/* if(k != d_st->n_of_reachable_tips[j]) break; */
}
}
}
}
else
{
For(i,3)
if(d_st->v[i] != a_st)
PART_Match_St_Edges_In_Gt_Recurr(a_gt,d_gt,d_st,d_st->v[i],gt,st);
}
}
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void PART_Simu(supert_tree *st)
{
int i,j,step,n_without_swap,it_lim_without_swap;
t_edge **sorted_b,*st_b,**tested_b;
int n_neg,n_tested,each;
phydbl lambda,old_loglk;
sorted_b = (t_edge **)mCalloc(st->tree->n_otu-3,sizeof(t_edge *));
tested_b = (t_edge **)mCalloc(st->tree->n_otu-3,sizeof(t_edge *));
For(i,st->n_part) Update_Dirs(st->treelist->tree[i]);
Update_Dirs(st->tree);
each = 4;
step = 0;
lambda = .75;
n_tested = 0;
n_without_swap = 0;
old_loglk = UNLIKELY;
it_lim_without_swap = 2;
st_b = NULL;
do
{
For(i,st->n_part) Check_Dirs(st->treelist->tree[i]);
++step;
each--;
/* PART_Print_Bl(st); */
/* Compute the likelihood of the supertreee */
st->tree->c_lnL = PART_Lk(st);
st->tree->c_pars = PART_Pars(st);
/* For(i,st->n_part) PhyML_Printf("\n. %s",Write_Tree(st->treelist->tree[i],NO)); */
/* PhyML_Printf("\n"); */
time(&(st->tree->t_current));
PhyML_Printf("\n. (%5d sec) [tot lnL=%15.5f] [# swaps=%3d]",
(int)(st->tree->t_current-st->tree->t_beg),
st->tree->c_lnL,n_tested);
/* For(i,st->n_part) PhyML_Printf("\n[gt %3d lnL=%15.5f]",i,st->treelist->tree[i]->c_lnL); */
if((FABS(old_loglk-st->tree->c_lnL) < st->tree->mod->s_opt->min_diff_lk_global) ||
(n_without_swap > it_lim_without_swap)) break;
if(st->tree->c_lnL < old_loglk)
{
PhyML_Printf("\n. Moving backward (topology + branch lengths) \n");
if(!PART_Mov_Backward_Topo_Bl(st,old_loglk,tested_b,n_tested))
Warn_And_Exit("\n. Err: mov_back failed\n");
if(!st->tree->n_swap) n_neg = 0;
PART_Record_Br_Len(st);
For(i,st->n_part) Optimiz_All_Free_Param(st->treelist->tree[i],0);
}
else
{
if(!each)
{
each = 4;
/* Markov model parameters are free to vary across data partitions */
For(i,st->n_part) Optimiz_All_Free_Param(st->treelist->tree[i],0);
For(i,st->n_part) st->treelist->tree[i]->both_sides = 1;
st->tree->c_lnL = PART_Lk(st);
st->tree->c_pars = PART_Pars(st);
}
old_loglk = st->tree->c_lnL;
For(i,2*st->tree->n_otu-3) Init_NNI(st->tree->t_edges[i]->nni);
/* Test NNIs */
For(i,2*st->tree->n_otu-3)
{
st_b = st->tree->t_edges[i];
if((!st_b->left->tax) && (!st_b->rght->tax)) PART_NNI(st_b,st);
}
/* Optimise external branch lengths */
For(i,2*st->tree->n_otu-3)
{
st_b = st->tree->t_edges[i];
if((st_b->left->tax) || (st_b->rght->tax))
{
PART_Record_Br_Len(st);
PART_Br_Len_Brent(st_b,0,st);
For(j,st->n_part) st->bl0[st->bl_partition[j]][st_b->num] = st->bl[st->bl_partition[j]][st_b->num];
st_b->nni->score = .0;
st_b->nni->best_conf = 0;
PART_Restore_Br_Len(st);
PART_Lk_At_Given_Edge(st_b,st);
}
}
/* Select and sort swaps */
n_neg = 0;
Select_Edges_To_Swap(st->tree,sorted_b,&n_neg);
Sort_Edges_NNI_Score(st->tree,sorted_b,n_neg);
n_tested = 0;
For(i,(int)CEIL((phydbl)n_neg*(lambda)))
tested_b[n_tested++] = sorted_b[i];
if(n_tested > 0) n_without_swap = 0;
else n_without_swap++;
PART_Record_Br_Len(st);
/* Apply swaps */
PART_Make_N_Swap(tested_b,0,n_tested,st);
/* Update branch lengths (all edges first and then swaped edges) */
PART_Update_Bl(lambda,st);
PART_Update_Bl_Swaped(tested_b,n_tested,st);
}
}
while(1);
PhyML_Printf("\n\n. End of PART_Simu \n");
Free(sorted_b);
Free(tested_b);
if((n_without_swap > it_lim_without_swap))
{
PhyML_Printf("\n. Last optimization step...\n");
For(i,st->n_part) Round_Optimize(st->treelist->tree[i],st->treelist->tree[i]->data,ROUND_MAX);
st->tree->c_lnL = PART_Lk(st);
PART_Simu(st);
}
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
int PART_Mov_Backward_Topo_Bl(supert_tree *st, phydbl lk_old, t_edge **tested_b, int n_tested)
{
int i,j,step,beg,end;
t_edge *st_b;
phydbl **l_init;
int dim;
l_init = (phydbl **)mCalloc(st->n_part,sizeof(phydbl *));
For(i,st->n_part) l_init[i] = (phydbl *)mCalloc(2*st->tree->n_otu-3,sizeof(phydbl ));
For(i,2*st->tree->n_otu-3) For(j,st->n_part) l_init[st->bl_partition[j]][i] = st->bl[st->bl_partition[j]][i];
step = 2;
do
{
For(i,2*st->tree->n_otu-3)
{
For(j,st->n_part)
{
st->bl[st->bl_partition[j]][i] = st->bl_cpy[st->bl_partition[j]][i] +
(1./step) * (l_init[st->bl_partition[j]][i] - st->bl_cpy[st->bl_partition[j]][i]);
/* st->bl[st->bl_partition[j]][i] = st->bl_cpy[st->bl_partition[j]][i]; */
}
}
beg = (int)FLOOR((phydbl)n_tested/(step-1));
end = 0;
st_b = NULL;
dim = 2*st->tree->n_otu-2;
for(i=beg-1;i>=end;i--)
{
st_b = tested_b[i];
PART_Swap(st_b->nni->swap_node_v2->v[st->tree->t_dir[st_b->nni->swap_node_v2->num*dim+st_b->nni->swap_node_v1->num]],
st_b->nni->swap_node_v2,
st_b->nni->swap_node_v3,
st_b->nni->swap_node_v3->v[st->tree->t_dir[st_b->nni->swap_node_v3->num*dim+st_b->nni->swap_node_v4->num]],
st);
Swap(st_b->nni->swap_node_v2->v[st->tree->t_dir[st_b->nni->swap_node_v2->num*dim+st_b->nni->swap_node_v1->num]],
st_b->nni->swap_node_v2,
st_b->nni->swap_node_v3,
st_b->nni->swap_node_v3->v[st->tree->t_dir[st_b->nni->swap_node_v3->num*dim+st_b->nni->swap_node_v4->num]],
st->tree);
PART_Do_Mapping(st);
}
beg = 0;
end = (int)FLOOR((phydbl)n_tested/step);
st_b = NULL;
dim = 2*st->tree->n_otu-2;
for(i=beg;inni->swap_node_v2->v[st->tree->t_dir[st_b->nni->swap_node_v2->num*dim+st_b->nni->swap_node_v1->num]],
st_b->nni->swap_node_v2,
st_b->nni->swap_node_v3,
st_b->nni->swap_node_v3->v[st->tree->t_dir[st_b->nni->swap_node_v3->num*dim+st_b->nni->swap_node_v4->num]],
st);
Swap(st_b->nni->swap_node_v2->v[st->tree->t_dir[st_b->nni->swap_node_v2->num*dim+st_b->nni->swap_node_v1->num]],
st_b->nni->swap_node_v2,
st_b->nni->swap_node_v3,
st_b->nni->swap_node_v3->v[st->tree->t_dir[st_b->nni->swap_node_v3->num*dim+st_b->nni->swap_node_v4->num]],
st->tree);
PART_Do_Mapping(st);
}
if(!end) st->tree->n_swap = 0;
PART_Lk(st);
PhyML_Printf("\n. lnL = %15.5f",st->tree->c_lnL);
step++;
}
while((st->tree->c_lnL < lk_old) && (step < 100));
if(step == 100)
{
For(i,2*st->tree->n_otu-3) For(j,st->n_part)
st->bl[st->bl_partition[j]][i] = st->bl_cpy[st->bl_partition[j]][i];
}
st->tree->n_swap = 0;
For(i,2*st->tree->n_otu-3)
{
if(st->tree->t_edges[i]->nni->score < 0.0) st->tree->n_swap++;
st->tree->t_edges[i]->nni->score = +1.0;
}
PART_Lk(st);
if(st->tree->c_lnL > lk_old) return 1;
else if(FABS(st->tree->c_lnL-lk_old) < st->tree->mod->s_opt->min_diff_lk_local) return -1;
else return 0;
For(i,st->n_part) Free(l_init[i]);
Free(l_init);
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void PART_Check_Extra_Taxa(supert_tree *st)
{
int i,j,k;
int sum;
int *st_taxa;
st_taxa = (int *)mCalloc(st->tree->n_otu,sizeof(int));
For(i,st->tree->n_otu)
{
For(j,st->n_part)
{
For(k,st->treelist->tree[j]->n_otu)
if(!strcmp(st->treelist->tree[j]->t_nodes[k]->name,st->tree->t_nodes[i]->name)) break;
if(k != st->treelist->tree[j]->n_otu) { st_taxa[i] = 1; break; }
}
}
sum = 0;
For(i,st->tree->n_otu) if(st_taxa[i]) sum++;
if(sum != st->tree->n_otu)
{
PhyML_Printf("\n. Err in file %s at line %d\n\n",__FILE__,__LINE__);
Warn_And_Exit("");
}
Free(st_taxa);
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
int PART_Get_Species_Found_In_St(supert_tree *st, calign *data)
{
int i,j;
For(i,data->n_otu)
{
For(j,st->tree->n_otu)
{
if(!strcmp(data->c_seq[i]->name,st->tree->t_nodes[j]->name))
{
break;
}
}
if(j == st->tree->n_otu) return 0;
}
return 1;
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void PART_Map_St_Nodes_In_Gt(t_tree *gt, supert_tree *st)
{
int i;
For(i,2*st->tree->n_otu-2)
{
st->map_st_node_in_gt[gt->dp][i][0][0] = NULL;
st->map_st_node_in_gt[gt->dp][i][1][0] = NULL;
st->map_st_node_in_gt[gt->dp][i][2][0] = NULL;
st->map_st_node_in_gt[gt->dp][i][0][1] = NULL;
st->map_st_node_in_gt[gt->dp][i][1][1] = NULL;
st->map_st_node_in_gt[gt->dp][i][2][1] = NULL;
}
/* Root */
PART_Map_St_Nodes_In_Gt_One_Edge(st->tree->t_nodes[0]->v[0],
st->tree->t_nodes[0],
st->tree->t_nodes[0]->b[0],
gt,st);
/* Internal nodes */
PART_Map_St_Nodes_In_Gt_Post(st->tree->t_nodes[0],st->tree->t_nodes[0]->v[0],gt,st);
PART_Map_St_Nodes_In_Gt_Pre (st->tree->t_nodes[0],st->tree->t_nodes[0]->v[0],gt,st);
/* Root */
PART_Map_St_Nodes_In_Gt_One_Edge(st->tree->t_nodes[0],
st->tree->t_nodes[0]->v[0],
st->tree->t_nodes[0]->b[0],
gt,st);
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void PART_Map_St_Nodes_In_Gt_Post(t_node *a_st, t_node *d_st, t_tree *gt, supert_tree *st)
{
int i,dir;
dir = -1;
if(d_st->tax) return;
else
{
For(i,3)
if(d_st->v[i] != a_st)
PART_Map_St_Nodes_In_Gt_Post(d_st,d_st->v[i],gt,st);
For(i,3)
if(d_st->v[i] != a_st)
{
PART_Map_St_Nodes_In_Gt_One_Edge(d_st,d_st->v[i],d_st->b[i],gt,st);
}
}
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void PART_Map_St_Nodes_In_Gt_Pre(t_node *a_st, t_node *d_st, t_tree *gt, supert_tree *st)
{
int i;
if(d_st->tax) return;
else
{
For(i,3)
{
if(d_st->v[i] != a_st)
{
PART_Map_St_Nodes_In_Gt_One_Edge(d_st->v[i],d_st,d_st->b[i],gt,st);
PART_Map_St_Nodes_In_Gt_Pre(d_st,d_st->v[i],gt,st);
}
}
}
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void PART_Map_St_Nodes_In_Gt_One_Edge(t_node *a_st, t_node *d_st, t_edge *b_st, t_tree *gt, supert_tree *st)
{
if(d_st->tax)
{
#ifdef DEBUG
if(b_st->rght != d_st)
{
PhyML_Printf("\n. Err in file %s at line %d\n\n",__FILE__,__LINE__);
Warn_And_Exit("");
}
#endif
st->map_st_node_in_gt[gt->dp][d_st->num][0][0] = st->match_st_node_in_gt[gt->dp][d_st->num];
}
else
{
t_node **list_of_nodes_d, **list_of_nodes_v1, **list_of_nodes_v2;
int dir1, dir2;
int i;
list_of_nodes_d = NULL;
list_of_nodes_v1 = NULL;
list_of_nodes_v2 = NULL;
dir1 = dir2 = -1;
For(i,3)
{
if(d_st->v[i] != a_st) (dir1 < 0)?(dir1 = i):(dir2 = i);
else list_of_nodes_d = st->map_st_node_in_gt[gt->dp][d_st->num][i];
}
For(i,3)
if((d_st->v[dir1]->v[i]) && (d_st->v[dir1]->v[i] == d_st))
{
list_of_nodes_v1 = st->map_st_node_in_gt[gt->dp][d_st->v[dir1]->num][i];
break;
}
For(i,3)
if((d_st->v[dir2]->v[i]) && (d_st->v[dir2]->v[i] == d_st))
{
list_of_nodes_v2 = st->map_st_node_in_gt[gt->dp][d_st->v[dir2]->num][i];
break;
}
/* d_st matches one t_node in gt */
if(st->match_st_node_in_gt[gt->dp][d_st->num])
{
list_of_nodes_d[0] = st->match_st_node_in_gt[gt->dp][d_st->num];
list_of_nodes_d[1] = NULL;
}
else
{
/* list_of_nodes = union of list_of_nodes_v1 & list_of_nodes_v2 */
if(!list_of_nodes_v1[0])
{
list_of_nodes_d[0] = list_of_nodes_v2[0];
list_of_nodes_d[1] = list_of_nodes_v2[1];
}
else if(!list_of_nodes_v2[0])
{
list_of_nodes_d[0] = list_of_nodes_v1[0];
list_of_nodes_d[1] = list_of_nodes_v1[1];
}
else
{
list_of_nodes_d[0] = list_of_nodes_v1[0];
list_of_nodes_d[1] = list_of_nodes_v2[0];
if(list_of_nodes_v1[1] || list_of_nodes_v2[1])
{
Print_Node(st->tree->t_nodes[0],
st->tree->t_nodes[0]->v[0],
st->tree);
PhyML_Printf("\n\n--------------------------\n\n");
Print_Node(gt->t_nodes[0],
gt->t_nodes[0]->v[0],
gt);
PhyML_Printf("\n\n--------------------------\n\n");
PhyML_Printf("\n. Err in file %s at line %d\n\n",__FILE__,__LINE__);
Warn_And_Exit("");
}
}
}
}
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void PART_Map_St_Edges_In_Gt(t_tree *gt, supert_tree *st)
{
int i,j;
t_edge *st_b;
t_node *gt_a, *gt_d;
gt_a = NULL;
gt_d = NULL;
For(i,2*st->tree->n_otu-3) st->map_st_edge_in_gt[gt->dp][i] = NULL;
For(i,2*st->tree->n_otu-3)
{
st_b = st->tree->t_edges[i];
if(!st->map_st_node_in_gt[gt->dp][st_b->left->num][st_b->l_r][0])
{
gt_a = st->map_st_node_in_gt[gt->dp][st_b->rght->num][st_b->r_l][0];
gt_d = st->map_st_node_in_gt[gt->dp][st_b->rght->num][st_b->r_l][1];
For(j,3)
{
if((gt_a->v[j]) && (gt_a->v[j] == gt_d))
{
st->map_st_edge_in_gt[gt->dp][st_b->num] = gt_a->b[j];
break;
}
}
}
else if(!st->map_st_node_in_gt[gt->dp][st_b->rght->num][st_b->r_l][0])
{
gt_a = st->map_st_node_in_gt[gt->dp][st_b->left->num][st_b->l_r][0];
gt_d = st->map_st_node_in_gt[gt->dp][st_b->left->num][st_b->l_r][1];
For(j,3)
{
if((gt_a->v[j]) && (gt_a->v[j] == gt_d))
{
st->map_st_edge_in_gt[gt->dp][st_b->num] = gt_a->b[j];
break;
}
}
}
else
{
gt_a = st->map_st_node_in_gt[gt->dp][st_b->left->num][st_b->l_r][0];
gt_d = st->map_st_node_in_gt[gt->dp][st_b->rght->num][st_b->r_l][0];
#ifdef DEBUG
if((!gt_a) || (!gt_d))
{
PhyML_Printf("\n. Err in file %s at line %d\n\n",__FILE__,__LINE__);
Warn_And_Exit("");
}
#endif
For(j,3)
{
if((gt_a->v[j]) && (gt_a->v[j] == gt_d))
{
st->map_st_edge_in_gt[gt->dp][st_b->num] = gt_a->b[j];
break;
}
}
}
}
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void PART_Map_Gt_Edges_In_St(t_tree *gt, supert_tree *st)
{
int i;
t_edge *st_b, *gt_b;
For(i,2*st->tree->n_otu-3) st->size_map_gt_edge_in_st[gt->dp][i] = 0;
st_b = NULL;
gt_b = NULL;
For(i,2*st->tree->n_otu-3)
{
st_b = st->tree->t_edges[i];
gt_b = st->map_st_edge_in_gt[gt->dp][st_b->num];
if(gt_b)
{
st->map_gt_edge_in_st[gt->dp][gt_b->num][st->size_map_gt_edge_in_st[gt->dp][gt_b->num]] = st_b;
st->size_map_gt_edge_in_st[gt->dp][gt_b->num]++;
}
}
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
int PART_Pars(supert_tree *st)
{
int i;
st->tree->c_pars = 0;
For(i,st->n_part)
{
st->treelist->tree[i]->both_sides = 1;
Pars(st->treelist->tree[i]);
st->tree->c_pars += st->treelist->tree[i]->c_pars;
}
return st->tree->c_pars;
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
int PART_Spr(phydbl init_lnL, supert_tree *st)
{
int gt;
int i;
t_edge *target, *pruned;
int move,best_move;
t_node *gt_a, *gt_d;
st->tree->n_root = st->tree->t_nodes[0];
st->tree->both_sides = 1;
pruned = NULL;
target = NULL;
move = -2;
gt_a = NULL;
gt_d = NULL;
For(i,2*st->tree->n_otu-3)
{
pruned = st->tree->t_edges[i];
st->tree->n_moves = 0;
Reset_Spr_List(st->tree);
For(gt,st->n_part) Reset_Spr_List(st->treelist->tree[gt]);
if(!pruned->rght->tax)
{
For(gt,st->n_part)
{
/* Check constraints at prune site on gt tree */
gt_a = st->map_st_node_in_gt[gt][pruned->rght->num][pruned->r_l][0];
gt_d = st->map_st_node_in_gt[gt][pruned->left->num][pruned->l_r][0];
if((gt_a) && (gt_d) && (!st->map_st_edge_in_gt[gt][pruned->num]->rght->tax))
{
Test_All_Spr_Targets(st->map_st_edge_in_gt[gt][pruned->num],
st->map_st_edge_in_gt[gt][pruned->num]->rght,
st->treelist->tree[gt]);
}
}
}
if(!pruned->left->tax)
{
For(gt,st->n_part)
{
/* Check constraints at prune site on gt tree */
gt_a = st->map_st_node_in_gt[gt][pruned->rght->num][pruned->r_l][0];
gt_d = st->map_st_node_in_gt[gt][pruned->left->num][pruned->l_r][0];
if((gt_a) && (gt_d) && (!st->map_st_edge_in_gt[gt][pruned->num]->left->tax))
{
Test_All_Spr_Targets(st->map_st_edge_in_gt[gt][pruned->num],
st->map_st_edge_in_gt[gt][pruned->num]->left,
st->treelist->tree[gt]);
}
}
}
if(!pruned->left->tax)
{
PART_Test_All_Spr_Targets(st->tree->t_edges[i],
st->tree->t_edges[i]->left,
st);
}
if(!pruned->rght->tax)
{
PART_Test_All_Spr_Targets(st->tree->t_edges[i],
st->tree->t_edges[i]->rght,
st);
}
if(st->tree->n_moves)
{
best_move = PART_Test_List_Of_Regraft_Pos(st->tree->spr_list,
(int)CEIL(0.1*(st->tree->n_moves)),
st);
if(st->tree->spr_list[best_move]->lnL > init_lnL)
{
PART_Try_One_Spr_Move(st->tree->spr_list[best_move],st);
}
else
{
st->tree->both_sides = 1;
st->tree->c_lnL = PART_Lk(st);
st->tree->c_pars = PART_Pars(st);
}
}
}
return 1;
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void PART_Speed_Spr(supert_tree *st)
{
int step;
int gt;
phydbl old_lnL;
Make_Spr_List(st->tree);
For(gt,st->n_part) Make_Spr_List(st->treelist->tree[gt]);
st->tree->both_sides = 1;
For(gt,st->n_part)
{
st->treelist->tree[gt]->both_sides = 1;
Record_Br_Len(st->treelist->tree[gt]);
}
st->tree->c_pars = PART_Pars(st);
st->tree->c_lnL = PART_Lk(st);
st->tree->best_lnL = st->tree->c_lnL;
old_lnL = st->tree->c_lnL;
step = 0;
do
{
++step;
PhyML_Printf("\n. Starting a SPR cycle... \n");
old_lnL = st->tree->c_lnL;
st->tree->n_improvements = 0;
st->tree->perform_spr_right_away = 1;
PART_Spr(UNLIKELY,st);
time(&(st->tree->t_current));
PhyML_Printf("\n. (%5d sec) [00] [%10.2f] [%5d]\n",
(int)(st->tree->t_current-st->tree->t_beg),
PART_Lk(st),PART_Pars(st));
/* Optimise parameters of the Markov model */
For(gt,st->n_part) Optimiz_All_Free_Param(st->treelist->tree[gt],
st->treelist->tree[gt]->mod->s_opt->print);
time(&(st->tree->t_current));
PhyML_Printf("\n. (%5d sec) [ 0] [%10.2f] [%5d]\n",
(int)(st->tree->t_current-st->tree->t_beg),
PART_Lk(st),PART_Pars(st));
/* Optimise branch lengths */
For(gt,st->n_part)
{
Optimize_Br_Len_Serie(st->treelist->tree[gt]->t_nodes[0],
st->treelist->tree[gt]->t_nodes[0]->v[0],
st->treelist->tree[gt]->t_nodes[0]->b[0],
st->treelist->tree[gt],
st->treelist->tree[gt]->data);
}
/* Update partial likelihoods & parsimony */
st->tree->both_sides = 1;
st->tree->c_pars = PART_Pars(st);
st->tree->c_lnL = PART_Lk(st);
time(&(st->tree->t_current));
PhyML_Printf("\n. (%5d sec) [**] [%10.2f] [%5d]\n",
(int)(st->tree->t_current-st->tree->t_beg),
st->tree->c_lnL,st->tree->c_pars);
/* Record the current best log-likleihood */
st->tree->best_lnL = st->tree->c_lnL;
if(st->tree->c_lnL < old_lnL)
{
PhyML_Printf("\n. old_lnL = %f c_lnL = %f\n",old_lnL,st->tree->c_lnL);
PhyML_Printf("\n. Err in file %s at line %d\n\n",__FILE__,__LINE__);
Warn_And_Exit("");
}
/* Record the current best branch lengths */
For(gt,st->n_part) Record_Br_Len(st->treelist->tree[gt]);
/* Exit if no improvements after complete optimization */
if((!st->tree->n_improvements) ||
(FABS(old_lnL-st->tree->c_lnL) < st->tree->mod->s_opt->min_diff_lk_global)) break;
}while(1);
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void PART_Test_All_Spr_Targets(t_edge *pruned, t_node *n_link, supert_tree *st)
{
int i,j;
For(i,3)
{
if(n_link->b[i] != pruned)
{
For(j,3)
{
if((n_link->v[i]->v[j]) && (n_link->v[i]->v[j] != n_link))
{
PART_Test_One_Spr_Target_Recur(n_link->v[i],n_link->v[i]->v[j],n_link->v[i]->b[j],pruned,n_link,st);
}
}
}
}
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void PART_Test_One_Spr_Target_Recur(t_node *a, t_node *d, t_edge *target, t_edge *pruned, t_node *n_link, supert_tree *st)
{
PART_Test_One_Spr_Target(pruned,target,n_link,st);
if(d->tax) return;
else
{
int i;
For(i,3)
if(d->v[i] != a)
{
PART_Test_One_Spr_Target_Recur(d,d->v[i],d->b[i],pruned,n_link,st);
}
}
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void PART_Test_One_Spr_Target(t_edge *st_p, t_edge *st_t, t_node *n_link, supert_tree *st)
{
int gt, move;
st->tree->n_moves++;
st->tree->spr_list[st->tree->size_spr_list]->b_target = st_t;
st->tree->spr_list[st->tree->size_spr_list]->n_link = n_link;
st->tree->spr_list[st->tree->size_spr_list]->n_opp_to_link = (n_link == st_p->left)?(st_p->rght):(st_p->left);
st->tree->spr_list[st->tree->size_spr_list]->b_opp_to_link = st_p;
st->tree->spr_list[st->tree->size_spr_list]->pars = 0;
For(gt,st->n_part)
{
move = Map_Spr_Move(st_p,st_t,n_link,st->treelist->tree[gt],st);
if(move > -1)
st->tree->spr_list[st->tree->size_spr_list]->pars += st->treelist->tree[gt]->spr_list[move]->pars;
else if(move == -1 || move == -2)
st->tree->spr_list[st->tree->size_spr_list]->pars += st->treelist->tree[gt]->c_pars;
}
Include_One_Spr_To_List_Of_Spr(st->tree->spr_list[st->tree->size_spr_list],st->tree);
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
int Map_Spr_Move(t_edge *st_pruned, t_edge *st_target, t_node *st_link, t_tree *gt, supert_tree *st)
{
int i;
t_edge *gt_pruned, *gt_target;
t_node *gt_link, *gt_a, *gt_d;
gt_pruned = NULL;
gt_target = NULL;
gt_link = NULL;
gt_a = NULL;
gt_d = NULL;
/* Check contraints at prune and regraft sites on the gt tree */
/* st_pruned is not on a path that matches a branch in gt */
gt_a = st->map_st_node_in_gt[gt->dp][st_pruned->left->num][st_pruned->l_r][0];
gt_d = st->map_st_node_in_gt[gt->dp][st_pruned->rght->num][st_pruned->r_l][0];
if((!gt_a) || (!gt_d)) return -1;
else
{
/* which gt nodes matches st_link ? */
gt_link = (st_pruned->left == st_link)?(gt_a):(gt_d);
if(gt_link->tax) return -1;
else
{
gt_pruned = st->map_st_edge_in_gt[gt->dp][st_pruned->num];
gt_target = st->map_st_edge_in_gt[gt->dp][st_target->num];
if((gt_pruned->left == gt_target->left) ||
(gt_pruned->left == gt_target->rght) ||
(gt_pruned->rght == gt_target->left) ||
(gt_pruned->rght == gt_target->rght)) return -1;
else
{
For(i,gt->size_spr_list)
{
if((gt_pruned == gt->spr_list[i]->b_opp_to_link) && (gt_target == gt->spr_list[i]->b_target))
return i;
}
}
}
}
return -2;
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
int PART_Test_List_Of_Regraft_Pos(spr **st_spr_list, int list_size, supert_tree *st)
{
int i,j,best_move;
spr *move;
t_edge *init_target, *b_residual;
phydbl best_lnL, init_lnL;
int dir_v0, dir_v1, dir_v2;
int gt;
int move_num;
best_lnL = UNLIKELY;
init_target = b_residual = NULL;
best_move = -1;
#ifdef DEBUG
if(!list_size)
{
PhyML_Printf("\n\n. List size is 0 !");
PhyML_Printf("\n. Err in file %s at line %d\n\n",__FILE__,__LINE__);
Warn_And_Exit("");
}
#endif
init_lnL = UNLIKELY;
For(i,list_size)
{
st->tree->spr_list[i]->lnL = .0;
For(gt,st->n_part)
{
move_num = Map_Spr_Move(st->tree->spr_list[i]->b_opp_to_link,
st->tree->spr_list[i]->b_target,
st->tree->spr_list[i]->n_link,
st->treelist->tree[gt],st);
if(move_num > -1)
{
move = st->treelist->tree[gt]->spr_list[move_num];
if(move->b_target)
{
init_lnL = st->treelist->tree[gt]->c_lnL;
/* Record t_edge lengths */
Record_Br_Len(st->treelist->tree[gt]);
/* Prune subtree */
Prune_Subtree(move->n_link,
move->n_opp_to_link,
&init_target,
&b_residual,
st->treelist->tree[gt]);
/* Rough optimisation of the branch length */
Fast_Br_Len(init_target,st->treelist->tree[gt],0);
/* Update the change proba matrix at prune position */
Update_PMat_At_Given_Edge(init_target,st->treelist->tree[gt]);
/* Update partial likelihood along the path from the prune to
the regraft position */
Update_P_Lk_Along_A_Path(move->path,move->depth_path,st->treelist->tree[gt]);
/* Regraft subtree */
Graft_Subtree(move->b_target,move->n_link,b_residual,st->treelist->tree[gt]);
/* Estimate the three t_edge lengths at the regraft site */
Triple_Dist(move->n_link,st->treelist->tree[gt],-1);
/* Update the transition proba matrices along edges defining
the regraft site */
For(j,3)
if(move->n_link->v[j] != move->n_opp_to_link)
Update_PMat_At_Given_Edge(move->n_link->b[j],st->treelist->tree[gt]);
/* Compute the likelihood */
Update_P_Lk(st->treelist->tree[gt],
move->b_opp_to_link,
move->n_link);
move->lnL = Lk_At_Given_Edge(move->b_opp_to_link,st->treelist->tree[gt]);
st->tree->spr_list[i]->lnL += move->lnL;
/* Record branch lengths */
dir_v1 = dir_v2 = dir_v0 = -1;
For(j,3)
{
if(move->n_link->v[j] == move->n_opp_to_link) dir_v0 = j;
else if(dir_v1 < 0) dir_v1 = j;
else dir_v2 = j;
}
move->l0 = move->n_link->b[dir_v0]->l;
if(move->n_link->v[dir_v1]->num > move->n_link->v[dir_v2]->num)
{
move->l1 = move->n_link->b[dir_v2]->l;
move->l2 = move->n_link->b[dir_v1]->l;
}
else
{
move->l1 = move->n_link->b[dir_v1]->l;
move->l2 = move->n_link->b[dir_v2]->l;
}
/* Regraft the subtree at its original position */
Prune_Subtree(move->n_link,
move->n_opp_to_link,
&move->b_target,
&b_residual,
st->treelist->tree[gt]);
Graft_Subtree(init_target,
move->n_link,
b_residual,
st->treelist->tree[gt]);
/* Restore branch lengths */
Restore_Br_Len(st->treelist->tree[gt]);
/* Update relevant change proba matrices */
Update_PMat_At_Given_Edge(move->b_target,st->treelist->tree[gt]);
For(j,3) Update_PMat_At_Given_Edge(move->n_link->b[j],st->treelist->tree[gt]);
/* Update relevant partial likelihoods */
For(j,3) Update_P_Lk(st->treelist->tree[gt],move->n_link->b[j],move->n_link);
st->treelist->tree[gt]->c_lnL = init_lnL;
}
}
else
{
st->tree->spr_list[i]->lnL += st->treelist->tree[gt]->c_lnL;
}
}
if(st->tree->spr_list[i]->lnL > best_lnL)
{
best_lnL = st->tree->spr_list[i]->lnL;
best_move = i;
}
}
return best_move;
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
int PART_Try_One_Spr_Move(spr *st_move, supert_tree *st)
{
int j;
spr **gt_move;
t_edge **init_target, **b_residual;
int dir_v0, dir_v1, dir_v2;
int gt;
int gt_move_num;
int n_moves;
init_target = (t_edge **)mCalloc(st->n_part,sizeof(t_edge *));
b_residual = (t_edge **)mCalloc(st->n_part,sizeof(t_edge *));
gt_move = (spr **)mCalloc(st->n_part,sizeof(spr *));
n_moves = 0;
For(gt,st->n_part)
{
gt_move_num = Map_Spr_Move(st_move->b_opp_to_link,
st_move->b_target,
st_move->n_link,
st->treelist->tree[gt],st);
if(gt_move_num > -1)
{
n_moves++;
gt_move[gt] = st->treelist->tree[gt]->spr_list[gt_move_num];
if(gt_move[gt]->b_target)
{
/* Record t_edge lengths */
Record_Br_Len(st->treelist->tree[gt]);
/* Prune subtree */
Prune_Subtree(gt_move[gt]->n_link,
gt_move[gt]->n_opp_to_link,
&(init_target[gt]),
&(b_residual[gt]),
st->treelist->tree[gt]);
/* Rough optimisation of the branch length */
Fast_Br_Len(init_target[gt],st->treelist->tree[gt],0);
/* Update the change proba matrix at prune position */
Update_PMat_At_Given_Edge(init_target[gt],st->treelist->tree[gt]); /* TO DO : NECESSARY ?? */
/* Update partial likelihood along the path from the prune to
the regraft position */
Update_P_Lk_Along_A_Path(gt_move[gt]->path,gt_move[gt]->depth_path,st->treelist->tree[gt]); /* TO DO : NECESSARY ?? */
/* Regraft subtree */
Graft_Subtree(gt_move[gt]->b_target,gt_move[gt]->n_link,b_residual[gt],st->treelist->tree[gt]);
dir_v1 = dir_v2 = dir_v0 = -1;
For(j,3)
{
if(gt_move[gt]->n_link->v[j] == gt_move[gt]->n_opp_to_link) dir_v0 = j;
else if(dir_v1 < 0) dir_v1 = j;
else dir_v2 = j;
}
gt_move[gt]->n_link->b[dir_v0]->l = gt_move[gt]->l0;
if(gt_move[gt]->n_link->v[dir_v1]->num > gt_move[gt]->n_link->v[dir_v2]->num)
{
gt_move[gt]->n_link->b[dir_v2]->l = gt_move[gt]->l1;
gt_move[gt]->n_link->b[dir_v1]->l = gt_move[gt]->l2;
}
else
{
gt_move[gt]->n_link->b[dir_v1]->l = gt_move[gt]->l1;
gt_move[gt]->n_link->b[dir_v2]->l = gt_move[gt]->l2;
}
}
}
}
if(n_moves)
{
if(st_move->lnL > st->tree->best_lnL)
{
t_edge *st_target, *st_residual;
/* Apply the move on the super-tree */
Prune_Subtree(st_move->n_link,
st_move->n_opp_to_link,
&st_target,
&st_residual,
st->tree);
Graft_Subtree(st_move->b_target,
st_move->n_link,
st_residual,
st->tree);
/* Map gt and st nodes and edges */
PART_Do_Mapping(st);
time(&(st->tree->t_current));
st->tree->both_sides = 1;
st->tree->both_sides = 1;
st->tree->c_lnL = PART_Lk(st);
st->tree->c_pars = PART_Pars(st);
if(FABS(st->tree->c_lnL - st_move->lnL) > st->tree->mod->s_opt->min_diff_lk_local)
{
PhyML_Printf("\n. st->tree->c_lnL = %f st_move->lnL = %f\n",
st->tree->c_lnL,st_move->lnL);
For(gt,st->n_part)
{
PhyML_Printf("\n. truth -> %f ; move -> %f",
Lk(st->treelist->tree[gt]),
gt_move[gt] ? gt_move[gt]->lnL : -1.);
}
}
PhyML_Printf("\n. (%5d sec) [+ ] [%10.2f] [%5d] -- ",
(int)(st->tree->t_current - st->tree->t_beg),
st->tree->c_lnL,st->tree->c_pars);
For(gt,st->n_part)
PhyML_Printf("[%10.2f] ",st->treelist->tree[gt]->c_lnL);
st->tree->n_improvements++;
st->tree->best_lnL = st->tree->c_lnL;
For(gt,st->n_part) Record_Br_Len(st->treelist->tree[gt]);
Free(init_target);
Free(b_residual);
Free(gt_move);
return 1;
}
/* else */
/* { */
/* For(gt,st->n_part) */
/* { */
/* if(gt_move[gt]) */
/* { */
/* Lk(st->treelist->tree[gt]); */
/* Fast_Br_Len_Recur(st->treelist->tree[gt]->t_nodes[0], */
/* st->treelist->tree[gt]->t_nodes[0]->v[0], */
/* st->treelist->tree[gt]->t_nodes[0]->b[0], */
/* st->treelist->tree[gt]); */
/* } */
/* } */
/* time(&(st->tree->t_current)); */
/* st->tree->both_sides = 1; */
/* st->tree->c_lnL = PART_Lk(st); */
/* if(st->tree->c_lnL > st->tree->best_lnL) */
/* { */
/* t_edge *st_target, *st_residual; */
/* /\* Apply the move on the super-tree *\/ */
/* Prune_Subtree(st_move->n_link, */
/* st_move->n_opp_to_link, */
/* &st_target, */
/* &st_residual, */
/* st->tree); */
/* Graft_Subtree(st_move->b_target, */
/* st_move->n_link, */
/* st_residual, */
/* st->tree); */
/* /\* Map gt and st nodes and edges *\/ */
/* PART_Do_Mapping(st); */
/* st->tree->c_pars = PART_Pars(st); */
/* PhyML_Printf("\n. (%5d sec) [++] [%10.2f] [%5d] -- ", */
/* (int)(st->tree->t_current-st->tree->t_beg), */
/* st->tree->c_lnL, */
/* st->tree->c_pars); */
/* For(gt,st->n_part) */
/* PhyML_Printf("[%10.2f] ",st->treelist->tree[gt]->c_lnL); */
/* st->tree->n_improvements++; */
/* st->tree->best_lnL = st->tree->c_lnL; */
/* For(gt,st->n_part) Record_Br_Len(st->treelist->tree[gt]); */
/* Free(init_target); */
/* Free(b_residual); */
/* Free(gt_move); */
/* return 1; */
/* } */
/* } */
}
For(gt,st->n_part)
{
if(gt_move[gt])
{
/* Regraft the subtree at its original position */
Prune_Subtree(gt_move[gt]->n_link,
gt_move[gt]->n_opp_to_link,
&(gt_move[gt]->b_target),
&(b_residual[gt]),
st->treelist->tree[gt]);
Graft_Subtree(init_target[gt],
gt_move[gt]->n_link,
b_residual[gt],
st->treelist->tree[gt]);
/* Restore branch lengths */
Restore_Br_Len(st->treelist->tree[gt]);
}
}
st->tree->both_sides = 1;
st->tree->c_lnL = PART_Lk(st);
st->tree->c_pars = PART_Pars(st);
time(&(st->tree->t_current));
PhyML_Printf("\n. (%5d sec) [--] [%10.2f] [%5d] -- ",
(int)(st->tree->t_current - st->tree->t_beg),
st->tree->c_lnL,st->tree->c_pars);
For(gt,st->n_part) PhyML_Printf("[%10.2f] ",st->treelist->tree[gt]->c_lnL);
Free(init_target);
Free(b_residual);
Free(gt_move);
return 0;
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void PART_NNI(t_edge *st_b, supert_tree *st)
{
t_node *v1, *v2, *v3, *v4;
phydbl lk_init;
phydbl lk0_init, lk1_init, lk2_init;
phydbl lk0_opt, lk1_opt, lk2_opt;
int i,j;
phydbl *init_bl;
t_edge **map_edge_bef_swap, **map_edge_aft_swap;
init_bl = (phydbl *)mCalloc(st->n_bl_part,sizeof(phydbl));
map_edge_bef_swap = (t_edge **)mCalloc(st->n_part,sizeof(t_edge *));
map_edge_aft_swap = (t_edge **)mCalloc(st->n_part,sizeof(t_edge *));
v1 = st_b->left->v[st_b->l_v1];
v2 = st_b->left->v[st_b->l_v2];
v3 = st_b->rght->v[st_b->r_v1];
v4 = st_b->rght->v[st_b->r_v2];
lk0_init = lk1_init = lk2_init = UNLIKELY;
lk0_opt = lk1_opt = lk2_opt = UNLIKELY;
if(v1->num < v2->num)
{
Check_Dirs(st->tree);
PhyML_Printf("\n. Err in file %s at line %d\n\n",__FILE__,__LINE__);
Warn_And_Exit("");
}
if(v3->num < v4->num)
{
Check_Dirs(st->tree);
PhyML_Printf("\n. Err in file %s at line %d\n\n",__FILE__,__LINE__);
Warn_And_Exit("");
}
lk_init = st->tree->c_lnL;
/* PhyML_Printf("oooooooo\n"); */
/* Print_Node(st->tree->t_nodes[0], */
/* st->tree->t_nodes[0]->v[0], */
/* st->tree); */
/* PhyML_Printf(">>>>>>>\n"); */
/* For(i,st->n_part) */
/* { */
/* Print_Node(st->treelist->tree[i]->t_nodes[0], */
/* st->treelist->tree[i]->t_nodes[0]->v[0], */
/* st->treelist->tree[i]); */
/* PhyML_Printf("<<<<<<<\n"); */
/* } */
PART_Record_Br_Len(st);
For(i,st->n_part) map_edge_bef_swap[i] = NULL;
For(i,st->n_part) if(st->map_st_edge_in_gt[i][st_b->num]) map_edge_bef_swap[i] = st->map_st_edge_in_gt[i][st_b->num];
/* First alternative topological configuration */
/* Swap */
PART_Swap(v2,st_b->left,st_b->rght,v3,st);
Swap(v2,st_b->left,st_b->rght,v3,st->tree);
PART_Do_Mapping(st);
PART_Set_Bl(st->bl,st);
For(i,st->n_part) map_edge_aft_swap[i] = NULL;
For(i,st->n_part) if(st->map_st_edge_in_gt[i][st_b->num]) map_edge_aft_swap[i] = st->map_st_edge_in_gt[i][st_b->num];
For(i,st->n_part) if(map_edge_bef_swap[i]) Update_PMat_At_Given_Edge(map_edge_bef_swap[i],st->treelist->tree[i]);
For(i,st->n_part) if(map_edge_aft_swap[i]) Update_PMat_At_Given_Edge(map_edge_aft_swap[i],st->treelist->tree[i]);
For(i,st->n_part) if(map_edge_bef_swap[i] && map_edge_aft_swap[i])
{
For(j,3) if((map_edge_aft_swap[i]->left->v[j]) &&
(map_edge_aft_swap[i]->left->b[j] == map_edge_bef_swap[i]) &&
(map_edge_aft_swap[i] != map_edge_bef_swap[i]))
Update_P_Lk(st->treelist->tree[i],
map_edge_aft_swap[i],
map_edge_aft_swap[i]->left);
For(j,3) if((map_edge_aft_swap[i]->rght->v[j]) &&
(map_edge_aft_swap[i]->rght->b[j] == map_edge_bef_swap[i]) &&
(map_edge_aft_swap[i] != map_edge_bef_swap[i]))
Update_P_Lk(st->treelist->tree[i],
map_edge_aft_swap[i],
map_edge_aft_swap[i]->rght);
}
lk1_init = PART_Update_Lk_At_Given_Edge(st_b,st);
lk1_opt = PART_Br_Len_Brent(st_b,0,st);
For(i,st->n_part) st->bl1[st->bl_partition[i]][st_b->num] = st->bl[st->bl_partition[i]][st_b->num];
/* Unswap */
PART_Swap(v3,st_b->left,st_b->rght,v2,st);
Swap(v3,st_b->left,st_b->rght,v2,st->tree);
PART_Do_Mapping(st);
PART_Restore_Br_Len(st);
PART_Set_Bl(st->bl,st);
For(i,st->n_part) if(map_edge_bef_swap[i]) Update_PMat_At_Given_Edge(map_edge_bef_swap[i],st->treelist->tree[i]);
For(i,st->n_part) if(map_edge_aft_swap[i]) Update_PMat_At_Given_Edge(map_edge_aft_swap[i],st->treelist->tree[i]);
For(i,st->n_part) if(map_edge_bef_swap[i] && map_edge_aft_swap[i])
{
For(j,3) if((map_edge_aft_swap[i]->left->v[j]) &&
(map_edge_aft_swap[i]->left->b[j] == map_edge_bef_swap[i]) &&
(map_edge_aft_swap[i] != map_edge_bef_swap[i]))
Update_P_Lk(st->treelist->tree[i],
map_edge_aft_swap[i],
map_edge_aft_swap[i]->left);
For(j,3) if((map_edge_aft_swap[i]->rght->v[j]) &&
(map_edge_aft_swap[i]->rght->b[j] == map_edge_bef_swap[i]) &&
(map_edge_aft_swap[i] != map_edge_bef_swap[i]))
Update_P_Lk(st->treelist->tree[i],
map_edge_aft_swap[i],
map_edge_aft_swap[i]->rght);
}
/* Second alternative topological configuration */
/* Swap */
PART_Swap(v2,st_b->left,st_b->rght,v4,st);
Swap(v2,st_b->left,st_b->rght,v4,st->tree);
PART_Do_Mapping(st);
PART_Set_Bl(st->bl,st);
For(i,st->n_part) map_edge_aft_swap[i] = NULL;
For(i,st->n_part) if(st->map_st_edge_in_gt[i][st_b->num]) map_edge_aft_swap[i] = st->map_st_edge_in_gt[i][st_b->num];
For(i,st->n_part) if(map_edge_bef_swap[i]) Update_PMat_At_Given_Edge(map_edge_bef_swap[i],st->treelist->tree[i]);
For(i,st->n_part) if(map_edge_aft_swap[i]) Update_PMat_At_Given_Edge(map_edge_aft_swap[i],st->treelist->tree[i]);
For(i,st->n_part) if(map_edge_bef_swap[i] && map_edge_aft_swap[i])
{
For(j,3) if((map_edge_aft_swap[i]->left->v[j]) &&
(map_edge_aft_swap[i]->left->b[j] == map_edge_bef_swap[i]) &&
(map_edge_aft_swap[i] != map_edge_bef_swap[i]))
Update_P_Lk(st->treelist->tree[i],
map_edge_aft_swap[i],
map_edge_aft_swap[i]->left);
For(j,3) if((map_edge_aft_swap[i]->rght->v[j]) &&
(map_edge_aft_swap[i]->rght->b[j] == map_edge_bef_swap[i]) &&
(map_edge_aft_swap[i] != map_edge_bef_swap[i]))
Update_P_Lk(st->treelist->tree[i],
map_edge_aft_swap[i],
map_edge_aft_swap[i]->rght);
}
lk2_init = PART_Update_Lk_At_Given_Edge(st_b,st);
lk2_opt = PART_Br_Len_Brent(st_b,0,st);
For(i,st->n_part) st->bl2[st->bl_partition[i]][st_b->num] = st->bl[st->bl_partition[i]][st_b->num];
/* PhyML_Printf("\n. lk2_init = %f lk2_opt = %f",lk2_init,lk2_opt); */
/* Unswap */
PART_Swap(v4,st_b->left,st_b->rght,v2,st);
Swap(v4,st_b->left,st_b->rght,v2,st->tree);
PART_Do_Mapping(st);
PART_Restore_Br_Len(st);
PART_Set_Bl(st->bl,st);
For(i,st->n_part) if(map_edge_bef_swap[i]) Update_PMat_At_Given_Edge(map_edge_bef_swap[i],st->treelist->tree[i]);
For(i,st->n_part) if(map_edge_aft_swap[i]) Update_PMat_At_Given_Edge(map_edge_aft_swap[i],st->treelist->tree[i]);
For(i,st->n_part) if(map_edge_bef_swap[i] && map_edge_aft_swap[i])
{
For(j,3) if((map_edge_aft_swap[i]->left->v[j]) &&
(map_edge_aft_swap[i]->left->b[j] == map_edge_bef_swap[i]) &&
(map_edge_aft_swap[i] != map_edge_bef_swap[i]))
Update_P_Lk(st->treelist->tree[i],
map_edge_aft_swap[i],
map_edge_aft_swap[i]->left);
For(j,3) if((map_edge_aft_swap[i]->rght->v[j]) &&
(map_edge_aft_swap[i]->rght->b[j] == map_edge_bef_swap[i]) &&
(map_edge_aft_swap[i] != map_edge_bef_swap[i]))
Update_P_Lk(st->treelist->tree[i],
map_edge_aft_swap[i],
map_edge_aft_swap[i]->rght);
}
/* Back to the initial topological configuration
* and branch lengths.
*/
PART_Do_Mapping(st);
PART_Set_Bl(st->bl,st);
PART_Restore_Br_Len(st);
For(i,st->n_part) map_edge_aft_swap[i] = NULL;
For(i,st->n_part) if(st->map_st_edge_in_gt[i][st_b->num]) map_edge_aft_swap[i] = st->map_st_edge_in_gt[i][st_b->num];
For(i,st->n_part) if(map_edge_bef_swap[i]) Update_PMat_At_Given_Edge(map_edge_bef_swap[i],st->treelist->tree[i]);
For(i,st->n_part) if(map_edge_aft_swap[i]) Update_PMat_At_Given_Edge(map_edge_aft_swap[i],st->treelist->tree[i]);
lk0_init = PART_Update_Lk_At_Given_Edge(st_b,st);
lk0_opt = PART_Br_Len_Brent(st_b,0,st);
For(i,st->n_part) st->bl0[st->bl_partition[i]][st_b->num] = st->bl[st->bl_partition[i]][st_b->num];
PART_Restore_Br_Len(st);
PART_Set_Bl(st->bl,st);
For(i,st->n_part) if(map_edge_bef_swap[i]) Update_PMat_At_Given_Edge(map_edge_bef_swap[i],st->treelist->tree[i]);
For(i,st->n_part) if(map_edge_aft_swap[i]) Update_PMat_At_Given_Edge(map_edge_aft_swap[i],st->treelist->tree[i]);
PART_Update_Lk_At_Given_Edge(st_b,st);
/* For(i,2*st->tree->n_otu-3) */
/* PhyML_Printf("\n. 3 Edge %3d --> lnL=%f",i,PART_Lk_At_Given_Edge(st->tree->t_edges[i],st)); */
st_b->nni->lk0 = lk0_opt;
st_b->nni->lk1 = lk1_opt;
st_b->nni->lk2 = lk2_opt;
st_b->nni->score = lk0_opt - MAX(lk1_opt,lk2_opt);
if((st_b->nni->score < st->tree->mod->s_opt->min_diff_lk_local) &&
(st_b->nni->score > -st->tree->mod->s_opt->min_diff_lk_local))
{
st_b->nni->score = .0;
st_b->nni->lk1 = st_b->nni->lk0;
st_b->nni->lk2 = st_b->nni->lk0;
}
PART_Restore_Br_Len(st);
PART_Update_Lk_At_Given_Edge(st_b,st); /* to replace by PART_Update_PMat_At_Given_Edge(st_b,st); */
/* PhyML_Printf("\n. lk_end = %f",st->tree->c_lnL); */
/* For(i,2*st->tree->n_otu-3) PhyML_Printf("\n. %f",PART_Lk_At_Given_Edge(st->tree->t_edges[i],st)); */
/* PhyML_Printf("\n. lk_end = %f",PART_Lk(st)); */
/* PhyML_Printf("\n"); */
/* PhyML_Printf("\n. Edge %3d, score = %20f",st_b->num,st_b->nni->score); */
if(st_b->num == 90)
PhyML_Printf("\n. v1=%d v2=%d v3=%d v4=%d left-%d right-%d",
v1->num,
v2->num,
v3->num,
v4->num,
st_b->left->num,
st_b->rght->num);
if(lk0_opt > MAX(lk1_opt,lk2_opt))
{
st_b->nni->best_conf = 0;
st_b->nni->swap_node_v1 = NULL;
st_b->nni->swap_node_v2 = NULL;
st_b->nni->swap_node_v3 = NULL;
st_b->nni->swap_node_v4 = NULL;
}
else if(lk1_opt > MAX(lk0_opt,lk2_opt))
{
st_b->nni->best_conf = 1;
st_b->nni->swap_node_v1 = v2;
st_b->nni->swap_node_v2 = st_b->left;
st_b->nni->swap_node_v3 = st_b->rght;
st_b->nni->swap_node_v4 = v3;
}
else if(lk2_opt > MAX(lk0_opt,lk1_opt))
{
st_b->nni->best_conf = 2;
st_b->nni->swap_node_v1 = v2;
st_b->nni->swap_node_v2 = st_b->left;
st_b->nni->swap_node_v3 = st_b->rght;
st_b->nni->swap_node_v4 = v4;
}
else
{
st_b->nni->score = +1.0;
st_b->nni->best_conf = 0;
st_b->nni->swap_node_v1 = NULL;
st_b->nni->swap_node_v2 = NULL;
st_b->nni->swap_node_v3 = NULL;
st_b->nni->swap_node_v4 = NULL;
}
Free(init_bl);
Free(map_edge_aft_swap);
Free(map_edge_bef_swap);
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void PART_Swap(t_node *st_a, t_node *st_b, t_node *st_c, t_node *st_d, supert_tree *st)
{
int i,j;
t_node *gt_a, *gt_b, *gt_c, *gt_d;
int ab, ba, cd, dc, bc;
ab = ba = cd = dc = bc = -1;
For(i,3) if(st_a->v[i] == st_b) { ab = i; break; }
For(i,3) if(st_b->v[i] == st_a) { ba = i; break; }
For(i,3) if(st_c->v[i] == st_d) { cd = i; break; }
For(i,3) if(st_d->v[i] == st_c) { dc = i; break; }
For(i,3) if(st_b->v[i] == st_c) { bc = i; break; }
if(ab < 0 || ba < 0 || cd < 0 || dc < 0)
{
PhyML_Printf("\n. Nodes %d %d %d %d\n",st_a->num,st_b->num,st_c->num,st_d->num);
PhyML_Printf("\n. Err in file %s at line %d\n\n",__FILE__,__LINE__);
Warn_And_Exit("");
}
gt_a = gt_b = gt_c = gt_d = NULL;
For(i,st->n_part)
{
gt_b = st->match_st_node_in_gt[i][st_b->num];
gt_c = st->match_st_node_in_gt[i][st_c->num];
if(gt_b && gt_c) /* The st t_edge with st_b and st_c at its extremities
* matches an t_edge in gt
*/
{
#ifdef DEBUG
For(j,3) if((gt_b->v[j]) && (gt_b->v[j] == gt_c)) break;
if(j == 3)
{
PhyML_Printf("\n. Err in file %s at line %d\n\n",__FILE__,__LINE__);
Warn_And_Exit("");
}
#endif
gt_a = st->map_st_node_in_gt[i][st_a->num][ab][0];
gt_d = st->map_st_node_in_gt[i][st_d->num][dc][0];
Swap(gt_a,gt_b,gt_c,gt_d,st->treelist->tree[i]);
}
}
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void PART_Set_Bl(phydbl **bl, supert_tree *st)
{
int i,j;
t_edge *gt_b;
gt_b = NULL;
/* Set all the actual branch lengths to 0.0
*/
For(i,st->n_part)
{
For(j,2*st->treelist->tree[i]->n_otu-3)
{
gt_b = st->treelist->tree[i]->t_edges[j];
gt_b->l = .0;
}
}
/* Update every branch length
*/
For(i,2*st->tree->n_otu-3)
{
For(j,st->n_part)
{
gt_b = st->map_st_edge_in_gt[j][i];
/* Need to make sure that st->tree->t_edges[i] is on an existing path in gt */
if((st->map_st_node_in_gt[j][st->tree->t_edges[i]->left->num][st->tree->t_edges[i]->l_r][0]) &&
(st->map_st_node_in_gt[j][st->tree->t_edges[i]->rght->num][st->tree->t_edges[i]->r_l][0]))
{
gt_b->l += bl[st->bl_partition[j]][i];
}
}
}
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void PART_Record_Br_Len(supert_tree *st)
{
int i,j;
For(i,st->n_part) For(j,2*st->tree->n_otu-3) st->bl_cpy[i][j] = st->bl[i][j];
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void PART_Restore_Br_Len(supert_tree *st)
{
int i,j;
For(i,st->n_part) For(j,2*st->tree->n_otu-3) st->bl[i][j] = st->bl_cpy[i][j];
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
phydbl PART_Lk(supert_tree *st)
{
int i;
PART_Do_Mapping(st);
PART_Set_Bl(st->bl,st);
st->tree->c_lnL = .0;
For(i,st->n_part)
{
st->treelist->tree[i]->both_sides = 1;
Lk(st->treelist->tree[i]);
/* PhyML_Printf("\n. Tree %3d lnL = %f",i+1,st->treelist->tree[i]->c_lnL); */
st->tree->c_lnL += st->treelist->tree[i]->c_lnL;
}
return st->tree->c_lnL;
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
phydbl PART_Lk_At_Given_Edge(t_edge *st_b, supert_tree *st)
{
int i;
t_edge *gt_b;
phydbl lnL;
PART_Set_Bl(st->bl,st);
gt_b = NULL;
st->tree->c_lnL = .0;
lnL = .0;
For(i,st->n_part)
{
gt_b = st->map_st_edge_in_gt[i][st_b->num];
lnL = Lk_At_Given_Edge(gt_b,st->treelist->tree[i]);
st->tree->c_lnL += lnL;
/* PhyML_Printf("\n. gt %d st t_edge %d gt t_edge %d lnL=%f l=%f ",i,st_b->num,gt_b->num,lnL,gt_b->l); */
}
return st->tree->c_lnL;
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
phydbl PART_Update_Lk_At_Given_Edge(t_edge *st_b, supert_tree *st)
{
int i;
t_edge *gt_b;
PART_Set_Bl(st->bl,st);
gt_b = NULL;
st->tree->c_lnL = .0;
For(i,st->n_part)
{
gt_b = st->map_st_edge_in_gt[i][st_b->num];
if(gt_b) st->tree->c_lnL += Update_Lk_At_Given_Edge(gt_b,st->treelist->tree[i]);
else st->tree->c_lnL += st->treelist->tree[i]->c_lnL;
}
return st->tree->c_lnL;
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void PART_Fill_Model_Partitions_Table(supert_tree *st)
{
int i,j;
char *c;
char *abc;
int lig, col;
int n_groups;
int *encountered_vals;
c = (char *)mCalloc(10,sizeof(char));
abc = (char *)mCalloc(20,sizeof(char));
encountered_vals = (int *)mCalloc(st->n_part,sizeof(int));
strcpy(abc,"ABCDEFGHIJKLMNOP\0");
PhyML_Printf("\n\n\n");
lig = col = 0;
while(1)
{
PhyML_Printf("\n\n");
For(i,st->n_part)
PhyML_Printf(". Data set %3d : %s\n",i+1,st->optionlist[i]->in_align_file);
PhyML_Printf("\n. Data set ");
For(i,st->n_part) PhyML_Printf("%3d ",i+1);
PhyML_Printf("\n. -A- t_edge lengths ");
For(i,st->n_part) PhyML_Printf("%3d ",st->bl_partition[i]);
if(lig == 1) break;
PhyML_Printf("\n. (%c-%2d)> ",abc[lig],col+1);
Getstring_Stdin(c);
switch(lig)
{
case 0 :
{
st->bl_partition[col] = atoi(c);
break;
}
default :
{
break;
}
}
col++;
if(col == st->n_part)
{
col = 0;
lig++;
}
}
n_groups = 0;
For(i,st->n_part)
{
For(j,n_groups)
if(encountered_vals[j] == st->bl_partition[i])
break;
if(j == n_groups)
{
encountered_vals[n_groups] = st->bl_partition[i];
n_groups++;
}
st->bl_partition[i] = j;
}
st->n_bl_part = n_groups;
Free(encountered_vals);
Free(c);
Free(abc);
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
phydbl PART_Br_Len_Brent(t_edge *st_b, int quickdirty, supert_tree *st)
{
phydbl ax, bx, cx;
int part;
phydbl cur_l;
For(part,st->n_bl_part)
{
cur_l = st->bl[part][st_b->num];
ax = 10.*cur_l;
bx = cur_l;
cx = st->tree->mod->l_min;
Generic_Brent_Lk(&(st->bl[part][st_b->num]),
ax,cx,
st->tree->mod->s_opt->min_diff_lk_local,
st->tree->mod->s_opt->brent_it_max,
st->tree->mod->s_opt->quickdirty,
Wrap_Part_Lk_At_Given_Edge,st_b,NULL,st);
}
return st->tree->c_lnL;
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void PART_Initialise_Bl_Partition(supert_tree *st)
{
int i,j;
For(i,st->n_bl_part)
{
For(j,2*st->tree->n_otu-3)
{
st->bl[i][j] = .1;
}
}
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void PART_Optimize_Br_Len_Serie(t_node *st_a, t_node *st_d, t_edge *st_b, supert_tree *st)
{
phydbl lk_init;
int i;
lk_init = st->tree->c_lnL;
PART_Br_Len_Brent(st_b,0,st);
if(st->tree->c_lnL < lk_init - st->tree->mod->s_opt->min_diff_lk_local)
{
PhyML_Printf("\n. %f -- %f",lk_init,st->tree->c_lnL);
PhyML_Printf("\n. Err in file %s at line %d\n\n",__FILE__,__LINE__);
Warn_And_Exit("");
}
if(st_d->tax) return;
else For(i,3) if(st_d->v[i] != st_a)
{
PART_Update_P_Lk(st_d->b[i],st_d,st);
PART_Optimize_Br_Len_Serie(st_d,st_d->v[i],st_d->b[i],st);
}
For(i,3) if((st_d->v[i] == st_a) && (!st_d->v[i]->tax)) PART_Update_P_Lk(st_d->b[i],st_d,st);
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void PART_Update_P_Lk(t_edge *st_b, t_node *st_n, supert_tree *st)
{
int i,dir;
dir = -1;
For(i,3) if((st_n->b[i]) && (st_n->b[i] == st_b)) {dir = i; break;}
if(dir < 0)
{
PhyML_Printf("\n. Err in file %s at line %d\n\n",__FILE__,__LINE__);
Warn_And_Exit("");
}
For(i,st->n_part)
{
if((st->map_st_node_in_gt[i][st_n->num][dir][0]) && (!st->map_st_node_in_gt[i][st_n->num][dir][0]->tax))
{
Update_P_Lk(st->treelist->tree[i],
st->map_st_edge_in_gt[i][st_b->num],
st->map_st_node_in_gt[i][st_n->num][dir][0]);
}
}
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void PART_Make_N_Swap(t_edge **st_b, int beg, int end, supert_tree *st)
{
int i;
int dim;
dim = 2*st->tree->n_otu-2;
st->tree->n_swap = 0;
for(i=beg;ileft->tax || st_b[i]->rght->tax)
{
PhyML_Printf("\n. Edge %d is external.",st_b[i]->num);
PhyML_Printf("\n. Err in file %s at line %d\n\n.",__FILE__,__LINE__);
Warn_And_Exit("");
}
PART_Swap(st_b[i]->nni->swap_node_v2->v[st->tree->t_dir[st_b[i]->nni->swap_node_v2->num*dim+st_b[i]->nni->swap_node_v1->num]],
st_b[i]->nni->swap_node_v2,
st_b[i]->nni->swap_node_v3,
st_b[i]->nni->swap_node_v3->v[st->tree->t_dir[st_b[i]->nni->swap_node_v3->num*dim+st_b[i]->nni->swap_node_v4->num]],
st);
Swap(st_b[i]->nni->swap_node_v2->v[st->tree->t_dir[st_b[i]->nni->swap_node_v2->num*dim+st_b[i]->nni->swap_node_v1->num]],
st_b[i]->nni->swap_node_v2,
st_b[i]->nni->swap_node_v3,
st_b[i]->nni->swap_node_v3->v[st->tree->t_dir[st_b[i]->nni->swap_node_v3->num*dim+st_b[i]->nni->swap_node_v4->num]],
st->tree);
PART_Do_Mapping(st);
st->tree->n_swap++;
}
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void PART_Update_Bl(phydbl fact, supert_tree *st)
{
int i,j;
For(i,2*st->tree->n_otu-3)
{
For(j,st->n_part)
st->bl[st->bl_partition[j]][i] =
st->bl_cpy[st->bl_partition[j]][i] +
(st->bl0[st->bl_partition[j]][i] - st->bl_cpy[st->bl_partition[j]][i]) * fact;
}
PART_Set_Bl(st->bl,st);
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void PART_Update_Bl_Swaped(t_edge **st_b, int n, supert_tree *st)
{
int i,j;
For(i,n)
{
For(j,st->n_part)
{
st->bl[st->bl_partition[j]][st_b[i]->num] =
(st_b[i]->nni->best_conf == 1)?
(st->bl1[st->bl_partition[j]][st_b[i]->num]):
(st->bl2[st->bl_partition[j]][st_b[i]->num]);
}
}
PART_Set_Bl(st->bl,st);
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void PART_Do_Mapping(supert_tree *st)
{
int k;
Fill_Dir_Table(st->tree);
For(k,st->n_part)
{
Fill_Dir_Table(st->treelist->tree[k]);
PART_Match_St_Nodes_In_Gt(st->treelist->tree[k],st);
PART_Match_St_Edges_In_Gt(st->treelist->tree[k],st);
PART_Map_St_Nodes_In_Gt(st->treelist->tree[k],st);
PART_Map_St_Edges_In_Gt(st->treelist->tree[k],st);
PART_Map_Gt_Edges_In_St(st->treelist->tree[k],st);
}
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void PART_Print_Bl(supert_tree *st)
{
int i,j;
For(j,2*st->tree->n_otu-3)
{
PhyML_Printf("\n. t_edge %4d ",j);
For(i,st->n_bl_part)
{
PhyML_Printf("%f ",st->bl[i][j]);
}
}
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
phyml-20120412/src/xml.c 0000644 0001750 0001750 00000023446 11741250001 011554 0000000 0000000 #include "xml.h"
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void XML_Load_File(FILE *fp, xml_node *top)
{
int c;
char *buffer,*bufptr;
int bufsize;
xml_node *parent;
xml_node *node;
buffer = (char *)mCalloc(T_MAX_XML_TAG,sizeof(char));
bufsize = T_MAX_XML_TAG;
bufptr = buffer;
parent = top;
node = NULL;
while((c = fgetc(fp)) != EOF)
{
if(c == '<' && bufptr > buffer)
{
*bufptr = '\0';
PhyML_Printf("\n. Read value '%s' for node '%s'",buffer,node->name);
fflush(NULL);
XML_Set_Node_Value(node,buffer);
bufptr = buffer;
}
if(c == '<')
{
bufptr = buffer;
while((c = fgetc(fp)) != EOF)
{
if(isspace(c) != NO || c == '>' || (c == '/' && bufptr > buffer)) break; // End of open or close tag
else if(c == '<')
{
Exit("\n. Bare < in element!");
}
else if(XML_Add_Character(c,&bufptr,&buffer,&bufsize))
{
PhyML_Printf("\n. Err in file %s at line %d\n",__FILE__,__LINE__);
Exit("\n");
}
}
*bufptr = '\0';
if(!strcmp(buffer,"!--")) // Get the rest of the comment
{
while((c = fgetc(fp)) != EOF)
{
if(c == '>' && bufptr > (buffer + 4) && bufptr[-3] != '-' &&
bufptr[-2] == '-' && bufptr[-1] == '-') break;
else if(XML_Add_Character(c,&bufptr,&buffer,&bufsize))
{
PhyML_Printf("\n. Err in file %s at line %d\n",__FILE__,__LINE__);
Exit("\n");
}
}
*bufptr = '\0';
if(c != '>')
{
PhyML_Printf("\n. Early EOF in comment node.");
Exit("\n");
}
}
else if(buffer[0] == '/') // Close tag
{
if(strcmp(buffer+1,parent->name))
{
PhyML_Printf("\n. Opened tag with name '%s' and closed it with '%s'...",node->name,buffer+1);
PhyML_Printf("\n. Err in file %s at line %d\n",__FILE__,__LINE__);
Exit("\n");
}
printf("\n. Closing node with name '%s'",node->name);
parent = parent->parent;
node = parent;
}
else if(buffer[0] == '?')
{
while((c = fgetc(fp)) != EOF)
{
if (c == '>' && bufptr > buffer && bufptr[-1] == '?')
break;
else if (XML_Add_Character(c, &bufptr, &buffer, &bufsize))
{
PhyML_Printf("\n. Err in file %s at line %d\n",__FILE__,__LINE__);
Exit("\n");
}
}
if(c != '>')
{
PhyML_Printf("\n. An error occurred when reading the processing instruction.");
PhyML_Printf("\n. Err in file %s at line %d\n",__FILE__,__LINE__);
Exit("\n");
}
*bufptr = '\0';
}
else // Open tag
{
printf("\n. Create node with name '%s'",buffer);
node = XML_New_Node(parent,buffer);
if(isspace(c) != NO) c=XML_Parse_Element(fp,node);
else if(c == '/')
{
if((c=fgetc(fp)) != '>')
{
PhyML_Printf("\n. Expected '>' but read '%c' instead",c);
Exit("\n");
}
c = '/';
}
if(c != '/') parent = node;
buffer[0] = '\0';
}
bufptr = buffer;
}
else if(isspace(c) == NO)
{
if(XML_Add_Character(c,&bufptr,&buffer,&bufsize))
{
PhyML_Printf("\n. Err in file %s at line %d\n",__FILE__,__LINE__);
Exit("\n");
}
}
}
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
int XML_Add_Character(int c, char **bufptr, char **buffer, int *bufsize)
{
char *newbuffer;
if(*bufptr >= (*buffer + *bufsize - 4))
{
// Increase the size of the buffer...
if (*bufsize < 1024)
(*bufsize) *= 2;
else
(*bufsize) += 1024;
if ((newbuffer = realloc(*buffer, *bufsize)) == NULL)
{
Free(*buffer);
PhyML_Printf("Unable to expand string buffer to %d bytes!", *bufsize);
Exit("\n");
}
*bufptr = newbuffer + (*bufptr - *buffer);
*buffer = newbuffer;
}
*(*bufptr)++ = c;
return 0;
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
int XML_Parse_Element(FILE *fp, xml_node *n)
{
int c;
int quote;
char *name, *value, *ptr;
int namesize, valsize;
name = (char *)mCalloc(64,sizeof(char));
value = (char *)mCalloc(64,sizeof(char));
namesize = 64;
valsize = 64;
while((c = fgetc(fp)) != EOF)
{
if(isspace(c) != NO) continue;
if(c == '/') // End of tag
{
printf("\n. Closing node '%s'.",n->name);
quote = fgetc(fp);
if(quote != '>')
{
PhyML_Printf("\n. Expected '>' after '%c' but read '%c' instead",c,quote);
Exit("\n");
}
break;
}
else if(c == '<')
{
Exit("\n. Bare < in element!");
}
else if(c == '>') // End of tag
{
break;
}
name[0] = c;
ptr = name + 1;
if(c == '\"' || c == '\'') // Name is in quotes
{
quote = c;
while((c = fgetc(fp)) != EOF)
{
if(XML_Add_Character(c,&ptr,&name,&namesize))
{
PhyML_Printf("\n. Err in file %s at line %d\n",__FILE__,__LINE__);
Exit("\n");
}
if(c == quote) break;
}
}
else // Name not in quotes
{
while((c = fgetc(fp)) != EOF)
{
if(isspace(c) != NO || c == '=' || c == '/' || c == '>' || c == '?')
break;
else
{
if(XML_Add_Character(c,&ptr,&name,&namesize))
{
PhyML_Printf("\n. Err in file %s at line %d\n",__FILE__,__LINE__);
Exit("\n");
}
}
}
}
*ptr = '\0';
while(c != EOF && isspace(c) != NO) c = fgetc(fp);
if(c == '=') // Read the attribute value
{
while((c = fgetc(fp)) != EOF && isspace(c) != NO);
if(c == EOF)
{
PhyML_Printf("\n. Missing value in attribute.");
PhyML_Printf("\n. Err in file %s at line %d\n",__FILE__,__LINE__);
Exit("\n");
}
if(c == '\'' || c == '\"')
{
quote = c;
ptr = value;
while((c = fgetc(fp)) != EOF)
{
if(c == quote) break;
else
{
if(XML_Add_Character(c,&ptr,&value,&valsize))
{
PhyML_Printf("\n. Err in file %s at line %d\n",__FILE__,__LINE__);
Exit("\n");
}
}
}
*ptr = '\0';
}
else
{
value[0] = c;
ptr = value + 1;
while((c = fgetc(fp)) != EOF)
{
if(isspace(c) != NO || c == '=' || c == '/' || c == '>')
break;
else
{
if(XML_Add_Character(c,&ptr,&value,&valsize))
{
PhyML_Printf("\n. Err in file %s at line %d\n",__FILE__,__LINE__);
Exit("\n");
}
}
}
}
}
printf("\n. Setting attribute '%s=%s' to node '%s'",name,value,n->name);
XML_Set_Attribute(n,name,value);
if(c == '>') break;
}
Free(name);
Free(value);
printf("\n. Return '%c'\n",c);
return(c);
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
xml_node *XML_New_Node(xml_node *parent, char *name)
{
xml_node *new_node;
new_node = (xml_node *)mCalloc(1,sizeof(xml_node));
if(name)
{
new_node->name = (char *)mCalloc(strlen(name)+1,sizeof(char));
strcpy(new_node->name,name);
}
new_node->parent = parent ? parent : NULL;
new_node->next = NULL;
new_node->prev = NULL;
new_node->child = NULL;
if(parent)
{
xml_node *prev;
prev = NULL;
while(parent->child)
{
prev = parent->child;
parent->child = parent->child->next;
}
parent->child = new_node;
new_node->prev = prev;
if(prev) new_node->prev->next = new_node;
}
new_node->attr = NULL;
return new_node;
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
int XML_Set_Attribute(xml_node *n, char *attr_name, char *attr_value)
{
xml_attr *prev;
char *s;
prev = NULL;
while(n->attr != NULL)
{
n->attr = n->attr->next;
prev = n->attr;
}
n->attr = XML_Make_Attribute(prev,attr_name,attr_value);
n->n_attr++;
while(n->attr->prev != NULL)
{
n->attr = n->attr->prev;
}
s = To_Lower_String(attr_name);
if(!strcmp(s,"id"))
{
XML_Set_Node_Id(n,attr_value);
printf("\n. Node '%s' id is '%s'",n->name,n->id);
}
Free(s);
return(0);
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
xml_attr *XML_Make_Attribute(xml_attr *prev, char *attr_name, char *attr_value)
{
xml_attr *new_attr;
new_attr = (xml_attr *)mCalloc(1,sizeof(xml_attr));
new_attr->prev = prev;
new_attr->next = NULL;
if(prev != NULL) prev->next = new_attr;
new_attr->name = (char *)mCalloc(strlen(attr_name)+1,sizeof(char));
strcpy(new_attr->name,attr_name);
new_attr->value = (char *)mCalloc(strlen(attr_value)+1,sizeof(char));
strcpy(new_attr->value,attr_value);
return new_attr;
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
int XML_Set_Node_Id(xml_node *n, char *id)
{
XML_Make_Node_Id(n,id);
strcpy(n->id,id);
return(0);
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void XML_Make_Node_Id(xml_node *n, char *id)
{
n->id = (char *)mCalloc(strlen(id)+1,sizeof(char));
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
int XML_Set_Node_Value(xml_node *n, char *val)
{
XML_Make_Node_Value(n,val);
strcpy(n->value,val);
return(0);
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void XML_Make_Node_Value(xml_node *n, char *val)
{
n->value = (char *)mCalloc(strlen(val)+1,sizeof(char));
}
phyml-20120412/src/free.h 0000644 0001750 0001750 00000003525 11637265524 011722 0000000 0000000 /*
PHYML : a program that computes maximum likelihood phylogenies from
DNA or AA homologous sequences
Copyright (C) Stephane Guindon. Oct 2003 onward
All parts of the source except where indicated are distributed under
the GNU public licence. See http://www.opensource.org for details.
*/
#include
#ifndef FREE_H
#define FREE_H
#include "utilities.h"
void Free_All_Nodes_Light(t_tree *tree);
void Free_All_Edges_Light(t_tree *tree);
void Free_Mat(matrix *mat);
void Free_Partial_Lk(phydbl *p_lk, int len, int n_catg);
void Free_Tree(t_tree *tree);
void Free_Edge(t_edge *b);
void Free_Node(t_node *n);
void Free_Cseq(calign *cdata);
void Free_Seq(align **d, int n_otu);
void Free_All(align **d, calign *cdata, t_tree *tree);
void Free_SubTree(t_edge *b_fcus, t_node *a, t_node *d, t_tree *tree);
void Free_Tree_Ins_Tar(t_tree *tree);
void Free_Tree_Lk(t_tree *tree);
void Free_NNI(t_tree *tree);
void Free_Edge_P_Lk_Struct(t_edge *b, t_tree *tree);
void Free_Node_Lk(t_node *n);
void Free_Edge_Lk(t_tree *tree, t_edge *b);
void Free_Model(model *mod);
void Free_Model_Complete(model *mod);
void Free_Model_Basic(model *mod);
void Free_Custom_Model(model *mod);
void Free(void *p);
void Free_Input(option *input);
void Free_Reachable(t_tree *tree);
void Free_St(supert_tree *st);
void Free_Eigen(eigen *eigen_struct);
void Free_Triplet(triplet *t);
void Free_Tree_Pars(t_tree *tree);
void Free_Edge_Pars(t_edge *b, t_tree *tree);
void Free_One_Spr(spr *this_spr);
void Free_Spr_List(t_tree *tree);
void Free_Actual_CSeq(calign *data);
void Free_Prefix_Tree(pnode *n, int size);
void Free_Pnode(pnode *n);
void Free_Edge_Labels(t_edge *b);
void Free_Nexus_Com(nexcom **com);
void Free_Nexus_Parm(nexparm *parm);
void Free_Nexus(option *io);
void Free_Optimiz(optimiz *s_opt);
void Free_Tree_List(t_treelist *list);
void Free_Bip(t_tree *tree);
#endif
phyml-20120412/src/free.c 0000644 0001750 0001750 00000035745 11721131022 011701 0000000 0000000 /*
PHYML : a program that computes maximum likelihood phyLOGenies from
DNA or AA homologous sequences
Copyright (C) Stephane Guindon. Oct 2003 onward
All parts of the source except where indicated are distributed under
the GNU public licence. See http://www.opensource.org for details.
*/
#include "free.h"
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void Free_All_Nodes_Light(t_tree *tree)
{
int i;
For(i,2*tree->n_otu-1)
{
if(tree->t_nodes[i])
{
Free_Node(tree->t_nodes[i]);
}
}
Free(tree->t_nodes);
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void Free_All_Edges_Light(t_tree *tree)
{
int i;
For(i,2*tree->n_otu-2)
if(tree->t_edges[i])
{
Free_Edge(tree->t_edges[i]);
}
Free(tree->t_edges);
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void Free_Mat(matrix *mat)
{
int i;
For(i,mat->n_otu)
{
Free(mat->P[i]);
Free(mat->Q[i]);
Free(mat->dist[i]);
Free(mat->name[i]);
}
Free(mat->P);
Free(mat->Q);
Free(mat->dist);
Free(mat->name);
Free(mat->tip_node);
Free(mat->on_off);
Free(mat);
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void Free_Partial_Lk(phydbl *p_lk, int len, int n_catg)
{
Free(p_lk);
/* int i,j; */
/* For(i,len) */
/* { */
/* For(j,n_catg) Free((*p_lk)[i][j]); */
/* Free((*p_lk)[i]); */
/* } */
/* Free((*p_lk)); */
/* (*p_lk) = NULL; */
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void Free_Tree(t_tree *tree)
{
Free(tree->t_dir);
if(tree->short_l) Free(tree->short_l);
if(tree->mutmap) Free(tree->mutmap);
Free_Bip(tree);
Free(tree->curr_path);
Free_All_Edges_Light(tree);
Free_All_Nodes_Light(tree);
Free(tree);
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void Free_Bip(t_tree *tree)
{
int i,j;
if(tree->has_bip)
{
For(i,2*tree->n_otu-2)
{
Free(tree->t_nodes[i]->bip_size);
For(j,3) Free(tree->t_nodes[i]->bip_node[j]);
Free(tree->t_nodes[i]->bip_node);
}
}
tree->has_bip = NO;
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void Free_Edge_Labels(t_edge *b)
{
int i;
if(b->labels)
{
For(i,b->n_labels-(b->n_labels%BLOCK_LABELS)+BLOCK_LABELS) Free(b->labels[i]);
Free(b->labels);
b->labels = NULL;
}
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void Free_Edge(t_edge *b)
{
Free_Edge_Labels(b);
Free(b);
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void Free_Node(t_node *n)
{
Free(n->b);
Free(n->v);
Free(n->l);
Free(n->score);
Free(n->s_ingrp);
Free(n->s_outgrp);
if(n->ori_name) { Free(n->ori_name); n->ori_name = NULL; }
/* if(n->name) { Free(n->name); n->name = NULL; } */
/* Don't do that: see Copy_Tax_Names_To_Tip_Labels
tree->t_nodes[i]->ori_name = tree->t_nodes[i]->name; */
Free(n);
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void Free_Cseq(calign *data)
{
int i;
Free(data->invar);
Free(data->wght);
Free(data->ambigu);
Free(data->b_frq);
Free(data->sitepatt);
For(i,data->n_otu)
{
Free(data->c_seq[i]->name);
if(data->c_seq[i]->state)
{
Free(data->c_seq[i]->state);
if(data->c_seq[i]->is_ambigu) Free(data->c_seq[i]->is_ambigu);
}
Free(data->c_seq[i]);
}
Free(data->c_seq);
Free(data);
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void Free_Seq(align **d, int n_otu)
{
int i;
For(i,n_otu)
{
Free(d[i]->name);
Free(d[i]->state);
if(d[i]->is_ambigu) Free(d[i]->is_ambigu);
Free(d[i]);
}
Free(d);
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void Free_All(align **d, calign *cdata, t_tree *tree)
{
Free_Cseq(cdata);
Free_Seq(d,tree->n_otu);
Free_Tree(tree);
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void Free_SubTree(t_edge *b_fcus, t_node *a, t_node *d, t_tree *tree)
{
int i;
if(d->tax) return;
else
{
For(i,3)
{
if(d->v[i] != a)
{
Free_SubTree(d->b[i],d,d->v[i],tree);
Free_Edge(d->b[i]);
Free_Node(d->v[i]);
}
}
}
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void Free_Tree_Ins_Tar(t_tree *tree)
{
return;
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void Free_Tree_Pars(t_tree *tree)
{
int i;
Free(tree->step_mat);
Free(tree->site_pars);
For(i,2*tree->n_otu-3)
Free_Edge_Pars(tree->t_edges[i],tree);
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void Free_Edge_Pars(t_edge *b, t_tree *tree)
{
/* int i; */
Free(b->pars_l);
Free(b->pars_r);
/* For(i,tree->data->crunch_len) */
/* { */
/* Free(b->p_pars_l[i]); */
/* Free(b->p_pars_r[i]); */
/* } */
Free(b->ui_l);
Free(b->ui_r);
Free(b->p_pars_l);
Free(b->p_pars_r);
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void Free_Tree_Lk(t_tree *tree)
{
int i;
t_edge *b;
t_node *n;
b = NULL;
n = NULL;
For(i,3) Free(tree->log_lks_aLRT[i]);
Free(tree->log_lks_aLRT);
Free(tree->c_lnL_sorted);
Free(tree->cur_site_lk);
Free(tree->old_site_lk);
Free(tree->site_lk_cat);
For(i,tree->mod->n_catg) Free(tree->log_site_lk_cat[i]);
Free(tree->log_site_lk_cat);
For(i,2*tree->n_otu-3)
{
b = tree->t_edges[i];
Free_Edge_Lk(tree,b);
}
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void Free_Node_Lk(t_node *n)
{
/* Free(n->n_ex_nodes); */
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void Free_Edge_Lk(t_tree *tree, t_edge *b)
{
Free(b->nni);
Free(b->div_post_pred_left);
Free(b->div_post_pred_rght);
if(b->p_lk_left)
{
Free(b->p_lk_left);
if(b->sum_scale_left) Free(b->sum_scale_left);
}
if(b->p_lk_tip_l) Free(b->p_lk_tip_l);
if(b->p_lk_rght)
{
Free(b->p_lk_rght);
if(b->sum_scale_rght) Free(b->sum_scale_rght);
}
if(b->p_lk_tip_r) Free(b->p_lk_tip_r);
Free(b->sum_scale_left_cat);
Free(b->sum_scale_rght_cat);
Free(b->patt_id_left);
Free(b->patt_id_rght);
Free(b->p_lk_loc_left);
Free(b->p_lk_loc_rght);
Free(b->Pij_rr);
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void Free_Model_Complete(model *mod)
{
Free(mod->pi->v);
Free(mod->pi_unscaled->v);
Free(mod->gamma_r_proba->v);
Free(mod->gamma_r_proba_unscaled->v);
Free(mod->gamma_rr->v);
Free(mod->gamma_rr_unscaled->v);
Free(mod->Pij_rr->v);
Free(mod->qmat->v);
Free(mod->qmat_buff->v);
Free_Eigen(mod->eigen);
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void Free_Model_Basic(model *mod)
{
Free(mod->modelname);
Free(mod->custom_mod_string);
Free(mod->user_b_freq->v);
Free(mod->user_b_freq);
Free(mod->kappa);
Free(mod->lambda);
Free(mod->alpha);
Free(mod->pinvar);
Free(mod->alpha_old);
Free(mod->kappa_old);
Free(mod->lambda_old);
Free(mod->pinvar_old);
Free(mod->rr);
Free(mod->rr_val);
Free(mod->rr_num);
Free(mod->n_rr_per_cat);
Free(mod->Pij_rr);
Free(mod->mr);
Free(mod->qmat);
Free(mod->qmat_buff);
Free(mod->pi);
Free(mod->pi_unscaled);
Free(mod->gamma_r_proba);
Free(mod->gamma_r_proba_unscaled);
Free(mod->gamma_rr);
Free(mod->gamma_rr_unscaled);
Free(mod->br_len_multiplier);
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void Free_Custom_Model(model *mod)
{
if(mod->rr->v)
{
Free(mod->rr_num->v);
Free(mod->rr->v);
Free(mod->rr_val->v);
Free(mod->n_rr_per_cat->v);
}
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void Free_Model(model *mod)
{
Free_Custom_Model(mod);
Free_Model_Complete(mod);
Free_Model_Basic(mod);
M4_Free_M4_Model(mod->m4mod);
Free(mod);
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void Free(void *p)
{
free(p);
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void Free_Input(option *io)
{
int i;
RATES_Free_Rates(io->rates);
MCMC_Free_MCMC(io->mcmc);
Free(io->in_align_file);
Free(io->in_tree_file);
Free(io->in_constraint_tree_file);
Free(io->out_tree_file);
Free(io->out_trees_file);
Free(io->out_boot_tree_file);
Free(io->out_boot_stats_file);
Free(io->out_stats_file);
Free(io->out_lk_file);
Free(io->out_ps_file);
Free(io->out_trace_file);
Free(io->aa_rate_mat_file);
Free(io->nt_or_cd);
Free(io->run_id_string);
Free(io->clade_list_file);
For(i,T_MAX_ALPHABET) Free(io->alphabet[i]);
Free(io->alphabet);
if(io->short_tax_names)
{
For(i,io->size_tax_names)
{
Free(io->short_tax_names[i]);
Free(io->long_tax_names[i]);
}
Free(io->long_tax_names);
Free(io->short_tax_names);
}
Free_Tree_List(io->treelist);
if(io->lon) Free(io->lon);
if(io->lat) Free(io->lat);
Free(io);
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void Free_Tree_List(t_treelist *list)
{
Free(list->tree);
Free(list);
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void Free_St(supert_tree *st)
{
int i;
For(i,2*st->tree->n_otu-3)
Free(st->tree->t_edges[i]->nni);
For(i,st->n_part) Free(st->match_st_node_in_gt[i]);
Free(st->match_st_node_in_gt);
Free_Tree(st->tree);
Free(st);
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void Free_Eigen(eigen *eigen_struct)
{
Free(eigen_struct->space_int);
Free(eigen_struct->space);
Free(eigen_struct->e_val);
Free(eigen_struct->e_val_im);
Free(eigen_struct->r_e_vect);
Free(eigen_struct->r_e_vect_im);
Free(eigen_struct->l_e_vect);
Free(eigen_struct->q);
Free(eigen_struct);
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void Free_One_Spr(spr *this_spr)
{
Free(this_spr->path);
Free(this_spr);
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void Free_Spr_List(t_tree *tree)
{
int i;
For(i,tree->size_spr_list+1) Free_One_Spr(tree->spr_list[i]);
Free(tree->spr_list);
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void Free_Triplet(triplet *t)
{
int i,j,k;
Free(t->F_bc);
Free(t->F_cd);
Free(t->F_bd);
Free(t->pi_bc);
Free(t->pi_cd);
Free(t->pi_bd);
For(k,t->mod->n_catg)
{
For(i,t->size)
{
For(j,t->size) Free(t->core[k][i][j]);
Free(t->core[k][i]);
}
Free(t->core[k]);
}
Free(t->core);
For(i,t->size)
{
For(j,t->size) Free(t->p_one_site[i][j]);
Free(t->p_one_site[i]);
}
Free(t->p_one_site);
For(i,t->size)
{
For(j,t->size) Free(t->sum_p_one_site[i][j]);
Free(t->sum_p_one_site[i]);
}
Free(t->sum_p_one_site);
Free_Eigen(t->eigen_struct);
Free(t);
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void Free_Actual_CSeq(calign *data)
{
int i;
For(i,data->n_otu)
{
Free(data->c_seq[i]->state);
data->c_seq[i]->state = NULL;
}
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void Free_Prefix_Tree(pnode *n, int size)
{
int i;
For(i,size)
{
if(n->next[i])
{
Free_Prefix_Tree(n->next[i],size);
}
}
Free_Pnode(n);
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void Free_Pnode(pnode *n)
{
Free(n->next);
Free(n);
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void Free_Optimiz(optimiz *s_opt)
{
Free(s_opt);
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void Free_Nexus(option *io)
{
int i,j;
For(i,N_MAX_NEX_COM)
{
For(j,io->nex_com_list[i]->nparm) Free_Nexus_Parm(io->nex_com_list[i]->parm[j]);
Free(io->nex_com_list[i]->parm);
Free(io->nex_com_list[i]->name);
Free(io->nex_com_list[i]);
}
Free(io->nex_com_list);
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void Free_Nexus_Com(nexcom **com)
{
int i;
For(i,N_MAX_NEX_COM)
{
Free(com[i]->parm);
Free(com[i]->name);
Free(com[i]);
}
Free(com);
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void Free_Nexus_Parm(nexparm *parm)
{
Free(parm->value);
Free(parm->name);
Free(parm);
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
phyml-20120412/src/Makefile.in 0000644 0001750 0001750 00000211263 11741362653 012672 0000000 0000000 # Makefile.in generated by automake 1.11.1 from Makefile.am.
# @configure_input@
# Copyright (C) 1994, 1995, 1996, 1997, 1998, 1999, 2000, 2001, 2002,
# 2003, 2004, 2005, 2006, 2007, 2008, 2009 Free Software Foundation,
# Inc.
# This Makefile.in is free software; the Free Software Foundation
# gives unlimited permission to copy and/or distribute it,
# with or without modifications, as long as this notice is preserved.
# This program is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY, to the extent permitted by law; without
# even the implied warranty of MERCHANTABILITY or FITNESS FOR A
# PARTICULAR PURPOSE.
@SET_MAKE@
VPATH = @srcdir@
pkgdatadir = $(datadir)/@PACKAGE@
pkgincludedir = $(includedir)/@PACKAGE@
pkglibdir = $(libdir)/@PACKAGE@
pkglibexecdir = $(libexecdir)/@PACKAGE@
am__cd = CDPATH="$${ZSH_VERSION+.}$(PATH_SEPARATOR)" && cd
install_sh_DATA = $(install_sh) -c -m 644
install_sh_PROGRAM = $(install_sh) -c
install_sh_SCRIPT = $(install_sh) -c
INSTALL_HEADER = $(INSTALL_DATA)
transform = $(program_transform_name)
NORMAL_INSTALL = :
PRE_INSTALL = :
POST_INSTALL = :
NORMAL_UNINSTALL = :
PRE_UNINSTALL = :
POST_UNINSTALL = :
build_triplet = @build@
host_triplet = @host@
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@WANT_M4_FALSE@@WANT_MPI_TRUE@@WANT_PART_FALSE@@WANT_PHYCONT_FALSE@@WANT_PHYTIME_FALSE@@WANT_RF_FALSE@@WANT_RWRAP_FALSE@@WANT_TIPORDER_FALSE@bin_PROGRAMS = phyml-mpi$(EXEEXT)
@WANT_M4_FALSE@@WANT_PART_FALSE@@WANT_PHYCONT_FALSE@@WANT_PHYTIME_FALSE@@WANT_RF_TRUE@@WANT_RWRAP_FALSE@@WANT_TIPORDER_FALSE@bin_PROGRAMS = rf$(EXEEXT)
@WANT_M4_TRUE@@WANT_PART_FALSE@@WANT_PHYCONT_FALSE@@WANT_PHYTIME_FALSE@@WANT_RWRAP_FALSE@@WANT_TIPORDER_FALSE@bin_PROGRAMS = m4$(EXEEXT)
@WANT_PART_FALSE@@WANT_PHYCONT_FALSE@@WANT_PHYTIME_FALSE@@WANT_RWRAP_FALSE@@WANT_TIPORDER_TRUE@bin_PROGRAMS = tiporder$(EXEEXT)
@WANT_PART_TRUE@@WANT_PHYCONT_FALSE@@WANT_PHYTIME_FALSE@bin_PROGRAMS = part$(EXEEXT)
@WANT_PHYCONT_TRUE@@WANT_PHYTIME_FALSE@bin_PROGRAMS = \
@WANT_PHYCONT_TRUE@@WANT_PHYTIME_FALSE@ phycont$(EXEEXT)
@WANT_PHYTIME_TRUE@bin_PROGRAMS = phytime$(EXEEXT)
subdir = src
DIST_COMMON = $(srcdir)/Makefile.am $(srcdir)/Makefile.in
ACLOCAL_M4 = $(top_srcdir)/aclocal.m4
am__aclocal_m4_deps = $(top_srcdir)/configure.ac
am__configure_deps = $(am__aclocal_m4_deps) $(CONFIGURE_DEPENDENCIES) \
$(ACLOCAL_M4)
mkinstalldirs = $(install_sh) -d
CONFIG_HEADER = $(top_builddir)/config.h
CONFIG_CLEAN_FILES =
CONFIG_CLEAN_VPATH_FILES =
am__installdirs = "$(DESTDIR)$(bindir)"
PROGRAMS = $(bin_PROGRAMS)
am__m4_SOURCES_DIST = main.c utilities.c utilities.h optimiz.c \
optimiz.h lk.c lk.h bionj.c bionj.h models.c models.h free.c \
free.h help.c help.h simu.c simu.h eigen.c eigen.h pars.c \
pars.h alrt.c alrt.h interface.c interface.h cl.c cl.h mg.c \
mg.h times.c times.h mcmc.c mcmc.h rates.c rates.h spr.c spr.h \
draw.c draw.h stats.c stats.h tiporder.c tiporder.h m4.c m4.h
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@WANT_M4_TRUE@@WANT_PART_FALSE@@WANT_PHYCONT_FALSE@@WANT_PHYTIME_FALSE@@WANT_TIPORDER_FALSE@ tiporder.$(OBJEXT) \
@WANT_M4_TRUE@@WANT_PART_FALSE@@WANT_PHYCONT_FALSE@@WANT_PHYTIME_FALSE@@WANT_TIPORDER_FALSE@ m4.$(OBJEXT)
m4_OBJECTS = $(am_m4_OBJECTS)
m4_DEPENDENCIES =
am__part_SOURCES_DIST = main.c utilities.c utilities.h optimiz.c \
optimiz.h lk.c lk.h bionj.c bionj.h models.c models.h free.c \
free.h help.c help.h simu.c simu.h eigen.c eigen.h pars.c \
pars.h alrt.c alrt.h interface.c interface.h cl.c cl.h mg.c \
mg.h spr.c spr.h m4.c m4.h draw.c draw.h stats.c stats.h \
tiporder.c tiporder.h
@WANT_PART_TRUE@@WANT_PHYCONT_FALSE@@WANT_PHYTIME_FALSE@am_part_OBJECTS = main.$(OBJEXT) \
@WANT_PART_TRUE@@WANT_PHYCONT_FALSE@@WANT_PHYTIME_FALSE@ utilities.$(OBJEXT) \
@WANT_PART_TRUE@@WANT_PHYCONT_FALSE@@WANT_PHYTIME_FALSE@ optimiz.$(OBJEXT) \
@WANT_PART_TRUE@@WANT_PHYCONT_FALSE@@WANT_PHYTIME_FALSE@ lk.$(OBJEXT) \
@WANT_PART_TRUE@@WANT_PHYCONT_FALSE@@WANT_PHYTIME_FALSE@ bionj.$(OBJEXT) \
@WANT_PART_TRUE@@WANT_PHYCONT_FALSE@@WANT_PHYTIME_FALSE@ models.$(OBJEXT) \
@WANT_PART_TRUE@@WANT_PHYCONT_FALSE@@WANT_PHYTIME_FALSE@ free.$(OBJEXT) \
@WANT_PART_TRUE@@WANT_PHYCONT_FALSE@@WANT_PHYTIME_FALSE@ help.$(OBJEXT) \
@WANT_PART_TRUE@@WANT_PHYCONT_FALSE@@WANT_PHYTIME_FALSE@ simu.$(OBJEXT) \
@WANT_PART_TRUE@@WANT_PHYCONT_FALSE@@WANT_PHYTIME_FALSE@ eigen.$(OBJEXT) \
@WANT_PART_TRUE@@WANT_PHYCONT_FALSE@@WANT_PHYTIME_FALSE@ pars.$(OBJEXT) \
@WANT_PART_TRUE@@WANT_PHYCONT_FALSE@@WANT_PHYTIME_FALSE@ alrt.$(OBJEXT) \
@WANT_PART_TRUE@@WANT_PHYCONT_FALSE@@WANT_PHYTIME_FALSE@ interface.$(OBJEXT) \
@WANT_PART_TRUE@@WANT_PHYCONT_FALSE@@WANT_PHYTIME_FALSE@ cl.$(OBJEXT) \
@WANT_PART_TRUE@@WANT_PHYCONT_FALSE@@WANT_PHYTIME_FALSE@ mg.$(OBJEXT) \
@WANT_PART_TRUE@@WANT_PHYCONT_FALSE@@WANT_PHYTIME_FALSE@ spr.$(OBJEXT) \
@WANT_PART_TRUE@@WANT_PHYCONT_FALSE@@WANT_PHYTIME_FALSE@ m4.$(OBJEXT) \
@WANT_PART_TRUE@@WANT_PHYCONT_FALSE@@WANT_PHYTIME_FALSE@ draw.$(OBJEXT) \
@WANT_PART_TRUE@@WANT_PHYCONT_FALSE@@WANT_PHYTIME_FALSE@ stats.$(OBJEXT) \
@WANT_PART_TRUE@@WANT_PHYCONT_FALSE@@WANT_PHYTIME_FALSE@ tiporder.$(OBJEXT)
part_OBJECTS = $(am_part_OBJECTS)
part_DEPENDENCIES =
am__phycont_SOURCES_DIST = main.c utilities.c utilities.h optimiz.c \
optimiz.h lk.c lk.h bionj.c bionj.h models.c models.h free.c \
free.h help.c help.h simu.c simu.h eigen.c eigen.h pars.c \
pars.h alrt.c alrt.h interface.c interface.h cl.c cl.h spr.c \
spr.h times.c times.h m4.c m4.h draw.c draw.h rates.c rates.h \
mcmc.c mcmc.h stats.c stats.h mg.c mg.h tiporder.c tiporder.h
@WANT_PHYCONT_TRUE@@WANT_PHYTIME_FALSE@am_phycont_OBJECTS = \
@WANT_PHYCONT_TRUE@@WANT_PHYTIME_FALSE@ main.$(OBJEXT) \
@WANT_PHYCONT_TRUE@@WANT_PHYTIME_FALSE@ utilities.$(OBJEXT) \
@WANT_PHYCONT_TRUE@@WANT_PHYTIME_FALSE@ optimiz.$(OBJEXT) \
@WANT_PHYCONT_TRUE@@WANT_PHYTIME_FALSE@ lk.$(OBJEXT) \
@WANT_PHYCONT_TRUE@@WANT_PHYTIME_FALSE@ bionj.$(OBJEXT) \
@WANT_PHYCONT_TRUE@@WANT_PHYTIME_FALSE@ models.$(OBJEXT) \
@WANT_PHYCONT_TRUE@@WANT_PHYTIME_FALSE@ free.$(OBJEXT) \
@WANT_PHYCONT_TRUE@@WANT_PHYTIME_FALSE@ help.$(OBJEXT) \
@WANT_PHYCONT_TRUE@@WANT_PHYTIME_FALSE@ simu.$(OBJEXT) \
@WANT_PHYCONT_TRUE@@WANT_PHYTIME_FALSE@ eigen.$(OBJEXT) \
@WANT_PHYCONT_TRUE@@WANT_PHYTIME_FALSE@ pars.$(OBJEXT) \
@WANT_PHYCONT_TRUE@@WANT_PHYTIME_FALSE@ alrt.$(OBJEXT) \
@WANT_PHYCONT_TRUE@@WANT_PHYTIME_FALSE@ interface.$(OBJEXT) \
@WANT_PHYCONT_TRUE@@WANT_PHYTIME_FALSE@ cl.$(OBJEXT) \
@WANT_PHYCONT_TRUE@@WANT_PHYTIME_FALSE@ spr.$(OBJEXT) \
@WANT_PHYCONT_TRUE@@WANT_PHYTIME_FALSE@ times.$(OBJEXT) \
@WANT_PHYCONT_TRUE@@WANT_PHYTIME_FALSE@ m4.$(OBJEXT) \
@WANT_PHYCONT_TRUE@@WANT_PHYTIME_FALSE@ draw.$(OBJEXT) \
@WANT_PHYCONT_TRUE@@WANT_PHYTIME_FALSE@ rates.$(OBJEXT) \
@WANT_PHYCONT_TRUE@@WANT_PHYTIME_FALSE@ mcmc.$(OBJEXT) \
@WANT_PHYCONT_TRUE@@WANT_PHYTIME_FALSE@ stats.$(OBJEXT) \
@WANT_PHYCONT_TRUE@@WANT_PHYTIME_FALSE@ mg.$(OBJEXT) \
@WANT_PHYCONT_TRUE@@WANT_PHYTIME_FALSE@ tiporder.$(OBJEXT)
phycont_OBJECTS = $(am_phycont_OBJECTS)
phycont_DEPENDENCIES =
am__phyml_SOURCES_DIST = main.c utilities.c utilities.h optimiz.c \
optimiz.h lk.c lk.h bionj.c bionj.h models.c models.h free.c \
free.h help.c help.h simu.c simu.h eigen.c eigen.h pars.c \
pars.h alrt.c alrt.h interface.c interface.h cl.c cl.h spr.c \
spr.h draw.c draw.h stats.c stats.h rates.c rates.h mcmc.c \
mcmc.h times.c times.h tiporder.c tiporder.h mg.c mg.h m4.c \
m4.h
@WANT_M4_FALSE@@WANT_MPI_FALSE@@WANT_PART_FALSE@@WANT_PHYCONT_FALSE@@WANT_PHYTIME_FALSE@@WANT_RF_FALSE@@WANT_TEST_FALSE@@WANT_TIPORDER_FALSE@am_phyml_OBJECTS = main.$(OBJEXT) \
@WANT_M4_FALSE@@WANT_MPI_FALSE@@WANT_PART_FALSE@@WANT_PHYCONT_FALSE@@WANT_PHYTIME_FALSE@@WANT_RF_FALSE@@WANT_TEST_FALSE@@WANT_TIPORDER_FALSE@ utilities.$(OBJEXT) \
@WANT_M4_FALSE@@WANT_MPI_FALSE@@WANT_PART_FALSE@@WANT_PHYCONT_FALSE@@WANT_PHYTIME_FALSE@@WANT_RF_FALSE@@WANT_TEST_FALSE@@WANT_TIPORDER_FALSE@ optimiz.$(OBJEXT) \
@WANT_M4_FALSE@@WANT_MPI_FALSE@@WANT_PART_FALSE@@WANT_PHYCONT_FALSE@@WANT_PHYTIME_FALSE@@WANT_RF_FALSE@@WANT_TEST_FALSE@@WANT_TIPORDER_FALSE@ lk.$(OBJEXT) \
@WANT_M4_FALSE@@WANT_MPI_FALSE@@WANT_PART_FALSE@@WANT_PHYCONT_FALSE@@WANT_PHYTIME_FALSE@@WANT_RF_FALSE@@WANT_TEST_FALSE@@WANT_TIPORDER_FALSE@ bionj.$(OBJEXT) \
@WANT_M4_FALSE@@WANT_MPI_FALSE@@WANT_PART_FALSE@@WANT_PHYCONT_FALSE@@WANT_PHYTIME_FALSE@@WANT_RF_FALSE@@WANT_TEST_FALSE@@WANT_TIPORDER_FALSE@ models.$(OBJEXT) \
@WANT_M4_FALSE@@WANT_MPI_FALSE@@WANT_PART_FALSE@@WANT_PHYCONT_FALSE@@WANT_PHYTIME_FALSE@@WANT_RF_FALSE@@WANT_TEST_FALSE@@WANT_TIPORDER_FALSE@ free.$(OBJEXT) \
@WANT_M4_FALSE@@WANT_MPI_FALSE@@WANT_PART_FALSE@@WANT_PHYCONT_FALSE@@WANT_PHYTIME_FALSE@@WANT_RF_FALSE@@WANT_TEST_FALSE@@WANT_TIPORDER_FALSE@ help.$(OBJEXT) \
@WANT_M4_FALSE@@WANT_MPI_FALSE@@WANT_PART_FALSE@@WANT_PHYCONT_FALSE@@WANT_PHYTIME_FALSE@@WANT_RF_FALSE@@WANT_TEST_FALSE@@WANT_TIPORDER_FALSE@ simu.$(OBJEXT) \
@WANT_M4_FALSE@@WANT_MPI_FALSE@@WANT_PART_FALSE@@WANT_PHYCONT_FALSE@@WANT_PHYTIME_FALSE@@WANT_RF_FALSE@@WANT_TEST_FALSE@@WANT_TIPORDER_FALSE@ eigen.$(OBJEXT) \
@WANT_M4_FALSE@@WANT_MPI_FALSE@@WANT_PART_FALSE@@WANT_PHYCONT_FALSE@@WANT_PHYTIME_FALSE@@WANT_RF_FALSE@@WANT_TEST_FALSE@@WANT_TIPORDER_FALSE@ pars.$(OBJEXT) \
@WANT_M4_FALSE@@WANT_MPI_FALSE@@WANT_PART_FALSE@@WANT_PHYCONT_FALSE@@WANT_PHYTIME_FALSE@@WANT_RF_FALSE@@WANT_TEST_FALSE@@WANT_TIPORDER_FALSE@ alrt.$(OBJEXT) \
@WANT_M4_FALSE@@WANT_MPI_FALSE@@WANT_PART_FALSE@@WANT_PHYCONT_FALSE@@WANT_PHYTIME_FALSE@@WANT_RF_FALSE@@WANT_TEST_FALSE@@WANT_TIPORDER_FALSE@ interface.$(OBJEXT) \
@WANT_M4_FALSE@@WANT_MPI_FALSE@@WANT_PART_FALSE@@WANT_PHYCONT_FALSE@@WANT_PHYTIME_FALSE@@WANT_RF_FALSE@@WANT_TEST_FALSE@@WANT_TIPORDER_FALSE@ cl.$(OBJEXT) \
@WANT_M4_FALSE@@WANT_MPI_FALSE@@WANT_PART_FALSE@@WANT_PHYCONT_FALSE@@WANT_PHYTIME_FALSE@@WANT_RF_FALSE@@WANT_TEST_FALSE@@WANT_TIPORDER_FALSE@ spr.$(OBJEXT) \
@WANT_M4_FALSE@@WANT_MPI_FALSE@@WANT_PART_FALSE@@WANT_PHYCONT_FALSE@@WANT_PHYTIME_FALSE@@WANT_RF_FALSE@@WANT_TEST_FALSE@@WANT_TIPORDER_FALSE@ draw.$(OBJEXT) \
@WANT_M4_FALSE@@WANT_MPI_FALSE@@WANT_PART_FALSE@@WANT_PHYCONT_FALSE@@WANT_PHYTIME_FALSE@@WANT_RF_FALSE@@WANT_TEST_FALSE@@WANT_TIPORDER_FALSE@ stats.$(OBJEXT) \
@WANT_M4_FALSE@@WANT_MPI_FALSE@@WANT_PART_FALSE@@WANT_PHYCONT_FALSE@@WANT_PHYTIME_FALSE@@WANT_RF_FALSE@@WANT_TEST_FALSE@@WANT_TIPORDER_FALSE@ rates.$(OBJEXT) \
@WANT_M4_FALSE@@WANT_MPI_FALSE@@WANT_PART_FALSE@@WANT_PHYCONT_FALSE@@WANT_PHYTIME_FALSE@@WANT_RF_FALSE@@WANT_TEST_FALSE@@WANT_TIPORDER_FALSE@ mcmc.$(OBJEXT) \
@WANT_M4_FALSE@@WANT_MPI_FALSE@@WANT_PART_FALSE@@WANT_PHYCONT_FALSE@@WANT_PHYTIME_FALSE@@WANT_RF_FALSE@@WANT_TEST_FALSE@@WANT_TIPORDER_FALSE@ times.$(OBJEXT) \
@WANT_M4_FALSE@@WANT_MPI_FALSE@@WANT_PART_FALSE@@WANT_PHYCONT_FALSE@@WANT_PHYTIME_FALSE@@WANT_RF_FALSE@@WANT_TEST_FALSE@@WANT_TIPORDER_FALSE@ tiporder.$(OBJEXT) \
@WANT_M4_FALSE@@WANT_MPI_FALSE@@WANT_PART_FALSE@@WANT_PHYCONT_FALSE@@WANT_PHYTIME_FALSE@@WANT_RF_FALSE@@WANT_TEST_FALSE@@WANT_TIPORDER_FALSE@ mg.$(OBJEXT) \
@WANT_M4_FALSE@@WANT_MPI_FALSE@@WANT_PART_FALSE@@WANT_PHYCONT_FALSE@@WANT_PHYTIME_FALSE@@WANT_RF_FALSE@@WANT_TEST_FALSE@@WANT_TIPORDER_FALSE@ m4.$(OBJEXT)
phyml_OBJECTS = $(am_phyml_OBJECTS)
phyml_DEPENDENCIES =
am__phyml_mpi_SOURCES_DIST = main.c utilities.c utilities.h optimiz.c \
optimiz.h lk.c lk.h bionj.c bionj.h models.c models.h free.c \
free.h help.c help.h simu.c simu.h eigen.c eigen.h pars.c \
pars.h alrt.c alrt.h interface.c interface.h cl.c cl.h spr.c \
spr.h draw.c draw.h mpi_boot.c mpi_boot.h stats.c stats.h \
rates.c rates.h mcmc.c mcmc.h times.c times.h tiporder.c \
tiporder.h mg.c mg.h m4.c m4.h xml.c xml.h
@WANT_M4_FALSE@@WANT_MPI_TRUE@@WANT_PART_FALSE@@WANT_PHYCONT_FALSE@@WANT_PHYTIME_FALSE@@WANT_RF_FALSE@@WANT_TIPORDER_FALSE@am_phyml_mpi_OBJECTS = main.$(OBJEXT) \
@WANT_M4_FALSE@@WANT_MPI_TRUE@@WANT_PART_FALSE@@WANT_PHYCONT_FALSE@@WANT_PHYTIME_FALSE@@WANT_RF_FALSE@@WANT_TIPORDER_FALSE@ utilities.$(OBJEXT) \
@WANT_M4_FALSE@@WANT_MPI_TRUE@@WANT_PART_FALSE@@WANT_PHYCONT_FALSE@@WANT_PHYTIME_FALSE@@WANT_RF_FALSE@@WANT_TIPORDER_FALSE@ optimiz.$(OBJEXT) \
@WANT_M4_FALSE@@WANT_MPI_TRUE@@WANT_PART_FALSE@@WANT_PHYCONT_FALSE@@WANT_PHYTIME_FALSE@@WANT_RF_FALSE@@WANT_TIPORDER_FALSE@ lk.$(OBJEXT) \
@WANT_M4_FALSE@@WANT_MPI_TRUE@@WANT_PART_FALSE@@WANT_PHYCONT_FALSE@@WANT_PHYTIME_FALSE@@WANT_RF_FALSE@@WANT_TIPORDER_FALSE@ bionj.$(OBJEXT) \
@WANT_M4_FALSE@@WANT_MPI_TRUE@@WANT_PART_FALSE@@WANT_PHYCONT_FALSE@@WANT_PHYTIME_FALSE@@WANT_RF_FALSE@@WANT_TIPORDER_FALSE@ models.$(OBJEXT) \
@WANT_M4_FALSE@@WANT_MPI_TRUE@@WANT_PART_FALSE@@WANT_PHYCONT_FALSE@@WANT_PHYTIME_FALSE@@WANT_RF_FALSE@@WANT_TIPORDER_FALSE@ free.$(OBJEXT) \
@WANT_M4_FALSE@@WANT_MPI_TRUE@@WANT_PART_FALSE@@WANT_PHYCONT_FALSE@@WANT_PHYTIME_FALSE@@WANT_RF_FALSE@@WANT_TIPORDER_FALSE@ help.$(OBJEXT) \
@WANT_M4_FALSE@@WANT_MPI_TRUE@@WANT_PART_FALSE@@WANT_PHYCONT_FALSE@@WANT_PHYTIME_FALSE@@WANT_RF_FALSE@@WANT_TIPORDER_FALSE@ simu.$(OBJEXT) \
@WANT_M4_FALSE@@WANT_MPI_TRUE@@WANT_PART_FALSE@@WANT_PHYCONT_FALSE@@WANT_PHYTIME_FALSE@@WANT_RF_FALSE@@WANT_TIPORDER_FALSE@ eigen.$(OBJEXT) \
@WANT_M4_FALSE@@WANT_MPI_TRUE@@WANT_PART_FALSE@@WANT_PHYCONT_FALSE@@WANT_PHYTIME_FALSE@@WANT_RF_FALSE@@WANT_TIPORDER_FALSE@ pars.$(OBJEXT) \
@WANT_M4_FALSE@@WANT_MPI_TRUE@@WANT_PART_FALSE@@WANT_PHYCONT_FALSE@@WANT_PHYTIME_FALSE@@WANT_RF_FALSE@@WANT_TIPORDER_FALSE@ alrt.$(OBJEXT) \
@WANT_M4_FALSE@@WANT_MPI_TRUE@@WANT_PART_FALSE@@WANT_PHYCONT_FALSE@@WANT_PHYTIME_FALSE@@WANT_RF_FALSE@@WANT_TIPORDER_FALSE@ interface.$(OBJEXT) \
@WANT_M4_FALSE@@WANT_MPI_TRUE@@WANT_PART_FALSE@@WANT_PHYCONT_FALSE@@WANT_PHYTIME_FALSE@@WANT_RF_FALSE@@WANT_TIPORDER_FALSE@ cl.$(OBJEXT) \
@WANT_M4_FALSE@@WANT_MPI_TRUE@@WANT_PART_FALSE@@WANT_PHYCONT_FALSE@@WANT_PHYTIME_FALSE@@WANT_RF_FALSE@@WANT_TIPORDER_FALSE@ spr.$(OBJEXT) \
@WANT_M4_FALSE@@WANT_MPI_TRUE@@WANT_PART_FALSE@@WANT_PHYCONT_FALSE@@WANT_PHYTIME_FALSE@@WANT_RF_FALSE@@WANT_TIPORDER_FALSE@ draw.$(OBJEXT) \
@WANT_M4_FALSE@@WANT_MPI_TRUE@@WANT_PART_FALSE@@WANT_PHYCONT_FALSE@@WANT_PHYTIME_FALSE@@WANT_RF_FALSE@@WANT_TIPORDER_FALSE@ mpi_boot.$(OBJEXT) \
@WANT_M4_FALSE@@WANT_MPI_TRUE@@WANT_PART_FALSE@@WANT_PHYCONT_FALSE@@WANT_PHYTIME_FALSE@@WANT_RF_FALSE@@WANT_TIPORDER_FALSE@ stats.$(OBJEXT) \
@WANT_M4_FALSE@@WANT_MPI_TRUE@@WANT_PART_FALSE@@WANT_PHYCONT_FALSE@@WANT_PHYTIME_FALSE@@WANT_RF_FALSE@@WANT_TIPORDER_FALSE@ rates.$(OBJEXT) \
@WANT_M4_FALSE@@WANT_MPI_TRUE@@WANT_PART_FALSE@@WANT_PHYCONT_FALSE@@WANT_PHYTIME_FALSE@@WANT_RF_FALSE@@WANT_TIPORDER_FALSE@ mcmc.$(OBJEXT) \
@WANT_M4_FALSE@@WANT_MPI_TRUE@@WANT_PART_FALSE@@WANT_PHYCONT_FALSE@@WANT_PHYTIME_FALSE@@WANT_RF_FALSE@@WANT_TIPORDER_FALSE@ times.$(OBJEXT) \
@WANT_M4_FALSE@@WANT_MPI_TRUE@@WANT_PART_FALSE@@WANT_PHYCONT_FALSE@@WANT_PHYTIME_FALSE@@WANT_RF_FALSE@@WANT_TIPORDER_FALSE@ tiporder.$(OBJEXT) \
@WANT_M4_FALSE@@WANT_MPI_TRUE@@WANT_PART_FALSE@@WANT_PHYCONT_FALSE@@WANT_PHYTIME_FALSE@@WANT_RF_FALSE@@WANT_TIPORDER_FALSE@ mg.$(OBJEXT) \
@WANT_M4_FALSE@@WANT_MPI_TRUE@@WANT_PART_FALSE@@WANT_PHYCONT_FALSE@@WANT_PHYTIME_FALSE@@WANT_RF_FALSE@@WANT_TIPORDER_FALSE@ m4.$(OBJEXT) \
@WANT_M4_FALSE@@WANT_MPI_TRUE@@WANT_PART_FALSE@@WANT_PHYCONT_FALSE@@WANT_PHYTIME_FALSE@@WANT_RF_FALSE@@WANT_TIPORDER_FALSE@ xml.$(OBJEXT)
phyml_mpi_OBJECTS = $(am_phyml_mpi_OBJECTS)
phyml_mpi_DEPENDENCIES =
am__phytime_SOURCES_DIST = main.c utilities.c utilities.h optimiz.c \
optimiz.h lk.c lk.h bionj.c bionj.h models.c models.h free.c \
free.h help.c help.h simu.c simu.h eigen.c eigen.h pars.c \
pars.h alrt.c alrt.h interface.c interface.h cl.c cl.h spr.c \
spr.h times.c times.h m4.c m4.h draw.c draw.h rates.c rates.h \
mcmc.c mcmc.h stats.c stats.h mg.c mg.h tiporder.c tiporder.h
@WANT_PHYTIME_TRUE@am_phytime_OBJECTS = main.$(OBJEXT) \
@WANT_PHYTIME_TRUE@ utilities.$(OBJEXT) optimiz.$(OBJEXT) \
@WANT_PHYTIME_TRUE@ lk.$(OBJEXT) bionj.$(OBJEXT) \
@WANT_PHYTIME_TRUE@ models.$(OBJEXT) free.$(OBJEXT) \
@WANT_PHYTIME_TRUE@ help.$(OBJEXT) simu.$(OBJEXT) \
@WANT_PHYTIME_TRUE@ eigen.$(OBJEXT) pars.$(OBJEXT) \
@WANT_PHYTIME_TRUE@ alrt.$(OBJEXT) interface.$(OBJEXT) \
@WANT_PHYTIME_TRUE@ cl.$(OBJEXT) spr.$(OBJEXT) times.$(OBJEXT) \
@WANT_PHYTIME_TRUE@ m4.$(OBJEXT) draw.$(OBJEXT) rates.$(OBJEXT) \
@WANT_PHYTIME_TRUE@ mcmc.$(OBJEXT) stats.$(OBJEXT) mg.$(OBJEXT) \
@WANT_PHYTIME_TRUE@ tiporder.$(OBJEXT)
phytime_OBJECTS = $(am_phytime_OBJECTS)
phytime_DEPENDENCIES =
am__rf_SOURCES_DIST = main.c utilities.c utilities.h optimiz.c \
optimiz.h lk.c lk.h bionj.c bionj.h models.c models.h free.c \
free.h help.c help.h simu.c simu.h eigen.c eigen.h pars.c \
pars.h alrt.c alrt.h interface.c interface.h cl.c cl.h mg.c \
mg.h times.c times.h mcmc.c mcmc.h rates.c rates.h spr.c spr.h \
draw.c draw.h stats.c stats.h tiporder.c tiporder.h m4.c m4.h
@WANT_M4_FALSE@@WANT_PART_FALSE@@WANT_PHYCONT_FALSE@@WANT_PHYTIME_FALSE@@WANT_RF_TRUE@@WANT_TIPORDER_FALSE@am_rf_OBJECTS = main.$(OBJEXT) \
@WANT_M4_FALSE@@WANT_PART_FALSE@@WANT_PHYCONT_FALSE@@WANT_PHYTIME_FALSE@@WANT_RF_TRUE@@WANT_TIPORDER_FALSE@ utilities.$(OBJEXT) \
@WANT_M4_FALSE@@WANT_PART_FALSE@@WANT_PHYCONT_FALSE@@WANT_PHYTIME_FALSE@@WANT_RF_TRUE@@WANT_TIPORDER_FALSE@ optimiz.$(OBJEXT) \
@WANT_M4_FALSE@@WANT_PART_FALSE@@WANT_PHYCONT_FALSE@@WANT_PHYTIME_FALSE@@WANT_RF_TRUE@@WANT_TIPORDER_FALSE@ lk.$(OBJEXT) \
@WANT_M4_FALSE@@WANT_PART_FALSE@@WANT_PHYCONT_FALSE@@WANT_PHYTIME_FALSE@@WANT_RF_TRUE@@WANT_TIPORDER_FALSE@ bionj.$(OBJEXT) \
@WANT_M4_FALSE@@WANT_PART_FALSE@@WANT_PHYCONT_FALSE@@WANT_PHYTIME_FALSE@@WANT_RF_TRUE@@WANT_TIPORDER_FALSE@ models.$(OBJEXT) \
@WANT_M4_FALSE@@WANT_PART_FALSE@@WANT_PHYCONT_FALSE@@WANT_PHYTIME_FALSE@@WANT_RF_TRUE@@WANT_TIPORDER_FALSE@ free.$(OBJEXT) \
@WANT_M4_FALSE@@WANT_PART_FALSE@@WANT_PHYCONT_FALSE@@WANT_PHYTIME_FALSE@@WANT_RF_TRUE@@WANT_TIPORDER_FALSE@ help.$(OBJEXT) \
@WANT_M4_FALSE@@WANT_PART_FALSE@@WANT_PHYCONT_FALSE@@WANT_PHYTIME_FALSE@@WANT_RF_TRUE@@WANT_TIPORDER_FALSE@ simu.$(OBJEXT) \
@WANT_M4_FALSE@@WANT_PART_FALSE@@WANT_PHYCONT_FALSE@@WANT_PHYTIME_FALSE@@WANT_RF_TRUE@@WANT_TIPORDER_FALSE@ eigen.$(OBJEXT) \
@WANT_M4_FALSE@@WANT_PART_FALSE@@WANT_PHYCONT_FALSE@@WANT_PHYTIME_FALSE@@WANT_RF_TRUE@@WANT_TIPORDER_FALSE@ pars.$(OBJEXT) \
@WANT_M4_FALSE@@WANT_PART_FALSE@@WANT_PHYCONT_FALSE@@WANT_PHYTIME_FALSE@@WANT_RF_TRUE@@WANT_TIPORDER_FALSE@ alrt.$(OBJEXT) \
@WANT_M4_FALSE@@WANT_PART_FALSE@@WANT_PHYCONT_FALSE@@WANT_PHYTIME_FALSE@@WANT_RF_TRUE@@WANT_TIPORDER_FALSE@ interface.$(OBJEXT) \
@WANT_M4_FALSE@@WANT_PART_FALSE@@WANT_PHYCONT_FALSE@@WANT_PHYTIME_FALSE@@WANT_RF_TRUE@@WANT_TIPORDER_FALSE@ cl.$(OBJEXT) \
@WANT_M4_FALSE@@WANT_PART_FALSE@@WANT_PHYCONT_FALSE@@WANT_PHYTIME_FALSE@@WANT_RF_TRUE@@WANT_TIPORDER_FALSE@ mg.$(OBJEXT) \
@WANT_M4_FALSE@@WANT_PART_FALSE@@WANT_PHYCONT_FALSE@@WANT_PHYTIME_FALSE@@WANT_RF_TRUE@@WANT_TIPORDER_FALSE@ times.$(OBJEXT) \
@WANT_M4_FALSE@@WANT_PART_FALSE@@WANT_PHYCONT_FALSE@@WANT_PHYTIME_FALSE@@WANT_RF_TRUE@@WANT_TIPORDER_FALSE@ mcmc.$(OBJEXT) \
@WANT_M4_FALSE@@WANT_PART_FALSE@@WANT_PHYCONT_FALSE@@WANT_PHYTIME_FALSE@@WANT_RF_TRUE@@WANT_TIPORDER_FALSE@ rates.$(OBJEXT) \
@WANT_M4_FALSE@@WANT_PART_FALSE@@WANT_PHYCONT_FALSE@@WANT_PHYTIME_FALSE@@WANT_RF_TRUE@@WANT_TIPORDER_FALSE@ spr.$(OBJEXT) \
@WANT_M4_FALSE@@WANT_PART_FALSE@@WANT_PHYCONT_FALSE@@WANT_PHYTIME_FALSE@@WANT_RF_TRUE@@WANT_TIPORDER_FALSE@ draw.$(OBJEXT) \
@WANT_M4_FALSE@@WANT_PART_FALSE@@WANT_PHYCONT_FALSE@@WANT_PHYTIME_FALSE@@WANT_RF_TRUE@@WANT_TIPORDER_FALSE@ stats.$(OBJEXT) \
@WANT_M4_FALSE@@WANT_PART_FALSE@@WANT_PHYCONT_FALSE@@WANT_PHYTIME_FALSE@@WANT_RF_TRUE@@WANT_TIPORDER_FALSE@ tiporder.$(OBJEXT) \
@WANT_M4_FALSE@@WANT_PART_FALSE@@WANT_PHYCONT_FALSE@@WANT_PHYTIME_FALSE@@WANT_RF_TRUE@@WANT_TIPORDER_FALSE@ m4.$(OBJEXT)
rf_OBJECTS = $(am_rf_OBJECTS)
rf_DEPENDENCIES =
am__test_SOURCES_DIST = main.c utilities.c utilities.h optimiz.c \
optimiz.h lk.c lk.h bionj.c bionj.h models.c models.h free.c \
free.h help.c help.h simu.c simu.h eigen.c eigen.h pars.c \
pars.h alrt.c alrt.h interface.c interface.h cl.c cl.h spr.c \
spr.h draw.c draw.h stats.c stats.h rates.c rates.h mcmc.c \
mcmc.h times.c times.h tiporder.c tiporder.h mg.c mg.h m4.c \
m4.h xml.c xml.h
@WANT_M4_FALSE@@WANT_MPI_FALSE@@WANT_PART_FALSE@@WANT_PHYCONT_FALSE@@WANT_PHYTIME_FALSE@@WANT_RF_FALSE@@WANT_TEST_TRUE@@WANT_TIPORDER_FALSE@am_test_OBJECTS = main.$(OBJEXT) \
@WANT_M4_FALSE@@WANT_MPI_FALSE@@WANT_PART_FALSE@@WANT_PHYCONT_FALSE@@WANT_PHYTIME_FALSE@@WANT_RF_FALSE@@WANT_TEST_TRUE@@WANT_TIPORDER_FALSE@ utilities.$(OBJEXT) \
@WANT_M4_FALSE@@WANT_MPI_FALSE@@WANT_PART_FALSE@@WANT_PHYCONT_FALSE@@WANT_PHYTIME_FALSE@@WANT_RF_FALSE@@WANT_TEST_TRUE@@WANT_TIPORDER_FALSE@ optimiz.$(OBJEXT) \
@WANT_M4_FALSE@@WANT_MPI_FALSE@@WANT_PART_FALSE@@WANT_PHYCONT_FALSE@@WANT_PHYTIME_FALSE@@WANT_RF_FALSE@@WANT_TEST_TRUE@@WANT_TIPORDER_FALSE@ lk.$(OBJEXT) \
@WANT_M4_FALSE@@WANT_MPI_FALSE@@WANT_PART_FALSE@@WANT_PHYCONT_FALSE@@WANT_PHYTIME_FALSE@@WANT_RF_FALSE@@WANT_TEST_TRUE@@WANT_TIPORDER_FALSE@ bionj.$(OBJEXT) \
@WANT_M4_FALSE@@WANT_MPI_FALSE@@WANT_PART_FALSE@@WANT_PHYCONT_FALSE@@WANT_PHYTIME_FALSE@@WANT_RF_FALSE@@WANT_TEST_TRUE@@WANT_TIPORDER_FALSE@ models.$(OBJEXT) \
@WANT_M4_FALSE@@WANT_MPI_FALSE@@WANT_PART_FALSE@@WANT_PHYCONT_FALSE@@WANT_PHYTIME_FALSE@@WANT_RF_FALSE@@WANT_TEST_TRUE@@WANT_TIPORDER_FALSE@ free.$(OBJEXT) \
@WANT_M4_FALSE@@WANT_MPI_FALSE@@WANT_PART_FALSE@@WANT_PHYCONT_FALSE@@WANT_PHYTIME_FALSE@@WANT_RF_FALSE@@WANT_TEST_TRUE@@WANT_TIPORDER_FALSE@ help.$(OBJEXT) \
@WANT_M4_FALSE@@WANT_MPI_FALSE@@WANT_PART_FALSE@@WANT_PHYCONT_FALSE@@WANT_PHYTIME_FALSE@@WANT_RF_FALSE@@WANT_TEST_TRUE@@WANT_TIPORDER_FALSE@ simu.$(OBJEXT) \
@WANT_M4_FALSE@@WANT_MPI_FALSE@@WANT_PART_FALSE@@WANT_PHYCONT_FALSE@@WANT_PHYTIME_FALSE@@WANT_RF_FALSE@@WANT_TEST_TRUE@@WANT_TIPORDER_FALSE@ eigen.$(OBJEXT) \
@WANT_M4_FALSE@@WANT_MPI_FALSE@@WANT_PART_FALSE@@WANT_PHYCONT_FALSE@@WANT_PHYTIME_FALSE@@WANT_RF_FALSE@@WANT_TEST_TRUE@@WANT_TIPORDER_FALSE@ pars.$(OBJEXT) \
@WANT_M4_FALSE@@WANT_MPI_FALSE@@WANT_PART_FALSE@@WANT_PHYCONT_FALSE@@WANT_PHYTIME_FALSE@@WANT_RF_FALSE@@WANT_TEST_TRUE@@WANT_TIPORDER_FALSE@ alrt.$(OBJEXT) \
@WANT_M4_FALSE@@WANT_MPI_FALSE@@WANT_PART_FALSE@@WANT_PHYCONT_FALSE@@WANT_PHYTIME_FALSE@@WANT_RF_FALSE@@WANT_TEST_TRUE@@WANT_TIPORDER_FALSE@ interface.$(OBJEXT) \
@WANT_M4_FALSE@@WANT_MPI_FALSE@@WANT_PART_FALSE@@WANT_PHYCONT_FALSE@@WANT_PHYTIME_FALSE@@WANT_RF_FALSE@@WANT_TEST_TRUE@@WANT_TIPORDER_FALSE@ cl.$(OBJEXT) \
@WANT_M4_FALSE@@WANT_MPI_FALSE@@WANT_PART_FALSE@@WANT_PHYCONT_FALSE@@WANT_PHYTIME_FALSE@@WANT_RF_FALSE@@WANT_TEST_TRUE@@WANT_TIPORDER_FALSE@ spr.$(OBJEXT) \
@WANT_M4_FALSE@@WANT_MPI_FALSE@@WANT_PART_FALSE@@WANT_PHYCONT_FALSE@@WANT_PHYTIME_FALSE@@WANT_RF_FALSE@@WANT_TEST_TRUE@@WANT_TIPORDER_FALSE@ draw.$(OBJEXT) \
@WANT_M4_FALSE@@WANT_MPI_FALSE@@WANT_PART_FALSE@@WANT_PHYCONT_FALSE@@WANT_PHYTIME_FALSE@@WANT_RF_FALSE@@WANT_TEST_TRUE@@WANT_TIPORDER_FALSE@ stats.$(OBJEXT) \
@WANT_M4_FALSE@@WANT_MPI_FALSE@@WANT_PART_FALSE@@WANT_PHYCONT_FALSE@@WANT_PHYTIME_FALSE@@WANT_RF_FALSE@@WANT_TEST_TRUE@@WANT_TIPORDER_FALSE@ rates.$(OBJEXT) \
@WANT_M4_FALSE@@WANT_MPI_FALSE@@WANT_PART_FALSE@@WANT_PHYCONT_FALSE@@WANT_PHYTIME_FALSE@@WANT_RF_FALSE@@WANT_TEST_TRUE@@WANT_TIPORDER_FALSE@ mcmc.$(OBJEXT) \
@WANT_M4_FALSE@@WANT_MPI_FALSE@@WANT_PART_FALSE@@WANT_PHYCONT_FALSE@@WANT_PHYTIME_FALSE@@WANT_RF_FALSE@@WANT_TEST_TRUE@@WANT_TIPORDER_FALSE@ times.$(OBJEXT) \
@WANT_M4_FALSE@@WANT_MPI_FALSE@@WANT_PART_FALSE@@WANT_PHYCONT_FALSE@@WANT_PHYTIME_FALSE@@WANT_RF_FALSE@@WANT_TEST_TRUE@@WANT_TIPORDER_FALSE@ tiporder.$(OBJEXT) \
@WANT_M4_FALSE@@WANT_MPI_FALSE@@WANT_PART_FALSE@@WANT_PHYCONT_FALSE@@WANT_PHYTIME_FALSE@@WANT_RF_FALSE@@WANT_TEST_TRUE@@WANT_TIPORDER_FALSE@ mg.$(OBJEXT) \
@WANT_M4_FALSE@@WANT_MPI_FALSE@@WANT_PART_FALSE@@WANT_PHYCONT_FALSE@@WANT_PHYTIME_FALSE@@WANT_RF_FALSE@@WANT_TEST_TRUE@@WANT_TIPORDER_FALSE@ m4.$(OBJEXT) \
@WANT_M4_FALSE@@WANT_MPI_FALSE@@WANT_PART_FALSE@@WANT_PHYCONT_FALSE@@WANT_PHYTIME_FALSE@@WANT_RF_FALSE@@WANT_TEST_TRUE@@WANT_TIPORDER_FALSE@ xml.$(OBJEXT)
test_OBJECTS = $(am_test_OBJECTS)
test_DEPENDENCIES =
am__tiporder_SOURCES_DIST = main.c utilities.c utilities.h optimiz.c \
optimiz.h lk.c lk.h bionj.c bionj.h models.c models.h free.c \
free.h help.c help.h simu.c simu.h eigen.c eigen.h pars.c \
pars.h alrt.c alrt.h interface.c interface.h cl.c cl.h mg.c \
mg.h times.c times.h mcmc.c mcmc.h rates.c rates.h spr.c spr.h \
m4.c m4.h draw.c draw.h stats.c stats.h tiporder.c tiporder.h
@WANT_PART_FALSE@@WANT_PHYCONT_FALSE@@WANT_PHYTIME_FALSE@@WANT_TIPORDER_TRUE@am_tiporder_OBJECTS = main.$(OBJEXT) \
@WANT_PART_FALSE@@WANT_PHYCONT_FALSE@@WANT_PHYTIME_FALSE@@WANT_TIPORDER_TRUE@ utilities.$(OBJEXT) \
@WANT_PART_FALSE@@WANT_PHYCONT_FALSE@@WANT_PHYTIME_FALSE@@WANT_TIPORDER_TRUE@ optimiz.$(OBJEXT) \
@WANT_PART_FALSE@@WANT_PHYCONT_FALSE@@WANT_PHYTIME_FALSE@@WANT_TIPORDER_TRUE@ lk.$(OBJEXT) \
@WANT_PART_FALSE@@WANT_PHYCONT_FALSE@@WANT_PHYTIME_FALSE@@WANT_TIPORDER_TRUE@ bionj.$(OBJEXT) \
@WANT_PART_FALSE@@WANT_PHYCONT_FALSE@@WANT_PHYTIME_FALSE@@WANT_TIPORDER_TRUE@ models.$(OBJEXT) \
@WANT_PART_FALSE@@WANT_PHYCONT_FALSE@@WANT_PHYTIME_FALSE@@WANT_TIPORDER_TRUE@ free.$(OBJEXT) \
@WANT_PART_FALSE@@WANT_PHYCONT_FALSE@@WANT_PHYTIME_FALSE@@WANT_TIPORDER_TRUE@ help.$(OBJEXT) \
@WANT_PART_FALSE@@WANT_PHYCONT_FALSE@@WANT_PHYTIME_FALSE@@WANT_TIPORDER_TRUE@ simu.$(OBJEXT) \
@WANT_PART_FALSE@@WANT_PHYCONT_FALSE@@WANT_PHYTIME_FALSE@@WANT_TIPORDER_TRUE@ eigen.$(OBJEXT) \
@WANT_PART_FALSE@@WANT_PHYCONT_FALSE@@WANT_PHYTIME_FALSE@@WANT_TIPORDER_TRUE@ pars.$(OBJEXT) \
@WANT_PART_FALSE@@WANT_PHYCONT_FALSE@@WANT_PHYTIME_FALSE@@WANT_TIPORDER_TRUE@ alrt.$(OBJEXT) \
@WANT_PART_FALSE@@WANT_PHYCONT_FALSE@@WANT_PHYTIME_FALSE@@WANT_TIPORDER_TRUE@ interface.$(OBJEXT) \
@WANT_PART_FALSE@@WANT_PHYCONT_FALSE@@WANT_PHYTIME_FALSE@@WANT_TIPORDER_TRUE@ cl.$(OBJEXT) \
@WANT_PART_FALSE@@WANT_PHYCONT_FALSE@@WANT_PHYTIME_FALSE@@WANT_TIPORDER_TRUE@ mg.$(OBJEXT) \
@WANT_PART_FALSE@@WANT_PHYCONT_FALSE@@WANT_PHYTIME_FALSE@@WANT_TIPORDER_TRUE@ times.$(OBJEXT) \
@WANT_PART_FALSE@@WANT_PHYCONT_FALSE@@WANT_PHYTIME_FALSE@@WANT_TIPORDER_TRUE@ mcmc.$(OBJEXT) \
@WANT_PART_FALSE@@WANT_PHYCONT_FALSE@@WANT_PHYTIME_FALSE@@WANT_TIPORDER_TRUE@ rates.$(OBJEXT) \
@WANT_PART_FALSE@@WANT_PHYCONT_FALSE@@WANT_PHYTIME_FALSE@@WANT_TIPORDER_TRUE@ spr.$(OBJEXT) \
@WANT_PART_FALSE@@WANT_PHYCONT_FALSE@@WANT_PHYTIME_FALSE@@WANT_TIPORDER_TRUE@ m4.$(OBJEXT) \
@WANT_PART_FALSE@@WANT_PHYCONT_FALSE@@WANT_PHYTIME_FALSE@@WANT_TIPORDER_TRUE@ draw.$(OBJEXT) \
@WANT_PART_FALSE@@WANT_PHYCONT_FALSE@@WANT_PHYTIME_FALSE@@WANT_TIPORDER_TRUE@ stats.$(OBJEXT) \
@WANT_PART_FALSE@@WANT_PHYCONT_FALSE@@WANT_PHYTIME_FALSE@@WANT_TIPORDER_TRUE@ tiporder.$(OBJEXT)
tiporder_OBJECTS = $(am_tiporder_OBJECTS)
tiporder_DEPENDENCIES =
DEFAULT_INCLUDES = -I.@am__isrc@ -I$(top_builddir)
depcomp = $(SHELL) $(top_srcdir)/depcomp
am__depfiles_maybe = depfiles
am__mv = mv -f
COMPILE = $(CC) $(DEFS) $(DEFAULT_INCLUDES) $(INCLUDES) $(AM_CPPFLAGS) \
$(CPPFLAGS) $(AM_CFLAGS) $(CFLAGS)
AM_V_CC = $(am__v_CC_$(V))
am__v_CC_ = $(am__v_CC_$(AM_DEFAULT_VERBOSITY))
am__v_CC_0 = @echo " CC " $@;
AM_V_at = $(am__v_at_$(V))
am__v_at_ = $(am__v_at_$(AM_DEFAULT_VERBOSITY))
am__v_at_0 = @
CCLD = $(CC)
LINK = $(CCLD) $(AM_CFLAGS) $(CFLAGS) $(AM_LDFLAGS) $(LDFLAGS) -o $@
AM_V_CCLD = $(am__v_CCLD_$(V))
am__v_CCLD_ = $(am__v_CCLD_$(AM_DEFAULT_VERBOSITY))
am__v_CCLD_0 = @echo " CCLD " $@;
AM_V_GEN = $(am__v_GEN_$(V))
am__v_GEN_ = $(am__v_GEN_$(AM_DEFAULT_VERBOSITY))
am__v_GEN_0 = @echo " GEN " $@;
SOURCES = $(m4_SOURCES) $(part_SOURCES) $(phycont_SOURCES) \
$(phyml_SOURCES) $(phyml_mpi_SOURCES) $(phytime_SOURCES) \
$(rf_SOURCES) $(test_SOURCES) $(tiporder_SOURCES)
DIST_SOURCES = $(am__m4_SOURCES_DIST) $(am__part_SOURCES_DIST) \
$(am__phycont_SOURCES_DIST) $(am__phyml_SOURCES_DIST) \
$(am__phyml_mpi_SOURCES_DIST) $(am__phytime_SOURCES_DIST) \
$(am__rf_SOURCES_DIST) $(am__test_SOURCES_DIST) \
$(am__tiporder_SOURCES_DIST)
ETAGS = etags
CTAGS = ctags
DISTFILES = $(DIST_COMMON) $(DIST_SOURCES) $(TEXINFOS) $(EXTRA_DIST)
ACLOCAL = @ACLOCAL@
AMTAR = @AMTAR@
AM_DEFAULT_VERBOSITY = @AM_DEFAULT_VERBOSITY@
AUTOCONF = @AUTOCONF@
AUTOHEADER = @AUTOHEADER@
AUTOMAKE = @AUTOMAKE@
AWK = @AWK@
CC = @CC@
CCDEPMODE = @CCDEPMODE@
CFLAGS = @CFLAGS@
CPP = @CPP@
CPPFLAGS = @CPPFLAGS@
CYGPATH_W = @CYGPATH_W@
DEFS = $(REVISION)
DEPDIR = @DEPDIR@
ECHO_C = @ECHO_C@
ECHO_N = @ECHO_N@
ECHO_T = @ECHO_T@
EGREP = @EGREP@
EXEEXT = @EXEEXT@
GREP = @GREP@
INSTALL = @INSTALL@
INSTALL_DATA = @INSTALL_DATA@
INSTALL_PROGRAM = @INSTALL_PROGRAM@
INSTALL_SCRIPT = @INSTALL_SCRIPT@
INSTALL_STRIP_PROGRAM = @INSTALL_STRIP_PROGRAM@
LDFLAGS = @LDFLAGS@
LIBOBJS = @LIBOBJS@
LIBS = @LIBS@
LTLIBOBJS = @LTLIBOBJS@
MAKEINFO = @MAKEINFO@
MKDIR_P = @MKDIR_P@
OBJEXT = @OBJEXT@
PACKAGE = @PACKAGE@
PACKAGE_BUGREPORT = @PACKAGE_BUGREPORT@
PACKAGE_NAME = @PACKAGE_NAME@
PACKAGE_STRING = @PACKAGE_STRING@
PACKAGE_TARNAME = @PACKAGE_TARNAME@
PACKAGE_URL = @PACKAGE_URL@
PACKAGE_VERSION = @PACKAGE_VERSION@
PATH_SEPARATOR = @PATH_SEPARATOR@
SET_MAKE = @SET_MAKE@
SHELL = @SHELL@
STRIP = @STRIP@
VERSION = @VERSION@
abs_builddir = @abs_builddir@
abs_srcdir = @abs_srcdir@
abs_top_builddir = @abs_top_builddir@
abs_top_srcdir = @abs_top_srcdir@
ac_ct_CC = @ac_ct_CC@
am__include = @am__include@
am__leading_dot = @am__leading_dot@
am__quote = @am__quote@
am__tar = @am__tar@
am__untar = @am__untar@
bindir = @bindir@
build = @build@
build_alias = @build_alias@
build_cpu = @build_cpu@
build_os = @build_os@
build_vendor = @build_vendor@
builddir = @builddir@
datadir = @datadir@
datarootdir = @datarootdir@
docdir = @docdir@
dvidir = @dvidir@
exec_prefix = @exec_prefix@
host = @host@
host_alias = @host_alias@
host_cpu = @host_cpu@
host_os = @host_os@
host_vendor = @host_vendor@
htmldir = @htmldir@
includedir = @includedir@
infodir = @infodir@
install_sh = @install_sh@
libdir = @libdir@
libexecdir = @libexecdir@
localedir = @localedir@
localstatedir = @localstatedir@
mandir = @mandir@
mkdir_p = @mkdir_p@
oldincludedir = @oldincludedir@
pdfdir = @pdfdir@
prefix = @prefix@
program_transform_name = @program_transform_name@
psdir = @psdir@
sbindir = @sbindir@
sharedstatedir = @sharedstatedir@
srcdir = @srcdir@
sysconfdir = @sysconfdir@
target_alias = @target_alias@
top_build_prefix = @top_build_prefix@
top_builddir = @top_builddir@
top_srcdir = @top_srcdir@
@WANT_M4_FALSE@@WANT_MPI_FALSE@@WANT_PART_FALSE@@WANT_PHYCONT_FALSE@@WANT_PHYTIME_FALSE@@WANT_RF_FALSE@@WANT_RWRAP_FALSE@@WANT_TEST_FALSE@@WANT_TIPORDER_FALSE@PROG = PHYML
@WANT_M4_FALSE@@WANT_MPI_FALSE@@WANT_PART_FALSE@@WANT_PHYCONT_FALSE@@WANT_PHYTIME_FALSE@@WANT_RF_FALSE@@WANT_RWRAP_FALSE@@WANT_TEST_TRUE@@WANT_TIPORDER_FALSE@PROG = TEST
@WANT_M4_FALSE@@WANT_MPI_TRUE@@WANT_PART_FALSE@@WANT_PHYCONT_FALSE@@WANT_PHYTIME_FALSE@@WANT_RF_FALSE@@WANT_RWRAP_FALSE@@WANT_TIPORDER_FALSE@PROG = PHYML
@WANT_M4_FALSE@@WANT_PART_FALSE@@WANT_PHYCONT_FALSE@@WANT_PHYTIME_FALSE@@WANT_RF_TRUE@@WANT_RWRAP_FALSE@@WANT_TIPORDER_FALSE@PROG = RF
@WANT_M4_TRUE@@WANT_PART_FALSE@@WANT_PHYCONT_FALSE@@WANT_PHYTIME_FALSE@@WANT_RWRAP_FALSE@@WANT_TIPORDER_FALSE@PROG = M4
@WANT_PART_FALSE@@WANT_PHYCONT_FALSE@@WANT_PHYTIME_FALSE@@WANT_RWRAP_FALSE@@WANT_TIPORDER_TRUE@PROG = TIPORDER
@WANT_PART_FALSE@@WANT_PHYCONT_FALSE@@WANT_PHYTIME_FALSE@@WANT_RWRAP_TRUE@PROG = RWRAP
@WANT_PART_TRUE@@WANT_PHYCONT_FALSE@@WANT_PHYTIME_FALSE@PROG = PART
@WANT_PHYCONT_TRUE@@WANT_PHYTIME_FALSE@PROG = PHYCONT
@WANT_PHYTIME_TRUE@PROG = PHYTIME
@WANT_PHYTIME_TRUE@phytime_SOURCES = main.c \
@WANT_PHYTIME_TRUE@utilities.c utilities.h\
@WANT_PHYTIME_TRUE@optimiz.c optimiz.h\
@WANT_PHYTIME_TRUE@lk.c lk.h\
@WANT_PHYTIME_TRUE@bionj.c bionj.h\
@WANT_PHYTIME_TRUE@models.c models.h\
@WANT_PHYTIME_TRUE@free.c free.h\
@WANT_PHYTIME_TRUE@help.c help.h\
@WANT_PHYTIME_TRUE@simu.c simu.h\
@WANT_PHYTIME_TRUE@eigen.c eigen.h\
@WANT_PHYTIME_TRUE@pars.c pars.h\
@WANT_PHYTIME_TRUE@alrt.c alrt.h\
@WANT_PHYTIME_TRUE@interface.c interface.h\
@WANT_PHYTIME_TRUE@cl.c cl.h\
@WANT_PHYTIME_TRUE@spr.c spr.h\
@WANT_PHYTIME_TRUE@times.c times.h\
@WANT_PHYTIME_TRUE@m4.c m4.h\
@WANT_PHYTIME_TRUE@draw.c draw.h\
@WANT_PHYTIME_TRUE@rates.c rates.h\
@WANT_PHYTIME_TRUE@mcmc.c mcmc.h\
@WANT_PHYTIME_TRUE@stats.c stats.h\
@WANT_PHYTIME_TRUE@mg.c mg.h\
@WANT_PHYTIME_TRUE@tiporder.c tiporder.h
@WANT_PHYTIME_TRUE@phytime_LDADD = -lm
@WANT_PHYCONT_TRUE@@WANT_PHYTIME_FALSE@phycont_SOURCES = main.c \
@WANT_PHYCONT_TRUE@@WANT_PHYTIME_FALSE@utilities.c utilities.h\
@WANT_PHYCONT_TRUE@@WANT_PHYTIME_FALSE@optimiz.c optimiz.h\
@WANT_PHYCONT_TRUE@@WANT_PHYTIME_FALSE@lk.c lk.h\
@WANT_PHYCONT_TRUE@@WANT_PHYTIME_FALSE@bionj.c bionj.h\
@WANT_PHYCONT_TRUE@@WANT_PHYTIME_FALSE@models.c models.h\
@WANT_PHYCONT_TRUE@@WANT_PHYTIME_FALSE@free.c free.h\
@WANT_PHYCONT_TRUE@@WANT_PHYTIME_FALSE@help.c help.h\
@WANT_PHYCONT_TRUE@@WANT_PHYTIME_FALSE@simu.c simu.h\
@WANT_PHYCONT_TRUE@@WANT_PHYTIME_FALSE@eigen.c eigen.h\
@WANT_PHYCONT_TRUE@@WANT_PHYTIME_FALSE@pars.c pars.h\
@WANT_PHYCONT_TRUE@@WANT_PHYTIME_FALSE@alrt.c alrt.h\
@WANT_PHYCONT_TRUE@@WANT_PHYTIME_FALSE@interface.c interface.h\
@WANT_PHYCONT_TRUE@@WANT_PHYTIME_FALSE@cl.c cl.h\
@WANT_PHYCONT_TRUE@@WANT_PHYTIME_FALSE@spr.c spr.h\
@WANT_PHYCONT_TRUE@@WANT_PHYTIME_FALSE@times.c times.h\
@WANT_PHYCONT_TRUE@@WANT_PHYTIME_FALSE@m4.c m4.h\
@WANT_PHYCONT_TRUE@@WANT_PHYTIME_FALSE@draw.c draw.h\
@WANT_PHYCONT_TRUE@@WANT_PHYTIME_FALSE@rates.c rates.h\
@WANT_PHYCONT_TRUE@@WANT_PHYTIME_FALSE@mcmc.c mcmc.h\
@WANT_PHYCONT_TRUE@@WANT_PHYTIME_FALSE@stats.c stats.h\
@WANT_PHYCONT_TRUE@@WANT_PHYTIME_FALSE@mg.c mg.h\
@WANT_PHYCONT_TRUE@@WANT_PHYTIME_FALSE@tiporder.c tiporder.h
# continuous.c continuous.h
@WANT_PHYCONT_TRUE@@WANT_PHYTIME_FALSE@phycont_LDADD = -lm
# if WANT_RWRAP
# lib_LTLIBRARIES = librwrap.la
# librwrap_la_SOURCES = main.c \
# utilities.c utilities.h\
# optimiz.c optimiz.h\
# lk.c lk.h\
# bionj.c bionj.h\
# models.c models.h\
# free.c free.h\
# help.c help.h\
# simu.c simu.h\
# eigen.c eigen.h\
# pars.c pars.h\
# alrt.c alrt.h\
# interface.c interface.h\
# cl.c cl.h\
# mg.c mg.h\
# spr.c spr.h\
# m4.c m4.h\
# draw.c draw.h\
# mcmc.c mcmc.h\
# stats.c stats.h\
# times.c times.h\
# tiporder.c tiporder.h\
# rates.c rates.h\
# rwrapper.c rwrapper.h
# librwrap_la_LIBADD = -lm
# librwrap_la_LDFLAGS = -I/Library/Frameworks/R.framework/Resources/include -I/Library/Frameworks/R.framework/Resources/include/i386 -I/usr/local/include -flat_namespace -undefined suppress -shared -module
# librwrap_la_CFLAGS=-std=gnu99 -fPIC
# else
@WANT_PART_TRUE@@WANT_PHYCONT_FALSE@@WANT_PHYTIME_FALSE@part_SOURCES = main.c \
@WANT_PART_TRUE@@WANT_PHYCONT_FALSE@@WANT_PHYTIME_FALSE@utilities.c utilities.h\
@WANT_PART_TRUE@@WANT_PHYCONT_FALSE@@WANT_PHYTIME_FALSE@optimiz.c optimiz.h\
@WANT_PART_TRUE@@WANT_PHYCONT_FALSE@@WANT_PHYTIME_FALSE@lk.c lk.h\
@WANT_PART_TRUE@@WANT_PHYCONT_FALSE@@WANT_PHYTIME_FALSE@bionj.c bionj.h\
@WANT_PART_TRUE@@WANT_PHYCONT_FALSE@@WANT_PHYTIME_FALSE@models.c models.h\
@WANT_PART_TRUE@@WANT_PHYCONT_FALSE@@WANT_PHYTIME_FALSE@free.c free.h\
@WANT_PART_TRUE@@WANT_PHYCONT_FALSE@@WANT_PHYTIME_FALSE@help.c help.h\
@WANT_PART_TRUE@@WANT_PHYCONT_FALSE@@WANT_PHYTIME_FALSE@simu.c simu.h\
@WANT_PART_TRUE@@WANT_PHYCONT_FALSE@@WANT_PHYTIME_FALSE@eigen.c eigen.h\
@WANT_PART_TRUE@@WANT_PHYCONT_FALSE@@WANT_PHYTIME_FALSE@pars.c pars.h\
@WANT_PART_TRUE@@WANT_PHYCONT_FALSE@@WANT_PHYTIME_FALSE@alrt.c alrt.h\
@WANT_PART_TRUE@@WANT_PHYCONT_FALSE@@WANT_PHYTIME_FALSE@interface.c interface.h\
@WANT_PART_TRUE@@WANT_PHYCONT_FALSE@@WANT_PHYTIME_FALSE@cl.c cl.h\
@WANT_PART_TRUE@@WANT_PHYCONT_FALSE@@WANT_PHYTIME_FALSE@mg.c mg.h\
@WANT_PART_TRUE@@WANT_PHYCONT_FALSE@@WANT_PHYTIME_FALSE@spr.c spr.h\
@WANT_PART_TRUE@@WANT_PHYCONT_FALSE@@WANT_PHYTIME_FALSE@m4.c m4.h\
@WANT_PART_TRUE@@WANT_PHYCONT_FALSE@@WANT_PHYTIME_FALSE@draw.c draw.h\
@WANT_PART_TRUE@@WANT_PHYCONT_FALSE@@WANT_PHYTIME_FALSE@stats.c stats.h\
@WANT_PART_TRUE@@WANT_PHYCONT_FALSE@@WANT_PHYTIME_FALSE@tiporder.c tiporder.h
@WANT_PART_TRUE@@WANT_PHYCONT_FALSE@@WANT_PHYTIME_FALSE@part_LDADD = -lm
@WANT_PART_FALSE@@WANT_PHYCONT_FALSE@@WANT_PHYTIME_FALSE@@WANT_TIPORDER_TRUE@tiporder_SOURCES = main.c \
@WANT_PART_FALSE@@WANT_PHYCONT_FALSE@@WANT_PHYTIME_FALSE@@WANT_TIPORDER_TRUE@utilities.c utilities.h\
@WANT_PART_FALSE@@WANT_PHYCONT_FALSE@@WANT_PHYTIME_FALSE@@WANT_TIPORDER_TRUE@optimiz.c optimiz.h\
@WANT_PART_FALSE@@WANT_PHYCONT_FALSE@@WANT_PHYTIME_FALSE@@WANT_TIPORDER_TRUE@lk.c lk.h\
@WANT_PART_FALSE@@WANT_PHYCONT_FALSE@@WANT_PHYTIME_FALSE@@WANT_TIPORDER_TRUE@bionj.c bionj.h\
@WANT_PART_FALSE@@WANT_PHYCONT_FALSE@@WANT_PHYTIME_FALSE@@WANT_TIPORDER_TRUE@models.c models.h\
@WANT_PART_FALSE@@WANT_PHYCONT_FALSE@@WANT_PHYTIME_FALSE@@WANT_TIPORDER_TRUE@free.c free.h\
@WANT_PART_FALSE@@WANT_PHYCONT_FALSE@@WANT_PHYTIME_FALSE@@WANT_TIPORDER_TRUE@help.c help.h\
@WANT_PART_FALSE@@WANT_PHYCONT_FALSE@@WANT_PHYTIME_FALSE@@WANT_TIPORDER_TRUE@simu.c simu.h\
@WANT_PART_FALSE@@WANT_PHYCONT_FALSE@@WANT_PHYTIME_FALSE@@WANT_TIPORDER_TRUE@eigen.c eigen.h\
@WANT_PART_FALSE@@WANT_PHYCONT_FALSE@@WANT_PHYTIME_FALSE@@WANT_TIPORDER_TRUE@pars.c pars.h\
@WANT_PART_FALSE@@WANT_PHYCONT_FALSE@@WANT_PHYTIME_FALSE@@WANT_TIPORDER_TRUE@alrt.c alrt.h\
@WANT_PART_FALSE@@WANT_PHYCONT_FALSE@@WANT_PHYTIME_FALSE@@WANT_TIPORDER_TRUE@interface.c interface.h\
@WANT_PART_FALSE@@WANT_PHYCONT_FALSE@@WANT_PHYTIME_FALSE@@WANT_TIPORDER_TRUE@cl.c cl.h\
@WANT_PART_FALSE@@WANT_PHYCONT_FALSE@@WANT_PHYTIME_FALSE@@WANT_TIPORDER_TRUE@mg.c mg.h\
@WANT_PART_FALSE@@WANT_PHYCONT_FALSE@@WANT_PHYTIME_FALSE@@WANT_TIPORDER_TRUE@times.c times.h\
@WANT_PART_FALSE@@WANT_PHYCONT_FALSE@@WANT_PHYTIME_FALSE@@WANT_TIPORDER_TRUE@mcmc.c mcmc.h\
@WANT_PART_FALSE@@WANT_PHYCONT_FALSE@@WANT_PHYTIME_FALSE@@WANT_TIPORDER_TRUE@rates.c rates.h\
@WANT_PART_FALSE@@WANT_PHYCONT_FALSE@@WANT_PHYTIME_FALSE@@WANT_TIPORDER_TRUE@spr.c spr.h\
@WANT_PART_FALSE@@WANT_PHYCONT_FALSE@@WANT_PHYTIME_FALSE@@WANT_TIPORDER_TRUE@m4.c m4.h\
@WANT_PART_FALSE@@WANT_PHYCONT_FALSE@@WANT_PHYTIME_FALSE@@WANT_TIPORDER_TRUE@draw.c draw.h\
@WANT_PART_FALSE@@WANT_PHYCONT_FALSE@@WANT_PHYTIME_FALSE@@WANT_TIPORDER_TRUE@stats.c stats.h\
@WANT_PART_FALSE@@WANT_PHYCONT_FALSE@@WANT_PHYTIME_FALSE@@WANT_TIPORDER_TRUE@tiporder.c tiporder.h
@WANT_PART_FALSE@@WANT_PHYCONT_FALSE@@WANT_PHYTIME_FALSE@@WANT_TIPORDER_TRUE@tiporder_LDADD = -lm
@WANT_M4_TRUE@@WANT_PART_FALSE@@WANT_PHYCONT_FALSE@@WANT_PHYTIME_FALSE@@WANT_TIPORDER_FALSE@m4_SOURCES = main.c \
@WANT_M4_TRUE@@WANT_PART_FALSE@@WANT_PHYCONT_FALSE@@WANT_PHYTIME_FALSE@@WANT_TIPORDER_FALSE@utilities.c utilities.h\
@WANT_M4_TRUE@@WANT_PART_FALSE@@WANT_PHYCONT_FALSE@@WANT_PHYTIME_FALSE@@WANT_TIPORDER_FALSE@optimiz.c optimiz.h\
@WANT_M4_TRUE@@WANT_PART_FALSE@@WANT_PHYCONT_FALSE@@WANT_PHYTIME_FALSE@@WANT_TIPORDER_FALSE@lk.c lk.h\
@WANT_M4_TRUE@@WANT_PART_FALSE@@WANT_PHYCONT_FALSE@@WANT_PHYTIME_FALSE@@WANT_TIPORDER_FALSE@bionj.c bionj.h\
@WANT_M4_TRUE@@WANT_PART_FALSE@@WANT_PHYCONT_FALSE@@WANT_PHYTIME_FALSE@@WANT_TIPORDER_FALSE@models.c models.h\
@WANT_M4_TRUE@@WANT_PART_FALSE@@WANT_PHYCONT_FALSE@@WANT_PHYTIME_FALSE@@WANT_TIPORDER_FALSE@free.c free.h\
@WANT_M4_TRUE@@WANT_PART_FALSE@@WANT_PHYCONT_FALSE@@WANT_PHYTIME_FALSE@@WANT_TIPORDER_FALSE@help.c help.h\
@WANT_M4_TRUE@@WANT_PART_FALSE@@WANT_PHYCONT_FALSE@@WANT_PHYTIME_FALSE@@WANT_TIPORDER_FALSE@simu.c simu.h\
@WANT_M4_TRUE@@WANT_PART_FALSE@@WANT_PHYCONT_FALSE@@WANT_PHYTIME_FALSE@@WANT_TIPORDER_FALSE@eigen.c eigen.h\
@WANT_M4_TRUE@@WANT_PART_FALSE@@WANT_PHYCONT_FALSE@@WANT_PHYTIME_FALSE@@WANT_TIPORDER_FALSE@pars.c pars.h\
@WANT_M4_TRUE@@WANT_PART_FALSE@@WANT_PHYCONT_FALSE@@WANT_PHYTIME_FALSE@@WANT_TIPORDER_FALSE@alrt.c alrt.h\
@WANT_M4_TRUE@@WANT_PART_FALSE@@WANT_PHYCONT_FALSE@@WANT_PHYTIME_FALSE@@WANT_TIPORDER_FALSE@interface.c interface.h\
@WANT_M4_TRUE@@WANT_PART_FALSE@@WANT_PHYCONT_FALSE@@WANT_PHYTIME_FALSE@@WANT_TIPORDER_FALSE@cl.c cl.h\
@WANT_M4_TRUE@@WANT_PART_FALSE@@WANT_PHYCONT_FALSE@@WANT_PHYTIME_FALSE@@WANT_TIPORDER_FALSE@mg.c mg.h\
@WANT_M4_TRUE@@WANT_PART_FALSE@@WANT_PHYCONT_FALSE@@WANT_PHYTIME_FALSE@@WANT_TIPORDER_FALSE@times.c times.h\
@WANT_M4_TRUE@@WANT_PART_FALSE@@WANT_PHYCONT_FALSE@@WANT_PHYTIME_FALSE@@WANT_TIPORDER_FALSE@mcmc.c mcmc.h\
@WANT_M4_TRUE@@WANT_PART_FALSE@@WANT_PHYCONT_FALSE@@WANT_PHYTIME_FALSE@@WANT_TIPORDER_FALSE@rates.c rates.h\
@WANT_M4_TRUE@@WANT_PART_FALSE@@WANT_PHYCONT_FALSE@@WANT_PHYTIME_FALSE@@WANT_TIPORDER_FALSE@spr.c spr.h\
@WANT_M4_TRUE@@WANT_PART_FALSE@@WANT_PHYCONT_FALSE@@WANT_PHYTIME_FALSE@@WANT_TIPORDER_FALSE@draw.c draw.h\
@WANT_M4_TRUE@@WANT_PART_FALSE@@WANT_PHYCONT_FALSE@@WANT_PHYTIME_FALSE@@WANT_TIPORDER_FALSE@stats.c stats.h\
@WANT_M4_TRUE@@WANT_PART_FALSE@@WANT_PHYCONT_FALSE@@WANT_PHYTIME_FALSE@@WANT_TIPORDER_FALSE@tiporder.c tiporder.h\
@WANT_M4_TRUE@@WANT_PART_FALSE@@WANT_PHYCONT_FALSE@@WANT_PHYTIME_FALSE@@WANT_TIPORDER_FALSE@m4.c m4.h
@WANT_M4_TRUE@@WANT_PART_FALSE@@WANT_PHYCONT_FALSE@@WANT_PHYTIME_FALSE@@WANT_TIPORDER_FALSE@m4_LDADD = -lm
@WANT_M4_FALSE@@WANT_PART_FALSE@@WANT_PHYCONT_FALSE@@WANT_PHYTIME_FALSE@@WANT_RF_TRUE@@WANT_TIPORDER_FALSE@rf_SOURCES = main.c \
@WANT_M4_FALSE@@WANT_PART_FALSE@@WANT_PHYCONT_FALSE@@WANT_PHYTIME_FALSE@@WANT_RF_TRUE@@WANT_TIPORDER_FALSE@utilities.c utilities.h\
@WANT_M4_FALSE@@WANT_PART_FALSE@@WANT_PHYCONT_FALSE@@WANT_PHYTIME_FALSE@@WANT_RF_TRUE@@WANT_TIPORDER_FALSE@optimiz.c optimiz.h\
@WANT_M4_FALSE@@WANT_PART_FALSE@@WANT_PHYCONT_FALSE@@WANT_PHYTIME_FALSE@@WANT_RF_TRUE@@WANT_TIPORDER_FALSE@lk.c lk.h\
@WANT_M4_FALSE@@WANT_PART_FALSE@@WANT_PHYCONT_FALSE@@WANT_PHYTIME_FALSE@@WANT_RF_TRUE@@WANT_TIPORDER_FALSE@bionj.c bionj.h\
@WANT_M4_FALSE@@WANT_PART_FALSE@@WANT_PHYCONT_FALSE@@WANT_PHYTIME_FALSE@@WANT_RF_TRUE@@WANT_TIPORDER_FALSE@models.c models.h\
@WANT_M4_FALSE@@WANT_PART_FALSE@@WANT_PHYCONT_FALSE@@WANT_PHYTIME_FALSE@@WANT_RF_TRUE@@WANT_TIPORDER_FALSE@free.c free.h\
@WANT_M4_FALSE@@WANT_PART_FALSE@@WANT_PHYCONT_FALSE@@WANT_PHYTIME_FALSE@@WANT_RF_TRUE@@WANT_TIPORDER_FALSE@help.c help.h\
@WANT_M4_FALSE@@WANT_PART_FALSE@@WANT_PHYCONT_FALSE@@WANT_PHYTIME_FALSE@@WANT_RF_TRUE@@WANT_TIPORDER_FALSE@simu.c simu.h\
@WANT_M4_FALSE@@WANT_PART_FALSE@@WANT_PHYCONT_FALSE@@WANT_PHYTIME_FALSE@@WANT_RF_TRUE@@WANT_TIPORDER_FALSE@eigen.c eigen.h\
@WANT_M4_FALSE@@WANT_PART_FALSE@@WANT_PHYCONT_FALSE@@WANT_PHYTIME_FALSE@@WANT_RF_TRUE@@WANT_TIPORDER_FALSE@pars.c pars.h\
@WANT_M4_FALSE@@WANT_PART_FALSE@@WANT_PHYCONT_FALSE@@WANT_PHYTIME_FALSE@@WANT_RF_TRUE@@WANT_TIPORDER_FALSE@alrt.c alrt.h\
@WANT_M4_FALSE@@WANT_PART_FALSE@@WANT_PHYCONT_FALSE@@WANT_PHYTIME_FALSE@@WANT_RF_TRUE@@WANT_TIPORDER_FALSE@interface.c interface.h\
@WANT_M4_FALSE@@WANT_PART_FALSE@@WANT_PHYCONT_FALSE@@WANT_PHYTIME_FALSE@@WANT_RF_TRUE@@WANT_TIPORDER_FALSE@cl.c cl.h\
@WANT_M4_FALSE@@WANT_PART_FALSE@@WANT_PHYCONT_FALSE@@WANT_PHYTIME_FALSE@@WANT_RF_TRUE@@WANT_TIPORDER_FALSE@mg.c mg.h\
@WANT_M4_FALSE@@WANT_PART_FALSE@@WANT_PHYCONT_FALSE@@WANT_PHYTIME_FALSE@@WANT_RF_TRUE@@WANT_TIPORDER_FALSE@times.c times.h\
@WANT_M4_FALSE@@WANT_PART_FALSE@@WANT_PHYCONT_FALSE@@WANT_PHYTIME_FALSE@@WANT_RF_TRUE@@WANT_TIPORDER_FALSE@mcmc.c mcmc.h\
@WANT_M4_FALSE@@WANT_PART_FALSE@@WANT_PHYCONT_FALSE@@WANT_PHYTIME_FALSE@@WANT_RF_TRUE@@WANT_TIPORDER_FALSE@rates.c rates.h\
@WANT_M4_FALSE@@WANT_PART_FALSE@@WANT_PHYCONT_FALSE@@WANT_PHYTIME_FALSE@@WANT_RF_TRUE@@WANT_TIPORDER_FALSE@spr.c spr.h\
@WANT_M4_FALSE@@WANT_PART_FALSE@@WANT_PHYCONT_FALSE@@WANT_PHYTIME_FALSE@@WANT_RF_TRUE@@WANT_TIPORDER_FALSE@draw.c draw.h\
@WANT_M4_FALSE@@WANT_PART_FALSE@@WANT_PHYCONT_FALSE@@WANT_PHYTIME_FALSE@@WANT_RF_TRUE@@WANT_TIPORDER_FALSE@stats.c stats.h\
@WANT_M4_FALSE@@WANT_PART_FALSE@@WANT_PHYCONT_FALSE@@WANT_PHYTIME_FALSE@@WANT_RF_TRUE@@WANT_TIPORDER_FALSE@tiporder.c tiporder.h\
@WANT_M4_FALSE@@WANT_PART_FALSE@@WANT_PHYCONT_FALSE@@WANT_PHYTIME_FALSE@@WANT_RF_TRUE@@WANT_TIPORDER_FALSE@m4.c m4.h
@WANT_M4_FALSE@@WANT_PART_FALSE@@WANT_PHYCONT_FALSE@@WANT_PHYTIME_FALSE@@WANT_RF_TRUE@@WANT_TIPORDER_FALSE@rf_LDADD = -lm
@WANT_M4_FALSE@@WANT_MPI_TRUE@@WANT_PART_FALSE@@WANT_PHYCONT_FALSE@@WANT_PHYTIME_FALSE@@WANT_RF_FALSE@@WANT_TIPORDER_FALSE@phyml_mpi_SOURCES = main.c \
@WANT_M4_FALSE@@WANT_MPI_TRUE@@WANT_PART_FALSE@@WANT_PHYCONT_FALSE@@WANT_PHYTIME_FALSE@@WANT_RF_FALSE@@WANT_TIPORDER_FALSE@utilities.c utilities.h\
@WANT_M4_FALSE@@WANT_MPI_TRUE@@WANT_PART_FALSE@@WANT_PHYCONT_FALSE@@WANT_PHYTIME_FALSE@@WANT_RF_FALSE@@WANT_TIPORDER_FALSE@optimiz.c optimiz.h\
@WANT_M4_FALSE@@WANT_MPI_TRUE@@WANT_PART_FALSE@@WANT_PHYCONT_FALSE@@WANT_PHYTIME_FALSE@@WANT_RF_FALSE@@WANT_TIPORDER_FALSE@lk.c lk.h\
@WANT_M4_FALSE@@WANT_MPI_TRUE@@WANT_PART_FALSE@@WANT_PHYCONT_FALSE@@WANT_PHYTIME_FALSE@@WANT_RF_FALSE@@WANT_TIPORDER_FALSE@bionj.c bionj.h\
@WANT_M4_FALSE@@WANT_MPI_TRUE@@WANT_PART_FALSE@@WANT_PHYCONT_FALSE@@WANT_PHYTIME_FALSE@@WANT_RF_FALSE@@WANT_TIPORDER_FALSE@models.c models.h\
@WANT_M4_FALSE@@WANT_MPI_TRUE@@WANT_PART_FALSE@@WANT_PHYCONT_FALSE@@WANT_PHYTIME_FALSE@@WANT_RF_FALSE@@WANT_TIPORDER_FALSE@free.c free.h\
@WANT_M4_FALSE@@WANT_MPI_TRUE@@WANT_PART_FALSE@@WANT_PHYCONT_FALSE@@WANT_PHYTIME_FALSE@@WANT_RF_FALSE@@WANT_TIPORDER_FALSE@help.c help.h\
@WANT_M4_FALSE@@WANT_MPI_TRUE@@WANT_PART_FALSE@@WANT_PHYCONT_FALSE@@WANT_PHYTIME_FALSE@@WANT_RF_FALSE@@WANT_TIPORDER_FALSE@simu.c simu.h\
@WANT_M4_FALSE@@WANT_MPI_TRUE@@WANT_PART_FALSE@@WANT_PHYCONT_FALSE@@WANT_PHYTIME_FALSE@@WANT_RF_FALSE@@WANT_TIPORDER_FALSE@eigen.c eigen.h\
@WANT_M4_FALSE@@WANT_MPI_TRUE@@WANT_PART_FALSE@@WANT_PHYCONT_FALSE@@WANT_PHYTIME_FALSE@@WANT_RF_FALSE@@WANT_TIPORDER_FALSE@pars.c pars.h\
@WANT_M4_FALSE@@WANT_MPI_TRUE@@WANT_PART_FALSE@@WANT_PHYCONT_FALSE@@WANT_PHYTIME_FALSE@@WANT_RF_FALSE@@WANT_TIPORDER_FALSE@alrt.c alrt.h\
@WANT_M4_FALSE@@WANT_MPI_TRUE@@WANT_PART_FALSE@@WANT_PHYCONT_FALSE@@WANT_PHYTIME_FALSE@@WANT_RF_FALSE@@WANT_TIPORDER_FALSE@interface.c interface.h\
@WANT_M4_FALSE@@WANT_MPI_TRUE@@WANT_PART_FALSE@@WANT_PHYCONT_FALSE@@WANT_PHYTIME_FALSE@@WANT_RF_FALSE@@WANT_TIPORDER_FALSE@cl.c cl.h\
@WANT_M4_FALSE@@WANT_MPI_TRUE@@WANT_PART_FALSE@@WANT_PHYCONT_FALSE@@WANT_PHYTIME_FALSE@@WANT_RF_FALSE@@WANT_TIPORDER_FALSE@spr.c spr.h\
@WANT_M4_FALSE@@WANT_MPI_TRUE@@WANT_PART_FALSE@@WANT_PHYCONT_FALSE@@WANT_PHYTIME_FALSE@@WANT_RF_FALSE@@WANT_TIPORDER_FALSE@draw.c draw.h\
@WANT_M4_FALSE@@WANT_MPI_TRUE@@WANT_PART_FALSE@@WANT_PHYCONT_FALSE@@WANT_PHYTIME_FALSE@@WANT_RF_FALSE@@WANT_TIPORDER_FALSE@mpi_boot.c mpi_boot.h\
@WANT_M4_FALSE@@WANT_MPI_TRUE@@WANT_PART_FALSE@@WANT_PHYCONT_FALSE@@WANT_PHYTIME_FALSE@@WANT_RF_FALSE@@WANT_TIPORDER_FALSE@stats.c stats.h\
@WANT_M4_FALSE@@WANT_MPI_TRUE@@WANT_PART_FALSE@@WANT_PHYCONT_FALSE@@WANT_PHYTIME_FALSE@@WANT_RF_FALSE@@WANT_TIPORDER_FALSE@rates.c rates.h\
@WANT_M4_FALSE@@WANT_MPI_TRUE@@WANT_PART_FALSE@@WANT_PHYCONT_FALSE@@WANT_PHYTIME_FALSE@@WANT_RF_FALSE@@WANT_TIPORDER_FALSE@mcmc.c mcmc.h\
@WANT_M4_FALSE@@WANT_MPI_TRUE@@WANT_PART_FALSE@@WANT_PHYCONT_FALSE@@WANT_PHYTIME_FALSE@@WANT_RF_FALSE@@WANT_TIPORDER_FALSE@times.c times.h\
@WANT_M4_FALSE@@WANT_MPI_TRUE@@WANT_PART_FALSE@@WANT_PHYCONT_FALSE@@WANT_PHYTIME_FALSE@@WANT_RF_FALSE@@WANT_TIPORDER_FALSE@tiporder.c tiporder.h\
@WANT_M4_FALSE@@WANT_MPI_TRUE@@WANT_PART_FALSE@@WANT_PHYCONT_FALSE@@WANT_PHYTIME_FALSE@@WANT_RF_FALSE@@WANT_TIPORDER_FALSE@mg.c mg.h\
@WANT_M4_FALSE@@WANT_MPI_TRUE@@WANT_PART_FALSE@@WANT_PHYCONT_FALSE@@WANT_PHYTIME_FALSE@@WANT_RF_FALSE@@WANT_TIPORDER_FALSE@m4.c m4.h\
@WANT_M4_FALSE@@WANT_MPI_TRUE@@WANT_PART_FALSE@@WANT_PHYCONT_FALSE@@WANT_PHYTIME_FALSE@@WANT_RF_FALSE@@WANT_TIPORDER_FALSE@xml.c xml.h
@WANT_M4_FALSE@@WANT_MPI_TRUE@@WANT_PART_FALSE@@WANT_PHYCONT_FALSE@@WANT_PHYTIME_FALSE@@WANT_RF_FALSE@@WANT_TIPORDER_FALSE@phyml_mpi_LDADD = -lm
@WANT_M4_FALSE@@WANT_MPI_FALSE@@WANT_PART_FALSE@@WANT_PHYCONT_FALSE@@WANT_PHYTIME_FALSE@@WANT_RF_FALSE@@WANT_TEST_TRUE@@WANT_TIPORDER_FALSE@test_SOURCES = main.c \
@WANT_M4_FALSE@@WANT_MPI_FALSE@@WANT_PART_FALSE@@WANT_PHYCONT_FALSE@@WANT_PHYTIME_FALSE@@WANT_RF_FALSE@@WANT_TEST_TRUE@@WANT_TIPORDER_FALSE@utilities.c utilities.h\
@WANT_M4_FALSE@@WANT_MPI_FALSE@@WANT_PART_FALSE@@WANT_PHYCONT_FALSE@@WANT_PHYTIME_FALSE@@WANT_RF_FALSE@@WANT_TEST_TRUE@@WANT_TIPORDER_FALSE@optimiz.c optimiz.h\
@WANT_M4_FALSE@@WANT_MPI_FALSE@@WANT_PART_FALSE@@WANT_PHYCONT_FALSE@@WANT_PHYTIME_FALSE@@WANT_RF_FALSE@@WANT_TEST_TRUE@@WANT_TIPORDER_FALSE@lk.c lk.h\
@WANT_M4_FALSE@@WANT_MPI_FALSE@@WANT_PART_FALSE@@WANT_PHYCONT_FALSE@@WANT_PHYTIME_FALSE@@WANT_RF_FALSE@@WANT_TEST_TRUE@@WANT_TIPORDER_FALSE@bionj.c bionj.h\
@WANT_M4_FALSE@@WANT_MPI_FALSE@@WANT_PART_FALSE@@WANT_PHYCONT_FALSE@@WANT_PHYTIME_FALSE@@WANT_RF_FALSE@@WANT_TEST_TRUE@@WANT_TIPORDER_FALSE@models.c models.h\
@WANT_M4_FALSE@@WANT_MPI_FALSE@@WANT_PART_FALSE@@WANT_PHYCONT_FALSE@@WANT_PHYTIME_FALSE@@WANT_RF_FALSE@@WANT_TEST_TRUE@@WANT_TIPORDER_FALSE@free.c free.h\
@WANT_M4_FALSE@@WANT_MPI_FALSE@@WANT_PART_FALSE@@WANT_PHYCONT_FALSE@@WANT_PHYTIME_FALSE@@WANT_RF_FALSE@@WANT_TEST_TRUE@@WANT_TIPORDER_FALSE@help.c help.h\
@WANT_M4_FALSE@@WANT_MPI_FALSE@@WANT_PART_FALSE@@WANT_PHYCONT_FALSE@@WANT_PHYTIME_FALSE@@WANT_RF_FALSE@@WANT_TEST_TRUE@@WANT_TIPORDER_FALSE@simu.c simu.h\
@WANT_M4_FALSE@@WANT_MPI_FALSE@@WANT_PART_FALSE@@WANT_PHYCONT_FALSE@@WANT_PHYTIME_FALSE@@WANT_RF_FALSE@@WANT_TEST_TRUE@@WANT_TIPORDER_FALSE@eigen.c eigen.h\
@WANT_M4_FALSE@@WANT_MPI_FALSE@@WANT_PART_FALSE@@WANT_PHYCONT_FALSE@@WANT_PHYTIME_FALSE@@WANT_RF_FALSE@@WANT_TEST_TRUE@@WANT_TIPORDER_FALSE@pars.c pars.h\
@WANT_M4_FALSE@@WANT_MPI_FALSE@@WANT_PART_FALSE@@WANT_PHYCONT_FALSE@@WANT_PHYTIME_FALSE@@WANT_RF_FALSE@@WANT_TEST_TRUE@@WANT_TIPORDER_FALSE@alrt.c alrt.h\
@WANT_M4_FALSE@@WANT_MPI_FALSE@@WANT_PART_FALSE@@WANT_PHYCONT_FALSE@@WANT_PHYTIME_FALSE@@WANT_RF_FALSE@@WANT_TEST_TRUE@@WANT_TIPORDER_FALSE@interface.c interface.h\
@WANT_M4_FALSE@@WANT_MPI_FALSE@@WANT_PART_FALSE@@WANT_PHYCONT_FALSE@@WANT_PHYTIME_FALSE@@WANT_RF_FALSE@@WANT_TEST_TRUE@@WANT_TIPORDER_FALSE@cl.c cl.h\
@WANT_M4_FALSE@@WANT_MPI_FALSE@@WANT_PART_FALSE@@WANT_PHYCONT_FALSE@@WANT_PHYTIME_FALSE@@WANT_RF_FALSE@@WANT_TEST_TRUE@@WANT_TIPORDER_FALSE@spr.c spr.h\
@WANT_M4_FALSE@@WANT_MPI_FALSE@@WANT_PART_FALSE@@WANT_PHYCONT_FALSE@@WANT_PHYTIME_FALSE@@WANT_RF_FALSE@@WANT_TEST_TRUE@@WANT_TIPORDER_FALSE@draw.c draw.h\
@WANT_M4_FALSE@@WANT_MPI_FALSE@@WANT_PART_FALSE@@WANT_PHYCONT_FALSE@@WANT_PHYTIME_FALSE@@WANT_RF_FALSE@@WANT_TEST_TRUE@@WANT_TIPORDER_FALSE@stats.c stats.h\
@WANT_M4_FALSE@@WANT_MPI_FALSE@@WANT_PART_FALSE@@WANT_PHYCONT_FALSE@@WANT_PHYTIME_FALSE@@WANT_RF_FALSE@@WANT_TEST_TRUE@@WANT_TIPORDER_FALSE@rates.c rates.h\
@WANT_M4_FALSE@@WANT_MPI_FALSE@@WANT_PART_FALSE@@WANT_PHYCONT_FALSE@@WANT_PHYTIME_FALSE@@WANT_RF_FALSE@@WANT_TEST_TRUE@@WANT_TIPORDER_FALSE@mcmc.c mcmc.h\
@WANT_M4_FALSE@@WANT_MPI_FALSE@@WANT_PART_FALSE@@WANT_PHYCONT_FALSE@@WANT_PHYTIME_FALSE@@WANT_RF_FALSE@@WANT_TEST_TRUE@@WANT_TIPORDER_FALSE@times.c times.h\
@WANT_M4_FALSE@@WANT_MPI_FALSE@@WANT_PART_FALSE@@WANT_PHYCONT_FALSE@@WANT_PHYTIME_FALSE@@WANT_RF_FALSE@@WANT_TEST_TRUE@@WANT_TIPORDER_FALSE@tiporder.c tiporder.h\
@WANT_M4_FALSE@@WANT_MPI_FALSE@@WANT_PART_FALSE@@WANT_PHYCONT_FALSE@@WANT_PHYTIME_FALSE@@WANT_RF_FALSE@@WANT_TEST_TRUE@@WANT_TIPORDER_FALSE@mg.c mg.h\
@WANT_M4_FALSE@@WANT_MPI_FALSE@@WANT_PART_FALSE@@WANT_PHYCONT_FALSE@@WANT_PHYTIME_FALSE@@WANT_RF_FALSE@@WANT_TEST_TRUE@@WANT_TIPORDER_FALSE@m4.c m4.h\
@WANT_M4_FALSE@@WANT_MPI_FALSE@@WANT_PART_FALSE@@WANT_PHYCONT_FALSE@@WANT_PHYTIME_FALSE@@WANT_RF_FALSE@@WANT_TEST_TRUE@@WANT_TIPORDER_FALSE@xml.c xml.h
@WANT_M4_FALSE@@WANT_MPI_FALSE@@WANT_PART_FALSE@@WANT_PHYCONT_FALSE@@WANT_PHYTIME_FALSE@@WANT_RF_FALSE@@WANT_TEST_TRUE@@WANT_TIPORDER_FALSE@test_LDADD = -lm
@WANT_M4_FALSE@@WANT_MPI_FALSE@@WANT_PART_FALSE@@WANT_PHYCONT_FALSE@@WANT_PHYTIME_FALSE@@WANT_RF_FALSE@@WANT_TEST_FALSE@@WANT_TIPORDER_FALSE@phyml_SOURCES = main.c \
@WANT_M4_FALSE@@WANT_MPI_FALSE@@WANT_PART_FALSE@@WANT_PHYCONT_FALSE@@WANT_PHYTIME_FALSE@@WANT_RF_FALSE@@WANT_TEST_FALSE@@WANT_TIPORDER_FALSE@utilities.c utilities.h\
@WANT_M4_FALSE@@WANT_MPI_FALSE@@WANT_PART_FALSE@@WANT_PHYCONT_FALSE@@WANT_PHYTIME_FALSE@@WANT_RF_FALSE@@WANT_TEST_FALSE@@WANT_TIPORDER_FALSE@optimiz.c optimiz.h\
@WANT_M4_FALSE@@WANT_MPI_FALSE@@WANT_PART_FALSE@@WANT_PHYCONT_FALSE@@WANT_PHYTIME_FALSE@@WANT_RF_FALSE@@WANT_TEST_FALSE@@WANT_TIPORDER_FALSE@lk.c lk.h\
@WANT_M4_FALSE@@WANT_MPI_FALSE@@WANT_PART_FALSE@@WANT_PHYCONT_FALSE@@WANT_PHYTIME_FALSE@@WANT_RF_FALSE@@WANT_TEST_FALSE@@WANT_TIPORDER_FALSE@bionj.c bionj.h\
@WANT_M4_FALSE@@WANT_MPI_FALSE@@WANT_PART_FALSE@@WANT_PHYCONT_FALSE@@WANT_PHYTIME_FALSE@@WANT_RF_FALSE@@WANT_TEST_FALSE@@WANT_TIPORDER_FALSE@models.c models.h\
@WANT_M4_FALSE@@WANT_MPI_FALSE@@WANT_PART_FALSE@@WANT_PHYCONT_FALSE@@WANT_PHYTIME_FALSE@@WANT_RF_FALSE@@WANT_TEST_FALSE@@WANT_TIPORDER_FALSE@free.c free.h\
@WANT_M4_FALSE@@WANT_MPI_FALSE@@WANT_PART_FALSE@@WANT_PHYCONT_FALSE@@WANT_PHYTIME_FALSE@@WANT_RF_FALSE@@WANT_TEST_FALSE@@WANT_TIPORDER_FALSE@help.c help.h\
@WANT_M4_FALSE@@WANT_MPI_FALSE@@WANT_PART_FALSE@@WANT_PHYCONT_FALSE@@WANT_PHYTIME_FALSE@@WANT_RF_FALSE@@WANT_TEST_FALSE@@WANT_TIPORDER_FALSE@simu.c simu.h\
@WANT_M4_FALSE@@WANT_MPI_FALSE@@WANT_PART_FALSE@@WANT_PHYCONT_FALSE@@WANT_PHYTIME_FALSE@@WANT_RF_FALSE@@WANT_TEST_FALSE@@WANT_TIPORDER_FALSE@eigen.c eigen.h\
@WANT_M4_FALSE@@WANT_MPI_FALSE@@WANT_PART_FALSE@@WANT_PHYCONT_FALSE@@WANT_PHYTIME_FALSE@@WANT_RF_FALSE@@WANT_TEST_FALSE@@WANT_TIPORDER_FALSE@pars.c pars.h\
@WANT_M4_FALSE@@WANT_MPI_FALSE@@WANT_PART_FALSE@@WANT_PHYCONT_FALSE@@WANT_PHYTIME_FALSE@@WANT_RF_FALSE@@WANT_TEST_FALSE@@WANT_TIPORDER_FALSE@alrt.c alrt.h\
@WANT_M4_FALSE@@WANT_MPI_FALSE@@WANT_PART_FALSE@@WANT_PHYCONT_FALSE@@WANT_PHYTIME_FALSE@@WANT_RF_FALSE@@WANT_TEST_FALSE@@WANT_TIPORDER_FALSE@interface.c interface.h\
@WANT_M4_FALSE@@WANT_MPI_FALSE@@WANT_PART_FALSE@@WANT_PHYCONT_FALSE@@WANT_PHYTIME_FALSE@@WANT_RF_FALSE@@WANT_TEST_FALSE@@WANT_TIPORDER_FALSE@cl.c cl.h\
@WANT_M4_FALSE@@WANT_MPI_FALSE@@WANT_PART_FALSE@@WANT_PHYCONT_FALSE@@WANT_PHYTIME_FALSE@@WANT_RF_FALSE@@WANT_TEST_FALSE@@WANT_TIPORDER_FALSE@spr.c spr.h\
@WANT_M4_FALSE@@WANT_MPI_FALSE@@WANT_PART_FALSE@@WANT_PHYCONT_FALSE@@WANT_PHYTIME_FALSE@@WANT_RF_FALSE@@WANT_TEST_FALSE@@WANT_TIPORDER_FALSE@draw.c draw.h\
@WANT_M4_FALSE@@WANT_MPI_FALSE@@WANT_PART_FALSE@@WANT_PHYCONT_FALSE@@WANT_PHYTIME_FALSE@@WANT_RF_FALSE@@WANT_TEST_FALSE@@WANT_TIPORDER_FALSE@stats.c stats.h\
@WANT_M4_FALSE@@WANT_MPI_FALSE@@WANT_PART_FALSE@@WANT_PHYCONT_FALSE@@WANT_PHYTIME_FALSE@@WANT_RF_FALSE@@WANT_TEST_FALSE@@WANT_TIPORDER_FALSE@rates.c rates.h\
@WANT_M4_FALSE@@WANT_MPI_FALSE@@WANT_PART_FALSE@@WANT_PHYCONT_FALSE@@WANT_PHYTIME_FALSE@@WANT_RF_FALSE@@WANT_TEST_FALSE@@WANT_TIPORDER_FALSE@mcmc.c mcmc.h\
@WANT_M4_FALSE@@WANT_MPI_FALSE@@WANT_PART_FALSE@@WANT_PHYCONT_FALSE@@WANT_PHYTIME_FALSE@@WANT_RF_FALSE@@WANT_TEST_FALSE@@WANT_TIPORDER_FALSE@times.c times.h\
@WANT_M4_FALSE@@WANT_MPI_FALSE@@WANT_PART_FALSE@@WANT_PHYCONT_FALSE@@WANT_PHYTIME_FALSE@@WANT_RF_FALSE@@WANT_TEST_FALSE@@WANT_TIPORDER_FALSE@tiporder.c tiporder.h\
@WANT_M4_FALSE@@WANT_MPI_FALSE@@WANT_PART_FALSE@@WANT_PHYCONT_FALSE@@WANT_PHYTIME_FALSE@@WANT_RF_FALSE@@WANT_TEST_FALSE@@WANT_TIPORDER_FALSE@mg.c mg.h\
@WANT_M4_FALSE@@WANT_MPI_FALSE@@WANT_PART_FALSE@@WANT_PHYCONT_FALSE@@WANT_PHYTIME_FALSE@@WANT_RF_FALSE@@WANT_TEST_FALSE@@WANT_TIPORDER_FALSE@m4.c m4.h
@WANT_M4_FALSE@@WANT_MPI_FALSE@@WANT_PART_FALSE@@WANT_PHYCONT_FALSE@@WANT_PHYTIME_FALSE@@WANT_RF_FALSE@@WANT_TEST_FALSE@@WANT_TIPORDER_FALSE@phyml_LDADD = -lm
all: all-am
.SUFFIXES:
.SUFFIXES: .c .o .obj
$(srcdir)/Makefile.in: $(srcdir)/Makefile.am $(am__configure_deps)
@for dep in $?; do \
case '$(am__configure_deps)' in \
*$$dep*) \
( cd $(top_builddir) && $(MAKE) $(AM_MAKEFLAGS) am--refresh ) \
&& { if test -f $@; then exit 0; else break; fi; }; \
exit 1;; \
esac; \
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# Otherwise a system limit (for SysV at least) may be exceeded.
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phyml-20120412/src/stats.c 0000644 0001750 0001750 00000426405 11631005213 012115 0000000 0000000 /*
PhyML: a program that computes maximum likelihood phylogenies from
DNA or AA homologous sequences.
Copyright (C) Stephane Guindon. Oct 2003 onward.
All parts of the source except where indicated are distributed under
the GNU public licence. See http://www.opensource.org for details.
*/
#include "stats.h"
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
/* RANDOM VARIATES GENERATORS */
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
/*********************************************************************/
/* A C-function for TT800 : July 8th 1996 Version */
/* by M. Matsumoto, email: matumoto@math.keio.ac.jp */
/* tt800() generate one pseudorandom number with double precision */
/* which is uniformly distributed on [0,1]-interval */
/* for each call. One may choose any initial 25 seeds */
/* except all zeros. */
/* See: ACM Transactions on Modelling and Computer Simulation, */
/* Vol. 4, No. 3, 1994, pages 254-266. */
phydbl tt800()
{
int M=7;
unsigned long y;
static int k = 0;
static unsigned long x[25]={ /* initial 25 seeds, change as you wish */
0x95f24dab, 0x0b685215, 0xe76ccae7, 0xaf3ec239, 0x715fad23,
0x24a590ad, 0x69e4b5ef, 0xbf456141, 0x96bc1b7b, 0xa7bdf825,
0xc1de75b7, 0x8858a9c9, 0x2da87693, 0xb657f9dd, 0xffdc8a9f,
0x8121da71, 0x8b823ecb, 0x885d05f5, 0x4e20cd47, 0x5a9ad5d9,
0x512c0c03, 0xea857ccd, 0x4cc1d30f, 0x8891a8a1, 0xa6b7aadb
};
static unsigned long mag01[2]={
0x0, 0x8ebfd028 /* this is magic vector `a', don't change */
};
if (k==25) { /* generate 25 words at one time */
int kk;
for (kk=0;kk<25-M;kk++) {
x[kk] = x[kk+M] ^ (x[kk] >> 1) ^ mag01[x[kk] % 2];
}
for (; kk<25;kk++) {
x[kk] = x[kk+(M-25)] ^ (x[kk] >> 1) ^ mag01[x[kk] % 2];
}
k=0;
}
y = x[k];
y ^= (y << 7) & 0x2b5b2500; /* s and b, magic vectors */
y ^= (y << 15) & 0xdb8b0000; /* t and c, magic vectors */
y &= 0xffffffff; /* you may delete this line if word size = 32 */
/*
the following line was added by Makoto Matsumoto in the 1996 version
to improve lower bit's corellation.
Delete this line to o use the code published in 1994.
*/
y ^= (y >> 16); /* added to the 1994 version */
k++;
return((phydbl)y / (unsigned long) 0xffffffff);
}
/*********************************************************************/
phydbl Uni()
{
phydbl r,mx;
mx = (phydbl)RAND_MAX;
r = (phydbl)rand();
r /= mx;
/* r = tt800(); */
return r;
}
/*********************************************************************/
int Rand_Int(int min, int max)
{
/* phydbl u; */
/* u = (phydbl)rand(); */
/* u /= (RAND_MAX); */
/* u *= (max - min + 1); */
/* u += min; */
/* return (int)FLOOR(u); */
int u;
u = rand();
return (u%(max+1-min)+min);
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
/********************* random Gamma generator ************************
* Properties:
* (1) X = Gamma(alpha,lambda) = Gamma(alpha,1)/lambda
* (2) X1 = Gamma(alpha1,1), X2 = Gamma(alpha2,1) independent
* then X = X1+X2 = Gamma(alpha1+alpha2,1)
* (3) alpha = k = integer then
* X = Gamma(k,1) = Erlang(k,1) = -sum(LOG(Ui)) = -LOG(prod(Ui))
* where U1,...Uk iid uniform(0,1)
*
* Decompose alpha = k+delta with k = [alpha], and 00.)
{
phydbl y = 0.;
phydbl b = (alpha+EXP(1.))/EXP(1.);
phydbl p = 1./alpha;
int go = 0;
while (go==0)
{
phydbl u = Uni();
phydbl w = Uni();
phydbl v = b*u;
if (v<=1.)
{
x = POW(v,p);
y = EXP(-x);
}
else
{
x = -LOG(p*(b-v));
y = POW(x,alpha-1.);
}
go = (w=1.)
{
int k = (int)FLOOR(shape);
delta = shape - k;
phydbl u = 1.;
for (i=0; i.0 && d<1.) break;
}
while(1);
u1 = x*SQRT((-2.*LOG(d))/d);
res = u1*sd+mean;
if(isnan(res) || isinf(res))
{
printf("\n. res=%f sd=%f mean=%f u1=%f u2=%f",res,sd,mean,u1,u2);
}
return res;
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
phydbl *Rnorm_Multid(phydbl *mu, phydbl *cov, int dim)
{
phydbl *L,*x,*y;
int i,j;
x = (phydbl *)mCalloc(dim,sizeof(phydbl));
y = (phydbl *)mCalloc(dim,sizeof(phydbl));
L = (phydbl *)Cholesky_Decomp(cov,dim);
For(i,dim) x[i]=Rnorm(0.0,1.0);
For(i,dim) For(j,dim) y[i] += L[i*dim+j]*x[j];
For(i,dim) y[i] += mu[i];
Free(L);
Free(x);
return(y);
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
phydbl Rnorm_Trunc_Inverse(phydbl mean, phydbl sd, phydbl min, phydbl max, int *error)
{
phydbl u, ret_val,eps;
phydbl z,rz;
phydbl z_min,z_max;
phydbl cdf_min, cdf_max;
z = 0.0;
rz = 0.0;
u = -1.0;
*error = 0;
if(sd < 1.E-100)
{
PhyML_Printf("\n. Small variance detected in Rnorm_Trunc.");
PhyML_Printf("\n. mean=%f sd=%f min=%f max=%f",mean,sd,min,max);
*error = 1;
return -1.0;
}
z_min = (min - mean)/sd;
z_max = (max - mean)/sd;
eps = (z_max-z_min)/1E+6;
/* Simple inversion method. Seems to work well. Needs more thorough testing though... */
cdf_min = Pnorm(z_min,0.0,1.0);
cdf_max = Pnorm(z_max,0.0,1.0);
u = cdf_min + (cdf_max-cdf_min) * Uni();
z = PointNormal(u);
if((z < z_min-eps) || (z > z_max+eps))
{
*error = 1;
PhyML_Printf("\n. Numerical precision issue detected in Rnorm_Trunc.");
PhyML_Printf("\n. z = %f",z);
PhyML_Printf("\n. mean=%f sd=%f z_min=%f z_max=%f min=%f max=%f",mean,sd,z_min,z_max,min,max);
ret_val = (max - min)/2.;
Exit("\n");
}
ret_val = z*sd+mean;
return ret_val;
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
phydbl Rnorm_Trunc(phydbl mean, phydbl sd, phydbl min, phydbl max, int *error)
{
phydbl u, ret_val,eps;
int iter;
phydbl z,rz;
phydbl z_min,z_max;
z = 0.0;
rz = 0.0;
u = -1.0;
*error = NO;
if(sd < 1.E-100)
{
PhyML_Printf("\n. Small variance detected in Rnorm_Trunc.");
PhyML_Printf("\n. mean=%f sd=%f min=%f max=%f",mean,sd,min,max);
*error = YES;
return -1.0;
}
if(max < min)
{
PhyML_Printf("\n. Max < Min");
PhyML_Printf("\n. mean=%f sd=%f min=%f max=%f",mean,sd,min,max);
*error = YES;
return -1.0;
}
z_min = (min - mean)/sd;
z_max = (max - mean)/sd;
eps = (z_max-z_min)/1E+6;
/* Damien and Walker (2001) method */
phydbl y,slice_min,slice_max;
/* if((z_min < -10.) && (z_max > +10.)) /\* cdf < 1.E-6, we should be safe. *\/ */
/* { */
/* z = Rnorm(0.0,1.0); */
/* } */
/* else */
/* { */
iter = 0;
do
{
y = Uni()*EXP(-(z*z)/2.);
slice_min = MAX(z_min,-SQRT(-2.*LOG(y)));
slice_max = MIN(z_max, SQRT(-2.*LOG(y)));
z = Uni()*(slice_max - slice_min) + slice_min;
iter++;
if(iter > 1000) break;
}
while(slice_max < slice_min || iter < 10);
if(iter > 1000)
{
PhyML_Printf("\n. Too many iterations in Rnorm_Trunc...");
*error = 1;
}
/* } */
/* Inverson method */
/* phydbl cdf_min, cdf_max; */
/* if((z_min < -10.) && (z_max > +10.)) /\* cdf < 1.E-6, we should be safe. *\/ */
/* { */
/* z = Rnorm(0.0,1.0); */
/* } */
/* else */
/* { */
/* /\* Simple inversion method. Seems to work well. Needs more thorough testing though... *\/ */
/* cdf_min = Pnorm(z_min,0.0,1.0); */
/* cdf_max = Pnorm(z_max,0.0,1.0); */
/* u = cdf_min + (cdf_max-cdf_min) * Uni(); */
/* z = PointNormal(u); */
/* } */
if((z < z_min-eps) || (z > z_max+eps))
{
*error = YES;
PhyML_Printf("\n. Numerical precision issue detected in Rnorm_Trunc.");
PhyML_Printf("\n. z = %f",z);
PhyML_Printf("\n. mean=%f sd=%f z_min=%f z_max=%f min=%f max=%f",mean,sd,z_min,z_max,min,max);
ret_val = (max - min)/2.;
Exit("\n");
}
ret_val = z*sd+mean;
return ret_val;
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
phydbl *Rnorm_Multid_Trunc(phydbl *mean, phydbl *cov, phydbl *min, phydbl *max, int dim)
{
int i,j;
phydbl *L,*x, *u;
phydbl up, low, rec;
int err;
u = (phydbl *)mCalloc(dim,sizeof(phydbl));
x = (phydbl *)mCalloc(dim,sizeof(phydbl));
L = Cholesky_Decomp(cov,dim);
low = (min[0]-mean[0])/L[0*dim+0];
up = (max[0]-mean[0])/L[0*dim+0];
u[0] = Rnorm_Trunc(0.0,1.0,low,up,&err);
for(i=1;i>>\n"); */
/* For(i,dim) */
/* { */
/* For(j,dim) */
/* { */
/* PhyML_Printf("%10lf ",L[i*dim+j]); */
/* } */
/* PhyML_Printf("\n"); */
/* } */
/* PhyML_Printf("\n"); */
/* For(i,dim) PhyML_Printf("%f ",u[i]); */
/* PhyML_Printf("\n"); */
/* PhyML_Printf("\n"); */
/* For(i,dim) PhyML_Printf("%10lf ",x[i]); */
/* PhyML_Printf("\n<<<\n"); */
For(i,dim) x[i] += mean[i];
Free(L);
Free(u);
return x;
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
/* DENSITIES / PROBA */
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
phydbl Dnorm_Moments(phydbl x, phydbl mean, phydbl var)
{
phydbl dens,sd,pi;
pi = 3.141593;
sd = SQRT(var);
dens = 1./(SQRT(2*pi)*sd)*EXP(-((x-mean)*(x-mean)/(2.*sd*sd)));
return dens;
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
phydbl Dnorm(phydbl x, phydbl mean, phydbl sd)
{
phydbl dens;
/* dens = -(.5*LOG2PI+LOG(sd)) - .5*POW(x-mean,2)/POW(sd,2); */
/* return EXP(dens); */
x = (x-mean)/sd;
dens = M_1_SQRT_2_PI * EXP(-0.5*x*x);
return dens / sd;
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
phydbl Log_Dnorm(phydbl x, phydbl mean, phydbl sd, int *err)
{
phydbl dens;
*err = NO;
x = (x-mean)/sd;
/* dens = -(phydbl)LOG_SQRT_2_PI - x*x*0.5 - LOG(sd); */
dens = -(phydbl)LOG(SQRT(2.*PI)) - x*x*0.5 - LOG(sd);
if(dens < -BIG)
{
PhyML_Printf("\n. dens=%f -- x=%f mean=%f sd=%f\n",dens,x,mean,sd);
*err = 1;
}
return dens;
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
phydbl Log_Dnorm_Trunc(phydbl x, phydbl mean, phydbl sd, phydbl lo, phydbl up, int *err)
{
phydbl log_dens;
phydbl cdf_up, cdf_lo;
*err = NO;
cdf_lo = cdf_up = 0.0;
log_dens = Log_Dnorm(x,mean,sd,err);
if(*err == YES)
{
PhyML_Printf("\n. mean=%f sd=%f lo=%f up=%f cdf_lo=%G CDF_up=%G log_dens=%G",mean,sd,lo,up,cdf_lo,cdf_up,log_dens);
PhyML_Printf("\n. Warning in file %s at line %d\n",__FILE__,__LINE__);
*err = YES;
}
cdf_up = Pnorm(up,mean,sd);
cdf_lo = Pnorm(lo,mean,sd);
if(cdf_up - cdf_lo < 1.E-20)
{
log_dens = -230.; /* ~LOG(1.E-100) */
}
else
{
log_dens -= LOG(cdf_up - cdf_lo);
}
if(isnan(log_dens) || isinf(FABS(log_dens)))
{
PhyML_Printf("\n. x=%f mean=%f sd=%f lo=%f up=%f cdf_lo=%G CDF_up=%G log_dens=%G",x,mean,sd,lo,up,cdf_lo,cdf_up,log_dens);
PhyML_Printf("\n. Warning in file %s at line %d\n",__FILE__,__LINE__);
*err = YES;
}
return log_dens;
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
phydbl Dnorm_Trunc(phydbl x, phydbl mean, phydbl sd, phydbl lo, phydbl up)
{
phydbl dens;
phydbl cdf_up, cdf_lo;
dens = Dnorm(x,mean,sd);
cdf_up = Pnorm(up,mean,sd);
cdf_lo = Pnorm(lo,mean,sd);
dens /= (cdf_up - cdf_lo);
if(isnan(dens) || isinf(FABS(dens)))
{
PhyML_Printf("\n. mean=%f sd=%f lo=%f up=%f cdf_lo=%G CDF_up=%G",mean,sd,lo,up,cdf_lo,cdf_up);
PhyML_Printf("\n. Err in file %s at line %d\n",__FILE__,__LINE__);
Exit("\n");
}
return dens;
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
phydbl Dnorm_Multi(phydbl *x, phydbl *mu, phydbl *cov, int size, int _log)
{
phydbl *xmmu,*invcov;
phydbl *buff1,*buff2;
int i;
phydbl det,density;
xmmu = (phydbl *)mCalloc(size,sizeof(phydbl));
invcov = (phydbl *)mCalloc(size*size,sizeof(phydbl));
For(i,size) xmmu[i] = x[i] - mu[i];
For(i,size*size) invcov[i] = cov[i];
if(!Matinv(invcov,size,size,NO))
{
PhyML_Printf("\n. Err in file %s at line %d\n",__FILE__,__LINE__);
Exit("\n");
}
buff1 = Matrix_Mult(xmmu,invcov,1,size,size,size);
buff2 = Matrix_Mult(buff1,xmmu,1,size,size,1);
det = Matrix_Det(cov,size,NO);
/* det_1D(cov,size,&det); */
density = size * LOG2PI + LOG(det) + buff2[0];
density /= -2.;
/* density = (1./(POW(2.*PI,size/2.)*SQRT(FABS(det)))) * EXP(-0.5*buff2[0]); */
Free(xmmu);
Free(invcov);
Free(buff1);
Free(buff2);
return (_log)?(density):(EXP(density));
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
phydbl Dnorm_Multi_Given_InvCov_Det(phydbl *x, phydbl *mu, phydbl *invcov, phydbl log_det, int size, int _log)
{
phydbl *xmmu;
phydbl *buff1,*buff2;
int i;
phydbl density;
xmmu = (phydbl *)mCalloc(size,sizeof(phydbl));
For(i,size) xmmu[i] = x[i] - mu[i];
buff1 = Matrix_Mult(xmmu,invcov,1,size,size,size);
buff2 = Matrix_Mult(buff1,xmmu,1,size,size,1);
density = size * LOG2PI + log_det + buff2[0];
density /= -2.;
Free(xmmu);
Free(buff1);
Free(buff2);
return (_log)?(density):(EXP(density));
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
phydbl Pbinom(int N, int ni, phydbl p)
{
return Bico(N,ni)*POW(p,ni)*POW(1-p,N-ni);
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
phydbl Bivariate_Normal_Density(phydbl x, phydbl y, phydbl mux, phydbl muy, phydbl sdx, phydbl sdy, phydbl rho)
{
phydbl cx, cy;
phydbl pi;
phydbl dens;
phydbl rho2;
pi = 3.141593;
cx = x - mux;
cy = y - muy;
rho2 = rho*rho;
dens = 1./(2*pi*sdx*sdy*SQRT(1.-rho2));
dens *= EXP((-1./(2.*(1.-rho2)))*(cx*cx/(sdx*sdx)+cy*cy/(sdy*sdy)+2*rho*cx*cy/(sdx*sdy)));
return dens;
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
phydbl Dgamma_Moments(phydbl x, phydbl mean, phydbl var)
{
phydbl shape, scale;
if(var < 1.E-20)
{
/* var = 1.E-20; */
PhyML_Printf("\n. var=%f mean=%f",var,mean);
PhyML_Printf("\n. Err in file %s at line %d\n",__FILE__,__LINE__);
Exit("\n");
}
if(mean < 1.E-20)
{
/* mean = 1.E-20; */
PhyML_Printf("\n. var=%f mean=%f",var,mean);
PhyML_Printf("\n. Err in file %s at line %d\n",__FILE__,__LINE__);
Exit("\n");
}
shape = mean * mean / var;
scale = var / mean;
return(Dgamma(x,shape,scale));
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
phydbl Dgamma(phydbl x, phydbl shape, phydbl scale)
{
phydbl v;
if(x > INFINITY)
{
PhyML_Printf("\n. WARNING: huge value of x -> x = %G",x);
x = 1.E+10;
}
if(x < 1.E-20)
{
if(x < 0.0) return 0.0;
else
{
PhyML_Printf("\n. WARNING: small value of x -> x = %G",x);
x = 1.E-20;
}
}
if(scale < 0.0 || shape < 0.0)
{
PhyML_Printf("\n. scale=%f shape=%f",scale,shape);
Exit("\n");
}
v = (shape-1.) * LOG(x) - shape * LOG(scale) - x / scale - LnGamma(shape);
if(v < 500.)
{
v = EXP(v);
}
else
{
PhyML_Printf("\n. WARNING v=%f x=%f shape=%f scale=%f",v,x,shape,scale);
PhyML_Printf("\n. LOG(x) = %G LnGamma(shape)=%G",LOG(x),LnGamma(shape));
v = EXP(v);
/* PhyML_Printf("\n. Err in file %s at line %d\n",__FILE__,__LINE__); */
/* Exit("\n"); */
}
return v;
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
phydbl Dexp(phydbl x, phydbl param)
{
return param * EXP(-param * x);
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
phydbl Dpois(phydbl x, phydbl param)
{
phydbl v;
if(x < 0)
{
PhyML_Printf("\n. x = %f",x);
PhyML_Printf("\n. Err in file %s at line %d\n",__FILE__,__LINE__);
Warn_And_Exit("");
}
v = x * LOG(param) - param - LnGamma(x+1);
if(v < 500)
{
v = EXP(v);
}
else
{
PhyML_Printf("\n. WARNING v=%f x=%f param=%f",v,x,param);
v = EXP(500);
}
/* PhyML_Printf("\n. Poi %f %f (x=%f param=%f)", */
/* v, */
/* POW(param,x) * EXP(-param) / EXP(LnGamma(x+1)), */
/* x,param); */
/* return POW(param,x) * EXP(-param) / EXP(LnGamma(x+1)); */
return v;
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
/* CDFs */
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
phydbl Pnorm(phydbl x, phydbl mean, phydbl sd)
{
/* const phydbl b1 = 0.319381530; */
/* const phydbl b2 = -0.356563782; */
/* const phydbl b3 = 1.781477937; */
/* const phydbl b4 = -1.821255978; */
/* const phydbl b5 = 1.330274429; */
/* const phydbl p = 0.2316419; */
/* const phydbl c = 0.39894228; */
x = (x-mean)/sd;
/* if(x >= 0.0) */
/* { */
/* phydbl t = 1.0 / ( 1.0 + p * x ); */
/* return (1.0 - c * EXP( -x * x / 2.0 ) * t * */
/* ( t *( t * ( t * ( t * b5 + b4 ) + b3 ) + b2 ) + b1 )); */
/* } */
/* else */
/* { */
/* phydbl t = 1.0 / ( 1.0 - p * x ); */
/* return ( c * EXP( -x * x / 2.0 ) * t * */
/* ( t *( t * ( t * ( t * b5 + b4 ) + b3 ) + b2 ) + b1 )); */
/* } */
/* i_tail in {0,1,2} means: "lower", "upper", or "both" :
if(lower) return *cum := P[X <= x]
if(upper) return *ccum := P[X > x] = 1 - P[X <= x]
*/
/* return Pnorm_Marsaglia(x); */
return Pnorm_Ihaka_Derived_From_Cody(x);
}
/* G. Marsaglia. "Evaluating the Normal distribution". Journal of Statistical Software. 2004. Vol. 11. Issue 4. */
phydbl Pnorm_Marsaglia(phydbl x)
{
long double s=x,t=0,b=x,q=x*x,i=1;
while(s!=t) s=(t=s)+(b*=q/(i+=2));
return .5+s*exp(-.5*q-.91893853320467274178L);
}
/* Stolen from R source code */
#define SIXTEN 16
phydbl Pnorm_Ihaka_Derived_From_Cody(phydbl x)
{
const static double a[5] = {
2.2352520354606839287,
161.02823106855587881,
1067.6894854603709582,
18154.981253343561249,
0.065682337918207449113
};
const static double b[4] = {
47.20258190468824187,
976.09855173777669322,
10260.932208618978205,
45507.789335026729956
};
const static double c[9] = {
0.39894151208813466764,
8.8831497943883759412,
93.506656132177855979,
597.27027639480026226,
2494.5375852903726711,
6848.1904505362823326,
11602.651437647350124,
9842.7148383839780218,
1.0765576773720192317e-8
};
const static double d[8] = {
22.266688044328115691,
235.38790178262499861,
1519.377599407554805,
6485.558298266760755,
18615.571640885098091,
34900.952721145977266,
38912.003286093271411,
19685.429676859990727
};
const static double p[6] = {
0.21589853405795699,
0.1274011611602473639,
0.022235277870649807,
0.001421619193227893466,
2.9112874951168792e-5,
0.02307344176494017303
};
const static double q[5] = {
1.28426009614491121,
0.468238212480865118,
0.0659881378689285515,
0.00378239633202758244,
7.29751555083966205e-5
};
double xden, xnum, temp, del, eps, xsq, y;
int i, lower, upper;
double cum,ccum;
int i_tail;
i_tail = 0;
cum = ccum = 0.0;
if(isnan(x)) { cum = ccum = x; return (phydbl)cum; }
/* Consider changing these : */
eps = DBL_EPSILON * 0.5;
/* i_tail in {0,1,2} =^= {lower, upper, both} */
lower = i_tail != 1;
upper = i_tail != 0;
y = fabs(x);
if (y <= 0.67448975) { /* qnorm(3/4) = .6744.... -- earlier had 0.66291 */
if (y > eps) {
xsq = x * x;
xnum = a[4] * xsq;
xden = xsq;
for (i = 0; i < 3; ++i) {
xnum = (xnum + a[i]) * xsq;
xden = (xden + b[i]) * xsq;
}
} else xnum = xden = 0.0;
temp = x * (xnum + a[3]) / (xden + b[3]);
if(lower) cum = 0.5 + temp;
if(upper) ccum = 0.5 - temp;
}
else if (y <= M_SQRT_32) {
/* Evaluate pnorm for 0.674.. = qnorm(3/4) < |x| <= SQRT(32) ~= 5.657 */
xnum = c[8] * y;
xden = y;
for (i = 0; i < 7; ++i) {
xnum = (xnum + c[i]) * y;
xden = (xden + d[i]) * y;
}
temp = (xnum + c[7]) / (xden + d[7]);
#define do_del(X) \
xsq = floor(X * SIXTEN) / SIXTEN; \
del = (X - xsq) * (X + xsq); \
cum = exp(-xsq * xsq * 0.5) * exp(-del * 0.5) * temp; \
ccum = 1.0 - cum; \
#define swap_tail \
if (x > 0.) {/* swap ccum <--> cum */ \
temp = cum; if(lower) cum = ccum; ccum = temp; \
}
do_del(y);
swap_tail;
}
/* else |x| > SQRT(32) = 5.657 :
* the next two case differentiations were really for lower=T, log=F
* Particularly *not* for log_p !
* Cody had (-37.5193 < x && x < 8.2924) ; R originally had y < 50
*
* Note that we do want symmetry(0), lower/upper -> hence use y
*/
else if((lower && -37.5193 < x && x < 8.2924) || (upper && -8.2924 < x && x < 37.5193))
{
/* Evaluate pnorm for x in (-37.5, -5.657) union (5.657, 37.5) */
xsq = 1.0 / (x * x);
xnum = p[5] * xsq;
xden = xsq;
for (i = 0; i < 4; ++i) {
xnum = (xnum + p[i]) * xsq;
xden = (xden + q[i]) * xsq;
}
temp = xsq * (xnum + p[4]) / (xden + q[4]);
temp = (M_1_SQRT_2_PI - temp) / y;
do_del(x);
swap_tail;
}
else
{ /* no log_p , large x such that probs are 0 or 1 */
if(x > 0) { cum = 1.; ccum = 0.; }
else { cum = 0.; ccum = 1.; }
}
return (phydbl)cum;
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
phydbl Pgamma(phydbl x, phydbl shape, phydbl scale)
{
return IncompleteGamma(x/scale,shape,LnGamma(shape));
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
phydbl Ppois(phydbl x, phydbl param)
{
/* Press et al. (1990) approximation of the CDF for the Poisson distribution */
if(param < SMALL || x < 0.0)
{
PhyML_Printf("\n. param = %G x=%G",param,x);
PhyML_Printf("\n. Err in file %s at line %d\n",__FILE__,__LINE__);
Warn_And_Exit("");
}
return IncompleteGamma(x,param,LnGamma(param));
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
/* Inverse CDFs */
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
phydbl PointChi2 (phydbl prob, phydbl v)
{
/* returns z so that Prob{x.999998 || v<=0) return ((phydbl)-1);
g = (double)LnGamma(v/2);
xx=v/2; c=xx-1;
if (v >= -1.24*log(p)) goto l1;
ch=pow((p*xx*exp(g+xx*aa)), 1/xx);
if (ch-e<0) return (ch);
goto l4;
l1:
if (v>.32) goto l3;
ch=0.4; a=log(1-p);
l2:
q=ch; p1=1+ch*(4.67+ch); p2=ch*(6.73+ch*(6.66+ch));
t=-0.5+(4.67+2*ch)/p1 - (6.73+ch*(13.32+3*ch))/p2;
ch-=(1-exp(a+g+.5*ch+c*aa)*p2/p1)/t;
if (fabs(q/ch-1)-.01 <= 0) goto l4;
else goto l2;
l3:
x=(double)PointNormal (p);
p1=0.222222/v; ch=v*pow((x*sqrt(p1)+1-p1), 3.0);
if (ch>2.2*v+6) ch=-2*(log(1-p)-c*log(.5*ch)+g);
l4:
q=ch; p1=.5*ch;
if ((t=(double)IncompleteGamma (p1, xx, g))<0) {
PhyML_Printf ("\nerr IncompleteGamma");
return ((phydbl)-1.);
}
p2=p-t;
t=p2*exp(xx*aa+g+p1-c*log(ch));
b=t/ch; a=0.5*t-b*c;
s1=(210+a*(140+a*(105+a*(84+a*(70+60*a))))) / 420;
s2=(420+a*(735+a*(966+a*(1141+1278*a))))/2520;
s3=(210+a*(462+a*(707+932*a)))/2520;
s4=(252+a*(672+1182*a)+c*(294+a*(889+1740*a)))/5040;
s5=(84+264*a+c*(175+606*a))/2520;
s6=(120+c*(346+127*c))/5040;
ch+=t*(1+0.5*t*s1-b*c*(s1-b*(s2-b*(s3-b*(s4-b*(s5-b*s6))))));
if (FABS(q/ch-1) > e) goto l4;
return (phydbl)(ch);
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
/*
The following function was extracted from the source code of R.
It implements the methods referenced below.
* REFERENCE
*
* Beasley, J. D. and S. G. Springer (1977).
* Algorithm AS 111: The percentage points of the normal distribution,
* Applied Statistics, 26, 118-121.
*
* Wichura, M.J. (1988).
* Algorithm AS 241: The Percentage Points of the Normal Distribution.
* Applied Statistics, 37, 477-484.
*/
phydbl PointNormal (phydbl prob)
{
/* returns z so that Prob{x 0) */
/* r = 1-p;/\* 1-p *\/ */
/* else */
/* r = p_;/\* = R_DT_Iv(p) ^= p *\/ */
/* r = sqrt(-log(r)); */
/* /\* r = sqrt(-log(r)) <==> min(p, 1-p) = exp( - r^2 ) *\/ */
/* if (r <= 5.) { /\* <==> min(p,1-p) >= exp(-25) ~= 1.3888e-11 *\/ */
/* r += -1.6; */
/* val = (((((((r * 7.7454501427834140764e-4 + */
/* .0227238449892691845833) * r + .24178072517745061177) * */
/* r + 1.27045825245236838258) * r + */
/* 3.64784832476320460504) * r + 5.7694972214606914055) * */
/* r + 4.6303378461565452959) * r + */
/* 1.42343711074968357734) */
/* / (((((((r * */
/* 1.05075007164441684324e-9 + 5.475938084995344946e-4) * */
/* r + .0151986665636164571966) * r + */
/* .14810397642748007459) * r + .68976733498510000455) * */
/* r + 1.6763848301838038494) * r + */
/* 2.05319162663775882187) * r + 1.); */
/* } */
/* else */
/* { /\* very close to 0 or 1 *\/ */
/* r += -5.; */
/* val = (((((((r * 2.01033439929228813265e-7 + */
/* 2.71155556874348757815e-5) * r + */
/* .0012426609473880784386) * r + .026532189526576123093) * */
/* r + .29656057182850489123) * r + */
/* 1.7848265399172913358) * r + 5.4637849111641143699) * */
/* r + 6.6579046435011037772) */
/* / (((((((r * */
/* 2.04426310338993978564e-15 + 1.4215117583164458887e-7)* */
/* r + 1.8463183175100546818e-5) * r + */
/* 7.868691311456132591e-4) * r + .0148753612908506148525) */
/* * r + .13692988092273580531) * r + */
/* .59983220655588793769) * r + 1.); */
/* } */
/* if(q < 0.0) */
/* val = -val; */
/* /\* return (q >= 0.)? r : -r ;*\/ */
/* } */
/* return (phydbl)val; */
/* } */
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
/* MISCs */
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
phydbl Bico(int n, int k)
{
return FLOOR(0.5+EXP(Factln(n)-Factln(k)-Factln(n-k)));
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
phydbl Factln(int n)
{
static phydbl a[101];
if (n < 0) { Warn_And_Exit("\n. Err: negative factorial in routine FACTLN"); }
if (n <= 1) return 0.0;
if (n <= 100) return (a[n]>SMALL) ? a[n] : (a[n]=Gammln(n+1.0));
else return Gammln(n+1.0);
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
phydbl Gammln(phydbl xx)
{
double x,tmp,ser;
static double cof[6]={76.18009173,-86.50532033,24.01409822,
-1.231739516,0.120858003e-2,-0.536382e-5};
int j;
x=xx-1.0;
tmp=x+5.5;
tmp -= (x+0.5)*log(tmp);
ser=1.0;
for (j=0;j<=5;j++)
{
x += 1.0;
ser += cof[j]/x;
}
return (phydbl)(-tmp+log(2.50662827465*ser));
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
/* void Plim_Binom(phydbl pH0, int N, phydbl *pinf, phydbl *psup) */
/* { */
/* *pinf = pH0 - 1.64*SQRT(pH0*(1-pH0)/(phydbl)N); */
/* if(*pinf < 0) *pinf = .0; */
/* *psup = pH0 + 1.64*SQRT(pH0*(1-pH0)/(phydbl)N); */
/* } */
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
phydbl LnGamma (phydbl alpha)
{
/* returns ln(gamma(alpha)) for alpha>0, accurate to 10 decimal places.
Stirling's formula is used for the central polynomial part of the procedure.
Pike MC & Hill ID (1966) Algorithm 291: Logarithm of the gamma function.
Communications of the Association for Computing Machinery, 9:684
*/
double x=alpha, f=0, z;
if (x<7) {
f=1; z=x-1;
while (++z<7) f*=z;
x=z; f=-log(f);
}
z = 1/(x*x);
return (phydbl)(f + (x-0.5)*log(x) - x + .918938533204673
+ (((-.000595238095238*z+.000793650793651)*z-.002777777777778)*z
+.083333333333333)/x);
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
phydbl IncompleteGamma(phydbl x, phydbl alpha, phydbl ln_gamma_alpha)
{
/* returns the incomplete gamma ratio I(x,alpha) where x is the upper
limit of the integration and alpha is the shape parameter.
returns (-1) if in error
ln_gamma_alpha = ln(Gamma(alpha)), is almost redundant.
(1) series expansion if (alpha>x || x<=1)
(2) continued fraction otherwise
RATNEST FORTRAN by
Bhattacharjee GP (1970) The incomplete gamma integral. Applied Statistics,
19: 285-287 (AS32)
*/
int i;
double p=alpha, g=ln_gamma_alpha;
double accurate=1e-8, overflow=1e30;
double factor, gin=0, rn=0, a=0,b=0,an=0,dif=0, term=0, pn[6];
if (fabs(x) < SMALL) return ((phydbl).0);
if (x<0 || p<=0) return ((phydbl)-1);
factor=exp(p*log(x)-x-g);
if (x>1 && x>=p) goto l30;
/* (1) series expansion */
gin=1; term=1; rn=p;
l20:
rn++;
term*=x/rn; gin+=term;
if (term > accurate) goto l20;
gin*=factor/p;
goto l50;
l30:
/* (2) continued fraction */
a=1-p; b=a+x+1; term=0;
pn[0]=1; pn[1]=x; pn[2]=x+1; pn[3]=x*b;
gin=pn[2]/pn[3];
l32:
a++; b+=2; term++; an=a*term;
for (i=0; i<2; i++) pn[i+4]=b*pn[i+2]-an*pn[i];
if (fabs(pn[5]) < .0) goto l35;
rn=pn[4]/pn[5]; dif=fabs(gin-rn);
if (dif>accurate) goto l34;
if (dif<=accurate*rn) goto l42;
l34:
gin=rn;
l35:
for (i=0; i<4; i++) pn[i]=pn[i+2];
if (fabs(pn[4]) < overflow) goto l32;
for (i=0; i<4; i++) pn[i]/=overflow;
goto l32;
l42:
gin=1-factor*gin;
l50:
return (phydbl)(gin);
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
int DiscreteGamma (phydbl freqK[], phydbl rK[],
phydbl alfa, phydbl beta, int K, int median)
{
/* discretization of gamma distribution with equal proportions in each
category
*/
int i;
phydbl gap05=1.0/(2.0*K), t, factor=alfa/beta*K, lnga1;
if(K==1)
{
freqK[0] = 1.0;
rK[0] = 1.0;
return 0;
}
if (median)
{
for (i=0; i n) return(0);
if (k > n/2) k = n-k;
if(!k) return(1);
accum = 1.;
for(i=1;in_otu-3;
cov = (phydbl *)mCalloc(dim*dim,sizeof(phydbl));
mean = (phydbl *)mCalloc( dim,sizeof(phydbl));
ori_wght = (int *)mCalloc(tree->data->crunch_len,sizeof(int));
site_num = (int *)mCalloc(tree->data->init_len,sizeof(int));
var_min = 1./POW(tree->data->init_len,2);
For(i,tree->data->crunch_len) ori_wght[i] = tree->data->wght[i];
n_site = 0;
For(i,tree->data->crunch_len) For(j,tree->data->wght[i])
{
site_num[n_site] = i;
n_site++;
}
tree->mod->s_opt->print = 0;
For(replicate,sample_size)
{
For(i,2*tree->n_otu-3) tree->t_edges[i]->l = .1;
For(i,tree->data->crunch_len) tree->data->wght[i] = 0;
For(i,tree->data->init_len)
{
position = Rand_Int(0,(int)(tree->data->init_len-1.0));
tree->data->wght[site_num[position]] += 1;
}
Round_Optimize(tree,tree->data,ROUND_MAX);
For(i,2*tree->n_otu-3) For(j,2*tree->n_otu-3) cov[i*dim+j] += LOG(tree->t_edges[i]->l) * LOG(tree->t_edges[j]->l);
For(i,2*tree->n_otu-3) mean[i] += LOG(tree->t_edges[i]->l);
PhyML_Printf("[%3d/%3d]",replicate,sample_size); fflush(NULL);
/* PhyML_Printf("\n. %3d %12f %12f %12f ", */
/* replicate, */
/* cov[1*dim+1]/(replicate+1)-mean[1]*mean[1]/POW(replicate+1,2), */
/* tree->t_edges[1]->l, */
/* mean[1]/(replicate+1)); */
}
For(i,2*tree->n_otu-3) mean[i] /= (phydbl)sample_size;
For(i,2*tree->n_otu-3) For(j,2*tree->n_otu-3) cov[i*dim+j] /= (phydbl)sample_size;
For(i,2*tree->n_otu-3) For(j,2*tree->n_otu-3) cov[i*dim+j] -= mean[i]*mean[j];
/* For(i,2*tree->n_otu-3) if(cov[i*dim+i] < var_min) cov[i*dim+i] = var_min; */
/* PhyML_Printf("\n"); */
/* For(i,2*tree->n_otu-3) PhyML_Printf("%f %f\n",mean[i],tree->t_edges[i]->l); */
/* PhyML_Printf("\n"); */
/* PhyML_Printf("\n"); */
/* For(i,2*tree->n_otu-3) */
/* { */
/* For(j,2*tree->n_otu-3) */
/* { */
/* PhyML_Printf("%G\n",cov[i*dim+j]); */
/* } */
/* PhyML_Printf("\n"); */
/* } */
For(i,tree->data->crunch_len) tree->data->wght[i] = ori_wght[i];
Free(mean);
Free(ori_wght);
Free(site_num);
return cov;
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
/* Work out the Hessian for the likelihood function. Only branch lengths are considered as variable.
This function is very much inspired from Jeff Thorne's 'hessian' function in his program 'estbranches'. */
phydbl *Hessian(t_tree *tree)
{
phydbl *hessian;
phydbl *plus_plus, *minus_minus, *plus_zero, *minus_zero, *plus_minus, zero_zero;
phydbl *ori_bl,*inc,*buff;
int *ok_edges,*is_ok;
int dim;
int n_ok_edges;
int i,j;
phydbl eps;
phydbl lk;
phydbl lnL,lnL1,lnL2,ori_lnL;
phydbl l_inf;
dim = 2*tree->n_otu-3;
eps = (tree->mod->log_l == YES)?(0.2):(1E-4);
hessian = (phydbl *)mCalloc((int)dim*dim,sizeof(phydbl));
ori_bl = (phydbl *)mCalloc((int)dim,sizeof(phydbl));
plus_plus = (phydbl *)mCalloc((int)dim*dim,sizeof(phydbl));
minus_minus = (phydbl *)mCalloc((int)dim*dim,sizeof(phydbl));
plus_minus = (phydbl *)mCalloc((int)dim*dim,sizeof(phydbl));
plus_zero = (phydbl *)mCalloc((int)dim ,sizeof(phydbl));
minus_zero = (phydbl *)mCalloc((int)dim ,sizeof(phydbl));
inc = (phydbl *)mCalloc((int)dim ,sizeof(phydbl));
buff = (phydbl *)mCalloc((int)dim*dim,sizeof(phydbl));
ok_edges = (int *)mCalloc((int)dim,sizeof(int));
is_ok = (int *)mCalloc((int)dim,sizeof(int));
lnL = lnL1 = lnL2 = UNLIKELY;
tree->both_sides = 1;
Lk(tree);
ori_lnL = tree->c_lnL;
For(i,dim) ori_bl[i] = tree->t_edges[i]->l;
if(tree->mod->log_l == NO)
l_inf = MAX(tree->mod->l_min,1./(phydbl)tree->data->init_len);
else
l_inf = MAX(tree->mod->l_min,-LOG((phydbl)tree->data->init_len));
n_ok_edges = 0;
For(i,dim)
{
if(tree->t_edges[i]->l*(1.-eps) > l_inf)
{
inc[i] = eps * tree->t_edges[i]->l;
ok_edges[n_ok_edges] = i;
n_ok_edges++;
is_ok[i] = 1;
}
else
{
inc[i] = -1.0;
is_ok[i] = 0;
}
}
/* Fine tune the increments */
For(i,dim)
{
do
{
tree->t_edges[i]->l += inc[i];
lnL1 = Lk_At_Given_Edge(tree->t_edges[i],tree);
tree->t_edges[i]->l = ori_bl[i];
inc[i] *= 1.1;
}while((FABS(lnL1 - ori_lnL) < 1.E-1) &&
(tree->t_edges[i]->l+inc[i] < tree->mod->l_max));
inc[i] /= 1.1;
}
/* zero zero */
zero_zero = tree->c_lnL;
/* plus zero */
For(i,dim)
{
if(is_ok[i])
{
tree->t_edges[i]->l += inc[i];
lk = Lk_At_Given_Edge(tree->t_edges[i],tree);
plus_zero[i] = lk;
tree->t_edges[i]->l = ori_bl[i];
}
}
/* minus zero */
For(i,dim)
{
if(is_ok[i])
{
tree->t_edges[i]->l -= inc[i];
lk = Lk_At_Given_Edge(tree->t_edges[i],tree);
minus_zero[i] = lk;
tree->t_edges[i]->l = ori_bl[i];
}
}
For(i,dim) Update_PMat_At_Given_Edge(tree->t_edges[i],tree);
/* plus plus */
For(i,dim)
{
if(is_ok[i])
{
tree->t_edges[i]->l += inc[i];
Update_PMat_At_Given_Edge(tree->t_edges[i],tree);
For(j,3)
if((!tree->t_edges[i]->left->tax) && (tree->t_edges[i]->left->v[j] != tree->t_edges[i]->rght))
Recurr_Hessian(tree->t_edges[i]->left,tree->t_edges[i]->left->v[j],1,inc,plus_plus+i*dim,is_ok,tree);
For(j,3)
if((!tree->t_edges[i]->rght->tax) && (tree->t_edges[i]->rght->v[j] != tree->t_edges[i]->left))
Recurr_Hessian(tree->t_edges[i]->rght,tree->t_edges[i]->rght->v[j],1,inc,plus_plus+i*dim,is_ok,tree);
tree->t_edges[i]->l = ori_bl[i];
Lk(tree);
}
}
/* plus minus */
For(i,dim)
{
if(is_ok[i])
{
tree->t_edges[i]->l += inc[i];
Update_PMat_At_Given_Edge(tree->t_edges[i],tree);
For(j,3)
if((!tree->t_edges[i]->left->tax) && (tree->t_edges[i]->left->v[j] != tree->t_edges[i]->rght))
Recurr_Hessian(tree->t_edges[i]->left,tree->t_edges[i]->left->v[j],-1,inc,plus_minus+i*dim,is_ok,tree);
For(j,3)
if((!tree->t_edges[i]->rght->tax) && (tree->t_edges[i]->rght->v[j] != tree->t_edges[i]->left))
Recurr_Hessian(tree->t_edges[i]->rght,tree->t_edges[i]->rght->v[j],-1,inc,plus_minus+i*dim,is_ok,tree);
tree->t_edges[i]->l = ori_bl[i];
Lk(tree);
}
}
/* minus minus */
For(i,dim)
{
if(is_ok[i])
{
tree->t_edges[i]->l -= inc[i];
Update_PMat_At_Given_Edge(tree->t_edges[i],tree);
For(j,3)
if((!tree->t_edges[i]->left->tax) && (tree->t_edges[i]->left->v[j] != tree->t_edges[i]->rght))
Recurr_Hessian(tree->t_edges[i]->left,tree->t_edges[i]->left->v[j],-1,inc,minus_minus+i*dim,is_ok,tree);
For(j,3)
if((!tree->t_edges[i]->rght->tax) && (tree->t_edges[i]->rght->v[j] != tree->t_edges[i]->left))
Recurr_Hessian(tree->t_edges[i]->rght,tree->t_edges[i]->rght->v[j],-1,inc,minus_minus+i*dim,is_ok,tree);
tree->t_edges[i]->l = ori_bl[i];
Lk(tree);
}
}
For(i,dim)
{
if(is_ok[i])
{
hessian[i*dim+i] = (plus_zero[i]-2*zero_zero+minus_zero[i])/(POW(inc[i],2));
for(j=i+1;jdata->init_len; */
/* Approximate variance for very short branches */
For(i,dim)
if(inc[i] < 0.0 || hessian[i*dim+i] < MIN_VAR_BL)
{
eps = 0.2 * tree->t_edges[i]->l;
do
{
lnL = Lk_At_Given_Edge(tree->t_edges[i],tree);
tree->t_edges[i]->l += eps;
lnL1 = Lk_At_Given_Edge(tree->t_edges[i],tree);
tree->t_edges[i]->l += eps;
lnL2 = Lk_At_Given_Edge(tree->t_edges[i],tree);
tree->t_edges[i]->l -= 2.*eps;
hessian[i*dim+i] = (lnL2 - 2.*lnL1 + lnL) / POW(eps,2);
/* printf("\n* l=%G eps=%f lnL=%f lnL1=%f lnL2=%f var=%f",tree->t_edges[i]->l,eps,lnL,lnL1,lnL2,hessian[i*dim+i]); */
eps *= 5.;
}while(FABS(lnL2 - lnL) < 1.E-3);
hessian[i*dim+i] = -1.0 / hessian[i*dim+i];
}
/* Fit a straight line to the log-likelihood (i.e., an exponential to the likelihood) */
/* It is only a straight line when considering branch length (rather than log(branch lengths)) */
For(i,dim)
if((tree->t_edges[i]->l / tree->mod->l_min < 1.1) &&
(tree->t_edges[i]->l / tree->mod->l_min > 0.9))
{
phydbl *x,*y,l;
phydbl cov,var;
x=plus_plus;
y=minus_minus;
l=(tree->mod->log_l == YES)?(EXP(tree->t_edges[i]->l)):(tree->t_edges[i]->l); /* Get actual branch length */
For(j,dim)
{
x[j] = l + (100.*l-l)*((phydbl)j/dim);
tree->t_edges[i]->l = (tree->mod->log_l)?(LOG(x[j])):(x[j]); /* Transform to log if necessary */
y[j] = Lk_At_Given_Edge(tree->t_edges[i],tree);
tree->t_edges[i]->l = (tree->mod->log_l)?(LOG(l)):(l); /* Go back to initial edge length */
}
cov = Covariance(x,y,dim);
var = Covariance(x,x,dim);
/* cov/var is minus the parameter of the exponential distribution.
The variance is therefore : */
hessian[i*dim+i] = 1.0 / pow(cov/var,2);
/* printf("\n. Hessian = %G cov=%G var=%G",hessian[i*dim+i],cov,var); */
}
/* } */
For(i,dim)
if(hessian[i*dim+i] < 0.0)
{
PhyML_Printf("\n. l=%G var=%G",tree->t_edges[i]->l,hessian[i*dim+i]);
/* PhyML_Printf("\n. Err in file %s at line %d\n",__FILE__,__LINE__); */
/* Exit("\n"); */
hessian[i*dim+i] = MIN_VAR_BL;
}
For(i,dim)
{
if(hessian[i*dim+i] < MIN_VAR_BL)
{
PhyML_Printf("\n. l=%10G var(l)=%12G. WARNING: numerical precision issues may affect this analysis.",
tree->t_edges[i]->l,hessian[i*dim+i]);
hessian[i*dim+i] = MIN_VAR_BL;
}
if(hessian[i*dim+i] > MAX_VAR_BL)
{
PhyML_Printf("\n. l=%10G var(l)=%12G. WARNING: numerical precision issues may affect this analysis.",
tree->t_edges[i]->l,hessian[i*dim+i]);
hessian[i*dim+i] = MAX_VAR_BL;
}
}
Iter_Matinv(hessian,dim,dim,NO);
For(i,dim*dim) hessian[i] = -1.0*hessian[i];
For(i,dim)
{
For(j,dim)
{
if(FABS(hessian[i*dim+j]-hessian[j*dim+i]) > 1.E-3)
{
PhyML_Printf("\n. Hessian not symmetrical.");
PhyML_Printf("\n. Err in file %s at line %d\n",__FILE__,__LINE__);
Exit("\n");
}
hessian[i*dim+j] = (hessian[i*dim+j] + hessian[j*dim+i]) / 2.;
hessian[j*dim+i] = hessian[i*dim+j];
}
}
/* printf("\n"); */
/* printf("HESSIAN\n"); */
/* For(i,dim) */
/* { */
/* PhyML_Printf("[%f] ",tree->t_edges[i]->l); */
/* For(j,dim) */
/* { */
/* PhyML_Printf("%12lf ",hessian[i*dim+j]); */
/* } */
/* PhyML_Printf("\n"); */
/* } */
/* Matinv(hessian,dim,dim,NO); */
/* PhyML_Printf("\n"); */
/* For(i,dim) */
/* { */
/* PhyML_Printf("[%f] ",tree->t_edges[i]->l); */
/* For(j,dim) */
/* { */
/* PhyML_Printf("%12G ",-hessian[i*dim+j]); */
/* } */
/* PhyML_Printf("\n"); */
/* } */
/* Exit("\n"); */
/* Make sure to update likelihood before bailing out */
tree->both_sides = YES;
Lk(tree);
Free(ori_bl);
Free(plus_plus);
Free(minus_minus);
Free(plus_zero);
Free(minus_zero);
Free(plus_minus);
Free(inc);
Free(buff);
Free(ok_edges);
Free(is_ok);
return hessian;
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
/* Work out the gradient for the likelihood function. Only branch lengths are considered as variable.
*/
phydbl *Gradient(t_tree *tree)
{
phydbl *gradient;
phydbl *plus, *minus;
phydbl *ori_bl,*inc;
int *is_ok;
int dim;
int n_ok_edges;
int i;
phydbl eps;
phydbl lk;
phydbl lnL,lnL1,lnL2;
phydbl l_inf;
dim = 2*tree->n_otu-3;
eps = (tree->mod->log_l == YES)?(0.2):(1.E-6);
gradient = (phydbl *)mCalloc((int)dim,sizeof(phydbl));
ori_bl = (phydbl *)mCalloc((int)dim,sizeof(phydbl));
plus = (phydbl *)mCalloc((int)dim,sizeof(phydbl));
minus = (phydbl *)mCalloc((int)dim,sizeof(phydbl));
inc = (phydbl *)mCalloc((int)dim ,sizeof(phydbl));
is_ok = (int *)mCalloc((int)dim,sizeof(int));
lnL = lnL1 = lnL2 = UNLIKELY;
tree->both_sides = 1;
Lk(tree);
For(i,dim) ori_bl[i] = tree->t_edges[i]->l;
if(tree->mod->log_l == NO)
l_inf = MAX(tree->mod->l_min,1./(phydbl)tree->data->init_len);
else
l_inf = MAX(tree->mod->l_min,-LOG((phydbl)tree->data->init_len));
n_ok_edges = 0;
For(i,dim)
{
if(tree->t_edges[i]->l*(1.-eps) > l_inf)
{
inc[i] = eps * tree->t_edges[i]->l;
is_ok[i] = YES;
}
else
{
inc[i] = -1.0;
is_ok[i] = NO;
}
}
/* plus */
For(i,dim)
{
if(is_ok[i] == YES)
{
tree->t_edges[i]->l += inc[i];
lk = Lk_At_Given_Edge(tree->t_edges[i],tree);
plus[i] = lk;
tree->t_edges[i]->l = ori_bl[i];
}
}
/* minus */
For(i,dim)
{
if(is_ok[i] == YES)
{
tree->t_edges[i]->l -= inc[i];
lk = Lk_At_Given_Edge(tree->t_edges[i],tree);
minus[i] = lk;
tree->t_edges[i]->l = ori_bl[i];
}
}
For(i,dim)
{
if(is_ok[i] == YES)
{
gradient[i] = (plus[i] - minus[i])/(2.*inc[i]);
}
}
For(i,dim)
{
if(is_ok[i] == NO)
{
eps = FABS(0.2 * tree->t_edges[i]->l);
lnL = Lk_At_Given_Edge(tree->t_edges[i],tree);
tree->t_edges[i]->l += eps;
lnL1 = Lk_At_Given_Edge(tree->t_edges[i],tree);
tree->t_edges[i]->l += eps;
lnL2 = Lk_At_Given_Edge(tree->t_edges[i],tree);
tree->t_edges[i]->l -= eps;
tree->t_edges[i]->l -= eps;
gradient[i] = (4.*lnL1 - lnL2 - 3.*lnL) / (2.*eps);
}
}
/* Make sure to update likelihood before bailing out */
tree->both_sides = YES;
Lk(tree);
Free(ori_bl);
Free(plus);
Free(minus);
Free(inc);
Free(is_ok);
/* printf("\n"); */
/* printf("GRADIENT\n"); */
/* For(i,dim) */
/* { */
/* PhyML_Printf("[%f] ",tree->t_edges[i]->l); */
/* For(j,dim) */
/* { */
/* printf("%12lf ",gradient[i]*gradient[j]); */
/* } */
/* printf("\n"); */
/* } */
/* printf("\n"); */
/* For(i,dim) */
/* { */
/* PhyML_Printf("[%f] [%f]\n",tree->t_edges[i]->l,gradient[i]); */
/* } */
/* Exit("\n"); */
return gradient;
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
/* Work out the Hessian for the likelihood function using the method described by Seo et al., 2004, MBE.
Corresponds to the outer product of the scores approach described in Porter, 2002. (matrix J1)
*/
phydbl *Hessian_Seo(t_tree *tree)
{
phydbl *hessian,*site_hessian;
phydbl *gradient;
phydbl *plus, *minus, *plusplus, *zero;
phydbl *ori_bl,*inc_plus,*inc_minus,*inc;
int *is_ok;
int dim;
int n_ok_edges;
int i,j,k;
phydbl eps;
phydbl ori_lnL,lnL,lnL1,lnL2;
phydbl l_inf;
int l,n;
phydbl small_var;
dim = 2*tree->n_otu-3;
eps = (tree->mod->log_l == YES)?(0.2):(1.E-4);
hessian = (phydbl *)mCalloc((int)dim*dim,sizeof(phydbl));
site_hessian = (phydbl *)mCalloc((int)dim*dim,sizeof(phydbl));
gradient = (phydbl *)mCalloc((int)dim,sizeof(phydbl));
ori_bl = (phydbl *)mCalloc((int)dim,sizeof(phydbl));
plus = (phydbl *)mCalloc((int)dim*tree->n_pattern,sizeof(phydbl));
plusplus = (phydbl *)mCalloc((int)dim*tree->n_pattern,sizeof(phydbl));
minus = (phydbl *)mCalloc((int)dim*tree->n_pattern,sizeof(phydbl));
zero = (phydbl *)mCalloc((int)dim*tree->n_pattern,sizeof(phydbl));
inc_plus = (phydbl *)mCalloc((int)dim,sizeof(phydbl));
inc_minus = (phydbl *)mCalloc((int)dim,sizeof(phydbl));
inc = (phydbl *)mCalloc((int)dim,sizeof(phydbl));
is_ok = (int *)mCalloc((int)dim,sizeof(int));
lnL = lnL1 = lnL2 = UNLIKELY;
tree->both_sides = YES;
Lk(tree);
ori_lnL = tree->c_lnL;
For(i,dim) ori_bl[i] = tree->t_edges[i]->l;
if(tree->mod->log_l == NO)
l_inf = MAX(tree->mod->l_min,1./(phydbl)tree->data->init_len);
else
l_inf = MAX(tree->mod->l_min,-LOG((phydbl)tree->data->init_len));
n_ok_edges = 0;
For(i,dim)
{
if(tree->t_edges[i]->l*(1.-eps) > l_inf)
{
inc_plus[i] = FABS(eps * tree->t_edges[i]->l);
inc_minus[i] = FABS(eps * tree->t_edges[i]->l);
is_ok[i] = YES;
}
else
{
inc_plus[i] = FABS(0.2 * tree->t_edges[i]->l);
inc_minus[i] = FABS(0.2 * tree->t_edges[i]->l);
is_ok[i] = NO;
}
}
/* Fine tune the increments */
For(i,dim)
{
do
{
tree->t_edges[i]->l += inc_plus[i];
lnL1 = Lk_At_Given_Edge(tree->t_edges[i],tree);
tree->t_edges[i]->l = ori_bl[i];
inc_plus[i] *= 1.1;
}while((FABS(lnL1 - ori_lnL) < 1.E-1) &&
(tree->t_edges[i]->l+inc_plus[i] < tree->mod->l_max));
inc_plus[i] /= 1.1;
}
For(i,dim)
{
do
{
tree->t_edges[i]->l -= inc_minus[i];
lnL1 = Lk_At_Given_Edge(tree->t_edges[i],tree);
tree->t_edges[i]->l = ori_bl[i];
inc_minus[i] *= 1.1;
}while((FABS(lnL1 - ori_lnL) < 1.E-1) &&
(tree->t_edges[i]->l-inc_minus[i] > tree->mod->l_min));
inc_minus[i] /= 1.1;
}
For(i,dim)
{
inc[i] = MIN(inc_plus[i],inc_minus[i]);
}
/* plus */
For(i,dim)
{
if(is_ok[i] == YES)
{
tree->t_edges[i]->l += inc[i];
lnL = Lk_At_Given_Edge(tree->t_edges[i],tree);
For(j,tree->n_pattern) plus[i*tree->n_pattern+j] = tree->cur_site_lk[j];
tree->t_edges[i]->l = ori_bl[i];
}
}
/* minus */
For(i,dim)
{
if(is_ok[i] == YES)
{
tree->t_edges[i]->l -= inc[i];
lnL = Lk_At_Given_Edge(tree->t_edges[i],tree);
For(j,tree->n_pattern) minus[i*tree->n_pattern+j] = tree->cur_site_lk[j];
tree->t_edges[i]->l = ori_bl[i];
}
}
For(i,dim)
{
if(is_ok[i] == NO)
{
lnL = Lk_At_Given_Edge(tree->t_edges[i],tree);
For(j,tree->n_pattern) zero[i*tree->n_pattern+j] = tree->cur_site_lk[j];
tree->t_edges[i]->l += inc[i];
lnL1 = Lk_At_Given_Edge(tree->t_edges[i],tree);
For(j,tree->n_pattern) plus[i*tree->n_pattern+j] = tree->cur_site_lk[j];
tree->t_edges[i]->l += inc[i];
lnL2 = Lk_At_Given_Edge(tree->t_edges[i],tree);
For(j,tree->n_pattern) plusplus[i*tree->n_pattern+j] = tree->cur_site_lk[j];
tree->t_edges[i]->l = ori_bl[i];
}
}
For(i,dim*dim) hessian[i] = 0.0;
For(k,tree->n_pattern)
{
For(i,dim)
{
if(is_ok[i] == YES)
gradient[i] = (plus[i*tree->n_pattern+k] - minus[i*tree->n_pattern+k])/(inc[i] + inc[i]);
else
gradient[i] = (4.*plus[i*tree->n_pattern+k] - plusplus[i*tree->n_pattern+k] - 3.*zero[i*tree->n_pattern+k])/(inc[i] + inc[i]);
/* if(is_ok[i] == NO) */
/* printf("\n. i=%d site=%d l=%G plus=%G plusplus=%G zero=%G num=%f grad=%G", */
/* i,k,tree->t_edges[i]->l, */
/* plus[i*tree->n_pattern+k],plusplus[i*tree->n_pattern+k],zero[i*tree->n_pattern+k], */
/* (4.*plus[i*tree->n_pattern+k] - plusplus[i*tree->n_pattern+k] - 3.*zero[i*tree->n_pattern+k]), */
/* gradient[i]); */
}
For(i,dim) For(j,dim) site_hessian[i*dim+j] = gradient[i] * gradient[j];
For(i,dim*dim) hessian[i] -= site_hessian[i] * tree->data->wght[k];
}
/* Make sure to update likelihood before bailing out */
tree->both_sides = YES;
Lk(tree);
l = tree->data->init_len;
n = tree->mod->ns;
/* Delta method for variance. Assume Jukes and Cantor with p=1/n */
small_var = (1./(l*l))*(1.-1./l)*(n-1.)*(n-1.)/(n-1.-n/l);
For(i,dim)
if(is_ok[i] == NO)
{
For(j,dim)
{
hessian[i*dim+j] = 0.;
hessian[j*dim+i] = 0.;
}
hessian[i*dim+i] = -1./small_var;
if(tree->mod->log_l == YES)
{
hessian[i*dim+i] = small_var * POW(EXP(tree->t_edges[i]->l),-2);
hessian[i*dim+i] = -1./hessian[i*dim+i];
}
}
For(i,dim)
if(is_ok[i] == YES && hessian[i*dim+i] < -1./small_var)
{
For(j,dim)
{
hessian[i*dim+j] = 0.;
hessian[j*dim+i] = 0.;
}
hessian[i*dim+i] = -1./small_var;
if(tree->mod->log_l == YES)
{
hessian[i*dim+i] = small_var * POW(EXP(tree->t_edges[i]->l),-2);
hessian[i*dim+i] = -1./hessian[i*dim+i];
}
}
For(i,dim)
{
For(j,dim)
{
if(FABS(hessian[i*dim+j]-hessian[j*dim+i]) > 1.E-3)
{
PhyML_Printf("\n. Hessian not symmetrical.");
PhyML_Printf("\n. Err in file %s at line %d\n",__FILE__,__LINE__);
Exit("\n");
}
hessian[i*dim+j] = (hessian[i*dim+j] + hessian[j*dim+i]) / 2.;
hessian[j*dim+i] = hessian[i*dim+j];
}
}
/* printf("\n"); */
/* printf("HESSIAN SEO\n"); */
/* For(i,dim) */
/* { */
/* PhyML_Printf("[%f] ",tree->t_edges[i]->l); */
/* For(j,dim) */
/* { */
/* PhyML_Printf("%12lf ",hessian[i*dim+j]); */
/* } */
/* PhyML_Printf("\n"); */
/* } */
Free(site_hessian);
Free(ori_bl);
Free(plus);
Free(minus);
Free(plusplus);
Free(zero);
Free(inc);
Free(inc_plus);
Free(inc_minus);
Free(is_ok);
Free(gradient);
return hessian;
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void Recurr_Hessian(t_node *a, t_node *d, int plus_minus, phydbl *inc, phydbl *res, int *is_ok, t_tree *tree)
{
int i;
phydbl ori_l;
For(i,3)
if(a->v[i] == d)
{
Update_P_Lk(tree,a->b[i],a);
ori_l = a->b[i]->l;
if(is_ok[a->b[i]->num])
{
if(plus_minus > 0) a->b[i]->l += inc[a->b[i]->num];
else a->b[i]->l -= inc[a->b[i]->num];
res[a->b[i]->num] = Lk_At_Given_Edge(a->b[i],tree);
a->b[i]->l = ori_l;
Update_PMat_At_Given_Edge(a->b[i],tree);
}
break;
}
if(d->tax) return;
else
For(i,3)
if(d->v[i] != a)
Recurr_Hessian(d,d->v[i],plus_minus,inc,res,is_ok,tree);
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
/* Work out the Hessian for the likelihood function. Only LOGARITHM of branch lengths are considered as variable.
This function is very much inspired from Jeff Thorne's 'hessian' function in his program 'estbranches'. */
phydbl *Hessian_Log(t_tree *tree)
{
phydbl *hessian;
phydbl *plus_plus, *minus_minus, *plus_zero, *minus_zero, *plus_minus, *zero_zero;
phydbl *ori_bl,*inc,*buff;
int *ok_edges,*is_ok;
int dim;
int n_ok_edges;
int i,j;
phydbl eps;
phydbl lk;
dim = 2*tree->n_otu-3;
eps = 1.E-4;
hessian = (phydbl *)mCalloc((int)dim*dim,sizeof(phydbl));
ori_bl = (phydbl *)mCalloc((int)dim, sizeof(phydbl));
plus_plus = (phydbl *)mCalloc((int)dim*dim,sizeof(phydbl));
minus_minus = (phydbl *)mCalloc((int)dim*dim,sizeof(phydbl));
plus_minus = (phydbl *)mCalloc((int)dim*dim,sizeof(phydbl));
plus_zero = (phydbl *)mCalloc((int)dim ,sizeof(phydbl));
minus_zero = (phydbl *)mCalloc((int)dim ,sizeof(phydbl));
zero_zero = (phydbl *)mCalloc((int)dim ,sizeof(phydbl));
inc = (phydbl *)mCalloc((int)dim ,sizeof(phydbl));
buff = (phydbl *)mCalloc((int)dim*dim,sizeof(phydbl));
ok_edges = (int *)mCalloc((int)dim, sizeof(int));
is_ok = (int *)mCalloc((int)dim, sizeof(int));
tree->both_sides = 1;
Lk(tree);
For(i,dim) ori_bl[i] = tree->t_edges[i]->l;
n_ok_edges = 0;
For(i,dim)
{
if(tree->t_edges[i]->l > 3.0/(phydbl)tree->data->init_len)
{
inc[i] = FABS(eps * tree->t_edges[i]->l);
ok_edges[n_ok_edges] = i;
n_ok_edges++;
is_ok[i] = 1;
}
else is_ok[i] = 0;
}
/* zero zero */
lk = Log_Det(is_ok,tree);
For(i,dim) if(is_ok[i]) zero_zero[i] = tree->c_lnL+lk;
/* plus zero */
For(i,dim)
{
if(is_ok[i])
{
tree->t_edges[i]->l += inc[i];
lk = Lk_At_Given_Edge(tree->t_edges[i],tree);
plus_zero[i] = lk+Log_Det(is_ok,tree);
tree->t_edges[i]->l = ori_bl[i];
}
}
/* minus zero */
For(i,dim)
{
if(is_ok[i])
{
tree->t_edges[i]->l -= inc[i];
lk = Lk_At_Given_Edge(tree->t_edges[i],tree);
minus_zero[i] = lk+Log_Det(is_ok,tree);
tree->t_edges[i]->l = ori_bl[i];
}
}
For(i,dim) Update_PMat_At_Given_Edge(tree->t_edges[i],tree);
/* plus plus */
For(i,dim)
{
if(is_ok[i])
{
tree->t_edges[i]->l += inc[i];
Update_PMat_At_Given_Edge(tree->t_edges[i],tree);
For(j,3)
if((!tree->t_edges[i]->left->tax) && (tree->t_edges[i]->left->v[j] != tree->t_edges[i]->rght))
Recurr_Hessian_Log(tree->t_edges[i]->left,tree->t_edges[i]->left->v[j],1,inc,plus_plus+i*dim,is_ok,tree);
For(j,3)
if((!tree->t_edges[i]->rght->tax) && (tree->t_edges[i]->rght->v[j] != tree->t_edges[i]->left))
Recurr_Hessian_Log(tree->t_edges[i]->rght,tree->t_edges[i]->rght->v[j],1,inc,plus_plus+i*dim,is_ok,tree);
/* For(j,dim) */
/* if(j != i) */
/* { */
/* if(inc[j] > 0.0) */
/* { */
/* tree->t_edges[j]->l += inc[j]; */
/* Lk(tree); */
/* plus_plus[i*dim+j]=tree->c_lnL; */
/* tree->t_edges[j]->l = ori_bl[j]; */
/* } */
/* } */
tree->t_edges[i]->l = ori_bl[i];
Lk(tree);
}
}
/* plus minus */
For(i,dim)
{
if(is_ok[i])
{
tree->t_edges[i]->l += inc[i];
Update_PMat_At_Given_Edge(tree->t_edges[i],tree);
For(j,3)
if((!tree->t_edges[i]->left->tax) && (tree->t_edges[i]->left->v[j] != tree->t_edges[i]->rght))
Recurr_Hessian_Log(tree->t_edges[i]->left,tree->t_edges[i]->left->v[j],-1,inc,plus_minus+i*dim,is_ok,tree);
For(j,3)
if((!tree->t_edges[i]->rght->tax) && (tree->t_edges[i]->rght->v[j] != tree->t_edges[i]->left))
Recurr_Hessian_Log(tree->t_edges[i]->rght,tree->t_edges[i]->rght->v[j],-1,inc,plus_minus+i*dim,is_ok,tree);
/* For(j,dim) */
/* if(j != i) */
/* { */
/* if(inc[j] > 0.0) */
/* { */
/* tree->t_edges[j]->l -= inc[j]; */
/* Lk(tree); */
/* plus_minus[i*dim+j] = tree->c_lnL; */
/* tree->t_edges[j]->l = ori_bl[j]; */
/* } */
/* } */
tree->t_edges[i]->l = ori_bl[i];
Lk(tree);
}
}
/* minus minus */
For(i,dim)
{
if(is_ok[i])
{
tree->t_edges[i]->l -= inc[i];
Update_PMat_At_Given_Edge(tree->t_edges[i],tree);
For(j,3)
if((!tree->t_edges[i]->left->tax) && (tree->t_edges[i]->left->v[j] != tree->t_edges[i]->rght))
Recurr_Hessian_Log(tree->t_edges[i]->left,tree->t_edges[i]->left->v[j],-1,inc,minus_minus+i*dim,is_ok,tree);
For(j,3)
if((!tree->t_edges[i]->rght->tax) && (tree->t_edges[i]->rght->v[j] != tree->t_edges[i]->left))
Recurr_Hessian_Log(tree->t_edges[i]->rght,tree->t_edges[i]->rght->v[j],-1,inc,minus_minus+i*dim,is_ok,tree);
/* For(j,dim) */
/* if(j != i) */
/* { */
/* if(inc[j] > 0.0) */
/* { */
/* tree->t_edges[j]->l -= inc[j]; */
/* Lk(tree); */
/* minus_minus[i*dim+j] = tree->c_lnL; */
/* tree->t_edges[j]->l = ori_bl[j]; */
/* } */
/* } */
tree->t_edges[i]->l = ori_bl[i];
Lk(tree);
}
}
/* For(i,dim) if(is_ok[i]) inc[i] = POW(tree->t_edges[i]->l+inc[i],2)-POW(tree->t_edges[i]->l,2); */
For(i,dim) if(is_ok[i]) inc[i] = LOG(tree->t_edges[i]->l+inc[i])-LOG(tree->t_edges[i]->l);
/* For(i,dim) inc[i] = 2.*inc[i]; */
/* For(i,dim) if(is_ok[i]) inc[i] = SQRT(tree->t_edges[i]->l+inc[i])-SQRT(tree->t_edges[i]->l); */
For(i,dim)
{
if(is_ok[i])
{
hessian[i*dim+i] = (plus_zero[i]-2*zero_zero[i]+minus_zero[i])/(POW(inc[i],2));
for(j=i+1;jdata->init_len,2);
}
if(!Matinv(hessian,dim,dim,NO))
{
PhyML_Printf("\n. Err in file %s at line %d\n",__FILE__,__LINE__);
Exit("\n");
}
For(i,dim*dim) hessian[i] = -1.0*hessian[i];
/* For(i,dim) */
/* { */
/* PhyML_Printf("[%f] ",tree->t_edges[i]->l); */
/* For(j,i+1) */
/* { */
/* PhyML_Printf("%12lf ",hessian[i*dim+j]); */
/* } */
/* PhyML_Printf("\n"); */
/* } */
/* Matinv(hessian,dim,dim); */
/* PhyML_Printf("\n"); */
For(i,dim)
{
PhyML_Printf("[%f] ",tree->t_edges[i]->l);
For(j,i+1)
{
PhyML_Printf("%12lf ",hessian[i*dim+j]);
}
PhyML_Printf("\n");
}
/* Exit("\n"); */
Free(ori_bl);
Free(plus_plus);
Free(minus_minus);
Free(plus_zero);
Free(minus_zero);
Free(plus_minus);
Free(zero_zero);
Free(inc);
Free(buff);
Free(ok_edges);
Free(is_ok);
return hessian;
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void Recurr_Hessian_Log(t_node *a, t_node *d, int plus_minus, phydbl *inc, phydbl *res, int *is_ok, t_tree *tree)
{
int i;
phydbl ori_l;
For(i,3)
if(a->v[i] == d)
{
Update_P_Lk(tree,a->b[i],a);
ori_l = a->b[i]->l;
if(is_ok[a->b[i]->num])
{
if(plus_minus > 0) a->b[i]->l += inc[a->b[i]->num];
else a->b[i]->l -= inc[a->b[i]->num];
res[a->b[i]->num] = Lk_At_Given_Edge(a->b[i],tree);
res[a->b[i]->num] += Log_Det(is_ok,tree);
a->b[i]->l = ori_l;
Update_PMat_At_Given_Edge(a->b[i],tree);
}
break;
}
if(d->tax) return;
else
For(i,3)
if(d->v[i] != a)
Recurr_Hessian_Log(d,d->v[i],plus_minus,inc,res,is_ok,tree);
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
phydbl Log_Det(int *is_ok, t_tree *tree)
{
int i;
phydbl ldet;
ldet = 0.0;
/* For(i,2*tree->n_otu-3) if(is_ok[i]) ldet += LOG(2.*SQRT(tree->t_edges[i]->l)); */
For(i,2*tree->n_otu-3) if(is_ok[i]) ldet += LOG(tree->t_edges[i]->l);
/* For(i,2*tree->n_otu-3) if(is_ok[i]) ldet -= LOG(2*tree->t_edges[i]->l); */
return ldet;
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
phydbl Normal_Trunc_Mean(phydbl mu, phydbl sd, phydbl min, phydbl max)
{
phydbl mean;
mean = mu + sd *
(Dnorm((min-mu)/sd,0.,1.)-Dnorm((max-mu)/sd,0.,1.))/
(Pnorm((max-mu)/sd,0.,1.)-Pnorm((min-mu)/sd,0.,1.));
return mean;
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
phydbl Constraint_Normal_Trunc_Mean(phydbl wanted_mu, phydbl sd, phydbl min, phydbl max)
{
int j;
phydbl dx,f,fmid,xmid,rtb;
phydbl x1, x2;
x1 = min;
x2 = max;
f = Normal_Trunc_Mean(x1,sd,min,max) - wanted_mu;
fmid = Normal_Trunc_Mean(x2,sd,min,max) - wanted_mu;
if(f*fmid >= 0.0)
{
PhyML_Printf("\n. Root must be bracketed for bisection!");
PhyML_Printf("\n. f=%f fmid=%f",f,fmid);
PhyML_Printf("\n. Err in file %s at line %d\n",__FILE__,__LINE__);
Exit("\n");
}
rtb = f < 0.0 ? (dx=x2-x1,x1) : (dx=x1-x2,x2);
For(j,100)
{
xmid=rtb+(dx *= 0.5);
fmid=Normal_Trunc_Mean(xmid,sd,min,max)-wanted_mu;
if(fmid <= 0.0) rtb=xmid;
if(fmid > -1.E-10 && fmid < 1.E-10) return rtb;
}
Exit("Too many bisections in RTBIS");
return(-1.);
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
int Matinv(phydbl *x, int n, int m, int verbose)
{
/* x[n*m] ... m>=n
*/
int i,j,k;
int *irow;
phydbl ee, t,t1,xmax;
phydbl det;
ee = 1.0E-10;
det = 1.0;
irow = (int *)mCalloc(n,sizeof(int));
For (i,n)
{
xmax = 0.;
for (j=i; j=0; i--)
{
if (irow[i] == i) continue;
For(j,n)
{
t = x[j*m+i];
x[j*m+i] = x[j*m + irow[i]];
x[j*m + irow[i]] = t;
}
}
Free(irow);
return (1);
/* int i, j, k, lower, upper; */
/* phydbl temp; */
/* phydbl *a; */
/* int nsize; */
/* nsize = n; */
/* a = x; */
/* /\*Gauss-Jordan reduction -- invert matrix a in place, */
/* overwriting previous contents of a. On exit, matrix a */
/* contains the inverse.*\/ */
/* lower = 0; */
/* upper = nsize-1; */
/* for(i = lower; i <= upper; i++) */
/* { */
/* temp = 1.0 / a[i*n+i]; */
/* a[i*n+i] = 1.0; */
/* for (j = lower; j <= upper; j++) */
/* { */
/* a[i*n+j] *= temp; */
/* } */
/* for (j = lower; j <= upper; j++) */
/* { */
/* if (j != i) */
/* { */
/* temp = a[j*n+i]; */
/* a[j*n+i] = 0.0; */
/* for (k = lower; k <= upper; k++) */
/* { */
/* a[j*n+k] -= temp * a[i*n+k]; */
/* } */
/* } */
/* } */
/* } */
return(1);
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
int Iter_Matinv(phydbl *x, int n, int m, int verbose)
{
phydbl *buff;
int i,iter;
phydbl scaler;
int pb;
buff = (phydbl *)mCalloc(n*m,sizeof(phydbl));
pb = NO;
iter = 0;
scaler = 1.;
For(i,n*m) buff[i] = x[i];
while(!Matinv(buff,n,m,verbose))
{
pb = YES;
For(i,n*m) buff[i] = x[i];
scaler *= 10.;
For(i,n*m) buff[i] *= scaler;
iter++;
if(iter > 100)
{
PhyML_Printf("\n. Err in file %s at line %d.",__FILE__,__LINE__);
return 0;
}
}
if(pb) PhyML_Printf("\n. Managed to fix the problem by rescaling the matrix.");
For(i,n*m) x[i] = buff[i]*scaler;
Free(buff);
return 1;
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
phydbl *Matrix_Mult(phydbl *A, phydbl *B, int nra, int nca, int nrb, int ncb)
{
int i,j,k;
phydbl *C;
C = (phydbl *)mCalloc(nra*ncb,sizeof(phydbl));
if(nca != nrb)
{
PhyML_Printf("\n. Matrices dimensions don't match.");
PhyML_Printf("\n. Err in file %s at line %d\n",__FILE__,__LINE__);
Exit("\n");
}
For(i,nra)
For(j,ncb)
For(k,nca)
C[i*ncb+j] += A[i*nca+k] * B[k*ncb+j];
return C;
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
phydbl *Matrix_Transpose(phydbl *A, int dim)
{
phydbl *tA,buff;
int i,j;
tA = (phydbl *)mCalloc(dim*dim,sizeof(phydbl));
For(i,dim*dim) tA[i]=A[i];
For(i,dim) for(j=i+1;j 1.E-3) */
/* { */
/* PhyML_Printf("\n. Err in file %s at line %d\n",__FILE__,__LINE__); */
/* Warn_And_Exit(""); */
/* } */
/* } */
For(i,n)
{
for(j=i+1;j 1.E-3)
{
PhyML_Printf("\n. Err in file %s at line %d\n",__FILE__,__LINE__);
Warn_And_Exit("");
}
}
Free(mu1);
Free(mu2);
Free(sig11);
Free(sig12);
Free(sig21);
Free(sig22);
Free(ctrd_a);
Free(cond_cov_norder);
Free(cond_mu_norder);
Free(sig12_invsig22);
Free(buff_mat);
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
/* http://en.wikipedia.org/wiki/Multivariate_normal_distribution (Conditional distributions) */
void Normal_Conditional_Unsorted(phydbl *mu, phydbl *cov, phydbl *a, int n, short int *is_1, int n1, phydbl *cond_mu, phydbl *cond_cov)
{
phydbl *mu1,*mu2;
phydbl *sig11,*sig12,*sig21,*sig22,*sig12_invsig22,*buff;
phydbl *ctrd_a;
int n2;
int i,j,nr,nc;
n2 = n-n1;
mu1 = (phydbl *)mCalloc(n1, sizeof(phydbl));
mu2 = (phydbl *)mCalloc(n2, sizeof(phydbl));
sig11 = (phydbl *)mCalloc(n1*n1,sizeof(phydbl));
sig12 = (phydbl *)mCalloc(n1*n2,sizeof(phydbl));
sig21 = (phydbl *)mCalloc(n2*n1,sizeof(phydbl));
sig22 = (phydbl *)mCalloc(n2*n2,sizeof(phydbl));
ctrd_a = (phydbl *)mCalloc(n2, sizeof(phydbl));
nr=0;
For(i,n) { if(!is_1[i]) { ctrd_a[nr] = a[i]-mu[i]; nr++; } }
nr=0;
For(i,n) { if( is_1[i]) { mu1[nr] = mu[i]; nr++; } }
nr=0;
For(i,n) { if(!is_1[i]) { mu2[nr] = mu[i]; nr++; } }
nr=0; nc=0;
For(i,n)
{
if(is_1[i])
{
nc = nr;
for(j=i;jrates->cov_l;
mean = tree->rates->mean_l;
dim = 2*tree->n_otu-3;
fp = fopen("covariance","w");
fprintf(fp,"\n");
fprintf(fp,"Run\t");
fprintf(fp,"lnL\t");
For(i,dim) fprintf(fp,"Edge%d[%f]\t",i,tree->rates->u_ml_l[i]);
For(i,dim) mean[i] = .0;
For(i,dim*dim) cov[i] = .0;
MCMC_Randomize_Branch_Lengths(tree);
/* For(i,2*tree->n_otu-3) tree->t_edges[i]->l *= Rgamma(5.,1./5.); */
tree->both_sides = YES;
Lk(tree);
iter = 0;
do
{
/* tree->both_sides = YES; */
/* Lk(tree); */
MCMC_Br_Lens(tree);
/* MCMC_Scale_Br_Lens(tree); */
max_diff_mean = 0.0;
For(i,dim)
{
cur_mean = mean[i];
mean[i] *= (phydbl)iter;
mean[i] += tree->t_edges[i]->l;
mean[i] /= (phydbl)(iter+1);
new_mean = mean[i];
diff_mean = MAX(cur_mean,new_mean)/MIN(cur_mean,new_mean);
if(diff_mean > max_diff_mean) max_diff_mean = diff_mean;
/* printf("\n. %d diff_mean = %f %f %f %f",i,diff_mean,cur_mean,new_mean,tree->t_edges[i]->l); */
}
max_diff_cov = 0.0;
For(i,dim)
{
For(j,dim)
{
cur_cov = cov[i*dim+j];
cov[i*dim+j] *= (phydbl)iter;
cov[i*dim+j] += tree->t_edges[i]->l * tree->t_edges[j]->l;
cov[i*dim+j] /= (phydbl)(iter+1);
new_cov = cov[i*dim+j];
diff_cov = MAX(cur_cov,new_cov)/MIN(cur_cov,new_cov);
if(diff_cov > max_diff_cov) max_diff_cov = diff_cov;
}
}
iter++;
/* if(!(iter%10)) */
/* printf("\n. iter=%d max_diff_mean=%f max_diff_cov=%f",iter,max_diff_mean,max_diff_cov); */
/* if(iter && max_diff_mean < 1.01 && max_diff_cov < 1.01) break; */
if(!(iter%20))
{
fprintf(fp,"\n");
fprintf(fp,"%d\t",iter);
fprintf(fp,"%f\t",tree->c_lnL);
For(i,dim) fprintf(fp,"%f\t",tree->t_edges[i]->l);
fflush(NULL);
}
}while(iter < 5000);
For(i,dim)
{
For(j,dim)
{
cov[i*dim+j] = cov[i*dim+j] - mean[i]*mean[j];
if(i == j && cov[i*dim+j] < MIN_VAR_BL) cov[i*dim+j] = MIN_VAR_BL;
}
}
fclose(fp);
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
/* Order statistic. x_is are uniformily distributed in [min,max] */
phydbl Dorder_Unif(phydbl x, int r, int n, phydbl min, phydbl max)
{
phydbl cons;
phydbl Fx;
phydbl dens;
if(x < min || x > max || min > max)
{
PhyML_Printf("\n. Err in file %s at line %d\n",__FILE__,__LINE__);
Exit("\n");
}
cons = LnGamma(n+1) - LnGamma(r) - LnGamma(n-r+1);
cons = EXP(cons);
cons = ROUND(cons);
Fx = (x-min)/(max-min);
dens = cons * pow(Fx,r-1) * pow(1.-Fx,n-r) * (1./(max-min));
/* printf("\n. x=%f r=%d n=%d min=%f max=%f dens=%f",x,r,n,min,max,dens); */
/* Exit("\n"); */
return(dens);
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
phydbl Covariance(phydbl *x, phydbl *y, int n)
{
int i;
phydbl mean_x,mean_y,mean_xy;
mean_x = .0;
For(i,n) mean_x += x[i];
mean_x /= (phydbl)n;
mean_y = .0;
For(i,n) mean_y += y[i];
mean_y /= (phydbl)n;
mean_xy = .0;
For(i,n) mean_xy += x[i]*y[i];
mean_xy /= (phydbl)n;
return (mean_xy - mean_x*mean_y);
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
/* Sample X from a multivariate normal with mean mu and covariance cov, within
the interval [min,max], under the linear constraint X.lambda=k
*/
phydbl *Rnorm_Multid_Trunc_Constraint(phydbl *mu, phydbl *cov, phydbl *min, phydbl *max, phydbl *lambda, phydbl k, phydbl *res, int len)
{
phydbl *loc_res;
int i,j,cond,iter;
phydbl *x;
phydbl cond_mean,cond_var;
phydbl cov_zic,cov_zii,cov_zcc;
phydbl mean_zi, mean_zc;
phydbl alpha;
phydbl sum;
int err;
phydbl zi;
cond = 0;
loc_res = NULL;
if(!res)
{
loc_res = (phydbl *)mCalloc(len,sizeof(phydbl));
x = loc_res;
}
else x = res;
/* zi = x[i] . lambda[i] */
iter = 0;
do
{
sum = 0.0;
For(i,len)
{
if(i != cond)
{
cov_zic = lambda[i] * lambda[cond] * cov[i*len+cond];
cov_zii = lambda[i] * lambda[i] * cov[i*len+i];
cov_zcc = lambda[cond] * lambda[cond] * cov[cond*len+cond];
mean_zi = lambda[i];
mean_zc = lambda[cond];
/* alpha = k - \sum_{j != cond, j !=i} z_j */
alpha = k;
For(j,len) if(j != cond && j != i) alpha -= lambda[j] * x[j];
cond_mean = mean_zi + (cov_zii + cov_zic) / (cov_zii + 2.*cov_zic + cov_zcc) * (alpha - mean_zi - mean_zc);
cond_var = cov_zii - POW(cov_zii + cov_zic,2)/(cov_zii + 2.*cov_zic + cov_zcc);
if(lambda[i]*min[i] > alpha - lambda[cond]*min[i])
{
PhyML_Printf("\n. Cannot satisfy the constraint.\n");
PhyML_Printf("\n. Err in file %s at line %d\n",__FILE__,__LINE__);
Exit("\n");
}
err = NO;
zi = Rnorm_Trunc(cond_mean,SQRT(cond_var),
MAX(lambda[i]*min[i],alpha-lambda[cond]*max[cond]),
MIN(lambda[i]*max[i],alpha-lambda[cond]*min[cond]),&err);
if(err == YES)
{
PhyML_Printf("\n. Err in file %s at line %d\n",__FILE__,__LINE__);
Exit("\n");
}
sum += zi;
x[i] = zi / lambda[i];
}
}
x[cond] = (k - sum)/lambda[cond];
}while(iter++ < 10);
return(loc_res);
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void PMat_MGF_Gamma(phydbl *Pij, phydbl shape, phydbl scale, phydbl scaling_fact, model *mod)
{
int dim;
int i,j,k;
phydbl *uexpt,*imbd;
dim = mod->eigen->size;
uexpt = mod->eigen->r_e_vect_im;
imbd = mod->eigen->e_val_im;
/* Get the eigenvalues of Q (not the exponentials) */
For(i,dim) imbd[i] = LOG(mod->eigen->e_val[i]);
/* Multiply them by the scaling factor */
For(i,dim) imbd[i] *= scaling_fact;
For(i,dim) imbd[i] *= -scale;
For(i,dim) imbd[i] += 1.0;
For(i,dim) imbd[i] = POW(imbd[i],-shape);
For(i,dim) For(k,dim) uexpt[i*dim+k] = mod->eigen->r_e_vect[i*dim+k] * imbd[k];
For(i,dim) For(k,dim) Pij[dim*i+k] = .0;
For(i,dim)
{
For(j,dim)
{
For(k,dim)
{
Pij[dim*i+j] += (uexpt[i*dim+k] * mod->eigen->l_e_vect[k*dim+j]);
}
if(Pij[dim*i+j] < SMALL_PIJ) Pij[dim*i+j] = SMALL_PIJ;
}
}
/* printf("\n. shape = %f scale = %f",shape,scale); */
/* printf("\n. Qmat"); */
/* For(i,dim) */
/* { */
/* printf("\n"); */
/* For(j,dim) */
/* { */
/* printf("%12f ",mod->qmat[i*dim+j]); */
/* } */
/* } */
/* printf("\n. Pmat"); */
/* For(i,dim) */
/* { */
/* printf("\n"); */
/* For(j,dim) */
/* { */
/* printf("%12f ",Pij[i*dim+j]); */
/* } */
/* } */
/* Exit("\n"); */
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void Integrated_Brownian_Bridge_Moments(phydbl x_beg, phydbl x_end,
phydbl y_beg, phydbl y_end,
phydbl brownian_var, phydbl *mean, phydbl *var)
{
/* phydbl *y; */
/* phydbl *y_mean; */
/* int n_rep; */
int n_breaks;
int i;
/* int j; */
/* phydbl traj_mean, traj_sd; */
/* phydbl x_prev, x_curr; */
phydbl x;
phydbl x_step;
phydbl sum;
/* phydbl sumsum; */
phydbl scaled_var;
scaled_var = brownian_var/FABS(x_end - x_beg);
n_breaks = 100;
/* n_rep = 500; */
/* x_step = (x_end - x_beg)/(n_breaks+1); */
/* y = (phydbl *)mCalloc(n_breaks+2,sizeof(phydbl)); */
/* y_mean = (phydbl *)mCalloc(n_rep,sizeof(phydbl)); */
/* y[0] = y_beg; */
/* y[n_breaks+1] = y_end; */
/* For(i,n_rep) */
/* { */
/* for(j=1;j
#ifndef _SPR_H_
#define _SPR_H_
#include "utilities.h"
#include "models.h"
#include "lk.h"
#include "free.h"
#include "optimiz.h"
#include "alrt.h"
#include "pars.h"
#include "simu.h"
#define ALL 1
#define BEST 2
#define ONE 3
/*
** _move_: Structure for holding the relevant information for candidate SPR moves.
*/
typedef struct
{
t_node *v_prune, *u_prune, *v_n, *v_nx1, *u_n, **path;
t_edge *e_prune, *e_regraft;
phydbl l_connect, l_est[3], delta_lk, d_L, d_up_v, d_un_v;
int dist, rgrft_rank, optim_rank, globl_rank;
} _move_;
void Init_SPR (t_tree *tree);
void Clean_SPR (t_tree *tree);
void Optim_SPR (t_tree *tree, int max_size, int method);
int Perform_SPR_Moves (t_tree *tree, int max_size);
int Perform_Best_SPR (t_tree *tree, int max_size);
int Perform_One_SPR (t_tree *tree, int max_size);
void Calc_Tree_Length (t_edge *e_prune, t_node *v_prune, t_tree *tree);
void Tree_Length (t_node *v_prune, t_node *u_prune, t_node *v_n, t_node *v_n_1,
t_node *v_nx1, t_node *v_0, t_node *u_n, phydbl d_up_v_1,
phydbl d_uu, phydbl d_L_1, int n, t_tree *tree);
int Est_Lk_Change (t_edge *e_prune, t_node *v_prune, t_tree *tree);
int Best_Lk_Change (t_edge *e_prune, t_node *v_prune, t_tree *tree);
void Make_Move (_move_ *move, int type, t_tree *tree);
int Find_Optim_Local (t_tree *tree);
int Find_Optim_Globl (t_tree *tree);
void Prune (t_edge *e, t_node *v, t_edge **e_connect, t_edge **e_avail,
t_tree *tree);
void Regraft (t_edge *e, t_node *v, t_edge *avail, t_tree *tree);
void PostOrder_v (t_tree *tree, t_node *v, t_edge *e);
void PostOrder_w (t_tree *tree, t_node *v, t_edge *v_e, t_node *w, t_edge *e);
void Speed_Spr(t_tree *tree, int max_cycles);
void Speed_Spr_Loop(t_tree *tree);
void Make_Spr_List(t_tree *tree);
void Init_One_Spr(spr *a_spr);
spr *Make_One_Spr(t_tree *tree);
int Spr(phydbl init_lnL, t_tree *tree);
int Spr_Recur(t_node *a, t_node *d, t_tree *tree);
int Test_All_Spr_Targets(t_edge *pulled, t_node *link, t_tree *tree);
void Randomize_Spr_List(t_tree *tree);
void Test_One_Spr_Target_Recur(t_node *a, t_node *d, t_edge *pulled, t_node *link, t_edge *residual, int *best_found, t_tree *tree);
phydbl Test_One_Spr_Target(t_edge *target, t_edge *arrow, t_node *link, t_edge *residual, t_tree *tree);
void Apply_Spr_Moves_One_By_One(t_tree *tree);
int Try_One_Spr_Move_Triple(spr *move, t_tree *tree);
int Try_One_Spr_Move_Full(spr *move, t_tree *tree);
void Make_Best_Spr(t_tree *tree);
void Random_Spr(int n_moves, t_tree *tree);
void Include_One_Spr_To_List_Of_Spr(spr *move, t_tree *tree);
void Reset_Spr_List(t_tree *tree);
int Evaluate_List_Of_Regraft_Pos_Triple(spr **spr_list, int list_size, t_tree *tree);
void Best_Spr(t_tree *tree);
int Check_Spr_Move_Validity(spr *this_spr_move, t_tree *tree);
void Spr_Subtree(t_edge *b, t_node *link, t_tree *tree);
void Spr_Pars(t_tree *tree);
int Check_Lk_At_Given_Edge(t_tree *tree);
void SPR_Shuffle(t_tree *tree);
#endif /* _SPR_H_ */
/*
** EOF: spr.h
*/
phyml-20120412/src/m4.c 0000644 0001750 0001750 00000143277 11665025366 011324 0000000 0000000 /*
PhyML: a program that computes maximum likelihood phylogenies from
DNA or AA homoLOGous sequences.
Copyright (C) Stephane Guindon. Oct 2003 onward.
All parts of the source except where indicated are distributed under
the GNU public licence. See http://www.opensource.org for details.
*/
/* Routines for Markov-Modulated Markov Models (M4) */
#include "m4.h"
int M4_main(int argc, char **argv)
{
calign *cdata;
option *io;
t_tree *tree;
int n_otu, num_data_set;
int num_tree,tree_line_number,num_rand_tree;
matrix *mat;
model *mod;
time_t t_beg,t_end;
phydbl best_lnL,most_likely_size,tree_size;
int r_seed;
char *most_likely_tree=NULL;
#ifdef MPI
int rc;
rc = MPI_Init(&argc,&argv);
if (rc != MPI_SUCCESS) {
PhyML_Printf("\n. Error starting MPI program. Terminating.\n");
MPI_Abort(MPI_COMM_WORLD, rc);
}
MPI_Comm_size(MPI_COMM_WORLD,&Global_numTask);
MPI_Comm_rank(MPI_COMM_WORLD,&Global_myRank);
#endif
#ifdef QUIET
setvbuf(stdout,NULL,_IOFBF,2048);
#endif
tree = NULL;
mod = NULL;
best_lnL = UNLIKELY;
most_likely_size = -1.0;
tree_size = -1.0;
io = (option *)Get_Input(argc,argv);
r_seed = (io->r_seed < 0)?(time(NULL)):(io->r_seed);
srand(r_seed);
io->r_seed = r_seed;
if(io->in_tree == 2) Test_Multiple_Data_Set_Format(io);
else io->n_trees = 1;
mat = NULL;
tree_line_number = 0;
if((io->n_data_sets > 1) && (io->n_trees > 1))
{
io->n_data_sets = MIN(io->n_trees,io->n_data_sets);
io->n_trees = MIN(io->n_trees,io->n_data_sets);
}
For(num_data_set,io->n_data_sets)
{
n_otu = 0;
best_lnL = UNLIKELY;
Get_Seq(io);
Make_Model_Complete(io->mod);
Set_Model_Name(io->mod);
Print_Settings(io);
mod = io->mod;
if(io->data)
{
if(io->n_data_sets > 1) PhyML_Printf("\n. Data set [#%d]\n",num_data_set+1);
cdata = Compact_Data(io->data,io);
Free_Seq(io->data,cdata->n_otu);
if(cdata) Check_Ambiguities(cdata,io->datatype,io->mod->state_len);
else
{
PhyML_Printf("\n. Err in file %s at line %d\n",__FILE__,__LINE__);
Warn_And_Exit("");
}
for(num_tree=(io->n_trees == 1)?(0):(num_data_set);num_tree < io->n_trees;num_tree++)
{
if(!io->mod->s_opt->random_input_tree) io->mod->s_opt->n_rand_starts = 1;
For(num_rand_tree,io->mod->s_opt->n_rand_starts)
{
if((io->mod->s_opt->random_input_tree) && (io->mod->s_opt->topo_search != NNI_MOVE))
if(!io->quiet) PhyML_Printf("\n. [Random start %3d/%3d]\n",num_rand_tree+1,io->mod->s_opt->n_rand_starts);
Init_Model(cdata,mod,io);
if(io->mod->use_m4mod) M4_Init_Model(mod->m4mod,cdata,mod);
switch(io->in_tree)
{
case 0 : case 1 : { tree = Dist_And_BioNJ(cdata,mod,io); break; }
case 2 : { tree = Read_User_Tree(cdata,mod,io); break; }
}
if(!tree) continue;
time(&t_beg);
time(&(tree->t_beg));
tree->mod = mod;
tree->io = io;
tree->data = cdata;
tree->both_sides = YES;
tree->n_pattern = tree->data->crunch_len;
if(mod->s_opt->random_input_tree) Random_Tree(tree);
if((!num_data_set) && (!num_tree) && (!num_rand_tree)) Check_Memory_Amount(tree);
Prepare_Tree_For_Lk(tree);
if(io->in_tree == 1) Spr_Pars(tree);
if(io->do_alias_subpatt)
{
tree->update_alias_subpatt = YES;
Lk(tree);
tree->update_alias_subpatt = NO;
}
if(tree->mod->s_opt->opt_topo)
{
if(tree->mod->s_opt->topo_search == NNI_MOVE) Simu_Loop(tree);
else if(tree->mod->s_opt->topo_search == SPR_MOVE) Speed_Spr_Loop(tree);
else Best_Of_NNI_And_SPR(tree);
}
else
{
if(tree->mod->s_opt->opt_subst_param ||
tree->mod->s_opt->opt_bl) Round_Optimize(tree,tree->data,ROUND_MAX);
else Lk(tree);
}
tree->both_sides = 1;
Lk(tree);
Pars(tree);
Get_Tree_Size(tree);
PhyML_Printf("\n. Log likelihood of the current tree: %f.\n",tree->c_lnL);
Exit("\n");
/* */
M4_Compute_Proba_Hidden_States_On_Edges(tree);
/* */
Get_Best_Root_Position(tree);
/* Print the tree estimated using the current random (or BioNJ) starting tree */
if(io->mod->s_opt->n_rand_starts > 1)
{
Br_Len_Involving_Invar(tree);
Print_Tree(io->fp_out_trees,tree);
fflush(NULL);
}
/* Record the most likely tree in a string of characters */
if(tree->c_lnL > best_lnL)
{
best_lnL = tree->c_lnL;
Br_Len_Involving_Invar(tree);
if(most_likely_tree) Free(most_likely_tree);
most_likely_tree = Write_Tree(tree,NO);
most_likely_size = Get_Tree_Size(tree);
}
/* JF(tree); */
time(&t_end);
Print_Fp_Out(io->fp_out_stats,t_beg,t_end,tree,
io,num_data_set+1,
(tree->mod->s_opt->n_rand_starts > 1)?
(num_rand_tree):(num_tree));
if(tree->io->print_site_lnl) Print_Site_Lk(tree,io->fp_out_lk);
/* Start from BioNJ tree */
if((num_rand_tree == io->mod->s_opt->n_rand_starts-1) && (tree->mod->s_opt->random_input_tree))
{
/* Do one more iteration in the loop, but don't randomize the tree */
num_rand_tree--;
tree->mod->s_opt->random_input_tree = 0;
}
Free_Spr_List(tree);
Free_One_Spr(tree->best_spr);
if(tree->mat) Free_Mat(tree->mat);
Free_Triplet(tree->triplet_struct);
Free_Tree_Pars(tree);
Free_Tree_Lk(tree);
Free_Tree(tree);
}
/* Launch bootstrap analysis */
if(mod->bootstrap)
{
if(!io->quiet) PhyML_Printf("\n. Launch bootstrap analysis on the most likely tree...\n");
#ifdef MPI
MPI_Bcast (most_likely_tree, strlen(most_likely_tree)+1, MPI_CHAR, 0, MPI_COMM_WORLD);
if(!io->quiet) PhyML_Printf("\n. The bootstrap analysis will use %d CPUs.\n",Global_numTask);
#endif
most_likely_tree = Bootstrap_From_String(most_likely_tree,cdata,mod,io);
}
else if(io->ratio_test)
{
/* Launch aLRT */
if(!io->quiet) PhyML_Printf("\n. Compute aLRT branch supports on the most likely tree...\n");
most_likely_tree = aLRT_From_String(most_likely_tree,cdata,mod,io);
}
/* Print the most likely tree in the output file */
if(!io->quiet) PhyML_Printf("\n. Printing the most likely tree in file '%s'...\n", Basename(io->out_tree_file));
if(io->n_data_sets == 1) rewind(io->fp_out_tree);
PhyML_Fprintf(io->fp_out_tree,"%s\n",most_likely_tree);
if(io->n_trees > 1 && io->n_data_sets > 1) break;
}
Free_Cseq(cdata);
}
else
{
PhyML_Printf("\n. No data was found.\n");
PhyML_Printf("\n. Err in file %s at line %d\n",__FILE__,__LINE__);
Warn_And_Exit("");
}
Free_Model_Complete(mod);
}
if(most_likely_tree) Free(most_likely_tree);
if(mod->s_opt->n_rand_starts > 1) PhyML_Printf("\n. Best log likelihood: %f\n",best_lnL);
Free_Optimiz(mod->s_opt);
Free_Model_Basic(mod);
if(io->fp_in_align) fclose(io->fp_in_align);
if(io->fp_in_tree) fclose(io->fp_in_tree);
if(io->fp_out_lk) fclose(io->fp_out_lk);
if(io->fp_out_tree) fclose(io->fp_out_tree);
if(io->fp_out_trees) fclose(io->fp_out_trees);
if(io->fp_out_stats) fclose(io->fp_out_stats);
Free_Input(io);
time(&t_end);
Print_Time_Info(t_beg,t_end);
#ifdef MPI
MPI_Finalize();
#endif
return 0;
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
/* Allocate memory */
m4 *M4_Make_Light()
{
m4 *m4mod;
m4mod = (m4 *)mCalloc(1,sizeof(m4));
M4_Set_M4mod_Default(m4mod);
return m4mod;
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void M4_Set_M4mod_Default(m4 *m4mod)
{
m4mod->use_cov_alpha = 1;
m4mod->use_cov_alpha = 0;
m4mod->n_h = 3;
m4mod->n_o = 4;
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
/* Allocate memory */
void M4_Make_Complete(int n_h, int n_o, m4 *m4mod)
{
int i;
m4mod->n_h = n_h;
m4mod->n_o = n_o;
m4mod->n_o = n_o;
m4mod->o_rr = (phydbl *)mCalloc(n_o*n_o,sizeof(phydbl));
m4mod->o_fq = (phydbl *)mCalloc(n_o,sizeof(phydbl));
m4mod->o_mats = (phydbl **)mCalloc(n_h,sizeof(phydbl *));
For(i,n_h) m4mod->o_mats[i] = (phydbl *)mCalloc(n_o*n_o,sizeof(phydbl));
m4mod->h_mat = (phydbl *)mCalloc(n_h*n_h,sizeof(phydbl));
m4mod->h_rr = (phydbl *)mCalloc(n_h*n_h,sizeof(phydbl));
m4mod->h_fq = (phydbl *)mCalloc(n_h,sizeof(phydbl));
m4mod->multipl = (phydbl *)mCalloc(n_h,sizeof(phydbl));
m4mod->multipl_unscaled = (phydbl *)mCalloc(n_h,sizeof(phydbl));
m4mod->h_fq_unscaled = (phydbl *)mCalloc(n_h,sizeof(phydbl));
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
/* Free memory */
void M4_Free_M4_Model(m4 *m4mod)
{
int i;
if(m4mod->o_mats)
{
For(i,m4mod->n_h) Free(m4mod->o_mats[i]);
Free(m4mod->o_mats);
Free(m4mod->h_mat);
Free(m4mod->o_rr);
Free(m4mod->h_rr);
Free(m4mod->o_fq);
Free(m4mod->h_fq);
Free(m4mod->multipl);
Free(m4mod->multipl_unscaled);
Free(m4mod->h_fq_unscaled);
}
Free(m4mod);
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void M4_Init_Model(m4 *m4mod, calign *data, model *mod)
{
int i,j,ct;
phydbl fq;
if(mod->io->datatype == NT) m4mod->n_o = 4;
else if(mod->io->datatype == AA) m4mod->n_o = 20;
else
{
PhyML_Printf("\n. Not implemented yet.");
PhyML_Printf("\n. Err in file %s at line %d\n",__FILE__,__LINE__);
Warn_And_Exit("");
}
mod->ns = m4mod->n_o * m4mod->n_h;
For(i,m4mod->n_o) m4mod->o_fq[i] = mod->pi->v[i]; /*! At that stage, the mod->pi vector as been initialized
under a standard non covarion type of model. Use these
frequencies as they have been set according to the
nucleotide substitution model chosen (e.g., 1/4 for JC69). !*/
For(i,(int)(m4mod->n_h)) m4mod->multipl[i] = 1.;
ct = 0;
For(i,m4mod->n_o-1)
{
for(j=i+1;jn_o;j++)
{
m4mod->o_rr[ct] = MAX(mod->qmat->v[i*m4mod->n_o+j],1.E-5);
ct++;
}
}
For(i,(int)(m4mod->n_h*(m4mod->n_h-1)/2)) m4mod->h_rr[i] = 1.;
fq = (phydbl)(1./m4mod->n_h);
if(mod->s_opt->opt_cov_delta) m4mod->delta = 1.0;
if(mod->s_opt->opt_cov_alpha) m4mod->alpha = 1.0;
For(i,m4mod->n_h) m4mod->h_fq[i] = fq;
For(i,m4mod->n_h) m4mod->h_fq_unscaled[i] = 1.0;
For(i,m4mod->n_h) m4mod->multipl[i] = (phydbl)i;
For(i,m4mod->n_h) m4mod->multipl_unscaled[i] = (phydbl)i;
mod->update_eigen = YES;
M4_Update_Qmat(m4mod,mod);
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
/* Fill in the (big) rate matrix of the M4 model */
void M4_Update_Qmat(m4 *m4mod, model *mod)
{
int i,j;
int n_s, n_o, n_h;
phydbl mr, sum;
phydbl scale;
/* The number of states in M4 models is the product
of the number of hidden states (or classes) by the
number of observable states
*/
n_s = mod->ns;
n_o = m4mod->n_o;
n_h = m4mod->n_h;
/* Set the relative substitution rates */
if(mod->m4mod->use_cov_alpha)
{
DiscreteGamma(m4mod->h_fq,m4mod->multipl,m4mod->alpha,m4mod->alpha,m4mod->n_h,mod->gamma_median);
}
else if(mod->m4mod->use_cov_free)
{
sum = .0;
For(i,mod->m4mod->n_h) sum += FABS(mod->m4mod->h_fq_unscaled[i]);
For(i,mod->m4mod->n_h) mod->m4mod->h_fq[i] = FABS(mod->m4mod->h_fq_unscaled[i])/sum;
do
{
sum = .0;
For(i,mod->m4mod->n_h)
{
if(mod->m4mod->h_fq[i] < 0.01) mod->m4mod->h_fq[i]=0.01;
if(mod->m4mod->h_fq[i] > 0.99) mod->m4mod->h_fq[i]=0.99;
sum += mod->m4mod->h_fq[i];
}
For(i,mod->m4mod->n_h) mod->m4mod->h_fq[i]/=sum;
}
while((sum > 1.01) || (sum < 0.99));
/* Make sure the multipliers are centered on 1.0 */
sum = .0;
For(i,mod->m4mod->n_h) sum += FABS(mod->m4mod->multipl_unscaled[i]) * mod->m4mod->h_fq[i];
For(i,mod->m4mod->n_h) mod->m4mod->multipl[i] = mod->m4mod->multipl_unscaled[i] / sum;
/* printf("\n. WARNING\n"); */
/* mod->m4mod->h_fq[0] = 1./3; */
/* mod->m4mod->h_fq[1] = 1./3; */
/* mod->m4mod->h_fq[2] = 1./3; */
/* mod->m4mod->multipl[0] = 1.0; */
/* mod->m4mod->multipl[1] = 1.0; */
/* mod->m4mod->multipl[2] = 1.0; */
sum = 0;
For(i,mod->m4mod->n_h) sum += mod->m4mod->multipl[i] * mod->m4mod->h_fq[i];
if(sum < 0.99 || sum > 1.01)
{
PhyML_Printf("\n. sum = %f",sum);
PhyML_Printf("\n. Err in file %s at line %d\n\n",__FILE__,__LINE__);
Warn_And_Exit("\n");
}
/* PhyML_Printf("\n__ "); */
/* For(i,mod->m4mod->n_h) PhyML_Printf("\n.%f %f %f", */
/* mod->m4mod->h_fq[i], */
/* mod->m4mod->h_fq_unscaled[i], */
/* mod->m4mod->multipl[i]); */
}
/* PhyML_Printf("\n."); */
/* PhyML_Printf("\n. M4 model parameters"); */
/* m4mod->delta=.0; */
/* PhyML_Printf("\n. Delta = %f",m4mod->delta); */
/* For(i,mod->m4mod->n_h) PhyML_Printf("\n. multipl %d = %f",i,m4mod->multipl[i]); */
/* For(i,mod->m4mod->n_h) PhyML_Printf("\n. fq %d = %f",i,m4mod->h_fq[i]); */
/* Set up the stationary frequency vector */
For(i,n_s) mod->pi->v[i] = m4mod->o_fq[i%n_o] * m4mod->h_fq[i/n_o];
if(mod->whichmodel != CUSTOM &&
mod->whichmodel != GTR &&
mod->io->datatype == NT)
{
phydbl kappa1,kappa2;
if((mod->whichmodel != F84) && (mod->whichmodel != TN93)) mod->lambda->v = 1.;
else if(mod->whichmodel == F84)
{
mod->lambda->v = Get_Lambda_F84(mod->pi->v,&(mod->kappa->v));
}
kappa2 = mod->kappa->v*2./(1.+mod->lambda->v);
kappa1 = kappa2 * mod->lambda->v;
/* A <-> C */ m4mod->o_rr[0] = 1.0;
/* A <-> G */ m4mod->o_rr[1] = kappa2;
/* A <-> T */ m4mod->o_rr[2] = 1.0;
/* C <-> G */ m4mod->o_rr[3] = 1.0;
/* C <-> T */ m4mod->o_rr[4] = kappa1;
}
/* Fill in the matrices of nucleotide or amino-acid substitution rates here */
Update_Qmat_Generic(m4mod->o_rr, m4mod->o_fq, m4mod->n_o, m4mod->o_mats[0]);
/* Print_Square_Matrix_Generic(n_o,m4mod->o_mats[0]); */
/* Multiply each of these matrix by a relative substitution rate */
for(i=1;in_h;i++) For(j,n_o*n_o) m4mod->o_mats[i][j] = m4mod->o_mats[0][j]*m4mod->multipl[i];
For(j,n_o*n_o) m4mod->o_mats[0][j] *= m4mod->multipl[0];
For(i,n_s*n_s) mod->qmat->v[i] = .0;
/* Diagonal blocks (i.e, nucleotide substitutions), symmetric */
For(i,n_s)
{
for(j=i+1;jqmat->v[i*n_s+j] = m4mod->o_mats[(int)(i/n_o)][(i%n_o)*n_o+j%n_o];
mod->qmat->v[j*n_s+i] = mod->qmat->v[i*n_s+j] * m4mod->o_fq[i%n_o] / m4mod->o_fq[j%n_o];
}
}
}
/* Work out scaling factor */
mr = .0;
For(i,n_s)
{
sum = .0;
For(j,n_s) sum += mod->qmat->v[i*n_s+j];
mr += sum * m4mod->o_fq[i%n_o] * m4mod->h_fq[(int)(i/n_o)];
}
/* Scale the diagonal blocks */
For(i,n_s*n_s) mod->qmat->v[i] /= mr;
/* We are done with the diagonal blocks. Let's fill the non-diagonal ones now. */
/* Fill the matrix of substitution rate across classes (switches) here */
Update_Qmat_Generic(m4mod->h_rr, m4mod->h_fq, m4mod->n_h, m4mod->h_mat);
/* Print_Square_Matrix_Generic(m4mod->n_h,m4mod->h_mat); */
/* Multiply this matrix by the switching rate */
For(i,n_h*n_h) m4mod->h_mat[i] *= m4mod->delta;
/* Fill the non diagonal blocks */
For(i,n_s)
{
for(j=i+1;jqmat->v[i*n_s+j] = m4mod->h_mat[(int)(i/n_o)*n_h+(int)(j/n_o)];
mod->qmat->v[j*n_s+i] = mod->qmat->v[i*n_s+j] * m4mod->h_fq[(int)(i/n_o)] / m4mod->h_fq[(int)(j/n_o)];
}
}
}
}
/* Note: class equilibrium frequencies are already built in the h_mat matrix.
No need to 'add' these frequencies later on. */
/* We are done with the non diagonal blocks */
/* Scaling matrix */
scale = 0.0;
For(i,n_s)
{
For(j,n_s)
{
if((int)(i/n_o) == (j/n_o))
{
scale +=
m4mod->h_fq[(int)(j/n_o)] *
m4mod->o_fq[i%n_o] *
mod->qmat->v[i*n_s+j];
}
}
}
For(i,n_s*n_s) mod->qmat->v[i] /= scale;
/* Diagonal cells */
For(i,n_s)
{
sum = .0;
For(j,n_s)
{
if(j != i)
sum += mod->qmat->v[i*n_s+j];
}
mod->qmat->v[i*n_s+i] = -sum;
}
For(i,n_s*n_s) mod->eigen->q[i] = mod->qmat->v[i];
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void M4_Init_P_Lk_Tips_Double(t_tree *tree)
{
int curr_site,i,j,k,l,dim1,dim2,dim3;
dim1 = tree->mod->n_catg * tree->mod->m4mod->n_h * tree->mod->m4mod->n_o;
dim2 = tree->mod->m4mod->n_h * tree->mod->m4mod->n_o;
dim3 = tree->mod->m4mod->n_o;
Fors(curr_site,tree->data->crunch_len,tree->mod->state_len)
{
For(i,tree->n_otu)
{
for(j=1;jmod->m4mod->n_h;j++)
{
For(k,tree->mod->m4mod->n_o)
{
tree->t_nodes[i]->b[0]->p_lk_rght[curr_site*dim1 + 0*dim2 + j*dim3+k] =
tree->t_nodes[i]->b[0]->p_lk_rght[curr_site*dim1 + 0*dim2 + 0*dim3+k];
printf("\n() i=%d plk=%f",
curr_site*dim1 + 0*dim2 + j*dim3+k,
tree->t_nodes[i]->b[0]->p_lk_rght[curr_site*dim1 + 0*dim2 + j*dim3+k]);
/* tree->t_nodes[i]->b[0]->p_lk_rght[curr_site][0][j*tree->mod->m4mod->n_o+k] = */
/* tree->t_nodes[i]->b[0]->p_lk_rght[curr_site][0][k]; */
}
For(k,tree->mod->m4mod->n_o)
for(l=1;lmod->n_catg;l++)
tree->t_nodes[i]->b[0]->p_lk_rght[curr_site*dim1 + l*dim2 + j*dim3+k] =
tree->t_nodes[i]->b[0]->p_lk_rght[curr_site*dim1 + 0*dim2 + j*dim3+k];
/* tree->t_nodes[i]->b[0]->p_lk_rght[curr_site][l][j*tree->mod->m4mod->n_o+k] = */
/* tree->t_nodes[i]->b[0]->p_lk_rght[curr_site][0][j*tree->mod->m4mod->n_o+k]; */
}
}
}
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void M4_Init_P_Lk_Tips_Int(t_tree *tree)
{
int curr_site,i,j,k,dim2,dim3;
dim2 = tree->mod->m4mod->n_h * tree->mod->m4mod->n_o;
dim3 = tree->mod->m4mod->n_o;
Fors(curr_site,tree->data->crunch_len,tree->mod->state_len)
{
For(i,tree->n_otu)
{
for(j=1;jmod->m4mod->n_h;j++)
{
For(k,tree->mod->m4mod->n_o)
{
tree->t_nodes[i]->b[0]->p_lk_tip_r[curr_site*dim2 + j*dim3+k] =
tree->t_nodes[i]->b[0]->p_lk_tip_r[curr_site*dim2 + 0*dim3+k];
/* tree->t_nodes[i]->b[0]->p_lk_tip_r[curr_site][j*tree->mod->m4mod->n_o+k] = */
/* tree->t_nodes[i]->b[0]->p_lk_tip_r[curr_site][k]; */
}
}
}
}
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
phydbl ****M4_Integral_Term_On_One_Edge(t_edge *b, t_tree *tree)
{
phydbl ****integral,*P1,*P2;
int ns;
int g,i,j,k,l;
int step;
ns = tree->mod->ns;
P1 = (phydbl *)mCalloc(tree->mod->n_catg*ns*ns,sizeof(phydbl));
P2 = (phydbl *)mCalloc(tree->mod->n_catg*ns*ns,sizeof(phydbl));
integral = (phydbl ****)mCalloc(tree->mod->n_catg,sizeof(phydbl ***));
For(g,tree->mod->n_catg)
{
integral[g] = (phydbl ***)mCalloc(ns,sizeof(phydbl **));
For(j,ns)
{
integral[g][j] = (phydbl **)mCalloc(ns,sizeof(phydbl *));
For(k,ns) integral[g][j][k] = (phydbl *)mCalloc(ns,sizeof(phydbl));
}
}
/* Integral calculation */
step = 100;
PhyML_Printf("\n. [");
For(i,step)
{
For(g,tree->mod->n_catg)
{
PMat(((phydbl)(i+0.5)/step)*b->l*tree->mod->gamma_rr->v[g],tree->mod,g*ns*ns,P1);
PMat(((phydbl)(step-i-0.5)/step)*b->l*tree->mod->gamma_rr->v[g],tree->mod,g*ns*ns,P2);
For(j,ns)
{
For(k,ns)
{
For(l,ns)
{
/* integral[g][j][k][l] += P1[g][j][k] * P2[g][j][l] / ((phydbl)(step)); */
integral[g][j][k][l] += P1[g*ns*ns + j*ns+k] * P2[g*ns*ns + j*ns+l] / ((phydbl)(step));
}
}
}
}
PhyML_Printf("."); fflush(NULL);
}
PhyML_Printf("]\n");
Free(P1);
Free(P2);
return integral;
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void M4_Post_Prob_H_Class_Edge_Site(t_edge *b, phydbl ****integral, phydbl *postprob, t_tree *tree)
{
/* Calculation of the expected frequencies of each hidden
class at a given site. */
phydbl site_lk;
int g,i,j,k,l;
int ns,n_h;
phydbl sum;
int dim1,dim2;
dim1 = tree->mod->n_catg * tree->mod->ns;
dim2 = tree->mod->ns;
ns = tree->mod->ns;
n_h = tree->mod->m4mod->n_h; /* number of classes, i.e., number of hidden states */
site_lk = (phydbl)EXP(tree->cur_site_lk[tree->curr_site]);
if(b->rght->tax)
{
sum = .0;
For(i,n_h)
{
postprob[i] = .0;
For(j,tree->mod->m4mod->n_o)
{
For(g,tree->mod->n_catg)
{
For(k,tree->mod->ns)
{
For(l,tree->mod->ns)
{
postprob[i] +=
(1./site_lk) *
tree->mod->gamma_r_proba->v[g] *
tree->mod->m4mod->h_fq[i] *
tree->mod->m4mod->o_fq[j] *
b->p_lk_left[tree->curr_site*dim1 + g*dim2 + k] *
b->p_lk_tip_r[tree->curr_site*dim2 + l] *
integral[g][i*tree->mod->m4mod->n_o+j][k][l];
/* (1./site_lk) * */
/* tree->mod->gamma_r_proba[g] * */
/* tree->mod->m4mod->h_fq[i] * */
/* tree->mod->m4mod->o_fq[j] * */
/* b->p_lk_left[tree->curr_site][g][k] * */
/* b->p_lk_tip_r[tree->curr_site][l] * */
/* /\* b->p_lk_rght[tree->curr_site][0][l] * *\/ */
/* integral[g][i*tree->mod->m4mod->n_o+j][k][l]; */
}
}
}
}
sum += postprob[i];
}
/* TO DO */
For(i,n_h) postprob[i] *= EXP(b->sum_scale_left[tree->curr_site]);
}
else
{
sum = .0;
For(i,n_h)
{
postprob[i] = .0;
For(j,tree->mod->m4mod->n_o)
{
For(g,tree->mod->n_catg)
{
For(k,tree->mod->ns)
{
For(l,tree->mod->ns)
{
postprob[i] +=
(1./site_lk) *
tree->mod->gamma_r_proba->v[g] *
tree->mod->m4mod->h_fq[i] *
tree->mod->m4mod->o_fq[j] *
b->p_lk_left[tree->curr_site*dim1 + g*dim2 + k] *
b->p_lk_rght[tree->curr_site*dim1 + g*dim2 + l] *
integral[g][i*tree->mod->m4mod->n_o+j][k][l];
/* (1./site_lk) * */
/* tree->mod->gamma_r_proba[g] * */
/* tree->mod->m4mod->h_fq[i] * */
/* tree->mod->m4mod->o_fq[j] * */
/* b->p_lk_left[tree->curr_site][g][k] * */
/* b->p_lk_rght[tree->curr_site][g][l] * */
/* integral[g][i*tree->mod->m4mod->n_o+j][k][l]; */
}
}
}
}
sum += postprob[i];
}
/* TO DO */
For(i,n_h) postprob[i] *= EXP(b->sum_scale_left[tree->curr_site] + b->sum_scale_rght[tree->curr_site]);
}
For(i,n_h)
if((postprob[i] < -1.E-5) || (postprob[i] > 1.0+1.E-5))
{
PhyML_Printf("\n. Cat : %d Prob : %f\n",i,postprob[i]);
PhyML_Printf("\n. Err in file %s at line %d\n\n",__FILE__,__LINE__);
Warn_And_Exit("\n");
}
sum = 0.0;
For(i,n_h) sum += postprob[i];
if((sum > 1.0+1.E-2) || (sum < 1.0-1.E-2))
{
PhyML_Printf("\n. Sum = %f\n",sum);
PhyML_Printf("\n. Err in file %s at line %d\n\n",__FILE__,__LINE__);
Exit("\n");
}
return;
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
phydbl ***M4_Compute_Proba_Hidden_States_On_Edges(t_tree *tree)
{
int i;
phydbl ***post_probs, *dwell;
phydbl ****integral;
dwell = (phydbl *)mCalloc(tree->mod->m4mod->n_h,sizeof(phydbl));
post_probs = (phydbl ***)mCalloc(2*tree->n_otu-3,sizeof(phydbl **));
For(i,2*tree->n_otu-3)
{
post_probs[i] = (phydbl **)mCalloc(tree->n_pattern,sizeof(phydbl *));
For(tree->curr_site,tree->n_pattern)
post_probs[i][tree->curr_site] = (phydbl *)mCalloc(tree->mod->m4mod->n_h,sizeof(phydbl));
}
/* Compute posterior probabilities of each hidden class (usually a rate class)
on each edge, at each site.
*/
For(i,2*tree->n_otu-3)
{
PhyML_Printf("\n. Edge %4d/%4d",i+1,2*tree->n_otu-3);
integral = M4_Integral_Term_On_One_Edge(tree->t_edges[i],tree);
For(tree->curr_site,tree->n_pattern)
M4_Post_Prob_H_Class_Edge_Site(tree->t_edges[i],
integral,
post_probs[i][tree->curr_site],
tree);
M4_Free_Integral_Term_On_One_Edge(integral,tree);
}
return post_probs;
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
/* Estimate the (posterior) mean relative rate of substitution on each branch
at each site. The posterior mean rates averaged over sites is also estimated
for each edge. The corresponding trees are printed in a postscript file. Tree 0
is the tree with posterior mean rates averaged over the sites. The following trees
have posterior mean rates computed for each site.
*/
void M4_Compute_Posterior_Mean_Rates(phydbl ***post_probs, t_tree *tree)
{
char *s;
int i;
phydbl **mean_post_probs;
phydbl *mrr;
phydbl sum;
int patt,br,rcat;
phydbl *mean_br_len;
int best_r,len_var;
phydbl max_prob;
mean_br_len = (phydbl *)mCalloc(2*tree->n_otu-3,sizeof(phydbl));
mean_post_probs = (phydbl **)mCalloc(2*tree->n_otu-3,sizeof(phydbl *));
For(i,2*tree->n_otu-3) mean_post_probs[i] = (phydbl *)mCalloc(tree->mod->m4mod->n_h,sizeof(phydbl ));
mrr = (phydbl *)mCalloc(2*tree->n_otu-3,sizeof(phydbl));
Record_Br_Len(tree);
M4_Scale_Br_Len(tree);
/* Compute the posterior mean relative rate on each branch averaged over the
whole set of patterns (sites) */
len_var = 0;
For(patt,tree->n_pattern)
{
if(!Is_Invar(patt,1,NT,tree->data))
{
For(br,2*tree->n_otu-3)
{
max_prob = -1.;
best_r = -1;
For(rcat,tree->mod->m4mod->n_h)
{
if(post_probs[br][patt][rcat] > max_prob)
{
max_prob = post_probs[br][patt][rcat];
best_r = rcat;
}
}
/* /\* Add weight on each category, weight is proportional to the corresponding posterior probability *\/ */
/* For(rcat,tree->mod->m4mod->n_h) */
/* { */
/* mean_post_probs[br][rcat] += post_probs[br][patt][rcat] * tree->data->wght[patt]; */
/* } */
/* Add weight on the most probable rate category only */
mean_post_probs[br][best_r] += tree->data->wght[patt];
}
len_var += tree->data->wght[patt];
}
}
For(br,2*tree->n_otu-3)
{
For(rcat,tree->mod->m4mod->n_h)
{
mean_post_probs[br][rcat] /= (phydbl)len_var;
}
}
/* Compute the posterior mean relative rate and scale
each branch length using this factor */
For(br,2*tree->n_otu-3)
{
For(rcat,tree->mod->m4mod->n_h)
{
mrr[br] += mean_post_probs[br][rcat] * tree->mod->m4mod->multipl[rcat];
}
tree->t_edges[br]->l *= mrr[br];
}
PhyML_Fprintf(tree->io->fp_out_stats,"\n. Mean posterior probabilities & rates\n");
For(rcat,tree->mod->m4mod->n_h) PhyML_Fprintf(tree->io->fp_out_stats,"%2.4f ",tree->mod->m4mod->multipl[rcat]);
PhyML_Fprintf(tree->io->fp_out_stats,"\n");
For(br,2*tree->n_otu-3)
{
For(rcat,tree->mod->m4mod->n_h)
{
PhyML_Fprintf(tree->io->fp_out_stats,"%2.4f ",mean_post_probs[br][rcat]);
}
/* PhyML_Fprintf(tree->io->fp_out_stats," -- %f -> %f x %f = %f",mrr[br],tree->t_edges[br]->l,mrr[br],tree->t_edges[br]->l*mrr[br]); */
PhyML_Fprintf(tree->io->fp_out_stats," mrr=%f ",mrr[br]);
if(mrr[br] > 1.) PhyML_Fprintf(tree->io->fp_out_stats,"FAST ");
else PhyML_Fprintf(tree->io->fp_out_stats,"SLOW ");
PhyML_Fprintf(tree->io->fp_out_stats,"%s",tree->t_edges[br]->labels[0]);
PhyML_Fprintf(tree->io->fp_out_stats,"\n");
}
/* Print the tree */
PhyML_Fprintf(tree->io->fp_out_tree,"Constrained tree with corrected branch lengths = ");
s = Write_Tree(tree,NO);
PhyML_Fprintf(tree->io->fp_out_tree,"%s\n",s);
Free(s);
tree->ps_tree = DR_Make_Tdraw_Struct(tree);
DR_Print_Postscript_Header(tree->n_pattern,tree->io->fp_out_ps);
tree->ps_page_number = 0;
DR_Print_Tree_Postscript(tree->ps_page_number++,YES,tree->io->fp_out_ps,tree);
/* Go back to the initial scaled branch lengths */
For(br,2*tree->n_otu-3) tree->t_edges[br]->l /= mrr[br];
/* Compute the posterior mean relative rate at each site, for each branch
and each rate category. Scale branch lengths using these factors and
print each tree (i.e., on tree per site pattern) */
For(patt,tree->n_pattern)
{
For(br,2*tree->n_otu-3)
{
mrr[br] = .0;
max_prob = -1.;
best_r = -1;
For(rcat,tree->mod->m4mod->n_h) /* For each rate class */
{
mrr[br] += post_probs[br][patt][rcat] * tree->mod->m4mod->multipl[rcat];
if(post_probs[br][patt][rcat] > max_prob)
{
max_prob = post_probs[br][patt][rcat];
best_r = rcat;
}
}
/* mrr[br] = tree->mod->m4mod->multipl[best_r]; /\* Use the most probable relative rate instead of mean *\/ */
tree->t_edges[br]->l *= mrr[br];
}
For(br,2*tree->n_otu-3) mean_br_len[br] += tree->t_edges[br]->l * tree->data->wght[patt];
PhyML_Fprintf(tree->io->fp_out_stats,"\n. Posterior probabilities site %4d (weight=%d, is_inv=%d)\n",
patt,
tree->data->wght[patt],
Is_Invar(patt,1,NT,tree->data));
For(rcat,tree->mod->m4mod->n_h) PhyML_Fprintf(tree->io->fp_out_stats,"%2.4f ",tree->mod->m4mod->multipl[rcat]);
PhyML_Fprintf(tree->io->fp_out_stats,"\n");
For(br,2*tree->n_otu-3)
{
PhyML_Fprintf(tree->io->fp_out_stats,"Edge %3d ",br);
max_prob = -1.0;
best_r = -1;
For(rcat,tree->mod->m4mod->n_h)
{
if(post_probs[br][patt][rcat] > max_prob)
{
max_prob = post_probs[br][patt][rcat];
best_r = rcat;
}
}
For(rcat,tree->mod->m4mod->n_h)
{
PhyML_Fprintf(tree->io->fp_out_stats,"%2.4f",post_probs[br][patt][rcat]);
if(rcat == best_r) PhyML_Fprintf(tree->io->fp_out_stats,"* ");
else PhyML_Fprintf(tree->io->fp_out_stats," ");
}
/* PhyML_Fprintf(tree->io->fp_out_stats," -- %f -> %f x %f = %f",mrr[br],tree->t_edges[br]->l,mrr[br],tree->t_edges[br]->l*mrr[br]); */
if(mrr[br] > 1.01) PhyML_Fprintf(tree->io->fp_out_stats," %s ","FAST");
else if(mrr[br] < 0.99) PhyML_Fprintf(tree->io->fp_out_stats," %s ","SLOW");
else PhyML_Fprintf(tree->io->fp_out_stats," %s ","MEDIUM");
PhyML_Fprintf(tree->io->fp_out_stats,"%s ",tree->t_edges[br]->labels[0]);
PhyML_Fprintf(tree->io->fp_out_stats,"\n");
}
PhyML_Fprintf(tree->io->fp_out_tree,"tree %d = ",patt+1);
s = Write_Tree(tree,NO);
PhyML_Fprintf(tree->io->fp_out_tree,"%s\n",s);
Free(s);
DR_Print_Tree_Postscript(tree->ps_page_number++,YES,tree->io->fp_out_ps,tree);
/* Go back to the initial scaled branch lengths */
For(br,2*tree->n_otu-3) tree->t_edges[br]->l /= mrr[br];
For(br,2*tree->n_otu-3)
{
sum = .0;
For(rcat,tree->mod->m4mod->n_h)
{
sum += post_probs[br][patt][rcat];
}
if((sum < 0.99) || (sum > 1.01))
{
PhyML_Fprintf(tree->io->fp_out_stats,"\n. sum = %f\n",sum);
PhyML_Fprintf(tree->io->fp_out_stats,"\n. Err in file %s at line %d\n\n",__FILE__,__LINE__);
Warn_And_Exit("\n");
}
}
}
/* Mean branch lengths */
For(br,2*tree->n_otu-3)
{
mean_br_len[br] /= (phydbl)tree->data->init_len;
tree->t_edges[br]->l = mean_br_len[br];
}
PhyML_Fprintf(tree->io->fp_out_tree,"Mean branch lengths=");
s = Write_Tree(tree,NO);
PhyML_Fprintf(tree->io->fp_out_tree,"%s\n",s);
Free(s);
/* DR_Print_Tree_Postscript(tree->ps_page_number++,tree->io->fp_out_ps,tree); */
Restore_Br_Len(tree);
DR_Print_Postscript_EOF(tree->io->fp_out_ps);
For(br,2*tree->n_otu-3)
{
For(tree->curr_site,tree->n_pattern)
Free(post_probs[br][tree->curr_site]);
Free(post_probs[br]);
}
Free(post_probs);
For(i,2*tree->n_otu-3) Free(mean_post_probs[i]);
Free(mean_post_probs);
Free(mrr);
Free(mean_br_len);
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
/* Classifiy each branch, at each site, among one of the rate classes */
phydbl **M4_Site_Branch_Classification(phydbl ***post_probs, t_tree *tree)
{
int patt, br, rcat, i;
phydbl **best_probs;
phydbl post_prob_fast, post_prob_slow;
best_probs = (phydbl **)mCalloc(tree->n_pattern,sizeof(phydbl *));
For(i,tree->n_pattern) best_probs[i] = (phydbl *)mCalloc(2*tree->n_otu-3,sizeof(phydbl));
tree->print_labels = 1;
For(patt,tree->n_pattern)
{
For(br,2*tree->n_otu-3)
{
post_prob_fast = .0;
post_prob_slow = .0;
For(rcat,tree->mod->m4mod->n_h) /* For each rate class */
{
if(tree->mod->m4mod->multipl[rcat] > 1.0)
post_prob_fast += post_probs[br][patt][rcat];
else
post_prob_slow += post_probs[br][patt][rcat];
}
best_probs[patt][br] = (post_prob_fast > post_prob_slow)?(post_prob_fast):(post_prob_slow);
if(!(tree->t_edges[br]->n_labels%BLOCK_LABELS)) Make_New_Edge_Label(tree->t_edges[br]);
/* if((post_prob_fast > post_prob_slow) && (best_probs[patt][br] > 0.95)) */
/* strcpy(tree->t_edges[br]->labels[tree->t_edges[br]->n_labels],"FASTER"); */
/* else if((post_prob_fast < post_prob_slow) && (best_probs[patt][br] > 0.95)) */
/* strcpy(tree->t_edges[br]->labels[tree->t_edges[br]->n_labels],"SLOWER"); */
/* else */
/* strcpy(tree->t_edges[br]->labels[tree->t_edges[br]->n_labels],"UNKNOWN"); */
if(post_prob_fast > post_prob_slow)
strcpy(tree->t_edges[br]->labels[tree->t_edges[br]->n_labels],"FASTER");
else
strcpy(tree->t_edges[br]->labels[tree->t_edges[br]->n_labels],"SLOWER");
tree->t_edges[br]->n_labels++;
}
}
return best_probs;
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void M4_Site_Branch_Classification_Experiment(t_tree *tree)
{
calign *ori_data,*cpy_data;
short int **true_rclass, **est_rclass;
phydbl **best_probs;
int i,j;
phydbl correct_class, mis_class, unknown;
int ns;
true_rclass = (short int **)mCalloc(tree->data->init_len, sizeof(short int *));
est_rclass = (short int **)mCalloc(tree->data->init_len, sizeof(short int *));
For(i,tree->data->init_len)
{
true_rclass[i] = (short int *)mCalloc(2*tree->n_otu-3,sizeof(short int));
est_rclass[i] = (short int *)mCalloc(2*tree->n_otu-3,sizeof(short int));
}
ori_data = tree->data;
if(tree->io->datatype == NT) ns = 4;
else if(tree->io->datatype == AA) ns = 20;
else
{
PhyML_Printf("\n. Not implemented yet.");
PhyML_Printf("\n. Err in file %s at line %d\n",__FILE__,__LINE__);
Warn_And_Exit("");
}
cpy_data = Copy_Cseq(tree->data,tree->io);
/* Generate a simulated data set under H0, with the right sequence length. */
PhyML_Printf("\n. Evolving sequences (delta=%f, alpha=%f) ...\n",tree->mod->m4mod->delta,tree->mod->m4mod->alpha);
Evolve(cpy_data,tree->mod,tree);
For(i,cpy_data->init_len)
{
For(j,2*tree->n_otu-3)
{
if(!strcmp(tree->t_edges[j]->labels[i],"FASTER"))
{
true_rclass[i][j] = 1;
}
else if(!strcmp(tree->t_edges[j]->labels[i],"SLOWER"))
{
true_rclass[i][j] = 0;
}
else
{
PhyML_Printf("\n. Err in file %s at line %d\n\n",__FILE__,__LINE__);
Warn_And_Exit("\n");
}
}
}
For(j,2*tree->n_otu-3)
{
Free_Edge_Labels(tree->t_edges[j]);
tree->t_edges[j]->n_labels = 0;
}
/* Generate the memory needed for likelihood calculation because
we will need bigger arrays
*/
Free_Tree_Lk(tree);
Free_Tree_Pars(tree);
tree->data = cpy_data;
tree->n_pattern = tree->data->crunch_len;
/* Allocate memory and initialize likelihood structure with
simulated sequences (i.e., columns are not compressed)
*/
Make_Tree_4_Pars(tree,cpy_data,cpy_data->init_len);
Make_Tree_4_Lk(tree,cpy_data,cpy_data->init_len);
/* Estimate model parameters */
PhyML_Printf("\n. Estimating model parameters...\n");
tree->mod->s_opt->opt_cov_alpha = 1;
tree->mod->s_opt->opt_cov_delta = 1;
Round_Optimize(tree,tree->data,ROUND_MAX);
tree->both_sides = 1;
Lk(tree);
/* Classify branches */
best_probs = M4_Site_Branch_Classification(M4_Compute_Proba_Hidden_States_On_Edges(tree),tree);
For(i,tree->data->init_len)
{
For(j,2*tree->n_otu-3)
{
if(!strcmp(tree->t_edges[j]->labels[i],"FASTER"))
{
est_rclass[i][j] = 1;
}
else if(!strcmp(tree->t_edges[j]->labels[i],"SLOWER"))
{
est_rclass[i][j] = 0;
}
else if(!strcmp(tree->t_edges[j]->labels[i],"UNKNOWN"))
{
est_rclass[i][j] = -1;
}
else
{
PhyML_Printf("\n. Err in file %s at line %d\n\n",__FILE__,__LINE__);
Warn_And_Exit("\n");
}
}
}
unknown = .0;
correct_class = .0;
mis_class = .0;
For(i,tree->data->init_len)
{
For(j,2*tree->n_otu-3)
{
/* PhyML_Printf("\n. Edge %3d %4d %4d - %f",j,true_rclass[i][j],est_rclass[i][j],best_probs[i][j]); */
if(est_rclass[i][j] == -1)
{
unknown += 1.;
}
else if(est_rclass[i][j] == true_rclass[i][j])
{
correct_class += 1.;
}
else if(est_rclass[i][j] != true_rclass[i][j])
{
mis_class += 1.;
}
else
{
PhyML_Printf("\n. Err in file %s at line %d\n\n",__FILE__,__LINE__);
Warn_And_Exit("\n");
}
}
/* PhyML_Printf("\n"); */
}
correct_class /= ((tree->data->init_len * (2*tree->n_otu-3)) - unknown);
mis_class /= ((tree->data->init_len * (2*tree->n_otu-3)) - unknown);
unknown /= (tree->data->init_len * (2*tree->n_otu-3));
PhyML_Printf("\n. correct_class = %f mis_class = %f unknown = %f",
correct_class,
mis_class,
unknown);
For(i,tree->data->init_len)
{
Free(true_rclass[i]);
Free(est_rclass[i]);
Free(best_probs[i]);
}
Free(true_rclass);
Free(est_rclass);
Free(best_probs);
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
/* Scale branch lengths such that they express expected number
of nucleotide or amino-acid substitutions */
void M4_Scale_Br_Len(t_tree *tree)
{
phydbl scale_fact,mrs;
int i,j;
/* (1) Work out the relative mean rate of switches */
mrs = .0;
For(i,tree->mod->m4mod->n_h)
{
For(j,tree->mod->m4mod->n_h)
{
if(j != i)
mrs += tree->mod->m4mod->h_fq[i] * tree->mod->m4mod->h_mat[i*tree->mod->m4mod->n_h+j];
}
}
/* (2) scale_fact = (1 + delta x mrs) */
scale_fact = 1.0 + tree->mod->m4mod->delta * mrs;
/* (3) Scale branch lengths */
For(i,2*tree->n_otu-3) tree->t_edges[i]->l /= scale_fact;
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void M4_Free_Integral_Term_On_One_Edge(phydbl ****integral, t_tree *tree)
{
int g,i,j;
For(g,tree->mod->n_catg)
{
For(i,tree->mod->m4mod->n_h)
{
For(j,tree->mod->m4mod->n_h)
{
Free(integral[g][i][j]);
}
Free(integral[g][i]);
}
Free(integral[g]);
}
Free(integral);
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void M4_Detect_Site_Switches_Experiment(t_tree *tree)
{
model *nocov_mod,*cov_mod,*ori_mod;
calign *ori_data,*cpy_data;
int i,n_iter,ns;
phydbl *nocov_bl,*cov_bl;
phydbl *site_lnl_nocov, *site_lnl_cov;
nocov_bl = (phydbl *)mCalloc(2*tree->n_otu-3,sizeof(phydbl));
cov_bl = (phydbl *)mCalloc(2*tree->n_otu-3,sizeof(phydbl));
site_lnl_nocov = (phydbl *)mCalloc(tree->data->init_len,sizeof(phydbl));
site_lnl_cov = (phydbl *)mCalloc(tree->data->init_len,sizeof(phydbl));
ori_data = tree->data;
ori_mod = tree->mod;
if(tree->io->datatype == NT) ns = 4;
else if(tree->io->datatype == AA) ns = 20;
else
{
PhyML_Printf("\n. Not implemented yet.");
PhyML_Printf("\n. Err in file %s at line %d\n",__FILE__,__LINE__);
Warn_And_Exit("");
}
cpy_data = Copy_Cseq(tree->data,tree->io);
PhyML_Printf("\n. Estimate model parameters under non-switching substitution model.\n");
Switch_From_M4mod_To_Mod(tree->mod);
Simu_Loop(tree);
nocov_mod = (model *)Copy_Model(tree->mod); /* Record model parameters */
For(i,2*tree->n_otu-3) nocov_bl[i] = tree->t_edges[i]->l; /* Record branch lengths */
For(i,tree->data->crunch_len) site_lnl_nocov[i] = tree->cur_site_lk[i];
Print_Lk(tree,"[LnL under non-switching substitution model]");
PhyML_Printf("\n. Estimate model parameters under switching substitution model.\n");
Switch_From_Mod_To_M4mod(tree->mod);
Simu_Loop(tree);
cov_mod = (model *)Copy_Model(tree->mod); /* Record model parameters */
For(i,2*tree->n_otu-3) cov_bl[i] = tree->t_edges[i]->l; /* Record branch lengths */
For(i,tree->data->crunch_len) site_lnl_cov[i] = tree->cur_site_lk[i];
Print_Lk(tree,"[LnL under switching substitution model]");
PhyML_Printf("\n");
For(i,tree->data->crunch_len) PhyML_Printf("TRUTH %f %f\n",site_lnl_nocov[i],site_lnl_cov[i]);
/* Generate a simulated data set under H0, with the right sequence length. */
tree->mod = nocov_mod;
Evolve(cpy_data, nocov_mod, tree);
/* Generate the memory needed for likelihood calculation because
we will need bigger arrays
*/
tree->mod = cov_mod;
Free_Tree_Lk(tree);
Free_Tree_Pars(tree);
tree->data = cpy_data;
tree->n_pattern = tree->data->crunch_len;
tree->mod = cov_mod;
/* Allocate memory and initialize likelihood structure with
simulated sequences (i.e., columns are not compressed)
*/
Make_Tree_4_Pars(tree,cpy_data,cpy_data->init_len);
Make_Tree_4_Lk(tree,cpy_data,cpy_data->init_len);
n_iter = 0;
do
{
/* Get the transition proba right to generate sequences */
tree->mod = nocov_mod;
For(i,2*tree->n_otu-3) tree->t_edges[i]->l = nocov_bl[i];
For(i,2*tree->n_otu-3) Update_PMat_At_Given_Edge(tree->t_edges[i],tree);
/* Generate sequences */
Evolve(cpy_data, nocov_mod, tree);
tree->data = cpy_data;
if(tree->mod->s_opt->greedy) Init_P_Lk_Tips_Double(tree);
else Init_P_Lk_Tips_Int(tree);
tree->mod = nocov_mod;
For(i,2*tree->n_otu-3) tree->t_edges[i]->l = nocov_bl[i];
Lk(tree);
For(i,tree->data->crunch_len) site_lnl_nocov[i] = tree->cur_site_lk[i];
Print_Lk(tree,"[CPY LnL under non-switching substitution model]");
tree->mod = cov_mod;
For(i,2*tree->n_otu-3) tree->t_edges[i]->l = cov_bl[i];
Lk(tree);
For(i,tree->data->crunch_len) site_lnl_cov[i] = tree->cur_site_lk[i];
Print_Lk(tree,"[CPY LnL under switching substitution model]");
PhyML_Printf("\n");
For(i,tree->data->crunch_len) PhyML_Printf("SYNTH %f %f\n",site_lnl_nocov[i],site_lnl_cov[i]);
}
while(++n_iter < 200);
Free_Tree_Lk(tree);
Free_Tree_Pars(tree);
/* Back to the original data set to check that everything is ok */
tree->data = ori_data;
tree->n_pattern = tree->data->crunch_len;
Make_Tree_4_Pars(tree,ori_data,ori_data->init_len);
Make_Tree_4_Lk(tree,ori_data,ori_data->init_len);
tree->mod = nocov_mod;
For(i,2*tree->n_otu-3) tree->t_edges[i]->l = nocov_bl[i];
Lk(tree);
Print_Lk(tree,"[FINAL LnL under non-switching substitution model]");
tree->mod = cov_mod;
For(i,2*tree->n_otu-3) tree->t_edges[i]->l = cov_bl[i];
Lk(tree);
Print_Lk(tree,"[FINAL LnL under switching substitution model]");
tree->mod = ori_mod;
Free_Model(cov_mod);
Free_Model(nocov_mod);
Free(site_lnl_cov);
Free(site_lnl_nocov);
Free_Cseq(cpy_data);
Free(nocov_bl);
Free(cov_bl);
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void M4_Posterior_Prediction_Experiment(t_tree *tree)
{
model *ori_mod;
calign *ori_data,*cpy_data;
int i,n_iter,n_simul,ns;
FILE *fp_nocov,*fp_cov,*fp_obs;
char *s;
t_edge *best_edge;
s = (char *)mCalloc(100,sizeof(char));
best_edge = NULL;
strcpy(s,tree->io->in_align_file);
fp_nocov = Openfile(strcat(s,"_nocov"),1);
strcpy(s,tree->io->in_align_file);
fp_cov = Openfile(strcat(s,"_cov"),1);
strcpy(s,tree->io->in_align_file);
fp_obs = Openfile(strcat(s,"_obs"),1);
Free(s);
Print_Diversity_Header(fp_nocov, tree);
Print_Diversity_Header(fp_cov, tree);
Print_Diversity_Header(fp_obs, tree);
ori_data = tree->data;
ori_mod = tree->mod;
if(tree->io->datatype == NT) ns = 4;
else if(tree->io->datatype == AA) ns = 20;
else
{
PhyML_Printf("\n. Not implemented yet.");
PhyML_Printf("\n. Err in file %s at line %d\n",__FILE__,__LINE__);
Warn_And_Exit("");
}
cpy_data = Copy_Cseq(tree->data,tree->io);
/* Generate a simulated data set under H0, with the right sequence length. */
Set_Model_Parameters(tree->mod);
For(i,2*tree->n_otu-3) Update_PMat_At_Given_Edge(tree->t_edges[i],tree);
Evolve(cpy_data,tree->mod,tree);
/* Generate the memory needed for likelihood calculation because
we will need bigger arrays
*/
Free_Tree_Lk(tree);
Free_Tree_Pars(tree);
tree->data = cpy_data;
tree->n_pattern = tree->data->crunch_len;
/* Allocate memory and initialize likelihood structure with
simulated sequences (i.e., columns are not compressed)
*/
Make_Tree_4_Pars(tree,cpy_data,cpy_data->init_len);
Make_Tree_4_Lk(tree,cpy_data,cpy_data->init_len);
/* Go back to the original data set */
tree->data = ori_data;
tree->n_pattern = ori_data->crunch_len;
if(tree->mod->s_opt->greedy) Init_P_Lk_Tips_Double(tree);
else Init_P_Lk_Tips_Int(tree);
PhyML_Printf("\n. Estimate model parameters under non-switching substitution model.\n");
Switch_From_M4mod_To_Mod(tree->mod);
tree->bl_from_node_stamps = 1;
/* best_edge = TIMES_Find_Best_Root_Position(tree); */
PhyML_Printf("\n. Put root on t_edge %3d",i);
TIMES_Least_Square_Node_Times(best_edge,tree);
TIMES_Adjust_Node_Times(tree);
/* TIMES_Round_Optimize(tree); */
/* Round_Optimize(tree,tree->data); */
/* Simu_Loop(tree); */
Print_Lk(tree,"[LnL under non-switching substitution model]");
Print_Tree(tree->io->fp_out_tree,tree);
/* Print observed diversities */
Init_Ui_Tips(tree);
Site_Diversity(tree);
Print_Diversity(fp_obs,tree);
n_simul = 100;
n_iter = 0;
do
{
Evolve(cpy_data,tree->mod,tree);
tree->data = cpy_data;
tree->n_pattern = cpy_data->init_len;
if(tree->mod->s_opt->greedy) Init_P_Lk_Tips_Double(tree);
else Init_P_Lk_Tips_Int(tree);
Lk(tree);
Init_Ui_Tips(tree);
Site_Diversity(tree);
Print_Diversity(fp_nocov,tree);
Print_Lk(tree,"[CPY under non-switching substitution model]");
}while(++n_iter < n_simul);
/* Go back to the original data set */
tree->data = ori_data;
tree->n_pattern = ori_data->crunch_len;
if(tree->mod->s_opt->greedy) Init_P_Lk_Tips_Double(tree);
else Init_P_Lk_Tips_Int(tree);
PhyML_Printf("\n. Estimate model parameters under switching substitution model.\n");
Switch_From_Mod_To_M4mod(tree->mod);
/* TIME_Round_Optimize(tree); */
/* Round_Optimize(tree,tree->data); */
/* Simu_Loop(tree); */
Print_Lk(tree,"[LnL under switching substitution model]");
Print_Tree(tree->io->fp_out_tree,tree);
n_iter = 0;
do
{
Evolve(cpy_data,tree->mod,tree);
tree->data = cpy_data;
tree->n_pattern = cpy_data->init_len;
if(tree->mod->s_opt->greedy) Init_P_Lk_Tips_Double(tree);
else Init_P_Lk_Tips_Int(tree);
Lk(tree);
Init_Ui_Tips(tree);
Site_Diversity(tree);
Print_Diversity(fp_cov,tree);
Print_Lk(tree,"[LnL under switching substitution model]");
}while(++n_iter < n_simul);
fclose(fp_obs);
fclose(fp_nocov);
fclose(fp_cov);
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
m4 *M4_Copy_M4_Model(model *ori_mod, m4 *ori_m4mod)
{
int i,j,n_h, n_o;
m4 *cpy_m4mod;
int ns;
if(ori_mod->io->datatype == NT) ns = 4;
else if(ori_mod->io->datatype == AA) ns = 20;
else
{
PhyML_Printf("\n. Not implemented yet.");
PhyML_Printf("\n. Err in file %s at line %d\n",__FILE__,__LINE__);
Warn_And_Exit("");
}
cpy_m4mod = (m4 *)M4_Make_Light();
cpy_m4mod->n_o = ori_m4mod->n_o;
cpy_m4mod->n_h = ori_m4mod->n_h;
if(ori_mod->use_m4mod)
{
M4_Make_Complete(cpy_m4mod->n_h,
cpy_m4mod->n_o,
cpy_m4mod);
n_h = cpy_m4mod->n_h;
n_o = cpy_m4mod->n_o;
cpy_m4mod->n_h = ori_m4mod->n_h;
cpy_m4mod->n_o = ori_m4mod->n_o;
For(i,n_h) For(j,n_o*n_o) cpy_m4mod->o_mats[i][j] = ori_m4mod->o_mats[i][j];
For(i,n_h) cpy_m4mod->multipl[i] = ori_m4mod->multipl[i];
For(i,n_h) cpy_m4mod->multipl_unscaled[i] = ori_m4mod->multipl_unscaled[i];
For(i,n_o*n_o) cpy_m4mod->o_rr[i] = ori_m4mod->o_rr[i];
For(i,n_h*n_h) cpy_m4mod->h_rr[i] = ori_m4mod->h_rr[i];
For(i,n_h*n_h) cpy_m4mod->h_mat[i] = ori_m4mod->h_mat[i];
For(i,n_o) cpy_m4mod->o_fq[i] = ori_m4mod->o_fq[i];
For(i,n_h) cpy_m4mod->h_fq[i] = ori_m4mod->h_fq[i];
For(i,n_h) cpy_m4mod->h_fq_unscaled[i] = ori_m4mod->h_fq_unscaled[i];
cpy_m4mod->delta = ori_m4mod->delta;
cpy_m4mod->alpha = ori_m4mod->alpha;
}
return cpy_m4mod;
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
phyml-20120412/src/mg.h 0000644 0001750 0001750 00000006670 11637265602 011405 0000000 0000000 #include
#ifndef PART_H
#define PART_H
#include "utilities.h"
void Menu_Supertree(option *input);
void PART_Print_Nodes(t_node *a, t_node *d, supert_tree *st);
supert_tree *PART_Make_Supert_tree_Light(option *input);
void PART_Make_Supert_tree_Full(supert_tree *st, option *input, calign **data);
void PART_Get_List_Of_Reachable_Tips(t_node *a, t_node *d, calign **data, supert_tree *st);
void PART_Get_List_Of_Reachable_Tips_Pre(t_node *a, t_node *d, supert_tree *st);
void PART_Get_List_Of_Reachable_Tips_Post(t_node *a, t_node *d, supert_tree *st);
void PART_Prune_St_Topo(t_tree *tree, calign *data, supert_tree *st);
void PART_Match_St_Nodes_In_Gt_Recurr(t_node *a_gt, t_node *d_gt, t_node *a_st, t_node *d_st, t_tree *gt, supert_tree *st);
void PART_Match_St_Nodes_In_Gt(t_tree *tree, supert_tree *st);
void PART_Match_St_Edges_In_Gt(t_tree *gt, supert_tree *st);
void PART_Match_St_Edges_In_Gt_Recurr(t_node *a, t_node *d, t_node *a_st, t_node *d_st, t_tree *gt, supert_tree *st);
void PART_Simu(supert_tree *tr);
int PART_Mov_Backward_Topo_Bl(supert_tree *st, phydbl lk_old, t_edge **tested_b, int n_tested);
int PART_Get_Species_Found_In_St(supert_tree *st, calign *data);
void PART_Map_St_Nodes_In_Gt_Pre(t_node *a_st, t_node *d_st, t_tree *gt, supert_tree *st);
void PART_Map_St_Nodes_In_Gt_Post(t_node *a_st, t_node *d_st, t_tree *gt, supert_tree *st);
void PART_Map_St_Nodes_In_Gt(t_tree *gt, supert_tree *st);
void PART_Map_St_Nodes_In_Gt_One_Edge(t_node *a_st, t_node *d_st, t_edge *b_st, t_tree *gt, supert_tree *st);
void PART_Map_St_Edges_In_Gt(t_tree *gt, supert_tree *st);
phydbl PART_Lk(supert_tree *st);
int PART_Pars(supert_tree *st);
int PART_Spr(phydbl init_lnL, supert_tree *st);
void PART_Speed_Spr(supert_tree *st);
int Map_Spr_Move(t_edge *st_pruned, t_edge *st_target, t_node *st_link, t_tree *gt, supert_tree *st);
void PART_Test_All_Spr_Targets(t_edge *pruned, t_node *n_link, supert_tree *st);
void PART_Test_One_Spr_Target_Recur(t_node *a, t_node *d, t_edge *target, t_edge *pruned, t_node *n_link, supert_tree *st);
void PART_Test_One_Spr_Target(t_edge *st_p, t_edge *st_t, t_node *n_link, supert_tree *st);
int PART_Test_List_Of_Regraft_Pos(spr **st_spr_list, int list_size, supert_tree *st);
int PART_Try_One_Spr_Move(spr *st_move, supert_tree *st);
void PART_Map_Gt_Edges_In_St(t_tree *gt, supert_tree *st);
void PART_NNI(t_edge *st_b, supert_tree *st);
void PART_Swap(t_node *st_a, t_node *st_b, t_node *st_c, t_node *st_d, supert_tree *st);
void PART_Set_Bl(phydbl **bl, supert_tree *st);
void PART_Restore_Br_Len(supert_tree *st);
void PART_Record_Br_Len(supert_tree *st);
phydbl PART_Lk_At_Given_Edge(t_edge *st_b, supert_tree *st);
phydbl PART_Update_Lk_At_Given_Edge(t_edge *st_b, supert_tree *st);
void PART_Fill_Model_Partitions_Table(supert_tree *st);
phydbl PART_Br_Len_Brent(t_edge *st_b, int quickdirty, supert_tree *tree);
void PART_Initialise_Bl_Partition(supert_tree *st);
void PART_Update_P_Lk(t_edge *st_b, t_node *st_n, supert_tree *st);
void PART_Optimize_Br_Len_Serie(t_node *st_a, t_node *st_d, t_edge *st_b, supert_tree *st);
void PART_Update_Bl_Swaped(t_edge **st_b, int n, supert_tree *st);
void PART_Update_Bl(phydbl fact, supert_tree *st);
void PART_Make_N_Swap(t_edge **st_b, int beg, int end, supert_tree *st);
void PART_Do_Mapping(supert_tree *st);
void PART_Update_PMat(t_edge *st_b, supert_tree *st);
void PART_Print_Bl(supert_tree *st);
void PART_Check_Extra_Taxa(supert_tree *st);
int PART_main(int argc, char **argv);
#endif
phyml-20120412/src/tiporder.h 0000644 0001750 0001750 00000004047 11637265713 012631 0000000 0000000 /*
PhyML: a program that computes maximum likelihood phylogenies from
DNA or AA homologous sequences.
Copyright (C) Stephane Guindon. Oct 2003 onward.
All parts of the source except where indicated are distributed under
the GNU public licence. See http://www.opensource.org for details.
*/
#include
#ifndef TIPORDER_H
#define TIPORDER_H
#include "times.h"
#include "spr.h"
#include "utilities.h"
#include "lk.h"
#include "optimiz.h"
#include "bionj.h"
#include "models.h"
#include "free.h"
#include "help.h"
#include "simu.h"
#include "eigen.h"
#include "pars.h"
#include "alrt.h"
#include "m4.h"
#include "draw.h"
#include "rates.h"
#include "mcmc.h"
#include "stats.h"
void TIPO_Get_Tips_Y_Rank(t_tree *tree);
void TIPO_Get_Tips_Y_Rank_Pre(t_node *a, t_node *d, phydbl *curr_rank, t_tree *tree);
void TIPO_Get_All_Y_Rank(t_tree *tree);
void TIPO_Get_All_Y_Rank_Pre(t_node *a, t_node *d, t_tree *tree);
void TIPO_Swap_One_Node(t_node *d, t_tree *tree);
void TIPO_Minimize_Tip_Order_Score(int n_trees, t_tree **list_tree, t_tree *ref_tree);
void TIPO_Print_Tip_Ordered(t_tree *ref_tree);
void TIPO_Print_Tip_Ordered_Pre(t_node *a, t_node *d, t_tree *ref_tree);
phydbl TIPO_Untangle_Tree(t_tree *tree);
void TIPO_Untangle_Node(t_node *a, t_node *d, t_node **node_table, int *conflict, t_tree *tree);
int TIPO_Untangle_Tree_List(int n_trees, t_tree **list_tree, t_tree *ref_tree);
int TIPO_Check_Tip_Ranks(t_tree *tree);
void TIPO_Read_Taxa_Coordinates(FILE *fp_coord, t_tree *tree);
void TIPO_Get_Tips_Y_Rank_From_Zscores(t_tree *tree);
void TIPO_Init_Tip_Num(t_tree *tree);
void TIPO_Read_Taxa_Zscores(FILE *fp_coord, t_tree *tree);
void TIPO_Sort_Translation_Table(t_tree *tree);
void TIPO_Randomize_Tip_Y_Ranks(t_tree *tree);
phydbl TIPO_Read_One_Taxon_Zscore(FILE *fp, char *seqname_qry, int col, t_tree *tree);
void TIPO_Normalize_Zscores(t_tree *tree);
void TIPO_Get_Min_Number_Of_Tip_Permut(t_tree *tree);
phydbl TIPO_Lk(t_tree *tree);
phydbl TIPO_Lk_Post(t_node *a, t_node *d, t_tree *tree);
phydbl TIPO_Lk_Core(t_node *a, t_node *d, t_tree *tree);
#endif
phyml-20120412/src/mpi_boot.h 0000644 0001750 0001750 00000001334 11741127407 012576 0000000 0000000 /*
PhyML: a program that computes maximum likelihood phylogenies from
DNA or AA homologous sequences.
Copyright (C) Stephane Guindon. Oct 2003 onward.
All parts of the source except where indicated are distributed under
the GNU public licence. See http://www.opensource.org for details.
*/
#include
#ifndef MPI_H
#define MPI_H
#include "mpi.h"
#include "utilities.h"
#include "bionj.h"
#include "lk.h"
#include "pars.h"
#include "free.h"
#include "models.h"
#include "simu.h"
#include "spr.h"
#define BootTreeTag 0
#define BootStatTag 1
int Global_numTask, Global_myRank;
void Bootstrap_MPI(t_tree *tree);
void Print_Fp_Out_Lines_MPI(t_tree *tree, option *io, int n_data_set, char *bootStr);
#endif // MPI
phyml-20120412/src/utilities.h 0000644 0001750 0001750 00000204114 11741142226 012776 0000000 0000000 /*
PhyML: a program that computes maximum likelihood phylogenies from
DNA or AA homologous sequences.
Copyright (C) Stephane Guindon. Oct 2003 onward.
All parts of the source except where indicated are distributed under
the GNU public licence. See http://www.opensource.org for details.
*/
#include
#ifndef UTILITIES_H
#define UTILITIES_H
#include
#include
#include
#include
#include
#include
#include
#include
#include
#include
#define For(i,n) for(i=0; i(b)?(a):(b))
#define MIN(a,b) ((a)<(b)?(a):(b))
#define SIGN(a,b) ((b) > 0.0 ? fabs(a) : -fabs(a))
#define SHFT(a,b,c,d) (a)=(b);(b)=(c);(c)=(d);
#ifndef isnan
# define isnan(x) \
(sizeof (x) == sizeof (long double) ? isnan_ld (x) \
: sizeof (x) == sizeof (double) ? isnan_d (x) \
: isnan_f (x))
static inline int isnan_f (float x) { return x != x; }
static inline int isnan_d (double x) { return x != x; }
static inline int isnan_ld (long double x) { return x != x; }
#endif
#ifndef isinf
# define isinf(x) \
(sizeof (x) == sizeof (long double) ? isinf_ld (x) \
: sizeof (x) == sizeof (double) ? isinf_d (x) \
: isinf_f (x))
static inline int isinf_f (float x) { return isnan (x - x); }
static inline int isinf_d (double x) { return isnan (x - x); }
static inline int isinf_ld (long double x) { return isnan (x - x); }
#endif
#define MCMC_MOVE_RANDWALK_UNIFORM 0
#define MCMC_MOVE_LOG_RANDWALK_UNIFORM 1
#define MCMC_MOVE_RANDWALK_NORMAL 2
#define MCMC_MOVE_LOG_RANDWALK_NORMAL 3
#define MCMC_MOVE_SCALE_THORNE 4
#define MCMC_MOVE_SCALE_GAMMA 5
#define N_MAX_MOVES 50
#define N_MAX_NEX_COM 20
#define T_MAX_NEX_COM 100
#define N_MAX_NEX_PARM 50
#define T_MAX_TOKEN 200
#define NEXUS_COM 0
#define NEXUS_PARM 1
#define NEXUS_EQUAL 2
#define NEXUS_VALUE 3
#define NEXUS_SPACE 4
#define NNI_MOVE 0
#define SPR_MOVE 1
#define BEST_OF_NNI_AND_SPR 2
#define M_1_SQRT_2_PI 0.398942280401432677939946059934
#define M_SQRT_32 5.656854249492380195206754896838
#define PI 3.14159265358979311600
#define SQRT2PI 2.50662827463100024161
#define LOG2PI 1.83787706640934533908
#define LOG2 0.69314718055994528623
#define LOG_SQRT_2_PI 0.918938533204672741780329736406
#define NORMAL 1
#define EXACT 2
#define PHYLIP 0
#define NEXUS 1
#define YES 1
#define NO 0
#define TRUE 1
#define FALSE 0
#define NT 0 /*! nucleotides */
#define AA 1 /*! amino acids */
#define GENERIC 2 /*! custom alphabet */
#define UNDEFINED 3
#define ACGT 0 /*! A,G,G,T encoding */
#define RY 1 /*! R,Y encoding */
#define INTERFACE_DATA_TYPE 0
#define INTERFACE_MULTIGENE 1
#define INTERFACE_MODEL 2
#define INTERFACE_TOPO_SEARCH 3
#define INTERFACE_BRANCH_SUPPORT 4
#ifndef INFINITY
#define INFINITY HUGE
#endif
#define N_MAX_OPTIONS 100
#define T_MAX_FILE 500
#define T_MAX_LINE 2000000
#define T_MAX_NAME 100
#define T_MAX_SEQ 2000000
#define T_MAX_OPTION 100
#define T_MAX_LABEL 10
#define T_MAX_STATE 5
#define N_MAX_LABEL 10
#define BLOCK_LABELS 100
#define NODE_DEG_MAX 500
#define BRENT_ITMAX 10000
#define BRENT_CGOLD 0.3819660
#define BRENT_ZEPS 1.e-10
#define MNBRAK_GOLD 1.618034
#define MNBRAK_GLIMIT 100.0
#define MNBRAK_TINY 1.e-20
#define ALPHA_MIN 0.04
#define ALPHA_MAX 100
#define BL_START 1.e-04
#define GOLDEN_R 0.61803399
#define GOLDEN_C (1.0-GOLDEN_R)
#define N_MAX_INSERT 20
#define N_MAX_OTU 4000
#define UNLIKELY -1.e10
#define NJ_SEUIL 0.1
#define ROUND_MAX 100
#define DIST_MAX 2.00
#define AROUND_LK 50.0
#define PROP_STEP 1.0
#define T_MAX_ALPHABET 100
#define MDBL_MIN FLT_MIN
#define MDBL_MAX FLT_MAX
#define POWELL_ITMAX 200
#define LINMIN_TOL 2.0E-04
#define SCALE_POW 10 /*! Scaling factor will be 2^SCALE_POW or 2^(-SCALE_POW) [[ WARNING: SCALE_POW < 31 ]]*/
#define DEFAULT_SIZE_SPR_LIST 20
#define NEWICK 0
#define NEXUS 1
#define OUTPUT_TREE_FORMAT NEWICK
#define MAX_PARS 1000000000
#define LIM_SCALE_VAL 1.E-50 /*! Scaling limit (deprecated) */
#define MIN_CLOCK_RATE 1.E-10
#define MIN_VAR_BL 1.E-8
#define MAX_VAR_BL 1.E+3
#define JC69 1
#define K80 2
#define F81 3
#define HKY85 4
#define F84 5
#define TN93 6
#define GTR 7
#define CUSTOM 8
#define WAG 11
#define DAYHOFF 12
#define JTT 13
#define BLOSUM62 14
#define MTREV 15
#define RTREV 16
#define CPREV 17
#define DCMUT 18
#define VT 19
#define MTMAM 20
#define MTART 21
#define HIVW 22
#define HIVB 23
#define CUSTOMAA 24
#define LG 25
// Amino acid ordering:
// Ala Arg Asn Asp Cys Gln Glu Gly His Ile Leu Lys Met Phe Pro Ser Thr Trp Tyr Val
#define COMPOUND_COR 0
#define COMPOUND_NOCOR 1
#define EXPONENTIAL 2
#define GAMMA 3
#define THORNE 4
#define GUINDON 5
#define STRICTCLOCK 6
#define NONE -1
#define ALRTSTAT 1
#define ALRTCHI2 2
#define MINALRTCHI2SH 3
#define SH 4
#define ABAYES 5
/* #define USE_OLD_LK */
/* /\* Uncomment the lines below to switch to single precision *\/ */
/* typedef float phydbl; */
/* #define LOG logf */
/* #define POW powf */
/* #define EXP expf */
/* #define FABS fabsf */
/* #define SQRT sqrtf */
/* #define CEIL ceilf */
/* #define FLOOR floorf */
/* #define RINT rintf */
/* #define ROUND roundf */
/* #define TRUNC truncf */
/* #define COS cosf */
/* #define SIN sinf */
/* #define TAN tanf */
/* #define SMALL FLT_MIN */
/* #define BIG FLT_MAX */
/* #define SMALL_PIJ 1.E-10 */
/* #define BL_MIN 1.E-5 */
/* #define P_LK_LIM_INF 2.168404e-19 /\* 2^-62 *\/ */
/* #define P_LK_LIM_SUP 4.611686e+18 /\* 2^62 *\/ */
/* Uncomment the line below to switch to double precision */
typedef double phydbl;
#define LOG log
#define POW pow
#define EXP exp
#define FABS fabs
#define SQRT sqrt
#define CEIL ceil
#define FLOOR floor
#define RINT rint
#define ROUND round
#define TRUNC trunc
#define COS cos
#define SIN sin
#define TAN tan
#define SMALL DBL_MIN
#define BIG DBL_MAX
#define SMALL_PIJ 1.E-20
#ifndef PHYTIME
#define BL_MIN 1.E-8
#define BL_MAX 100.
#else
#define BL_MIN 1.E-6
#define BL_MAX 1.
#endif
/* #define P_LK_LIM_INF 7.888609052e-31 */
/* #define P_LK_LIM_MAX 1.267650600e+30 */
/* #define P_LK_LIM_INF 4.909093465e-91 /\* R: format(2^(-300),digits=10) *\/ */
/* #define P_LK_LIM_SUP 2.037035976e+90 /\* R: format(2^(+300),digits=10) *\/ */
#define P_LK_LIM_INF 3.054936e-151 /* 2^-500 */
#define P_LK_LIM_SUP 3.273391e+150 /* 2^500 */
/*!********************************************************/
typedef struct __Scalar_Int {
int v;
short int reflect;
}scalar_int;
/*!********************************************************/
typedef struct __Scalar_Dbl {
phydbl v;
short int reflect;
}scalar_dbl;
/*!********************************************************/
typedef struct __Vect_Int {
int *v;
short int reflect;
int len;
}vect_int;
/*!********************************************************/
typedef struct __Vect_Dbl {
phydbl *v;
short int reflect;
int len;
}vect_dbl;
/*!********************************************************/
typedef struct __Node {
struct __Node **v; /*! table of pointers to neighbor nodes. Dimension = 3 */
struct __Node ***bip_node; /*! three lists of pointer to tip nodes. One list for each direction */
struct __Edge **b; /*! table of pointers to neighbor branches */
struct __Node *anc; /*! direct ancestor t_node (for rooted tree only) */
struct __Node *ext_node;
struct __Node *match_node;
int *bip_size; /*! Size of each of the three lists from bip_node */
int num; /*! t_node number */
int tax; /*! tax = 1 -> external node, else -> internal t_node */
int check_branch; /*! check_branch=1 is the corresponding branch is labelled with '*' */
char *name; /*! taxon name (if exists) */
char *ori_name; /*! taxon name (if exists) */
phydbl *score; /*! score used in BioNJ to determine the best pair of nodes to agglomerate */
phydbl *l; /*! lengths of the (three or one) branche(s) connected this t_node */
phydbl dist_to_root; /*! distance to the root t_node */
short int common;
phydbl y_rank;
phydbl y_rank_ori;
phydbl y_rank_min;
phydbl y_rank_max;
int *s_ingrp; /*! does the subtree beneath belong to the ingroup */
int *s_outgrp; /*! does the subtree beneath belong to the outgroup */
int id_rank; /*! order taxa alphabetically and use id_rank to store the ranks */
int rank;
int rank_max;
}t_node;
/*!********************************************************/
typedef struct __Edge {
/*!
syntax : (node) [edge]
(left_1) . .(right_1)
\ (left) (right) /
\._____________./
/ [b_fcus] \
/ \
(left_2) . .(right_2)
*/
struct __Node *left,*rght; /*! t_node on the left/right side of the t_edge */
short int l_r,r_l,l_v1,l_v2,r_v1,r_v2;
/*! these are directions (i.e., 0, 1 or 2): */
/*! l_r (left to right) -> left[b_fcus->l_r] = right */
/*! r_l (right to left) -> right[b_fcus->r_l] = left */
/*! l_v1 (left t_node to first t_node != from right) -> left[b_fcus->l_v1] = left_1 */
/*! l_v2 (left t_node to secnd t_node != from right) -> left[b_fcus->l_v2] = left_2 */
/*! r_v1 (right t_node to first t_node != from left) -> right[b_fcus->r_v1] = right_1 */
/*! r_v2 (right t_node to secnd t_node != from left) -> right[b_fcus->r_v2] = right_2 */
struct __NNI *nni;
int num; /*! branch number */
phydbl l; /*! branch length */
phydbl best_l; /*! best branch length found so far */
phydbl l_old; /*! old branch length */
int bip_score; /*! score of the bipartition generated by the corresponding edge
bip_score = 1 iif the branch is found in both trees to be compared,
bip_score = 0 otherwise. */
phydbl *p_lk_left,*p_lk_rght; /*! likelihoods of the subtree on the left and
right side (for each site and each relative rate category) */
short int *p_lk_tip_r, *p_lk_tip_l;
short int *div_post_pred_left; /*! posterior prediction of nucleotide/aa diversity (left-hand subtree) */
short int *div_post_pred_rght; /*! posterior prediction of nucleotide/aa diversity (rght-hand subtree) */
short int does_exist;
int *patt_id_left;
int *patt_id_rght;
int *p_lk_loc_left;
int *p_lk_loc_rght;
phydbl *Pij_rr; /*! matrix of change probabilities and its first and secnd derivates */
int *pars_l,*pars_r; /*! parsimony of the subtree on the left and right sides (for each site) */
unsigned int *ui_l, *ui_r; /*! union - intersection vectors used in Fitch's parsimony algorithm */
int *p_pars_l, *p_pars_r; /*! conditional parsimony vectors */
int num_st_left; /*! number of the subtree on the left side */
int num_st_rght; /*! number of the subtree on the right side */
/*! Below are the likelihood scaling factors (used in functions
`Get_All_Partial_Lk_Scale' in lk.c */
int *sum_scale_left_cat;
int *sum_scale_rght_cat;
int *sum_scale_left;
int *sum_scale_rght;
phydbl bootval; /*! bootstrap value (if exists) */
short int is_alive; /*! is_alive = 1 if this t_edge is used in a tree */
phydbl dist_btw_edges;
int topo_dist_btw_edges;
int has_zero_br_len;
phydbl ratio_test; /*! approximate likelihood ratio test */
phydbl alrt_statistic; /*! aLRT statistic */
char **labels; /*! string of characters that labels the corresponding t_edge */
int n_labels; /*! number of labels */
int n_jumps; /*! number of jumps of substitution rates */
phydbl gamma_prior_mean; /* Branch length has a gamma distributed prior with this mean */
phydbl gamma_prior_var; /* Branch length has a gamma distributed prior with this var */
phydbl gamma_prior_mean_old; /* (Backup) Branch length has a gamma distributed prior with this mean */
phydbl gamma_prior_var_old; /* (Backup) Branch length has a gamma distributed prior with this var */
phydbl bin_cod_num;
}t_edge;
/*!********************************************************/
typedef struct __Tree{
struct __Node *n_root; /*! root t_node */
struct __Edge *e_root; /*! t_edge on which lies the root */
struct __Node **t_nodes; /*! array of nodes that defines the tree topology */
struct __Edge **t_edges; /*! array of edges */
struct __Model *mod; /*! substitution model */
struct __Calign *data; /*! sequences */
struct __Calign *anc_data; /*! ancestral sequences */
struct __Tree *nextree; /* set to NULL by default. Used for mixture models */
struct __Tree *prevtree; /* set to NULL by default. Used for mixture models */
struct __Option *io; /*! input/output */
struct __Matrix *mat; /*! pairwise distance matrix */
struct __Node **curr_path; /*! list of nodes that form a path in the tree */
struct __SPR **spr_list;
struct __SPR *best_spr;
struct __Tdraw *ps_tree; /*! structure for drawing trees in postscript format */
struct __T_Rate *rates; /*! structure for handling rates of evolution */
struct __Tmcmc *mcmc;
struct __Triplet *triplet_struct;
int tree_num; /*! tree number. Used for mixture models */
int ps_page_number; /*! when multiple trees are printed, this variable give the current page number */
int depth_curr_path; /*! depth of the t_node path defined by curr_path */
int has_bip; /*!if has_bip=1, then the structure to compare
tree topologies is allocated, has_bip=0 otherwise */
int n_otu; /*! number of taxa */
int curr_site; /*! current site of the alignment to be processed */
int curr_catg; /*! current class of the discrete gamma rate distribution */
int n_swap; /*! number of NNIs performed */
int n_pattern; /*! number of distinct site patterns */
int has_branch_lengths; /*! =1 iff input tree displays branch lengths */
int print_boot_val; /*! if print_boot_val=1, the bootstrap values are printed */
int print_alrt_val; /*! if print_boot_val=1, the bootstrap values are printed */
int both_sides; /*! both_sides=1 -> a pre-order and a post-order tree
traversals are required to compute the likelihood
of every subtree in the phylogeny*/
int num_curr_branch_available; /*!gives the number of the next cell in t_edges that is free to receive a pointer to a branch */
short int *t_dir;
int n_improvements;
int n_moves;
int dp; /*! Data partition */
int s_mod_num; /*! Substitution model number */
int lock_topo; /*! = 1 any subsequent topological modification will be banished */
int print_labels;
int *mutmap; /*! Mutational map */
phydbl init_lnL;
phydbl best_lnL; /*! highest value of the loglikelihood found so far */
int best_pars; /*! highest value of the parsimony found so far */
phydbl c_lnL; /*! loglikelihood */
phydbl c_lnL_mixt; /*! loglikelihood */
phydbl old_lnL; /*! old loglikelihood */
phydbl sum_min_sum_scale; /*! common factor of scaling factors */
phydbl *c_lnL_sorted; /*! used to compute c_lnL by adding sorted terms to minimize CPU errors */
phydbl *cur_site_lk; /*! vector of likelihoods at individual sites */
phydbl *old_site_lk; /*! vector of likelihoods at individual sites */
phydbl **log_site_lk_cat; /*! loglikelihood at individual sites and for each class of rate*/
phydbl *site_lk_cat; /*! loglikelihood at a single site and for each class of rate*/
phydbl unconstraint_lk; /*! unconstrained (or multinomial) likelihood */
phydbl **log_lks_aLRT; /*! used to compute several branch supports */
phydbl n_root_pos; /*! position of the root on its t_edge */
phydbl size; /*! tree size */
int *site_pars;
int c_pars;
int *step_mat;
int size_spr_list;
int perform_spr_right_away;
time_t t_beg;
time_t t_current;
int bl_from_node_stamps; /*! == 1 -> Branch lengths are determined by t_node times */
phydbl sum_y_dist_sq;
phydbl sum_y_dist;
phydbl tip_order_score;
phydbl temp; /*! temperature for the simulated annealing algo */
int write_tax_names;
int update_alias_subpatt;
phydbl geo_mig_sd; /*! standard deviation of the migration step random variable */
phydbl geo_lnL; /*! log likelihood of the phylo-geography model */
int bl_ndigits;
phydbl *short_l; /* Vector of short branch length values */
int n_short_l; /* Length of short_l */
phydbl norm_scale;
short int br_len_recorded;
int max_spr_depth;
}t_tree;
/*!********************************************************/
typedef struct __Super_Tree {
struct __Tree *tree;
struct __List_Tree *treelist; /*! list of trees. One tree for each data set to be processed */
struct __Calign *curr_cdata;
struct __Option **optionlist; /*! list of pointers to input structures (used in supertrees) */
struct __Node ***match_st_node_in_gt;
/*! match_st_in_gt_node[subdataset number][supertree t_node number]
* gives the t_node in tree estimated from 'subdataset number' that corresponds
* to 'supertree t_node number' in the supertree
*/
struct __Node *****map_st_node_in_gt;
/*! mat_st_gt_node[gt_num][st_node_num][direction] gives the
* t_node in gt gt_num that maps t_node st_node_num in st.
*/
struct __Edge ***map_st_edge_in_gt;
/*! map_st_gt_br[gt_num][st_branch_num] gives the
* branch in gt gt_num that maps branch st_branch_num
* in st.
*/
struct __Edge ****map_gt_edge_in_st;
/*! mat_gt_st_br[gt_num][gt_branch_num][] is the list of
* branches in st that map branch gt_branch_num
* in gt gt_num.
*/
int **size_map_gt_edge_in_st;
/*! size_map_gt_st_br[gt_num][gt_branch_num] gives the
* size of the list map_gt_st_br[gt_num][gt_branch_num][]
*/
struct __Edge ***match_st_edge_in_gt;
/*! match_st_edge_in_gt[gt_num][st_branch_num] gives the
* branch in gt gt_num that matches branch st_branch_num
*/
struct __Edge ***match_gt_edge_in_st;
/*! match_gt_edge_in_st[gt_num][gt_branch_num] gives the
* branch in st that matches branch gt_branch_num
*/
struct __Node ****closest_match;
/*! closest_match[gt_num][st_node_num][dir] gives the
* closest t_node in st that matches a t_node in gt gt_num
*/
int ***closest_dist;
/*! closest_dist[gt_num][st_node_num][dir] gives the
* number of edges to traverse to get to node
* closest_match[gt_num][st_node_num][dir]
*/
int n_part;
/*! number of trees */
phydbl **bl;
/*! bl[gt_num][gt_branch_num] gives the length of
* branch gt_branch_num
*/
phydbl **bl_cpy;
/*! copy of bl */
phydbl **bl0;
/*! bl estimated during NNI (original topo)
* See Mg_NNI.
*/
phydbl **bl1;
/*! bl estimated during NNI (topo conf 1)
* See Mg_NNI.
*/
phydbl **bl2;
/*! bl estimated during NNI (topo conf 2)
* See Mg_NNI.
*/
int *bl_partition;
/*! partition[gt_num] gives the t_edge partition number
* gt_num belongs to.
*/
int n_bl_part;
struct __Model **s_mod; /*! substitution model */
int n_s_mod;
int lock_br_len;
}supert_tree;
/*!********************************************************/
typedef struct __List_Tree { /*! a list of trees */
struct __Tree **tree;
int list_size; /*! number of trees in the list */
}t_treelist;
/*!********************************************************/
typedef struct __Align {
char *name; /*! sequence name */
int len; /*! sequence length */
char *state; /*! sequence itself */
short int *is_ambigu; /*! is_ambigu[site] = 1 if state[site] is an ambiguous character. 0 otherwise */
}align;
/*!********************************************************/
typedef struct __Calign {
struct __Align **c_seq; /*! compressed sequences */
phydbl *b_frq; /*! observed state frequencies */
short int *invar; /*! 1 -> states are identical, 0 states vary */
int *wght; /*! # of each site in c_align */
short int *ambigu; /*! ambigu[i]=1 is one or more of the sequences at site
i display an ambiguous character */
phydbl obs_pinvar;
int n_otu; /*! number of taxa */
int clean_len; /*! uncrunched sequences lenghts without gaps */
int crunch_len; /*! crunched sequences lengths */
int init_len; /*! length of the uncompressed sequences */
int *sitepatt; /*! this array maps the position of the patterns in the
compressed alignment to the positions in the uncompressed
one */
int format; /*! 0 (default): PHYLIP. 1: NEXUS. */
}calign;
/*!********************************************************/
typedef struct __Matrix { /*! mostly used in BIONJ */
phydbl **P,**Q,**dist; /*! observed proportions of transition, transverion and distances
between pairs of sequences */
t_tree *tree; /*! tree... */
int *on_off; /*! on_off[i]=1 if column/line i corresponds to a t_node that has not
been agglomerated yet */
int n_otu; /*! number of taxa */
char **name; /*! sequence names */
int r; /*! number of nodes that have not been agglomerated yet */
struct __Node **tip_node; /*! array of pointer to the leaves of the tree */
int curr_int; /*! used in the NJ/BIONJ algorithms */
int method; /*! if method=1->NJ method is used, BIONJ otherwise */
}matrix;
/*!********************************************************/
typedef struct __Model {
struct __Optimiz *s_opt; /*! pointer to parameters to optimize */
struct __Eigen *eigen;
struct __M4 *m4mod;
struct __Option *io;
struct __Model *nextmod;
char *modelname;
char *custom_mod_string; /*! string of characters used to define custom models of substitution */
int mod_num; /*! model number */
int n_diff_rr; /*! number of different relative substitution rates in the custom model */
int update_eigen; /*! update_eigen=1-> eigen values/vectors need to be updated */
int whichmodel;
int n_catg; /*! number of categories in the discrete gamma distribution */
int invar; /*! =1 iff the substitution model takes into account invariable sites */
int ns; /*! number of states (4 for ADN, 20 for AA) */
int bootstrap; /*! Number of bootstrap replicates (0 : no bootstrap analysis is launched) */
int use_m4mod; /*! Use a Makrkov modulated Markov model ? */
int gamma_median; /*! 1: use the median of each bin in the discrete gamma distribution. 0: the mean is used */
vect_dbl *pi; /*! states frequencies */
vect_dbl *pi_unscaled; /*! states frequencies (unscaled) */
vect_dbl *gamma_r_proba; /*! probabilities of the substitution rates defined by the discrete gamma distribution */
vect_dbl *gamma_r_proba_unscaled;
vect_dbl *gamma_rr; /*! substitution rates defined by the RAS distribution */
vect_dbl *gamma_rr_unscaled; /*! substitution rates defined by the RAS distribution (unscaled) */
scalar_dbl *kappa; /*! transition/transversion rate */
scalar_dbl *lambda; /*! parameter used to define the ts/tv ratios in the F84 and TN93 models */
scalar_dbl *alpha; /*! gamma shapa parameter */
scalar_dbl *pinvar; /*! proportion of invariable sites */
scalar_dbl *alpha_old;
scalar_dbl *kappa_old;
scalar_dbl *lambda_old;
scalar_dbl *pinvar_old;
scalar_dbl *br_len_multiplier;
vect_dbl *rr; /*! relative rate parameters of the GTR or custom model (given by rr_val[rr_num[i]]) */
vect_dbl *rr_val; /*! relative rate parameters of the GTR or custom model */
vect_int *rr_num;
vect_int *n_rr_per_cat; /*! number of rate parameters in each category */
vect_dbl *Pij_rr; /*! matrix of change probabilities */
scalar_dbl *mr; /*! mean rate = branch length/time interval mr = -sum(i)(vct_pi[i].mat_Q[ii]) */
vect_dbl *user_b_freq; /*! user-defined nucleotide frequencies */
vect_dbl *qmat;
vect_dbl *qmat_buff;
int state_len;
short int log_l; /*! Edge lengths are actually log(Edge lengths) if log_l == YES !*/
phydbl l_min; /*! Minimum branch length !*/
phydbl l_max; /*! Maximum branch length !*/
int free_mixt_rates;
int gamma_mgf_bl; /*! P = \int_0^inf exp(QL) p(L) where L=\int_0^t R(s) ds and p(L) is the gamma density. Set to NO by default !*/
phydbl prob; /*! model probability !*/
phydbl unscaled_prob; /*! model probability (not normalised to sum to 1.0) !*/
}model;
/*!********************************************************/
typedef struct __Eigen{
int size;
phydbl *q; /*! matrix which eigen values and vectors are computed */
phydbl *space;
int *space_int;
phydbl *e_val; /*! eigen values (vector), real part. */
phydbl *e_val_im; /*! eigen values (vector), imaginary part */
phydbl *r_e_vect; /*! right eigen vector (matrix), real part */
phydbl *r_e_vect_im; /*! right eigen vector (matrix), imaginary part */
phydbl *l_e_vect; /*! left eigen vector (matrix), real part */
short int reflect;
}eigen;
/*!********************************************************/
typedef struct __Option { /*! mostly used in 'help.c' */
struct __Model *mod; /*! pointer to a substitution model */
struct __Tree *tree; /*! pointer to the current tree */
struct __Align **data; /*! pointer to the uncompressed sequences */
struct __Tree *cstr_tree; /*! pointer to a constraint tree (can be a multifurcating one) */
struct __Calign *cdata; /*! pointer to the compressed sequences */
struct __Super_Tree *st; /*! pointer to supertree */
struct __Tnexcom **nex_com_list;
struct __List_Tree *treelist; /*! list of trees. */
int interleaved; /*! interleaved or sequential sequence file format ? */
int in_tree; /*! =1 iff a user input tree is used as input */
char *in_align_file; /*! alignment file name */
FILE *fp_in_align; /*! pointer to the alignment file */
char *in_tree_file; /*! input tree file name */
FILE *fp_in_tree; /*! pointer to the input tree file */
char *in_constraint_tree_file; /*! input constraint tree file name */
FILE *fp_in_constraint_tree; /*! pointer to the input constraint tree file */
char *out_tree_file; /*! name of the tree file */
FILE *fp_out_tree;
char *out_trees_file; /*! name of the tree file */
FILE *fp_out_trees; /*! pointer to the tree file containing all the trees estimated using random starting trees */
char *out_boot_tree_file; /*! name of the tree file */
FILE *fp_out_boot_tree; /*! pointer to the bootstrap tree file */
char *out_boot_stats_file; /*! name of the tree file */
FILE *fp_out_boot_stats; /*! pointer to the statistics file */
char *out_stats_file; /*! name of the statistics file */
FILE *fp_out_stats;
char *out_trace_file; /*! name of the file in which the likelihood of the model is written */
FILE *fp_out_trace;
char *out_lk_file; /*! name of the file in which the likelihood of the model is written */
FILE *fp_out_lk;
char *out_ps_file; /*! name of the file in which tree(s) is(are) written */
FILE *fp_out_ps;
char *aa_rate_mat_file;
FILE *fp_aa_rate_mat;
char *clade_list_file;
int datatype; /*! 0->DNA, 1->AA */
int print_boot_trees; /*! =1 if the bootstrapped trees are printed in output */
int out_stats_file_open_mode; /*! opening file mode for statistics file */
int out_tree_file_open_mode; /*! opening file mode for tree file */
int n_data_sets; /*! number of data sets to be analysed */
int n_trees; /*! number of trees */
int init_len; /*! sequence length */
int n_otu; /*! number of taxa */
int n_data_set_asked; /*! number of bootstrap replicates */
char *nt_or_cd; /*! nucleotide or codon data ? (not used) */
int multigene; /*! if=1 -> analyse several partitions. */
int config_multigene;
int n_part; /*! number of data partitions */
int curr_gt;
int ratio_test; /*! from 1 to 4 for specific branch supports, 0 of not */
int ready_to_go;
int data_file_format; /*! Data format: Phylip or Nexus */
int tree_file_format; /*! Tree format: Phylip or Nexus */
int curr_interface;
int r_seed; /*! random seed */
int collapse_boot; /*! 0 -> branch length on bootstrap trees are not collapsed if too small */
int random_boot_seq_order; /*! !0 -> sequence order in bootstrapped data set is random */
int print_trace;
int print_site_lnl;
int m4_model;
int rm_ambigu; /*! 0 is the default. 1: columns with ambiguous characters are discarded prior further analysis */
int colalias;
int appebr_run_ID;
char *run_id_string;
int quiet; /*! 0 is the default. 1: no interactive question (for batch mode) */
int lk_approx; /* EXACT or NORMAL */
char **alphabet;
int codpos;
int mutmap;
char **long_tax_names;
char **short_tax_names;
int size_tax_names;
phydbl *z_scores;
phydbl *lat;
phydbl *lon;
int boot_prog_every;
int mem_question;
int do_alias_subpatt;
struct __Tmcmc *mcmc;
struct __T_Rate *rates;
}option;
/*!********************************************************/
typedef struct __Optimiz { /*! parameters to be optimised (mostly used in 'optimiz.c') */
int print; /*! =1 -> verbose mode */
int opt_alpha; /*! =1 -> the gamma shape parameter is optimised */
int opt_kappa; /*! =1 -> the ts/tv ratio parameter is optimised */
int opt_lambda; /*! =1 -> the F84|TN93 model specific parameter is optimised */
int opt_pinvar; /*! =1 -> the proportion of invariants is optimised */
int opt_state_freq; /*! =1 -> the nucleotide frequencies are optimised */
int opt_rr; /*! =1 -> the relative rate parameters of the GTR or the customn model are optimised */
int opt_subst_param; /*! if opt_topo=0 and opt_subst_param=1 -> the numerical parameters of the
model are optimised. if opt_topo=0 and opt_free_param=0 -> no parameter is
optimised */
int opt_cov_delta;
int opt_cov_alpha;
int opt_cov_free_rates;
int opt_bl; /*! =1 -> the branch lengths are optimised */
int opt_topo; /*! =1 -> the tree topology is optimised */
int topo_search;
phydbl init_lk; /*! initial loglikelihood value */
int n_it_max; /*! maximum bnumber of iteration during an optimisation step */
int last_opt; /*! =1 -> the numerical parameters are optimised further while the
tree topology remains fixed */
int random_input_tree; /*! boolean */
int n_rand_starts; /*! number of random starting points */
int brent_it_max;
int steph_spr;
int user_state_freq;
int opt_five_branch;
int pars_thresh;
int hybrid_thresh;
phydbl tree_size_mult; /*! tree size multiplier */
phydbl min_diff_lk_local;
phydbl min_diff_lk_global;
phydbl min_diff_lk_move;
phydbl p_moves_to_examine;
int fast_nni;
int greedy;
int general_pars;
int quickdirty;
int spr_pars;
int spr_lnL;
int max_depth_path;
int min_depth_path;
int deepest_path;
phydbl max_delta_lnL_spr;
int br_len_in_spr;
int opt_free_mixt_rates;
int constrained_br_len;
int opt_gamma_br_len;
int wim_n_rgrft;
int wim_n_globl;
int wim_max_dist;
int wim_n_optim;
int wim_n_best;
int wim_inside_opt;
}optimiz;
/*!********************************************************/
typedef struct __NNI{
struct __Node *left;
struct __Node *rght;
struct __Edge *b;
phydbl score;
phydbl init_l;
phydbl init_lk;
phydbl best_l;
phydbl lk0,lk1,lk2;
phydbl l0,l1,l2;
struct __Node *swap_node_v1;
struct __Node *swap_node_v2;
struct __Node *swap_node_v3;
struct __Node *swap_node_v4;
int best_conf; /*! best topological configuration :
((left_1,left_2),right_1,right_2) or
((left_1,right_2),right_1,left_2) or
((left_1,right_1),right_1,left_2) */
}nni;
/*!********************************************************/
typedef struct __SPR{
struct __Node *n_link;
struct __Node *n_opp_to_link;
struct __Edge *b_opp_to_link;
struct __Edge *b_target;
struct __Edge *b_init_target;
struct __Node **path;
phydbl init_target_l;
phydbl l0,l1,l2;
phydbl lnL;
int depth_path;
int pars;
int dist;
}spr;
/*!********************************************************/
typedef struct __Triplet{
int size;
phydbl *F_bc;
phydbl *F_cd;
phydbl *F_bd;
phydbl ****core;
phydbl ***p_one_site;
phydbl ***sum_p_one_site;
phydbl *pi_bc;
phydbl *pi_cd;
phydbl *pi_bd;
struct __Eigen *eigen_struct;
struct __Model *mod;
}triplet;
/*!********************************************************/
typedef struct __Pnode{
struct __Pnode **next;
int weight;
int num;
}pnode;
/*!********************************************************/
typedef struct __M4 {
int n_h; /*! number of hidden states */
int n_o; /*! number of observable states */
int use_cov_alpha;
int use_cov_free;
phydbl **o_mats; /*! set of matrices of substitution rates across observable states */
phydbl *multipl; /*! vector of values that multiply each o_mats matrix */
phydbl *o_rr; /*! relative rates (symmetric) of substitution between observable states */
phydbl *h_rr; /*! relative rates (symmetric) of substitution between hidden states */
phydbl *h_mat; /*! matrix that describes the substitutions between hidden states (aka switches) */
phydbl *o_fq; /*! equilibrium frequencies for the observable states */
phydbl *h_fq; /*! equilibrium frequencies for the hidden states */
phydbl *h_fq_unscaled; /*! unscaled equilibrium frequencies for the hidden states */
phydbl *multipl_unscaled; /*! unscaled vector of values that multiply each o_mats matrix */
phydbl delta; /*! switching rate */
phydbl alpha; /*! gamma shape parameter */
}m4;
/*!********************************************************/
typedef struct __Tdraw {
phydbl *xcoord; /*! t_node coordinates on the x axis */
phydbl *ycoord; /*! t_node coordinates on the y axis */
phydbl *xcoord_s; /*! t_node coordinates on the x axis (scaled) */
phydbl *ycoord_s; /*! t_node coordinates on the y axis (scaled) */
int page_width;
int page_height;
int tree_box_width;
int *cdf_mat;
phydbl *cdf_mat_x;
phydbl *cdf_mat_y;
phydbl max_dist_to_root;
}tdraw;
/*!********************************************************/
typedef struct __T_Rate {
phydbl lexp; /*! Parameter of the exponential distribution that governs the rate at which substitution between rate classes ocur */
phydbl alpha;
phydbl less_likely;
phydbl birth_rate;
phydbl birth_rate_min;
phydbl birth_rate_max;
phydbl min_rate;
phydbl max_rate;
phydbl c_lnL1;
phydbl c_lnL2;
phydbl c_lnL_rates; /*! Prob(Br len | time stamps, model of rate evolution) */
phydbl c_lnL_times; /*! Prob(time stamps) */
phydbl c_lnL_jps; /*! Prob(# Jumps | time stamps, rates, model of rate evolution) */
phydbl clock_r; /*! Mean substitution rate, i.e., 'molecular clock' rate */
phydbl min_clock;
phydbl max_clock;
phydbl lbda_nu;
phydbl min_dt;
phydbl step_rate;
phydbl true_tree_size;
phydbl p_max;
phydbl norm_fact;
phydbl nu; /*! Parameter of the Exponential distribution for the corresponding model */
phydbl min_nu;
phydbl max_nu;
phydbl covdet;
phydbl sum_invalid_areas;
phydbl *nd_r; /*! Current rates at nodes */
phydbl *br_r; /*! Current rates along edges */
phydbl *nd_t; /*! Current t_node times */
phydbl *triplet;
phydbl *true_t; /*! true t_node times (including root node) */
phydbl *true_r; /*! true t_edge rates (on rooted tree) */
phydbl *buff_t;
phydbl *buff_r;
phydbl *dens; /*! Probability densities of mean substitution rates at the nodes */
phydbl *ml_l; /*! ML t_edge lengths (rooted) */
phydbl *cur_l; /*! Current t_edge lengths (rooted) */
phydbl *u_ml_l; /*! ML t_edge lengths (unrooted) */
phydbl *u_cur_l; /*! Current t_edge lengths (unrooted) */
phydbl *invcov;
phydbl *cov_r;
phydbl *mean_r; /*! average values of br_r taken across the sampled values during the MCMC */
phydbl *mean_t; /*! average values of nd_t taken across the sampled values during the MCMC */
phydbl *_2n_vect1;
phydbl *_2n_vect2;
phydbl *_2n_vect3;
phydbl *_2n_vect4;
short int *_2n_vect5;
phydbl *_2n2n_vect1;
phydbl *_2n2n_vect2;
phydbl *trip_cond_cov;
phydbl *trip_reg_coeff;
phydbl *cond_var;
phydbl *reg_coeff;
phydbl *t_prior;
phydbl *t_prior_min;
phydbl *t_prior_max;
phydbl *t_floor;
phydbl *t_mean;
int *t_ranked;
phydbl *mean_l;
phydbl *cov_l;
phydbl *grad_l; /* gradient */
phydbl inflate_var;
phydbl *time_slice_lims;
phydbl *survival_rank;
phydbl *survival_dur;
int adjust_rates; /*! if = 1, branch rates are adjusted such that a modification of a given t_node time
does not modify any branch lengths */
int use_rates; /*! if = 0, branch lengths are expressed as differences between t_node times */
int bl_from_rt; /*! if =1, branch lengths are obtained as the product of cur_r and t */
int approx;
int model; /*! Model number */
int is_allocated;
int met_within_gibbs;
int update_mean_l;
int update_cov_l;
int *n_jps;
int *t_jps;
int n_time_slices;
int *n_time_slice_spans;
int *curr_slice;
int *n_tips_below;
short int *t_has_prior;
struct __Node **lca; /*! 2-way table of common ancestral nodes for each pari of nodes */
short int *br_do_updt;
phydbl *cur_gamma_prior_mean;
phydbl *cur_gamma_prior_var;
int model_log_rates;
short int nd_t_recorded;
short int br_r_recorded;
int *has_survived;
}t_rate;
/*!********************************************************/
typedef struct __Tmcmc {
struct __Option *io;
phydbl *tune_move;
phydbl *move_weight;
phydbl *acc_rate;
int *acc_move;
int *run_move;
int *prev_acc_move;
int *prev_run_move;
int *num_move;
int *move_type;
char **move_name;
int num_move_nd_r;
int num_move_br_r;
int num_move_nd_t;
int num_move_nu;
int num_move_clock_r;
int num_move_tree_height;
int num_move_subtree_height;
int num_move_kappa;
int num_move_tree_rates;
int num_move_subtree_rates;
int num_move_updown_nu_cr;
int num_move_updown_t_cr;
int num_move_ras;
int num_move_cov_rates;
int num_move_cov_switch;
int num_move_birth_rate;
int nd_t_digits;
char *out_filename;
time_t t_beg;
time_t t_cur;
time_t t_last_print;
FILE *out_fp_stats;
FILE *out_fp_trees;
FILE *out_fp_means;
FILE *out_fp_last;
FILE *out_fp_constree;
FILE *in_fp_par;
int *adjust_tuning;
int n_moves;
int use_data;
int randomize;
int norm_freq;
int run;
int chain_len;
int sample_interval;
int chain_len_burnin;
int print_every;
int is_burnin;
phydbl max_tune;
phydbl min_tune;
phydbl *old_param_val;
phydbl *new_param_val;
phydbl *sum_val;
phydbl *sum_valsq;
phydbl *sum_curval_nextval;
phydbl *ess;
phydbl *first_val;
int *ess_run;
int *start_ess;
int is; /* Importance sampling? Yes or NO */
}t_mcmc;
/*!********************************************************/
typedef struct __Tpart {
int *ns; /*! number of states for each partition (e.g., 2, 4, 3) */
int *cum_ns; /*! cumulative number of states (e.g., 0, 2, 6) */
int ns_max; /*! maximum number of states */
int ns_min; /*! minimum number of states */
int n_partitions; /*! number of partitions */
struct __Eigen *eigen;
}part;
/*!********************************************************/
typedef struct __Tnexcom {
char *name;
int nparm;
int nxt_token_t;
int cur_token_t;
struct __Tnexparm **parm;
}nexcom;
/*!********************************************************/
typedef struct __Tnexparm {
char *name;
char *value;
int nxt_token_t;
int cur_token_t;
int (*fp)(char *, struct __Tnexparm *, struct __Option *);
struct __Tnexcom *com;
}nexparm;
/*!********************************************************/
typedef struct __ParamInt {
short int reflect;
int val;
}t_param_int;
/*!********************************************************/
typedef struct __ParamDbl {
short int reflect;
phydbl val;
}t_param_dbl;
/*!********************************************************/
/*!********************************************************/
/*!********************************************************/
/*!********************************************************/
/*!********************************************************/
/*!********************************************************/
/*!********************************************************/
/*!********************************************************/
void Plim_Binom(phydbl pH0,int N,phydbl *pinf,phydbl *psup);
t_tree *Read_Tree(char **s_tree);
void Make_All_Edges_Light(t_node *a,t_node *d);
void Make_All_Edges_Lk(t_node *a,t_node *d,t_tree *tree);
void R_rtree(char *s_tree_a, char *s_tree_d, t_node *a, t_tree *tree, int *n_int, int *n_ext);
void Clean_Multifurcation(char **subtrees,int current_deg,int end_deg);
char **Sub_Trees(char *tree,int *degree);
int Next_Par(char *s,int pos);
char *Write_Tree(t_tree *tree, int custom);
void R_wtree(t_node *pere,t_node *fils,int *available,char **s_tree, t_tree *tree);
void R_wtree_Custom(t_node *pere,t_node *fils,int *available,char **s_tree, int *pos,t_tree *tree);
void Init_Tree(t_tree *tree, int n_otu);
t_edge *Make_Edge_Light(t_node *a, t_node *d, int num);
void Init_Edge_Light(t_edge *b, int num);
void Make_Edge_Dirs(t_edge *b, t_node *a, t_node *d, t_tree *tree);
void Make_Edge_Lk(t_edge *b, t_tree *tree);
t_node *Make_Node_Light(int num);
void Make_Node_Lk(t_node *n);
align **Get_Seq(option *input);
align **Get_Seq_Phylip(option *input);
align **Read_Seq_Sequential(option *io);
align **Read_Seq_Interleaved(option *io);
int Read_One_Line_Seq(align ***data,int num_otu,FILE *in);
void Uppercase(char *ch);
void Lowercase(char *ch);
calign *Compact_Data(align **data,option *input);
calign *Compact_Cdata(calign *data, option *io);
void Get_Base_Freqs(calign *data);
void Get_AA_Freqs(calign *data);
t_tree *Read_Tree_File(option *io);
t_tree *Read_Tree_File_Phylip(FILE *fp_input_tree);
void Connect_Edges_To_Nodes(t_node *a,t_node *d,t_tree *tree,int *cur);
void Exit(char *message);
void *mCalloc(int nb,size_t size);
void *mRealloc(void *p,int nb,size_t size);
int Sort_Phydbl_Decrease(const void *a, const void *b);
void Qksort(phydbl *A, phydbl *B, int ilo,int ihi);
void Qksort_Int(int *A, int *B, int ilo,int ihi);
void Print_Site(calign *cdata,int num,int n_otu,char *sep,int stepsize);
void Print_Seq(align **data,int n_otu);
void Print_CSeq(FILE *fp,int compressed, calign *cdata);
void Print_CSeq_Select(FILE *fp, int compressed, calign *cdata, t_tree *tree);
void Order_Tree_Seq(t_tree *tree,align **data);
void Order_Tree_CSeq(t_tree *tree,calign *data);
matrix *Make_Mat(int n_otu);
void Init_Mat(matrix *mat,calign *data);
void Print_Dist(matrix *mat);
void Print_Node(t_node *a,t_node *d,t_tree *tree);
void Share_Lk_Struct(t_tree *t_full,t_tree *t_empt);
void Init_Constant();
void Print_Mat(matrix *mat);
int Sort_Edges_NNI_Score(t_tree *tree, t_edge **sorted_edges, int n_elem);
void NNI(t_tree *tree, t_edge *b_fcus, int do_swap);
void Swap(t_node *a,t_node *b,t_node *c,t_node *d,t_tree *tree);
void Update_All_Partial_Lk(t_edge *b_fcus,t_tree *tree);
void Update_SubTree_Partial_Lk(t_edge *b_fcus,t_node *a,t_node *d,t_tree *tree);
calign *Make_Cseq(int n_otu, int crunch_len, int state_len, int init_len, char **sp_names);
calign *Copy_Cseq(calign *ori, option *io);
optimiz *Make_Optimiz();
int Filexists(char *filename);
FILE *Openfile(char *filename,int mode);
void Print_Fp_Out(FILE *fp_out, time_t t_beg, time_t t_end, t_tree *tree, option *input, int n_data_set, int num_rand_tree);
void Print_Fp_Out_Lines(FILE *fp_out,time_t t_beg,time_t t_end,t_tree *tree,option *input,int n_data_set);
matrix *K80_dist(calign *data,phydbl g_shape);
matrix *JC69_Dist(calign *data, model *mod);
matrix *Hamming_Dist(calign *data,model *mod);
int Is_Ambigu(char *state,int datatype,int stepsize);
void Check_Ambiguities(calign *data,int datatype,int stepsize);
int Assign_State(char *c,int datatype,int stepsize);
void Bootstrap(t_tree *tree);
void Br_Len_Involving_Invar(t_tree *tree);
void Br_Len_Not_Involving_Invar(t_tree *tree);
void Getstring_Stdin(char *file_name);
void Print_Freq(t_tree *tree);
phydbl Num_Derivatives_One_Param(phydbl(*func)(t_tree *tree),t_tree *tree,phydbl f0,phydbl *param,phydbl stepsize,phydbl *err,int precise);
int Num_Derivative_Several_Param(t_tree *tree,phydbl *param,int n_param,phydbl stepsize,phydbl(*func)(t_tree *tree),phydbl *derivatives);
int Compare_Two_States(char *state1,char *state2,int state_size);
void Copy_One_State(char *from,char *to,int state_size);
model *Make_Model_Basic();
void Make_Model_Complete(model *mod);
model *Copy_Model(model *ori);
void Set_Defaults_Input(option *input);
void Set_Defaults_Model(model *mod);
void Set_Defaults_Optimiz(optimiz *s_opt);
void Get_Bip(t_node *a,t_node *d,t_tree *tree);
void Alloc_Bip(t_tree *tree);
int Sort_Phydbl_Increase(const void *a,const void *b);
int Sort_String(const void *a,const void *b);
int Compare_Bip(t_tree *tree1,t_tree *tree2, int on_existing_edges_only);
void Test_Multiple_Data_Set_Format(option *input);
int Are_Compatible(char *statea,char *stateb,int stepsize,int datatype);
void Hide_Ambiguities(calign *data);
void Print_Site_Lk(t_tree *tree, FILE *fp);
option *Make_Input();
t_tree *Make_Tree();
void Make_All_Tree_Nodes(t_tree *tree);
void Make_All_Tree_Edges(t_tree *tree);
void Copy_Tax_Names_To_Tip_Labels(t_tree *tree, calign *data);
t_tree *Make_And_Init_Tree(calign *data);
void Connect_Edges_To_Nodes_Recur(t_node *a, t_node *d, t_tree *tree);
void Connect_One_Edge_To_Two_Nodes(t_node *a, t_node *d, t_edge *b, t_tree *tree);
t_tree *Make_Tree_From_Scratch(int n_otu, calign *data);
t_treelist *Make_Treelist(int list_size);
void Put_Subtree_In_Dead_Objects(t_node *a, t_node *d, t_tree *tree);
void Prune_Subtree(t_node *a, t_node *d, t_edge **target, t_edge **residual, t_tree *tree);
void Reassign_Node_Nums(t_node *a, t_node *d, int *curr_ext_node, int *curr_int_node, t_tree *tree);
void Copy_Tree(t_tree *ori, t_tree *cpy);
void Reassign_Edge_Nums(t_node *a, t_node *d, int *curr_br, t_tree *tree);
void Init_Node_Light(t_node *n, int num);
void Make_All_Edge_Dirs(t_node *a, t_node *d, t_tree *tree);
void Graft_Subtree(t_edge *target, t_node *link, t_edge *add_br, t_tree *tree);
int Get_Subtree_Size(t_node *a, t_node *d);
void Pull_Subtree_From_Dead_Objects(t_node *a, t_node *d, t_tree *tree);
void Make_Edge_NNI(t_edge *b);
nni *Make_NNI();
void Init_NNI(nni *a_nni);
void Insert(t_tree *tree);
void Connect_Two_Nodes(t_node *a, t_node *d);
void Get_List_Of_Target_Edges(t_node *a, t_node *d, t_edge **list, int *list_size, t_tree *tree);
void Fix_All(t_tree *tree);
void Record_Br_Len(t_tree *tree);
void Restore_Br_Len(t_tree *tree);
void Get_Dist_Btw_Edges(t_node *a, t_node *d, t_tree *tree);
void Detect_Polytomies(t_edge *b, phydbl l_thresh, t_tree *tree);
void Find_Mutual_Direction(t_node *n1, t_node *n2, short int *dir_n1_to_n2, short int *dir_n2_to_n1);
void Fill_Dir_Table(t_tree *tree);
void Get_List_Of_Nodes_In_Polytomy(t_node *a, t_node *d, t_node ***list, int *size_list);
void NNI_Polytomies(t_tree *tree, t_edge *b_fcus, int do_swap);
void Check_Path(t_node *a, t_node *d, t_node *target, t_tree *tree);
void Get_List_Of_Adjacent_Targets(t_node *a, t_node *d, t_node ***node_list, t_edge ***edge_list, int *list_size);
void Sort_List_Of_Adjacent_Targets(t_edge ***list, int list_size);
t_node *Common_Nodes_Btw_Two_Edges(t_edge *a, t_edge *b);
void Make_Site_Lk_Backup(t_tree *tree);
int KH_Test(phydbl *site_lk_m1, phydbl *site_lk_M2, t_tree *tree);
void Store_P_Lk(phydbl ****ori, phydbl ****cpy, t_tree *tree);
phydbl Triple_Dist(t_node *a, t_tree *tree, int approx);
void Make_Symmetric(phydbl **F, int n);
void Round_Down_Freq_Patt(phydbl **F, t_tree *tree);
phydbl Get_Sum_Of_Cells(phydbl *F, t_tree *tree);
void Divide_Cells(phydbl **F, phydbl div, t_tree *tree);
void Divide_Mat_By_Vect(phydbl **F, phydbl *vect, int size);
void Multiply_Mat_By_Vect(phydbl **F, phydbl *vect, int size);
void Triple_Dist_Recur(t_node *a, t_node *d, t_tree *tree);
triplet *Make_Triplet_Struct(model *mod);
void Fast_Br_Len(t_edge *b, t_tree *tree, int approx);
void Fast_Br_Len_Recur(t_node *a, t_node *d, t_edge *b, t_tree *tree);
void Print_Tree(FILE *fp, t_tree *tree);
void Found_In_Subtree(t_node *a, t_node *d, t_node *target, int *match, t_tree *tree);
void Random_Tree(t_tree *tree);
void Copy_Dist(phydbl **cpy, phydbl **orig, int n);
eigen *Make_Eigen_Struct(int ns);
void Random_NNI(int n_moves, t_tree *tree);
void Make_Edge_Pars(t_edge *b, t_tree *tree);
void Make_Tree_Path(t_tree *tree);
void Share_Pars_Struct(t_tree *t_full, t_tree *t_empt);
void Share_Spr_Struct(t_tree *t_full, t_tree *t_empt);
void Clean_Tree_Connections(t_tree *tree);
void Print_Settings(option *input);
void Fill_Missing_Dist(matrix *mat);
void Fill_Missing_Dist_XY(int x, int y, matrix *mat);
phydbl Least_Square_Missing_Dist_XY(int x, int y, phydbl dxy, matrix *mat);
void Update_Dirs(t_tree *tree);
void Print_Banner(FILE *fp);
void Qksort_matrix(phydbl **A, int col, int ilo, int ihi);
void Check_Memory_Amount(t_tree *tree);
int Get_State_From_P_Lk(phydbl *p_lk, int pos, t_tree *tree);
int Get_State_From_P_Pars(short int *p_pars, int pos, t_tree *tree);
void Unroot_Tree(char **subtrees);
void Print_Lk(t_tree *tree, char *string);
void Print_Pars(t_tree *tree);
void Print_Lk_And_Pars(t_tree *tree);
void Check_Dirs(t_tree *tree);
void Warn_And_Exit(char *s);
void Print_Data_Set_Number(option *input, FILE *fp);
void NNI_Pars(t_tree *tree, t_edge *b_fcus, int do_swap);
void Evaluate_One_Regraft_Pos_Triple(spr *move, t_tree *tree);
int Get_State_From_Ui(int ui, int datatype);
void Read_Qmat(phydbl *daa, phydbl *pi, FILE *fp);
void Traverse_Prefix_Tree(int site, int seqnum, int *patt_num, int *n_patt, align **data, option *input, pnode *n);
pnode *Create_Pnode(int size);
int Assign_State_With_Ambiguity(char *c, int datatype, int stepsize);
void Randomize_Sequence_Order(calign *data);
void Dist_To_Node_Pre(t_node *a, t_node *d, t_edge *b, t_tree *tree);
void Add_Root(t_edge *target, t_tree *tree);
int Is_Invar(int patt_num, int stepsize, int datatype, calign *data);
void Update_Root_Pos(t_tree *tree);
void Read_Branch_Label(char *sub_part, char *full_part, t_edge *b);
void Read_Branch_Length(char *s_d, char *s_a, t_tree *tree);
void Read_Node_Name(t_node *d, char *s_tree_d, t_tree *tree);
t_tree *Generate_Random_Tree_From_Scratch(int n_otu, int rooted);
void Random_Lineage_Rates(t_node *a, t_node *d, t_edge *b, phydbl stick_prob, phydbl *rates, int curr_rate, int n_rates, t_tree *tree);
t_edge *Find_Edge_With_Label(char *label, t_tree *tree);
void Print_Square_Matrix_Generic(int n, phydbl *mat);
char Reciproc_Assign_State(int i_state, int datatype);
void Evolve(calign *data, model *mod, t_tree *tree);
int Pick_State(int n, phydbl *prob);
void Evolve_Recur(t_node *a, t_node *d, t_edge *b, int a_state, int r_class, int site_num, calign *gen_data, model *mod, t_tree *tree);
void Site_Diversity(t_tree *tree);
void Site_Diversity_Post(t_node *a, t_node *d, t_edge *b, t_tree *tree);
void Site_Diversity_Pre(t_node *a, t_node *d, t_edge *b, t_tree *tree);
void Subtree_Union(t_node *n, t_edge *b_fcus, t_tree *tree);
void Binary_Decomposition(int value, int *bit_vect, int size);
void Print_Diversity(FILE *fp, t_tree *tree);
void Print_Diversity_Header(FILE *fp, t_tree *tree);
void Print_Diversity_Pre(t_node *a, t_node *d, t_edge *b, FILE *fp, t_tree *tree);
void Make_New_Edge_Label(t_edge *b);
void Print_Qmat_AA(phydbl *daa, phydbl *pi);
t_rate *Make_Rate_Struct(t_tree *tree);
void Init_Rate_Struct(t_rate *rates, t_tree *tree);
phydbl Var(phydbl *x, int n);
phydbl Mean(phydbl *x, int n);
phydbl Multivariate_Kernel_Density_Estimate(phydbl *where, phydbl **x, int sample_size, int vect_size);
void Record_Model(model *ori, model *cpy);
void Best_Of_NNI_And_SPR(t_tree *tree);
int Polint(phydbl *xa, phydbl *ya, int n, phydbl x, phydbl *y, phydbl *dy);
void Reset_Model_Parameters(model *mod);
void Print_Banner_Small(FILE *fp);
void JF(t_tree *tree);
t_tree *Dist_And_BioNJ(calign *cdata, model *mod, option *io);
void Add_BioNJ_Branch_Lengths(t_tree *tree, calign *cdata, model *mod);
t_tree *Read_User_Tree(calign *cdata, model *mod, option *io);
void Print_Time_Info(time_t t_beg, time_t t_end);
void Prepare_Tree_For_Lk(t_tree *tree);
char *Bootstrap_From_String(char *s_tree, calign *cdata, model *mod, option *io);
char *aLRT_From_String(char *s_tree, calign *cdata, model *mod, option *io);
int Rand_Int(int min, int max);
void PhyML_Printf(char *format, ...);
void PhyML_Fprintf(FILE *fp, char *format, ...);
void Update_Ancestors(t_node *a, t_node *d, t_tree *tree);
void Find_Common_Tips(t_tree *tree1, t_tree *tree2);
phydbl Get_Tree_Size(t_tree *tree);
int Find_Bipartition(char **target_bip, int bip_size, t_tree *tree);
int Find_Duplication_Node(char **tax_set, int n_tax, t_tree *tree);
void Get_Rid_Of_Prefix(char delim, t_tree *tree);
void Dist_To_Root_Pre(t_node *a, t_node *d, t_edge *b, t_tree *tree);
void Dist_To_Root(t_node *n_root, t_tree *tree);
int Is_Duplication_Node(t_node *n, char **tax_set, int n_tax, t_tree *tree);
int Sort_Edges_Depth(t_tree *tree, t_edge **sorted_edges, int n_elem);
char *Basename(char *path);
void Get_List_Of_Ancestors(t_node *ref_nod, t_node **list, int *size, t_tree *tree);
t_node *Find_Lca_Pair_Of_Nodes(t_node *n1, t_node *n2, t_tree *tree);
t_node *Find_Lca_Clade(t_node **node_list, int node_list_size, t_tree *tree);
int Edge_Num_To_Node_Num(int edge_num, t_tree *tree);
void Branch_Lengths_To_Time_Lengths(t_tree *tree);
void Branch_Lengths_To_Time_Lengths_Pre(t_node *a, t_node *d, t_tree *tree);
void Branch_Lengths_To_Rate_Lengths(t_tree *tree);
void Branch_Lengths_To_Rate_Lengths_Pre(t_node *a, t_node *d, t_tree *tree);
int Find_Clade(char **tax_name_list, int list_size, t_tree *tree);
void Find_Clade_Pre(t_node *a, t_node *d, int *tax_num_list, int list_size, int *num, t_tree *tree);
void Read_Clade_Priors(char *file_name, t_tree *tree);
t_edge *Find_Root_Edge(FILE *fp_input_tree, t_tree *tree);
void Copy_Tree_Topology_With_Labels(t_tree *ori, t_tree *cpy);
void Make_Custom_Model(model *mod);
option *Get_Input(int argc, char **argv);
nexcom **Make_Nexus_Com();
void Free_Nexus_Com(nexcom **com);
void Init_Nexus_Format(nexcom **com);
void Find_Nexus_Com(char *token, nexcom **found_com, nexparm **default_parm, nexcom **com_list);
void Find_Nexus_Parm(char *token, nexparm **found_parm, nexcom *curr_com);
int Read_Nexus_Dimensions(char *token, nexparm *curr_parm, option *io);
int Read_Nexus_Format(char *token, nexparm *curr_parm, option *io);
int Read_Nexus_Eliminate(char *token, nexparm *curr_parm, option *io);
int Read_Nexus_Taxlabel(char *token, nexparm *curr_parm, option *io);
int Read_Nexus_Charstatelabels(char *token, nexparm *curr_parm, option *io);
int Read_Nexus_Charlabels(char *token, nexparm *curr_parm, option *io);
int Read_Nexus_Statelabels(char *token, nexparm *curr_parm, option *io);
int Read_Nexus_Matrix(char *token, nexparm *curr_parm, option *io);
int Read_Nexus_Begin(char *token, nexparm *curr_parm, option *io);
int Read_Nexus_Matrix(char *token, nexparm *curr_parm, option *io);
int Read_Nexus_Translate(char *token, nexparm *curr_parm, option *io);
int Read_Nexus_Tree(char *token, nexparm *curr_parm, option *io);
int Read_Nexus_Taxa(char *token, nexparm *curr_parm, option *io);
void Detect_Align_File_Format(option *io);
void Detect_Tree_File_Format(option *io);
int Get_Token(FILE *fp, char *token);
nexparm *Make_Nexus_Parm();
void Free_Nexus_Parm(nexparm *parm);
void Read_Ntax_Len_Phylip(FILE *fp ,int *n_otu, int *n_tax);
void Set_Model_Name(model *mod);
void Adjust_Min_Diff_Lk(t_tree *tree);
void Match_Tip_Numbers(t_tree *tree1, t_tree *tree2);
void Get_Nexus_Data(FILE *fp, option *io);
void Translate_Tax_Names(char **tax_names, t_tree *tree);
void Skip_Comment(FILE *fp);
void Update_Dir_To_Tips(t_node *a, t_node *d, t_tree *tree);
void Test_Node_Table_Consistency(t_tree *tree);
void Get_Best_Root_Position(t_tree *tree);
void Get_Best_Root_Position_Post(t_node *a, t_node *d, int *has_outgrp, t_tree *tree);
void Get_Best_Root_Position_Pre(t_node *a, t_node *d, t_tree *tree);
void Get_OutIn_Scores(t_node *a, t_node *d);
int Check_Sequence_Name(char *s);
int Scale_Node_Heights(phydbl K, phydbl floor, int *n_nodes, t_tree *tree);
void Scale_Node_Heights_Post(t_node *a, t_node *d, phydbl K, phydbl floor, int *n_nodes, t_tree *tree);
void Get_Node_Ranks(t_tree *tree);
void Get_Node_Ranks_Pre(t_node *a, t_node *d,t_tree *tree);
void Get_Node_Rank_Max_Post(t_node *a, t_node *d,t_tree *tree);
void Log_Br_Len(t_tree *tree);
void Make_Short_L(t_tree *tree);
phydbl Diff_Lk_Norm_At_Given_Edge(t_edge *b, t_tree *tree);
void Adjust_Variances(t_tree *tree);
int Scale_Subtree_Rates_Post(t_node *a, t_node *d, phydbl mult, int *n_nodes, t_tree *tree);
int Scale_Subtree_Rates(t_node *a, phydbl mult, int *n_nodes, t_tree *tree);
phydbl Effective_Sample_Size(phydbl first_val, phydbl last_val, phydbl sum, phydbl sumsq, phydbl sumcurnext, int iter);
phydbl Rescale_Free_Rate_Tree(t_tree *tree);
phydbl Rescale_Br_Len_Multiplier_Tree(t_tree *tree);
int Scale_Subtree_Height(t_node *a, phydbl K, phydbl floor, int *n_nodes, t_tree *tree);
phydbl Unscale_Br_Len_Multiplier_Tree(t_tree *tree);
phydbl Unscale_Free_Rate_Tree(t_tree *tree);
void Check_Br_Len_Bounds(t_tree *tree);
phydbl Reflect(phydbl x, phydbl l, phydbl u);
int Are_Equal(phydbl a, phydbl b, phydbl eps);
void Restrict_To_Coding_Position(align **data, option *io);
void Prune_Tree(t_tree *big_tree, t_tree *small_tree);
void Check_Constraint_Tree_Taxa_Names(t_tree *tree, calign *cdata);
int Check_Topo_Constraints(t_tree *big_tree, t_tree *small_tree);
void Prune_Tree(t_tree *big_tree, t_tree *small_tree);
void Match_Nodes_In_Small_Tree(t_tree *small_tree, t_tree *big_tree);
char *Return_Tree_String_Phylip(FILE *fp_input_tree);
char *Add_Taxa_To_Constraint_Tree(FILE *fp, calign *cdata);
void Find_Surviving_Edges_In_Small_Tree_Post(t_node *a, t_node *d, t_tree *small_tree, t_tree *big_tree);
void Find_Surviving_Edges_In_Small_Tree(t_tree *small_tree, t_tree *big_tree);
void Set_Taxa_Id_Ranking(t_tree *tree);
void Get_Edge_Binary_Coding_Number(t_tree *tree);
void Make_Ancestral_Seq(t_tree *tree);
void Make_MutMap(t_tree *tree);
int Get_Mutmap_Val(int edge, int site, int mut, t_tree *tree);
void Get_Mutmap_Coord(int idx, int *edge, int *site, int *mut, t_tree *tree);
void Make_Nextrees(int *n_trees, int n_tot_trees, t_tree *tree);
void Make_Mixtmod(int n_classes, t_tree *tree);
void Make_Nextmods(int *n_mods, int n_tot_mods, model *mod);
void Copy_Edge_Lengths(t_tree *to, t_tree *from);
void Init_Scalar_Dbl(scalar_dbl *p);
void Init_Scalar_Int(scalar_int *p);
void Init_Vect_Dbl(int len, vect_dbl *p);
void Init_Vect_Int(int len, vect_int *p);
void Init_Eigen_Struct(eigen *this);
void Swap_Nodes_On_Edges(t_edge *e1, t_edge *e2, int swap, t_tree *tree);
void Reorganize_Edges_Given_Lk_Struct(t_tree *tree);
void Print_Model(model *mod);
char *To_Lower_String(char *in);
#include "free.h"
#include "spr.h"
#include "lk.h"
#include "optimiz.h"
#include "models.h"
#include "bionj.h"
#include "simu.h"
#include "eigen.h"
#include "pars.h"
#include "alrt.h"
#include "stats.h"
#include "help.h"
#ifdef MPI
#include "mpi_boot.h"
#endif
#ifdef MG
#include "mg.h"
#endif
#ifdef TIME
#include "times.h"
#include "rates.h"
#endif
#ifdef _NOT_NEEDED_A_PRIORI
#include "m4.h"
#endif
#endif
phyml-20120412/src/help.h 0000644 0001750 0001750 00000000735 11637265532 011730 0000000 0000000 /*
PhyML: a program that computes maximum likelihood phylogenies from
DNA or AA homologous sequences.
Copyright (C) Stephane Guindon. Oct 2003 onward.
All parts of the source except where indicated are distributed under
the GNU public licence. See http://www.opensource.org for details.
*/
#include
#ifndef OPTIONS_H
#define OPTIONS_H
#include "utilities.h"
#include "cl.h"
#include "models.h"
#include "free.h"
#include "interface.h"
void Usage();
#endif
phyml-20120412/src/bionj.h 0000644 0001750 0001750 00000002450 11637265465 012102 0000000 0000000 /*
PhyML: a program that computes maximum likelihood phylogenies from
DNA or AA homologous sequences.
Copyright (C) Stephane Guindon. Oct 2003 onward.
All parts of the source except where indicated are distributed under
the GNU public licence. See http://www.opensource.org for details.
*/
#include
#ifndef NJ_H
#define NJ_H
#include "utilities.h"
#include "optimiz.h"
#include "free.h"
void Bionj(matrix *mat);
void Finish(matrix *mat);
void Compute_Sx(matrix *mat);
phydbl Sum_S(matrix *mat, int i);
phydbl Dist(matrix *mat, int x, int y);
phydbl Q_Agglo(matrix *mat, int x, int y);
phydbl Variance(matrix *mat, int x, int y);
phydbl Br_Length(matrix *mat, int x, int y);
void Update_Dist(matrix *mat, int x, int y);
phydbl Lamda(matrix *mat, int x, int y, phydbl vxy);
void Best_Pair(matrix *mat, int *x, int *y, phydbl *score);
phydbl Var_Red(matrix *mat, int x, int y, int i, phydbl lamda, phydbl vxy);
void Update_Tree(matrix *mat, int x, int y, phydbl lx, phydbl ly, phydbl score);
void Update_Mat(matrix *mat, int x, int y,
phydbl lx, phydbl ly, phydbl vxy, phydbl lamda);
phydbl Dist_Red(matrix *mat, int x, phydbl lx, int y,
phydbl ly, int i, phydbl lamda);
int Bionj_Br_Length_Post(t_node *a, t_node *d, matrix *mat);
void Bionj_Br_Length(matrix *mat);
#endif
phyml-20120412/src/eigen.c 0000644 0001750 0001750 00000063477 11566551262 012075 0000000 0000000 /***********************************************************
* This eigen() routine works for eigenvalue/vector analysis
* for real general square matrix A
* A will be destroyed
* rr,ri are vectors containing eigenvalues
* vr,vi are matrices containing (right) eigenvectors
*
* A*[vr+vi*i] = [vr+vi*i] * diag{rr+ri*i}
*
* Algorithm: Handbook for Automatic Computation, vol 2
* by Wilkinson and Reinsch, 1971
* most of source codes were taken from a public domain
* solftware called MATCALC.
* Credits: to the authors of MATCALC
*
* return -1 not converged
* 0 no complex eigenvalues/vectors
* 1 complex eigenvalues/vectors
* Tianlin Wang at University of Illinois
* Thu May 6 15:22:31 CDT 1993
***************************************************************/
#include "eigen.h"
#define BASE 2 /* base of floating point arithmetic */
/* no. of digits to the base BASE in the fraction */
#define DIGITS 40
/*
#define DIGITS 53
*/
#define MAXITER 30 /* max2. no. of iterations to converge */
#define pos(i,j,n) ((i)*(n)+(j))
/* rr/vr : real parts of eigen values/vectors */
/* ri/vi : imaginary part s of eigen values/vectors */
int Eigen(int job, phydbl *A, int n, phydbl *rr, phydbl *ri,
phydbl *vr, phydbl *vi, phydbl *work)
{
/* job=0: eigen values only
1: both eigen values and eigen vectors
phydbl w[n*2]: work space
*/
int low,hi,i,j,k, it, istate=0;
phydbl tiny, t;
/* tiny=SQRT(POW((phydbl)BASE,(phydbl)(1-(int)DIGITS))); */
tiny=FLT_MIN;
balance(A,n,&low,&hi,work);
elemhess(job,A,n,low,hi,vr,vi, (int*)(work+n));
if (-1 == realeig(job,A,n,low,hi,rr,ri,vr,vi)) return (-1);
if (job) unbalance(n,vr,vi,low,hi,work);
/* sort, added by Z. Yang */
for (i=0; itiny) istate=1;
}
return (istate) ;
}
/* complex funcctions
*/
complex compl (phydbl re,phydbl im)
{
complex r;
r.re = re;
r.im = im;
return(r);
}
complex _conj (complex a)
{
a.im = -a.im;
return(a);
}
complex cplus (complex a, complex b)
{
complex c;
c.re = a.re+b.re;
c.im = a.im+b.im;
return (c);
}
complex cminus (complex a, complex b)
{
complex c;
c.re = a.re-b.re;
c.im = a.im-b.im;
return (c);
}
complex cby (complex a, complex b)
{
complex c;
c.re = a.re*b.re-a.im*b.im ;
c.im = a.re*b.im+a.im*b.re ;
return (c);
}
complex cdiv (complex a,complex b)
{
phydbl ratio, den;
complex c;
if (FABS(b.re) <= FABS(b.im)) {
ratio = b.re / b.im;
den = b.im * (1 + ratio * ratio);
c.re = (a.re * ratio + a.im) / den;
c.im = (a.im * ratio - a.re) / den;
}
else {
ratio = b.im / b.re;
den = b.re * (1 + ratio * ratio);
c.re = (a.re + a.im * ratio) / den;
c.im = (a.im - a.re * ratio) / den;
}
return(c);
}
/* complex local_cexp (complex a) */
/* { */
/* complex c; */
/* c.re = EXP(a.re); */
/* if (FABS(a.im)==0) c.im = 0; */
/* else { c.im = c.re*sin(a.im); c.re*=cos(a.im); } */
/* return (c); */
/* } */
complex cfactor (complex x, phydbl a)
{
complex c;
c.re = a*x.re;
c.im = a*x.im;
return (c);
}
int cxtoy (complex *x, complex *y, int n)
{
int i;
For (i,n) y[i]=x[i];
return (0);
}
int cmatby (complex *a, complex *b, complex *c, int n,int m,int k)
/* a[n*m], b[m*k], c[n*k] ...... c = a*b
*/
{
int i,j,i1;
complex t;
For (i,n) For(j,k) {
for (i1=0,t=compl(0,0); i1=n
*/
int i,j,k, *irow=(int*) space;
phydbl xmaxsize, ee=1e-20;
complex xmax, t,t1;
For(i,n) {
xmaxsize = 0.;
for (j=i; j=0; i--) {
if (irow[i] == i) continue;
For(j,n) {
t = x[j*m+i];
x[j*m+i] = x[j*m+irow[i]];
x[ j*m+irow[i]] = t;
}
}
return (0);
}
void balance(phydbl *mat, int n,int *low, int *hi, phydbl *scale)
{
/* Balance a matrix for calculation of eigenvalues and eigenvectors
*/
phydbl c,f,g,r,s;
int i,j,k,l,done;
/* search for rows isolating an eigenvalue and push them down */
for (k = n - 1; k >= 0; k--)
{
for (j = k; j >= 0; j--)
{
for (i = 0; i <= k; i++)
{
if (i != j && FABS(mat[pos(j,i,n)]) > SMALL) break;
}
if (i > k) {
scale[k] = j;
if (j != k) {
for (i = 0; i <= k; i++) {
c = mat[pos(i,j,n)];
mat[pos(i,j,n)] = mat[pos(i,k,n)];
mat[pos(i,k,n)] = c;
}
for (i = 0; i < n; i++) {
c = mat[pos(j,i,n)];
mat[pos(j,i,n)] = mat[pos(k,i,n)];
mat[pos(k,i,n)] = c;
}
}
break;
}
}
if (j < 0) break;
}
/* search for columns isolating an eigenvalue and push them left */
for (l = 0; l <= k; l++) {
for (j = l; j <= k; j++) {
for (i = l; i <= k; i++) {
if (i != j && FABS(mat[pos(i,j,n)]) > SMALL) break;
}
if (i > k) {
scale[l] = j;
if (j != l) {
for (i = 0; i <= k; i++) {
c = mat[pos(i,j,n)];
mat[pos(i,j,n)] = mat[pos(i,l,n)];
mat[pos(i,l,n)] = c;
}
for (i = l; i < n; i++) {
c = mat[pos(j,i,n)];
mat[pos(j,i,n)] = mat[pos(l,i,n)];
mat[pos(l,i,n)] = c;
}
}
break;
}
}
if (j > k) break;
}
*hi = k;
*low = l;
/* balance the submatrix in rows l through k */
for (i = l; i <= k; i++) {
scale[i] = 1;
}
do {
for (done = 1,i = l; i <= k; i++) {
for (c = 0,r = 0,j = l; j <= k; j++) {
if (j != i) {
c += FABS(mat[pos(j,i,n)]);
r += FABS(mat[pos(i,j,n)]);
}
}
/* if (c != 0 && r != 0) { */
if (FABS(c) > SMALL && FABS(r) > SMALL) {
g = r / BASE;
f = 1;
s = c + r;
while (c < g) {
f *= BASE;
c *= BASE * BASE;
}
g = r * BASE;
while (c >= g) {
f /= BASE;
c /= BASE * BASE;
}
if ((c + r) / f < 0.95 * s) {
done = 0;
g = 1 / f;
scale[i] *= f;
for (j = l; j < n; j++) {
mat[pos(i,j,n)] *= g;
}
for (j = 0; j <= k; j++) {
mat[pos(j,i,n)] *= f;
}
}
}
}
} while (!done);
}
/*
* Transform back eigenvectors of a balanced matrix
* into the eigenvectors of the original matrix
*/
void unbalance(int n,phydbl *vr,phydbl *vi, int low, int hi, phydbl *scale)
{
int i,j,k;
phydbl tmp;
for (i = low; i <= hi; i++) {
for (j = 0; j < n; j++) {
vr[pos(i,j,n)] *= scale[i];
vi[pos(i,j,n)] *= scale[i];
}
}
for (i = low - 1; i >= 0; i--) {
if ((k = (int)scale[i]) != i) {
for (j = 0; j < n; j++) {
tmp = vr[pos(i,j,n)];
vr[pos(i,j,n)] = vr[pos(k,j,n)];
vr[pos(k,j,n)] = tmp;
tmp = vi[pos(i,j,n)];
vi[pos(i,j,n)] = vi[pos(k,j,n)];
vi[pos(k,j,n)] = tmp;
}
}
}
for (i = hi + 1; i < n; i++) {
if ((k = (int)scale[i]) != i) {
for (j = 0; j < n; j++) {
tmp = vr[pos(i,j,n)];
vr[pos(i,j,n)] = vr[pos(k,j,n)];
vr[pos(k,j,n)] = tmp;
tmp = vi[pos(i,j,n)];
vi[pos(i,j,n)] = vi[pos(k,j,n)];
vi[pos(k,j,n)] = tmp;
}
}
}
}
/*
* Reduce the submatrix in rows and columns low through hi of real matrix mat to
* Hessenberg form by elementary similarity transformations
*/
void elemhess(int job,phydbl *mat,int n,int low,int hi, phydbl *vr,
phydbl *vi, int *work)
{
/* work[n] */
int i,j,m;
phydbl x,y;
for (m = low + 1; m < hi; m++) {
for (x = 0,i = m,j = m; j <= hi; j++) {
if (FABS(mat[pos(j,m-1,n)]) > FABS(x)) {
x = mat[pos(j,m-1,n)];
i = j;
}
}
if ((work[m] = i) != m) {
for (j = m - 1; j < n; j++) {
y = mat[pos(i,j,n)];
mat[pos(i,j,n)] = mat[pos(m,j,n)];
mat[pos(m,j,n)] = y;
}
for (j = 0; j <= hi; j++) {
y = mat[pos(j,i,n)];
mat[pos(j,i,n)] = mat[pos(j,m,n)];
mat[pos(j,m,n)] = y;
}
}
if (FABS(x) > SMALL) {
for (i = m + 1; i <= hi; i++) {
if (FABS(y = mat[pos(i,m-1,n)]) > SMALL) {
y = mat[pos(i,m-1,n)] = y / x;
for (j = m; j < n; j++) {
mat[pos(i,j,n)] -= y * mat[pos(m,j,n)];
}
for (j = 0; j <= hi; j++) {
mat[pos(j,m,n)] += y * mat[pos(j,i,n)];
}
}
}
}
}
if (job) {
for (i=0; i low; m--) {
for (i = m + 1; i <= hi; i++) {
vr[pos(i,m,n)] = mat[pos(i,m-1,n)];
}
if ((i = work[m]) != m) {
for (j = m; j <= hi; j++) {
vr[pos(m,j,n)] = vr[pos(i,j,n)];
vr[pos(i,j,n)] = 0.0;
}
vr[pos(i,m,n)] = 1.0;
}
}
}
}
/*
* Calculate eigenvalues and eigenvectors of a real upper Hessenberg matrix
* Return 1 if converges successfully and 0 otherwise
*/
int realeig(int job,phydbl *mat,int n,int low, int hi, phydbl *valr,
phydbl *vali, phydbl *vr,phydbl *vi)
{
complex v;
phydbl p=.0,q=.0,r=.0,s=.0,t,w,x,y,z=0,ra,sa,norm,eps;
int niter,en,i,j,k,l,m;
phydbl precision = POW((phydbl)BASE,(phydbl)(1-(int)DIGITS));
eps = precision;
for (i=0; i hi) valr[i] = mat[pos(i,i,n)];
}
t = 0;
en = hi;
while (en >= low) {
niter = 0;
for (;;) {
/* look for single small subdiagonal element */
for (l = en; l > low; l--) {
s = FABS(mat[pos(l-1,l-1,n)]) + FABS(mat[pos(l,l,n)]);
if (FABS(s) < SMALL) s = norm;
if (FABS(mat[pos(l,l-1,n)]) <= eps * s) break;
}
/* form shift */
x = mat[pos(en,en,n)];
if (l == en) { /* one root found */
valr[en] = x + t;
if (job) mat[pos(en,en,n)] = x + t;
en--;
break;
}
y = mat[pos(en-1,en-1,n)];
w = mat[pos(en,en-1,n)] * mat[pos(en-1,en,n)];
if (l == en - 1) { /* two roots found */
p = (y - x) / 2;
q = p * p + w;
z = SQRT(FABS(q));
x += t;
if (job) {
mat[pos(en,en,n)] = x;
mat[pos(en-1,en-1,n)] = y + t;
}
if (q < 0) { /* complex pair */
valr[en-1] = x+p;
vali[en-1] = z;
valr[en] = x+p;
vali[en] = -z;
}
else { /* real pair */
z = (p < 0) ? p - z : p + z;
valr[en-1] = x + z;
valr[en] = (FABS(z) < SMALL) ? x + z : x - w / z;
if (job) {
x = mat[pos(en,en-1,n)];
s = FABS(x) + FABS(z);
p = x / s;
q = z / s;
r = SQRT(p*p+q*q);
p /= r;
q /= r;
for (j = en - 1; j < n; j++) {
z = mat[pos(en-1,j,n)];
mat[pos(en-1,j,n)] = q * z + p *
mat[pos(en,j,n)];
mat[pos(en,j,n)] = q * mat[pos(en,j,n)] - p*z;
}
for (i = 0; i <= en; i++) {
z = mat[pos(i,en-1,n)];
mat[pos(i,en-1,n)] = q * z + p * mat[pos(i,en,n)];
mat[pos(i,en,n)] = q * mat[pos(i,en,n)] - p*z;
}
for (i = low; i <= hi; i++) {
z = vr[pos(i,en-1,n)];
vr[pos(i,en-1,n)] = q*z + p*vr[pos(i,en,n)];
vr[pos(i,en,n)] = q*vr[pos(i,en,n)] - p*z;
}
}
}
en -= 2;
break;
}
if (niter == MAXITER) return(-1);
if (niter != 0 && niter % 10 == 0) {
t += x;
for (i = low; i <= en; i++) mat[pos(i,i,n)] -= x;
s = FABS(mat[pos(en,en-1,n)]) + FABS(mat[pos(en-1,en-2,n)]);
x = y = 0.75 * s;
w = -0.4375 * s * s;
}
niter++;
/* look for two consecutive small subdiagonal elements */
for (m = en - 2; m >= l; m--) {
z = mat[pos(m,m,n)];
r = x - z;
s = y - z;
p = (r * s - w) / mat[pos(m+1,m,n)] + mat[pos(m,m+1,n)];
q = mat[pos(m+1,m+1,n)] - z - r - s;
r = mat[pos(m+2,m+1,n)];
s = FABS(p) + FABS(q) + FABS(r);
p /= s;
q /= s;
r /= s;
if (m == l || FABS(mat[pos(m,m-1,n)]) * (FABS(q)+FABS(r)) <=
eps * (FABS(mat[pos(m-1,m-1,n)]) + FABS(z) +
FABS(mat[pos(m+1,m+1,n)])) * FABS(p)) break;
}
for (i = m + 2; i <= en; i++) mat[pos(i,i-2,n)] = 0;
for (i = m + 3; i <= en; i++) mat[pos(i,i-3,n)] = 0;
/* phydbl QR step involving rows l to en and columns m to en */
for (k = m; k < en; k++) {
if (k != m) {
p = mat[pos(k,k-1,n)];
q = mat[pos(k+1,k-1,n)];
r = (k == en - 1) ? 0 : mat[pos(k+2,k-1,n)];
if (FABS(x = FABS(p) + FABS(q) + FABS(r)) < SMALL) continue;
p /= x;
q /= x;
r /= x;
}
s = SQRT(p*p+q*q+r*r);
if (p < 0) s = -s;
if (k != m) {
mat[pos(k,k-1,n)] = -s * x;
}
else if (l != m) {
mat[pos(k,k-1,n)] = -mat[pos(k,k-1,n)];
}
p += s;
x = p / s;
y = q / s;
z = r / s;
q /= p;
r /= p;
/* row modification */
for (j = k; j <= (!job ? en : n-1); j++){
p = mat[pos(k,j,n)] + q * mat[pos(k+1,j,n)];
if (k != en - 1) {
p += r * mat[pos(k+2,j,n)];
mat[pos(k+2,j,n)] -= p * z;
}
mat[pos(k+1,j,n)] -= p * y;
mat[pos(k,j,n)] -= p * x;
}
j = MIN(en,k+3);
/* column modification */
for (i = (!job ? l : 0); i <= j; i++) {
p = x * mat[pos(i,k,n)] + y * mat[pos(i,k+1,n)];
if (k != en - 1) {
p += z * mat[pos(i,k+2,n)];
mat[pos(i,k+2,n)] -= p*r;
}
mat[pos(i,k+1,n)] -= p*q;
mat[pos(i,k,n)] -= p;
}
if (job) { /* accumulate transformations */
for (i = low; i <= hi; i++) {
p = x * vr[pos(i,k,n)] + y * vr[pos(i,k+1,n)];
if (k != en - 1) {
p += z * vr[pos(i,k+2,n)];
vr[pos(i,k+2,n)] -= p*r;
}
vr[pos(i,k+1,n)] -= p*q;
vr[pos(i,k,n)] -= p;
}
}
}
}
}
if (!job) return(0);
if (FABS(norm) > SMALL) {
/* back substitute to find vectors of upper triangular form */
for (en = n-1; en >= 0; en--) {
p = valr[en];
if ((q = vali[en]) < 0) { /* complex vector */
m = en - 1;
if (FABS(mat[pos(en,en-1,n)]) > FABS(mat[pos(en-1,en,n)])) {
mat[pos(en-1,en-1,n)] = q / mat[pos(en,en-1,n)];
mat[pos(en-1,en,n)] = (p - mat[pos(en,en,n)]) /
mat[pos(en,en-1,n)];
}
else {
v = cdiv(compl(0.0,-mat[pos(en-1,en,n)]),
compl(mat[pos(en-1,en-1,n)]-p,q));
mat[pos(en-1,en-1,n)] = v.re;
mat[pos(en-1,en,n)] = v.im;
}
mat[pos(en,en-1,n)] = 0;
mat[pos(en,en,n)] = 1;
for (i = en - 2; i >= 0; i--) {
w = mat[pos(i,i,n)] - p;
ra = 0;
sa = mat[pos(i,en,n)];
for (j = m; j < en; j++) {
ra += mat[pos(i,j,n)] * mat[pos(j,en-1,n)];
sa += mat[pos(i,j,n)] * mat[pos(j,en,n)];
}
if (vali[i] < 0) {
z = w;
r = ra;
s = sa;
}
else {
m = i;
if (FABS(vali[i]) < SMALL) {
v = cdiv(compl(-ra,-sa),compl(w,q));
mat[pos(i,en-1,n)] = v.re;
mat[pos(i,en,n)] = v.im;
}
else { /* solve complex equations */
x = mat[pos(i,i+1,n)];
y = mat[pos(i+1,i,n)];
v.re = (valr[i]- p)*(valr[i]-p) + vali[i]*vali[i] - q*q;
v.im = (valr[i] - p)*2*q;
if (FABS(v.re) + FABS(v.im) < SMALL) {
v.re = eps * norm * (FABS(w) +
FABS(q) + FABS(x) + FABS(y) + FABS(z));
}
v = cdiv(compl(x*r-z*ra+q*sa,x*s-z*sa-q*ra),v);
mat[pos(i,en-1,n)] = v.re;
mat[pos(i,en,n)] = v.im;
if (FABS(x) > FABS(z) + FABS(q)) {
mat[pos(i+1,en-1,n)] =
(-ra - w * mat[pos(i,en-1,n)] +
q * mat[pos(i,en,n)]) / x;
mat[pos(i+1,en,n)] = (-sa - w * mat[pos(i,en,n)] -
q * mat[pos(i,en-1,n)]) / x;
}
else {
v = cdiv(compl(-r-y*mat[pos(i,en-1,n)],
-s-y*mat[pos(i,en,n)]),compl(z,q));
mat[pos(i+1,en-1,n)] = v.re;
mat[pos(i+1,en,n)] = v.im;
}
}
}
}
}
else if (FABS(q) < SMALL) { /* real vector */
m = en;
mat[pos(en,en,n)] = 1;
for (i = en - 1; i >= 0; i--) {
w = mat[pos(i,i,n)] - p;
r = mat[pos(i,en,n)];
for (j = m; j < en; j++) {
r += mat[pos(i,j,n)] * mat[pos(j,en,n)];
}
if (vali[i] < 0) {
z = w;
s = r;
}
else {
m = i;
if (FABS(vali[i]) < SMALL) {
if (FABS(t = w) < SMALL) t = eps * norm;
mat[pos(i,en,n)] = -r / t;
}
else { /* solve real equations */
x = mat[pos(i,i+1,n)];
y = mat[pos(i+1,i,n)];
q = (valr[i] - p) * (valr[i] - p) + vali[i]*vali[i];
t = (x * s - z * r) / q;
mat[pos(i,en,n)] = t;
if (FABS(x) <= FABS(z)) {
mat[pos(i+1,en,n)] = (-s - y * t) / z;
}
else {
mat[pos(i+1,en,n)] = (-r - w * t) / x;
}
}
}
}
}
}
/* vectors of isolated roots */
for (i = 0; i < n; i++) {
if (i < low || i > hi) {
for (j = i; j < n; j++) {
vr[pos(i,j,n)] = mat[pos(i,j,n)];
}
}
}
/* multiply by transformation matrix */
for (j = n-1; j >= low; j--) {
m = MIN(j,hi);
for (i = low; i <= hi; i++) {
for (z = 0,k = low; k <= m; k++) {
z += vr[pos(i,k,n)] * mat[pos(k,j,n)];
}
vr[pos(i,j,n)] = z;
}
}
}
/* rearrange complex eigenvectors */
for (j = 0; j < n; j++) {
if (FABS(vali[j]) > SMALL) {
for (i = 0; i < n; i++) {
vi[pos(i,j,n)] = vr[pos(i,j+1,n)];
vr[pos(i,j+1,n)] = vr[pos(i,j,n)];
vi[pos(i,j+1,n)] = -vi[pos(i,j,n)];
}
j++;
}
}
return(0);
}
#define LUDCMP_TINY 1.0e-20;
int ludcmp(phydbl **a, int n, phydbl *d)
{
int i,imax,j,k;
phydbl big,dum,sum,temp;
phydbl *vv;
imax = 0;
vv = (phydbl *)mCalloc(n,sizeof(phydbl));
*d=1.0;
for (i=0;i big) big=temp;
if (FABS(big) < SMALL) Exit("\n. Singular matrix in routine LUDCMP");
vv[i]=1.0/big;
}
for (j=0;j= big)
{
big=dum;
imax=i;
}
}
if (j != imax)
{
for (k=0;k big) big=temp;
if (FABS(big) < SMALL) Exit("\n. Singular matrix in routine LUDCMP");
vv[i]=1.0/big;
}
for (j=0;j= big)
{
big=dum;
imax=i;
}
}
if (j != imax)
{
for (k=0;k ns)
{
PhyML_Printf("\n. %s %d cstate: %.2s istate: %d state_len: %d.\n",__FILE__,__LINE__,state,state_int,state_len);
PhyML_Printf("\n. Err in file %s at line %d\n",__FILE__,__LINE__);
Warn_And_Exit("");
}
p_lk[pos+state_int] = 1.;
/* PhyML_Printf("\n. %s %d cstate: %.2s istate: %d state_len: %d ns: %d pos: %d",__FILE__,__LINE__,state,state_int,state_len,ns,pos); */
}
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void Init_Tips_At_One_Site_Generic_Int(char *state, int ns, int state_len, int pos, short int *p_pars)
{
int i;
int state_int;
For(i,ns) p_pars[pos+i] = 0;
if(Is_Ambigu(state,GENERIC,state_len)) For(i,ns) p_pars[pos+i] = 1;
else
{
char format[6];
sprintf(format,"%%%dd",state_len);
if(!sscanf(state,format,&state_int))
{
PhyML_Printf("\n. state='%c'",state);
PhyML_Printf("\n. Err in file %s at line %d\n\n",__FILE__,__LINE__);
Warn_And_Exit("");
}
if(state_int > ns)
{
PhyML_Printf("\n. %s %d cstate: %.2s istate: %d state_len: %d.\n",__FILE__,__LINE__,state,state_int,state_len);
PhyML_Printf("\n. Err in file %s at line %d\n",__FILE__,__LINE__);
Warn_And_Exit("");
}
p_pars[pos+state_int] = 1;
/* PhyML_Printf("\n* %s %d cstate: %.2s istate: %d state_len: %d ns: %d pos: %d",__FILE__,__LINE__,state,state_int,state_len,ns,pos); */
}
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void Get_All_Partial_Lk_Scale(t_tree *tree, t_edge *b_fcus, t_node *a, t_node *d)
{
Update_P_Lk(tree,b_fcus,d);
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void Post_Order_Lk(t_node *a, t_node *d, t_tree *tree)
{
int i,dir;
dir = -1;
if(d->tax)
{
Get_All_Partial_Lk_Scale(tree,d->b[0],a,d);
return;
}
else
{
For(i,3)
{
if(d->v[i] != a)
Post_Order_Lk(d,d->v[i],tree);
else dir = i;
}
Get_All_Partial_Lk_Scale(tree,d->b[dir],a,d);
}
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void Pre_Order_Lk(t_node *a, t_node *d, t_tree *tree)
{
int i;
if(d->tax)
{
Get_All_Partial_Lk_Scale(tree,d->b[0],a,d);
return;
}
else
{
For(i,3)
{
if(d->v[i] != a)
{
Get_All_Partial_Lk_Scale(tree,d->b[i],d->v[i],d);
Pre_Order_Lk(d,d->v[i],tree);
}
}
}
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
phydbl Lk(t_tree *tree)
{
int br;
int n_patterns;
tree->old_lnL = tree->c_lnL;
#ifdef PHYTIME
if((tree->rates) && (tree->rates->bl_from_rt)) RATES_Update_Cur_Bl(tree);
#endif
Check_Br_Len_Bounds(tree);
if(tree->rates && tree->io->lk_approx == NORMAL)
{
tree->c_lnL = Lk_Normal_Approx(tree);
return tree->c_lnL;
}
n_patterns = tree->n_pattern;
Set_Model_Parameters(tree->mod);
For(br,2*tree->n_otu-3) Update_PMat_At_Given_Edge(tree->t_edges[br],tree);
Post_Order_Lk(tree->t_nodes[0],tree->t_nodes[0]->v[0],tree);
if(tree->both_sides)
Pre_Order_Lk(tree->t_nodes[0],
tree->t_nodes[0]->v[0],
tree);
tree->c_lnL = .0;
tree->sum_min_sum_scale = .0;
For(tree->curr_site,n_patterns)
if(tree->data->wght[tree->curr_site] > SMALL) Lk_Core(tree->t_nodes[0]->b[0],tree);
/* Qksort(tree->c_lnL_sorted,NULL,0,n_patterns-1); */
/* tree->c_lnL = .0; */
/* For(tree->curr_site,n_patterns) */
/* { */
/* tree->c_lnL += tree->c_lnL_sorted[tree->curr_site]; */
/* } */
Adjust_Min_Diff_Lk(tree);
tree->c_lnL_mixt = tree->c_lnL;
if(tree->nextree)
{
Copy_Edge_Lengths(tree->nextree,tree);
Lk(tree->nextree);
}
else Lk_LastFirst(tree);
return tree->c_lnL;
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
phydbl Lk_At_Given_Edge(t_edge *b_fcus, t_tree *tree)
{
int n_patterns;
n_patterns = tree->n_pattern;
#ifdef PHYTIME
if((tree->rates) && (tree->rates->bl_from_rt)) RATES_Update_Cur_Bl(tree);
#endif
Check_Br_Len_Bounds(tree);
if(tree->rates && tree->io->lk_approx == NORMAL)
{
tree->c_lnL = Lk_Normal_Approx(tree);
return tree->c_lnL;
}
Update_PMat_At_Given_Edge(b_fcus,tree);
if(b_fcus->left->tax)
{
PhyML_Printf("\n. Err in file %s at line %d\n\n",__FILE__,__LINE__);
Warn_And_Exit("");
}
tree->c_lnL = .0;
tree->sum_min_sum_scale = .0;
For(tree->curr_site,n_patterns)
{
if(tree->data->wght[tree->curr_site] > SMALL) Lk_Core(b_fcus,tree);
}
/* Qksort(tree->c_lnL_sorted,NULL,0,n_patterns-1); */
/* tree->c_lnL = .0; */
/* For(tree->curr_site,n_patterns) */
/* { */
/* tree->c_lnL += tree->c_lnL_sorted[tree->curr_site]; */
/* } */
Adjust_Min_Diff_Lk(tree);
tree->c_lnL_mixt = tree->c_lnL;
if(tree->nextree)
{
tree->nextree->t_edges[b_fcus->num]->l = b_fcus->l;
Lk_At_Given_Edge(tree->nextree->t_edges[b_fcus->num],tree->nextree);
}
else Lk_LastFirst(tree);
return tree->c_lnL;
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
/* Core of the likelihood calculcation. Assume that the partial likelihoods on both
sides of t_edge *b are up-to-date. Calculate the log-likelihood at one site.
*/
#ifndef USE_OLD_LK
phydbl Lk_Core(t_edge *b, t_tree *tree)
{
phydbl log_site_lk;
phydbl site_lk_cat, site_lk;
int sum_scale_left, sum_scale_rght;
int fact_sum_scale;
phydbl max_sum_scale;
phydbl sum;
int ambiguity_check,state;
int catg,ns,k,l,site;
int dim1,dim2,dim3;
int *sum_scale_left_cat,*sum_scale_rght_cat;
phydbl multiplier;
int exponent, piecewise_exponent;
phydbl tmp;
phydbl logbig;
phydbl inv_site_lk;
logbig = LOG((phydbl)BIG);
dim1 = tree->mod->n_catg * tree->mod->ns;
dim2 = tree->mod->ns;
dim3 = tree->mod->ns * tree->mod->ns;
log_site_lk = .0;
site_lk = .0;
site_lk_cat = .0;
ambiguity_check = -1;
state = -1;
site = tree->curr_site;
ns = tree->mod->ns;
if((b->rght->tax) && (!tree->mod->s_opt->greedy))
{
ambiguity_check = tree->data->c_seq[b->rght->num]->is_ambigu[site];
if(!ambiguity_check) state = Get_State_From_P_Pars(b->p_lk_tip_r,site*dim2,tree);
}
sum_scale_left = .0;
sum_scale_rght = .0;
if(tree->mod->use_m4mod) ambiguity_check = 1;
sum_scale_left_cat = b->sum_scale_left_cat;
sum_scale_rght_cat = b->sum_scale_rght_cat;
/* Actual likelihood calculation */
/* For all classes of rates */
For(catg,tree->mod->n_catg)
{
site_lk_cat = .0;
/* b is an external edge */
if((b->rght->tax) && (!tree->mod->s_opt->greedy))
{
/* If the character observed at the tip is NOT ambiguous: ns x 1 terms to consider */
if(!ambiguity_check)
{
sum = .0;
For(l,ns)
{
sum +=
b->Pij_rr[catg*dim3+state*dim2+l] *
b->p_lk_left[site*dim1+catg*dim2+l];
/* if(tree->curr_site == 0) printf("\n. %f %f %d", */
/* b->Pij_rr[catg*dim3+state*dim2+l], */
/* b->p_lk_left[site*dim1+catg*dim2+l],b->left->num); */
}
site_lk_cat += sum * tree->mod->pi->v[state];
}
/* If the character observed at the tip is ambiguous: ns x ns terms to consider */
else
{
For(k,ns)
{
sum = .0;
if(b->p_lk_tip_r[site*dim2+k] > .0)
{
For(l,ns)
{
sum +=
b->Pij_rr[catg*dim3+k*dim2+l] *
b->p_lk_left[site*dim1+catg*dim2+l];
}
site_lk_cat +=
sum *
tree->mod->pi->v[k] *
b->p_lk_tip_r[site*dim2+k];
}
}
}
}
/* b is an internal edge: ns x ns terms to consider */
else
{
For(k,ns)
{
sum = .0;
if(b->p_lk_rght[site*dim1+catg*dim2+k] > .0)
{
For(l,ns)
{
sum +=
b->Pij_rr[catg*dim3+k*dim2+l] *
b->p_lk_left[site*dim1+catg*dim2+l];
}
site_lk_cat +=
sum *
tree->mod->pi->v[k] *
b->p_lk_rght[site*dim1+catg*dim2+k];
}
}
}
tree->site_lk_cat[catg] = site_lk_cat;
}
max_sum_scale = (phydbl)BIG;
For(catg,tree->mod->n_catg)
{
sum_scale_left_cat[catg] =
(b->sum_scale_left)?
(b->sum_scale_left[catg*tree->n_pattern+site]):
(0.0);
sum_scale_rght_cat[catg] =
(b->sum_scale_rght)?
(b->sum_scale_rght[catg*tree->n_pattern+site]):
(0.0);
sum = sum_scale_left_cat[catg] + sum_scale_rght_cat[catg];
if(sum < .0)
{
PhyML_Printf("\n. sum = %G",sum);
PhyML_Printf("\n. Err in file %s at line %d\n\n",__FILE__,__LINE__);
Warn_And_Exit("\n");
}
tmp = sum + (logbig - LOG(tree->site_lk_cat[catg]))/(phydbl)LOG2;
if(tmp < max_sum_scale) max_sum_scale = tmp; /* min of the maxs */
}
/* fact_sum_scale = (int)((max_sum_scale + min_sum_scale) / 2); */
fact_sum_scale = (int)(max_sum_scale / 2);
/* Apply scaling factors */
For(catg,tree->mod->n_catg)
{
exponent = -(sum_scale_left_cat[catg]+sum_scale_rght_cat[catg])+fact_sum_scale;
site_lk_cat = tree->site_lk_cat[catg];
if(exponent > 0)
{
do
{
piecewise_exponent = MIN(exponent,63);
multiplier = (phydbl)((unsigned long long)(1) << piecewise_exponent);
site_lk_cat *= multiplier;
exponent -= piecewise_exponent;
}
while(exponent != 0);
}
else
{
do
{
piecewise_exponent = MAX(exponent,-63);
multiplier = 1. / (phydbl)((unsigned long long)(1) << -piecewise_exponent);
site_lk_cat *= multiplier;
exponent -= piecewise_exponent;
}
while(exponent != 0);
}
if(isinf(site_lk_cat))
{
PhyML_Printf("\n+ site=%4d cat=%4d site_lk_cat=%G sum_scale=%d max=%G fact=%d expo=%d dbl=%G",
tree->curr_site,
catg,
tree->site_lk_cat[catg],
sum_scale_left_cat[catg]+sum_scale_rght_cat[catg],
max_sum_scale,
fact_sum_scale,
-(sum_scale_left_cat[catg]+sum_scale_rght_cat[catg])+fact_sum_scale,
(double)tree->site_lk_cat[catg] * pow(2.,-(sum_scale_left_cat[catg]+sum_scale_rght_cat[catg])+fact_sum_scale));
site_lk_cat = BIG / 10;
}
if(site_lk_cat < SMALL)
{
if(tree->mod->n_catg == 1)
{
PhyML_Printf("\n- site=%4d cat=%4d site_lk_cat=%G sum_scale=%d max=%G fact=%d expo=%d dbl=%G",
tree->curr_site,
catg,
tree->site_lk_cat[catg],
sum_scale_left_cat[catg]+sum_scale_rght_cat[catg],
max_sum_scale,
fact_sum_scale,
-(sum_scale_left_cat[catg]+sum_scale_rght_cat[catg])+fact_sum_scale,
(double)tree->site_lk_cat[catg] * pow(2.,-(sum_scale_left_cat[catg]+sum_scale_rght_cat[catg])+fact_sum_scale));
Exit("\n");
}
site_lk_cat = .0;
}
tree->site_lk_cat[catg] = site_lk_cat;
}
site_lk = .0;
For(catg,tree->mod->n_catg)
{
site_lk += tree->site_lk_cat[catg] * tree->mod->gamma_r_proba->v[catg];
}
inv_site_lk = 0.;
/* The substitution model does include invariable sites */
if(tree->mod->invar)
{
/* The site is invariant */
if(tree->data->invar[site] > -0.5)
{
/* Multiply P(D|r=0) by 2^(fact_sum_scale) */
inv_site_lk = tree->mod->pi->v[tree->data->invar[site]];
exponent = fact_sum_scale;
do
{
piecewise_exponent = MIN(exponent,63);
multiplier = (phydbl)((unsigned long long)(1) << piecewise_exponent);
inv_site_lk *= multiplier;
exponent -= piecewise_exponent;
}
while(exponent != 0);
inv_site_lk *= tree->mod->pinvar->v;
/* Update the value of site_lk */
if(isinf(inv_site_lk)) // P(D|r=0) >> P(D|r>0) => assume P(D) = P(D|r=0)P(r=0)
{
PhyML_Printf("\n== Numerical precision issue alert.");
PhyML_Printf("\n== P(D|r=0)=%G P(D|r>0)=%G",
tree->mod->pi->v[tree->data->invar[site]],
EXP(LOG(site_lk) - (phydbl)LOG2 * fact_sum_scale));
site_lk = (1. - tree->mod->pinvar->v)*tree->mod->pi->v[tree->data->invar[site]];
fact_sum_scale = 0.0;
}
else
{
site_lk *= (1. - tree->mod->pinvar->v);
site_lk += inv_site_lk;
}
}
else
{
/* Same formula as above with P(D | subs, rate = 0) = 0 */
site_lk *= (1. - tree->mod->pinvar->v);
}
}
log_site_lk = LOG(site_lk) - (phydbl)LOG2 * fact_sum_scale;
For(catg,tree->mod->n_catg) tree->log_site_lk_cat[catg][site] = LOG(tree->site_lk_cat[catg]) - (phydbl)LOG2 * fact_sum_scale;
if(isinf(log_site_lk) || isnan(log_site_lk))
{
PhyML_Printf("\n. Site = %d",site);
PhyML_Printf("\n. invar = %d",tree->data->invar[site]);
PhyML_Printf("\n. scale_left = %d scale_rght = %d",sum_scale_left,sum_scale_rght);
PhyML_Printf("\n. inv_site_lk = %f",inv_site_lk);
PhyML_Printf("\n. Lk = %G LOG(Lk) = %f < %G",site_lk,log_site_lk,-BIG);
For(catg,tree->mod->n_catg) PhyML_Printf("\n. rr=%f p=%f",tree->mod->gamma_rr->v[catg],tree->mod->gamma_r_proba->v[catg]);
PhyML_Printf("\n. pinv = %G",tree->mod->pinvar->v);
PhyML_Printf("\n. bl mult = %G",tree->mod->br_len_multiplier->v);
/* int i; */
/* For(i,2*tree->n_otu-3) */
/* { */
/* PhyML_Printf("\n. b%3d->l = %f %f [%G] %f %f %f %f [%s]",i, */
/* tree->t_edges[i]->l, */
/* tree->t_edges[i]->gamma_prior_mean, */
/* tree->t_edges[i]->gamma_prior_var, */
/* tree->rates->nd_t[tree->t_edges[i]->left->num], */
/* tree->rates->nd_t[tree->t_edges[i]->rght->num], */
/* tree->rates->br_r[tree->t_edges[i]->left->num], */
/* tree->rates->br_r[tree->t_edges[i]->rght->num], */
/* tree->t_edges[i] == tree->e_root ? "YES" : "NO"); */
/* fflush(NULL); */
/* } */
PhyML_Printf("\n. Err in file %s at line %d",__FILE__,__LINE__);
Warn_And_Exit("\n");
}
tree->cur_site_lk[site] = log_site_lk;
/* Multiply log likelihood by the number of times this site pattern is found in the data */
tree->c_lnL_sorted[site] = tree->data->wght[site]*log_site_lk;
tree->c_lnL += tree->data->wght[site]*log_site_lk;
/* tree->sum_min_sum_scale += (int)tree->data->wght[site]*min_sum_scale; */
return log_site_lk;
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
/* Update partial likelihood on edge b on the side of b where
node d lies.
*/
void Update_P_Lk(t_tree *tree, t_edge *b, t_node *d)
{
if((tree->io->do_alias_subpatt == YES) &&
(tree->update_alias_subpatt == YES))
Alias_One_Subpatt((d==b->left)?(b->rght):(b->left),d,tree);
if(d->tax) return;
if(tree->mod->use_m4mod == NO)
{
if(tree->io->datatype == NT)
{
Update_P_Lk_Nucl(tree,b,d);
}
else if(tree->io->datatype == AA)
{
Update_P_Lk_AA(tree,b,d);
}
}
else
{
Update_P_Lk_Generic(tree,b,d);
}
if(tree->nextree) Update_P_Lk(tree->nextree,
tree->nextree->t_edges[b->num],
tree->nextree->t_nodes[d->num]);
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void Update_P_Lk_Generic(t_tree *tree, t_edge *b, t_node *d)
{
/*
|
|<- b
|
d
/ \
/ \
/ \
n_v1 n_v2
*/
t_node *n_v1, *n_v2;
phydbl p1_lk1,p2_lk2;
phydbl *p_lk,*p_lk_v1,*p_lk_v2;
phydbl *Pij1,*Pij2;
int *sum_scale, *sum_scale_v1, *sum_scale_v2;
int sum_scale_v1_val, sum_scale_v2_val;
int i,j;
int catg,site;
int dir1,dir2;
int n_patterns;
short int ambiguity_check_v1,ambiguity_check_v2;
int state_v1,state_v2;
int NsNg, Ns, NsNs;
phydbl curr_scaler;
int curr_scaler_pow, piecewise_scaler_pow;
phydbl p_lk_lim_inf;
phydbl smallest_p_lk;
int *p_lk_loc;
p_lk_lim_inf = (phydbl)P_LK_LIM_INF;
NsNg = tree->mod->n_catg * tree->mod->ns;
Ns = tree->mod->ns;
NsNs = tree->mod->ns * tree->mod->ns;
state_v1 = state_v2 = -1;
ambiguity_check_v1 = ambiguity_check_v2 = NO;
sum_scale_v1_val = sum_scale_v2_val = 0;
p1_lk1 = p2_lk2 = .0;
if(d->tax)
{
PhyML_Printf("\n. t_node %d is a leaf...",d->num);
PhyML_Printf("\n. Err in file %s at line %d\n\n",__FILE__,__LINE__);
Warn_And_Exit("\n");
}
n_patterns = tree->n_pattern;
/* TO DO: Might be worth keeping these directions in memory instead of
calculating them every time... */
dir1=dir2=-1;
For(i,3) if(d->b[i] != b) (dir1<0)?(dir1=i):(dir2=i);
/* if((dir1 == -1) || (dir2 == -1)) */
/* { */
/* PhyML_Printf("\n. d = %d",d->num); */
/* PhyML_Printf("\n. d->v[0] = %d, d->v[1] = %d, d->v[2] = %d",d->v[0]->num,d->v[1]->num,d->v[2]->num); */
/* PhyML_Printf("\n. d->b[0] = %d, d->b[1] = %d, d->b[2] = %d",d->b[0]->num,d->b[1]->num,d->b[2]->num); */
/* PhyML_Printf("\n. d->num = %d dir1 = %d dir2 = %d",d->num,dir1,dir2); */
/* PhyML_Printf("\n. Err in file %s at line %d\n\n",__FILE__,__LINE__); */
/* Exit(""); */
/* } */
n_v1 = d->v[dir1];
n_v2 = d->v[dir2];
/* Get the partial likelihood vectors on edge b and the two pendant
edges (i.e., the two other edges connected to d) */
if(d == b->left)
{
p_lk = b->p_lk_left;
sum_scale = b->sum_scale_left;
p_lk_loc = b->p_lk_loc_left;
}
else
{
p_lk = b->p_lk_rght;
sum_scale = b->sum_scale_rght;
p_lk_loc = b->p_lk_loc_rght;
}
if(d == d->b[dir1]->left)
{
p_lk_v1 = d->b[dir1]->p_lk_rght;
sum_scale_v1 = d->b[dir1]->sum_scale_rght;
}
else
{
p_lk_v1 = d->b[dir1]->p_lk_left;
sum_scale_v1 = d->b[dir1]->sum_scale_left;
}
if(d == d->b[dir2]->left)
{
p_lk_v2 = d->b[dir2]->p_lk_rght;
sum_scale_v2 = d->b[dir2]->sum_scale_rght;
}
else
{
p_lk_v2 = d->b[dir2]->p_lk_left;
sum_scale_v2 = d->b[dir2]->sum_scale_left;
}
/* Change probability matrices on the two pendant edges */
Pij1 = d->b[dir1]->Pij_rr;
Pij2 = d->b[dir2]->Pij_rr;
/* For every site in the alignment */
For(site,n_patterns)
{
state_v1 = state_v2 = -1;
ambiguity_check_v1 = ambiguity_check_v2 = NO;
if(!tree->mod->s_opt->greedy)
{
/* n_v1 and n_v2 are tip nodes */
if(n_v1->tax)
{
/* Is the state at this tip ambiguous? */
ambiguity_check_v1 = tree->data->c_seq[n_v1->num]->is_ambigu[site];
if(ambiguity_check_v1 == NO) state_v1 = Get_State_From_P_Pars(n_v1->b[0]->p_lk_tip_r,site*Ns,tree);
}
if(n_v2->tax)
{
/* Is the state at this tip ambiguous? */
ambiguity_check_v2 = tree->data->c_seq[n_v2->num]->is_ambigu[site];
if(ambiguity_check_v2 == NO) state_v2 = Get_State_From_P_Pars(n_v2->b[0]->p_lk_tip_r,site*Ns,tree);
}
}
if(tree->mod->use_m4mod)
{
ambiguity_check_v1 = YES;
ambiguity_check_v2 = YES;
}
if(p_lk_loc[site] < site)
{
Copy_P_Lk(p_lk,p_lk_loc[site],site,tree);
Copy_Scale(sum_scale,p_lk_loc[site],site,tree);
}
else
{
/* For all the rate classes */
For(catg,tree->mod->n_catg)
{
smallest_p_lk = BIG;
/* For all the states at node d */
For(i,tree->mod->ns)
{
p1_lk1 = .0;
/* n_v1 is a tip */
if((n_v1->tax) && (!tree->mod->s_opt->greedy))
{
if(ambiguity_check_v1 == NO)
{
/* For the (non-ambiguous) state at node n_v1 */
p1_lk1 = Pij1[catg*NsNs+i*Ns+state_v1];
}
else
{
/* For all the states at node n_v1 */
For(j,tree->mod->ns)
{
p1_lk1 += Pij1[catg*NsNs+i*Ns+j] * (phydbl)n_v1->b[0]->p_lk_tip_r[site*Ns+j];
}
}
}
/* n_v1 is an internal node */
else
{
/* For the states at node n_v1 */
For(j,tree->mod->ns)
{
p1_lk1 += Pij1[catg*NsNs+i*Ns+j] * p_lk_v1[site*NsNg+catg*Ns+j];
}
}
p2_lk2 = .0;
/* We do exactly the same as for node n_v1 but for node n_v2 this time.*/
/* n_v2 is a tip */
if((n_v2->tax) && (!tree->mod->s_opt->greedy))
{
if(ambiguity_check_v2 == NO)
{
/* For the (non-ambiguous) state at node n_v2 */
p2_lk2 = Pij2[catg*NsNs+i*Ns+state_v2];
}
else
{
/* For all the states at node n_v2 */
For(j,tree->mod->ns)
{
p2_lk2 += Pij2[catg*NsNs+i*Ns+j] * (phydbl)n_v2->b[0]->p_lk_tip_r[site*Ns+j];
}
}
}
/* n_v2 is an internal node */
else
{
/* For all the states at node n_v2 */
For(j,tree->mod->ns)
{
p2_lk2 += Pij2[catg*NsNs+i*Ns+j] * p_lk_v2[site*NsNg+catg*Ns+j];
}
}
p_lk[site*NsNg+catg*Ns+i] = p1_lk1 * p2_lk2;
/* PhyML_Printf("\n+ %G",p_lk[site*NsNg+catg*Ns+i]); */
if(p_lk[site*NsNg+catg*Ns+i] < smallest_p_lk) smallest_p_lk = p_lk[site*NsNg+catg*Ns+i] ;
}
/* Current scaling values at that site */
sum_scale_v1_val = (sum_scale_v1)?(sum_scale_v1[catg*n_patterns+site]):(0);
sum_scale_v2_val = (sum_scale_v2)?(sum_scale_v2[catg*n_patterns+site]):(0);
sum_scale[catg*n_patterns+site] = sum_scale_v1_val + sum_scale_v2_val;
/* PhyML_Printf("\n@ %d",sum_scale[catg*n_patterns+site]); */
/* Scaling */
if(smallest_p_lk < p_lk_lim_inf)
{
curr_scaler_pow = (int)(LOG(p_lk_lim_inf)-LOG(smallest_p_lk))/LOG2;
curr_scaler = (phydbl)((unsigned long long)(1) << curr_scaler_pow);
/* if(fabs(curr_scaler_pow) > 63 || fabs(curr_scaler_pow) > 63) */
/* { */
/* PhyML_Printf("\n. p_lk_lim_inf = %G smallest_p_lk = %G",p_lk_lim_inf,smallest_p_lk); */
/* PhyML_Printf("\n. curr_scaler_pow = %d",curr_scaler_pow); */
/* PhyML_Printf("\n. Err in file %s at line %d.",__FILE__,__LINE__); */
/* Warn_And_Exit("\n"); */
/* } */
sum_scale[catg*n_patterns+site] += curr_scaler_pow;
do
{
piecewise_scaler_pow = MIN(curr_scaler_pow,63);
curr_scaler = (phydbl)((unsigned long long)(1) << piecewise_scaler_pow);
For(i,tree->mod->ns)
{
p_lk[site*NsNg+catg*Ns+i] *= curr_scaler;
if(p_lk[site*NsNg+catg*Ns+i] > BIG)
{
PhyML_Printf("\n. p_lk_lim_inf = %G smallest_p_lk = %G",p_lk_lim_inf,smallest_p_lk);
PhyML_Printf("\n. curr_scaler_pow = %d",curr_scaler_pow);
PhyML_Printf("\n. Err in file %s at line %d.",__FILE__,__LINE__);
Warn_And_Exit("\n");
}
}
curr_scaler_pow -= piecewise_scaler_pow;
}
while(curr_scaler_pow != 0);
}
}
}
}
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void Update_P_Lk_Nucl(t_tree *tree, t_edge *b, t_node *d)
{
/*
|
|<- b
|
d
/ \
/ \
/ \
n_v1 n_v2
*/
t_node *n_v1, *n_v2;
phydbl p1_lk1,p2_lk2;
phydbl *p_lk,*p_lk_v1,*p_lk_v2;
phydbl *Pij1,*Pij2;
int *sum_scale, *sum_scale_v1, *sum_scale_v2;
int sum_scale_v1_val, sum_scale_v2_val;
int i;
int catg,site;
int dir1,dir2;
int n_patterns;
short int ambiguity_check_v1,ambiguity_check_v2;
int state_v1,state_v2;
int dim1, dim2, dim3;
phydbl curr_scaler;
int curr_scaler_pow, piecewise_scaler_pow;
phydbl p_lk_lim_inf;
phydbl smallest_p_lk;
phydbl p0,p1,p2,p3;
int *p_lk_loc;
p_lk_lim_inf = (phydbl)P_LK_LIM_INF;
dim1 = tree->mod->n_catg * tree->mod->ns;
dim2 = tree->mod->ns;
dim3 = tree->mod->ns * tree->mod->ns;
state_v1 = state_v2 = -1;
ambiguity_check_v1 = ambiguity_check_v2 = NO;
sum_scale_v1_val = sum_scale_v2_val = 0;
p1_lk1 = p2_lk2 = .0;
if(d->tax)
{
PhyML_Printf("\n. t_node %d is a leaf...",d->num);
PhyML_Printf("\n. Err in file %s at line %d\n\n",__FILE__,__LINE__);
Warn_And_Exit("\n");
}
n_patterns = tree->n_pattern;
dir1=dir2=-1;
For(i,3) if(d->b[i] != b) (dir1<0)?(dir1=i):(dir2=i);
if((dir1 == -1) || (dir2 == -1))
{
PhyML_Printf("\n. d = %d",d->num);
PhyML_Printf("\n. d->v[0] = %d, d->v[1] = %d, d->v[2] = %d",d->v[0]->num,d->v[1]->num,d->v[2]->num);
PhyML_Printf("\n. d->b[0] = %d, d->b[1] = %d, d->b[2] = %d",d->b[0]->num,d->b[1]->num,d->b[2]->num);
PhyML_Printf("\n. d->num = %d dir1 = %d dir2 = %d",d->num,dir1,dir2);
PhyML_Printf("\n. Err in file %s at line %d\n\n",__FILE__,__LINE__);
Exit("");
}
n_v1 = d->v[dir1];
n_v2 = d->v[dir2];
/* Get the partial likelihood vectors on edge b and the two pendant
edges (i.e., the two other edges connected to d) */
if(d == b->left)
{
p_lk = b->p_lk_left;
sum_scale = b->sum_scale_left;
p_lk_loc = b->p_lk_loc_left;
}
else
{
p_lk = b->p_lk_rght;
sum_scale = b->sum_scale_rght;
p_lk_loc = b->p_lk_loc_rght;
}
if(d == d->b[dir1]->left)
{
p_lk_v1 = d->b[dir1]->p_lk_rght;
sum_scale_v1 = d->b[dir1]->sum_scale_rght;
}
else
{
p_lk_v1 = d->b[dir1]->p_lk_left;
sum_scale_v1 = d->b[dir1]->sum_scale_left;
}
if(d == d->b[dir2]->left)
{
p_lk_v2 = d->b[dir2]->p_lk_rght;
sum_scale_v2 = d->b[dir2]->sum_scale_rght;
}
else
{
p_lk_v2 = d->b[dir2]->p_lk_left;
sum_scale_v2 = d->b[dir2]->sum_scale_left;
}
/* Change probability matrices on the two pendant edges */
Pij1 = d->b[dir1]->Pij_rr;
Pij2 = d->b[dir2]->Pij_rr;
/* For every site in the alignment */
For(site,n_patterns)
{
state_v1 = state_v2 = -1;
ambiguity_check_v1 = ambiguity_check_v2 = NO;
if(!tree->mod->s_opt->greedy)
{
/* n_v1 and n_v2 are tip nodes */
if(n_v1->tax)
{
/* Is the state at this tip ambiguous? */
ambiguity_check_v1 = tree->data->c_seq[n_v1->num]->is_ambigu[site];
if(ambiguity_check_v1 == NO) state_v1 = Get_State_From_P_Pars(n_v1->b[0]->p_lk_tip_r,site*dim2,tree);
}
if(n_v2->tax)
{
/* Is the state at this tip ambiguous? */
ambiguity_check_v2 = tree->data->c_seq[n_v2->num]->is_ambigu[site];
if(ambiguity_check_v2 == NO) state_v2 = Get_State_From_P_Pars(n_v2->b[0]->p_lk_tip_r,site*dim2,tree);
}
}
if(tree->mod->use_m4mod)
{
ambiguity_check_v1 = YES;
ambiguity_check_v2 = YES;
}
if(p_lk_loc[site] < site)
{
Copy_P_Lk(p_lk,p_lk_loc[site],site,tree);
Copy_Scale(sum_scale,p_lk_loc[site],site,tree);
}
else
{
/* For all the rate classes */
For(catg,tree->mod->n_catg)
{
smallest_p_lk = BIG;
/* For all the state at node d */
For(i,tree->mod->ns)
{
p1_lk1 = .0;
/* n_v1 is a tip */
if((n_v1->tax) && (!tree->mod->s_opt->greedy))
{
if(ambiguity_check_v1 == NO)
{
/* For the (non-ambiguous) state at node n_v1 */
p1_lk1 = Pij1[catg*dim3+i*dim2+state_v1];
}
else
{
/* For all the states at node n_v1 */
p0=Pij1[catg*dim3+i*dim2+0] * (phydbl)n_v1->b[0]->p_lk_tip_r[site*dim2+0];
p1=Pij1[catg*dim3+i*dim2+1] * (phydbl)n_v1->b[0]->p_lk_tip_r[site*dim2+1];
p2=Pij1[catg*dim3+i*dim2+2] * (phydbl)n_v1->b[0]->p_lk_tip_r[site*dim2+2];
p3=Pij1[catg*dim3+i*dim2+3] * (phydbl)n_v1->b[0]->p_lk_tip_r[site*dim2+3];
p1_lk1 = p0+p1+p2+p3;
if(isnan(p1_lk1))
{
PhyML_Printf("\n. p0=%f p1=%f p2=%f p3=%f",p0,p1,p2,p3);
PhyML_Printf("\n. Err in file %s at line %d.",__FILE__,__LINE__);
Warn_And_Exit("\n");
}
}
}
/* n_v1 is an internal node */
else
{
/* For the states at node n_v1 */
/* For(j,tree->mod->ns) */
/* { */
/* p1_lk1 += Pij1[catg*dim3+i*dim2+j] * p_lk_v1[site*dim1+catg*dim2+j]; */
/* } */
p0=Pij1[catg*dim3+i*dim2+0] * p_lk_v1[site*dim1+catg*dim2+0];
p1=Pij1[catg*dim3+i*dim2+1] * p_lk_v1[site*dim1+catg*dim2+1];
p2=Pij1[catg*dim3+i*dim2+2] * p_lk_v1[site*dim1+catg*dim2+2];
p3=Pij1[catg*dim3+i*dim2+3] * p_lk_v1[site*dim1+catg*dim2+3];
p1_lk1 = p0+p1+p2+p3;
if(isnan(p1_lk1))
{
PhyML_Printf("\n. p0=%f p1=%f p2=%f p3=%f",p0,p1,p2,p3);
PhyML_Printf("\n. Err in file %s at line %d.",__FILE__,__LINE__);
Warn_And_Exit("\n");
}
}
p2_lk2 = .0;
/* We do exactly the same as for node n_v1 but for node n_v2 this time.*/
/* n_v2 is a tip */
if((n_v2->tax) && (!tree->mod->s_opt->greedy))
{
if(ambiguity_check_v2 == NO)
{
/* For the (non-ambiguous) state at node n_v2 */
p2_lk2 = Pij2[catg*dim3+i*dim2+state_v2];
if(isnan(p2_lk2))
{
PhyML_Printf("\n. Tree %d",tree->tree_num);
PhyML_Printf("\n. catg=%d dim3=%d dim2=%d i=%d state_v2=%d",catg,dim3,dim2,i,state_v2);
PhyML_Printf("\n. Pij2[0] = %f",Pij2[0]);
PhyML_Printf("\n. q[0]=%f",tree->mod->eigen->q[0]);
PhyML_Printf("\n. Err in file %s at line %d.",__FILE__,__LINE__);
Warn_And_Exit("\n");
}
}
else
{
/* For all the states at node n_v2 */
p0=Pij2[catg*dim3+i*dim2+0] * (phydbl)n_v2->b[0]->p_lk_tip_r[site*dim2+0];
p1=Pij2[catg*dim3+i*dim2+1] * (phydbl)n_v2->b[0]->p_lk_tip_r[site*dim2+1];
p2=Pij2[catg*dim3+i*dim2+2] * (phydbl)n_v2->b[0]->p_lk_tip_r[site*dim2+2];
p3=Pij2[catg*dim3+i*dim2+3] * (phydbl)n_v2->b[0]->p_lk_tip_r[site*dim2+3];
p2_lk2 = p0+p1+p2+p3;
if(isnan(p2_lk2))
{
PhyML_Printf("\n. p0=%f p1=%f p2=%f p3=%f",p0,p1,p2,p3);
PhyML_Printf("\n. Err in file %s at line %d.",__FILE__,__LINE__);
Warn_And_Exit("\n");
}
}
}
/* n_v2 is an internal node */
else
{
/* For all the states at node n_v2 */
p0=Pij2[catg*dim3+i*dim2+0] * p_lk_v2[site*dim1+catg*dim2+0];
p1=Pij2[catg*dim3+i*dim2+1] * p_lk_v2[site*dim1+catg*dim2+1];
p2=Pij2[catg*dim3+i*dim2+2] * p_lk_v2[site*dim1+catg*dim2+2];
p3=Pij2[catg*dim3+i*dim2+3] * p_lk_v2[site*dim1+catg*dim2+3];
p2_lk2 = p0+p1+p2+p3;
if(isnan(p2_lk2))
{
PhyML_Printf("\n. p0=%f p1=%f p2=%f p3=%f",p0,p1,p2,p3);
PhyML_Printf("\n. Err in file %s at line %d.",__FILE__,__LINE__);
Warn_And_Exit("\n");
}
}
p_lk[site*dim1+catg*dim2+i] = p1_lk1 * p2_lk2;
if(isnan(p2_lk2))
{
PhyML_Printf("\n. Err in file %s at line %d.",__FILE__,__LINE__);
Warn_And_Exit("\n");
}
if(p_lk[site*dim1+catg*dim2+i] < smallest_p_lk) smallest_p_lk = p_lk[site*dim1+catg*dim2+i] ;
}
/* Current scaling values at that site */
sum_scale_v1_val = (sum_scale_v1)?(sum_scale_v1[catg*n_patterns+site]):(0);
sum_scale_v2_val = (sum_scale_v2)?(sum_scale_v2[catg*n_patterns+site]):(0);
sum_scale[catg*n_patterns+site] = sum_scale_v1_val + sum_scale_v2_val;
/* Scaling */
if(smallest_p_lk < p_lk_lim_inf)
{
curr_scaler_pow = (int)(LOG(p_lk_lim_inf)-LOG(smallest_p_lk))/LOG2;
curr_scaler = (phydbl)((unsigned long long)(1) << curr_scaler_pow);
/* if(fabs(curr_scaler_pow) > 63 || fabs(curr_scaler_pow) > 63) */
/* { */
/* PhyML_Printf("\n. p_lk_lim_inf = %G smallest_p_lk = %G",p_lk_lim_inf,smallest_p_lk); */
/* PhyML_Printf("\n. curr_scaler_pow = %d",curr_scaler_pow); */
/* PhyML_Printf("\n. Err in file %s at line %d.",__FILE__,__LINE__); */
/* Warn_And_Exit("\n"); */
/* } */
sum_scale[catg*n_patterns+site] += curr_scaler_pow;
do
{
piecewise_scaler_pow = MIN(curr_scaler_pow,63);
curr_scaler = (phydbl)((unsigned long long)(1) << piecewise_scaler_pow);
For(i,tree->mod->ns)
{
p_lk[site*dim1+catg*dim2+i] *= curr_scaler;
if(p_lk[site*dim1+catg*dim2+i] > BIG)
{
PhyML_Printf("\n. p_lk_lim_inf = %G smallest_p_lk = %G",p_lk_lim_inf,smallest_p_lk);
PhyML_Printf("\n. curr_scaler_pow = %d",curr_scaler_pow);
PhyML_Printf("\n. Err in file %s at line %d.",__FILE__,__LINE__);
Warn_And_Exit("\n");
}
}
curr_scaler_pow -= piecewise_scaler_pow;
}
while(curr_scaler_pow != 0);
}
}
}
}
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void Update_P_Lk_AA(t_tree *tree, t_edge *b, t_node *d)
{
/*
|
|<- b
|
d
/ \
/ \
/ \
n_v1 n_v2
*/
t_node *n_v1, *n_v2;
phydbl p1_lk1,p2_lk2;
phydbl *p_lk,*p_lk_v1,*p_lk_v2;
phydbl *Pij1,*Pij2;
int *sum_scale, *sum_scale_v1, *sum_scale_v2;
int sum_scale_v1_val, sum_scale_v2_val;
int i;
int catg,site;
int dir1,dir2;
int n_patterns;
short int ambiguity_check_v1,ambiguity_check_v2;
int state_v1,state_v2;
int dim1, dim2, dim3;
phydbl curr_scaler;
int curr_scaler_pow, piecewise_scaler_pow;
phydbl p_lk_lim_inf;
phydbl smallest_p_lk;
phydbl p0,p1,p2,p3,p4,p5,p6,p7,p8,p9,p10,p11,p12,p13,p14,p15,p16,p17,p18,p19;
int *p_lk_loc;
p_lk_lim_inf = (phydbl)P_LK_LIM_INF;
dim1 = tree->mod->n_catg * tree->mod->ns;
dim2 = tree->mod->ns;
dim3 = tree->mod->ns * tree->mod->ns;
state_v1 = state_v2 = -1;
ambiguity_check_v1 = ambiguity_check_v2 = NO;
sum_scale_v1_val = sum_scale_v2_val = 0;
p1_lk1 = p2_lk2 = .0;
if(d->tax)
{
PhyML_Printf("\n. t_node %d is a leaf...",d->num);
PhyML_Printf("\n. Err in file %s at line %d\n\n",__FILE__,__LINE__);
Warn_And_Exit("\n");
}
n_patterns = tree->n_pattern;
/* TO DO: Might be worth keeping these directions in memory instead of
calculating them every time... */
dir1=dir2=-1;
For(i,3) if(d->b[i] != b) (dir1<0)?(dir1=i):(dir2=i);
/* if((dir1 == -1) || (dir2 == -1)) */
/* { */
/* PhyML_Printf("\n. d = %d",d->num); */
/* PhyML_Printf("\n. d->v[0] = %d, d->v[1] = %d, d->v[2] = %d",d->v[0]->num,d->v[1]->num,d->v[2]->num); */
/* PhyML_Printf("\n. d->b[0] = %d, d->b[1] = %d, d->b[2] = %d",d->b[0]->num,d->b[1]->num,d->b[2]->num); */
/* PhyML_Printf("\n. d->num = %d dir1 = %d dir2 = %d",d->num,dir1,dir2); */
/* PhyML_Printf("\n. Err in file %s at line %d\n\n",__FILE__,__LINE__); */
/* Exit(""); */
/* } */
n_v1 = d->v[dir1];
n_v2 = d->v[dir2];
/* Get the partial likelihood vectors on edge b and the two pendant
edges (i.e., the two other edges connected to d) */
if(d == b->left)
{
p_lk = b->p_lk_left;
sum_scale = b->sum_scale_left;
p_lk_loc = b->p_lk_loc_left;
}
else
{
p_lk = b->p_lk_rght;
sum_scale = b->sum_scale_rght;
p_lk_loc = b->p_lk_loc_rght;
}
if(d == d->b[dir1]->left)
{
p_lk_v1 = d->b[dir1]->p_lk_rght;
sum_scale_v1 = d->b[dir1]->sum_scale_rght;
}
else
{
p_lk_v1 = d->b[dir1]->p_lk_left;
sum_scale_v1 = d->b[dir1]->sum_scale_left;
}
if(d == d->b[dir2]->left)
{
p_lk_v2 = d->b[dir2]->p_lk_rght;
sum_scale_v2 = d->b[dir2]->sum_scale_rght;
}
else
{
p_lk_v2 = d->b[dir2]->p_lk_left;
sum_scale_v2 = d->b[dir2]->sum_scale_left;
}
/* Change probability matrices on the two pendant edges */
Pij1 = d->b[dir1]->Pij_rr;
Pij2 = d->b[dir2]->Pij_rr;
/* For every site in the alignment */
For(site,n_patterns)
{
state_v1 = state_v2 = -1;
ambiguity_check_v1 = ambiguity_check_v2 = NO;
if(!tree->mod->s_opt->greedy)
{
/* n_v1 and n_v2 are tip nodes */
if(n_v1->tax)
{
/* Is the state at this tip ambiguous? */
ambiguity_check_v1 = tree->data->c_seq[n_v1->num]->is_ambigu[site];
if(ambiguity_check_v1 == NO) state_v1 = Get_State_From_P_Pars(n_v1->b[0]->p_lk_tip_r,site*dim2,tree);
}
if(n_v2->tax)
{
/* Is the state at this tip ambiguous? */
ambiguity_check_v2 = tree->data->c_seq[n_v2->num]->is_ambigu[site];
if(ambiguity_check_v2 == NO) state_v2 = Get_State_From_P_Pars(n_v2->b[0]->p_lk_tip_r,site*dim2,tree);
}
}
if(tree->mod->use_m4mod)
{
ambiguity_check_v1 = YES;
ambiguity_check_v2 = YES;
}
if(p_lk_loc[site] < site)
{
Copy_P_Lk(p_lk,p_lk_loc[site],site,tree);
Copy_Scale(sum_scale,p_lk_loc[site],site,tree);
}
else
{
/* For all the rate classes */
For(catg,tree->mod->n_catg)
{
smallest_p_lk = BIG;
/* For all the state at node d */
For(i,tree->mod->ns)
{
p1_lk1 = .0;
/* n_v1 is a tip */
if((n_v1->tax) && (!tree->mod->s_opt->greedy))
{
if(ambiguity_check_v1 == NO)
{
/* For the (non-ambiguous) state at node n_v1 */
p1_lk1 = Pij1[catg*dim3+i*dim2+state_v1];
}
else
{
/* For all the states at node n_v1 */
p0 = Pij1[catg*dim3+i*dim2+ 0] * (phydbl)n_v1->b[0]->p_lk_tip_r[site*dim2+ 0];
p1 = Pij1[catg*dim3+i*dim2+ 1] * (phydbl)n_v1->b[0]->p_lk_tip_r[site*dim2+ 1];
p2 = Pij1[catg*dim3+i*dim2+ 2] * (phydbl)n_v1->b[0]->p_lk_tip_r[site*dim2+ 2];
p3 = Pij1[catg*dim3+i*dim2+ 3] * (phydbl)n_v1->b[0]->p_lk_tip_r[site*dim2+ 3];
p4 = Pij1[catg*dim3+i*dim2+ 4] * (phydbl)n_v1->b[0]->p_lk_tip_r[site*dim2+ 4];
p5 = Pij1[catg*dim3+i*dim2+ 5] * (phydbl)n_v1->b[0]->p_lk_tip_r[site*dim2+ 5];
p6 = Pij1[catg*dim3+i*dim2+ 6] * (phydbl)n_v1->b[0]->p_lk_tip_r[site*dim2+ 6];
p7 = Pij1[catg*dim3+i*dim2+ 7] * (phydbl)n_v1->b[0]->p_lk_tip_r[site*dim2+ 7];
p8 = Pij1[catg*dim3+i*dim2+ 8] * (phydbl)n_v1->b[0]->p_lk_tip_r[site*dim2+ 8];
p9 = Pij1[catg*dim3+i*dim2+ 9] * (phydbl)n_v1->b[0]->p_lk_tip_r[site*dim2+ 9];
p10 = Pij1[catg*dim3+i*dim2+10] * (phydbl)n_v1->b[0]->p_lk_tip_r[site*dim2+10];
p11 = Pij1[catg*dim3+i*dim2+11] * (phydbl)n_v1->b[0]->p_lk_tip_r[site*dim2+11];
p12 = Pij1[catg*dim3+i*dim2+12] * (phydbl)n_v1->b[0]->p_lk_tip_r[site*dim2+12];
p13 = Pij1[catg*dim3+i*dim2+13] * (phydbl)n_v1->b[0]->p_lk_tip_r[site*dim2+13];
p14 = Pij1[catg*dim3+i*dim2+14] * (phydbl)n_v1->b[0]->p_lk_tip_r[site*dim2+14];
p15 = Pij1[catg*dim3+i*dim2+15] * (phydbl)n_v1->b[0]->p_lk_tip_r[site*dim2+15];
p16 = Pij1[catg*dim3+i*dim2+16] * (phydbl)n_v1->b[0]->p_lk_tip_r[site*dim2+16];
p17 = Pij1[catg*dim3+i*dim2+17] * (phydbl)n_v1->b[0]->p_lk_tip_r[site*dim2+17];
p18 = Pij1[catg*dim3+i*dim2+18] * (phydbl)n_v1->b[0]->p_lk_tip_r[site*dim2+18];
p19 = Pij1[catg*dim3+i*dim2+19] * (phydbl)n_v1->b[0]->p_lk_tip_r[site*dim2+19];
p1_lk1 = p0+p1+p2+p3+p4+p5+p6+p7+p8+p9+p10+p11+p12+p13+p14+p15+p16+p17+p18+p19;
}
}
/* n_v1 is an internal node */
else
{
/* For the states at node n_v1 */
p0 = Pij1[catg*dim3+i*dim2+ 0] * (phydbl)p_lk_v1[site*dim1+catg*dim2+ 0];
p1 = Pij1[catg*dim3+i*dim2+ 1] * (phydbl)p_lk_v1[site*dim1+catg*dim2+ 1];
p2 = Pij1[catg*dim3+i*dim2+ 2] * (phydbl)p_lk_v1[site*dim1+catg*dim2+ 2];
p3 = Pij1[catg*dim3+i*dim2+ 3] * (phydbl)p_lk_v1[site*dim1+catg*dim2+ 3];
p4 = Pij1[catg*dim3+i*dim2+ 4] * (phydbl)p_lk_v1[site*dim1+catg*dim2+ 4];
p5 = Pij1[catg*dim3+i*dim2+ 5] * (phydbl)p_lk_v1[site*dim1+catg*dim2+ 5];
p6 = Pij1[catg*dim3+i*dim2+ 6] * (phydbl)p_lk_v1[site*dim1+catg*dim2+ 6];
p7 = Pij1[catg*dim3+i*dim2+ 7] * (phydbl)p_lk_v1[site*dim1+catg*dim2+ 7];
p8 = Pij1[catg*dim3+i*dim2+ 8] * (phydbl)p_lk_v1[site*dim1+catg*dim2+ 8];
p9 = Pij1[catg*dim3+i*dim2+ 9] * (phydbl)p_lk_v1[site*dim1+catg*dim2+ 9];
p10 = Pij1[catg*dim3+i*dim2+10] * (phydbl)p_lk_v1[site*dim1+catg*dim2+10];
p11 = Pij1[catg*dim3+i*dim2+11] * (phydbl)p_lk_v1[site*dim1+catg*dim2+11];
p12 = Pij1[catg*dim3+i*dim2+12] * (phydbl)p_lk_v1[site*dim1+catg*dim2+12];
p13 = Pij1[catg*dim3+i*dim2+13] * (phydbl)p_lk_v1[site*dim1+catg*dim2+13];
p14 = Pij1[catg*dim3+i*dim2+14] * (phydbl)p_lk_v1[site*dim1+catg*dim2+14];
p15 = Pij1[catg*dim3+i*dim2+15] * (phydbl)p_lk_v1[site*dim1+catg*dim2+15];
p16 = Pij1[catg*dim3+i*dim2+16] * (phydbl)p_lk_v1[site*dim1+catg*dim2+16];
p17 = Pij1[catg*dim3+i*dim2+17] * (phydbl)p_lk_v1[site*dim1+catg*dim2+17];
p18 = Pij1[catg*dim3+i*dim2+18] * (phydbl)p_lk_v1[site*dim1+catg*dim2+18];
p19 = Pij1[catg*dim3+i*dim2+19] * (phydbl)p_lk_v1[site*dim1+catg*dim2+19];
p1_lk1 = p0+p1+p2+p3+p4+p5+p6+p7+p8+p9+p10+p11+p12+p13+p14+p15+p16+p17+p18+p19;
}
p2_lk2 = .0;
/* We do exactly the same as for node n_v1 but for node n_v2 this time.*/
/* n_v2 is a tip */
if((n_v2->tax) && (!tree->mod->s_opt->greedy))
{
if(ambiguity_check_v2 == NO)
{
/* For the (non-ambiguous) state at node n_v2 */
p2_lk2 = Pij2[catg*dim3+i*dim2+state_v2];
}
else
{
/* For all the states at node n_v2 */
p0 = Pij2[catg*dim3+i*dim2+ 0] * (phydbl)n_v2->b[0]->p_lk_tip_r[site*dim2+ 0];
p1 = Pij2[catg*dim3+i*dim2+ 1] * (phydbl)n_v2->b[0]->p_lk_tip_r[site*dim2+ 1];
p2 = Pij2[catg*dim3+i*dim2+ 2] * (phydbl)n_v2->b[0]->p_lk_tip_r[site*dim2+ 2];
p3 = Pij2[catg*dim3+i*dim2+ 3] * (phydbl)n_v2->b[0]->p_lk_tip_r[site*dim2+ 3];
p4 = Pij2[catg*dim3+i*dim2+ 4] * (phydbl)n_v2->b[0]->p_lk_tip_r[site*dim2+ 4];
p5 = Pij2[catg*dim3+i*dim2+ 5] * (phydbl)n_v2->b[0]->p_lk_tip_r[site*dim2+ 5];
p6 = Pij2[catg*dim3+i*dim2+ 6] * (phydbl)n_v2->b[0]->p_lk_tip_r[site*dim2+ 6];
p7 = Pij2[catg*dim3+i*dim2+ 7] * (phydbl)n_v2->b[0]->p_lk_tip_r[site*dim2+ 7];
p8 = Pij2[catg*dim3+i*dim2+ 8] * (phydbl)n_v2->b[0]->p_lk_tip_r[site*dim2+ 8];
p9 = Pij2[catg*dim3+i*dim2+ 9] * (phydbl)n_v2->b[0]->p_lk_tip_r[site*dim2+ 9];
p10 = Pij2[catg*dim3+i*dim2+10] * (phydbl)n_v2->b[0]->p_lk_tip_r[site*dim2+10];
p11 = Pij2[catg*dim3+i*dim2+11] * (phydbl)n_v2->b[0]->p_lk_tip_r[site*dim2+11];
p12 = Pij2[catg*dim3+i*dim2+12] * (phydbl)n_v2->b[0]->p_lk_tip_r[site*dim2+12];
p13 = Pij2[catg*dim3+i*dim2+13] * (phydbl)n_v2->b[0]->p_lk_tip_r[site*dim2+13];
p14 = Pij2[catg*dim3+i*dim2+14] * (phydbl)n_v2->b[0]->p_lk_tip_r[site*dim2+14];
p15 = Pij2[catg*dim3+i*dim2+15] * (phydbl)n_v2->b[0]->p_lk_tip_r[site*dim2+15];
p16 = Pij2[catg*dim3+i*dim2+16] * (phydbl)n_v2->b[0]->p_lk_tip_r[site*dim2+16];
p17 = Pij2[catg*dim3+i*dim2+17] * (phydbl)n_v2->b[0]->p_lk_tip_r[site*dim2+17];
p18 = Pij2[catg*dim3+i*dim2+18] * (phydbl)n_v2->b[0]->p_lk_tip_r[site*dim2+18];
p19 = Pij2[catg*dim3+i*dim2+19] * (phydbl)n_v2->b[0]->p_lk_tip_r[site*dim2+19];
p2_lk2 = p0+p1+p2+p3+p4+p5+p6+p7+p8+p9+p10+p11+p12+p13+p14+p15+p16+p17+p18+p19;
}
}
/* n_v2 is an internal node */
else
{
/* For all the states at node n_v2 */
p0 = Pij2[catg*dim3+i*dim2+ 0] * (phydbl)p_lk_v2[site*dim1+catg*dim2+ 0];
p1 = Pij2[catg*dim3+i*dim2+ 1] * (phydbl)p_lk_v2[site*dim1+catg*dim2+ 1];
p2 = Pij2[catg*dim3+i*dim2+ 2] * (phydbl)p_lk_v2[site*dim1+catg*dim2+ 2];
p3 = Pij2[catg*dim3+i*dim2+ 3] * (phydbl)p_lk_v2[site*dim1+catg*dim2+ 3];
p4 = Pij2[catg*dim3+i*dim2+ 4] * (phydbl)p_lk_v2[site*dim1+catg*dim2+ 4];
p5 = Pij2[catg*dim3+i*dim2+ 5] * (phydbl)p_lk_v2[site*dim1+catg*dim2+ 5];
p6 = Pij2[catg*dim3+i*dim2+ 6] * (phydbl)p_lk_v2[site*dim1+catg*dim2+ 6];
p7 = Pij2[catg*dim3+i*dim2+ 7] * (phydbl)p_lk_v2[site*dim1+catg*dim2+ 7];
p8 = Pij2[catg*dim3+i*dim2+ 8] * (phydbl)p_lk_v2[site*dim1+catg*dim2+ 8];
p9 = Pij2[catg*dim3+i*dim2+ 9] * (phydbl)p_lk_v2[site*dim1+catg*dim2+ 9];
p10 = Pij2[catg*dim3+i*dim2+10] * (phydbl)p_lk_v2[site*dim1+catg*dim2+10];
p11 = Pij2[catg*dim3+i*dim2+11] * (phydbl)p_lk_v2[site*dim1+catg*dim2+11];
p12 = Pij2[catg*dim3+i*dim2+12] * (phydbl)p_lk_v2[site*dim1+catg*dim2+12];
p13 = Pij2[catg*dim3+i*dim2+13] * (phydbl)p_lk_v2[site*dim1+catg*dim2+13];
p14 = Pij2[catg*dim3+i*dim2+14] * (phydbl)p_lk_v2[site*dim1+catg*dim2+14];
p15 = Pij2[catg*dim3+i*dim2+15] * (phydbl)p_lk_v2[site*dim1+catg*dim2+15];
p16 = Pij2[catg*dim3+i*dim2+16] * (phydbl)p_lk_v2[site*dim1+catg*dim2+16];
p17 = Pij2[catg*dim3+i*dim2+17] * (phydbl)p_lk_v2[site*dim1+catg*dim2+17];
p18 = Pij2[catg*dim3+i*dim2+18] * (phydbl)p_lk_v2[site*dim1+catg*dim2+18];
p19 = Pij2[catg*dim3+i*dim2+19] * (phydbl)p_lk_v2[site*dim1+catg*dim2+19];
p2_lk2 = p0+p1+p2+p3+p4+p5+p6+p7+p8+p9+p10+p11+p12+p13+p14+p15+p16+p17+p18+p19;
}
p_lk[site*dim1+catg*dim2+i] = p1_lk1 * p2_lk2;
if(p_lk[site*dim1+catg*dim2+i] < smallest_p_lk) smallest_p_lk = p_lk[site*dim1+catg*dim2+i] ;
}
/* Current scaling values at that site */
sum_scale_v1_val = (sum_scale_v1)?(sum_scale_v1[catg*n_patterns+site]):(0);
sum_scale_v2_val = (sum_scale_v2)?(sum_scale_v2[catg*n_patterns+site]):(0);
sum_scale[catg*n_patterns+site] = sum_scale_v1_val + sum_scale_v2_val;
/* Scaling */
if(smallest_p_lk < p_lk_lim_inf)
{
curr_scaler_pow = (int)(LOG(p_lk_lim_inf)-LOG(smallest_p_lk))/LOG2;
curr_scaler = (phydbl)((unsigned long long)(1) << curr_scaler_pow);
/* if(fabs(curr_scaler_pow) > 63 || fabs(curr_scaler_pow) > 63) */
/* { */
/* PhyML_Printf("\n. p_lk_lim_inf = %G smallest_p_lk = %G",p_lk_lim_inf,smallest_p_lk); */
/* PhyML_Printf("\n. curr_scaler_pow = %d",curr_scaler_pow); */
/* PhyML_Printf("\n. Err in file %s at line %d.",__FILE__,__LINE__); */
/* Warn_And_Exit("\n"); */
/* } */
sum_scale[catg*n_patterns+site] += curr_scaler_pow;
do
{
piecewise_scaler_pow = MIN(curr_scaler_pow,63);
curr_scaler = (phydbl)((unsigned long long)(1) << piecewise_scaler_pow);
For(i,tree->mod->ns)
{
p_lk[site*dim1+catg*dim2+i] *= curr_scaler;
if(p_lk[site*dim1+catg*dim2+i] > BIG)
{
PhyML_Printf("\n. p_lk_lim_inf = %G smallest_p_lk = %G",p_lk_lim_inf,smallest_p_lk);
PhyML_Printf("\n. curr_scaler_pow = %d",curr_scaler_pow);
PhyML_Printf("\n. Err in file %s at line %d.",__FILE__,__LINE__);
Warn_And_Exit("\n");
}
}
curr_scaler_pow -= piecewise_scaler_pow;
}
while(curr_scaler_pow != 0);
}
}
}
}
}
#endif
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
phydbl Return_Abs_Lk(t_tree *tree)
{
Lk(tree);
return FABS(tree->c_lnL);
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
matrix *ML_Dist(calign *data, model *mod)
{
int i,j,k,l;
phydbl init;
int n_catg;
phydbl d_max,sum;
matrix *mat;
calign *twodata,*tmpdata;
int state0, state1,len;
phydbl *F;
eigen *eigen_struct;
tmpdata = (calign *)mCalloc(1,sizeof(calign));
tmpdata->c_seq = (align **)mCalloc(2,sizeof(align *));
tmpdata->b_frq = (phydbl *)mCalloc(mod->ns,sizeof(phydbl));
tmpdata->ambigu = (short int *)mCalloc(data->crunch_len,sizeof(short int));
F = (phydbl *)mCalloc(mod->ns*mod->ns,sizeof(phydbl ));
eigen_struct = (eigen *)Make_Eigen_Struct(mod->ns);
tmpdata->n_otu = 2;
tmpdata->crunch_len = data->crunch_len;
tmpdata->init_len = data->init_len;
mat = NULL;
if(mod->io->datatype == NT) mat = (mod->whichmodel < 10)?(K80_dist(data,1E+6)):(JC69_Dist(data,mod));
else if(mod->io->datatype == AA) mat = JC69_Dist(data,mod);
else if(mod->io->datatype == GENERIC) mat = JC69_Dist(data,mod);
For(i,mod->n_catg) /* Don't use the discrete gamma distribution */
{
mod->gamma_rr->v[i] = 1.0;
mod->gamma_r_proba->v[i] = 1.0;
}
n_catg = mod->n_catg;
mod->n_catg = 1;
For(j,data->n_otu-1)
{
tmpdata->c_seq[0] = data->c_seq[j];
tmpdata->c_seq[0]->name = data->c_seq[j]->name;
tmpdata->wght = data->wght;
for(k=j+1;kn_otu;k++)
{
tmpdata->c_seq[1] = data->c_seq[k];
tmpdata->c_seq[1]->name = data->c_seq[k]->name;
twodata = Compact_Cdata(tmpdata,mod->io);
Check_Ambiguities(twodata,mod->io->datatype,mod->io->mod->state_len);
Hide_Ambiguities(twodata);
init = mat->dist[j][k];
if((init > DIST_MAX-SMALL) || (init < .0)) init = 0.1;
d_max = init;
For(i,mod->ns*mod->ns) F[i]=.0;
len = 0;
For(l,twodata->c_seq[0]->len)
{
state0 = Assign_State(twodata->c_seq[0]->state+l*mod->io->mod->state_len,mod->io->datatype,mod->io->mod->state_len);
state1 = Assign_State(twodata->c_seq[1]->state+l*mod->io->mod->state_len,mod->io->datatype,mod->io->mod->state_len);
if((state0 > -1) && (state1 > -1))
{
F[mod->ns*state0+state1] += twodata->wght[l];
len += (int)twodata->wght[l];
}
}
if(len > .0) {For(i,mod->ns*mod->ns) F[i] /= (phydbl)len;}
sum = 0.;
For(i,mod->ns*mod->ns) sum += F[i];
/* if(sum < .001) d_max = -1.; */
if(sum < .001) d_max = init;
else if((sum > 1. - .001) && (sum < 1. + .001)) Opt_Dist_F(&(d_max),F,mod);
else
{
PhyML_Printf("\n. sum = %f\n",sum);
PhyML_Printf("\n. Err in file %s at line %d\n\n",__FILE__,__LINE__);
Exit("");
}
if(d_max >= DIST_MAX) d_max = DIST_MAX;
/* Do not correct for dist < BL_MIN, otherwise Fill_Missing_Dist
* will not be called
*/
mat->dist[j][k] = d_max;
mat->dist[k][j] = mat->dist[j][k];
Free_Cseq(twodata);
}
}
mod->n_catg = n_catg;
Free(tmpdata->ambigu);
Free(tmpdata->b_frq);
Free(tmpdata->c_seq);
free(tmpdata);
Free_Eigen(eigen_struct);
Free(F);
return mat;
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
phydbl Lk_Given_Two_Seq(calign *data, int numseq1, int numseq2, phydbl dist, model *mod, phydbl *loglk)
{
align *seq1,*seq2;
phydbl site_lk,log_site_lk;
int i,j,k,l;
/* phydbl **p_lk_l,**p_lk_r; */
phydbl *p_lk_l,*p_lk_r;
phydbl len;
int dim1,dim2;
dim1 = mod->ns;
dim2 = mod->ns * mod->ns;
DiscreteGamma(mod->gamma_r_proba->v, mod->gamma_rr->v, mod->alpha->v,
mod->alpha->v,mod->n_catg,mod->gamma_median);
seq1 = data->c_seq[numseq1];
seq2 = data->c_seq[numseq2];
p_lk_l = (phydbl *)mCalloc(data->c_seq[0]->len * mod->ns,sizeof(phydbl));
p_lk_r = (phydbl *)mCalloc(data->c_seq[0]->len * mod->ns,sizeof(phydbl));
For(i,mod->n_catg)
{
len = dist*mod->gamma_rr->v[i];
if(len < mod->l_min) len = mod->l_min;
else if(len > mod->l_max) len = mod->l_max;
PMat(len,mod,dim2*i,mod->Pij_rr->v);
}
if(mod->io->datatype == NT)
{
For(i,data->c_seq[0]->len)
{
Init_Tips_At_One_Site_Nucleotides_Float(seq1->state[i],i*mod->ns,p_lk_l);
Init_Tips_At_One_Site_Nucleotides_Float(seq2->state[i],i*mod->ns,p_lk_r);
}
}
else if(mod->io->datatype == AA)
{
For(i,data->c_seq[0]->len)
{
Init_Tips_At_One_Site_AA_Float(seq1->state[i],i*mod->ns,p_lk_l);
Init_Tips_At_One_Site_AA_Float(seq2->state[i],i*mod->ns,p_lk_r);
}
}
else
{
PhyML_Printf("\n. Not implemented yet...");
PhyML_Printf("\n. Err in file %s at line %d\n\n",__FILE__,__LINE__);
Warn_And_Exit("\n");
}
site_lk = .0;
*loglk = 0;
For(i,data->c_seq[0]->len)
{
if(data->wght[i])
{
site_lk = log_site_lk = .0;
if(!data->ambigu[i])
{
For(k,mod->ns) {if(p_lk_l[i*mod->ns+k] > .0001) break;}
For(l,mod->ns) {if(p_lk_r[i*mod->ns+l] > .0001) break;}
For(j,mod->n_catg)
{
site_lk +=
mod->gamma_r_proba->v[j] *
mod->pi->v[k] *
p_lk_l[i*dim1+k] *
mod->Pij_rr->v[j*dim2+k*dim1+l] *
p_lk_r[i*dim1+l];
}
}
else
{
For(j,mod->n_catg)
{
For(k,mod->ns) /*sort sum terms ? No global effect*/
{
For(l,mod->ns)
{
site_lk +=
mod->gamma_r_proba->v[j] *
mod->pi->v[k] *
p_lk_l[i*dim1+k] *
mod->Pij_rr->v[j*dim2+k*dim1+l] *
p_lk_r[i*dim1+l];
}
}
}
}
if(site_lk <= .0)
{
PhyML_Printf("'%c' '%c'\n",seq1->state[i],seq2->state[i]);
Exit("\n. Err: site lk <= 0\n");
}
log_site_lk += (phydbl)LOG(site_lk);
*loglk += data->wght[i] * log_site_lk;/* sort sum terms ? No global effect*/
}
}
/* For(i,data->c_seq[0]->len) */
/* { */
/* Free(p_lk_l[i]); */
/* Free(p_lk_r[i]); */
/* } */
Free(p_lk_l); Free(p_lk_r);
return *loglk;
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void Unconstraint_Lk(t_tree *tree)
{
int i;
tree->unconstraint_lk = .0;
For(i,tree->data->crunch_len)
{
tree->unconstraint_lk +=
tree->data->wght[i]*(phydbl)LOG(tree->data->wght[i]);
}
tree->unconstraint_lk -=
tree->data->init_len*(phydbl)LOG(tree->data->init_len);
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void Make_Tree_4_Lk(t_tree *tree, calign *cdata, int n_site)
{
int i;
tree->c_lnL_sorted = (phydbl *)mCalloc(tree->n_pattern, sizeof(phydbl));
tree->cur_site_lk = (phydbl *)mCalloc(cdata->crunch_len,sizeof(phydbl));
tree->old_site_lk = (phydbl *)mCalloc(cdata->crunch_len,sizeof(phydbl));
tree->site_lk_cat = (phydbl *)mCalloc(tree->mod->n_catg,sizeof(phydbl));
tree->log_site_lk_cat = (phydbl **)mCalloc(tree->mod->n_catg,sizeof(phydbl *));
For(i,tree->mod->n_catg)
tree->log_site_lk_cat[i] = (phydbl *)mCalloc(cdata->crunch_len,sizeof(phydbl));
tree->log_lks_aLRT = (phydbl **)mCalloc(3,sizeof(phydbl *));
For(i,3) tree->log_lks_aLRT[i] = (phydbl *)mCalloc(tree->data->init_len,sizeof(phydbl));
For(i,2*tree->n_otu-3)
{
Make_Edge_Lk(tree->t_edges[i],tree);
Make_Edge_NNI(tree->t_edges[i]);
}
For(i,2*tree->n_otu-2) Make_Node_Lk(tree->t_nodes[i]);
if(tree->mod->s_opt->greedy)
{
Init_P_Lk_Tips_Double(tree);
}
else
{
Init_P_Lk_Tips_Int(tree);
}
Init_P_Lk_Loc(tree);
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void Init_P_Lk_Tips_Double(t_tree *tree)
{
int curr_site,i,j,k,dim1,dim2;
dim1 = tree->mod->n_catg * tree->mod->ns;
dim2 = tree->mod->ns;
For(curr_site,tree->data->crunch_len)
{
For(i,tree->n_otu)
{
if (tree->io->datatype == NT)
Init_Tips_At_One_Site_Nucleotides_Float(tree->data->c_seq[i]->state[curr_site],
curr_site*dim1+0*dim2,
tree->t_nodes[i]->b[0]->p_lk_rght);
else if(tree->io->datatype == AA)
Init_Tips_At_One_Site_AA_Float(tree->data->c_seq[i]->state[curr_site],
curr_site*dim1+0*dim2,
tree->t_nodes[i]->b[0]->p_lk_rght);
else if(tree->io->datatype == GENERIC)
Init_Tips_At_One_Site_Generic_Float(tree->data->c_seq[i]->state+curr_site*tree->mod->state_len,
tree->mod->ns,
tree->mod->state_len,
curr_site*dim1+0*dim2,
tree->t_nodes[i]->b[0]->p_lk_rght);
for(j=1;jmod->n_catg;j++)
{
For(k,tree->mod->ns)
{
tree->t_nodes[i]->b[0]->p_lk_rght[curr_site*dim1+j*dim2+k] =
tree->t_nodes[i]->b[0]->p_lk_rght[curr_site*dim1+0*dim2+k];
}
}
}
}
if(tree->mod->use_m4mod)
{
M4_Init_P_Lk_Tips_Double(tree);
}
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void Init_P_Lk_Tips_Int(t_tree *tree)
{
int curr_site,i,dim1;
dim1 = tree->mod->ns;
For(curr_site,tree->data->crunch_len)
{
For(i,tree->n_otu)
{
if(tree->io->datatype == NT)
Init_Tips_At_One_Site_Nucleotides_Int(tree->data->c_seq[i]->state[curr_site],
curr_site*dim1,
tree->t_nodes[i]->b[0]->p_lk_tip_r);
else if(tree->io->datatype == AA)
Init_Tips_At_One_Site_AA_Int(tree->data->c_seq[i]->state[curr_site],
curr_site*dim1,
tree->t_nodes[i]->b[0]->p_lk_tip_r);
else if(tree->io->datatype == GENERIC)
{
Init_Tips_At_One_Site_Generic_Int(tree->data->c_seq[i]->state+curr_site*tree->mod->state_len,
tree->mod->ns,
tree->mod->state_len,
curr_site*dim1,
tree->t_nodes[i]->b[0]->p_lk_tip_r);
}
}
}
if(tree->mod->use_m4mod)
{
M4_Init_P_Lk_Tips_Int(tree);
}
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void Update_PMat_At_Given_Edge(t_edge *b_fcus, t_tree *tree)
{
int i;
phydbl len;
phydbl l_min, l_max;
l_min = tree->mod->l_min;
l_max = tree->mod->l_max;
if(tree->mod->gamma_mgf_bl == YES)
{
phydbl shape,scale,mean,var;
mean = b_fcus->gamma_prior_mean;
var = b_fcus->gamma_prior_var;
if(mean < l_min) mean = l_min;
if(mean > l_max) mean = l_max;
shape = mean*mean/var;
scale = var/mean;
For(i,tree->mod->n_catg)
{
PMat_MGF_Gamma(b_fcus->Pij_rr+tree->mod->ns*tree->mod->ns*i,
shape,scale,tree->mod->gamma_rr->v[i],tree->mod);
}
}
else
{
len = -1.0;
if(tree->mod->log_l == YES) b_fcus->l = EXP(b_fcus->l);
For(i,tree->mod->n_catg)
{
if(b_fcus->has_zero_br_len == YES)
{
len = -1.0;
}
else
{
len = b_fcus->l*tree->mod->gamma_rr->v[i];
if(len < l_min) len = l_min;
else if(len > l_max) len = l_max;
}
len *= tree->mod->br_len_multiplier->v;
PMat(len,tree->mod,tree->mod->ns*tree->mod->ns*i,b_fcus->Pij_rr);
}
if(tree->mod->log_l == YES) b_fcus->l = LOG(b_fcus->l);
}
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
/* void Update_P_Lk_On_A_Path(t_node *a, t_node *d, t_edge *b, t_node *target_one_side, t_node *target_other_side, t_tree *tree) */
/* { */
/* /\* */
/* \ / */
/* target\___________b_/ */
/* / \ \ \ \ */
/* / \ \ \ \ */
/* target is the root of the subtree at which we want */
/* the likelihood to be updated */
/* *\/ */
/* /\* PhyML_Printf("Update_p_lk on (%d %d) at %d (target=%d %d)\n", *\/ */
/* /\* b->left->num, *\/ */
/* /\* b->rght->num, *\/ */
/* /\* a->num, *\/ */
/* /\* target_one_side->num, *\/ */
/* /\* target_other_side->num); *\/ */
/* Update_P_Lk(tree,b,a); */
/* if((a == target_one_side) && (d == target_other_side)) */
/* return; */
/* else */
/* { */
/* Update_P_Lk_On_A_Path(d, */
/* d->v[tree->t_dir[d->num][target_other_side->num]], */
/* d->b[tree->t_dir[d->num][target_other_side->num]], */
/* target_one_side, */
/* target_other_side, */
/* tree); */
/* } */
/* } */
void Update_P_Lk_Along_A_Path(t_node **path, int path_length, t_tree *tree)
{
int i,j;
For(i,path_length-1)
{
For(j,3)
if(path[i]->v[j] == path[i+1])
{
if(path[i] == path[i]->b[j]->left)
{
Update_P_Lk(tree,path[i]->b[j],path[i]->b[j]->left);
}
else if(path[i] == path[i]->b[j]->rght)
{
Update_P_Lk(tree,path[i]->b[j],path[i]->b[j]->rght);
}
else
{
PhyML_Printf("\n. Err in file %s at line %d\n\n",__FILE__,__LINE__);
Exit("");
}
break;
}
#ifdef DEBUG
if(j == 3)
{
PhyML_Printf("\n. Err in file %s at line %d\n\n",__FILE__,__LINE__);
Exit("");
}
#endif
}
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
phydbl Lk_Dist(phydbl *F, phydbl dist, model *mod)
{
int i,j,k;
phydbl lnL,len;
int dim1,dim2;
if(mod->log_l == YES) dist = EXP(dist);
For(k,mod->n_catg)
{
len = dist*mod->gamma_rr->v[k];
if(len < mod->l_min) len = mod->l_min;
else if(len > mod->l_max) len = mod->l_max;
PMat(len,mod,mod->ns*mod->ns*k,mod->Pij_rr->v);
}
dim1 = mod->ns*mod->ns;
dim2 = mod->ns;
lnL = .0;
/* For(i,mod->ns) */
/* { */
/* For(j,mod->ns) */
/* { */
/* For(k,mod->n_catg) */
/* { */
/* lnL += */
/* F[dim1*k+dim2*i+j] * */
/* LOG(mod->pi[i] * mod->Pij_rr[dim1*k+dim2*i+j]); */
/* } */
/* } */
/* } */
For(i,mod->ns-1)
{
for(j=i+1;jns;j++)
{
For(k,mod->n_catg)
{
lnL +=
(F[dim1*k+dim2*i+j] + F[dim1*k+dim2*j+i])*
LOG(mod->pi->v[i] * mod->Pij_rr->v[dim1*k+dim2*i+j]);
}
}
}
For(i,mod->ns) For(k,mod->n_catg) lnL += F[dim1*k+dim2*i+i]* LOG(mod->pi->v[i] * mod->Pij_rr->v[dim1*k+dim2*i+i]);
return lnL;
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
phydbl Update_Lk_At_Given_Edge(t_edge *b_fcus, t_tree *tree)
{
Update_P_Lk(tree,b_fcus,b_fcus->left);
Update_P_Lk(tree,b_fcus,b_fcus->rght);
tree->c_lnL = Lk_At_Given_Edge(b_fcus,tree);
return tree->c_lnL;
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void Print_Lk_Given_Edge_Recurr(t_node *a, t_node *d, t_edge *b, t_tree *tree)
{
PhyML_Printf("\n___ Edge %3d (left=%3d rght=%3d) lnL=%f",
b->num,
b->left->num,
b->rght->num,
Lk_At_Given_Edge(b,tree));
if(d->tax) return;
else
{
int i;
For(i,3)
if(d->v[i] != a)
Print_Lk_Given_Edge_Recurr(d,d->v[i],d->b[i],tree);
}
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
/* Core of the likelihood calculcation. Assume that the partial likelihoods on both
sides of t_edge *b are up-to-date. Calculate the log-likelihood at one site.
*/
#ifdef USE_OLD_LK
phydbl Lk_Core(t_edge *b, t_tree *tree)
{
phydbl log_site_lk, site_lk, site_lk_cat;
phydbl scale_left, scale_rght;
phydbl sum;
int ambiguity_check,state;
int catg,ns,k,l,site;
int dim1,dim2,dim3;
dim1 = tree->mod->n_catg * tree->mod->ns;
dim2 = tree->mod->ns;
dim3 = tree->mod->ns * tree->mod->ns;
log_site_lk = .0;
site_lk = .0;
site_lk_cat = .0;
ambiguity_check = -1;
state = -1;
site = tree->curr_site;
ns = tree->mod->ns;
tree->old_site_lk[site] = tree->cur_site_lk[site];
/* Get the vectors of partial likelihood scaling */
scale_left =
(b->sum_scale_left)?
(b->sum_scale_left[site]):
(0.0);
scale_rght =
(b->sum_scale_rght)?
(b->sum_scale_rght[site]):
(0.0);
if((b->rght->tax) && (!tree->mod->s_opt->greedy))
{
ambiguity_check = tree->data->c_seq[b->rght->num]->is_ambigu[site];
if(!ambiguity_check) state = Get_State_From_P_Pars(b->p_lk_tip_r,site*dim2,tree);
}
if(tree->mod->use_m4mod) ambiguity_check = 1;
/* For all classes of rates */
For(catg,tree->mod->n_catg)
{
site_lk_cat = .0;
/* b is an external edge */
if((b->rght->tax) && (!tree->mod->s_opt->greedy))
{
/* If the character observed at the tip is NOT ambiguous: ns x 1 terms to consider */
if(!ambiguity_check)
{
sum = .0;
For(l,ns)
{
sum +=
b->Pij_rr[catg*dim3+state*dim2+l] *
(phydbl)b->p_lk_left[site*dim1+catg*dim2+l];
}
site_lk_cat += sum * tree->mod->pi->v[state];
}
/* If the character observed at the tip is ambiguous: ns x ns terms to consider */
else
{
For(k,ns)
{
sum = .0;
if(b->p_lk_tip_r[site*dim2+k] > .0)
{
For(l,ns)
{
sum +=
b->Pij_rr[catg*dim3+k*dim2+l] *
(phydbl)b->p_lk_left[site*dim1+catg*dim2+l];
}
site_lk_cat +=
sum *
tree->mod->pi->v[k] *
(phydbl)b->p_lk_tip_r[site*dim2+k];
}
}
}
}
/* b is an internal edge: ns x ns terms to consider */
else
{
For(k,ns)
{
sum = .0;
if(b->p_lk_rght[site*dim1+catg*dim2+k] > .0)
{
For(l,ns)
{
sum +=
b->Pij_rr[catg*dim3+k*dim2+l] *
(phydbl)b->p_lk_left[site*dim1+catg*dim2+l];
}
site_lk_cat +=
sum *
tree->mod->pi->v[k] *
(phydbl)b->p_lk_rght[site*dim1+catg*dim2+k];
}
}
}
tree->log_site_lk_cat[catg][site] = site_lk_cat;
site_lk += site_lk_cat * tree->mod->gamma_r_proba->v[catg];
}
/* site_lk may be too small ? */
if(site_lk < 1.E-300) site_lk = 1.E-300;
/* The substitution model does not consider invariable sites */
if(!tree->mod->invar)
{
log_site_lk = (phydbl)LOG(site_lk) + (phydbl)scale_left + (phydbl)scale_rght;
}
else
{
/* The site is invariant */
if((phydbl)tree->data->invar[site] > -0.5)
{
if((scale_left + scale_rght > 0.0) || (scale_left + scale_rght < 0.0))
site_lk *= (phydbl)EXP(scale_left + scale_rght);
log_site_lk =
(phydbl)LOG(site_lk*(1.0-tree->mod->pinvar->v) + tree->mod->pinvar->v*tree->mod->pi->v[tree->data->invar[site]]);
/* LOG(P(D)) = LOG(P(D | subst. rate > 0) * P(subst. rate > 0) + P(D | subst. rate = 0) * P(subst. rate = 0)) */
}
else
{
log_site_lk = (phydbl)LOG(site_lk*(1.0-tree->mod->pinvar->v)) + (phydbl)scale_left + (phydbl)scale_rght;
/* Same formula as above with P(D | subs, rate = 0) = 0 */
}
}
if(log_site_lk < -BIG) Warn_And_Exit("\nlog_site_lk < -BIG\n");
For(catg,tree->mod->n_catg)
tree->log_site_lk_cat[catg][site] =
LOG(tree->log_site_lk_cat[catg][site]) +
scale_left +
scale_rght;
tree->cur_site_lk[site] = log_site_lk;
/* Multiply log likelihood by the number of times this site pattern is found oin the data */
tree->c_lnL_sorted[site] = tree->data->wght[site]*log_site_lk;
tree->c_lnL += tree->c_lnL_sorted[site];
return log_site_lk;
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
/* Update partial likelihood on edge b on the side of b where
node d lies.
*/
void Update_P_Lk(t_tree *tree, t_edge *b, t_node *d)
{
/*
|
|<- b
|
d
/ \
/ \
/ \
n_v1 n_v2
*/
t_node *n_v1, *n_v2;
phydbl p1_lk1,p2_lk2;
phydbl *p_lk,*p_lk_v1,*p_lk_v2;
phydbl *Pij1,*Pij2;
phydbl max_p_lk;
phydbl *sum_scale;
phydbl scale_v1, scale_v2;
int i,j;
int catg,site;
int dir1,dir2;
int n_patterns;
int ambiguity_check_v1,ambiguity_check_v2;
int state_v1,state_v2;
int dim1, dim2, dim3;
dim1 = tree->mod->n_catg * tree->mod->ns;
dim2 = tree->mod->ns;
dim3 = tree->mod->ns * tree->mod->ns;
state_v1 = state_v2 = -1;
ambiguity_check_v1 = ambiguity_check_v2 = -1;
scale_v1 = scale_v2 = 0.0;
p1_lk1 = p2_lk2 = .0;
if(d->tax)
{
PhyML_Printf("\n. t_node %d is a leaf...",d->num);
PhyML_Printf("\n. Err in file %s at line %d\n\n",__FILE__,__LINE__);
Warn_And_Exit("\n");
}
n_patterns = tree->n_pattern;
/* TO DO: Might be worth keeping these directions in memory instead of
calculating them every time... */
dir1=dir2=-1;
For(i,3) if(d->b[i] != b) (dir1<0)?(dir1=i):(dir2=i);
if((dir1 == -1) || (dir2 == -1))
{
PhyML_Printf("\n. d = %d",d->num);
PhyML_Printf("\n. d->v[0] = %d, d->v[1] = %d, d->v[2] = %d",d->v[0]->num,d->v[1]->num,d->v[2]->num);
PhyML_Printf("\n. d->b[0] = %d, d->b[1] = %d, d->b[2] = %d",d->b[0]->num,d->b[1]->num,d->b[2]->num);
PhyML_Printf("\n. d->num = %d dir1 = %d dir2 = %d",d->num,dir1,dir2);
PhyML_Printf("\n. Err in file %s at line %d\n\n",__FILE__,__LINE__);
Exit("");
}
n_v1 = d->v[dir1];
n_v2 = d->v[dir2];
/* Get the partial likelihood vectors on edge b and the two pendant
edges (i.e., the two other edges connected to d) */
if(d == b->left)
{
p_lk = b->p_lk_left;
sum_scale = b->sum_scale_left;
}
else
{
p_lk = b->p_lk_rght;
sum_scale = b->sum_scale_rght;
}
if(d == d->b[dir1]->left)
{
p_lk_v1 = d->b[dir1]->p_lk_rght;
}
else
{
p_lk_v1 = d->b[dir1]->p_lk_left;
}
if(d == d->b[dir2]->left)
{
p_lk_v2 = d->b[dir2]->p_lk_rght;
}
else
{
p_lk_v2 = d->b[dir2]->p_lk_left;
}
/* Change probability matrices on the two pendant edges */
Pij1 = d->b[dir1]->Pij_rr;
Pij2 = d->b[dir2]->Pij_rr;
/* For every site in the alignment */
For(site,n_patterns)
{
/* Current scaling values at that site */
/* scale_v1 = (sum_scale_v1)?(sum_scale_v1[site]):(0.0); */
/* scale_v2 = (sum_scale_v2)?(sum_scale_v2[site]):(0.0); */
/* sum_scale[site] = scale_v1 + scale_v2; */
max_p_lk = -BIG;
state_v1 = state_v2 = -1;
ambiguity_check_v1 = ambiguity_check_v2 = -1;
if(!tree->mod->s_opt->greedy)
{
/* n_v1 and n_v2 are tip nodes */
if(n_v1->tax)
{
/* Is the state at this tip ambiguous? */
ambiguity_check_v1 = tree->data->c_seq[n_v1->num]->is_ambigu[site];
if(!ambiguity_check_v1) state_v1 = Get_State_From_P_Pars(n_v1->b[0]->p_lk_tip_r,site*dim2,tree);
}
if(n_v2->tax)
{
/* Is the state at this tip ambiguous? */
ambiguity_check_v2 = tree->data->c_seq[n_v2->num]->is_ambigu[site];
if(!ambiguity_check_v2) state_v2 = Get_State_From_P_Pars(n_v2->b[0]->p_lk_tip_r,site*dim2,tree);
}
}
if(tree->mod->use_m4mod)
{
ambiguity_check_v1 = 1;
ambiguity_check_v2 = 1;
}
/* For all the rate classes */
For(catg,tree->mod->n_catg)
{
/* For all the state at node d */
For(i,tree->mod->ns)
{
p1_lk1 = .0;
/* n_v1 is a tip */
if((n_v1->tax) && (!tree->mod->s_opt->greedy))
{
if(!ambiguity_check_v1)
{
/* For the (non-ambiguous) state at node n_v1 */
p1_lk1 = Pij1[catg*dim3+i*dim2+state_v1];
}
else
{
/* For all the states at node n_v1 */
For(j,tree->mod->ns)
{
p1_lk1 += Pij1[catg*dim3+i*dim2+j] * (phydbl)n_v1->b[0]->p_lk_tip_r[site*dim2+j];
}
}
}
/* n_v1 is an internal node */
else
{
/* For the states at node n_v1 */
For(j,tree->mod->ns)
{
p1_lk1 += Pij1[catg*dim3+i*dim2+j] * (phydbl)p_lk_v1[site*dim1+catg*dim2+j];
}
}
p2_lk2 = .0;
/* We do exactly the same as for node n_v1 but for node n_v2 this time.*/
/* n_v2 is a tip */
if((n_v2->tax) && (!tree->mod->s_opt->greedy))
{
if(!ambiguity_check_v2)
{
/* For the (non-ambiguous) state at node n_v2 */
p2_lk2 = Pij2[catg*dim3+i*dim2+state_v2];
}
else
{
/* For all the states at node n_v2 */
For(j,tree->mod->ns)
{
p2_lk2 += Pij2[catg*dim3+i*dim2+j] * (phydbl)n_v2->b[0]->p_lk_tip_r[site*dim2+j];
}
}
}
/* n_v2 is an internal node */
else
{
/* For all the states at node n_v2 */
For(j,tree->mod->ns)
{
p2_lk2 += Pij2[catg*dim3+i*dim2+j] * (phydbl)p_lk_v2[site*dim1+catg*dim2+j];
}
}
p_lk[site*dim1+catg*dim2+i] = (phydbl)(p1_lk1 * p2_lk2);
/* Work out the maximum value of the partial likelihoods at node d */
if(p_lk[site*dim1+catg*dim2+i] > max_p_lk) max_p_lk = p_lk[site*dim1+catg*dim2+i];
}
}
/* Scaling */
if((max_p_lk < LIM_SCALE_VAL) || (max_p_lk > (1./LIM_SCALE_VAL)))
{
/* For each rate class */
For(catg,tree->mod->n_catg)
{
/* For each state at node d */
For(i,tree->mod->ns)
{
/* Divide the corresponding partial likelihood by the maximum
value of the partial likelihoods calculated over all rate
classes and states. */
p_lk[site*dim1+catg*dim2+i] /= max_p_lk;
/* if((p_lk[site][catg][i] > BIG) || (p_lk[site][catg][i] < SMALL)) */
/* { */
/* PhyML_Printf("\n. Err in file %s at line %d\n\n",__FILE__,__LINE__); */
/* PhyML_Printf("\n. p_lk[%3d][%2d][%3d] = %G max_p_lk = %G",site,catg,i,p_lk[site][catg][i],max_p_lk); */
/* PhyML_Printf("\n. alpha=%f pinv=%f",tree->mod->alpha->v,tree->mod->pinvar->v); */
/* For(i,tree->mod->n_catg) PhyML_Printf("\n. rr[%2d] = %G",i,tree->mod->rr[i]); */
/* PhyML_Printf("\n. d->b[dir1]->l = %f, d->b[dir2]->l = %f",d->b[dir1]->l,d->b[dir2]->l); */
/* PhyML_Printf("\n. d->v[dir1]->num = %d, d->v[dir2]->num = %d",d->v[dir1]->num,d->v[dir2]->num); */
/* if(d->v[dir1]->tax) */
/* { */
/* PhyML_Printf("\n. Character observed at d->v[dir1] = %d",state_v1); */
/* } */
/* if(d->v[dir2]->tax) */
/* { */
/* PhyML_Printf("\n. Character observed at d->v[dir2] = %d",state_v2); */
/* } */
/* Warn_And_Exit("\n. Numerical precision problem ! (send me an e-mail : s.guindon@auckland.ac.nz)\n"); */
/* } */
}
}
sum_scale[site] += (phydbl)LOG(max_p_lk);
}
}
}
#endif
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void Alias_Subpatt(t_tree *tree)
{
if(tree->n_root)
{
Alias_Subpatt_Post(tree->n_root,tree->n_root->v[0],tree);
Alias_Subpatt_Post(tree->n_root,tree->n_root->v[1],tree);
}
else
{
Alias_Subpatt_Post(tree->t_nodes[0],tree->t_nodes[0]->v[0],tree);
/* if(tree->both_sides) */
Alias_Subpatt_Pre(tree->t_nodes[0],tree->t_nodes[0]->v[0],tree);
}
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void Alias_One_Subpatt(t_node *a, t_node *d, t_tree *tree)
{
int i,j;
int *patt_id_v1, *patt_id_v2, *patt_id_d;
int *p_lk_loc_d, *p_lk_loc_v1, *p_lk_loc_v2;
t_node *v1, *v2;
t_edge *b0, *b1, *b2;
int curr_patt_id_v1, curr_patt_id_v2;
int curr_p_lk_loc_v1, curr_p_lk_loc_v2;
int num_subpatt;
b0 = b1 = b2 = NULL;
if(d->tax)
{
patt_id_d = (d == d->b[0]->left)?(d->b[0]->patt_id_left):(d->b[0]->patt_id_rght);
p_lk_loc_d = (d == d->b[0]->left)?(d->b[0]->p_lk_loc_left):(d->b[0]->p_lk_loc_rght);
For(i,tree->n_pattern)
{
For(j,tree->n_pattern)
{
if(patt_id_d[i] == patt_id_d[j])
{
p_lk_loc_d[i] = j;
break;
}
if(j > i)
{
PhyML_Printf("\n. Err in file %s at line %d\n\n",__FILE__,__LINE__);
Warn_And_Exit("");
}
}
}
return;
}
else
{
v1 = v2 = NULL;
For(i,3)
{
if(d->v[i] != a && d->b[i] != tree->e_root)
{
if(!v1) { v1=d->v[i]; b1=d->b[i];}
else { v2=d->v[i]; b2=d->b[i];}
}
else
{
b0 = d->b[i];
}
}
patt_id_v1 = (v1 == b1->left)?(b1->patt_id_left):(b1->patt_id_rght);
patt_id_v2 = (v2 == b2->left)?(b2->patt_id_left):(b2->patt_id_rght);
patt_id_d = (d == b0->left)?(b0->patt_id_left):(b0->patt_id_rght);
p_lk_loc_d = (d == b0->left)?(b0->p_lk_loc_left):(b0->p_lk_loc_rght);
p_lk_loc_v1 = (v1 == b1->left)?(b1->p_lk_loc_left):(b1->p_lk_loc_rght);
p_lk_loc_v2 = (v2 == b2->left)?(b2->p_lk_loc_left):(b2->p_lk_loc_rght);
num_subpatt = 0;
For(i,tree->n_pattern)
{
curr_patt_id_v1 = patt_id_v1[i];
curr_patt_id_v2 = patt_id_v2[i];
curr_p_lk_loc_v1 = p_lk_loc_v1[i];
curr_p_lk_loc_v2 = p_lk_loc_v2[i];
p_lk_loc_d[i] = i;
if((curr_p_lk_loc_v1 == i) || (curr_p_lk_loc_v2 == i))
{
p_lk_loc_d[i] = i;
patt_id_d[i] = num_subpatt;
num_subpatt++;
}
else
if(curr_p_lk_loc_v1 == curr_p_lk_loc_v2)
{
p_lk_loc_d[i] = curr_p_lk_loc_v1;
patt_id_d[i] = patt_id_d[curr_p_lk_loc_v1];
}
else
{
for(j=MAX(curr_p_lk_loc_v1,curr_p_lk_loc_v2);jn_pattern;j++)
{
if((patt_id_v1[j] == curr_patt_id_v1) &&
(patt_id_v2[j] == curr_patt_id_v2))
{
p_lk_loc_d[i] = j;
if(j == i)
{
patt_id_d[i] = num_subpatt;
num_subpatt++;
}
else patt_id_d[i] = patt_id_d[j];
break;
}
if(j > i)
{
PhyML_Printf("\n. Err in file %s at line %d\n\n",__FILE__,__LINE__);
Warn_And_Exit("");
}
}
}
}
}
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void Alias_Subpatt_Post(t_node *a, t_node *d, t_tree *tree)
{
if(d->tax) return;
else
{
int i;
For(i,3)
{
if(d->v[i] != a && d->b[i] != tree->e_root)
{
Alias_Subpatt_Post(d,d->v[i],tree);
}
}
Alias_One_Subpatt(a, d, tree);
}
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void Alias_Subpatt_Pre(t_node *a, t_node *d, t_tree *tree)
{
if(d->tax) return;
else
{
int i;
For(i,3)
{
if(d->v[i] != a && d->b[i] != tree->e_root)
{
Alias_One_Subpatt(d->v[i],d,tree);
Alias_Subpatt_Pre(d,d->v[i],tree);
}
}
}
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void Copy_P_Lk(phydbl *p_lk, int site_from, int site_to, t_tree *tree)
{
int i,j;
int dim1,dim2;
dim1 = tree->mod->n_catg * tree->mod->ns;
dim2 = tree->mod->ns;
/* PhyML_Printf("\n# %d %d",site_to,site_from); */
For(i,tree->mod->ns) For(j,tree->mod->n_catg)
{
p_lk[site_to*dim1+j*dim2+i] = p_lk[site_from*dim1+j*dim2+i];
}
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void Copy_Scale(int *scale, int site_from, int site_to, t_tree *tree)
{
int i;
For(i,tree->mod->n_catg)
{
scale[i*tree->n_pattern+site_to] = scale[i*tree->n_pattern+site_from];
/* PhyML_Printf("\n. %d",scale[i*tree->n_pattern+site_to]); */
}
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void Init_P_Lk_Loc(t_tree *tree)
{
int i,j;
t_node *d;
int *patt_id_d;
For(i,2*tree->n_otu-3)
{
For(j,tree->n_pattern)
{
tree->t_edges[i]->p_lk_loc_left[j] = j;
tree->t_edges[i]->p_lk_loc_rght[j] = j;
}
}
For(i,tree->n_otu)
{
d = tree->t_nodes[i];
patt_id_d = (d == d->b[0]->left)?(d->b[0]->patt_id_left):(d->b[0]->patt_id_rght);
For(j,tree->n_pattern)
{
patt_id_d[j] = (int)tree->data->c_seq[d->num]->state[j];
}
}
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
phydbl Lk_Normal_Approx(t_tree *tree)
{
phydbl lnL;
int i;
int dim;
phydbl first_order;
dim = 2*tree->n_otu-3;
lnL = Dnorm_Multi_Given_InvCov_Det(tree->rates->u_cur_l,
tree->rates->mean_l,
tree->rates->invcov,
tree->rates->covdet,
2*tree->n_otu-3,YES);
first_order = 0.0;
For(i,dim) first_order += (tree->rates->u_cur_l[i] - tree->rates->mean_l[i]) * tree->rates->grad_l[i];
lnL += first_order;
/* printf("\n"); */
/* For(i,dim) printf("%f\t",tree->rates->u_cur_l[i]); */
/* printf("\n. Lk=%f %f",lnL,tree->mod->l_min); */
/* err = NO; */
/* dim = 2*tree->n_otu-3; */
/* For(i,dim) */
/* { */
/* if((tree->rates->mean_l[i] / tree->mod->l_min < 1.1) && */
/* (tree->rates->mean_l[i] / tree->mod->l_min > 0.9)) */
/* { */
/* lnL -= Log_Dnorm(tree->t_edges[i]->l,tree->rates->mean_l[i],SQRT(tree->rates->cov_l[i*dim+i]),&err); */
/* if(err) */
/* { */
/* PhyML_Printf("\n. Err in file %s at line %d\n\n",__FILE__,__LINE__); */
/* Warn_And_Exit(""); */
/* } */
/* lambda = 1./SQRT(tree->rates->cov_l[i*dim+i]); */
/* l = (tree->mod->log_l == YES)?(EXP(tree->t_edges[i]->l)):(tree->t_edges[i]->l); */
/* lnL += LOG(Dexp(l,lambda)); */
/* /\* printf("\n. lambda = %f",lambda); *\/ */
/* } */
/* } */
return(lnL);
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
phydbl Wrap_Part_Lk_At_Given_Edge(t_edge *b, t_tree *tree, supert_tree *stree)
{
return PART_Lk_At_Given_Edge(b,stree);;
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
phydbl Wrap_Part_Lk(t_edge *b, t_tree *tree, supert_tree *stree)
{
return PART_Lk(stree);
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
phydbl Wrap_Lk(t_edge *b, t_tree *tree, supert_tree *stree)
{
Lk(tree);
return tree->c_lnL;
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
phydbl Wrap_Geo_Lk(t_edge *b, t_tree *tree, supert_tree *stree)
{
TIPO_Lk(tree);
return tree->geo_lnL;
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
phydbl Wrap_Lk_At_Given_Edge(t_edge *b, t_tree *tree, supert_tree *stree)
{
Lk_At_Given_Edge(b,tree);
return tree->c_lnL;
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
phydbl Wrap_Lk_Rates(t_edge *b, t_tree *tree, supert_tree *stree)
{
RATES_Lk_Rates(tree);
return tree->rates->c_lnL_rates;
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
phydbl Wrap_Lk_Times(t_edge *b, t_tree *tree, supert_tree *stree)
{
TIMES_Lk_Times(tree);
return tree->rates->c_lnL_times;
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
phydbl Wrap_Lk_Linreg(t_edge *b, t_tree *tree, supert_tree *stree)
{
/* RATES_Lk_Linreg(tree); */
return -1.;
/* return tree->rates->c_lnL_linreg; */
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
phydbl Wrap_Diff_Lk_Norm_At_Given_Edge(t_edge *b, t_tree *tree, supert_tree *stree)
{
phydbl diff;
diff = Diff_Lk_Norm_At_Given_Edge(b,tree);
return(-diff);
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void Sample_Ancestral_Seq(int mutmap, int fromprior, t_tree *tree)
{
int rate_cat;
int i,j,k,l;
phydbl *probs;
phydbl sum;
phydbl u;
int n_mut;
FILE *fp;
phydbl *muttime;
int *muttype;
char *s;
int *ordering;
probs = (phydbl *)mCalloc(tree->mod->n_catg,sizeof(phydbl));
muttime = (phydbl *)mCalloc((2*tree->n_otu-3)*5, // At most 5 mutations per branch on average
sizeof(phydbl));
muttype = (int *)mCalloc((2*tree->n_otu-3)*5, // At most 5 mutations per branch on average
sizeof(int));
ordering = (int *)mCalloc((2*tree->n_otu-3)*5, // At most 5 mutations per branch on average
sizeof(int));
s = (char *)mCalloc(T_MAX_NAME,sizeof(char));
if(fromprior == YES)
{
/* Update P(D_x|X=i) for each state i and node X */
tree->both_sides = YES;
Lk(tree);
}
For(i,tree->n_pattern)
{
/* Sample the rate class from its posterior density */
For(j,tree->mod->n_catg)
{
if(fromprior == NO)
probs[j] =
EXP(tree->log_site_lk_cat[j][i])*
tree->mod->gamma_r_proba->v[j];
else
probs[j] = tree->mod->gamma_r_proba->v[j];
}
/* Scale probas. */
sum = .0;
For(j,tree->mod->n_catg) sum += probs[j];
For(j,tree->mod->n_catg) probs[j]/=sum;
/* CDF */
for(j=1;jmod->n_catg;j++) probs[j] += probs[j-1];
/* Sample rate */
u = Uni();
rate_cat = -1;
For(j,tree->mod->n_catg)
if(probs[j] > u)
{
rate_cat = j;
break;
}
n_mut = 0;
Sample_Ancestral_Seq_Pre(tree->t_nodes[0],tree->t_nodes[0]->v[0],tree->t_nodes[0]->b[0],
i,rate_cat,
muttype,muttime,&n_mut,
mutmap,fromprior,tree);
For(j,n_mut) ordering[j] = 0;
For(j,n_mut-1)
{
for(k=j+1;k muttime[j]) ordering[k]++;
else ordering[j]++;
}
}
strcpy(s,"rosetta.");
sprintf(s+strlen(s),"%d",i);
fp = fopen(s,"a");
PhyML_Fprintf(fp,"\n-1 -1 -1.0 -1");
For(j,n_mut)
{
For(k,n_mut)
{
if(ordering[k] == j)
{
For(l,tree->data->init_len) if(tree->data->sitepatt[l] == i) break;
PhyML_Fprintf(fp,"\n%4d %4d %12f %4d",j,muttype[k],muttime[k],l);
/* PhyML_Fprintf(fp,"\n%d",muttype[ordering[j]]); */
break;
}
}
}
For(j,n_mut)
{
muttype[j] = -2;
muttime[j] = +1.;
}
fclose(fp);
}
Free(s);
Free(muttype);
Free(muttime);
Free(ordering);
Free(probs);
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void Sample_Ancestral_Seq_Pre(t_node *a, t_node *d, t_edge *b,
int site, int rate_cat,
int *muttype, phydbl *muttime, int *n_mut,
int mutmap, int fromprior, t_tree *tree)
{
int i,j;
int sa,sd;
phydbl *Pij;
phydbl *p_lk;
int dim1, dim2, dim3;
phydbl sum;
phydbl u;
char *c;
phydbl *probs;
probs = (phydbl *)mCalloc(tree->mod->ns,sizeof(phydbl));
if(a->tax)
c = tree->data->c_seq[a->num]->state+site*tree->mod->state_len;
else
c = tree->anc_data->c_seq[a->num-tree->n_otu]->state+site*tree->mod->state_len;
sa = Assign_State(c,
tree->mod->io->datatype,
tree->mod->state_len);
if(sa == -1) // c is an indel
{
For(j,tree->mod->ns) probs[j] = tree->mod->pi->v[j];
for(j=1;jmod->ns;j++) probs[j] += probs[j-1];
u = Uni();
For(j,tree->mod->ns)
if(probs[j] > u)
{
sa = j;
break;
}
}
if(d->tax == NO) // Need to sample state at node d
{
dim1 = tree->mod->n_catg * tree->mod->ns;
dim2 = tree->mod->ns;
dim3 = tree->mod->ns * tree->mod->ns;
sum = 0.0;
Pij = b->Pij_rr;
if(d == b->left)
p_lk = b->p_lk_left;
else
p_lk = b->p_lk_rght;
For(j,tree->mod->ns) probs[j] = 0.0;
/* Formula (10) in Nielsen's Mutation Maping paper, e.g. */
For(j,tree->mod->ns)
{
if(fromprior == NO)
probs[j] =
p_lk[site*dim1+rate_cat*dim2+j] *
Pij[rate_cat*dim3+sa*dim2+j];
else
probs[j] = Pij[rate_cat*dim3+sa*dim2+j];
}
/* if(site == 92) */
/* printf("\n. l=%f pr[%f %f %f %f] Pij[%f %f %f %f] plk[%f %f %f %f]", */
/* b->l * tree->mod->gamma_rr->v[rate_cat], */
/* probs[0],probs[1],probs[2],probs[3], */
/* Pij[rate_cat*dim3+sa*dim2+0], */
/* Pij[rate_cat*dim3+sa*dim2+1], */
/* Pij[rate_cat*dim3+sa*dim2+2], */
/* Pij[rate_cat*dim3+sa*dim2+3], */
/* p_lk[site*dim1+rate_cat*dim2+0], */
/* p_lk[site*dim1+rate_cat*dim2+1], */
/* p_lk[site*dim1+rate_cat*dim2+2], */
/* p_lk[site*dim1+rate_cat*dim2+3]); */
/* Scale the probabilities */
sum = 0.0;
For(j,tree->mod->ns) sum += probs[j];
For(j,tree->mod->ns) probs[j] /= sum;
/* CDF */
for(j=1;jmod->ns;j++) probs[j] += probs[j-1];
/* Sample state according to their posterior probas. */
sd = -1;
u = Uni();
For(j,tree->mod->ns)
if(probs[j] > u)
{
sd = j;
break;
}
/* Assign state */
tree->anc_data->c_seq[d->num-tree->n_otu]->state[site] = Reciproc_Assign_State(sd,tree->io->datatype);
}
else
{
c = tree->data->c_seq[d->num]->state+site*tree->mod->state_len;
sd = Assign_State(c,
tree->mod->io->datatype,
tree->mod->state_len);
if(sd == -1) // c is an indel
{
For(j,tree->mod->ns) probs[j] = tree->mod->pi->v[j];
for(j=1;jmod->ns;j++) probs[j] += probs[j-1];
u = Uni();
For(j,tree->mod->ns)
if(probs[j] > u)
{
sd = j;
break;
}
}
}
/* if(site == 92) */
/* { */
/* printf("\n. sa=%d (%s,%d) sd=%d (%s,%d) b->l=%f", */
/* sa,a->tax?a->name:"",a->num,sd,d->tax?d->name:"",d->num,b->l); */
/* } */
if(mutmap == YES) Map_Mutations(a,d,sa,sd,b,site,rate_cat,muttype,muttime,n_mut,tree);
Free(probs);
if(d->tax) return;
else
{
For(i,3)
{
if(d->v[i] != a)
{
Sample_Ancestral_Seq_Pre(d,d->v[i],d->b[i],site,rate_cat,muttype,muttime,n_mut,mutmap,fromprior,tree);
}
}
}
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void Map_Mutations(t_node *a, t_node *d, int sa, int sd, t_edge *b, int site, int rate_cat, int *muttype, phydbl *muttime, int *n_mut, t_tree *tree)
{
int i,j;
phydbl *probs,*all_probs;
int slast; // Last state visited
phydbl tlast, td;
phydbl *Q;
phydbl u,sum;
int *mut; // Array of mutations
int thismut;
int n_mut_branch;
phydbl br,cr,ta,gr;
int n_iter;
int first_mut;
all_probs = (phydbl *)mCalloc(tree->mod->ns*tree->mod->ns,sizeof(phydbl));
mut = (int *)mCalloc(tree->mod->ns*tree->mod->ns,sizeof(int));
// Edge rate
br =
(tree->rates->model_log_rates == YES)?
EXP(tree->rates->br_r[d->num]):
tree->rates->br_r[d->num];
// Clock (i.e., overall) rate
cr = tree->rates->clock_r;
// Age of node a
ta = tree->rates->nd_t[a->num];
// Site relative rate
gr = tree->mod->gamma_rr->v[rate_cat];
// Rate matrix
Q = tree->mod->qmat->v;
// Length of the 'time' interval considered: product of the branch length by the
// current relative rate at that site (set when sampling ancestral sequences)
td = b->l * gr;
// Matrix of change probabilities
For(i,tree->mod->ns)
{
// We only care about the non-diagonal elements here
For(j,tree->mod->ns) all_probs[i*tree->mod->ns+j] = -Q[i*tree->mod->ns+j] / Q[i*tree->mod->ns+i];
// Set the diagonal to 0
all_probs[i*tree->mod->ns+i] = 0.0;
// \sum_{j != i} -q_{ij}/q_{ii}
sum = 0;
For(j,tree->mod->ns) sum += all_probs[i*tree->mod->ns+j];
// Diagonal: 1 - \sum_{j != i} -q_{ij}/q_{ii}
all_probs[i*tree->mod->ns+i] = 1.-sum;
// Get the cumulative probas
for(j=1;jmod->ns;j++) all_probs[i*tree->mod->ns+j] += all_probs[i*tree->mod->ns+j-1];
}
For(i,tree->mod->ns*tree->mod->ns) mut[i] = 0;
tlast = .0;
slast = sa;
probs = NULL;
n_mut_branch = 0;
n_iter = 0;
first_mut = YES;
do
{
if((sa != sd) && (first_mut == YES)) // ancestral and descendant states are distinct
{
// Sample a time for the first mutation conditional on at least one mutation
// occurring (see formula A2 in Nielsen's Genetics paper (2001))
u = Uni();
tlast = -LOG(1. - u*(1.-EXP(Q[sa*tree->mod->ns+sa]*td)))/-Q[sa*tree->mod->ns+sa];
}
else
{
// Sample a time for the next mutation
tlast = tlast + Rexp(-Q[slast*tree->mod->ns+slast]);
}
// Select the appropriate vector of change probabilities
probs = all_probs+slast*tree->mod->ns;
/* printf("\n. slast=%2d sd=%2d tlast=%12G td=%12G p=%12f rcat=%12f site=%4d", */
/* slast,sd,tlast,td,-Q[slast*tree->mod->ns+slast], */
/* tree->mod->gamma_rr->v[rate_cat],site); */
// The time for the next mutation does not exceed the length
// of the time interval -> sample a new mutation event
if(tlast < td)
{
first_mut = NO;
n_mut_branch++;
u = Uni();
For(i,tree->mod->ns)
if(probs[i] > u)
{
// Record mutation type
mut[slast*tree->mod->ns+i]++;
// Record mutation type in the site mutation array
thismut = MIN(i,slast) * tree->mod->ns + MAX(i,slast) - (MIN(i,slast)+1+(int)POW(MIN(i,slast)+1,2))/2;
muttype[(*n_mut)+n_mut_branch-1] = thismut;
if((thismut > 5) || (thismut < 0))
{
PhyML_Printf("\n. thismut = %d",thismut);
PhyML_Printf("\n. Err in file %s at line %d\n\n",__FILE__,__LINE__);
Warn_And_Exit("");
}
// Record time of mutation
muttime[(*n_mut)+n_mut_branch-1] = ta + br*cr*gr;
// Update the last state
slast = i;
break;
}
}
else
{
if(slast == sd) break;
else
{
// Restart from the beginning
For(i,tree->mod->ns*tree->mod->ns) mut[i] = 0;
For(i,n_mut_branch) muttype[(*n_mut)+n_mut_branch-1] = -2;
For(i,n_mut_branch) muttime[(*n_mut)+n_mut_branch-1] = +1.;
tlast = 0.0;
slast = sa;
n_mut_branch = 0;
first_mut = YES;
n_iter++;
}
}
}
while(1);
(*n_mut) += n_mut_branch;
For(i,tree->mod->ns)
{
for(j=i+1;jmod->ns;j++)
{
if(mut[i*tree->mod->ns+j] + mut[j*tree->mod->ns+i] > 0)
{
thismut = MIN(i,j) * tree->mod->ns + MAX(i,j) - (MIN(i,j)+1+(int)POW(MIN(i,j)+1,2))/2;
tree->mutmap[thismut*(tree->n_pattern)*(2*tree->n_otu-3) + b->num*(tree->n_pattern) + site]++;
/* if(site == 92) */
/* { */
/* printf("\nx sa=%d sd=%d mut=%d",sa,sd,thismut); */
/* } */
}
}
}
Free(all_probs);
Free(mut);
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
phydbl Lk_LastFirst(t_tree *tree)
{
phydbl c_lnL;
t_tree *buff;
phydbl sum;
c_lnL = 0.0;
// Normalise the mixture model class proba
buff = tree;
sum = 0.0;
do
{
sum += buff->mod->unscaled_prob;
buff = buff->prevtree;
}while(buff);
buff = tree;
do
{
buff->mod->prob = buff->mod->unscaled_prob/sum;
buff = buff->prevtree;
}while(buff);
// Calculate the likelihood
buff = tree;
do
{
c_lnL += buff->c_lnL_mixt * buff->mod->prob;
/* printf("\n. lk tree %d: %f %f",buff->tree_num,buff->c_lnL_mixt,buff->mod->kappa->v); */
buff = buff->prevtree;
}while(buff);
buff = tree;
do
{
buff->c_lnL = c_lnL; // Overrides the values of c_lnL;
buff = buff->prevtree;
}while(buff);
return(c_lnL);
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
phyml-20120412/src/pars.c 0000644 0001750 0001750 00000101664 11644731655 011745 0000000 0000000 /*
PHYML : a program that computes maximum likelihood phyLOGenies from
DNA or AA homoLOGous sequences
Copyright (C) Stephane Guindon. Oct 2003 onward
All parts of the source except where indicated are distributed under
the GNU public licence. See http://www.opensource.org for details.
*/
#include "pars.h"
/*********************************************************/
void Make_Tree_4_Pars(t_tree *tree, calign *cdata, int n_site)
{
int i;
tree->site_pars = (int *)mCalloc(tree->n_pattern, sizeof(int));
tree->step_mat = (int *)mCalloc(tree->mod->ns * tree->mod->ns, sizeof(int));
For(i,2*tree->n_otu-3) Make_Edge_Pars(tree->t_edges[i],tree);
Init_Ui_Tips(tree);
Init_P_Pars_Tips(tree); /* Must be called after Init_Ui_Tips is called */
Get_Step_Mat(tree);
}
/*********************************************************/
int Pars(t_tree *tree)
{
int site,n_patterns;
n_patterns = tree->n_pattern;
Post_Order_Pars(tree->t_nodes[0],tree->t_nodes[0]->v[0],tree);
if(tree->both_sides) Pre_Order_Pars(tree->t_nodes[0],tree->t_nodes[0]->v[0],tree);
tree->c_pars = 0;
For(site,n_patterns)
{
tree->site_pars[site] = 0;
tree->curr_site = site;
Site_Pars(tree);
tree->c_pars += tree->site_pars[site] * tree->data->wght[site];
}
return tree->c_pars;
}
/*********************************************************/
void Post_Order_Pars(t_node *a, t_node *d, t_tree *tree)
{
int i,dir;
dir = -1;
if(d->tax) return;
else
{
For(i,3)
{
if(d->v[i] != a)
Post_Order_Pars(d,d->v[i],tree);
else dir = i;
}
Get_All_Partial_Pars(tree,d->b[dir],a,d);
}
}
/*********************************************************/
void Pre_Order_Pars(t_node *a, t_node *d, t_tree *tree)
{
int i;
if(d->tax) return;
else
{
For(i,3)
{
if(d->v[i] != a)
{
Get_All_Partial_Pars(tree,d->b[i],d->v[i],d);
Pre_Order_Pars(d,d->v[i],tree);
}
}
}
}
/*********************************************************/
void Get_All_Partial_Pars(t_tree *tree, t_edge *b_fcus, t_node *a, t_node *d)
{
Update_P_Pars(tree,b_fcus,d);
}
/*********************************************************/
void Site_Pars(t_tree *tree)
{
tree->site_pars[tree->curr_site] = Pars_Core(tree->t_nodes[0]->b[0],tree);
}
/*********************************************************/
void Init_P_Pars_Tips(t_tree *tree)
{
int curr_site,i,j;
short int *state_v;
int dim1;
dim1 = tree->mod->ns;
state_v = (short int *)mCalloc(tree->mod->ns,sizeof(short int));
For(curr_site,tree->data->crunch_len)
{
For(i,tree->n_otu)
{
if(tree->t_nodes[i]->b[0]->rght->tax != 1)
{
PhyML_Printf("\n. Err in file %s at line %d\n",__FILE__,__LINE__);
Warn_And_Exit("\n");
}
if(tree->io->datatype == NT)
{
Init_Tips_At_One_Site_Nucleotides_Int(tree->data->c_seq[i]->state[curr_site],
0,
state_v);
For(j,tree->mod->ns) tree->t_nodes[i]->b[0]->p_pars_r[curr_site*dim1+j] = MAX_PARS;
For(j,tree->mod->ns) if(state_v[j] > 0.5) tree->t_nodes[i]->b[0]->p_pars_r[curr_site*dim1+j] = 0;
}
else if(tree->io->datatype == AA)
{
Init_Tips_At_One_Site_AA_Int(tree->data->c_seq[i]->state[curr_site],
0,
state_v);
For(j,tree->mod->ns) tree->t_nodes[i]->b[0]->p_pars_r[curr_site*dim1+j] = MAX_PARS;
For(j,tree->mod->ns) if(state_v[j] > 0.5) tree->t_nodes[i]->b[0]->p_pars_r[curr_site*dim1+j] = 0;
}
else if(tree->io->datatype == GENERIC)
{
Init_Tips_At_One_Site_Generic_Int(tree->data->c_seq[i]->state+curr_site*tree->mod->state_len,
tree->mod->ns,
tree->mod->state_len,
0,
state_v);
For(j,tree->mod->ns) tree->t_nodes[i]->b[0]->p_pars_r[curr_site*dim1+j] = MAX_PARS;
For(j,tree->mod->ns) if(state_v[j] > 0.5) tree->t_nodes[i]->b[0]->p_pars_r[curr_site*dim1+j] = 0;
}
}
}
Free(state_v);
}
/*********************************************************/
void Init_Ui_Tips(t_tree *tree)
{
int curr_site,i,j,br;
short int *state_v;
state_v = (short int *)mCalloc(tree->mod->ns,sizeof(short int));
For(curr_site,tree->data->crunch_len)
{
For(i,tree->n_otu)
{
if(tree->io->datatype == NT)
{
if(tree->t_nodes[i]->b[0]->rght->tax != 1)
{
PhyML_Printf("\n. Err in file %s at line %d\n",__FILE__,__LINE__);
Warn_And_Exit("\n");
}
Init_Tips_At_One_Site_Nucleotides_Int(tree->data->c_seq[i]->state[curr_site],
0,
state_v);
tree->t_nodes[i]->b[0]->ui_r[curr_site] = 0;
For(j,tree->mod->ns) tree->t_nodes[i]->b[0]->ui_r[curr_site] += (unsigned int)(state_v[j] * POW(2,j));
}
else if(tree->io->datatype == AA)
{
Init_Tips_At_One_Site_AA_Int(tree->data->c_seq[i]->state[curr_site],
0,
state_v);
tree->t_nodes[i]->b[0]->ui_r[curr_site] = 0;
For(j,tree->mod->ns) tree->t_nodes[i]->b[0]->ui_r[curr_site] += (unsigned int)(state_v[j] * POW(2,j));
}
else if(tree->io->datatype == GENERIC)
{
Init_Tips_At_One_Site_Generic_Int(tree->data->c_seq[i]->state+curr_site*tree->mod->state_len,
tree->mod->ns,
tree->mod->state_len,
0,
state_v);
tree->t_nodes[i]->b[0]->ui_r[curr_site] = 0;
For(j,tree->mod->ns) tree->t_nodes[i]->b[0]->ui_r[curr_site] += (unsigned int)(state_v[j] * POW(2,j));
}
}
}
For(br,2*tree->n_otu-3)
{
For(curr_site,tree->data->crunch_len)
{
tree->t_edges[br]->pars_r[curr_site] = 0;
tree->t_edges[br]->pars_l[curr_site] = 0;
}
}
Free(state_v);
}
/*********************************************************/
void Update_P_Pars(t_tree *tree, t_edge *b_fcus, t_node *n)
{
/*
|
|<- b_cus
|
n
/ \
/ \
/ \
*/
int i,j;
int site;
unsigned int *ui, *ui_v1, *ui_v2;
int *p_pars_v1, *p_pars_v2, *p_pars;
int *pars, *pars_v1, *pars_v2;
int n_patterns,matches;
int min_v1,min_v2;
int v;
int dim1;
if((tree->io->do_alias_subpatt == YES) &&
(tree->update_alias_subpatt == YES))
Alias_One_Subpatt((n==b_fcus->left)?(b_fcus->rght):(b_fcus->left),n,tree);
if(n->tax) return;
dim1 = tree->mod->ns;
matches = 0;
ui = ui_v1 = ui_v2 = NULL;
p_pars = p_pars_v1 = p_pars_v2 = NULL;
pars = pars_v1 = pars_v2 = NULL;
n_patterns = tree->n_pattern;
if(n == b_fcus->left)
{
ui = b_fcus->ui_l;
pars = b_fcus->pars_l;
p_pars = b_fcus->p_pars_l;
ui_v1 =
(n == n->b[b_fcus->l_v1]->left)?
(n->b[b_fcus->l_v1]->ui_r):
(n->b[b_fcus->l_v1]->ui_l);
ui_v2 =
(n == n->b[b_fcus->l_v2]->left)?
(n->b[b_fcus->l_v2]->ui_r):
(n->b[b_fcus->l_v2]->ui_l);
p_pars_v1 =
(n == n->b[b_fcus->l_v1]->left)?
(n->b[b_fcus->l_v1]->p_pars_r):
(n->b[b_fcus->l_v1]->p_pars_l);
p_pars_v2 =
(n == n->b[b_fcus->l_v2]->left)?
(n->b[b_fcus->l_v2]->p_pars_r):
(n->b[b_fcus->l_v2]->p_pars_l);
pars_v1 =
(n == n->b[b_fcus->l_v1]->left)?
(n->b[b_fcus->l_v1]->pars_r):
(n->b[b_fcus->l_v1]->pars_l);
pars_v2 =
(n == n->b[b_fcus->l_v2]->left)?
(n->b[b_fcus->l_v2]->pars_r):
(n->b[b_fcus->l_v2]->pars_l);
}
else
{
ui = b_fcus->ui_r;
pars = b_fcus->pars_r;
p_pars = b_fcus->p_pars_r;
ui_v1 =
(n == n->b[b_fcus->r_v1]->left)?
(n->b[b_fcus->r_v1]->ui_r):
(n->b[b_fcus->r_v1]->ui_l);
ui_v2 =
(n == n->b[b_fcus->r_v2]->left)?
(n->b[b_fcus->r_v2]->ui_r):
(n->b[b_fcus->r_v2]->ui_l);
p_pars_v1 =
(n == n->b[b_fcus->r_v1]->left)?
(n->b[b_fcus->r_v1]->p_pars_r):
(n->b[b_fcus->r_v1]->p_pars_l);
p_pars_v2 =
(n == n->b[b_fcus->r_v2]->left)?
(n->b[b_fcus->r_v2]->p_pars_r):
(n->b[b_fcus->r_v2]->p_pars_l);
pars_v1 =
(n == n->b[b_fcus->r_v1]->left)?
(n->b[b_fcus->r_v1]->pars_r):
(n->b[b_fcus->r_v1]->pars_l);
pars_v2 =
(n == n->b[b_fcus->r_v2]->left)?
(n->b[b_fcus->r_v2]->pars_r):
(n->b[b_fcus->r_v2]->pars_l);
}
if(tree->mod->s_opt->general_pars)
{
For(site,n_patterns)
{
For(i,tree->mod->ns)
{
min_v1 = MAX_PARS;
For(j,tree->mod->ns)
{
v = p_pars_v1[site*dim1+j] + tree->step_mat[i*tree->mod->ns+j];
if(v < min_v1) min_v1 = v;
}
min_v2 = MAX_PARS;
For(j,tree->mod->ns)
{
v = p_pars_v2[site*dim1+j] + tree->step_mat[i*tree->mod->ns+j];
if(v < min_v2) min_v2 = v;
}
p_pars[site*dim1+i] = min_v1 + min_v2;
}
}
}
else
{
For(site,n_patterns)
{
pars[site] = pars_v1[site] + pars_v2[site];
ui[site] = ui_v1[site] & ui_v2[site];
if(!ui[site])
{
pars[site]++;
ui[site] = ui_v1[site] | ui_v2[site];
}
}
}
}
/*********************************************************/
int Pars_Core(t_edge *b, t_tree *tree)
{
int site;
int i,j;
int site_pars;
int min_l,min_r;
int v;
int dim1;
dim1 = tree->mod->ns;
site = tree->curr_site;
site_pars = MAX_PARS;
if(tree->mod->s_opt->general_pars)
{
For(i,tree->mod->ns)
{
min_l = MAX_PARS;
For(j,tree->mod->ns)
{
v = b->p_pars_l[site*dim1+j] + tree->step_mat[i*tree->mod->ns+j];
if(v < min_l) min_l = v;
}
min_r = MAX_PARS;
For(j,tree->mod->ns)
{
v = b->p_pars_r[site*dim1+j] + tree->step_mat[i*tree->mod->ns+j];
if(v < min_r) min_r = v;
}
if((min_l + min_r) < site_pars) site_pars = min_l + min_r;
}
}
else
{
site_pars = b->pars_l[site] + b->pars_r[site];
if(!(b->ui_l[site] & b->ui_r[site])) site_pars++;
}
return site_pars;
}
/*********************************************************/
/* Is there one or more parsimoniy step(s) along this t_edge ?
0 -> NO; 1 -> YES
*/
int One_Pars_Step(t_edge *b,t_tree *tree)
{
int site;
int init_general_pars;
init_general_pars = tree->mod->s_opt->general_pars;
tree->mod->s_opt->general_pars = 0;
tree->both_sides = 1;
Pars(tree);
For(site,tree->n_pattern)
{
if(!(b->ui_l[site] & b->ui_r[site])) break;
}
tree->mod->s_opt->general_pars = init_general_pars;
if(site == tree->n_pattern) return 0;
else
{
PhyML_Printf("\n. One parsimony step ocurred at site %4d",site);
return 1;
}
}
/*********************************************************/
int Pars_At_Given_Edge(t_edge *b, t_tree *tree)
{
int site,n_patterns;
/* n_patterns = (int)FLOOR(tree->n_pattern*tree->prop_of_sites_to_consider); */
n_patterns = tree->n_pattern;
tree->c_pars = .0;
For(site,n_patterns)
{
tree->site_pars[site] = 0;
tree->curr_site = site;
tree->site_pars[site] = Pars_Core(b,tree);
tree->c_pars += tree->site_pars[site] * tree->data->wght[site];
}
return tree->c_pars;
}
/*********************************************************/
int Update_Pars_At_Given_Edge(t_edge *b_fcus, t_tree *tree)
{
Update_P_Pars(tree,b_fcus,b_fcus->left);
Update_P_Pars(tree,b_fcus,b_fcus->rght);
tree->c_pars = Pars_At_Given_Edge(b_fcus,tree);
return tree->c_pars;
}
/*********************************************************/
void Get_Step_Mat(t_tree *tree)
{
int i;
if(tree->io->datatype == AA)
{
tree->step_mat[ 0*tree->mod->ns+ 0] = 0 ;
tree->step_mat[ 0*tree->mod->ns+ 1] = 3 ;
tree->step_mat[ 0*tree->mod->ns+ 2] = 3 ;
tree->step_mat[ 0*tree->mod->ns+ 3] = 2 ;
tree->step_mat[ 0*tree->mod->ns+ 4] = 3 ;
tree->step_mat[ 0*tree->mod->ns+ 5] = 3 ;
tree->step_mat[ 0*tree->mod->ns+ 6] = 2 ;
tree->step_mat[ 0*tree->mod->ns+ 7] = 2 ;
tree->step_mat[ 0*tree->mod->ns+ 8] = 3 ;
tree->step_mat[ 0*tree->mod->ns+ 9] = 3 ;
tree->step_mat[ 0*tree->mod->ns+10] = 3 ;
tree->step_mat[ 0*tree->mod->ns+11] = 3 ;
tree->step_mat[ 0*tree->mod->ns+12] = 3 ;
tree->step_mat[ 0*tree->mod->ns+13] = 3 ;
tree->step_mat[ 0*tree->mod->ns+14] = 2 ;
tree->step_mat[ 0*tree->mod->ns+15] = 2 ;
tree->step_mat[ 0*tree->mod->ns+16] = 2 ;
tree->step_mat[ 0*tree->mod->ns+17] = 3 ;
tree->step_mat[ 0*tree->mod->ns+18] = 3 ;
tree->step_mat[ 0*tree->mod->ns+19] = 2 ;
tree->step_mat[ 1*tree->mod->ns+ 0] = 3 ;
tree->step_mat[ 1*tree->mod->ns+ 1] = 0 ;
tree->step_mat[ 1*tree->mod->ns+ 2] = 2 ;
tree->step_mat[ 1*tree->mod->ns+ 3] = 3 ;
tree->step_mat[ 1*tree->mod->ns+ 4] = 2 ;
tree->step_mat[ 1*tree->mod->ns+ 5] = 2 ;
tree->step_mat[ 1*tree->mod->ns+ 6] = 3 ;
tree->step_mat[ 1*tree->mod->ns+ 7] = 2 ;
tree->step_mat[ 1*tree->mod->ns+ 8] = 2 ;
tree->step_mat[ 1*tree->mod->ns+ 9] = 2 ;
tree->step_mat[ 1*tree->mod->ns+10] = 2 ;
tree->step_mat[ 1*tree->mod->ns+11] = 2 ;
tree->step_mat[ 1*tree->mod->ns+12] = 2 ;
tree->step_mat[ 1*tree->mod->ns+13] = 3 ;
tree->step_mat[ 1*tree->mod->ns+14] = 2 ;
tree->step_mat[ 1*tree->mod->ns+15] = 2 ;
tree->step_mat[ 1*tree->mod->ns+16] = 2 ;
tree->step_mat[ 1*tree->mod->ns+17] = 2 ;
tree->step_mat[ 1*tree->mod->ns+18] = 3 ;
tree->step_mat[ 1*tree->mod->ns+19] = 3 ;
tree->step_mat[ 2*tree->mod->ns+ 0] = 3 ;
tree->step_mat[ 2*tree->mod->ns+ 1] = 2 ;
tree->step_mat[ 2*tree->mod->ns+ 2] = 0 ;
tree->step_mat[ 2*tree->mod->ns+ 3] = 2 ;
tree->step_mat[ 2*tree->mod->ns+ 4] = 2 ;
tree->step_mat[ 2*tree->mod->ns+ 5] = 2 ;
tree->step_mat[ 2*tree->mod->ns+ 6] = 2 ;
tree->step_mat[ 2*tree->mod->ns+ 7] = 3 ;
tree->step_mat[ 2*tree->mod->ns+ 8] = 2 ;
tree->step_mat[ 2*tree->mod->ns+ 9] = 2 ;
tree->step_mat[ 2*tree->mod->ns+10] = 3 ;
tree->step_mat[ 2*tree->mod->ns+11] = 1 ;
tree->step_mat[ 2*tree->mod->ns+12] = 2 ;
tree->step_mat[ 2*tree->mod->ns+13] = 2 ;
tree->step_mat[ 2*tree->mod->ns+14] = 3 ;
tree->step_mat[ 2*tree->mod->ns+15] = 2 ;
tree->step_mat[ 2*tree->mod->ns+16] = 2 ;
tree->step_mat[ 2*tree->mod->ns+17] = 3 ;
tree->step_mat[ 2*tree->mod->ns+18] = 2 ;
tree->step_mat[ 2*tree->mod->ns+19] = 3 ;
tree->step_mat[ 3*tree->mod->ns+ 0] = 2 ;
tree->step_mat[ 3*tree->mod->ns+ 1] = 3 ;
tree->step_mat[ 3*tree->mod->ns+ 2] = 2 ;
tree->step_mat[ 3*tree->mod->ns+ 3] = 0 ;
tree->step_mat[ 3*tree->mod->ns+ 4] = 2 ;
tree->step_mat[ 3*tree->mod->ns+ 5] = 2 ;
tree->step_mat[ 3*tree->mod->ns+ 6] = 1 ;
tree->step_mat[ 3*tree->mod->ns+ 7] = 2 ;
tree->step_mat[ 3*tree->mod->ns+ 8] = 2 ;
tree->step_mat[ 3*tree->mod->ns+ 9] = 3 ;
tree->step_mat[ 3*tree->mod->ns+10] = 3 ;
tree->step_mat[ 3*tree->mod->ns+11] = 2 ;
tree->step_mat[ 3*tree->mod->ns+12] = 3 ;
tree->step_mat[ 3*tree->mod->ns+13] = 2 ;
tree->step_mat[ 3*tree->mod->ns+14] = 3 ;
tree->step_mat[ 3*tree->mod->ns+15] = 3 ;
tree->step_mat[ 3*tree->mod->ns+16] = 3 ;
tree->step_mat[ 3*tree->mod->ns+17] = 3 ;
tree->step_mat[ 3*tree->mod->ns+18] = 2 ;
tree->step_mat[ 3*tree->mod->ns+19] = 2 ;
tree->step_mat[ 4*tree->mod->ns+ 0] = 3 ;
tree->step_mat[ 4*tree->mod->ns+ 1] = 2 ;
tree->step_mat[ 4*tree->mod->ns+ 2] = 2 ;
tree->step_mat[ 4*tree->mod->ns+ 3] = 2 ;
tree->step_mat[ 4*tree->mod->ns+ 4] = 0 ;
tree->step_mat[ 4*tree->mod->ns+ 5] = 3 ;
tree->step_mat[ 4*tree->mod->ns+ 6] = 3 ;
tree->step_mat[ 4*tree->mod->ns+ 7] = 2 ;
tree->step_mat[ 4*tree->mod->ns+ 8] = 2 ;
tree->step_mat[ 4*tree->mod->ns+ 9] = 3 ;
tree->step_mat[ 4*tree->mod->ns+10] = 2 ;
tree->step_mat[ 4*tree->mod->ns+11] = 3 ;
tree->step_mat[ 4*tree->mod->ns+12] = 3 ;
tree->step_mat[ 4*tree->mod->ns+13] = 2 ;
tree->step_mat[ 4*tree->mod->ns+14] = 3 ;
tree->step_mat[ 4*tree->mod->ns+15] = 2 ;
tree->step_mat[ 4*tree->mod->ns+16] = 3 ;
tree->step_mat[ 4*tree->mod->ns+17] = 1 ;
tree->step_mat[ 4*tree->mod->ns+18] = 2 ;
tree->step_mat[ 4*tree->mod->ns+19] = 3 ;
tree->step_mat[ 5*tree->mod->ns+ 0] = 3 ;
tree->step_mat[ 5*tree->mod->ns+ 1] = 2 ;
tree->step_mat[ 5*tree->mod->ns+ 2] = 2 ;
tree->step_mat[ 5*tree->mod->ns+ 3] = 2 ;
tree->step_mat[ 5*tree->mod->ns+ 4] = 3 ;
tree->step_mat[ 5*tree->mod->ns+ 5] = 0 ;
tree->step_mat[ 5*tree->mod->ns+ 6] = 2 ;
tree->step_mat[ 5*tree->mod->ns+ 7] = 3 ;
tree->step_mat[ 5*tree->mod->ns+ 8] = 1 ;
tree->step_mat[ 5*tree->mod->ns+ 9] = 3 ;
tree->step_mat[ 5*tree->mod->ns+10] = 2 ;
tree->step_mat[ 5*tree->mod->ns+11] = 2 ;
tree->step_mat[ 5*tree->mod->ns+12] = 2 ;
tree->step_mat[ 5*tree->mod->ns+13] = 3 ;
tree->step_mat[ 5*tree->mod->ns+14] = 2 ;
tree->step_mat[ 5*tree->mod->ns+15] = 3 ;
tree->step_mat[ 5*tree->mod->ns+16] = 3 ;
tree->step_mat[ 5*tree->mod->ns+17] = 2 ;
tree->step_mat[ 5*tree->mod->ns+18] = 2 ;
tree->step_mat[ 5*tree->mod->ns+19] = 3 ;
tree->step_mat[ 6*tree->mod->ns+ 0] = 2 ;
tree->step_mat[ 6*tree->mod->ns+ 1] = 3 ;
tree->step_mat[ 6*tree->mod->ns+ 2] = 2 ;
tree->step_mat[ 6*tree->mod->ns+ 3] = 1 ;
tree->step_mat[ 6*tree->mod->ns+ 4] = 3 ;
tree->step_mat[ 6*tree->mod->ns+ 5] = 2 ;
tree->step_mat[ 6*tree->mod->ns+ 6] = 0 ;
tree->step_mat[ 6*tree->mod->ns+ 7] = 2 ;
tree->step_mat[ 6*tree->mod->ns+ 8] = 2 ;
tree->step_mat[ 6*tree->mod->ns+ 9] = 3 ;
tree->step_mat[ 6*tree->mod->ns+10] = 3 ;
tree->step_mat[ 6*tree->mod->ns+11] = 2 ;
tree->step_mat[ 6*tree->mod->ns+12] = 2 ;
tree->step_mat[ 6*tree->mod->ns+13] = 3 ;
tree->step_mat[ 6*tree->mod->ns+14] = 3 ;
tree->step_mat[ 6*tree->mod->ns+15] = 3 ;
tree->step_mat[ 6*tree->mod->ns+16] = 3 ;
tree->step_mat[ 6*tree->mod->ns+17] = 2 ;
tree->step_mat[ 6*tree->mod->ns+18] = 2 ;
tree->step_mat[ 6*tree->mod->ns+19] = 2 ;
tree->step_mat[ 7*tree->mod->ns+ 0] = 2 ;
tree->step_mat[ 7*tree->mod->ns+ 1] = 2 ;
tree->step_mat[ 7*tree->mod->ns+ 2] = 3 ;
tree->step_mat[ 7*tree->mod->ns+ 3] = 2 ;
tree->step_mat[ 7*tree->mod->ns+ 4] = 2 ;
tree->step_mat[ 7*tree->mod->ns+ 5] = 3 ;
tree->step_mat[ 7*tree->mod->ns+ 6] = 2 ;
tree->step_mat[ 7*tree->mod->ns+ 7] = 0 ;
tree->step_mat[ 7*tree->mod->ns+ 8] = 3 ;
tree->step_mat[ 7*tree->mod->ns+ 9] = 3 ;
tree->step_mat[ 7*tree->mod->ns+10] = 3 ;
tree->step_mat[ 7*tree->mod->ns+11] = 3 ;
tree->step_mat[ 7*tree->mod->ns+12] = 3 ;
tree->step_mat[ 7*tree->mod->ns+13] = 3 ;
tree->step_mat[ 7*tree->mod->ns+14] = 3 ;
tree->step_mat[ 7*tree->mod->ns+15] = 2 ;
tree->step_mat[ 7*tree->mod->ns+16] = 3 ;
tree->step_mat[ 7*tree->mod->ns+17] = 2 ;
tree->step_mat[ 7*tree->mod->ns+18] = 3 ;
tree->step_mat[ 7*tree->mod->ns+19] = 2 ;
tree->step_mat[ 8*tree->mod->ns+ 0] = 3 ;
tree->step_mat[ 8*tree->mod->ns+ 1] = 2 ;
tree->step_mat[ 8*tree->mod->ns+ 2] = 2 ;
tree->step_mat[ 8*tree->mod->ns+ 3] = 2 ;
tree->step_mat[ 8*tree->mod->ns+ 4] = 2 ;
tree->step_mat[ 8*tree->mod->ns+ 5] = 1 ;
tree->step_mat[ 8*tree->mod->ns+ 6] = 2 ;
tree->step_mat[ 8*tree->mod->ns+ 7] = 3 ;
tree->step_mat[ 8*tree->mod->ns+ 8] = 0 ;
tree->step_mat[ 8*tree->mod->ns+ 9] = 3 ;
tree->step_mat[ 8*tree->mod->ns+10] = 2 ;
tree->step_mat[ 8*tree->mod->ns+11] = 2 ;
tree->step_mat[ 8*tree->mod->ns+12] = 3 ;
tree->step_mat[ 8*tree->mod->ns+13] = 2 ;
tree->step_mat[ 8*tree->mod->ns+14] = 2 ;
tree->step_mat[ 8*tree->mod->ns+15] = 3 ;
tree->step_mat[ 8*tree->mod->ns+16] = 3 ;
tree->step_mat[ 8*tree->mod->ns+17] = 3 ;
tree->step_mat[ 8*tree->mod->ns+18] = 2 ;
tree->step_mat[ 8*tree->mod->ns+19] = 3 ;
tree->step_mat[ 9*tree->mod->ns+ 0] = 3 ;
tree->step_mat[ 9*tree->mod->ns+ 1] = 2 ;
tree->step_mat[ 9*tree->mod->ns+ 2] = 2 ;
tree->step_mat[ 9*tree->mod->ns+ 3] = 3 ;
tree->step_mat[ 9*tree->mod->ns+ 4] = 3 ;
tree->step_mat[ 9*tree->mod->ns+ 5] = 3 ;
tree->step_mat[ 9*tree->mod->ns+ 6] = 3 ;
tree->step_mat[ 9*tree->mod->ns+ 7] = 3 ;
tree->step_mat[ 9*tree->mod->ns+ 8] = 3 ;
tree->step_mat[ 9*tree->mod->ns+ 9] = 0 ;
tree->step_mat[ 9*tree->mod->ns+10] = 2 ;
tree->step_mat[ 9*tree->mod->ns+11] = 2 ;
tree->step_mat[ 9*tree->mod->ns+12] = 1 ;
tree->step_mat[ 9*tree->mod->ns+13] = 2 ;
tree->step_mat[ 9*tree->mod->ns+14] = 3 ;
tree->step_mat[ 9*tree->mod->ns+15] = 2 ;
tree->step_mat[ 9*tree->mod->ns+16] = 2 ;
tree->step_mat[ 9*tree->mod->ns+17] = 3 ;
tree->step_mat[ 9*tree->mod->ns+18] = 3 ;
tree->step_mat[ 9*tree->mod->ns+19] = 2 ;
tree->step_mat[10*tree->mod->ns+ 0] = 3 ;
tree->step_mat[10*tree->mod->ns+ 1] = 2 ;
tree->step_mat[10*tree->mod->ns+ 2] = 3 ;
tree->step_mat[10*tree->mod->ns+ 3] = 3 ;
tree->step_mat[10*tree->mod->ns+ 4] = 2 ;
tree->step_mat[10*tree->mod->ns+ 5] = 2 ;
tree->step_mat[10*tree->mod->ns+ 6] = 3 ;
tree->step_mat[10*tree->mod->ns+ 7] = 3 ;
tree->step_mat[10*tree->mod->ns+ 8] = 2 ;
tree->step_mat[10*tree->mod->ns+ 9] = 2 ;
tree->step_mat[10*tree->mod->ns+10] = 0 ;
tree->step_mat[10*tree->mod->ns+11] = 3 ;
tree->step_mat[10*tree->mod->ns+12] = 2 ;
tree->step_mat[10*tree->mod->ns+13] = 2 ;
tree->step_mat[10*tree->mod->ns+14] = 2 ;
tree->step_mat[10*tree->mod->ns+15] = 3 ;
tree->step_mat[10*tree->mod->ns+16] = 3 ;
tree->step_mat[10*tree->mod->ns+17] = 2 ;
tree->step_mat[10*tree->mod->ns+18] = 2 ;
tree->step_mat[10*tree->mod->ns+19] = 2 ;
tree->step_mat[11*tree->mod->ns+ 0] = 3 ;
tree->step_mat[11*tree->mod->ns+ 1] = 2 ;
tree->step_mat[11*tree->mod->ns+ 2] = 1 ;
tree->step_mat[11*tree->mod->ns+ 3] = 2 ;
tree->step_mat[11*tree->mod->ns+ 4] = 3 ;
tree->step_mat[11*tree->mod->ns+ 5] = 2 ;
tree->step_mat[11*tree->mod->ns+ 6] = 2 ;
tree->step_mat[11*tree->mod->ns+ 7] = 3 ;
tree->step_mat[11*tree->mod->ns+ 8] = 2 ;
tree->step_mat[11*tree->mod->ns+ 9] = 2 ;
tree->step_mat[11*tree->mod->ns+10] = 3 ;
tree->step_mat[11*tree->mod->ns+11] = 0 ;
tree->step_mat[11*tree->mod->ns+12] = 2 ;
tree->step_mat[11*tree->mod->ns+13] = 3 ;
tree->step_mat[11*tree->mod->ns+14] = 3 ;
tree->step_mat[11*tree->mod->ns+15] = 2 ;
tree->step_mat[11*tree->mod->ns+16] = 2 ;
tree->step_mat[11*tree->mod->ns+17] = 2 ;
tree->step_mat[11*tree->mod->ns+18] = 2 ;
tree->step_mat[11*tree->mod->ns+19] = 3 ;
tree->step_mat[12*tree->mod->ns+ 0] = 3 ;
tree->step_mat[12*tree->mod->ns+ 1] = 2 ;
tree->step_mat[12*tree->mod->ns+ 2] = 2 ;
tree->step_mat[12*tree->mod->ns+ 3] = 3 ;
tree->step_mat[12*tree->mod->ns+ 4] = 3 ;
tree->step_mat[12*tree->mod->ns+ 5] = 2 ;
tree->step_mat[12*tree->mod->ns+ 6] = 2 ;
tree->step_mat[12*tree->mod->ns+ 7] = 3 ;
tree->step_mat[12*tree->mod->ns+ 8] = 3 ;
tree->step_mat[12*tree->mod->ns+ 9] = 1 ;
tree->step_mat[12*tree->mod->ns+10] = 2 ;
tree->step_mat[12*tree->mod->ns+11] = 2 ;
tree->step_mat[12*tree->mod->ns+12] = 0 ;
tree->step_mat[12*tree->mod->ns+13] = 2 ;
tree->step_mat[12*tree->mod->ns+14] = 3 ;
tree->step_mat[12*tree->mod->ns+15] = 2 ;
tree->step_mat[12*tree->mod->ns+16] = 2 ;
tree->step_mat[12*tree->mod->ns+17] = 2 ;
tree->step_mat[12*tree->mod->ns+18] = 3 ;
tree->step_mat[12*tree->mod->ns+19] = 2 ;
tree->step_mat[13*tree->mod->ns+ 0] = 3 ;
tree->step_mat[13*tree->mod->ns+ 1] = 3 ;
tree->step_mat[13*tree->mod->ns+ 2] = 2 ;
tree->step_mat[13*tree->mod->ns+ 3] = 2 ;
tree->step_mat[13*tree->mod->ns+ 4] = 2 ;
tree->step_mat[13*tree->mod->ns+ 5] = 3 ;
tree->step_mat[13*tree->mod->ns+ 6] = 3 ;
tree->step_mat[13*tree->mod->ns+ 7] = 3 ;
tree->step_mat[13*tree->mod->ns+ 8] = 2 ;
tree->step_mat[13*tree->mod->ns+ 9] = 2 ;
tree->step_mat[13*tree->mod->ns+10] = 2 ;
tree->step_mat[13*tree->mod->ns+11] = 3 ;
tree->step_mat[13*tree->mod->ns+12] = 2 ;
tree->step_mat[13*tree->mod->ns+13] = 0 ;
tree->step_mat[13*tree->mod->ns+14] = 3 ;
tree->step_mat[13*tree->mod->ns+15] = 2 ;
tree->step_mat[13*tree->mod->ns+16] = 3 ;
tree->step_mat[13*tree->mod->ns+17] = 2 ;
tree->step_mat[13*tree->mod->ns+18] = 2 ;
tree->step_mat[13*tree->mod->ns+19] = 2 ;
tree->step_mat[14*tree->mod->ns+ 0] = 2 ;
tree->step_mat[14*tree->mod->ns+ 1] = 2 ;
tree->step_mat[14*tree->mod->ns+ 2] = 3 ;
tree->step_mat[14*tree->mod->ns+ 3] = 3 ;
tree->step_mat[14*tree->mod->ns+ 4] = 3 ;
tree->step_mat[14*tree->mod->ns+ 5] = 2 ;
tree->step_mat[14*tree->mod->ns+ 6] = 3 ;
tree->step_mat[14*tree->mod->ns+ 7] = 3 ;
tree->step_mat[14*tree->mod->ns+ 8] = 2 ;
tree->step_mat[14*tree->mod->ns+ 9] = 3 ;
tree->step_mat[14*tree->mod->ns+10] = 2 ;
tree->step_mat[14*tree->mod->ns+11] = 3 ;
tree->step_mat[14*tree->mod->ns+12] = 3 ;
tree->step_mat[14*tree->mod->ns+13] = 3 ;
tree->step_mat[14*tree->mod->ns+14] = 0 ;
tree->step_mat[14*tree->mod->ns+15] = 2 ;
tree->step_mat[14*tree->mod->ns+16] = 2 ;
tree->step_mat[14*tree->mod->ns+17] = 3 ;
tree->step_mat[14*tree->mod->ns+18] = 3 ;
tree->step_mat[14*tree->mod->ns+19] = 3 ;
tree->step_mat[15*tree->mod->ns+ 0] = 2 ;
tree->step_mat[15*tree->mod->ns+ 1] = 2 ;
tree->step_mat[15*tree->mod->ns+ 2] = 2 ;
tree->step_mat[15*tree->mod->ns+ 3] = 3 ;
tree->step_mat[15*tree->mod->ns+ 4] = 2 ;
tree->step_mat[15*tree->mod->ns+ 5] = 3 ;
tree->step_mat[15*tree->mod->ns+ 6] = 3 ;
tree->step_mat[15*tree->mod->ns+ 7] = 2 ;
tree->step_mat[15*tree->mod->ns+ 8] = 3 ;
tree->step_mat[15*tree->mod->ns+ 9] = 2 ;
tree->step_mat[15*tree->mod->ns+10] = 3 ;
tree->step_mat[15*tree->mod->ns+11] = 2 ;
tree->step_mat[15*tree->mod->ns+12] = 2 ;
tree->step_mat[15*tree->mod->ns+13] = 2 ;
tree->step_mat[15*tree->mod->ns+14] = 2 ;
tree->step_mat[15*tree->mod->ns+15] = 0 ;
tree->step_mat[15*tree->mod->ns+16] = 2 ;
tree->step_mat[15*tree->mod->ns+17] = 2 ;
tree->step_mat[15*tree->mod->ns+18] = 2 ;
tree->step_mat[15*tree->mod->ns+19] = 3 ;
tree->step_mat[16*tree->mod->ns+ 0] = 2 ;
tree->step_mat[16*tree->mod->ns+ 1] = 2 ;
tree->step_mat[16*tree->mod->ns+ 2] = 2 ;
tree->step_mat[16*tree->mod->ns+ 3] = 3 ;
tree->step_mat[16*tree->mod->ns+ 4] = 3 ;
tree->step_mat[16*tree->mod->ns+ 5] = 3 ;
tree->step_mat[16*tree->mod->ns+ 6] = 3 ;
tree->step_mat[16*tree->mod->ns+ 7] = 3 ;
tree->step_mat[16*tree->mod->ns+ 8] = 3 ;
tree->step_mat[16*tree->mod->ns+ 9] = 2 ;
tree->step_mat[16*tree->mod->ns+10] = 3 ;
tree->step_mat[16*tree->mod->ns+11] = 2 ;
tree->step_mat[16*tree->mod->ns+12] = 2 ;
tree->step_mat[16*tree->mod->ns+13] = 3 ;
tree->step_mat[16*tree->mod->ns+14] = 2 ;
tree->step_mat[16*tree->mod->ns+15] = 2 ;
tree->step_mat[16*tree->mod->ns+16] = 0 ;
tree->step_mat[16*tree->mod->ns+17] = 3 ;
tree->step_mat[16*tree->mod->ns+18] = 3 ;
tree->step_mat[16*tree->mod->ns+19] = 3 ;
tree->step_mat[17*tree->mod->ns+ 0] = 3 ;
tree->step_mat[17*tree->mod->ns+ 1] = 2 ;
tree->step_mat[17*tree->mod->ns+ 2] = 3 ;
tree->step_mat[17*tree->mod->ns+ 3] = 3 ;
tree->step_mat[17*tree->mod->ns+ 4] = 1 ;
tree->step_mat[17*tree->mod->ns+ 5] = 2 ;
tree->step_mat[17*tree->mod->ns+ 6] = 2 ;
tree->step_mat[17*tree->mod->ns+ 7] = 2 ;
tree->step_mat[17*tree->mod->ns+ 8] = 3 ;
tree->step_mat[17*tree->mod->ns+ 9] = 3 ;
tree->step_mat[17*tree->mod->ns+10] = 2 ;
tree->step_mat[17*tree->mod->ns+11] = 2 ;
tree->step_mat[17*tree->mod->ns+12] = 2 ;
tree->step_mat[17*tree->mod->ns+13] = 2 ;
tree->step_mat[17*tree->mod->ns+14] = 3 ;
tree->step_mat[17*tree->mod->ns+15] = 2 ;
tree->step_mat[17*tree->mod->ns+16] = 3 ;
tree->step_mat[17*tree->mod->ns+17] = 0 ;
tree->step_mat[17*tree->mod->ns+18] = 2 ;
tree->step_mat[17*tree->mod->ns+19] = 3 ;
tree->step_mat[18*tree->mod->ns+ 0] = 3 ;
tree->step_mat[18*tree->mod->ns+ 1] = 3 ;
tree->step_mat[18*tree->mod->ns+ 2] = 2 ;
tree->step_mat[18*tree->mod->ns+ 3] = 2 ;
tree->step_mat[18*tree->mod->ns+ 4] = 2 ;
tree->step_mat[18*tree->mod->ns+ 5] = 2 ;
tree->step_mat[18*tree->mod->ns+ 6] = 2 ;
tree->step_mat[18*tree->mod->ns+ 7] = 3 ;
tree->step_mat[18*tree->mod->ns+ 8] = 2 ;
tree->step_mat[18*tree->mod->ns+ 9] = 3 ;
tree->step_mat[18*tree->mod->ns+10] = 2 ;
tree->step_mat[18*tree->mod->ns+11] = 2 ;
tree->step_mat[18*tree->mod->ns+12] = 3 ;
tree->step_mat[18*tree->mod->ns+13] = 2 ;
tree->step_mat[18*tree->mod->ns+14] = 3 ;
tree->step_mat[18*tree->mod->ns+15] = 2 ;
tree->step_mat[18*tree->mod->ns+16] = 3 ;
tree->step_mat[18*tree->mod->ns+17] = 2 ;
tree->step_mat[18*tree->mod->ns+18] = 0 ;
tree->step_mat[18*tree->mod->ns+19] = 3 ;
tree->step_mat[19*tree->mod->ns+ 0] = 2 ;
tree->step_mat[19*tree->mod->ns+ 1] = 3 ;
tree->step_mat[19*tree->mod->ns+ 2] = 3 ;
tree->step_mat[19*tree->mod->ns+ 3] = 2 ;
tree->step_mat[19*tree->mod->ns+ 4] = 3 ;
tree->step_mat[19*tree->mod->ns+ 5] = 3 ;
tree->step_mat[19*tree->mod->ns+ 6] = 2 ;
tree->step_mat[19*tree->mod->ns+ 7] = 2 ;
tree->step_mat[19*tree->mod->ns+ 8] = 3 ;
tree->step_mat[19*tree->mod->ns+ 9] = 2 ;
tree->step_mat[19*tree->mod->ns+10] = 2 ;
tree->step_mat[19*tree->mod->ns+11] = 3 ;
tree->step_mat[19*tree->mod->ns+12] = 2 ;
tree->step_mat[19*tree->mod->ns+13] = 2 ;
tree->step_mat[19*tree->mod->ns+14] = 3 ;
tree->step_mat[19*tree->mod->ns+15] = 3 ;
tree->step_mat[19*tree->mod->ns+16] = 3 ;
tree->step_mat[19*tree->mod->ns+17] = 3 ;
tree->step_mat[19*tree->mod->ns+18] = 3 ;
tree->step_mat[19*tree->mod->ns+19] = 0 ;
}
else
{
tree->step_mat[0*tree->mod->ns+0] = 0;
tree->step_mat[0*tree->mod->ns+1] = 2;
tree->step_mat[0*tree->mod->ns+2] = 1;
tree->step_mat[0*tree->mod->ns+3] = 2;
tree->step_mat[1*tree->mod->ns+0] = 2;
tree->step_mat[1*tree->mod->ns+1] = 0;
tree->step_mat[1*tree->mod->ns+2] = 2;
tree->step_mat[1*tree->mod->ns+3] = 1;
tree->step_mat[2*tree->mod->ns+0] = 1;
tree->step_mat[2*tree->mod->ns+1] = 2;
tree->step_mat[2*tree->mod->ns+2] = 0;
tree->step_mat[2*tree->mod->ns+3] = 2;
tree->step_mat[3*tree->mod->ns+0] = 2;
tree->step_mat[3*tree->mod->ns+1] = 1;
tree->step_mat[3*tree->mod->ns+2] = 2;
tree->step_mat[3*tree->mod->ns+3] = 0;
/* tree->step_mat[0*tree->mod->ns+0] = 0; */
/* tree->step_mat[0*tree->mod->ns+1] = 1; */
/* tree->step_mat[0*tree->mod->ns+2] = 1; */
/* tree->step_mat[0*tree->mod->ns+3] = 1; */
/* tree->step_mat[1*tree->mod->ns+0] = 1; */
/* tree->step_mat[1*tree->mod->ns+1] = 0; */
/* tree->step_mat[1*tree->mod->ns+2] = 1; */
/* tree->step_mat[1*tree->mod->ns+3] = 1; */
/* tree->step_mat[2*tree->mod->ns+0] = 1; */
/* tree->step_mat[2*tree->mod->ns+1] = 1; */
/* tree->step_mat[2*tree->mod->ns+2] = 0; */
/* tree->step_mat[2*tree->mod->ns+3] = 1; */
/* tree->step_mat[3*tree->mod->ns+0] = 1; */
/* tree->step_mat[3*tree->mod->ns+1] = 1; */
/* tree->step_mat[3*tree->mod->ns+2] = 1; */
/* tree->step_mat[3*tree->mod->ns+3] = 0; */
}
For(i,tree->mod->ns) tree->step_mat[i*tree->mod->ns+i] = 0;
}
/*********************************************************/
/*********************************************************/
phyml-20120412/src/rates.c 0000644 0001750 0001750 00000333701 11731505265 012106 0000000 0000000 /*
PhyML: a program that computes maximum likelihood phyLOGenies from
DNA or AA homoLOGous sequences.
Copyright (C) Stephane Guindon. Oct 2003 onward.
All parts of the source except where indicated are distributed under
the GNU public licence. See http://www.opensource.org for details.
*/
/* Routines for molecular clock trees and molecular dating */
#include "rates.h"
#ifdef RWRAPPER
#include
#endif
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
phydbl RATES_Lk_Rates(t_tree *tree)
{
tree->rates->c_lnL_rates = .0;
RATES_Lk_Rates_Pre(tree->n_root,tree->n_root->v[0],NULL,tree);
RATES_Lk_Rates_Pre(tree->n_root,tree->n_root->v[1],NULL,tree);
if(isnan(tree->rates->c_lnL_rates))
{
PhyML_Printf("\n. Err in file %s at line %d\n",__FILE__,__LINE__);
Exit("\n");
}
return tree->rates->c_lnL_rates;
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void RATES_Lk_Rates_Pre(t_node *a, t_node *d, t_edge *b, t_tree *tree)
{
int i;
phydbl log_dens,mu_a,mu_d,r_a,r_d,dt_a,dt_d;
int n_a,n_d;
log_dens = -1.;
if(d->anc != a)
{
PhyML_Printf("\n. d=%d d->anc=%d a=%d root=%d",d->num,d->anc->num,a->num,tree->n_root->num);
PhyML_Printf("\n. Err in file %s at line %d\n",__FILE__,__LINE__);
Warn_And_Exit("");
}
dt_a = -1.;
if(a != tree->n_root) dt_a = tree->rates->nd_t[a->num] - tree->rates->nd_t[a->anc->num];
mu_a = tree->rates->br_r[a->num];
r_a = tree->rates->nd_r[a->num];
n_a = tree->rates->n_jps[a->num];
dt_d = FABS(tree->rates->nd_t[d->num] - tree->rates->nd_t[a->num]);
mu_d = tree->rates->br_r[d->num];
r_d = tree->rates->nd_r[d->num];
n_d = tree->rates->n_jps[d->num];
log_dens = RATES_Lk_Rates_Core(mu_a,mu_d,r_a,r_d,n_a,n_d,dt_a,dt_d,tree);
tree->rates->c_lnL_rates += log_dens;
/* printf("\n. a=%3d d=%3d r(a)=%10f r(d)=%10f %f",a->num,d->num,mu_a,mu_d,log_dens); */
if(isnan(tree->rates->c_lnL_rates))
{
PhyML_Printf("\n. Err in file %s at line %d\n",__FILE__,__LINE__);
MCMC_Print_Param(tree->mcmc,tree);
Exit("\n");
}
tree->rates->triplet[a->num] += log_dens;
if(d->tax) return;
else
{
For(i,3)
{
if((d->v[i] != a) && (d->b[i] != tree->e_root))
{
RATES_Lk_Rates_Pre(d,d->v[i],d->b[i],tree);
}
}
}
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
phydbl RATES_Lk_Change_One_Rate(t_node *d, phydbl new_rate, t_tree *tree)
{
tree->rates->br_r[d->num] = new_rate;
RATES_Update_Triplet(d,tree);
RATES_Update_Triplet(d->anc,tree);
return(tree->rates->c_lnL_rates);
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
phydbl RATES_Lk_Change_One_Time(t_node *n, phydbl new_t, t_tree *tree)
{
if(n == tree->n_root)
{
PhyML_Printf("\n. Moving the time of the root t_node is not permitted.");
PhyML_Printf("\n. Err in file %s at line %d\n",__FILE__,__LINE__);
Warn_And_Exit("");
}
else
{
int i;
tree->rates->nd_t[n->num] = new_t;
RATES_Update_Triplet(n,tree);
For(i,3)
{
if(n->b[i] != tree->e_root) RATES_Update_Triplet(n->v[i],tree);
else RATES_Update_Triplet(tree->n_root,tree);
}
}
return(tree->rates->c_lnL_rates);
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void RATES_Update_Triplet(t_node *n, t_tree *tree)
{
phydbl curr_triplet,new_triplet;
phydbl dt0,dt1,dt2;
phydbl mu1_mu0,mu2_mu0;
phydbl mu0,mu1,mu2;
phydbl r0,r1,r2;
int n0,n1,n2;
int i;
t_node *v1,*v2;
if(n->tax) return;
curr_triplet = tree->rates->triplet[n->num];
dt0 = dt1 = dt2 = -100.0;
r0 = r1 = r2 = 0.0;
if(n == tree->n_root)
{
phydbl log_dens;
log_dens = 0.0;
dt0 = tree->rates->nd_t[tree->n_root->v[0]->num] - tree->rates->nd_t[tree->n_root->num];
dt1 = tree->rates->nd_t[tree->n_root->v[1]->num] - tree->rates->nd_t[tree->n_root->num];
mu0 = tree->rates->br_r[tree->n_root->v[0]->num];
mu1 = tree->rates->br_r[tree->n_root->v[1]->num];
r0 = tree->rates->nd_r[tree->n_root->v[0]->num];
r1 = tree->rates->nd_r[tree->n_root->v[1]->num];
n0 = tree->rates->n_jps[tree->n_root->v[0]->num];
n1 = tree->rates->n_jps[tree->n_root->v[1]->num];
switch(tree->rates->model)
{
case COMPOUND_COR : case COMPOUND_NOCOR :
{
log_dens = RATES_Dmu(mu0,n0,dt0,tree->rates->nu,1./tree->rates->nu,tree->rates->lexp,0,1);
log_dens *= RATES_Dmu(mu1,n1,dt1,tree->rates->nu,1./tree->rates->nu,tree->rates->lexp,0,1);
log_dens = LOG(log_dens);
break;
}
case EXPONENTIAL :
{
log_dens = Dexp(mu0,tree->rates->lexp) * Dexp(mu1,tree->rates->lexp);
log_dens = LOG(log_dens);
break;
}
case GAMMA :
{
log_dens = Dgamma(mu0,tree->rates->nu,1./tree->rates->nu) * Dgamma(mu1,tree->rates->nu,1./tree->rates->nu);
log_dens = LOG(log_dens);
break;
}
case THORNE :
{
int err;
phydbl mean0,sd0;
phydbl mean1,sd1;
sd0 = SQRT(tree->rates->nu*dt0);
mean0 = 1.0;
sd1 = SQRT(tree->rates->nu*dt1);
mean1 = 1.0;
log_dens =
Log_Dnorm_Trunc(mu0,mean0,sd0,tree->rates->min_rate,tree->rates->max_rate,&err) +
Log_Dnorm_Trunc(mu1,mean1,sd1,tree->rates->min_rate,tree->rates->max_rate,&err);
break;
}
case GUINDON :
{
Exit("\n. Not implemented yet.\n");
PhyML_Printf("\n. Err in file %s at line %d\n",__FILE__,__LINE__);
break;
}
default :
{
Exit("\n. Model not implemented yet.\n");
break;
}
}
new_triplet = log_dens;
if(isnan(log_dens) || isinf(FABS(log_dens)))
{
PhyML_Printf("\n. Err in file %s at line %d\n",__FILE__,__LINE__);
MCMC_Print_Param(tree->mcmc,tree);
Exit("\n");
}
}
else
{
mu0 = mu1 = mu2 = -1.;
n0 = n1 = n2 = -1;
mu0 = tree->rates->br_r[n->num];
dt0 = FABS(tree->rates->nd_t[n->num] - tree->rates->nd_t[n->anc->num]);
n0 = tree->rates->n_jps[n->num];
r0 = tree->rates->nd_r[n->num];
v1 = v2 = NULL;
For(i,3)
{
if((n->v[i] != n->anc) && (n->b[i] != tree->e_root))
{
if(!v1)
{
v1 = n->v[i];
mu1 = tree->rates->br_r[v1->num];
dt1 = FABS(tree->rates->nd_t[v1->num] - tree->rates->nd_t[n->num]);
n1 = tree->rates->n_jps[v1->num];
r1 = tree->rates->nd_r[v1->num];
}
else
{
v2 = n->v[i];
mu2 = tree->rates->br_r[v2->num];
dt2 = FABS(tree->rates->nd_t[v2->num] - tree->rates->nd_t[n->num]);
n2 = tree->rates->n_jps[v2->num];
r2 = tree->rates->nd_r[v2->num];
}
}
}
mu1_mu0 = RATES_Lk_Rates_Core(mu0,mu1,r0,r1,n0,n1,dt0,dt1,tree);
mu2_mu0 = RATES_Lk_Rates_Core(mu0,mu2,r0,r1,n0,n2,dt0,dt2,tree);
new_triplet = mu1_mu0 + mu2_mu0;
}
tree->rates->c_lnL_rates = tree->rates->c_lnL_rates + new_triplet - curr_triplet;
tree->rates->triplet[n->num] = new_triplet;
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
/* Returns LOG(f(br_r_rght;br_r_left)) */
phydbl RATES_Lk_Rates_Core(phydbl br_r_a, phydbl br_r_d, phydbl nd_r_a, phydbl nd_r_d, int n_a, int n_d, phydbl dt_a, phydbl dt_d, t_tree *tree)
{
phydbl log_dens;
phydbl mean,sd;
phydbl min_r, max_r;
phydbl cr,logcr;
cr = tree->rates->clock_r;
logcr = LOG(cr);
log_dens = UNLIKELY;
mean = sd = -1.;
min_r = tree->rates->min_rate;
max_r = tree->rates->max_rate;
dt_d = MAX(0.5,dt_d); // We give only one decimal when printing out node heights. It is therefore a fair approximation
switch(tree->rates->model)
{
case THORNE :
{
int err;
if(tree->rates->model_log_rates == YES)
{
br_r_d += logcr;
br_r_a += logcr;
min_r += logcr;
max_r += logcr;
sd = SQRT(tree->rates->nu*dt_d);
mean = br_r_a - .5*sd*sd;
log_dens = Log_Dnorm_Trunc(br_r_d,mean,sd,min_r,max_r,&err);
if(err)
{
PhyML_Printf("\n. Run: %d",tree->mcmc->run);
PhyML_Printf("\n. br_r_d = %f br_r_a = %f dt_d = %f logcr = %f",br_r_d,br_r_a,dt_d,logcr);
PhyML_Printf("\n. Err in file %s at line %d\n",__FILE__,__LINE__);
Exit("\n");
}
}
else
{
PhyML_Printf("\n. Not implemented yet.");
PhyML_Printf("\n. Err in file %s at line %d\n",__FILE__,__LINE__);
Exit("\n");
}
/* int err; */
/* phydbl cr; */
/* phydbl min_r, max_r; */
/* cr = tree->rates->clock_r; */
/* min_r = tree->rates->min_rate * cr; */
/* max_r = tree->rates->max_rate * cr; */
/* /\* !!!!!!!!!!!!1 *\/ */
/* br_r_d *= cr; */
/* br_r_a *= cr; */
/* err = NO; */
/* /\* if(dt_d < 5.0) dt_d = 5.0; *\/ */
/* sd = SQRT(dt_d*tree->rates->nu); */
/* /\* sd = SQRT(dt_d*EXP(tree->rates->nu)); *\/ */
/* /\* mean = LOG(br_r_a) - .5*sd*sd; *\/ */
/* if(tree->rates->model_log_rates == YES) */
/* { */
/* mean = br_r_a - .5*sd*sd; */
/* } */
/* else */
/* { */
/* mean = br_r_a; */
/* } */
/* log_dens = Log_Dnorm_Trunc(br_r_d,mean,sd,min_r,max_r,&err); */
/* if(err || isnan(log_dens) || isinf(log_dens)) */
/* { */
/* PhyML_Printf("\n. br_r_a=%f br_r_d=%f dt_d=%f nu=%G",br_r_a,br_r_d,dt_d,tree->rates->nu); */
/* PhyML_Printf("\n. Run: %d",tree->mcmc->run); */
/* PhyML_Printf("\n. Err in file %s at line %d\n",__FILE__,__LINE__); */
/* Exit("\n"); */
/* } */
break;
}
case GUINDON :
{
int err;
min_r = tree->rates->min_rate;
max_r = tree->rates->max_rate;
br_r_d += logcr;
br_r_a += logcr;
min_r += logcr;
max_r += logcr;
sd = SQRT(tree->rates->nu*dt_d);
mean = br_r_a - .5*sd*sd;
log_dens = Log_Dnorm_Trunc(br_r_d,mean,sd,min_r,max_r,&err);
if(err)
{
PhyML_Printf("\n. Run: %d",tree->mcmc->run);
PhyML_Printf("\n. br_r_d=%f mean=%f sd=%f min_r=%f max_r=%f dt_d=%f",br_r_d,mean,sd,min_r,max_r,dt_d);
PhyML_Printf("\n. Err in file %s at line %d\n",__FILE__,__LINE__);
Exit("\n");
}
break;
}
case GAMMA :
{
if(tree->rates->model_log_rates == YES)
log_dens = Dgamma(EXP(br_r_d),1./tree->rates->nu,tree->rates->nu);
else
log_dens = Dgamma(br_r_d,1./tree->rates->nu,tree->rates->nu);
log_dens = LOG(log_dens);
break;
}
case STRICTCLOCK :
{
log_dens = 0.0;
break;
}
default :
{
PhyML_Printf("\n. Err in file %s at line %d\n",__FILE__,__LINE__);
Warn_And_Exit("");
}
}
if(isnan(log_dens) || isinf(FABS(log_dens)))
{
PhyML_Printf("\n. Run=%4d br_r_d=%f br_r_a=%f dt_d=%f dt_a=%f nu=%f log_dens=%G sd=%f mean=%f\n",
tree->mcmc->run,
br_r_d,br_r_a,dt_d,dt_a,tree->rates->nu,log_dens,
sd,mean);
PhyML_Printf("\n. Err in file %s at line %d\n",__FILE__,__LINE__);
Exit("\n");
}
return log_dens;
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
phydbl RATES_Compound_Core(phydbl mu1, phydbl mu2, int n1, int n2, phydbl dt1, phydbl dt2, phydbl alpha, phydbl beta, phydbl lexp, phydbl eps, int approx)
{
if((n1 > -1) && (n2 > -1))
{
return RATES_Compound_Core_Joint(mu1,mu2,n1,n2,dt1,dt2,alpha,beta,lexp,eps,approx);
}
else
{
return RATES_Compound_Core_Marginal(mu1,mu2,dt1,dt2,alpha,beta,lexp,eps,approx);
}
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
phydbl RATES_Compound_Core_Marginal(phydbl mu1, phydbl mu2, phydbl dt1, phydbl dt2, phydbl alpha, phydbl beta, phydbl lexp, phydbl eps, int approx)
{
phydbl p0,p1,v0,v1,v2;
phydbl dmu1;
int equ;
phydbl dens;
v0 = v1 = v2 = 0.0;
/* Probability of 0 and 1 jumps */
p0 = Dpois(0,lexp*(dt2+dt1));
p1 = Dpois(1,lexp*(dt2+dt1));
dmu1 = RATES_Dmu(mu1,-1,dt1,alpha,beta,lexp,0,0);
/* Are the two rates equal ? */
equ = 0;
if(FABS(mu1-mu2) < eps) equ = 1;
/* No jump */
if(equ)
{
v0 = 1.0*Dgamma(mu1,alpha,beta)/dmu1;
/* Rprintf("\n. mu1=%f mu2=%f",mu1,mu2); */
}
else
{
v0 = 1.E-100;
}
/* One jump */
v1 = RATES_Dmu1_And_Mu2_One_Jump_Two_Intervals(mu1,mu2,dt1,dt2,alpha,beta);
v1 /= dmu1;
/* Two jumps and more (approximation) */
if(approx == 1)
{
v2 =
RATES_Dmu(mu1,-1,dt1,alpha,beta,lexp,0,0)*RATES_Dmu(mu2,-1,dt2,alpha,beta,lexp,0,0) -
Dpois(0,lexp*dt1) * Dpois(0,lexp*dt2) *
Dgamma(mu1,alpha,beta) * Dgamma(mu2,alpha,beta);
}
else
{
v2 =
RATES_Dmu_One(mu1,dt1,alpha,beta,lexp) *
RATES_Dmu_One(mu2,dt2,alpha,beta,lexp);
v2 += Dpois(0,lexp*dt1)*Dgamma(mu1,alpha,beta)*RATES_Dmu(mu2,-1,dt2,alpha,beta,lexp,1,0);
v2 += Dpois(0,lexp*dt2)*Dgamma(mu2,alpha,beta)*RATES_Dmu(mu1,-1,dt1,alpha,beta,lexp,1,0);
}
/* PhyML_Printf("\n. %f %f %f %f %f ",mu1,mu2,dt1,dt2,v2); */
v2 /= dmu1;
dens = p0*v0 + p1*v1 + v2;
/* dens = p1*v1 + v2; */
/* dens = p1*v1 + v2; */
/* dens = v0; */
/* dens *= dmu1; */
if(dens < SMALL)
{
PhyML_Printf("\n. dens=%12G mu1=%12G mu2=%12G dt1=%12G dt2=%12G lexp=%12G alpha=%f v0=%f v1=%f v2=%f p0=%f p1=%f p2=%f",
dens,
mu1,mu2,dt1,dt2,
lexp,
alpha,
v0,v1,v2,
p0,p1,1.-p0-p1);
}
return dens;
}
/**********************************************************/
phydbl RATES_Compound_Core_Joint(phydbl mu1, phydbl mu2, int n1, int n2, phydbl dt1, phydbl dt2,
phydbl alpha, phydbl beta, phydbl lexp, phydbl eps, int approx)
{
phydbl density;
phydbl dmu1;
if(n1 < 0 || n2 < 0)
{
PhyML_Printf("\n. n1=%d n2=%d",n1,n2);
PhyML_Printf("\n. Err in file %s at line %d\n",__FILE__,__LINE__);
Warn_And_Exit("");
}
dmu1 = RATES_Dmu(mu1,n1,dt1,alpha,beta,lexp,0,0);
if((n1 < 0) || (n2 < 0))
{
PhyML_Printf("\n. Err in file %s at line %d\n",__FILE__,__LINE__);
Warn_And_Exit("");
}
if((n1 == 0) && (n2 == 0))
{
if(FABS(mu1-mu2) < eps) { density = Dgamma(mu1,alpha,beta); }
else { density = 1.E-70; }
}
else if((n1 == 0) && (n2 == 1))
{
density =
Dgamma(mu1,alpha,beta) *
RATES_Dmu1_Given_V_And_N(mu2,mu1,1,dt2,alpha,beta);
}
else if((n1 == 1) && (n2 == 0))
{
density =
Dgamma(mu2,alpha,beta) *
RATES_Dmu1_Given_V_And_N(mu1,mu2,1,dt1,alpha,beta);
}
else /* independent */
{
density =
RATES_Dmu(mu1,n1,dt1,alpha,beta,lexp,0,0) *
RATES_Dmu(mu2,n2,dt2,alpha,beta,lexp,0,0);
}
density /= dmu1;
density *= Dpois(n2,dt2*lexp);
if(density < 1.E-70) density = 1.E-70;
/* PhyML_Printf("\n. density = %15G mu1=%3.4f mu2=%3.4f dt1=%3.4f dt2=%3.4f n1=%2d n2=%2d",density,mu1,mu2,dt1,dt2,n1,n2); */
return density;
}
/**********************************************************/
void RATES_Print_Triplets(t_tree *tree)
{
int i;
For(i,2*tree->n_otu-1) PhyML_Printf("\n. Node %3d t=%f",i,tree->rates->triplet[i]);
}
/**********************************************************/
void RATES_Print_Rates(t_tree *tree)
{
RATES_Print_Rates_Pre(tree->n_root,tree->n_root->v[0],NULL,tree);
RATES_Print_Rates_Pre(tree->n_root,tree->n_root->v[1],NULL,tree);
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void RATES_Print_Rates_Pre(t_node *a, t_node *d, t_edge *b, t_tree *tree)
{
if((d == tree->n_root->v[0] && d->tax) || (d == tree->n_root->v[1] && d->tax))
PhyML_Printf("\n. a=%3d ++d=%3d rate=%12f t_left=%12f t_rght=%12f ml=%12f l=%12f %12f",
a->num,d->num,
tree->rates->br_r[d->num],
tree->rates->nd_t[a->num],tree->rates->nd_t[d->num],
tree->rates->ml_l[d->num],
tree->rates->cur_l[d->num],
(tree->rates->nd_t[d->num]-tree->rates->nd_t[a->num])*tree->rates->clock_r*tree->rates->br_r[d->num]);
else if((d == tree->n_root->v[0]) || (d == tree->n_root->v[1]))
PhyML_Printf("\n. a=%3d __d=%3d rate=%12f t_left=%12f t_rght=%12f ml=%12f l=%12f %12f",
a->num,d->num,
tree->rates->br_r[d->num],
tree->rates->nd_t[a->num],tree->rates->nd_t[d->num],
tree->rates->ml_l[d->num],
tree->rates->cur_l[d->num],
(tree->rates->nd_t[d->num]-tree->rates->nd_t[a->num])*tree->rates->clock_r*tree->rates->br_r[d->num]);
else
PhyML_Printf("\n. a=%3d d=%3d rate=%12f t_left=%12f t_rght=%12f ml=%12f l=%12f %12f",
a->num,d->num,
tree->rates->br_r[d->num],
tree->rates->nd_t[a->num],tree->rates->nd_t[d->num],
tree->rates->ml_l[d->num],
tree->rates->cur_l[d->num],
(tree->rates->nd_t[d->num]-tree->rates->nd_t[a->num])*tree->rates->clock_r*tree->rates->br_r[d->num]);
if(d->tax) return;
else
{
int i;
For(i,3)
{
if((d->v[i] != a) && (d->b[i] != tree->e_root))
{
RATES_Print_Rates_Pre(d,d->v[i],d->b[i],tree);
}
}
}
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
phydbl RATES_Average_Rate(t_tree *tree)
{
int i;
phydbl sum;
sum = 0.0;
For(i,2*tree->n_otu-2) sum += tree->rates->br_r[i];
return sum/(2*tree->n_otu-2);
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
phydbl RATES_Average_Substitution_Rate(t_tree *tree)
{
phydbl sum_r,sum_dt;
phydbl u,t,t_anc,tmp;
int i;
u = 0.0;
tmp = 0.0;
sum_r = 0.0;
sum_dt = 0.0;
/* For(i,2*tree->n_otu-3) */
/* { */
/* t = tree->rates->nd_t[i]; */
/* t_anc = tree->rates->nd_t[tree->t_nodes[i]->anc->num]; */
/* u = tree->t_edges[i]->l; */
/* if(tree->rates->model == GUINDON) u = tree->t_edges[i]->gamma_prior_mean; */
/* sum_r += u; */
/* sum_dt += FABS(t-t_anc); */
/* } */
For(i,2*tree->n_otu-3)
{
if(tree->t_edges[i] != tree->e_root)
{
t = tree->rates->nd_t[tree->t_edges[i]->left->num];
t_anc = tree->rates->nd_t[tree->t_edges[i]->rght->num];
u = tree->t_edges[i]->l;
if(tree->rates->model == GUINDON) u = tree->t_edges[i]->gamma_prior_mean;
sum_r += u;
sum_dt += FABS(t-t_anc);
}
sum_dt += FABS(tree->rates->nd_t[tree->n_root->v[0]->num] - tree->rates->nd_t[tree->n_root->num]);
sum_dt += FABS(tree->rates->nd_t[tree->n_root->v[1]->num] - tree->rates->nd_t[tree->n_root->num]);
u = tree->e_root->l;
if(tree->rates->model == GUINDON) u = tree->e_root->gamma_prior_mean;
sum_r += u;
}
return(sum_r / sum_dt);
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
phydbl RATES_Check_Mean_Rates_True(t_tree *tree)
{
phydbl sum;
int i;
sum = 0.0;
For(i,2*tree->n_otu-2) sum += tree->rates->true_r[i];
return(sum/(phydbl)(2*tree->n_otu-2));
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
int RATES_Check_Node_Times(t_tree *tree)
{
int err;
err = NO;
RATES_Check_Node_Times_Pre(tree->n_root,tree->n_root->v[0],&err,tree);
RATES_Check_Node_Times_Pre(tree->n_root,tree->n_root->v[1],&err,tree);
return err;
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void RATES_Check_Node_Times_Pre(t_node *a, t_node *d, int *err, t_tree *tree)
{
if(tree->rates->nd_t[d->num] < tree->rates->nd_t[a->num])
{
PhyML_Printf("\n. a->t=%f d->t=%f",tree->rates->nd_t[a->num],tree->rates->nd_t[d->num]);
PhyML_Printf("\n. a->t_prior_min=%f a->t_prior_max=%f",tree->rates->t_prior_min[a->num],tree->rates->t_prior_max[a->num]);
PhyML_Printf("\n. d->t_prior_min=%f d->t_prior_max=%f",tree->rates->t_prior_min[d->num],tree->rates->t_prior_max[d->num]);
*err = YES;
}
if(d->tax) return;
else
{
int i;
For(i,3)
if((d->v[i] != a) && (d->b[i] != tree->e_root))
RATES_Check_Node_Times_Pre(d,d->v[i],err,tree);
}
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
t_rate *RATES_Make_Rate_Struct(int n_otu)
{
t_rate *rates;
rates = (t_rate *)mCalloc(1,sizeof(t_rate));
rates->is_allocated = NO;
if(n_otu > 0)
{
rates->is_allocated = YES;
rates->nd_r = (phydbl *)mCalloc(2*n_otu-1,sizeof(phydbl));
rates->br_r = (phydbl *)mCalloc(2*n_otu-1,sizeof(phydbl));
rates->buff_r = (phydbl *)mCalloc(2*n_otu-1,sizeof(phydbl));
rates->true_r = (phydbl *)mCalloc(2*n_otu-1,sizeof(phydbl));
rates->nd_t = (phydbl *)mCalloc(2*n_otu-1,sizeof(phydbl));
rates->buff_t = (phydbl *)mCalloc(2*n_otu-1,sizeof(phydbl));
rates->true_t = (phydbl *)mCalloc(2*n_otu-1,sizeof(phydbl));
rates->t_mean = (phydbl *)mCalloc(2*n_otu-1,sizeof(phydbl));
rates->t_prior = (phydbl *)mCalloc(2*n_otu-1,sizeof(phydbl));
rates->t_prior_min = (phydbl *)mCalloc(2*n_otu-1,sizeof(phydbl));
rates->t_prior_max = (phydbl *)mCalloc(2*n_otu-1,sizeof(phydbl));
rates->t_floor = (phydbl *)mCalloc(2*n_otu-1,sizeof(phydbl));
rates->t_ranked = (int *)mCalloc(2*n_otu-1,sizeof(int));
rates->t_has_prior = (short int *)mCalloc(2*n_otu-1,sizeof(short int));
rates->dens = (phydbl *)mCalloc(2*n_otu-2,sizeof(phydbl));
rates->triplet = (phydbl *)mCalloc(2*n_otu-1,sizeof(phydbl));
rates->n_jps = (int *)mCalloc(2*n_otu-1,sizeof(int));
rates->t_jps = (int *)mCalloc(2*n_otu-2,sizeof(int));
rates->cov_l = (phydbl *)mCalloc((2*n_otu-2)*(2*n_otu-2),sizeof(phydbl));
rates->invcov = (phydbl *)mCalloc((2*n_otu-2)*(2*n_otu-2),sizeof(phydbl));
rates->mean_l = (phydbl *)mCalloc(2*n_otu-2,sizeof(phydbl));
rates->ml_l = (phydbl *)mCalloc(2*n_otu-2,sizeof(phydbl));
rates->cur_l = (phydbl *)mCalloc(2*n_otu-2,sizeof(phydbl));
rates->u_ml_l = (phydbl *)mCalloc(2*n_otu-3,sizeof(phydbl));
rates->u_cur_l = (phydbl *)mCalloc(2*n_otu-3,sizeof(phydbl));
rates->cov_r = (phydbl *)mCalloc((2*n_otu-2)*(2*n_otu-2),sizeof(phydbl));
rates->cond_var = (phydbl *)mCalloc(2*n_otu-2,sizeof(phydbl));
rates->mean_r = (phydbl *)mCalloc(2*n_otu-2,sizeof(phydbl));
rates->mean_t = (phydbl *)mCalloc(2*n_otu-1,sizeof(phydbl));
rates->lca = (t_node **)mCalloc((2*n_otu-1)*(2*n_otu-1),sizeof(t_node *));
rates->reg_coeff = (phydbl *)mCalloc((2*n_otu-2)*(2*n_otu-2),sizeof(phydbl));
rates->trip_reg_coeff = (phydbl *)mCalloc((2*n_otu-2)*(6*n_otu-9),sizeof(phydbl));
rates->trip_cond_cov = (phydbl *)mCalloc((2*n_otu-2)*9,sizeof(phydbl));
rates->_2n_vect1 = (phydbl *)mCalloc(2*n_otu,sizeof(phydbl));
rates->_2n_vect2 = (phydbl *)mCalloc(2*n_otu,sizeof(phydbl));
rates->_2n_vect3 = (phydbl *)mCalloc(2*n_otu,sizeof(phydbl));
rates->_2n_vect4 = (phydbl *)mCalloc(2*n_otu,sizeof(phydbl));
rates->_2n_vect5 = (short int *)mCalloc(2*n_otu,sizeof(short int));
rates->_2n2n_vect1 = (phydbl *)mCalloc(4*n_otu*n_otu,sizeof(phydbl));
rates->_2n2n_vect2 = (phydbl *)mCalloc(4*n_otu*n_otu,sizeof(phydbl));
rates->br_do_updt = (short int *)mCalloc(2*n_otu-1,sizeof(short int));
rates->cur_gamma_prior_mean = (phydbl *)mCalloc(2*n_otu-1,sizeof(phydbl));
rates->cur_gamma_prior_var = (phydbl *)mCalloc(2*n_otu-1,sizeof(phydbl));
rates->n_tips_below = (int *)mCalloc(2*n_otu-1,sizeof(int));
rates->time_slice_lims = (phydbl *)mCalloc(2*n_otu-1,sizeof(phydbl));
rates->n_time_slice_spans = (int *)mCalloc(2*n_otu-1,sizeof(int));
rates->curr_slice = (int *)mCalloc(2*n_otu-1,sizeof(int));
rates->has_survived = (int *)mCalloc(2*n_otu-1,sizeof(int));
rates->survival_rank = (phydbl *)mCalloc(2*n_otu-1,sizeof(phydbl));
rates->survival_dur = (phydbl *)mCalloc(2*n_otu-1,sizeof(phydbl));
}
return rates;
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void RATES_Free_Rates(t_rate *rates)
{
if(rates->is_allocated == YES)
{
Free(rates->nd_r);
Free(rates->br_r);
Free(rates->buff_r);
Free(rates->true_r);
Free(rates->buff_t);
Free(rates->nd_t);
Free(rates->true_t);
Free(rates->t_prior);
Free(rates->t_mean);
Free(rates->t_prior_min);
Free(rates->t_prior_max);
Free(rates->t_floor);
Free(rates->t_has_prior);
Free(rates->t_ranked);
Free(rates->dens);
Free(rates->triplet);
Free(rates->n_jps);
Free(rates->t_jps);
Free(rates->cond_var);
Free(rates->invcov);
Free(rates->ml_l);
Free(rates->cur_l);
Free(rates->u_ml_l);
Free(rates->u_cur_l);
Free(rates->cov_r);
Free(rates->lca);
Free(rates->trip_cond_cov);
Free(rates->trip_reg_coeff);
Free(rates->_2n_vect1);
Free(rates->_2n_vect2);
Free(rates->_2n_vect3);
Free(rates->_2n_vect4);
Free(rates->_2n_vect5);
Free(rates->_2n2n_vect1);
Free(rates->_2n2n_vect2);
Free(rates->cov_l);
Free(rates->mean_l);
Free(rates->mean_t);
Free(rates->grad_l);
Free(rates->br_do_updt);
Free(rates->cur_gamma_prior_mean);
Free(rates->cur_gamma_prior_var);
Free(rates->n_tips_below);
Free(rates->time_slice_lims);
Free(rates->n_time_slice_spans);
Free(rates->curr_slice);
Free(rates->has_survived);
Free(rates->survival_rank);
Free(rates->survival_dur);
}
Free(rates);
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void RATES_Init_Rate_Struct(t_rate *rates, t_rate *existing_rates, int n_otu)
{
int i;
if(existing_rates && (existing_rates->model != -1))
{
rates->model = existing_rates->model;
}
else
{
rates->model = NONE;
}
if(rates->model == NONE)
rates->model_log_rates = NO;
else if(rates->model == THORNE)
rates->model_log_rates = YES;
else if(rates->model == GUINDON)
rates->model_log_rates = YES;
else if(rates->model == GAMMA)
rates->model_log_rates = NO;
else if(rates->model == STRICTCLOCK)
rates->model_log_rates = NO;
else
{
PhyML_Printf("\n. Please initialize model properly.");
PhyML_Printf("\n. Err in file %s at line %d\n",__FILE__,__LINE__);
Warn_And_Exit("");
}
rates->met_within_gibbs = NO;
rates->c_lnL_rates = UNLIKELY;
rates->c_lnL_jps = UNLIKELY;
rates->adjust_rates = 0;
rates->use_rates = 1;
rates->lexp = 1.E-3;
rates->norm_fact = 1.0;
rates->inflate_var = 1.0;
rates->nd_t_recorded = NO;
rates->br_r_recorded = NO;
rates->birth_rate = 1.E-2;
rates->birth_rate_min = 1.E-3;
rates->birth_rate_max = 1.E+1;
if(rates->model_log_rates == YES)
{
rates->max_rate = LOG(10.);
rates->min_rate = -LOG(10.);
/* rates->max_rate = MDBL_MAX; */
/* rates->min_rate = -MDBL_MAX; */
}
else
{
rates->max_rate = 10.0;
rates->min_rate = 0.0;
}
/* rates->max_rate = 6.0; */
/* rates->min_rate = 0.0; */
rates->clock_r = 1.E-4;
rates->min_clock = 1.E-8;
rates->max_clock = 1.E-3;
/* rates->clock_r = 3.E-4; */
/* rates->max_clock = 1.E-3; */
/* rates->min_clock = 1.E-5; */
if(rates->model != GAMMA)
{
rates->nu = 1.E-3;
rates->min_nu = 0.0;
rates->max_nu = 1.0;
}
else
{
rates->nu = 1.E-1;
rates->min_nu = 1.E-2;
rates->max_nu = 100.0;
}
/* rates->max_nu = 2.0; */
/* rates->nu = 1.E-4; */
/* rates->max_nu = 1.E-1; */
/* rates->min_nu = 1.E-5; */
rates->min_dt = 0.0;
rates->step_rate = 1.E-4;
rates->approx = 1;
rates->bl_from_rt = 0;
rates->update_mean_l = NO;
rates->update_cov_l = NO;
rates->p_max = 0.01;
rates->true_tree_size = 0.0;
if(n_otu > 0)
{
For(i,(2*n_otu-2)*(2*n_otu-2)) rates->cov_l[i] = 0.0;
For(i,2*n_otu-2)
{
rates->n_jps[i] = -1;
rates->t_jps[i] = -1;
rates->mean_r[i] = 1.0;
rates->mean_l[i] = 0.0;
}
For(i,2*n_otu-1)
{
if(rates->model_log_rates == YES)
{
rates->nd_r[i] = 0.0;
rates->br_r[i] = 0.0;
}
else
{
rates->nd_r[i] = 1.0;
rates->br_r[i] = 1.0;
}
rates->mean_t[i] = 0.0;
rates->nd_t[i] = 0.0;
rates->true_t[i] = 0.0;
if(i < n_otu)
{
rates->t_has_prior[i] = YES;
rates->t_prior_max[i] = 0.0;
rates->t_prior_min[i] = 0.0;
}
else
{
rates->t_has_prior[i] = NO;
rates->t_prior_max[i] = BIG;
rates->t_prior_min[i] = -BIG;
}
rates->br_do_updt[i] = YES;
rates->has_survived[i] = NO;
rates->t_ranked[i] = i;
}
}
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void RATES_Bracket_N_Jumps(int *up, int *down, phydbl param)
{
phydbl cdf,eps,a,b,c;
int step;
step = 10;
eps = 1.E-10;
cdf = 0.0;
c = 1;
while(cdf < 1.-eps)
{
c = (int)FLOOR(c * step);
cdf = Ppois(c,param);
}
a = 0.0;
b = (c-a)/2.;
step = 0;
do
{
step++;
cdf = Ppois(b,param);
if(cdf < eps) a = b;
else
{
break;
}
b = (c-a)/2.;
}
while(step < 1000);
if(step == 1000)
{
PhyML_Printf("\n. a=%f b=%f c=%f param=%f",a,b,c,param);
PhyML_Printf("\n. Err in file %s at line %d\n",__FILE__,__LINE__);
Warn_And_Exit("");
}
*up = c;
*down = a;
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
/*
mu : average rate of the time period dt
dt : time period to be considered
a : rate at a given time point is gamma distributed. a is the shape parameter
b : rate at a given time point is gamma distributed. b is the scale parameter
lexp : the number of rate switches is Poisson distributed with parameter lexp * dt
*/
/* compute f(mu;dt,a,b,lexp), the probability density of mu. We need to integrate over the
possible number of jumps (n) during the time interval dt */
phydbl RATES_Dmu(phydbl mu, int n_jumps, phydbl dt, phydbl a, phydbl b, phydbl lexp, int min_n, int jps_dens)
{
if(n_jumps < 0) /* Marginal, i.e., the number of jumps is not fixed */
{
phydbl var,cumpoissprob,dens,mean,poissprob,ab2,gammadens,lexpdt,*suminv,b2;
int n,up,down;
var = 0.0;
cumpoissprob = 0.0;
dens = 0.0;
n = 0;
mean = a*b;
ab2 = a*b*b;
lexpdt = lexp*dt;
b2 = b*b;
suminv = NULL;
RATES_Bracket_N_Jumps(&up,&down,lexpdt);
For(n,MAX(down,min_n)-1) cumpoissprob += Dpois(n,lexpdt);
for(n=MAX(down,min_n);n 1.-1.E-04) break;
}
if(dens < 1.E-70) dens = 1.E-70;
return(dens);
}
else /* Joint, i.e., return P(mu | dt, n_jumps) */
{
phydbl mean, var, density;
mean = 1.0;
var = (2./(n_jumps+2.))*a*b*b;
if(jps_dens)
density = Dgamma_Moments(mu,mean,var) * Dpois(n_jumps,dt*lexp);
else
density = Dgamma_Moments(mu,mean,var);
if(density < 1.E-70) density = 1.E-70;
return density;
}
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
phydbl RATES_Dmu_One(phydbl mu, phydbl dt, phydbl a, phydbl b, phydbl lexp)
{
phydbl var,cumpoissprob,dens,mean,poissprob,ab2,gammadens,lexpdt,*suminv,b2;
int n,up,down;
var = 0.0;
cumpoissprob = 0.0;
dens = 0.0;
n = 0;
mean = a*b;
ab2 = a*b*b;
lexpdt = lexp*dt;
b2 = b*b;
suminv = NULL;
if(dt < 0.0)
{
PhyML_Printf("\n. dt=%f",dt);
PhyML_Printf("\n. Err in file %s at line %d\n",__FILE__,__LINE__);
Warn_And_Exit("");
}
if(lexpdt < SMALL)
{
PhyML_Printf("\n. lexpdt=%G lexp=%G dt=%G",lexpdt,lexp,dt);
PhyML_Printf("\n. Err in file %s at line %d\n",__FILE__,__LINE__);
Warn_And_Exit("");
}
if(mu < 1.E-10)
{
PhyML_Printf("\n. mu=%G",mu);
PhyML_Printf("\n. Err in file %s at line %d\n",__FILE__,__LINE__);
Warn_And_Exit("");
}
RATES_Bracket_N_Jumps(&up,&down,lexpdt);
For(n,MAX(1,down)-1) cumpoissprob += Dpois(n,lexpdt);
for(n=MAX(1,down);n 1.-1.E-06) break;
}
return(dens);
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
/* Given the times of nodes a (ta) and d (td), the shape of the gamma distribution of instantaneous
rates, the parameter of the exponential distribution of waiting times between rate jumps and the
instantaneous rate at t_node a, this function works out an expected number of (amino-acids or
nucleotide) substitutions per site.
*/
void RATES_Expect_Number_Subst(phydbl t_beg, phydbl t_end, phydbl r_beg, int *n_jumps, phydbl *mean_r, phydbl *r_end, t_rate *rates, t_tree *tree)
{
phydbl curr_r, curr_t, next_t;
switch(rates->model)
{
case COMPOUND_COR:case COMPOUND_NOCOR:
{
/* Compound Poisson */
if(rates->model == COMPOUND_COR)
{
curr_r = r_beg;
*mean_r = r_beg;
}
else
{
curr_r = Rgamma(rates->nu,1./rates->nu);;
*mean_r = curr_r;
}
curr_t = t_beg + Rexp(rates->lexp); /* Exponentially distributed waiting times */
next_t = curr_t;
*n_jumps = 0;
while(curr_t < t_end)
{
curr_r = Rgamma(rates->nu,1./rates->nu); /* Gamma distributed random instantaneous rate */
(*n_jumps)++;
next_t = curr_t + Rexp(rates->lexp);
if(next_t < t_end)
{
*mean_r = (1./(next_t - t_beg)) * (*mean_r * (curr_t - t_beg) + curr_r * (next_t - curr_t));
}
else
{
*mean_r = (1./(t_end - t_beg)) * (*mean_r * (curr_t - t_beg) + curr_r * (t_end - curr_t));
}
curr_t = next_t;
}
/* PhyML_Printf("\n. [%3d %f %f]",*n_jumps,*mean_r,r_beg); */
if(*mean_r < rates->min_rate) *mean_r = rates->min_rate;
if(*mean_r > rates->max_rate) *mean_r = rates->max_rate;
*r_end = curr_r;
break;
}
case EXPONENTIAL:
{
*mean_r = Rexp(rates->nu);
if(*mean_r < rates->min_rate) *mean_r = rates->min_rate;
if(*mean_r > rates->max_rate) *mean_r = rates->max_rate;
*r_end = *mean_r;
break;
}
case GAMMA:
{
*mean_r = Rgamma(rates->nu,1./rates->nu);
if(*mean_r < rates->min_rate) *mean_r = rates->min_rate;
if(*mean_r > rates->max_rate) *mean_r = rates->max_rate;
*r_end = *mean_r;
break;
}
case THORNE:
{
phydbl sd,mean;
int err;
sd = SQRT(rates->nu*FABS(t_beg-t_end));
mean = r_beg;
*mean_r = Rnorm_Trunc(mean,sd,rates->min_rate,rates->max_rate,&err);
if(err) PhyML_Printf("\n. %s %d %d",__FILE__,__LINE__,tree->mcmc->run);
*r_end = *mean_r;
break;
}
default:
{
PhyML_Printf("\n. Err in file %s at line %d\n",__FILE__,__LINE__);
Exit("\n. Model not implemented yet.\n");
break;
}
}
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void RATES_Get_Mean_Rates_Pre(t_node *a, t_node *d, t_edge *b, phydbl r_a, t_tree *tree)
{
phydbl a_t,d_t;
phydbl mean_r;
int n_jumps;
phydbl r_d;
a_t = tree->rates->nd_t[a->num];
d_t = tree->rates->nd_t[d->num];
RATES_Expect_Number_Subst(a_t,d_t,r_a,&n_jumps,&mean_r,&r_d,tree->rates,tree);
tree->rates->br_r[d->num] = mean_r;
tree->rates->true_r[d->num] = mean_r;
tree->rates->t_jps[d->num] = n_jumps;
/* Move to the next branches */
if(d->tax) return;
else
{
int i;
For(i,3)
{
if((d->v[i] != a) && (d->b[i] != tree->e_root))
{
RATES_Get_Mean_Rates_Pre(d,d->v[i],d->b[i],r_d,tree);
}
}
}
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void RATES_Random_Branch_Lengths(t_tree *tree)
{
phydbl r0,r_d;
r0 = 1.0;
r_d = 0;
tree->rates->br_r[tree->n_root->num] = r0;
RATES_Get_Mean_Rates_Pre(tree->n_root,tree->n_root->v[0],NULL,r0,tree);
RATES_Get_Mean_Rates_Pre(tree->n_root,tree->n_root->v[1],NULL,r0,tree);
/* RATES_Normalise_Rates(tree); */
RATES_Update_Cur_Bl(tree);
RATES_Initialize_True_Rates(tree);
tree->n_root_pos =
tree->rates->cur_l[tree->n_root->v[0]->num] /
(tree->rates->cur_l[tree->n_root->v[0]->num] + tree->rates->cur_l[tree->n_root->v[1]->num]);
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void RATES_Set_Node_Times(t_tree *tree)
{
RATES_Set_Node_Times_Pre(tree->n_root,tree->n_root->v[0],tree);
RATES_Set_Node_Times_Pre(tree->n_root,tree->n_root->v[1],tree);
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void RATES_Init_Triplets(t_tree *tree)
{
int i;
For(i,2*tree->n_otu-1) tree->rates->triplet[i] = 0.0;
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void RATES_Set_Node_Times_Pre(t_node *a, t_node *d, t_tree *tree)
{
if(d->tax) return;
else
{
t_node *v1, *v2; /* the two sons of d */
phydbl t_sup, t_inf;
int i;
v1 = v2 = NULL;
For(i,3) if((d->v[i] != a) && (d->b[i] != tree->e_root))
{
if(!v1) v1 = d->v[i];
else v2 = d->v[i];
}
t_inf = MIN(tree->rates->nd_t[v1->num],tree->rates->nd_t[v2->num]);
t_sup = tree->rates->nd_t[a->num];
if(t_sup > t_inf)
{
PhyML_Printf("\n. t_sup = %f t_inf = %f",t_sup,t_inf);
PhyML_Printf("\n. Run = %d",tree->mcmc->run);
PhyML_Printf("\n. Err in file %s at line %d\n",__FILE__,__LINE__);
Warn_And_Exit("");
}
if(tree->rates->nd_t[d->num] > t_inf)
{
tree->rates->nd_t[d->num] = t_inf;
PhyML_Printf("\n. Time for t_node %d is larger than should be. Set it to %f",d->num,tree->rates->nd_t[d->num]);
}
else if(tree->rates->nd_t[d->num] < t_sup)
{
tree->rates->nd_t[d->num] = t_sup;
PhyML_Printf("\n. Time for t_node %d is lower than should be. Set it to %f",d->num,tree->rates->nd_t[d->num]);
}
For(i,3)
{
if((d->v[i] != a) && (d->b[i] != tree->e_root))
{
RATES_Set_Node_Times_Pre(d,d->v[i],tree);
}
}
}
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
phydbl RATES_Dmu1_And_Mu2_One_Jump_Two_Intervals(phydbl mu1, phydbl mu2, phydbl dt1, phydbl dt2, phydbl alpha, phydbl beta)
{
phydbl dens;
if(mu2 < 1.E-10)
{
PhyML_Printf("\n. mu2=%G",mu2);
PhyML_Printf("\n. Err in file %s at line %d\n",__FILE__,__LINE__);
Warn_And_Exit("");
}
if(mu1 < 1.E-10)
{
PhyML_Printf("\n. mu2=%G",mu1);
PhyML_Printf("\n. Err in file %s at line %d\n",__FILE__,__LINE__);
Warn_And_Exit("");
}
dens =
((dt1/(dt1+dt2)) * RATES_Dmu1_Given_V_And_N(mu1,mu2,1,dt1,alpha,beta) * Dgamma(mu2,alpha,beta)) +
((dt2/(dt1+dt2)) * RATES_Dmu1_Given_V_And_N(mu2,mu1,1,dt2,alpha,beta) * Dgamma(mu1,alpha,beta));
return dens;
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
phydbl RATES_Dmu1_Given_V_And_N(phydbl mu1, phydbl v, int n, phydbl dt1, phydbl a, phydbl b)
{
phydbl lbda,dens,h,u;
phydbl mean,var;
int n_points,i;
phydbl ndb;
phydbl end, beg;
n_points = 20;
end = MIN(mu1/v-0.01,0.99);
beg = 0.01;
dens = 0.0;
if(end > beg)
{
mean = a*b;
var = a*b*b*2./(n+1.);
ndb = (phydbl)n/dt1;
h = (end - beg) / (phydbl)n_points;
lbda = beg;
For(i,n_points-1)
{
lbda += h;
u = (mu1 - lbda*v)/(1.-lbda);
if(u < 1.E-10)
{
PhyML_Printf("\n. u = %G",u);
PhyML_Printf("\n. Err in file %s at line %d\n",__FILE__,__LINE__);
Warn_And_Exit("");
}
dens += Dgamma_Moments(u,mean,var) / (1.-lbda) * ndb * POW(1.-lbda,n-1);
}
dens *= 2.;
lbda = beg;
u = (mu1 - lbda*v)/(1.-lbda);
if(u < 1.E-10)
{
PhyML_Printf("\n. mu1 = %f lambda = %f v = %f u = %G beg = %f end = %f",mu1,lbda,v,u,beg,end);
PhyML_Printf("\n. Err in file %s at line %d\n",__FILE__,__LINE__);
Warn_And_Exit("");
}
dens += Dgamma_Moments(u,mean,var) / (1.-lbda) * ndb * POW(1.-lbda,n-1);
lbda = end;
u = (mu1 - lbda*v)/(1.-lbda);
if(u < 1.E-10)
{
PhyML_Printf("\n. u = %G",u);
PhyML_Printf("\n. Err in file %s at line %d\n",__FILE__,__LINE__);
Warn_And_Exit("");
}
dens += Dgamma_Moments(u,mean,var) / (1.-lbda) * ndb * POW(1.-lbda,n-1);
dens *= (h/2.);
dens *= dt1;
}
return(dens);
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
/* Joint density of mu1 and a minimum number of jumps occuring in the interval dt1+dt2 given mu1.
1 jump occurs at the junction of the two intervals, which makes mu1 and mu2 independant */
phydbl RATES_Dmu2_And_Mu1_Given_Min_N(phydbl mu1, phydbl mu2, phydbl dt1, phydbl dt2, int n_min, phydbl a, phydbl b, phydbl lexp)
{
phydbl density, lexpdt,cumpoiss,poiss;
int i;
int up,down;
density = 0.0;
lexpdt = lexp * (dt1+dt2);
cumpoiss = 0.0;
RATES_Bracket_N_Jumps(&up,&down,lexpdt);
For(i,MAX(up,n_min)-1)
{
poiss = Dpois(i,lexpdt);
cumpoiss = cumpoiss + poiss;
}
for(i=MAX(up,n_min);i 1.-1.E-6) break;
}
if(density < 0.0)
{
PhyML_Printf("\n. density=%f cmpoiss = %f i=%d n_min=%d mu1=%f mu2=%f dt1=%f dt2=%f",
density,cumpoiss,i,n_min,mu1,mu2,dt1,dt2);
PhyML_Printf("\n. Err in file %s at line %d\n",__FILE__,__LINE__);
Warn_And_Exit("");
}
return(density);
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
/* Joint density of mu1 and mu2 given the number of jumps (n) in the interval dt1+dt2, which are considered
as independant. Hence, for n jumps occuring in dt1+dt2, the number of jumps occuring in dt1 and dt2 are
n and 0, or n-1 and 1, or n-2 and 2 ... or 0 and n. This function sums over all these scenarios, with
weights corresponding to the probability of each partitition.
*/
phydbl RATES_Dmu2_And_Mu1_Given_N(phydbl mu1, phydbl mu2, phydbl dt1, phydbl dt2, int n, phydbl a, phydbl b, phydbl lexp)
{
phydbl density,lexpdt1,lexpdt2,texpn,cumpoiss,poiss,abb,ab,LOGnf,LOGdt1,LOGdt2,nLOGdt;
int i;
density = 0.0;
lexpdt1 = lexp*dt1;
lexpdt2 = lexp*dt2;
texpn = POW(dt1+dt2,n);
abb = a*b*b;
ab = a*b;
cumpoiss = 0.0;
poiss = 0.0;
LOGnf = LnFact(n);
LOGdt1 = LOG(dt1);
LOGdt2 = LOG(dt2);
nLOGdt = n*LOG(dt1+dt2);
For(i,n+1)
{
poiss = LOGnf - LnFact(i) - LnFact(n-i) + i*LOGdt1 + (n-i)*LOGdt2 - nLOGdt;
poiss = EXP(poiss);
cumpoiss = cumpoiss + poiss;
if(mu2 < 1.E-10)
{
PhyML_Printf("\n. mu2=%f",mu2);
PhyML_Printf("\n. Err in file %s at line %d\n",__FILE__,__LINE__);
Warn_And_Exit("");
}
if(mu1 < 1.E-10)
{
PhyML_Printf("\n. mu1=%f",mu1);
PhyML_Printf("\n. Err in file %s at line %d\n",__FILE__,__LINE__);
Warn_And_Exit("");
}
density = density + poiss * Dgamma_Moments(mu2,ab,2./((n-i)+2.)*abb) * Dgamma_Moments(mu1,ab,2./(i+2.)*abb);
if(cumpoiss > 1.-1.E-6) break;
}
return(density);
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void RATES_Initialize_True_Rates(t_tree *tree)
{
int i;
For(i,2*tree->n_otu-2) tree->rates->true_r[i] = tree->rates->br_r[i];
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void RATES_Get_Rates_From_Bl(t_tree *tree)
{
phydbl dt,cr;
t_node *left, *rght;
int i;
dt = -1.0;
cr = tree->rates->clock_r;
if(tree->n_root)
{
dt = FABS(tree->rates->nd_t[tree->n_root->num] - tree->rates->nd_t[tree->n_root->v[0]->num]);
tree->rates->br_r[tree->n_root->v[0]->num] = 0.5 * tree->e_root->l / (dt*cr);
dt = FABS(tree->rates->nd_t[tree->n_root->num] - tree->rates->nd_t[tree->n_root->v[1]->num]);
tree->rates->br_r[tree->n_root->v[1]->num] = 0.5 * tree->e_root->l / (dt*cr);
}
For(i,2*tree->n_otu-3)
{
if(tree->t_edges[i] != tree->e_root)
{
left = tree->t_edges[i]->left;
rght = tree->t_edges[i]->rght;
dt = FABS(tree->rates->nd_t[left->num] - tree->rates->nd_t[rght->num]);
if(left->anc == rght) tree->rates->br_r[left->num] = tree->t_edges[i]->l / (dt*cr);
else tree->rates->br_r[rght->num] = tree->t_edges[i]->l / (dt*cr);
}
}
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
phydbl RATES_Lk_Jumps(t_tree *tree)
{
int i,n_jps;
phydbl dens,dt,lexp;
t_node *n;
n = NULL;
lexp = tree->rates->lexp;
n_jps = 0;
dt = 0.0;
dens = 0.0;
For(i,2*tree->n_otu-2)
{
n = tree->t_nodes[i];
dt = FABS(tree->rates->nd_t[n->num]-tree->rates->nd_t[n->anc->num]);
n_jps = tree->rates->n_jps[n->num];
dens += LOG(Dpois(n_jps,lexp*dt));
}
tree->rates->c_lnL_jps = dens;
return dens;
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void RATES_Posterior_Rates(t_tree *tree)
{
int node_num;
node_num = Rand_Int(0,2*tree->n_otu-3);
RATES_Posterior_One_Rate(tree->t_nodes[node_num]->anc,tree->t_nodes[node_num],NO,tree);
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void RATES_Posterior_Times(t_tree *tree)
{
int node_num;
node_num = Rand_Int(tree->n_otu,2*tree->n_otu-3);
RATES_Posterior_One_Time(tree->t_nodes[node_num]->anc,tree->t_nodes[node_num],NO,tree);
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void RATES_Posterior_One_Rate(t_node *a, t_node *d, int traversal, t_tree *tree)
{
phydbl like_mean, like_var;
phydbl prior_mean, prior_var;
phydbl post_mean, post_var, post_sd;
phydbl dt,ra,rd,cr,nu,cel,cvl;
phydbl cur_l;
int dim;
short int *is_1;
phydbl *cond_mu, *cond_cov;
phydbl l_opp; /* length of the branch connected to the root, opposite to the one connected to d */
t_edge *b;
int i;
t_node *v2,*v3;
phydbl T0,T1,T2,T3;
phydbl U0,U1,U2,U3;
phydbl V1,V2,V3;
phydbl r_min,r_max;
int err;
phydbl ratio,u;
phydbl cvr, cer;
phydbl nf;
phydbl new_lnL_data, cur_lnL_data, new_lnL_rate, cur_lnL_rate;
phydbl sd1,sd2,sd3;
phydbl inflate_var;
if(d == tree->n_root) return;
dim = 2*tree->n_otu-3;
err = NO;
is_1 = tree->rates->_2n_vect5;
cond_mu = tree->rates->_2n_vect1;
cond_cov = tree->rates->_2n2n_vect1;
inflate_var = tree->rates->inflate_var;
b = NULL;
if(a == tree->n_root) b = tree->e_root;
else For(i,3) if(d->v[i] == a) { b = d->b[i]; break; }
v2 = v3 = NULL;
if(!d->tax)
{
For(i,3)
if((d->v[i] != a) && (d->b[i] != tree->e_root))
{
if(!v2) { v2 = d->v[i]; }
else { v3 = d->v[i]; }
}
}
T3 = T2 = 0.0;
T0 = tree->rates->nd_t[a->num];
T1 = tree->rates->nd_t[d->num];
U0 = tree->rates->br_r[a->num];
U1 = tree->rates->br_r[d->num];
U3 = U2 = -1.0;
if(!d->tax)
{
T2 = tree->rates->nd_t[v2->num];
T3 = tree->rates->nd_t[v3->num];
U2 = tree->rates->br_r[v2->num];
U3 = tree->rates->br_r[v3->num];
}
V1 = tree->rates->nu * FABS(T1 - T0);
V2 = tree->rates->nu * FABS(T2 - T1);
V3 = tree->rates->nu * FABS(T3 - T1);
dt = T1 - T0;
ra = U0;
rd = U1;
cr = tree->rates->clock_r;
nu = tree->rates->nu;
cur_l = tree->rates->cur_l[d->num];
r_min = tree->rates->min_rate;
r_max = tree->rates->max_rate;
nf = tree->rates->norm_fact;
sd1 = SQRT(V1);
sd2 = SQRT(V2);
sd3 = SQRT(V3);
/* Likelihood */
cel=0.0;
For(i,dim)
if(i != b->num)
cel += tree->rates->reg_coeff[b->num*dim+i] * (tree->rates->u_cur_l[i] - tree->rates->mean_l[i]);
cel += tree->rates->mean_l[b->num];
cvl = tree->rates->cond_var[b->num];
l_opp = 0.0;
if(a == tree->n_root)
{
if(d == a->v[0]) l_opp = tree->rates->cur_l[a->v[1]->num];
else l_opp = tree->rates->cur_l[a->v[0]->num];
cel -= l_opp;
}
if(isnan(cvl) || isnan(cel) || cvl < .0)
{
For(i,dim) if(i != b->num) printf("\n. reg: %f %f %f nu=%f clock=%f",
tree->rates->reg_coeff[b->num*dim+i],
tree->rates->u_cur_l[i],
tree->rates->mean_l[i],
tree->rates->nu,tree->rates->clock_r);
PhyML_Printf("\n. cel=%f cvl=%f\n",cel,cvl);
PhyML_Printf("\n. Warning: invalid expected and/or std. dev. values. Skipping this step.\n");
Exit("\n");
}
/* Model rates */
/* if(tree->mod->log_l == YES) cel = EXP(cel); */
/* like_mean = cel / (dt*cr*nf); */
/* like_var = cvl / POW(dt*cr*nf,2); */
/* Model log of rates. Branch lengths are given in log units */
if(tree->rates->model_log_rates == YES)
{
like_mean = cel - LOG(dt*cr*nf);
like_var = cvl - 2.*LOG(dt*cr*nf);
}
else
{
like_mean = cel / (dt*cr*nf);
like_var = cvl / POW(dt*cr*nf,2);
}
/* Prior */
if(!d->tax)
{
cvr = 1./(1./V1 + 1./V2 + 1./V3);
cer = cvr*(U0/V1 + U2/V2 + U3/V3);
}
else
{
cvr = V1;
cer = U0;
}
if(cvr < 0.0)
{
PhyML_Printf("\n. cvr=%f d->tax=%d V1=%f v2=%f V3=%f",cvr,d->tax,V1,V2,V3);
PhyML_Printf("\n. T0=%f T1=%f T2=%f T3=%f",T0,T1,T2,T3);
Exit("\n");
}
prior_mean = cer;
prior_var = cvr;
/* Posterior */
post_mean = (prior_mean/prior_var + like_mean/like_var)/(1./prior_var + 1./like_var);
post_var = 1./(1./prior_var + 1./like_var);
/* Sample according to priors */
if(tree->mcmc->use_data == NO)
{
post_mean = prior_mean;
post_var = prior_var;
}
post_sd = SQRT(post_var);
rd = Rnorm_Trunc(post_mean,inflate_var*post_sd,r_min,r_max,&err);
if(err || isnan(rd))
{
PhyML_Printf("\n");
PhyML_Printf("\n. run: %d err=%d d->tax=%d",tree->mcmc->run,err,d->tax);
PhyML_Printf("\n. rd=%f cvr=%G dt=%G cr=%G",rd,cvr,dt,cr);
PhyML_Printf("\n. prior_mean = %G prior_var = %G",prior_mean,prior_var);
PhyML_Printf("\n. like_mean = %G like_var = %G",like_mean,like_var);
PhyML_Printf("\n. post_mean = %G post_var = %G",post_mean,post_var);
PhyML_Printf("\n. clock_r = %f",tree->rates->clock_r);
PhyML_Printf("\n. T0=%f T1=%f T2=%f T3=%f",T0,T1,T2,T3);
PhyML_Printf("\n. U0=%f U1=%f U2=%f U3=%f",U0,U1,U2,U3);
PhyML_Printf("\n. Err in file %s at line %d\n",__FILE__,__LINE__);
Exit("\n");
}
/* !!!!!!!!!!!!!! */
/* u = Uni(); */
/* rd = U1 * EXP(1.*(u-0.5)); */
if(rd > r_min && rd < r_max)
{
cur_lnL_data = tree->c_lnL;
cur_lnL_rate = tree->rates->c_lnL_rates;
new_lnL_data = tree->c_lnL;
new_lnL_rate = tree->rates->c_lnL_rates;
tree->rates->br_r[d->num] = rd;
RATES_Update_Norm_Fact(tree);
RATES_Update_Cur_Bl(tree);
if(tree->mcmc->use_data) new_lnL_data = Lk_At_Given_Edge(b,tree);
/* new_lnL_rate = RATES_Lk_Rates(tree); */
new_lnL_rate =
cur_lnL_rate -
(Log_Dnorm_Trunc(U1,U0,sd1,r_min,r_max,&err)) +
(Log_Dnorm_Trunc(rd,U0,sd1,r_min,r_max,&err));
if(!d->tax)
{
new_lnL_rate -= (Log_Dnorm_Trunc(U2,U1,sd2,r_min,r_max,&err) + Log_Dnorm_Trunc(U3,U1,sd3,r_min,r_max,&err));
new_lnL_rate += (Log_Dnorm_Trunc(U2,rd,sd2,r_min,r_max,&err) + Log_Dnorm_Trunc(U3,rd,sd3,r_min,r_max,&err));
}
tree->rates->c_lnL_rates = new_lnL_rate;
/* printf("\n. %f %f sd1=%f U1=%f rd=%f ra=%f a=%d d=%d [%f] [%f %f]", */
/* new_lnL_rate,RATES_Lk_Rates(tree),sd1,U1,rd,ra,a->num,d->num,tree->rates->br_r[tree->n_root->num], */
/* Log_Dnorm_Trunc(U1,ra,sd1,r_min,r_max,&err), */
/* Log_Dnorm_Trunc(rd,ra,sd1,r_min,r_max,&err)); */
ratio = 0.0;
/* Proposal ratio */
ratio += (Log_Dnorm_Trunc(U1,post_mean,inflate_var*post_sd,r_min,r_max,&err) - Log_Dnorm_Trunc(rd,post_mean,inflate_var*post_sd,r_min,r_max,&err));
/* ratio += LOG(rd/U1); */
/* Prior ratio */
ratio += (new_lnL_rate - cur_lnL_rate);
/* Likelihood ratio */
ratio += (new_lnL_data - cur_lnL_data);
ratio = EXP(ratio);
/* printf("\n. R a=%3d T0=%6.1f T1=%6.1f T2=%6.1f T3=%6.1f ratio=%8f pm=%7f U1=%7.2f rd=%7.2f %f %f lr=%f %f ld=%f %f [%f]",a->num,T0,T1,T2,T3,ratio,post_mean,U1,rd, */
/* Log_Dnorm_Trunc(U1,post_mean,post_sd,r_min,r_max,&err), */
/* Log_Dnorm_Trunc(rd,post_mean,post_sd,r_min,r_max,&err), */
/* new_lnL_rate,cur_lnL_rate, */
/* new_lnL_data,cur_lnL_data, */
/* ((Pnorm(r_max,U1,sd2)-Pnorm(r_min,U1,sd2)) * */
/* (Pnorm(r_max,U1,sd3)-Pnorm(r_min,U1,sd3)))/ */
/* ((Pnorm(r_max,rd,sd2)-Pnorm(r_min,rd,sd2)) * */
/* (Pnorm(r_max,rd,sd3)-Pnorm(r_min,rd,sd3)))); */
u = Uni();
if(u > MIN(1.,ratio))
{
tree->rates->br_r[d->num] = U1; /* reject */
tree->rates->c_lnL_rates = cur_lnL_rate;
tree->c_lnL = cur_lnL_data;
RATES_Update_Cur_Bl(tree);
Update_PMat_At_Given_Edge(b,tree);
}
else
{
tree->mcmc->acc_move[tree->mcmc->num_move_br_r+d->num]++;
}
RATES_Update_Norm_Fact(tree);
tree->mcmc->acc_rate[tree->mcmc->num_move_br_r+d->num] =
(tree->mcmc->acc_move[tree->mcmc->num_move_br_r+d->num]+1.E-6)/
(tree->mcmc->run_move[tree->mcmc->num_move_br_r+d->num]+1.E-6);
}
tree->mcmc->run_move[tree->mcmc->num_move_br_r+d->num]++;
if(traversal == YES)
{
if(d->tax == YES) return;
else
{
For(i,3)
if(d->v[i] != a && d->b[i] != tree->e_root)
{
if(tree->io->lk_approx == EXACT && tree->mcmc->use_data) Update_P_Lk(tree,d->b[i],d);
/* if(tree->io->lk_approx == EXACT && tree->mcmc->use_data) { tree->both_sides = YES; Lk(tree); } */
RATES_Posterior_One_Rate(d,d->v[i],YES,tree);
}
}
if(tree->io->lk_approx == EXACT && tree->mcmc->use_data) Update_P_Lk(tree,b,d);
/* if(tree->io->lk_approx == EXACT && tree->mcmc->use_data) { tree->both_sides = YES; Lk(tree); } */
}
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void RATES_Posterior_One_Time(t_node *a, t_node *d, int traversal, t_tree *tree)
{
/*
T0 (a)
|
| l1,U1,b1
|
T1 (d)
/ \
l2,u2,b2 / \ L3,u3,b3
/ \
t2 t3
(v2) (v3)
*/
phydbl l1,l2,l3;
phydbl new_l1;
phydbl El1,El2,El3;
phydbl u0,r1,r2,r3;
phydbl t0,t1,t2,t3;
phydbl t_min, t_max;
/* phydbl t_max_12,t_max_13; */
phydbl bl_min, bl_max;
phydbl t1_new;
phydbl EX,EY;
phydbl VX,VY;
phydbl cr;
int i,j;
phydbl *mu, *cov;
phydbl *cond_mu, *cond_cov;
short int *is_1;
phydbl sig11, sig1X, sig1Y, sigXX, sigXY, sigYY;
phydbl cov11,cov12,cov13,cov22,cov23,cov33;
int dim;
t_edge *b1, *b2, *b3;
t_node *v2,*v3;
phydbl *l2XY;
phydbl l_opp;
t_edge *buff_b;
t_node *buff_n;
int err;
int num_1, num_2, num_3;
phydbl nf;
phydbl u, ratio;
phydbl new_lnL_data, cur_lnL_data, new_lnL_rate, cur_lnL_rate;
int num_move;
phydbl inflate_var;
dim = 2*tree->n_otu-3;
num_move = tree->mcmc->num_move_nd_t+d->num-tree->n_otu;
inflate_var = tree->rates->inflate_var;
if(d->tax) return;
if(FABS(tree->rates->t_prior_min[d->num] - tree->rates->t_prior_max[d->num]) < 1.E-10) return;
l2XY = tree->rates->_2n_vect2;
mu = tree->rates->_2n_vect3;
cov = tree->rates->_2n2n_vect1;
cond_mu = tree->rates->_2n_vect1;
cond_cov = tree->rates->_2n2n_vect2;
is_1 = tree->rates->_2n_vect5;
err = NO;
b1 = NULL;
if(a == tree->n_root) b1 = tree->e_root;
else For(i,3) if(d->v[i] == a) { b1 = d->b[i]; break; }
b2 = b3 = NULL;
v2 = v3 = NULL;
For(i,3)
if((d->v[i] != a) && (d->b[i] != tree->e_root))
{
if(!v2) { v2 = d->v[i]; b2 = d->b[i]; }
else { v3 = d->v[i]; b3 = d->b[i]; }
}
t2 = tree->rates->nd_t[v2->num];
t3 = tree->rates->nd_t[v3->num];
buff_n = NULL;
buff_b = NULL;
if(t3 > t2)
{
buff_n = v2;
v2 = v3;
v3 = buff_n;
buff_b = b2;
b2 = b3;
b3 = buff_b;
}
t0 = tree->rates->nd_t[a->num];
t1 = tree->rates->nd_t[d->num];
t2 = tree->rates->nd_t[v2->num];
t3 = tree->rates->nd_t[v3->num];
u0 = tree->rates->br_r[a->num];
r1 = tree->rates->br_r[d->num];
r2 = tree->rates->br_r[v2->num];
r3 = tree->rates->br_r[v3->num];
l1 = tree->rates->cur_l[d->num];
l2 = tree->rates->cur_l[v2->num];
l3 = tree->rates->cur_l[v3->num];
cr = tree->rates->clock_r;
nf = tree->rates->norm_fact;
For(i,dim) is_1[i] = 0;
is_1[b1->num] = 1;
is_1[b2->num] = 1;
is_1[b3->num] = 1;
/* For(i,dim) cond_mu[i] = 0.0; */
/* For(i,dim*dim) cond_cov[i] = 0.0; */
/* Normal_Conditional(tree->rates->mean_l,tree->rates->cov_l,tree->rates->u_cur_l,dim,is_1,3,cond_mu,cond_cov); */
/* El1 = cond_mu[b1->num]; */
/* El2 = cond_mu[b2->num]; */
/* El3 = cond_mu[b3->num]; */
/* cov11 = cond_cov[b1->num*dim+b1->num]; */
/* cov12 = cond_cov[b1->num*dim+b2->num]; */
/* cov13 = cond_cov[b1->num*dim+b3->num]; */
/* cov23 = cond_cov[b2->num*dim+b3->num]; */
/* cov22 = cond_cov[b2->num*dim+b2->num]; */
/* cov33 = cond_cov[b3->num*dim+b3->num]; */
/* El1 = tree->rates->u_ml_l[b1->num]; */
/* El2 = tree->rates->u_ml_l[b2->num]; */
/* El3 = tree->rates->u_ml_l[b3->num]; */
/* cov11 = tree->rates->cov[b1->num*dim+b1->num]; */
/* cov12 = tree->rates->cov[b1->num*dim+b2->num]; */
/* cov13 = tree->rates->cov[b1->num*dim+b3->num]; */
/* cov23 = tree->rates->cov[b2->num*dim+b3->num]; */
/* cov22 = tree->rates->cov[b2->num*dim+b2->num]; */
/* cov33 = tree->rates->cov[b3->num*dim+b3->num]; */
/* PhyML_Printf("\n- El1=%10f El2=%10f El3=%10f",El1,El2,El3); */
/* PhyML_Printf("\n- cov11=%10f cov12=%10f cov13=%10f cov23=%10f cov22=%10f cov33=%10f", cov11,cov12,cov13,cov23,cov22,cov33); */
num_1 = num_2 = num_3 = -1;
if(b1->num < b2->num && b2->num < b3->num) { num_1 = 0; num_2 = 1; num_3 = 2; }
if(b1->num < b3->num && b3->num < b2->num) { num_1 = 0; num_2 = 2; num_3 = 1; }
if(b2->num < b1->num && b1->num < b3->num) { num_1 = 1; num_2 = 0; num_3 = 2; }
if(b2->num < b3->num && b3->num < b1->num) { num_1 = 2; num_2 = 0; num_3 = 1; }
if(b3->num < b2->num && b2->num < b1->num) { num_1 = 2; num_2 = 1; num_3 = 0; }
if(b3->num < b1->num && b1->num < b2->num) { num_1 = 1; num_2 = 2; num_3 = 0; }
cov11 = tree->rates->trip_cond_cov[d->num * 9 + num_1 * 3 + num_1];
cov12 = tree->rates->trip_cond_cov[d->num * 9 + num_1 * 3 + num_2];
cov13 = tree->rates->trip_cond_cov[d->num * 9 + num_1 * 3 + num_3];
cov23 = tree->rates->trip_cond_cov[d->num * 9 + num_2 * 3 + num_3];
cov22 = tree->rates->trip_cond_cov[d->num * 9 + num_2 * 3 + num_2];
cov33 = tree->rates->trip_cond_cov[d->num * 9 + num_3 * 3 + num_3];
El1=0.0;
For(i,dim)
if(i != b1->num && i != b2->num && i != b3->num)
El1 += tree->rates->trip_reg_coeff[d->num * (6*tree->n_otu-9) + num_1 * dim +i] * (tree->rates->u_cur_l[i] - tree->rates->mean_l[i]);
El1 += tree->rates->mean_l[b1->num];
El2=0.0;
For(i,dim)
if(i != b1->num && i != b2->num && i != b3->num)
El2 += tree->rates->trip_reg_coeff[d->num * (6*tree->n_otu-9) + num_2 * dim +i] * (tree->rates->u_cur_l[i] - tree->rates->mean_l[i]);
El2 += tree->rates->mean_l[b2->num];
El3=0.0;
For(i,dim)
if(i != b1->num && i != b2->num && i != b3->num)
El3 += tree->rates->trip_reg_coeff[d->num * (6*tree->n_otu-9) + num_3 * dim +i] * (tree->rates->u_cur_l[i] - tree->rates->mean_l[i]);
El3 += tree->rates->mean_l[b3->num];
/* PhyML_Printf("\n+ El1=%10f El2=%10f El3=%10f",El1,El2,El3); */
/* PhyML_Printf("\n+ cov11=%10f cov12=%10f cov13=%10f cov23=%10f cov22=%10f cov33=%10f", cov11,cov12,cov13,cov23,cov22,cov33); */
t1_new = +1;
t_min = MAX(t0,tree->rates->t_prior_min[d->num]);
t_max = MIN(MIN(t2,t3),tree->rates->t_prior_max[d->num]);
t_min += tree->rates->min_dt;
t_max -= tree->rates->min_dt;
if(t_min > t_max)
{
PhyML_Printf("\n. Err in file %s at line %d\n",__FILE__,__LINE__);
Exit("\n");
}
bl_min = bl_max = -1.0;
l_opp = 0.0;
if(a == tree->n_root)
{
l_opp = (d == a->v[0])?(tree->rates->cur_l[a->v[1]->num]):(tree->rates->cur_l[a->v[0]->num]);
El1 -= l_opp;
}
EX = El1/r1 + El2/r2;
EY = El1/r1 + El3/r3;
VX = cov11/(r1*r1) + cov22/(r2*r2) + 2.*cov12/(r1*r2);
VY = cov11/(r1*r1) + cov33/(r3*r3) + 2.*cov13/(r1*r3);
mu[0] = El1;
mu[1] = EX;
mu[2] = EY;
sig11 = cov11;
sig1X = cov11/r1 + cov12/r2;
sig1Y = cov11/r1 + cov13/r3;
sigXX = VX;
sigYY = VY;
sigXY = cov11/(r1*r1) + cov13/(r1*r3) + cov12/(r1*r2) + cov23/(r2*r3);
cov[0*3+0] = sig11; cov[0*3+1] = sig1X; cov[0*3+2] = sig1Y;
cov[1*3+0] = sig1X; cov[1*3+1] = sigXX; cov[1*3+2] = sigXY;
cov[2*3+0] = sig1Y; cov[2*3+1] = sigXY; cov[2*3+2] = sigYY;
l2XY[0] = 0.0; /* does not matter */
l2XY[1] = (t2-t0)*cr*nf; /* constraint 1 */
l2XY[2] = (t3-t0)*cr*nf; /* constraint 2 */
is_1[0] = is_1[1] = is_1[2] = 0;
is_1[0] = 1;
Normal_Conditional(mu,cov,l2XY,3,is_1,1,cond_mu,cond_cov);
if(cond_cov[0*3+0] < 0.0)
{
PhyML_Printf("\n. a: %d d: %d",a->num,d->num);
PhyML_Printf("\n. Conditional mean=%G var=%G",cond_mu[0],cond_cov[0*3+0]);
PhyML_Printf("\n. t0=%G t1=%f t2=%f t3=%f l1=%G l2=%G l3=%G",t0,t1,t2,t3,l1,l2,l3);
PhyML_Printf("\n. El1=%G El2=%G El3=%G Nu=%G r1=%G r2=%G r3=%G cr=%G",El1,El2,El3,tree->rates->nu,r1,r2,r3,cr);
PhyML_Printf("\n. COV11=%f COV12=%f COV13=%f COV22=%f COV23=%f COV33=%f",cov11,cov12,cov13,cov22,cov23,cov33);
PhyML_Printf("\n. constraint1: %f constraints2: %f",l2XY[1],l2XY[2]);
PhyML_Printf("\n");
For(i,3)
{
PhyML_Printf(". mu%d=%12lf\t",i,mu[i]);
For(j,3)
{
PhyML_Printf("%12lf ",cov[i*3+j]);
}
PhyML_Printf("\n");
}
cond_cov[0*3+0] = 1.E-10;
}
bl_min = (t_min - t0) * r1 * cr * nf;
bl_max = (t_max - t0) * r1 * cr * nf;
new_l1 = Rnorm_Trunc(cond_mu[0],inflate_var*SQRT(cond_cov[0*3+0]),bl_min,bl_max,&err);
/* new_l1 = Rnorm(cond_mu[0],SQRT(cond_cov[0*3+0])); */
if(new_l1 < bl_min) new_l1 = l1;
if(new_l1 > bl_max) new_l1 = l1;
t1_new = new_l1/(r1*cr*nf) + t0;
if(err)
{
PhyML_Printf("\n");
PhyML_Printf("\n. Root ? %s",(tree->n_root==a)?("yes"):("no"));
PhyML_Printf("\n. %s %d %d",__FILE__,__LINE__,tree->mcmc->run);
PhyML_Printf("\n. t0=%f t1=%f t2=%f t3=%f",t0,t1,t2,t3);
PhyML_Printf("\n. t_min=%f t_max=%f",t_min,t_max);
PhyML_Printf("\n. bl_min=%f bl_max=%f",bl_min,bl_max);
PhyML_Printf("\n. cond_mu[0]=%f cond_cov[0]=%f",cond_mu[0],SQRT(cond_cov[0*3+0]));
PhyML_Printf("\n. El1=%f El2=%f El3=%f",El1,El2,El3);
PhyML_Printf("\n. l1=%f l2=%f l3=%f",l1,l2,l3);
PhyML_Printf("\n. u0=%f r1=%f r2=%f r3=%f",u0,r1,r2,r3);
PhyML_Printf("\n. COV11=%f COV22=%f",cov11,cov22);
PhyML_Printf("\n. Clock rate = %f",tree->rates->clock_r);
PhyML_Printf("\n. Setting t1_new to %f",t1);
t1_new = t1;
/* Exit("\n"); */
}
/* } */
/* else */
/* { */
/* bl_min = (t2 - t_max) * r2; */
/* bl_max = (t2 - t_min) * r2; */
/* l2 = Rnorm_Trunc(cond_mu[0],SQRT(cond_cov[0*3+0]),bl_min,bl_max,&err); */
/* t1_new = -l2/r2 + t2; */
/* if(err) */
/* { */
/* PhyML_Printf("\n"); */
/* PhyML_Printf("\n. %s %d %d",__FILE__,__LINE__,tree->mcmc->run); */
/* PhyML_Printf("\n. t0=%f t1=%f t2=%f t3=%f",t0,t1,t2,t3); */
/* PhyML_Printf("\n. t_min=%f t_max=%f",t_min,t_max); */
/* PhyML_Printf("\n. bl_min=%f bl_max=%f",bl_min,bl_max); */
/* PhyML_Printf("\n. cond_mu[0]=%f cond_cov[0]=%f",cond_mu[0],SQRT(cond_cov[0*3+0])); */
/* PhyML_Printf("\n. El1=%f El2=%f El3=%f",El1,El2,El3); */
/* PhyML_Printf("\n. l1=%f l2=%f l3=%f",l1,l2,l3); */
/* PhyML_Printf("\n. u0=%f r1=%f r2=%f r3=%f",u0,r1,r2,r3); */
/* PhyML_Printf("\n. COV11=%f COV22=%f",cov11,cov22); */
/* PhyML_Printf("\n. Clock rate = %f",tree->rates->clock_r); */
/* PhyML_Printf("\n. Setting t1_new to %f",t1); */
/* t1_new = t1; */
/* /\* Exit("\n"); *\/ */
/* } */
/* } */
if(t1_new < t0)
{
t1_new = t0+1.E-4;
PhyML_Printf("\n");
PhyML_Printf("\n. a is root -> %s",(a == tree->n_root)?("YES"):("NO"));
PhyML_Printf("\n. t0 = %f t1_new = %f t1 = %f",t0,t1_new,t1);
PhyML_Printf("\n. t_min=%f t_max=%f",t_min,t_max);
PhyML_Printf("\n. l1 = %f",l1);
PhyML_Printf("\n. bl_min = %f bl_max = %f",bl_min,bl_max);
PhyML_Printf("\n. (t1-t0)=%f (t2-t1)=%f",t1-t0,t2-t1);
PhyML_Printf("\n. l1 = %f l2 = %f cov11=%f cov22=%f cov33=%f",l1,l2,cov11,cov22,cov33);
PhyML_Printf("\n. clock=%G",tree->rates->clock_r);
PhyML_Printf("\n. u0=%f r1=%f r2=%f r3=%f",u0,r1,r2,r3);
PhyML_Printf("\n. Err in file %s at line %d\n",__FILE__,__LINE__);
/* Exit("\n"); */
}
if(t1_new > MIN(t2,t3))
{
PhyML_Printf("\n");
PhyML_Printf("\n. a is root -> %s",(a == tree->n_root)?("YES"):("NO"));
PhyML_Printf("\n. t0 = %f t1_new = %f t1 = %f t2 = %f t3 = %f MIN(t2,t3)=%f",t0,t1_new,t1,t2,t3,MIN(t2,t3));
PhyML_Printf("\n. t_min=%f t_max=%f",t_min,t_max);
PhyML_Printf("\n. l2 = %f",l2);
PhyML_Printf("\n. bl_min = %f bl_max = %f",bl_min,bl_max);
PhyML_Printf("\n. (t1-t0)=%f (t2-t1)=%f",t1-t0,t2-t1);
PhyML_Printf("\n. l1 = %f l2 = %f cov11=%f cov22=%f cov33=%f",l1,l2,cov11,cov22,cov33);
PhyML_Printf("\n. clock=%G",tree->rates->clock_r);
PhyML_Printf("\n. u0=%f r1=%f r2=%f r3=%f",u0,r1,r2,r3);
PhyML_Printf("\n. Err in file %s at line %d\n",__FILE__,__LINE__);
/* Exit("\n"); */
}
if(isnan(t1_new))
{
PhyML_Printf("\n. run=%d",tree->mcmc->run);
PhyML_Printf("\n. mean=%G var=%G",cond_mu[0],cond_cov[0*3+0]);
PhyML_Printf("\n. t1=%f l1=%G r1=%G t0=%G",t1,l1,r1,t0);
PhyML_Printf("\n. Err in file %s at line %d\n",__FILE__,__LINE__);
/* Exit("\n"); */
}
if(tree->mcmc->use_data == YES)
tree->rates->nd_t[d->num] = t1_new;
else
{
u = Uni();
tree->rates->nd_t[d->num] = u*(t_max-t_min) + t_min;
}
RATES_Update_Norm_Fact(tree);
RATES_Update_Cur_Bl(tree);
cur_lnL_data = tree->c_lnL;
cur_lnL_rate = tree->rates->c_lnL_rates;
new_lnL_data = tree->c_lnL;
new_lnL_rate = tree->rates->c_lnL_rates;
if(tree->mcmc->use_data)
{
/* !!!!!!!!!!!!!!!!! */
/* tree->both_sides = NO; */
/* new_lnL_data = Lk(tree); */
if(tree->io->lk_approx == EXACT)
{
Update_PMat_At_Given_Edge(b1,tree);
Update_PMat_At_Given_Edge(b2,tree);
Update_PMat_At_Given_Edge(b3,tree);
Update_P_Lk(tree,b1,d);
}
new_lnL_data = Lk_At_Given_Edge(b1,tree);
}
new_lnL_rate = RATES_Lk_Rates(tree);
ratio = 0.0;
/* Proposal ratio */
if(tree->mcmc->use_data)
ratio += (Log_Dnorm_Trunc(l1, cond_mu[0],inflate_var*SQRT(cond_cov[0*3+0]),bl_min,bl_max,&err) -
Log_Dnorm_Trunc(new_l1,cond_mu[0],inflate_var*SQRT(cond_cov[0*3+0]),bl_min,bl_max,&err));
/* Prior ratio */
ratio += (new_lnL_rate - cur_lnL_rate);
/* Likelihood ratio */
ratio += (new_lnL_data - cur_lnL_data);
/* printf("\n* d:%d Ratio=%f l1=%f new_l1=%f mean=%f ml=%f sd=%f [%f %f]", */
/* d->num, */
/* EXP(ratio), */
/* l1,new_l1, */
/* cond_mu[0], */
/* tree->rates->mean_l[b1->num], */
/* SQRT(cond_cov[0*3+0]), */
/* Log_Dnorm(l1,cond_mu[0],SQRT(cond_cov[0*3+0]),&err),Log_Dnorm(new_l1,cond_mu[0],SQRT(cond_cov[0*3+0]),&err)); */
ratio = EXP(ratio);
u = Uni();
if(u > MIN(1.,ratio))
{
tree->rates->nd_t[d->num] = t1; /* reject */
tree->rates->c_lnL_rates = cur_lnL_rate;
tree->c_lnL = cur_lnL_data;
RATES_Update_Cur_Bl(tree);
if(tree->io->lk_approx == EXACT && tree->mcmc->use_data)
{
Update_PMat_At_Given_Edge(b1,tree);
Update_PMat_At_Given_Edge(b2,tree);
Update_PMat_At_Given_Edge(b3,tree);
Update_P_Lk(tree,b1,d);
}
}
else
{
tree->mcmc->acc_move[num_move]++;
}
RATES_Update_Norm_Fact(tree);
tree->mcmc->run_move[num_move]++;
if(traversal == YES)
{
if(d->tax == YES) return;
else
{
For(i,3)
if(d->v[i] != a && d->b[i] != tree->e_root)
{
if(tree->io->lk_approx == EXACT && tree->mcmc->use_data) Update_P_Lk(tree,d->b[i],d);
RATES_Posterior_One_Time(d,d->v[i],YES,tree);
}
}
if(tree->io->lk_approx == EXACT && tree->mcmc->use_data) Update_P_Lk(tree,b1,d);
}
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void RATES_Posterior_Time_Root(t_tree *tree)
{
/*
Root, T0
/ \
l1 / \ l2
/ \
v1,t1 v2,t2
*/
phydbl t1,t2;
phydbl u0,u1,u2;
phydbl cel,cvl;
int i,dim;
t_edge *b;
t_node *root;
phydbl t0,t0_min, t0_max;
phydbl new_t0;
/* phydbl t_max_01, t_max_02; */
int err;
phydbl cr;
phydbl bl_min, bl_max;
phydbl new_l,cur_l;
phydbl new_lnL_data, cur_lnL_data, new_lnL_rate, cur_lnL_rate;
phydbl u,ratio;
dim = 2*tree->n_otu-3;
b = tree->e_root;
root = tree->n_root;
cur_l = b->l;
t0 = tree->rates->nd_t[root->num];
t1 = tree->rates->nd_t[root->v[0]->num];
t2 = tree->rates->nd_t[root->v[1]->num];
u1 = tree->rates->br_r[root->v[0]->num];
u2 = tree->rates->br_r[root->v[1]->num];
u0 = 1.0;
cr = tree->rates->clock_r;
t0_min = -BIG;
t0_max = MIN(t1,t2);
/* t0_max = MIN(t1 - (1./tree->rates->nu)*POW((u0-u1)/tree->rates->z_max,2), */
/* t2 - (1./tree->rates->nu)*POW((u0-u2)/tree->rates->z_max,2)); */
/* if(u1 > u0) t_max_01 = t1 - (1./tree->rates->nu)*POW((u1-u0)/(PointNormal(tree->rates->p_max*Pnorm(.0,.0,1.))),2); */
/* else t_max_01 = t1 - (1./tree->rates->nu)*POW((u1-u0)/(PointNormal(tree->rates->p_max*(1.-Pnorm(.0,.0,1.)))),2); */
/* if(u2 > u0) t_max_02 = t2 - (1./tree->rates->nu)*POW((u2-u0)/(PointNormal(tree->rates->p_max*Pnorm(.0,.0,1.))),2); */
/* else t_max_02 = t2 - (1./tree->rates->nu)*POW((u2-u0)/(PointNormal(tree->rates->p_max*(1.-Pnorm(.0,.0,1.)))),2); */
/* t_max_01 = RATES_Find_Max_Dt_Bisec(u1,u0,tree->rates->t_prior_min[root->num],t1,tree->rates->nu,tree->rates->p_max,(u1 < u0)?YES:NO); */
/* t_max_02 = RATES_Find_Max_Dt_Bisec(u2,u0,tree->rates->t_prior_min[root->num],t2,tree->rates->nu,tree->rates->p_max,(u2 < u0)?YES:NO); */
/* t0_max = MIN(t_max_01,t_max_02); */
/* RATES_Min_Max_Interval(u0,u1,u2,r3,t0,t2,t3,&t_min,&t_max,tree->rates->nu,tree->rates->p_max,tree); */
t0_min = MAX(t0_min,tree->rates->t_prior_min[root->num]);
t0_max = MIN(t0_max,tree->rates->t_prior_max[root->num]);
t0_max -= tree->rates->min_dt;
if(t0_min > t0_max) return;
tree->rates->t_prior[root->num] = Uni()*(t0_max - t0_min) + t0_min;
u0 *= cr;
u1 *= cr;
u2 *= cr;
if(FABS(tree->rates->t_prior_min[root->num] - tree->rates->t_prior_max[root->num]) < 1.E-10) return;
cel=0.0;
For(i,dim) if(i != b->num) cel += tree->rates->reg_coeff[b->num*dim+i] * (tree->rates->u_cur_l[i] - tree->rates->mean_l[i]);
cel += tree->rates->mean_l[b->num];
cvl = tree->rates->cond_var[b->num];
bl_min = u1 * (t1 - t0_max) + u2 * (t2 - t0_max);
bl_max = u1 * (t1 - t0_min) + u2 * (t2 - t0_min);
if(bl_min > bl_max) return;
new_l = Rnorm_Trunc(cel,SQRT(cvl),bl_min,bl_max,&err);
new_t0 = (u1*t1 + u2*t2 - new_l)/(u1+u2);
if(t0 > t1 || t0 > t2)
{
PhyML_Printf("\n");
PhyML_Printf("\n. Run = %d",tree->mcmc->run);
PhyML_Printf("\n. t0=%f t1=%f t2=%f",t0,t1,t2);
PhyML_Printf("\n. t0_min=%f t0_max=%f",t0_min,t0_max);
PhyML_Printf("\n. new_l=%f cel=%f",new_l,cel);
PhyML_Printf("\n. u0=%f u1=%f u2=%f",u0/cr,u1/cr,u2/cr);
PhyML_Printf("\n. Nu = %f Clock = %f",tree->rates->nu,tree->rates->clock_r);
PhyML_Printf("\n. Setting t0 to %f",tree->rates->nd_t[root->num]);
return;
}
if(t0 < t0_min || t0 > t0_max)
{
PhyML_Printf("\n");
PhyML_Printf("\n. Run = %d",tree->mcmc->run);
PhyML_Printf("\n. t0=%f t1=%f t2=%f",t0,t1,t2);
PhyML_Printf("\n. t0_min=%f t0_max=%f",t0_min,t0_max);
PhyML_Printf("\n. u0=%f u1=%f u2=%f",u0/cr,u1/cr,u2/cr);
PhyML_Printf("\n. Nu = %f Clock = %f",tree->rates->nu,tree->rates->clock_r);
PhyML_Printf("\n. Setting t0 to %f",tree->rates->nd_t[root->num]);
t0 = tree->rates->nd_t[root->num];
}
/* Sample according to prior */
/* tree->rates->nd_t[root->num] = tree->rates->t_prior[root->num]; */
/* Sample according to posterior */
tree->rates->nd_t[root->num] = new_t0;
RATES_Update_Norm_Fact(tree);
RATES_Update_Cur_Bl(tree);
cur_lnL_data = tree->c_lnL;
cur_lnL_rate = tree->rates->c_lnL_rates;
new_lnL_data = tree->c_lnL;
new_lnL_rate = tree->rates->c_lnL_rates;
if(tree->mcmc->use_data) new_lnL_data = Lk(tree);
ratio = 0.0;
/* Prior ratio */
ratio += .0;
/* Likelihood ratio */
ratio += new_lnL_data - cur_lnL_data;
ratio = EXP(ratio);
u = Uni();
if(u > MIN(1.,ratio))
{
tree->rates->nd_t[root->num] = t0; /* reject */
tree->rates->c_lnL_rates = cur_lnL_rate;
tree->c_lnL = cur_lnL_data;
}
else
{
tree->mcmc->acc_move[tree->mcmc->num_move_nd_t]++;
}
RATES_Update_Norm_Fact(tree);
RATES_Update_Cur_Bl(tree);
tree->mcmc->run_move[tree->mcmc->num_move_nd_t]++;
tree->mcmc->acc_rate[tree->mcmc->num_move_nd_t] =
(tree->mcmc->acc_move[tree->mcmc->num_move_nd_t]+1.E-6)/
(tree->mcmc->run_move[tree->mcmc->num_move_nd_t]+1.E+6);
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void RATES_Update_Cur_Bl(t_tree *tree)
{
RATES_Update_Norm_Fact(tree);
RATES_Update_Cur_Bl_Pre(tree->n_root,tree->n_root->v[0],NULL,tree);
RATES_Update_Cur_Bl_Pre(tree->n_root,tree->n_root->v[1],NULL,tree);
if(tree->mod->log_l == YES)
{
tree->e_root->l =
EXP(tree->rates->cur_l[tree->n_root->v[0]->num]) +
EXP(tree->rates->cur_l[tree->n_root->v[1]->num]) ;
tree->e_root->l = LOG(tree->e_root->l);
}
else
{
tree->e_root->l =
tree->rates->cur_l[tree->n_root->v[0]->num] +
tree->rates->cur_l[tree->n_root->v[1]->num] ;
}
tree->rates->u_cur_l[tree->e_root->num] = tree->e_root->l;
tree->n_root_pos = tree->rates->cur_l[tree->n_root->v[0]->num] / tree->e_root->l;
if(tree->rates->model == GUINDON)
{
phydbl t0,t1,t2;
t_node *n0, *n1;
n0 = tree->n_root->v[0];
n1 = tree->n_root->v[1];
t1 = tree->rates->nd_t[tree->n_root->v[0]->num];
t2 = tree->rates->nd_t[tree->n_root->v[1]->num];
t0 = tree->rates->nd_t[tree->n_root->num];
tree->e_root->gamma_prior_mean =
(t1-t0)/(t1+t2-2.*t0)*tree->rates->cur_gamma_prior_mean[n0->num] +
(t2-t0)/(t1+t2-2.*t0)*tree->rates->cur_gamma_prior_mean[n1->num];
tree->e_root->gamma_prior_var =
POW((t1-t0)/(t1+t2-2.*t0),2)*tree->rates->cur_gamma_prior_var[n0->num] +
POW((t2-t0)/(t1+t2-2.*t0),2)*tree->rates->cur_gamma_prior_var[n1->num];
tree->e_root->l = tree->e_root->gamma_prior_mean; // Required for having proper branch lengths in Write_Tree function
/* printf("\n. ROOT: %f %f %f %f", */
/* tree->rates->cur_gamma_prior_mean[n0->num], */
/* tree->rates->cur_gamma_prior_var[n0->num], */
/* tree->rates->cur_gamma_prior_mean[n1->num], */
/* tree->rates->cur_gamma_prior_var[n1->num]); */
}
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void RATES_Update_Cur_Bl_Pre(t_node *a, t_node *d, t_edge *b, t_tree *tree)
{
phydbl dt,rr,cr,nf,ra,rd,ta,td,nu;
/* !!!!!!!!!!!!!!!!!!!!1 */
tree->rates->br_do_updt[d->num] = YES;
if(tree->rates->br_do_updt[d->num] == YES)
{
tree->rates->br_do_updt[d->num] = NO;
dt = tree->rates->nd_t[d->num] - tree->rates->nd_t[a->num];
cr = tree->rates->clock_r;
nf = tree->rates->norm_fact;
rd = tree->rates->br_r[d->num];
ra = tree->rates->br_r[a->num];
td = tree->rates->nd_t[d->num];
ta = tree->rates->nd_t[a->num];
nu = tree->rates->nu;
if(tree->rates->model_log_rates == YES)
{
/* Artihmetic average */
rr = (EXP(ra) + EXP(rd))/2.;
}
else
{
rr = (ra+rd)/2.;
}
tree->rates->cur_l[d->num] = dt*rr*cr;
if(tree->rates->model == GUINDON)
{
phydbl m,v;
Integrated_Geometric_Brownian_Bridge_Moments(dt,ra,rd,nu,&m,&v);
m *= cr*dt;
v *= (cr*cr)*(dt*dt);
tree->rates->cur_gamma_prior_mean[d->num] = m;
tree->rates->cur_gamma_prior_var[d->num] = v;
tree->rates->cur_l[d->num] = tree->rates->cur_gamma_prior_mean[d->num]; // Required for having proper branch lengths in Write_Tree function
}
if(tree->mod->log_l == YES) tree->rates->cur_l[d->num] = LOG(tree->rates->cur_l[d->num]);
if(b)
{
b->l = tree->rates->cur_l[d->num];
tree->rates->u_cur_l[b->num] = tree->rates->cur_l[d->num];
b->gamma_prior_mean = tree->rates->cur_gamma_prior_mean[d->num];
b->gamma_prior_var = tree->rates->cur_gamma_prior_var[d->num];
}
if(b && (isnan(b->l) || isnan(b->gamma_prior_var) || isnan(b->gamma_prior_mean)))
{
PhyML_Printf("\n. dt=%G rr=%G cr=%G ra=%G rd=%G nu=%G %f %f ",dt,rr,cr,ra,rd,nu,b->gamma_prior_var,b->gamma_prior_mean);
PhyML_Printf("\n. ta=%G td=%G ra*cr=%G rd*cr=%G sd=%G",
ta,td,ra*cr,rd*cr,
SQRT(dt*nu)*cr);
PhyML_Printf("\n. Err in file %s at line %d\n",__FILE__,__LINE__);
Exit("\n");
}
}
if(d->tax) return;
else
{
int i;
For(i,3)
if((d->v[i] != a) && (d->b[i] != tree->e_root))
RATES_Update_Cur_Bl_Pre(d,d->v[i],d->b[i],tree);
}
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void RATES_Bl_To_Bl(t_tree *tree)
{
RATES_Bl_To_Bl_Pre(tree->n_root,tree->n_root->v[0],NULL,tree);
RATES_Bl_To_Bl_Pre(tree->n_root,tree->n_root->v[1],NULL,tree);
/* tree->rates->cur_l[tree->n_root->v[0]->num] = tree->t_edges[tree->e_root->num]->l * tree->n_root_pos; */
/* tree->rates->cur_l[tree->n_root->v[1]->num] = tree->t_edges[tree->e_root->num]->l * (1. - tree->n_root_pos); */
tree->rates->cur_l[tree->n_root->v[0]->num] = tree->t_edges[tree->e_root->num]->l * 0.5;
tree->rates->cur_l[tree->n_root->v[1]->num] = tree->t_edges[tree->e_root->num]->l * (1. - 0.5);
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void RATES_Bl_To_Bl_Pre(t_node *a, t_node *d, t_edge *b, t_tree *tree)
{
if(b)
{
tree->rates->cur_l[d->num] = b->l;
}
if(d->tax) return;
else
{
int i;
For(i,3)
if((d->v[i] != a) && (d->b[i] != tree->e_root))
RATES_Bl_To_Bl_Pre(d,d->v[i],d->b[i],tree);
}
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void RATES_Bl_To_Ml(t_tree *tree)
{
RATES_Bl_To_Ml_Pre(tree->n_root,tree->n_root->v[0],NULL,tree);
RATES_Bl_To_Ml_Pre(tree->n_root,tree->n_root->v[1],NULL,tree);
tree->rates->u_ml_l[tree->e_root->num] = tree->t_edges[tree->e_root->num]->l;
tree->rates->ml_l[tree->n_root->v[0]->num] = tree->rates->u_ml_l[tree->e_root->num] * tree->n_root_pos;
tree->rates->ml_l[tree->n_root->v[1]->num] = tree->rates->u_ml_l[tree->e_root->num] * (1. - tree->n_root_pos);
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void RATES_Bl_To_Ml_Pre(t_node *a, t_node *d, t_edge *b, t_tree *tree)
{
if(b)
{
tree->rates->u_ml_l[b->num] = b->l;
tree->rates->ml_l[d->num] = b->l;
}
if(d->tax) return;
else
{
int i;
For(i,3)
if((d->v[i] != a) && (d->b[i] != tree->e_root))
RATES_Bl_To_Ml_Pre(d,d->v[i],d->b[i],tree);
}
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void RATES_Get_Cov_Matrix_Rooted(phydbl *unroot_cov, t_tree *tree)
{
int i,dim;
dim = 2*tree->n_otu-3;
RATES_Get_Cov_Matrix_Rooted_Pre(tree->n_root,tree->n_root->v[0],NULL,unroot_cov,tree);
RATES_Get_Cov_Matrix_Rooted_Pre(tree->n_root,tree->n_root->v[1],NULL,unroot_cov,tree);
For(i,dim+1) tree->rates->cov_l[i*(dim+1)+tree->n_root->v[0]->num] /= 2.;
For(i,dim+1) tree->rates->cov_l[i*(dim+1)+tree->n_root->v[1]->num] /= 2.;
For(i,dim+1) tree->rates->cov_l[tree->n_root->v[0]->num*(dim+1)+i] /= 2.;
For(i,dim+1) tree->rates->cov_l[tree->n_root->v[1]->num*(dim+1)+i] /= 2.;
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void RATES_Get_Cov_Matrix_Rooted_Pre(t_node *a, t_node *d, t_edge *b, phydbl *cov, t_tree *tree)
{
int i, dim, done_left;
t_node *n;
dim = 2*tree->n_otu-3;
done_left = 0;
n = NULL;
For(i,dim)
{
if(tree->t_edges[i] != tree->e_root)
{
n =
(tree->t_edges[i]->left->anc == tree->t_edges[i]->rght)?
(tree->t_edges[i]->left):
(tree->t_edges[i]->rght);
if(b)
{
tree->rates->cov_l[d->num*(dim+1) + n->num] = cov[b->num*dim + i];
}
else
{
tree->rates->cov_l[d->num*(dim+1) + n->num] = cov[tree->e_root->num*dim + i];
}
}
else
{
n = tree->e_root->left;
if(b)
tree->rates->cov_l[d->num*(dim+1) + n->num] = cov[b->num*dim + i];
else
tree->rates->cov_l[d->num*(dim+1) + n->num] = cov[tree->e_root->num*dim + i];
n = tree->e_root->rght;
if(b)
tree->rates->cov_l[d->num*(dim+1) + n->num] = cov[b->num*dim + i];
else
tree->rates->cov_l[d->num*(dim+1) + n->num] = cov[tree->e_root->num*dim + i];
}
}
if(d->tax) return;
else
{
For(i,3)
if((d->v[i] != a) && (d->b[i] != tree->e_root))
RATES_Get_Cov_Matrix_Rooted_Pre(d,d->v[i],d->b[i],cov,tree);
}
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void RATES_Covariance_Mu(t_tree *tree)
{
int i,j;
phydbl dt,var;
int dim;
int lca_num;
dim = 2*tree->n_otu-2;
For(i,dim*dim) tree->rates->cov_r[i] = 0.0;
dt = tree->rates->nd_t[tree->n_root->v[0]->num] - tree->rates->nd_t[tree->n_root->num];
var = dt * tree->rates->nu;
tree->rates->cov_r[tree->n_root->v[0]->num*dim+tree->n_root->v[0]->num] = var;
dt = tree->rates->nd_t[tree->n_root->v[1]->num] - tree->rates->nd_t[tree->n_root->num];
var = dt * tree->rates->nu;
tree->rates->cov_r[tree->n_root->v[1]->num*dim+tree->n_root->v[1]->num] = var;
RATES_Variance_Mu_Pre(tree->n_root,tree->n_root->v[0],tree);
RATES_Variance_Mu_Pre(tree->n_root,tree->n_root->v[1],tree);
For(i,dim)
{
for(j=i+1;jrates->lca[i*(dim+1)+j]->num;
if(lca_num < dim)
{
tree->rates->cov_r[i*dim+j] = tree->rates->cov_r[lca_num*dim+lca_num];
tree->rates->cov_r[j*dim+i] = tree->rates->cov_r[i*dim+j];
}
else if(lca_num == dim)
{
tree->rates->cov_r[i*dim+j] = 0.0;
tree->rates->cov_r[j*dim+i] = 0.0;
}
else
{
PhyML_Printf("\n. Err in file %s at line %d\n",__FILE__,__LINE__);
Exit("\n");
}
}
}
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void RATES_Variance_Mu_Pre(t_node *a, t_node *d, t_tree *tree)
{
int dim;
phydbl dt0,var0;
phydbl dt1,var1;
phydbl dt2,var2;
int i;
int dir1, dir2;
dim = 2*tree->n_otu-2;
if(d->tax) return;
dir1 = dir2 = -1;
For(i,3)
{
if((d->v[i] != a) && (d->b[i] != tree->e_root))
{
if(dir1 < 0) dir1 = i;
else dir2 = i;
}
}
dt0 = tree->rates->nd_t[d->num] - tree->rates->nd_t[a->num];
var0 = tree->rates->cov_r[d->num*dim+d->num];
dt1 = tree->rates->nd_t[d->v[dir1]->num] - tree->rates->nd_t[d->num];
var1 = tree->rates->nu*dt1;
dt2 = tree->rates->nd_t[d->v[dir2]->num] - tree->rates->nd_t[d->num];
var2 = tree->rates->nu*dt2;
tree->rates->cov_r[d->v[dir1]->num*dim+d->v[dir1]->num] = var0+var1;
tree->rates->cov_r[d->v[dir2]->num*dim+d->v[dir2]->num] = var0+var2;
For(i,3)
{
if((d->v[i] != a) && (d->b[i] != tree->e_root))
{
RATES_Variance_Mu_Pre(d,d->v[i],tree);
}
}
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void RATES_Fill_Lca_Table(t_tree *tree)
{
int i,j;
int dim;
dim = 2*tree->n_otu-1;
For(i,dim)
{
for(j=i;jrates->lca[i*dim+j] = Find_Lca_Pair_Of_Nodes(tree->t_nodes[i],tree->t_nodes[j],tree);
tree->rates->lca[j*dim+i] = tree->rates->lca[i*dim+j];
}
}
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
/* Get V(L_{i} | L_{-i}) for all i */
void RATES_Get_Conditional_Variances(t_tree *tree)
{
int i,j;
short int *is_1;
phydbl *a;
int dim;
t_edge *b;
phydbl *cond_mu, *cond_cov;
dim = 2*tree->n_otu-3;
a = tree->rates->_2n_vect1;
is_1 = tree->rates->_2n_vect5;
b = NULL;
cond_mu = tree->rates->_2n_vect2;
cond_cov = tree->rates->_2n2n_vect1;
For(i,dim) a[i] = tree->rates->mean_l[i] * (Uni() * 0.2 + 0.9);
For(i,dim)
{
b = tree->t_edges[i];
For(j,dim) is_1[j] = 0;
is_1[b->num] = 1;
For(j,dim*dim) cond_cov[j] = 0.0;
For(j,dim) cond_mu[j] = 0.0;
Normal_Conditional(tree->rates->mean_l,tree->rates->cov_l,a,dim,is_1,1,cond_mu,cond_cov);
tree->rates->cond_var[b->num] = cond_cov[b->num*dim+b->num];
}
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void RATES_Get_All_Reg_Coeff(t_tree *tree)
{
int i,j;
short int *is_1;
phydbl *a;
int dim;
t_edge *b;
dim = 2*tree->n_otu-3;
a = tree->rates->_2n_vect1;
is_1 = tree->rates->_2n_vect5;
b = NULL;
For(i,dim) a[i] = tree->rates->mean_l[i] * (Uni() * 0.2 + 0.9);
For(i,dim)
{
b = tree->t_edges[i];
For(j,dim) is_1[j] = 0;
is_1[b->num] = 1;
Get_Reg_Coeff(tree->rates->mean_l,tree->rates->cov_l,a,dim,is_1,1,tree->rates->reg_coeff+b->num*dim);
}
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
/* Get V(L_{i} | L_{-i}) for all i */
void RATES_Get_Trip_Conditional_Variances(t_tree *tree)
{
int i,j;
short int *is_1;
phydbl *a;
phydbl *cond_mu, *cond_cov;
t_node *n;
int n_otu;
a = tree->rates->_2n_vect1;
is_1 = tree->rates->_2n_vect5;
cond_mu = tree->rates->_2n_vect2;
cond_cov = tree->rates->_2n2n_vect1;
n = NULL;
n_otu = tree->n_otu;
For(i,2*n_otu-3) a[i] = tree->rates->mean_l[i] * (Uni() * 0.2 + 0.9);
For(i,2*n_otu-2)
{
n = tree->t_nodes[i];
if(!n->tax)
{
For(j,2*n_otu-3) is_1[j] = 0;
is_1[n->b[0]->num] = 1;
is_1[n->b[1]->num] = 1;
is_1[n->b[2]->num] = 1;
Normal_Conditional_Unsorted(tree->rates->mean_l,tree->rates->cov_l,a,2*n_otu-3,is_1,3,cond_mu,cond_cov);
For(j,9) tree->rates->trip_cond_cov[n->num*9+j] = cond_cov[j];
}
}
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void RATES_Get_All_Trip_Reg_Coeff(t_tree *tree)
{
int i,j;
short int *is_1;
phydbl *a;
t_node *n;
int n_otu;
a = tree->rates->_2n_vect1;
is_1 = tree->rates->_2n_vect5;
n = NULL;
n_otu = tree->n_otu;
For(i,2*n_otu-3) a[i] = tree->rates->mean_l[i] * (Uni() * 0.2 + 0.9);
For(i,2*n_otu-2)
{
n = tree->t_nodes[i];
if(!n->tax)
{
For(j,2*n_otu-3) is_1[j] = 0;
is_1[n->b[0]->num] = 1;
is_1[n->b[1]->num] = 1;
is_1[n->b[2]->num] = 1;
Get_Reg_Coeff(tree->rates->mean_l,tree->rates->cov_l,a,2*n_otu-3,is_1,3,tree->rates->trip_reg_coeff+n->num*(6*n_otu-9));
}
}
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void RATES_Check_Lk_Rates(t_tree *tree, int *err)
{
int i;
phydbl u,u_anc;
phydbl t,t_anc;
phydbl z;
*err = 0;
z = 0.0;
For(i,2*tree->n_otu-2)
{
u = tree->rates->br_r[i];
u_anc = tree->rates->br_r[tree->t_nodes[i]->anc->num];
t = tree->rates->nd_t[i];
t_anc = tree->rates->nd_t[tree->t_nodes[i]->anc->num];
if(t_anc > t)
{
PhyML_Printf("\n. %d %d u=%f u_anc=%f t=%f t_anc=%f",i,tree->t_nodes[i]->anc->num,u,u_anc,t,t_anc);
PhyML_Printf("\n. %d %d %d",tree->n_root->num,tree->n_root->v[0]->num,tree->n_root->v[1]->num);
*err = 1;
}
}
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
phydbl RATES_Expected_Tree_Length(t_tree *tree)
{
int n;
phydbl mean;
n = 0;
mean = 0.0;
RATES_Expected_Tree_Length_Pre(tree->n_root,tree->n_root->v[0],1.0,&mean,&n,tree);
RATES_Expected_Tree_Length_Pre(tree->n_root,tree->n_root->v[1],1.0,&mean,&n,tree);
if(n != 2*tree->n_otu-2)
{
PhyML_Printf("\n. n=%d 2n-2=%d",n,2*tree->n_otu-2);
PhyML_Printf("\n. Err in file %s at line %d\n",__FILE__,__LINE__);
Exit("\n");
}
return mean;
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void RATES_Expected_Tree_Length_Pre(t_node *a, t_node *d, phydbl eranc, phydbl *mean, int *n, t_tree *tree)
{
phydbl erdes;
int i;
phydbl u,u_anc,t,t_anc;
phydbl loc_mean;
int loc_n;
phydbl sd;
u = tree->rates->br_r[d->num];
u_anc = tree->rates->br_r[a->num];
t = tree->rates->nd_t[d->num];
t_anc = tree->rates->nd_t[a->num];
sd = SQRT((t-t_anc)*tree->rates->nu);
/* erdes = u_anc - */
/* sd*(Dnorm((tree->rates->min_rate-u_anc)/sd,.0,1.) - Dnorm((tree->rates->max_rate-u_anc)/sd,.0,1.))/ */
/* (Pnorm((tree->rates->max_rate-u_anc)/sd,.0,1.) - Pnorm((tree->rates->min_rate-u_anc)/sd,.0,1.)); */
/* erdes = Norm_Trunc_Mean(eranc,sd,tree->rates->min_rate,tree->rates->max_rate); */
erdes = 1.0;
loc_mean = *mean;
loc_n = *n;
loc_mean *= loc_n;
loc_mean += erdes;
loc_mean /= (loc_n + 1);
*mean = loc_mean;
*n = loc_n + 1;
if(d->tax) return;
else
For(i,3)
if(d->v[i] != a && d->b[i] != tree->e_root)
RATES_Expected_Tree_Length_Pre(d,d->v[i],erdes,mean,n,tree);
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void RATES_Update_Norm_Fact(t_tree *tree)
{
int i;
phydbl r,t,t_anc;
phydbl num,denom;
num = denom = 0.0;
For(i,2*tree->n_otu-2)
{
r = tree->rates->br_r[i];
t = tree->rates->nd_t[i];
t_anc = tree->rates->nd_t[tree->t_nodes[i]->anc->num];
num += (t-t_anc);
denom += (t-t_anc) * r;
}
tree->rates->norm_fact = num/denom;
/* !!!!!!!!!!!!!!!!!! */
tree->rates->norm_fact = 1.0;
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void RATES_Normalise_Rates(t_tree *tree)
{
phydbl expr,curr;
int i;
curr = RATES_Average_Substitution_Rate(tree);
curr /= tree->rates->clock_r;
/* Set expected mean rate to one such that clock_r is
easy to interpret regarding the mean values of br_r */
expr = 1.0;
For(i,2*tree->n_otu-2)
{
tree->rates->br_r[i] *= expr/curr;
if(tree->rates->br_r[i] > tree->rates->max_rate)
tree->rates->br_r[i] = tree->rates->max_rate;
if(tree->rates->br_r[i] < tree->rates->min_rate)
tree->rates->br_r[i] = tree->rates->min_rate;
}
tree->rates->clock_r *= curr/expr;
/* Branch lengths therefore do not change */
/* if(tree->rates->clock_r < tree->rates->min_clock) */
/* { */
/* PhyML_Printf("\n. Curr mean rates: %G",curr); */
/* PhyML_Printf("\n. Set clock rate to: %G",tree->rates->clock_r); */
/* tree->rates->clock_r = tree->rates->min_clock; */
/* } */
/* if(tree->rates->clock_r > tree->rates->max_clock) */
/* { */
/* PhyML_Printf("\n. Curr mean rates: %G",curr); */
/* PhyML_Printf("\n. Set clock rate to: %G",tree->rates->clock_r); */
/* tree->rates->clock_r = tree->rates->max_clock; */
/* } */
RATES_Update_Norm_Fact(tree);
RATES_Update_Cur_Bl(tree);
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
phydbl RATES_Find_Max_Dt_Bisec(phydbl r, phydbl r_mean, phydbl ta, phydbl tc, phydbl nu, phydbl threshp, int inf)
{
phydbl cdfr,cdf0;
phydbl sd;
phydbl trunc_cdf;
phydbl ori_tc, ori_ta;
phydbl tb;
ori_tc = tc;
ori_ta = ta;
/* PhyML_Printf("\n Max %s r=%f r_mean%f",inf?"inf":"sup",r,r_mean); */
do
{
tb = ta + (tc - ta)/2.;
sd = SQRT(nu*(ori_tc - tb));
cdfr = Pnorm(r ,r_mean,sd);
cdf0 = Pnorm(.0,r_mean,sd);
if(inf)
trunc_cdf = (cdfr - cdf0)/(1. - cdf0);
else
trunc_cdf = (1. - cdfr)/(1. - cdf0);
/* PhyML_Printf("\n. ta=%15f tb=%15f tc=%15f cdf = %15f",ta,tb,tc,trunc_cdf); */
if(trunc_cdf > threshp)
{
ta = tb;
}
else
{
tc = tb;
}
}while((tc - ta)/(ori_tc - ori_ta) > 0.001);
if(tb < ori_ta)
{
PhyML_Printf("\n. tb < ta r=%f r_mean=%f",r,r_mean);
PhyML_Printf("\n. Err in file %s at line %d\n",__FILE__,__LINE__);
Exit("\n");
}
if(tb > ori_tc)
{
PhyML_Printf("\n. tb > tc r=%f r_mean=%f ori_ta=%f ori_tc=%f tb=%f",r,r_mean,ori_ta,ori_tc,tb);
PhyML_Printf("\n. Err in file %s at line %d\n",__FILE__,__LINE__);
Exit("\n");
}
return tb;
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
phydbl RATES_Find_Min_Dt_Bisec(phydbl r, phydbl r_mean, phydbl ta, phydbl tc, phydbl nu, phydbl threshp, int inf)
{
phydbl cdfr,cdf0;
phydbl sd;
phydbl trunc_cdf;
phydbl ori_tc, ori_ta;
phydbl tb;
ori_tc = tc;
ori_ta = ta;
/* PhyML_Printf("\n Min %s r=%f r_mean=%f",inf?"inf":"sup",r,r_mean); */
do
{
tb = ta + (tc - ta)/2.;
sd = SQRT(nu*(tb - ori_ta));
cdfr = Pnorm(r ,r_mean,sd);
cdf0 = Pnorm(.0,r_mean,sd);
if(inf)
trunc_cdf = (cdfr - cdf0)/(1. - cdf0);
else
trunc_cdf = (1. - cdfr)/(1. - cdf0);
/* PhyML_Printf("\n. ta=%15f tb=%15f tc=%15f cdf = %15f",ta,tb,tc,trunc_cdf); */
if(trunc_cdf > threshp)
{
tc = tb;
}
else
{
ta = tb;
}
}while((tc - ta)/(ori_tc - ori_ta) > 0.001);
if(tb < ori_ta)
{
PhyML_Printf("\n. tb < ta r=%f r_mean=%f",r,r_mean);
PhyML_Printf("\n. Err in file %s at line %d\n",__FILE__,__LINE__);
Exit("\n");
}
if(tb > ori_tc)
{
PhyML_Printf("\n. tb > tc r=%f r_mean=%f ori_ta=%f ori_tc=%f tb=%f",r,r_mean,ori_ta,ori_tc,tb);
PhyML_Printf("\n. Err in file %s at line %d\n",__FILE__,__LINE__);
Exit("\n");
}
return tb;
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void RATES_Min_Max_Interval(phydbl u0, phydbl u1, phydbl u2, phydbl u3, phydbl t0, phydbl t2, phydbl t3,
phydbl *t_min, phydbl *t_max, phydbl nu, phydbl p_thresh, t_tree *tree)
{
int n_eval;
int i;
phydbl sum_cdf;
phydbl *cdf;
phydbl t1;
phydbl mint2t3;
mint2t3 = MIN(t2,t3);
n_eval = 5;
cdf = (phydbl *)mCalloc(n_eval,sizeof(phydbl));
sum_cdf = .0;
For(i,n_eval)
{
t1 = t0 + (i + 1)*(mint2t3 - t0)/(n_eval + 1);
cdf[i] =
Dnorm_Trunc(u1,u0,SQRT(nu*(t1-t0)),tree->rates->min_rate,tree->rates->max_rate) *
Dnorm_Trunc(u2,u1,SQRT(nu*(t2-t1)),tree->rates->min_rate,tree->rates->max_rate) *
Dnorm_Trunc(u3,u1,SQRT(nu*(t3-t1)),tree->rates->min_rate,tree->rates->max_rate) *
(mint2t3 - t0) / (n_eval + 1);
if(i) cdf[i] += cdf[i-1];
}
sum_cdf = cdf[i-1];
For(i,n_eval) cdf[i] /= sum_cdf;
/* PhyML_Printf("\n"); */
/* For(i,n_eval) PhyML_Printf("\n* %f %f",cdf[i],sum_cdf); */
For(i,n_eval)
if(cdf[i] > p_thresh)
{
*t_min = t0 + (i + 1)*(mint2t3 - t0)/(n_eval + 1);
break;
}
For(i,n_eval)
if(cdf[i] > (1. - p_thresh))
{
*t_max = t0 + (i + 1)*(mint2t3 - t0)/(n_eval + 1);
break;
}
Free(cdf);
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
phydbl RATES_Get_Correction_Factor(phydbl mode, phydbl sd, int *err, t_tree *tree)
{
phydbl K,X0,X1,X2,Y0,Y1,Y2;
phydbl eps=0.01;
phydbl A,B;
phydbl slope,inter;
phydbl num, denom;
*err = NO;
/* DO NOTHING */
return 0.0;
A = tree->rates->min_rate / sd;
B = tree->rates->max_rate / sd;
K = mode / sd;
X0 = 0.;
/* Y0 = Dnorm(X0-K,.0,1.)/(1. - Pnorm(X0-K,.0,1.)) - X0; */
Y0 = (Dnorm(A-K+X0,.0,1.)-Dnorm(B-K+X0,.0,1.))/(Pnorm(B-K+X0,.0,1.)-Pnorm(A-K+X0,.0,1.)) - X0;
X1 = .1;
/* Y1 = Dnorm(X1-K,.0,1.)/(1. - Pnorm(X1-K,.0,1.)) - X1; */
Y1 = (Dnorm(A-K+X1,.0,1.)-Dnorm(B-K+X1,.0,1.))/(Pnorm(B-K+X1,.0,1.)-Pnorm(A-K+X1,.0,1.)) - X1;
/* printf("\n. ^^ mean=%f sd=%f",mode,sd); */
/* printf("\n. X0=%f Y0=%f X1=%f Y1=%f",X0,Y0,X1,Y1); */
do
{
slope = (Y1-Y0)/(X1-X0);
inter = Y0 - X0*(Y1-Y0)/(X1-X0);
X2 = -inter/slope;
num = (Dnorm(A-K+X2,.0,1.)-Dnorm(B-K+X2,.0,1.));
denom = (Pnorm(B-K+X2,.0,1.)-Pnorm(A-K+X2,.0,1.));
if(denom < 1.E-10)
{
/* printf("\n. X2 = %f Y2=%f num=%f denom=%f Y1=%f Y0=%f X1=%f X0=%f mode=%f sd=%f",X2,Y2,num,denom,Y1,Y0,X1,X0,mode,sd); */
*err = YES;
break;
}
/* Y2 = Dnorm(X2-K,.0,1.)/(1. - Pnorm(X2-K,.0,1.)) - X2; */
Y2 = (Dnorm(A-K+X2,.0,1.)-Dnorm(B-K+X2,.0,1.))/(Pnorm(B-K+X2,.0,1.)-Pnorm(A-K+X2,.0,1.)) - X2;
/* printf("\n. X2 = %f Y2=%f num=%f denom=%f Y1=%f Y0=%f X1=%f X0=%f",X2,Y2,num,denom,Y1,Y0,X1,X0); */
if(X2 > X1)
{
X0 = X1;
X1 = X2;
Y0 = Y1;
Y1 = Y2;
}
else
{
X1 = X0;
X0 = X2;
Y1 = Y0;
Y0 = Y2;
}
}while(fabs(Y2) > eps);
/* printf("\n. shift = %f X2=%f Y2 = %f",X2*sd,X2,Y2); */
return X2 * sd;
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
phydbl Sample_Average_Rate(t_node *a, t_node *d, t_tree *tree)
{
phydbl ra,rd;
phydbl ta,td;
ra = tree->rates->br_r[a->num];
rd = tree->rates->br_r[d->num];
ta = tree->rates->nd_t[a->num];
td = tree->rates->nd_t[d->num];
return(-1.);
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void RATES_Update_Mean_Br_Len(int iter, t_tree *tree)
{
int i,dim;
phydbl *mean;
if(tree->rates->update_mean_l == NO) return;
dim = 2*tree->n_otu-3;
mean = tree->rates->mean_l;
For(i,dim)
{
mean[i] *= (phydbl)iter;
mean[i] += tree->t_edges[i]->l;
mean[i] /= (phydbl)(iter+1);
}
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void RATES_Update_Cov_Br_Len(int iter, t_tree *tree)
{
int i,j,dim;
phydbl *mean,*cov;
if(tree->rates->update_cov_l == NO) return;
dim = 2*tree->n_otu-3;
mean = tree->rates->mean_l;
cov = tree->rates->cov_l;
For(i,dim)
{
For(j,dim)
{
cov[i*dim+j] += mean[i]*mean[j];
cov[i*dim+j] *= (phydbl)tree->mcmc->run;
cov[i*dim+j] += tree->t_edges[i]->l * tree->t_edges[j]->l;
cov[i*dim+j] /= (phydbl)(tree->mcmc->run+1);
cov[i*dim+j] -= mean[i]*mean[j];
if(i == j && cov[i*dim+j] < MIN_VAR_BL) cov[i*dim+j] = MIN_VAR_BL;
}
}
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void RATES_Set_Mean_L(t_tree *tree)
{
int i;
For(i,2*tree->n_otu-3)
{
tree->rates->mean_l[i] = tree->t_edges[i]->l;
}
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void RATES_Record_Times(t_tree *tree)
{
int i;
if(tree->rates->nd_t_recorded == YES)
{
PhyML_Printf("\n. Overwriting recorded times is forbidden.\n");
PhyML_Printf("\n. Err in file %s at line %d\n",__FILE__,__LINE__);
Exit("\n");
}
For(i,2*tree->n_otu-1) tree->rates->buff_t[i] = tree->rates->nd_t[i];
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void RATES_Reset_Times(t_tree *tree)
{
int i;
tree->rates->nd_t_recorded = NO;
For(i,2*tree->n_otu-1) tree->rates->nd_t[i] = tree->rates->buff_t[i];
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void RATES_Record_Rates(t_tree *tree)
{
int i;
if(tree->rates->br_r_recorded == YES)
{
PhyML_Printf("\n. Overwriting recorded rates is forbidden.\n");
PhyML_Printf("\n. Err in file %s at line %d\n",__FILE__,__LINE__);
Exit("\n");
}
For(i,2*tree->n_otu-2) tree->rates->buff_r[i] = tree->rates->br_r[i];
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void RATES_Reset_Rates(t_tree *tree)
{
int i;
tree->rates->br_r_recorded = NO;
For(i,2*tree->n_otu-2) tree->rates->br_r[i] = tree->rates->buff_r[i];
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void RATES_Set_Clock_And_Nu_Max(t_tree *tree)
{
phydbl dt,nu;
phydbl min_t;
int i;
phydbl step;
phydbl l_max;
phydbl max_clock;
phydbl a;
phydbl r_min,r_max;
phydbl tune;
phydbl pa,pb;
if(tree->rates->model == THORNE ||
tree->rates->model == GUINDON)
{
tune = 1.05;
if(tree->rates->model_log_rates == NO)
{
r_min = LOG(tree->rates->min_rate);
r_max = LOG(tree->rates->max_rate);
}
else
{
r_min = tree->rates->min_rate;
r_max = tree->rates->max_rate;
}
l_max = tree->mod->l_max;
min_t = .0;
For(i,2*tree->n_otu-1) if(tree->rates->t_prior_min[i] < min_t) min_t = tree->rates->t_prior_min[i];
dt = FABS(min_t);
max_clock = l_max / dt;
nu = 1.E-10;
step = 1.E-1;
a = 0.5;
do
{
do
{
nu += step;
pa = Dnorm(0.0, 0.0,SQRT(nu*dt));
pb = Dnorm(r_max,0.0,SQRT(nu*dt));
}while(pa/pb > tune);
nu -= step;
step /= 10.;
}while(step > 1.E-10);
tree->rates->max_nu = nu;
/* tree->rates->max_nu = 1.0; */
tree->rates->max_clock = max_clock;
PhyML_Printf("\n. Clock rate parameter upper bound set to %f expected subst./site/time unit",tree->rates->max_clock);
PhyML_Printf("\n. Autocorrelation parameter upper bound set to %f",tree->rates->max_nu);
}
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void RATES_Set_Birth_Rate_Boundaries(t_tree *tree)
{
phydbl lbda;
phydbl p_above_min,p_below_max;
phydbl min,max;
int assign = YES;
min = -tree->rates->t_prior_max[tree->n_root->num];
max = -tree->rates->t_prior_min[tree->n_root->num];
for(lbda = 0.001; lbda < 10; lbda+=0.001)
{
p_above_min = 1. - POW(1.-EXP(-lbda*min),tree->n_otu);
p_below_max = POW(1.-EXP(-lbda*max),tree->n_otu);
if(p_above_min < 1.E-5)
{
tree->rates->birth_rate_max = lbda;
break;
}
if(p_below_max > 1.E-5 && assign==YES)
{
assign = NO;
tree->rates->birth_rate_min = lbda;
}
}
PhyML_Printf("\n. Birth rate lower bound set to %f.",tree->rates->birth_rate_min);
PhyML_Printf("\n. Birth rate upper bound set to %f.",tree->rates->birth_rate_max);
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void RATES_Write_Mean_R_On_Edge_Label(t_node *a, t_node *d, t_edge *b, t_tree *tree)
{
if(b)
{
if(!b->labels)
{
Make_New_Edge_Label(b);
b->n_labels++;
}
sprintf(b->labels[0],"%f",tree->rates->mean_r[d->num] / (phydbl)(tree->mcmc->run/tree->mcmc->sample_interval+1.));
}
if(d->tax) return;
else
{
int i;
For(i,3)
{
if((d->v[i] != a) && (d->b[i] != tree->e_root))
{
RATES_Write_Mean_R_On_Edge_Label(d,d->v[i],d->b[i],tree);
}
}
}
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
phydbl RATES_Get_Mean_Rate_In_Subtree(t_node *root, t_tree *tree)
{
phydbl sum;
int n;
sum = 0.0;
n = 0;
if(root->tax == NO)
{
if(root == tree->n_root)
{
RATES_Get_Mean_Rate_In_Subtree_Pre(root,root->v[0],&sum,&n,tree);
RATES_Get_Mean_Rate_In_Subtree_Pre(root,root->v[1],&sum,&n,tree);
}
else
{
int i;
For(i,3)
{
if(root->v[i] != root->anc && root->b[i] != tree->e_root)
{
RATES_Get_Mean_Rate_In_Subtree_Pre(root,root->v[i],&sum,&n,tree);
}
}
}
return sum/(phydbl)n;
}
else
{
return 0.0;
}
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void RATES_Get_Mean_Rate_In_Subtree_Pre(t_node *a, t_node *d, phydbl *sum, int *n, t_tree *tree)
{
(*sum) += EXP(tree->rates->nd_r[d->num]);
(*n) += 1;
if(d->tax == YES) return;
else
{
int i;
For(i,3)
{
if(d->v[i] != a && d->b[i] != tree->e_root)
{
RATES_Get_Mean_Rate_In_Subtree_Pre(d,d->v[i],sum,n,tree);
}
}
}
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
char *RATES_Get_Model_Name(int model)
{
char *s;
s = (char *)mCalloc(T_MAX_NAME,sizeof(char));
switch(model)
{
case GUINDON : {strcpy(s,"gbs"); break;}
case THORNE : {strcpy(s,"gbd"); break;}
case GAMMA : {strcpy(s,"gamma"); break;}
case STRICTCLOCK : {strcpy(s,"clock"); break;}
default :
{
PhyML_Printf("\n. Err in file %s at line %d\n",__FILE__,__LINE__);
Exit("\n");
break;
}
}
return s;
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void RATES_Get_Survival_Ranks(t_tree *tree)
{
int i,j;
phydbl rank;
For(i,2*tree->n_otu-2)
{
rank = 0.;
For(j,2*tree->n_otu-2)
{
if(tree->rates->br_r[i] > tree->rates->br_r[j]) rank += 1.0;
}
tree->rates->survival_rank[i] = rank;
}
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
phyml-20120412/src/times.h 0000644 0001750 0001750 00000007140 11664126546 012117 0000000 0000000 /*
PhyML: a program that computes maximum likelihood phylogenies from
DNA or AA homologous sequences.
Copyright (C) Stephane Guindon. Oct 2003 onward.
All parts of the source except where indicated are distributed under
the GNU public licence. See http://www.opensource.org for details.
*/
#include
#ifndef TIMES_H
#define TIMES_H
#include "spr.h"
#include "utilities.h"
#include "lk.h"
#include "optimiz.h"
#include "bionj.h"
#include "models.h"
#include "free.h"
#include "help.h"
#include "simu.h"
#include "eigen.h"
#include "pars.h"
#include "alrt.h"
#include "m4.h"
#include "draw.h"
#include "rates.h"
#include "mcmc.h"
#include "stats.h"
#include "tiporder.h"
#include
#include
#include
int TIMES_main(int argc, char **argv);
void TIMES_Bl_From_T_Post(t_node *a, t_node *d, t_edge *b, t_tree *tree);
void TIMES_Bl_From_T(t_tree *tree);
void TIMES_Optimize_Node_Times_Serie(t_node *a, t_node *d, t_tree *tree);
void TIMES_Round_Optimize(t_tree *tree);
void TIMES_Print_Node_Times(t_node *a, t_node *d, t_tree *tree);
t_edge *TIMES_Find_Best_Root_Position(t_tree *tree);
void TIMES_Least_Square_Node_Times(t_edge *e_root, t_tree *tree);
void TIMES_Least_Square_Node_Times_Pre(t_node *a, t_node *d, phydbl *A, phydbl *b, int n, t_tree *tree);
void TIMES_Mult_Time_Stamps(t_tree *tree);
void TIMES_Div_Time_Stamps(t_tree *tree);
void TIMES_Optimize_Tree_Height(t_tree *tree);
void TIMES_Adjust_Node_Times(t_tree *tree);
void TIMES_Adjust_Node_Times_Pre(t_node *a, t_node *d, t_tree *tree);
void TIMES_Optimize_Root_Height(t_tree *tree);
void TIMES_Estimate_Branch_Rates(t_tree *tree);
t_edge *TIMES_Find_Best_Root_Position_Approx(t_tree *tree);
void TIMES_Estimate_Branch_Rate_Parameter(t_tree *tree);
phydbl TIMES_Classify_Branch_In_Rate_Class(t_tree *tree);
void TIMES_Compute_Rates_And_Times_Least_Square_Adjustments(t_tree *tree);
void TIMES_Compute_Rates_And_Times_Least_Square_Adjustments_Post(t_node *a, t_node *d, t_edge *b, t_tree *tree);
void TIMES_Classify_Branch_Rates(t_tree *tree);
int TIMES_Check_MC(t_tree *tree);
void TIMES_Set_All_Node_Priors(t_tree *tree);
void TIMES_Set_All_Node_Priors_Bottom_Up(t_node *a, t_node *d, t_tree *tree);
void TIMES_Set_All_Node_Priors_Top_Down(t_node *a, t_node *d, t_tree *tree);
void TIMES_Set_Floor(t_tree *tree);
void TIMES_Set_Floor_Post(t_node *a, t_node *d, t_tree *tree);
phydbl TIMES_Log_Conditional_Uniform_Density(t_tree *tree);
phydbl TIMES_Log_Yule(t_tree *tree);
phydbl TIMES_Lk_Times(t_tree *tree);
void TIMES_Lk_Times_Trav(t_node *a, t_node *d, phydbl lim_inf, phydbl lim_sup, phydbl *logdens, t_tree *tree);
phydbl TIMES_Log_Number_Of_Ranked_Labelled_Histories(t_node *root, int per_slice, t_tree *tree);
void TIMES_Log_Number_Of_Ranked_Labelled_Histories_Post(t_node *a, t_node *d, int per_slice, phydbl *logn, t_tree *tree);
phydbl TIMES_Lk_Uniform_Core(t_tree *tree);
void TIMES_Get_Number_Of_Time_Slices(t_tree *tree);
void TIMES_Get_Number_Of_Time_Slices_Post(t_node *a, t_node *d, t_tree *tree);
void TIMES_Get_N_Slice_Spans(t_tree *tree);
void TIMES_Allocate_Vectors_Time_Slice_Combin(t_tree *tree);
void TIMES_Allocate_Vectors_Time_Slice_Combin_Post(t_node *a, t_node *d, t_tree *tree);
void TIMES_Update_Curr_Slice(t_tree *tree);
void TIMES_Lk_Uniform_Post(t_node *a, t_node *d, t_tree *tree);
void TIMES_Set_Root_Given_Tip_Dates(t_tree *tree);
void Get_Survival_Duration(t_tree *tree);
void Get_Survival_Duration_Post(t_node *a, t_node *d, t_tree *tree);
phydbl TIMES_Lk_Yule_Root_Marginal(t_tree *tree);
phydbl TIMES_Lk_Yule_Joint(t_tree *tree);
void TIMES_Update_Node_Ordering(t_tree *tree);
phydbl TIMES_Lk_Yule_Order(t_tree *tree);
#endif
phyml-20120412/src/cl.h 0000644 0001750 0001750 00000001063 11637265472 011374 0000000 0000000
/*
PHYML : a program that computes maximum likelihood phylogenies from
DNA or AA homologous sequences
Copyright (C) Stephane Guindon. Oct 2003 onward
All parts of the source except where indicated are distributed under
the GNU public licence. See http://www.opensource.org for details.
*/
#include
#ifndef CL_H
#define CL_H
#include
#include
#include "utilities.h"
#include "help.h"
#include "models.h"
#include "free.h"
#include "interface.h"
void Read_Command_Line(option *input, int argc, char **argv);
#endif
phyml-20120412/src/cl.c 0000644 0001750 0001750 00000107273 11741250130 011356 0000000 0000000 /*
PhyML: a program that computes maximum likelihood phyLOGenies from
DNA or AA homoLOGous sequences.
Copyright (C) Stephane Guindon. Oct 2003 onward.
All parts of the source except where indicated are distributed under
the GNU public licence. See http://www.opensource.org for details.
*/
#include "cl.h"
/*********************************************************/
/**
* Fill the Option fields, with the argc array
*/
void Read_Command_Line(option *io, int argc, char **argv)
{
int c;
int open_ps_file;
int use_gamma;
int writemode;
int idx;
if(argc == 1) Exit("\n. No argument was passed to the program. Please check the documentation. \n");
struct option longopts[] =
{
{"n_rgrft", required_argument,NULL,0},
{"n_globl", required_argument,NULL,1},
{"max_dist", required_argument,NULL,2},
{"n_optim", required_argument,NULL,3},
{"n_best", required_argument,NULL,4},
{"model", required_argument,NULL,5},
{"search", required_argument,NULL,6},
{"datatype", required_argument,NULL,7},
{"multiple", required_argument,NULL,8},
{"input", required_argument,NULL,9},
{"bootstrap", required_argument,NULL,10},
{"ts/tv", required_argument,NULL,11},
{"nclasses", required_argument,NULL,12},
{"pinv", required_argument,NULL,13},
{"alpha", required_argument,NULL,14},
{"inputtree", required_argument,NULL,15},
{"min_diff_lk_local", required_argument,NULL,16},
{"min_diff_lk_global",required_argument,NULL,17},
{"steph_spr", no_argument,NULL,18},
{"brent_it_max", required_argument,NULL,19},
{"rand_start", no_argument,NULL,20},
{"n_rand_starts", required_argument,NULL,21},
{"sequential", no_argument,NULL,22},
{"inside_opt", no_argument,NULL,23},
{"p_moves", required_argument,NULL,24},
{"fast_nni", no_argument,NULL,25},
{"g_pars", no_argument,NULL,26},
{"r_seed", required_argument,NULL,27},
{"collapse_boot", required_argument,NULL,28},
{"random_boot", required_argument,NULL,29},
{"print_trace", no_argument,NULL,30},
{"print_site_lnl", no_argument,NULL,31},
{"print_site_lk", no_argument,NULL,31},
{"cov", no_argument,NULL,32},
{"cov_delta", required_argument,NULL,33},
{"cov_alpha", required_argument,NULL,34},
{"cov_ncats", required_argument,NULL,35},
{"ps", no_argument,NULL,36},
{"cov_free", no_argument,NULL,37},
{"no_gap", no_argument,NULL,38},
{"n_rr_branch", required_argument,NULL,39},
{"append", no_argument,NULL,40},
{"no_five_branch", no_argument,NULL,41},
{"pars_thresh", required_argument,NULL,42},
{"min_diff_lk_move", required_argument,NULL,43},
{"hybrid", no_argument,NULL,44},
{"use_median", no_argument,NULL,45},
{"run_id", required_argument,NULL,46},
{"pars", no_argument,NULL,47},
{"quiet", no_argument,NULL,48},
{"version", no_argument,NULL,49},
{"calibration_file", required_argument,NULL,50},
{"calibration", required_argument,NULL,50},
{"clade_file", required_argument,NULL,50},
{"boot_progress_every", required_argument,NULL,51},
{"aa_rate_file", required_argument,NULL,52},
{"chain_len", required_argument,NULL,53},
{"sample_freq", required_argument,NULL,54},
{"burnin", required_argument,NULL,55},
{"no_memory_check", no_argument,NULL,56},
{"no_colalias", no_argument,NULL,57},
{"alias_subpatt", no_argument,NULL,58},
{"no_data", no_argument,NULL,59},
{"prior", no_argument,NULL,59},
{"fastlk", no_argument,NULL,60},
{"free_rates", no_argument,NULL,61},
{"freerates", no_argument,NULL,61},
{"is", no_argument,NULL,62},
// no 63 since it corresponds to character '?'
{"rate_model", required_argument,NULL,64},
{"ratemodel", required_argument,NULL,64},
{"log_l", no_argument,NULL,65},
{"gamma_lens", no_argument,NULL,66},
{"codpos", required_argument,NULL,67},
{"constraint_file", required_argument,NULL,68},
{"constraint_tree", required_argument,NULL,68},
{"help", no_argument,NULL,69},
{"mutmap", no_argument,NULL,70},
{"parvals", required_argument,NULL,71},
{"constrained_lens", no_argument,NULL,72},
{0,0,0,0}
};
io->datatype = UNDEFINED;
writemode = 1;
open_ps_file = 0;
use_gamma = 0;
idx=-1;
do
{
c = getopt_long(argc,argv,"qi:d:m:b:n:t:f:zk:v:c:a:u:ho:s:x:g:l:ep",longopts,&idx);
switch(c)
{
case 72:
{
io->mod->s_opt->constrained_br_len = YES;
break;
}
case 71:
{
io->mcmc->in_fp_par = fopen(optarg,"r");
io->mcmc->randomize = NO;
break;
}
case 70:
{
io->mutmap = YES;
break;
}
case 68:
{
char *tmp;
tmp = (char *)mCalloc(T_MAX_FILE, sizeof(char));
if(strlen(optarg) > T_MAX_FILE -11)
{
char choix;
strcpy (tmp, "\n. The file name'");
strcat (tmp, optarg);
strcat (tmp, "' is too long.\n");
PhyML_Printf("%s",tmp);
PhyML_Printf("\n. Type any key to exit.\n");
if(!scanf("%c",&choix)) Exit("\n");
Exit("\n");
}
else if (!Filexists (optarg))
{
char choix;
strcpy (tmp, "\n. The file '");
strcat (tmp, optarg);
strcat (tmp, "' doesn't exist.\n");
PhyML_Printf("%s",tmp);
PhyML_Printf("\n. Type any key to exit.\n");
if(!scanf("%c",&choix)) Exit("\n");
Exit("\n");
}
else
{
strcpy(io->in_constraint_tree_file, optarg);
io->fp_in_constraint_tree = Openfile(io->in_constraint_tree_file,0);
}
Free(tmp);
break;
}
case 67:
{
phydbl pos;
pos = atof(optarg);
io->codpos = (int)pos;
if(io->codpos < 1 || io->codpos > 3)
{
char choix;
PhyML_Printf("\n. Coding position must be set to 1, 2 or 3.\n");
PhyML_Printf("\n. Type any key to exit.\n");
if(!scanf("%c",&choix)) Exit("\n");
Exit("\n");
}
break;
break;
}
case 66:
{
io->mod->gamma_mgf_bl = YES;
io->mod->s_opt->opt_gamma_br_len = YES;
break;
}
case 65:
{
io->mod->log_l = YES;
break;
}
case 64:
{
char *s;
int i;
s = (char *)mCalloc(T_MAX_NAME,sizeof(char));
i = 0;
while(optarg[i++]) s[i]=tolower(optarg[i]);
if(!strcmp(optarg,"gbd")) io->rates->model = THORNE;
else if(!strcmp(optarg,"gbs")) io->rates->model = GUINDON;
else if(!strcmp(optarg,"gamma")) io->rates->model = GAMMA;
else if(!strcmp(optarg,"clock")) io->rates->model = STRICTCLOCK;
else if(!strcmp(optarg,"strictclock")) io->rates->model = STRICTCLOCK;
else if(!strcmp(optarg,"strict_clock")) io->rates->model = STRICTCLOCK;
else
{
PhyML_Printf("\n. rate_model should be 'gbs', 'gbd', 'gamma' or 'clock'.");
Exit("\n");
}
Free(s);
break;
}
case 62:
{
io->mcmc->is = YES;
break;
}
case 61:
{
io->mod->free_mixt_rates = YES;
io->mod->s_opt->opt_free_mixt_rates = YES;
break;
}
case 60:
{
io->lk_approx = NORMAL;
break;
}
case 59:
{
io->mcmc->use_data = NO;
break;
}
case 58:
{
io->do_alias_subpatt = YES;
break;
}
case 57:
{
io->colalias = NO;
break;
}
case 56:
{
io->mem_question = NO;
break;
}
case 55:
{
phydbl len;
len = atof(optarg);
io->mcmc->chain_len_burnin = (int)len;
if(io->mcmc->chain_len_burnin < 1)
{
char choix;
PhyML_Printf("\n. chain_len_burnin must be an integer greater than 0.\n");
PhyML_Printf("\n. Type any key to exit.\n");
if(!scanf("%c",&choix)) Exit("\n");
Exit("\n");
}
break;
}
case 54:
{
phydbl len;
len = atof(optarg);
io->mcmc->sample_interval = (int)len;
if(io->mcmc->sample_interval < 1)
{
char choix;
PhyML_Printf("\n. sample_interval must be an integer greater than 0.\n");
PhyML_Printf("\n. Type any key to exit.\n");
if(!scanf("%c",&choix)) Exit("\n");
Exit("\n");
}
break;
}
case 53:
{
phydbl len;
len = atof(optarg);
io->mcmc->chain_len = (int)len;
if(io->mcmc->chain_len < 1)
{
char choix;
PhyML_Printf("\n. chain_len must be an integer greater than 0.\n");
PhyML_Printf("\n. Type any key to exit.\n");
if(!scanf("%c",&choix)) Exit("\n");
Exit("\n");
}
break;
}
case 52:
{
char *s;
s = (char *)mCalloc(T_MAX_FILE, sizeof(char));
strcpy(s,optarg);
io->fp_aa_rate_mat = Openfile(s,0);
strcpy(io->aa_rate_mat_file,s);
Free(s);
break;
}
case 51:
{
io->boot_prog_every = atoi(optarg);
if(io->boot_prog_every < 1)
{
char choix;
PhyML_Printf("\n. boot_progress_every must be an integer greater than 0.\n");
PhyML_Printf("\n. Type any key to exit.\n");
if(!scanf("%c",&choix)) Exit("\n");
Exit("\n");
}
break;
}
case 50:
{
strcpy(io->clade_list_file,optarg);
break;
}
case 49:
{
PhyML_Printf("\n. This is PhyML version %s.\n\n",VERSION);
Exit("");
break;
}
case 48 :
{
io->quiet = 1;
break;
}
case 'p' : case 47 :
{
io->in_tree = 1;
break;
}
case 46 :
{
io->appebr_run_ID = 1;
strcpy(io->run_id_string,optarg);
break;
}
case 45 :
{
io->mod->gamma_median = 1;
break;
}
case 44 :
{
io->mod->s_opt->hybrid_thresh = 0;
break;
}
case 43 :
{
io->mod->s_opt->min_diff_lk_move = atof(optarg);
if(io->mod->s_opt->min_diff_lk_move < 0)
{
char choix;
PhyML_Printf("\n. Min_diff_lk_move must be a double greater than 0.\n");
PhyML_Printf("\n. Type any key to exit.\n");
if(!scanf("%c",&choix)) Exit("\n");
Exit("\n");
}
break;
}
case 42 :
{
io->mod->s_opt->pars_thresh = (int)atoi(optarg);
if(io->mod->s_opt->pars_thresh < 0)
{
PhyML_Printf("\n. The parsimony threshold must be an integer greater than 0.\n");
PhyML_Printf("\n. Type any key to exit.\n");
Exit("\n");
}
break;
}
case 41 :
{
io->mod->s_opt->opt_five_branch = 0;
break;
}
case 40 :
{
writemode = 2;
break;
}
case 39 :
{
break;
}
case 38 :
{
io->rm_ambigu = 1;
break;
}
case 37 :
{
io->mod->s_opt->opt_cov_free_rates = 1;
io->mod->m4mod->use_cov_alpha = 0;
io->mod->m4mod->use_cov_free = 1;
break;
}
case 36 :
{
open_ps_file = 1;
break;
}
case 35 :
{
io->mod->m4mod->n_h = (int)atoi(optarg);
if(io->mod->m4mod->n_h < 1)
{
char choix;
PhyML_Printf("\n. The number of classes must be greater than 0.\n");
PhyML_Printf("\n. Type any key to exit.\n");
if(!scanf("%c",&choix)) Exit("\n");
Exit("\n");
}
break;
}
case 34 :
{
io->mod->m4mod->use_cov_alpha = 1;
io->mod->m4mod->use_cov_free = 0;
if(!strcmp(optarg,"e") || !strcmp(optarg,"E") ||
!strcmp(optarg,"estimated") || !strcmp(optarg,"ESTIMATED"))
{
io->mod->s_opt->opt_cov_alpha = 1;
io->mod->m4mod->alpha = 1.0;
}
else
{
io->mod->m4mod->alpha = (phydbl)atof(optarg);
if(io->mod->m4mod->alpha < 1.E-5)
{
char choix;
PhyML_Printf("\n. The value of alpha must be greater than 1.E-5.\n");
PhyML_Printf("\n. Type any key to exit.\n");
if(!scanf("%c",&choix)) Exit("\n");
Exit("\n");
}
}
break;
}
case 33 :
{
if(!strcmp(optarg,"e") || !strcmp(optarg,"E") ||
!strcmp(optarg,"estimated") || !strcmp(optarg,"ESTIMATED"))
{
io->mod->s_opt->opt_cov_delta = YES;
io->mod->m4mod->delta = 1.0;
}
else
{
io->mod->m4mod->delta = (phydbl)atof(optarg);
if(atof(optarg) < 1.E-10)
{
char choix;
PhyML_Printf("\n. The value of delta must be larger than 1.E-10.\n");
PhyML_Printf("\n. Type any key to exit.\n");
if(!scanf("%c",&choix)) Exit("\n");
Exit("\n");
}
}
break;
}
case 32 :
{
io->mod->use_m4mod = YES;
break;
}
case 31 :
{
io->print_site_lnl = 1;
break;
}
case 30 :
{
io->print_trace = 1;
break;
}
case 29 :
{
io->random_boot_seq_order = (int)atoi(optarg);
break;
}
case 28 :
{
io->collapse_boot = (int)atoi(optarg);
break;
}
case 27 :
{
io->r_seed = (int)atoi(optarg);
break;
}
case 26 :
{
io->mod->s_opt->general_pars = 1;
break;
}
case 25 :
{
io->mod->s_opt->fast_nni = 1;
break;
}
case 24 :
{
io->mod->s_opt->p_moves_to_examine = (phydbl)atof(optarg);
break;
}
case 23 :
{
io->mod->s_opt->wim_inside_opt = 1;
break;
}
case 0 :
{
io->mod->s_opt->wim_n_rgrft = atoi(optarg);
break;
}
case 1 :
{
io->mod->s_opt->wim_n_globl = atoi(optarg);
break;
}
case 2 :
{
io->mod->s_opt->wim_max_dist = atoi(optarg);
break;
}
case 3 :
{
io->mod->s_opt->wim_n_optim = atoi(optarg);
break;
}
case 4 :
{
io->mod->s_opt->wim_n_best = atoi(optarg);
break;
}
case 16 :
{
io->mod->s_opt->min_diff_lk_local = atof(optarg);
break;
}
case 17 :
{
io->mod->s_opt->min_diff_lk_global = atof(optarg);
break;
}
case 18 :
{
io->mod->s_opt->steph_spr = 0;
io->mod->s_opt->greedy = 1;
break;
}
case 19 :
{
io->mod->s_opt->brent_it_max = atoi(optarg);
break;
}
case 20 :
{
io->mod->s_opt->random_input_tree = 1;
break;
}
case 21 :
{
io->mod->s_opt->random_input_tree = 1;
io->mod->s_opt->n_rand_starts = atoi(optarg);
if(io->mod->s_opt->n_rand_starts < 1) Exit("\n. Nunmber of random starting trees must be > 0.\n\n");
}
case 's':case 6:
{
if((!strcmp(optarg,"spr")) || (!strcmp(optarg,"SPR")))
{
io->mod->s_opt->topo_search = SPR_MOVE;
io->mod->s_opt->greedy = (io->mod->s_opt->steph_spr)?(0):(1);
}
else if((!strcmp(optarg,"nni")) || (!strcmp(optarg,"NNI")))
{
io->mod->s_opt->topo_search = NNI_MOVE;
io->mod->s_opt->random_input_tree = 0;
}
else if((!strcmp(optarg,"best")) || (!strcmp(optarg,"BEST")))
{
io->mod->s_opt->topo_search = BEST_OF_NNI_AND_SPR;
io->mod->s_opt->greedy = (io->mod->s_opt->steph_spr)?(0):(1);
}
break;
}
case 'd':case 7:
{
if(!strcmp(optarg,"nt"))
{
io->datatype = NT;
io->mod->ns = 4;
io->mod->state_len = 1;
io->mod->m4mod->n_o = 4;
if(
(io->mod->whichmodel == LG) ||
(io->mod->whichmodel == WAG) ||
(io->mod->whichmodel == DAYHOFF) ||
(io->mod->whichmodel == JTT) ||
(io->mod->whichmodel == BLOSUM62) ||
(io->mod->whichmodel == MTREV) ||
(io->mod->whichmodel == RTREV) ||
(io->mod->whichmodel == CPREV) ||
(io->mod->whichmodel == DCMUT) ||
(io->mod->whichmodel == VT) ||
(io->mod->whichmodel == MTMAM) ||
(io->mod->whichmodel == MTART) ||
(io->mod->whichmodel == HIVW) ||
(io->mod->whichmodel == HIVB) ||
(io->mod->whichmodel == CUSTOMAA)
)
{
io->mod->whichmodel = HKY85;
strcpy(io->mod->modelname, "HKY85\0");
}
}
else if (!strcmp(optarg,"aa"))
{
io->datatype = AA;
io->mod->state_len = 1;
io->mod->s_opt->opt_kappa = 0;
io->mod->ns = 20;
io->mod->m4mod->n_o = 20;
if(
(io->mod->whichmodel == JC69) ||
(io->mod->whichmodel == K80) ||
(io->mod->whichmodel == F81) ||
(io->mod->whichmodel == HKY85) ||
(io->mod->whichmodel == F84) ||
(io->mod->whichmodel == TN93) ||
(io->mod->whichmodel == GTR) ||
(io->mod->whichmodel == CUSTOM)
)
{
io->mod->whichmodel = LG;
strcpy(io->mod->modelname, "LG\0");
}
}
else if ((!strcmp(optarg,"generic")) || (!strcmp(optarg,"gen")))
{
io->datatype = GENERIC;
}
else
{
char choix;
PhyML_Printf("\n. Unknown argument to -d option: please use `nt' for DNA or `aa' for Amino-Acids\n");
PhyML_Printf("\n. Type any key to exit.\n");
if(!scanf("%c",&choix)) Exit("\n");
Exit("\n");
}
break;
}
case 'm': case 5 :
{
int i;
For(i,strlen(optarg)) Uppercase(optarg+i);
if(!isalpha(optarg[0]))
{
strcpy(io->mod->custom_mod_string,optarg);
if(strlen(io->mod->custom_mod_string) != 6)
{
Warn_And_Exit("\n. The string should be of length 6.\n");
}
else
{
Make_Custom_Model(io->mod);
Translate_Custom_Mod_String(io->mod);
}
io->datatype = NT;
io->mod->whichmodel = CUSTOM;
strcpy(io->mod->modelname, "custom");
io->mod->s_opt->opt_kappa = 0;
io->mod->s_opt->opt_rr = 1;
}
else if (strcmp(optarg, "JC69") == 0)
{
io->datatype = NT;
io->mod->whichmodel = JC69;
}
else if(strcmp(optarg, "K80") == 0)
{
io->datatype = NT;
io->mod->whichmodel = K80;
}
else if(strcmp(optarg, "F81") == 0)
{
io->datatype = NT;
io->mod->whichmodel = F81;
}
else if (strcmp(optarg, "HKY85") == 0)
{
io->datatype = NT;
io->mod->whichmodel = HKY85;
}
else if(strcmp(optarg, "F84") == 0)
{
io->datatype = NT;
io->mod->whichmodel = F84;
}
else if (strcmp (optarg,"TN93") == 0)
{
io->datatype = NT;
io->mod->whichmodel = TN93;
}
else if(strcmp (optarg, "GTR") == 0)
{
io->datatype = NT;
io->mod->whichmodel = GTR;
}
else if(strcmp(optarg, "DAYHOFF") == 0)
{
io->datatype = AA;
io->mod->whichmodel = DAYHOFF;
}
else if(strcmp (optarg, "JTT") == 0)
{
io->datatype = AA;
io->mod->whichmodel = JTT;
}
else if(strcmp(optarg, "MTREV") == 0)
{
io->datatype = AA;
io->mod->whichmodel = MTREV;
}
else if(strcmp (optarg, "LG") == 0)
{
io->datatype = AA;
io->mod->whichmodel = LG;
}
else if(strcmp (optarg, "WAG") == 0)
{
io->datatype = AA;
io->mod->whichmodel = WAG;
}
else if(strcmp(optarg, "DCMUT") == 0)
{
io->datatype = AA;
io->mod->whichmodel = DCMUT;
}
else if(strcmp (optarg, "RTREV") == 0)
{
io->datatype = AA;
io->mod->whichmodel = RTREV;
}
else if(strcmp(optarg, "CPREV") == 0)
{
io->datatype = AA;
io->mod->whichmodel = CPREV;
}
else if(strcmp(optarg, "VT") == 0)
{
io->datatype = AA;
io->mod->whichmodel = VT;
}
else if(strcmp(optarg, "BLOSUM62") == 0)
{
io->datatype = AA;
io->mod->whichmodel = BLOSUM62;
}
else if(strcmp(optarg, "MTMAM") == 0)
{
io->datatype = AA;
io->mod->whichmodel = MTMAM;
}
else if (strcmp(optarg,"MTART") == 0)
{
io->datatype = AA;
io->mod->whichmodel = MTART;
}
else if (strcmp(optarg,"HIVW") == 0)
{
io->datatype = AA;
io->mod->whichmodel = HIVW;
}
else if(strcmp(optarg, "HIVB") == 0)
{
io->datatype = AA;
io->mod->whichmodel = HIVB;
}
else if (strcmp(optarg, "CUSTOM") == 0)
{
io->datatype = AA;
io->mod->whichmodel = CUSTOMAA;
}
else
{
PhyML_Printf("\n. The model name is incorrect. Please see the documentation.\n");
Exit("\n");
}
Set_Model_Name(io->mod);
break;
}
case 'a':case 14 :
{
use_gamma = 1;
if ((strcmp (optarg, "e") == 0) ||
(strcmp (optarg, "E") == 0) ||
(strcmp (optarg, "estimated") == 0) ||
(strcmp (optarg, "ESTIMATED") == 0))
{
io->mod->s_opt->opt_alpha = 1;
}
else if (atof(optarg) < 1.E-10)
{
char choix;
PhyML_Printf("\n. Alpha must be > 1.E-10.\n");
PhyML_Printf("\n. Type any key to exit.\n");
if(!scanf("%c",&choix)) Exit("\n");
Exit("\n");
}
else
{
io->mod->alpha->v = (phydbl)atof(optarg);
io->mod->s_opt->opt_alpha = 0;
}
break;
}
case 'b':case 10:
{
if (atoi(optarg) < -5)
{
char choix;
PhyML_Printf("\n. Branch test value must be a positive integer for bootstrap, or between -1 and -4 for aLRT branch test\n");
PhyML_Printf("\n. Type any key to exit.\n");
if(!scanf("%c",&choix)) Exit("\n");
Exit("\n");
}
else
{
if((int)atoi(optarg) > 0)
{
io->ratio_test = 0;
io->mod->bootstrap = (int)atoi(optarg);
io->print_boot_trees = 1;
if(io->n_data_sets > 1)
{
char choix;
PhyML_Printf("\n. Bootstrap option is not allowed with multiple data sets\n");
PhyML_Printf("\n. Type any key to exit.\n");
if(!scanf("%c",&choix)) Exit("\n");
Exit("\n");
}
}
else if (atoi(optarg)==0)
{
io->mod->bootstrap = 0;
io->ratio_test = 0;
}
else
{
io->mod->bootstrap = 0;
io->ratio_test = -(int)atoi(optarg);
}
}
break;
}
case 'c':case 12:
{
if ((!atoi(optarg)) || (atoi(optarg) < 0))
{
char choix;
PhyML_Printf("\n. Unknown argument to -c option: the number of rate categories must be a positive integer\n");
PhyML_Printf("\n. Type any key to exit.\n");
if(!scanf("%c",&choix)) Exit("\n");
Exit("\n");
}
else
{
io->mod->n_catg = atoi(optarg);
if(io->mod->n_catg < 1)
{
PhyML_Printf("\n. The number of rate categories must be a positive integer\n");
Exit("\n");
}
}
break;
}
case 'f':
{
if(!strcmp(optarg,"e"))
{
if(io->datatype == NT)
io->mod->s_opt->opt_state_freq = NO;
else if (io->datatype == AA)
io->mod->s_opt->opt_state_freq = YES;
else
{
PhyML_Printf("\n. Please define the data type (nt or aa) before setting the -f option\n");
Exit("\n");
}
}
else if(!strcmp(optarg,"m"))
{
if (io->datatype == NT)
io->mod->s_opt->opt_state_freq = YES;
else if (io->datatype == AA)
io->mod->s_opt->opt_state_freq = NO;
else
{
PhyML_Printf("\n. Please define the data type (nt or aa) before setting the -f option\n");
Exit("\n");
}
}
else if(!isalpha(optarg[0]))
{
phydbl sum;
double val1,val2,val3,val4;
io->mod->s_opt->opt_state_freq = 0;
io->mod->s_opt->user_state_freq = 1;
/* sscanf(optarg,"%lf,%lf,%lf,%lf", */
/* io->mod->user_b_freq, */
/* io->mod->user_b_freq+1, */
/* io->mod->user_b_freq+2, */
/* io->mod->user_b_freq+3); */
sscanf(optarg,"%lf,%lf,%lf,%lf",&val1,&val2,&val3,&val4);
io->mod->user_b_freq->v[0] = (phydbl)val1;
io->mod->user_b_freq->v[1] = (phydbl)val2;
io->mod->user_b_freq->v[2] = (phydbl)val3;
io->mod->user_b_freq->v[3] = (phydbl)val4;
sum =
(io->mod->user_b_freq->v[0] +
io->mod->user_b_freq->v[1] +
io->mod->user_b_freq->v[2] +
io->mod->user_b_freq->v[3]);
io->mod->user_b_freq->v[0] /= sum;
io->mod->user_b_freq->v[1] /= sum;
io->mod->user_b_freq->v[2] /= sum;
io->mod->user_b_freq->v[3] /= sum;
if(io->mod->user_b_freq->v[0] < .0 ||
io->mod->user_b_freq->v[1] < .0 ||
io->mod->user_b_freq->v[2] < .0 ||
io->mod->user_b_freq->v[3] < .0 ||
io->mod->user_b_freq->v[0] > 1. ||
io->mod->user_b_freq->v[1] > 1. ||
io->mod->user_b_freq->v[2] > 1. ||
io->mod->user_b_freq->v[3] > 1.)
{
Warn_And_Exit("\n. Invalid base frequencies.\n");
}
}
break;
}
case 'h':case 69:
{
Usage();
break;
}
case 'i':case 9:
{
char *tmp;
tmp = (char *) mCalloc (T_MAX_FILE, sizeof(char));
if (strlen (optarg) > T_MAX_FILE -16)
{
char choix;
strcpy (tmp, "\n. The file name'");
strcat (tmp, optarg);
strcat (tmp, "' is too long.\n");
PhyML_Printf("%s",tmp);
PhyML_Printf("\n. Type any key to exit.\n");
if(!scanf("%c",&choix)) Exit("\n");
Exit("\n");
}
else if (!Filexists (optarg))
{
char choix;
strcpy (tmp, "\n. The file '");
strcat (tmp, optarg);
strcat (tmp, "' does not exist.\n");
PhyML_Printf("%s",tmp);
PhyML_Printf("\n. Type any key to exit.\n");
if(!scanf("%c",&choix)) Exit("\n");
Exit("\n");
}
else
{
strcpy(io->in_align_file, optarg);
io->fp_in_align = Openfile(io->in_align_file,0);
strcpy(io->out_tree_file,optarg);
#ifdef PHYML
strcat(io->out_tree_file,"_phyml_tree");
#elif(MC)
strcat(io->out_tree_file,"_mc_tree");
#elif(M4)
strcat(io->out_tree_file,"_m4_tree");
#endif
strcpy(io->out_stats_file,optarg);
#ifdef PHYML
strcat(io->out_stats_file,"_phyml_stats");
#elif(MC)
strcat(io->out_stats_file,"_mc_stats");
#elif(M4)
strcat(io->out_stats_file,"_m4_stats");
#endif
}
Free (tmp);
break;
}
case 't':case 11:
{
if ((io->mod->whichmodel != JC69) &&
(io->mod->whichmodel != F81) &&
(io->mod->whichmodel != GTR))
{
if ((strcmp(optarg, "e") == 0) ||
(strcmp(optarg, "E") == 0) ||
(strcmp(optarg, "estimated") == 0) ||
(strcmp(optarg, "ESTIMATED") == 0))
{
io->mod->kappa->v = 4.0;
io->mod->s_opt->opt_kappa = 1;
if (io->mod->whichmodel == TN93)
io->mod->s_opt->opt_lambda = 1;
}
else
{
if (atof(optarg) < .0)
{
char choix;
PhyML_Printf("\n. The ts/tv ratio must be a positive number\n");
PhyML_Printf("\n. Type any key to exit.\n");
if(!scanf("%c",&choix)) Exit("\n");
Exit("\n");
}
else
{
io->mod->kappa->v = (phydbl)atof(optarg);
io->mod->s_opt->opt_kappa = 0;
io->mod->s_opt->opt_lambda = 0;
}
}
}
break;
}
case 'n':case 8:
{
if ((!atoi(optarg)) || (atoi(optarg) < 0))
{
char choix;
PhyML_Printf("\n. The number of alignments must be a positive integer\n");
PhyML_Printf("\n. Type any key to exit.\n");
if(!scanf("%c",&choix)) Exit("\n");
Exit("\n");
}
else io->n_data_sets = atoi (optarg);
break;
}
case 'q':case 22:
{
io->interleaved = 0;
break;
}
case 'u':case 15:
{
char *tmp;
tmp = (char *)mCalloc(T_MAX_FILE, sizeof(char));
if(strlen(optarg) > T_MAX_FILE -11)
{
char choix;
strcpy (tmp, "\n. The file name'");
strcat (tmp, optarg);
strcat (tmp, "' is too long.\n");
PhyML_Printf("%s",tmp);
PhyML_Printf("\n. Type any key to exit.\n");
if(!scanf("%c",&choix)) Exit("\n");
Exit("\n");
}
else if (! Filexists (optarg))
{
char choix;
strcpy (tmp, "\n. The file '");
strcat (tmp, optarg);
strcat (tmp, "' doesn't exist.\n");
PhyML_Printf("%s",tmp);
PhyML_Printf("\n. Type any key to exit.\n");
if(!scanf("%c",&choix)) Exit("\n");
Exit("\n");
}
else
{
strcpy(io->in_tree_file, optarg);
io->in_tree = 2;
io->fp_in_tree = Openfile(io->in_tree_file,0);
}
Free(tmp);
break;
}
case 'v':case 13:
{
if ((strcmp (optarg, "e") == 0) ||
(strcmp (optarg, "E") == 0) ||
(strcmp (optarg, "estimated") == 0) ||
(strcmp (optarg, "ESTIMATED") == 0))
{
io->mod->s_opt->opt_pinvar = 1;
io->mod->invar = 1;
}
else if ((atof(optarg) < 0.0) || (atof(optarg) > 1.0))
{
char choix;
PhyML_Printf("\n. The proportion of invariable site must be a number between 0.0 and 1.0\n");
PhyML_Printf("\n. Type any key to exit.");
if(!scanf("%c",&choix)) Exit("\n");
Exit("\n");
}
else
{
io->mod->pinvar->v = (phydbl)atof(optarg);
if (io->mod->pinvar->v > 0.0+SMALL)
io->mod->invar = 1;
else
io->mod->invar = 0;
io->mod->s_opt->opt_pinvar = 0;
}
break;
}
case 'o':
{
if(!strcmp(optarg,"tlr"))
{
io->mod->s_opt->opt_topo = YES;
io->mod->s_opt->opt_bl = YES;
io->mod->s_opt->opt_subst_param = YES;
}
else if(!strcmp(optarg,"tl"))
{
io->mod->s_opt->opt_topo = YES;
io->mod->s_opt->opt_bl = YES;
io->mod->s_opt->opt_subst_param = NO;
}
else if(!strcmp(optarg,"t"))
{
Warn_And_Exit("\n. You can't optimize the topology without adjusting branch length too...\n");
}
else if(!strcmp(optarg,"lr"))
{
io->mod->s_opt->opt_topo = NO;
io->mod->s_opt->opt_bl = YES;
io->mod->s_opt->opt_subst_param = YES;
}
else if(!strcmp(optarg,"l"))
{
io->mod->s_opt->opt_topo = NO;
io->mod->s_opt->opt_bl = YES;
io->mod->s_opt->opt_subst_param = NO;
}
else if(!strcmp(optarg,"r"))
{
io->mod->s_opt->opt_topo = NO;
io->mod->s_opt->opt_bl = NO;
io->mod->s_opt->opt_subst_param = YES;
}
else if(!strcmp(optarg,"none") || !strcmp(optarg,"n"))
{
io->mod->s_opt->opt_topo = NO;
io->mod->s_opt->opt_bl = NO;
io->mod->s_opt->opt_subst_param = NO;
}
else
{
char choix;
PhyML_Printf ("\n. The optimization parameter must be 'tlr' or 'tl' or 'lr' or 'l' or 'r' or ''.");
PhyML_Printf("\n. Type any key to exit.\n");
if(!scanf("%c",&choix)) Exit("\n");
Exit("\n");
}
break;
}
case '?':
{
Exit("\n");
break;
}
case -1:
{
break;
}
default:
{
Usage();
break;
}
}
}while(c != -1);
/* if((io->mod->whichmodel == K80) || (io->mod->whichmodel == JC69)) */
/* { */
/* if(io->mod->s_opt->opt_state_freq) */
/* { */
/* char c; */
/* PhyML_Printf("\n. WARNING: nucleotide frequencies must be set to 1/4 with this model.\n"); */
/* PhyML_Printf("\n. Type the enter key to resume the analysis.\n"); */
/* scanf("%c",&c); */
/* } */
/* io->mod->s_opt->opt_state_freq = 0; */
/* } */
if(io->mod->s_opt->constrained_br_len == YES)
{
io->mod->s_opt->opt_topo = NO;
/* io->mod->s_opt->opt_bl = NO; */
}
#ifndef PHYML
if((open_ps_file) || (io->m4_model == YES))
{
strcpy(io->out_ps_file,io->in_align_file);
strcat(io->out_ps_file, "_mc_tree.ps");
io->fp_out_ps = Openfile(io->out_ps_file,1);
}
#endif
if(io->datatype == UNDEFINED) io->datatype = NT;
if((io->mod->s_opt->n_rand_starts) &&
(io->mod->s_opt->topo_search == NNI_MOVE) &&
(io->mod->s_opt->random_input_tree))
{
Warn_And_Exit("\n. The random starting tree option is only compatible with SPR based search options.\n");
}
if ((io->datatype == NT) && (io->mod->whichmodel > 10))
{
char choix;
PhyML_Printf("\n. Err: model incompatible with the data type. Please use JC69, K80, F81, HKY, F84, TN93 or GTR\n");
PhyML_Printf("\n. Type any key to exit.\n");
if(!scanf("%c",&choix)) Exit("\n");
Warn_And_Exit("\n");
}
else if ((io->datatype == AA) && (io->mod->whichmodel < 11))
{
char choix;
PhyML_Printf("\n. Err: model incompatible with the data type. Please use LG, Dayhoff, JTT, MtREV, WAG, DCMut, RtREV, CpREV, VT, Blosum62, MtMam, MtArt, HIVw or HIVb.\n");
PhyML_Printf("\n. Type any key to exit.\n");
if(!scanf("%c",&choix)) Exit("\n");
Exit("\n");
}
if(io->mod->use_m4mod == NO)
{
io->mod->s_opt->opt_cov_delta = 0;
io->mod->s_opt->opt_cov_alpha = 0;
io->mod->s_opt->opt_cov_free_rates = 0;
}
if((io->mod->s_opt->opt_cov_free_rates) && (io->mod->s_opt->opt_cov_alpha))
{
io->mod->s_opt->opt_cov_free_rates = 1;
io->mod->m4mod->use_cov_alpha = 0;
io->mod->m4mod->use_cov_free = 1;
}
if(io->print_site_lnl)
{
strcpy(io->out_lk_file,io->in_align_file);
strcat(io->out_lk_file, "_phyml_lk");
if(io->appebr_run_ID) { strcat(io->out_lk_file,"_"); strcat(io->out_lk_file,io->run_id_string); }
strcat(io->out_lk_file, ".txt");
io->fp_out_lk = Openfile(io->out_lk_file,1);
}
if(io->print_trace)
{
strcpy(io->out_trace_file,io->in_align_file);
strcat(io->out_trace_file,"_phyml_trace");
if(io->appebr_run_ID) { strcat(io->out_trace_file,"_"); strcat(io->out_trace_file,io->run_id_string); }
strcat(io->out_trace_file,".txt");
io->fp_out_trace = Openfile(io->out_trace_file,1);
}
if(io->mod->s_opt->random_input_tree)
{
strcpy(io->out_trees_file,io->in_align_file);
strcat(io->out_trees_file,"_phyml_rand_trees");
if(io->appebr_run_ID) { strcat(io->out_trees_file,"_"); strcat(io->out_trees_file,io->run_id_string); }
strcat(io->out_trees_file,".txt");
io->fp_out_trees = Openfile(io->out_trees_file,1);
}
if((io->print_boot_trees) && (io->mod->bootstrap > 0))
{
strcpy(io->out_boot_tree_file,io->in_align_file);
strcat(io->out_boot_tree_file,"_phyml_boot_trees");
if(io->appebr_run_ID) { strcat(io->out_boot_tree_file,"_"); strcat(io->out_boot_tree_file,io->run_id_string); }
strcat(io->out_boot_tree_file,".txt");
io->fp_out_boot_tree = Openfile(io->out_boot_tree_file,1);
strcpy(io->out_boot_stats_file,io->in_align_file);
strcat(io->out_boot_stats_file,"_phyml_boot_stats");
if(io->appebr_run_ID) { strcat(io->out_boot_stats_file,"_"); strcat(io->out_boot_stats_file,io->run_id_string); }
strcat(io->out_boot_stats_file,".txt");
io->fp_out_boot_stats = Openfile(io->out_boot_stats_file,1);
}
if(io->appebr_run_ID)
{
strcat(io->out_tree_file,"_");
strcat(io->out_stats_file,"_");
strcat(io->out_tree_file,io->run_id_string);
strcat(io->out_stats_file,io->run_id_string);
}
strcat(io->out_tree_file,".txt");
strcat(io->out_stats_file,".txt");
if(io->mod->n_catg == 1) io->mod->s_opt->opt_alpha = 0;
if(!io->mod->s_opt->opt_subst_param)
{
io->mod->s_opt->opt_alpha = 0;
io->mod->s_opt->opt_kappa = 0;
io->mod->s_opt->opt_lambda = 0;
io->mod->s_opt->opt_pinvar = 0;
io->mod->s_opt->opt_rr = 0;
}
if(io->mod->whichmodel != K80 &&
io->mod->whichmodel != HKY85 &&
io->mod->whichmodel != F84 &&
io->mod->whichmodel != TN93)
{
io->mod->s_opt->opt_kappa = 0;
}
if(io->datatype == AA && io->mod->whichmodel == CUSTOMAA && !io->fp_aa_rate_mat)
{
PhyML_Printf("\n. Custom model option with amino-acid requires you to specify a rate matrix file through the '--aa_rate_file' option.\n");
Exit("\n");
}
io->fp_out_tree = Openfile(io->out_tree_file,writemode);
io->fp_out_stats = Openfile(io->out_stats_file,writemode);
if(io->mod->whichmodel == GTR)
{
Make_Custom_Model(io->mod);
io->mod->s_opt->opt_rr = 1;
}
return;
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
phyml-20120412/src/times.c 0000644 0001750 0001750 00000130152 11730212533 012074 0000000 0000000 /*
PhyML: a program that computes maximum likelihood phylogenies from
DNA or AA homologous sequences.
Copyright (C) Stephane Guindon. Oct 2003 onward.
All parts of the source except where indicated are distributed under
the GNU public licence. See http://www.opensource.org for details.
*/
/* Routines for molecular clock trees and molecular dating */
#include "times.h"
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
#ifdef PHYTIME
int TIMES_main(int argc, char **argv)
{
align **data;
calign *cdata;
option *io;
t_tree *tree;
int n_otu, num_data_set;
int num_tree,tree_line_number,num_rand_tree;
matrix *mat;
model *mod;
time_t t_beg,t_end;
phydbl best_lnL,most_likely_size,tree_size;
int r_seed;
char *most_likely_tree;
int i;
int user_lk_approx;
#ifdef MPI
int rc;
rc = MPI_Init(&argc,&argv);
if (rc != MPI_SUCCESS) {
PhyML_Printf("\n. Error starting MPI program. Terminating.\n");
MPI_Abort(MPI_COMM_WORLD, rc);
}
MPI_Comm_size(MPI_COMM_WORLD,&Global_numTask);
MPI_Comm_rank(MPI_COMM_WORLD,&Global_myRank);
#endif
#ifdef QUIET
setvbuf(stdout,NULL,_IOFBF,2048);
#endif
tree = NULL;
mod = NULL;
data = NULL;
most_likely_tree = NULL;
best_lnL = UNLIKELY;
most_likely_size = -1.0;
tree_size = -1.0;
io = (option *)Get_Input(argc,argv);
r_seed = (io->r_seed < 0)?(time(NULL)):(io->r_seed);
/* !!!!!!!!!!!!!!!!!!!!!!!! */
/* r_seed = 1289246338; */
/* r_seed = 1289266727; */
/* r_seed = 1289422815; */
/* r_seed = 1289443891; */
/* r_seed = 1290652518; */
/* r_seed = 1292195490; */
/* r_seed = 1298284669; */
/* r_seed = 1298403366; */
/* r_seed = 1298509108; */
/* sys = system("sleep 5s"); */
/* r_seed = 1299649586; */
/* r_seed = 1302160422; */
/* r_seed = 1302576741; */
/* r_seed = 1302588678; */
/* r_seed = 1303247709; */
/* r_seed = 1303970631; */
/* r_seed = 1304059976; */
/* r_seed = 1306315195; */
/* r_seed = 1308263660; */
/* r_seed = 1313356025; */
io->r_seed = r_seed;
srand(r_seed); rand();
PhyML_Printf("\n. Seed: %d\n",r_seed);
PhyML_Printf("\n. Pid: %d\n",getpid());
Make_Model_Complete(io->mod);
mod = io->mod;
if(io->in_tree == 2) Test_Multiple_Data_Set_Format(io);
else io->n_trees = 1;
mat = NULL;
tree_line_number = 0;
if((io->n_data_sets > 1) && (io->n_trees > 1))
{
io->n_data_sets = MIN(io->n_trees,io->n_data_sets);
io->n_trees = MIN(io->n_trees,io->n_data_sets);
}
For(num_data_set,io->n_data_sets)
{
n_otu = 0;
best_lnL = UNLIKELY;
data = Get_Seq(io);
if(data)
{
if(io->n_data_sets > 1) PhyML_Printf("\n. Data set [#%d]\n",num_data_set+1);
PhyML_Printf("\n. Compressing sequences...\n");
cdata = Compact_Data(data,io);
Free_Seq(data,cdata->n_otu);
Check_Ambiguities(cdata,io->mod->io->datatype,io->mod->state_len);
for(num_tree=(io->n_trees == 1)?(0):(num_data_set);num_tree < io->n_trees;num_tree++)
{
if(!io->mod->s_opt->random_input_tree) io->mod->s_opt->n_rand_starts = 1;
For(num_rand_tree,io->mod->s_opt->n_rand_starts)
{
if((io->mod->s_opt->random_input_tree) && (io->mod->s_opt->topo_search != NNI_MOVE))
PhyML_Printf("\n. [Random start %3d/%3d]\n",num_rand_tree+1,io->mod->s_opt->n_rand_starts);
Init_Model(cdata,mod,io);
if(io->mod->use_m4mod) M4_Init_Model(mod->m4mod,cdata,mod);
/* A BioNJ tree is built here */
if(!io->in_tree) tree = Dist_And_BioNJ(cdata,mod,io);
/* A user-given tree is used here instead of BioNJ */
else tree = Read_User_Tree(cdata,mod,io);
if(io->fp_in_constraint_tree != NULL)
{
io->cstr_tree = Read_Tree_File_Phylip(io->fp_in_constraint_tree);
io->cstr_tree->rates = RATES_Make_Rate_Struct(io->cstr_tree->n_otu);
RATES_Init_Rate_Struct(io->cstr_tree->rates,io->rates,io->cstr_tree->n_otu);
}
if(!tree) continue;
if(!tree->n_root)
{
PhyML_Printf("\n. Sorry, PhyTime requires a rooted tree as input.");
Exit("\n");
}
time(&t_beg);
time(&(tree->t_beg));
tree->rates = RATES_Make_Rate_Struct(tree->n_otu);
RATES_Init_Rate_Struct(tree->rates,io->rates,tree->n_otu);
Update_Ancestors(tree->n_root,tree->n_root->v[0],tree);
Update_Ancestors(tree->n_root,tree->n_root->v[1],tree);
RATES_Fill_Lca_Table(tree);
tree->mod = mod;
tree->io = io;
tree->data = cdata;
tree->both_sides = 1;
tree->n_pattern = tree->data->crunch_len/tree->mod->state_len;
/* phydbl *l1,*l2,crit; */
/* int i; */
/* l1 = (phydbl *)mCalloc(2*tree->n_otu-1,sizeof(phydbl)); */
/* l2 = (phydbl *)mCalloc(2*tree->n_otu-1,sizeof(phydbl)); */
/* RATES_Bl_To_Bl(tree); */
/* For(i,2*tree->n_otu-2) l1[i] = tree->rates->cur_l[i]; */
/* TIMES_Least_Square_Node_Times(tree->e_root,tree); */
/* Branch_Lengths_To_Time_Lengths(tree); */
/* printf("\n. %s",Write_Tree(tree,NO)); */
/* For(i,2*tree->n_otu-2) l2[i] = tree->rates->cur_l[i]; */
/* crit = .0; */
/* For(i,2*tree->n_otu-2) crit += POW(l1[i]-l2[i],2); */
/* PhyML_Printf("\n. crit = %f",crit); */
/* Exit("\n"); */
Prepare_Tree_For_Lk(tree);
/* Read node age priors */
Read_Clade_Priors(io->clade_list_file,tree);
/* Set upper and lower bounds for all node ages */
TIMES_Set_All_Node_Priors(tree);
/* Count the number of time slices */
TIMES_Get_Number_Of_Time_Slices(tree);
/* Get_Edge_Binary_Coding_Number(tree); */
/* Exit("\n"); */
/* Print_CSeq_Select(stdout,NO,tree->data,tree); */
/* Exit("\n"); */
/* TIMES_Set_Root_Given_Tip_Dates(tree); */
/* int i; */
/* char *s; */
/* FILE *fp; */
/* For(i,2*tree->n_otu-2) tree->rates->cur_l[i] = 1.; */
/* s = Write_Tree(tree,NO); */
/* fp = fopen("rooted_tree","w"); */
/* fprintf(fp,"%s\n",s); */
/* fclose(fp); */
/* Exit("\n"); */
/* Work with log of branch lengths? */
if(tree->mod->log_l == YES) Log_Br_Len(tree);
if(io->mcmc->use_data == YES)
{
/* Force the exact likelihood score */
user_lk_approx = tree->io->lk_approx;
tree->io->lk_approx = EXACT;
/* MLE for branch lengths */
PhyML_Printf("\n");
Round_Optimize(tree,tree->data,ROUND_MAX);
/* Set vector of mean branch lengths for the Normal approximation
of the likelihood */
RATES_Set_Mean_L(tree);
/* Estimate the matrix of covariance for the Normal approximation of
the likelihood */
PhyML_Printf("\n");
PhyML_Printf("\n. Computing Hessian...");
tree->rates->bl_from_rt = 0;
Free(tree->rates->cov_l);
tree->rates->cov_l = Hessian_Seo(tree);
/* tree->rates->cov_l = Hessian_Log(tree); */
For(i,(2*tree->n_otu-3)*(2*tree->n_otu-3)) tree->rates->cov_l[i] *= -1.0;
if(!Iter_Matinv(tree->rates->cov_l,2*tree->n_otu-3,2*tree->n_otu-3,YES)) Exit("\n");
tree->rates->covdet = Matrix_Det(tree->rates->cov_l,2*tree->n_otu-3,YES);
For(i,(2*tree->n_otu-3)*(2*tree->n_otu-3)) tree->rates->invcov[i] = tree->rates->cov_l[i];
if(!Iter_Matinv(tree->rates->invcov,2*tree->n_otu-3,2*tree->n_otu-3,YES)) Exit("\n");
tree->rates->grad_l = Gradient(tree);
/* Pre-calculation of conditional variances to speed up calculations */
RATES_Bl_To_Ml(tree);
RATES_Get_Conditional_Variances(tree);
RATES_Get_All_Reg_Coeff(tree);
RATES_Get_Trip_Conditional_Variances(tree);
RATES_Get_All_Trip_Reg_Coeff(tree);
Lk(tree);
PhyML_Printf("\n");
PhyML_Printf("\n. p(data|model) [exact ] ~ %.2f",tree->c_lnL);
tree->io->lk_approx = NORMAL;
For(i,2*tree->n_otu-3) tree->rates->u_cur_l[i] = tree->rates->mean_l[i] ;
tree->c_lnL = Lk(tree);
PhyML_Printf("\n. p(data|model) [approx] ~ %.2f",tree->c_lnL);
tree->io->lk_approx = user_lk_approx;
}
tree->rates->model = io->rates->model;
PhyML_Printf("\n. Selected model '%s'",RATES_Get_Model_Name(io->rates->model));
if(tree->rates->model == GUINDON) tree->mod->gamma_mgf_bl = YES;
tree->rates->bl_from_rt = YES;
if(tree->io->cstr_tree) Find_Surviving_Edges_In_Small_Tree(tree,tree->io->cstr_tree);
time(&t_beg);
tree->mcmc = MCMC_Make_MCMC_Struct();
MCMC_Copy_MCMC_Struct(tree->io->mcmc,tree->mcmc,"phytime");
MCMC_Complete_MCMC(tree->mcmc,tree);
tree->mcmc->is_burnin = NO;
MCMC(tree);
MCMC_Close_MCMC(tree->mcmc);
MCMC_Free_MCMC(tree->mcmc);
PhyML_Printf("\n");
/* tree->mcmc = MCMC_Make_MCMC_Struct(); */
/* MCMC_Copy_MCMC_Struct(tree->io->mcmc,tree->mcmc,"burnin"); */
/* MCMC_Complete_MCMC(tree->mcmc,tree); */
/* tree->mcmc->adjust_tuning = YES; */
/* tree->mcmc->is_burnin = YES; */
/* tree->mcmc->chain_len = tree->io->mcmc->chain_len_burnin; */
/* MCMC(tree); */
/* MCMC_Close_MCMC(tree->mcmc); */
/* new_mcmc = MCMC_Make_MCMC_Struct(tree); */
/* MCMC_Complete_MCMC(new_mcmc,tree); */
/* MCMC_Copy_MCMC_Struct(tree->mcmc,new_mcmc,"phytime"); */
/* MCMC_Free_MCMC(tree->mcmc); */
/* tree->mcmc = new_mcmc; */
/* tree->mcmc->chain_len = tree->io->mcmc->chain_len; */
/* tree->mcmc->randomize = NO; */
/* tree->mcmc->adjust_tuning = NO; */
/* tree->mcmc->is_burnin = NO; */
/* time(&t_beg); */
/* MCMC(tree); */
/* MCMC_Close_MCMC(tree->mcmc); */
/* MCMC_Free_MCMC(tree->mcmc); */
/* PhyML_Printf("\n"); */
Free_Tree_Pars(tree);
Free_Tree_Lk(tree);
Free_Tree(tree);
}
break;
}
Free_Cseq(cdata);
}
}
Free_Model(mod);
if(io->fp_in_align) fclose(io->fp_in_align);
if(io->fp_in_tree) fclose(io->fp_in_tree);
if(io->fp_out_lk) fclose(io->fp_out_lk);
if(io->fp_out_tree) fclose(io->fp_out_tree);
if(io->fp_out_trees) fclose(io->fp_out_trees);
if(io->fp_out_stats) fclose(io->fp_out_stats);
Free(most_likely_tree);
Free_Input(io);
time(&t_end);
Print_Time_Info(t_beg,t_end);
#ifdef MPI
MPI_Finalize();
#endif
return 0;
}
#endif
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void TIMES_Least_Square_Node_Times(t_edge *e_root, t_tree *tree)
{
/* Solve A.x = b, where x are the t_node time estimated
under the least square criterion.
A is a n x n matrix, with n being the number of
nodes in a rooted tree (i.e. 2*n_otu-1).
*/
phydbl *A, *b, *x;
int n;
int i,j;
t_node *root;
n = 2*tree->n_otu-1;
A = (phydbl *)mCalloc(n*n,sizeof(phydbl));
b = (phydbl *)mCalloc(n, sizeof(phydbl));
x = (phydbl *)mCalloc(n, sizeof(phydbl));
if(!tree->n_root && e_root) Add_Root(e_root,tree);
else if(!e_root) Add_Root(tree->t_edges[0],tree);
root = tree->n_root;
TIMES_Least_Square_Node_Times_Pre(root,root->v[0],A,b,n,tree);
TIMES_Least_Square_Node_Times_Pre(root,root->v[1],A,b,n,tree);
b[root->num] = tree->e_root->l/2.;
A[root->num * n + root->num] = 1.0;
A[root->num * n + root->v[0]->num] = -.5;
A[root->num * n + root->v[1]->num] = -.5;
if(!Matinv(A, n, n,YES))
{
PhyML_Printf("\n. Err in file %s at line %d\n",__FILE__,__LINE__);
Exit("\n");
}
For(i,n) x[i] = .0;
For(i,n) For(j,n) x[i] += A[i*n+j] * b[j];
For(i,n-1) { tree->rates->nd_t[tree->t_nodes[i]->num] = -x[i]; }
tree->rates->nd_t[root->num] = -x[n-1];
tree->n_root->l[0] = tree->rates->nd_t[root->v[0]->num] - tree->rates->nd_t[root->num];
tree->n_root->l[1] = tree->rates->nd_t[root->v[1]->num] - tree->rates->nd_t[root->num];
////////////////////////////////////////
return;
////////////////////////////////////////
/* Rescale the t_node times such that the time at the root
is -100. This constraint implies that the clock rate
is fixed to the actual tree length divided by the tree
length measured in term of differences of t_node times */
phydbl scale_f,time_tree_length,tree_length;
scale_f = -100./tree->rates->nd_t[root->num];
For(i,2*tree->n_otu-1) tree->rates->nd_t[i] *= scale_f;
For(i,2*tree->n_otu-1) if(tree->rates->nd_t[i] > .0) tree->rates->nd_t[i] = .0;
time_tree_length = 0.0;
For(i,2*tree->n_otu-3)
if(tree->t_edges[i] != tree->e_root)
time_tree_length +=
FABS(tree->rates->nd_t[tree->t_edges[i]->left->num] -
tree->rates->nd_t[tree->t_edges[i]->rght->num]);
time_tree_length += FABS(tree->rates->nd_t[root->num] - tree->rates->nd_t[root->v[0]->num]);
time_tree_length += FABS(tree->rates->nd_t[root->num] - tree->rates->nd_t[root->v[1]->num]);
tree_length = 0.0;
For(i,2*tree->n_otu-3) tree_length += tree->t_edges[i]->l;
tree->rates->clock_r = tree_length / time_tree_length;
Free(A);
Free(b);
Free(x);
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void TIMES_Least_Square_Node_Times_Pre(t_node *a, t_node *d, phydbl *A, phydbl *b, int n, t_tree *tree)
{
if(d->tax)
{
A[d->num * n + d->num] = 1.;
/* Set the time stamp at tip nodes to 0.0 */
/* PhyML_Printf("\n. Tip t_node date set to 0"); */
b[d->num] = 0.0;
return;
}
else
{
int i;
For(i,3)
if((d->v[i] != a) && (d->b[i] != tree->e_root))
TIMES_Least_Square_Node_Times_Pre(d,d->v[i],A,b,n,tree);
A[d->num * n + d->num] = 1.;
b[d->num] = .0;
For(i,3)
{
A[d->num * n + d->v[i]->num] = -1./3.;
if(d->v[i] != a) b[d->num] += d->b[i]->l;
else b[d->num] -= d->b[i]->l;
}
b[d->num] /= 3.;
}
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
/* Adjust t_node times in order to have correct time stamp ranking with
respect to the tree topology */
void TIMES_Adjust_Node_Times(t_tree *tree)
{
TIMES_Adjust_Node_Times_Pre(tree->n_root->v[0],tree->n_root->v[1],tree);
TIMES_Adjust_Node_Times_Pre(tree->n_root->v[1],tree->n_root->v[0],tree);
if(tree->rates->nd_t[tree->n_root->num] > MIN(tree->rates->nd_t[tree->n_root->v[0]->num],
tree->rates->nd_t[tree->n_root->v[1]->num]))
{
tree->rates->nd_t[tree->n_root->num] = MIN(tree->rates->nd_t[tree->n_root->v[0]->num],
tree->rates->nd_t[tree->n_root->v[1]->num]);
}
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void TIMES_Adjust_Node_Times_Pre(t_node *a, t_node *d, t_tree *tree)
{
if(d->tax) return;
else
{
int i;
phydbl min_height;
For(i,3)
if((d->v[i] != a) && (d->b[i] != tree->e_root))
{
TIMES_Adjust_Node_Times_Pre(d,d->v[i],tree);
}
min_height = 0.0;
For(i,3)
{
if((d->v[i] != a) && (d->b[i] != tree->e_root))
{
if(tree->rates->nd_t[d->v[i]->num] < min_height)
{
min_height = tree->rates->nd_t[d->v[i]->num];
}
}
}
if(tree->rates->nd_t[d->num] > min_height) tree->rates->nd_t[d->num] = min_height;
if(tree->rates->nd_t[d->num] < -100.) tree->rates->nd_t[d->num] = -100.;
}
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
/* Multiply each time stamp at each internal
t_node by 'tree->time_stamp_mult'.
*/
void TIMES_Mult_Time_Stamps(t_tree *tree)
{
int i;
For(i,2*tree->n_otu-2) tree->rates->nd_t[tree->t_nodes[i]->num] *= FABS(tree->mod->s_opt->tree_size_mult);
tree->rates->nd_t[tree->n_root->num] *= FABS(tree->mod->s_opt->tree_size_mult);
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void TIMES_Print_Node_Times(t_node *a, t_node *d, t_tree *tree)
{
t_edge *b;
int i;
b = NULL;
For(i,3) if((d->v[i]) && (d->v[i] == a)) {b = d->b[i]; break;}
PhyML_Printf("\n. (%3d %3d) a->t = %12f d->t = %12f (#=%12f) b->l = %12f [%12f;%12f]",
a->num,d->num,
tree->rates->nd_t[a->num],
tree->rates->nd_t[d->num],
tree->rates->nd_t[a->num]-tree->rates->nd_t[d->num],
(b)?(b->l):(-1.0),
tree->rates->t_prior_min[d->num],
tree->rates->t_prior_max[d->num]);
if(d->tax) return;
else
{
int i;
For(i,3)
if((d->v[i] != a) && (d->b[i] != tree->e_root))
TIMES_Print_Node_Times(d,d->v[i],tree);
}
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void TIMES_Set_All_Node_Priors(t_tree *tree)
{
int i;
phydbl min_prior;
/* Set all t_prior_max values */
TIMES_Set_All_Node_Priors_Bottom_Up(tree->n_root,tree->n_root->v[0],tree);
TIMES_Set_All_Node_Priors_Bottom_Up(tree->n_root,tree->n_root->v[1],tree);
tree->rates->t_prior_max[tree->n_root->num] =
MIN(tree->rates->t_prior_max[tree->n_root->num],
MIN(tree->rates->t_prior_max[tree->n_root->v[0]->num],
tree->rates->t_prior_max[tree->n_root->v[1]->num]));
/* Set all t_prior_min values */
if(!tree->rates->t_has_prior[tree->n_root->num])
{
min_prior = 1.E+10;
For(i,2*tree->n_otu-2)
{
if(tree->rates->t_has_prior[i])
{
if(tree->rates->t_prior_min[i] < min_prior)
min_prior = tree->rates->t_prior_min[i];
}
}
tree->rates->t_prior_min[tree->n_root->num] = 2.0 * min_prior;
/* tree->rates->t_prior_min[tree->n_root->num] = 10. * min_prior; */
}
TIMES_Set_All_Node_Priors_Top_Down(tree->n_root,tree->n_root->v[0],tree);
TIMES_Set_All_Node_Priors_Top_Down(tree->n_root,tree->n_root->v[1],tree);
Get_Node_Ranks(tree);
TIMES_Set_Floor(tree);
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void TIMES_Set_All_Node_Priors_Bottom_Up(t_node *a, t_node *d, t_tree *tree)
{
int i;
phydbl t_sup;
if(d->tax) return;
else
{
t_node *v1, *v2; /* the two sons of d */
For(i,3)
{
if((d->v[i] != a) && (d->b[i] != tree->e_root))
{
TIMES_Set_All_Node_Priors_Bottom_Up(d,d->v[i],tree);
}
}
v1 = v2 = NULL;
For(i,3) if((d->v[i] != a) && (d->b[i] != tree->e_root))
{
if(!v1) v1 = d->v[i];
else v2 = d->v[i];
}
if(tree->rates->t_has_prior[d->num] == YES)
{
t_sup = MIN(tree->rates->t_prior_max[d->num],
MIN(tree->rates->t_prior_max[v1->num],
tree->rates->t_prior_max[v2->num]));
tree->rates->t_prior_max[d->num] = t_sup;
if(tree->rates->t_prior_max[d->num] < tree->rates->t_prior_min[d->num])
{
PhyML_Printf("\n. prior_min=%f prior_max=%f",tree->rates->t_prior_min[d->num],tree->rates->t_prior_max[d->num]);
PhyML_Printf("\n. Inconsistency in the prior settings detected at t_node %d",d->num);
PhyML_Printf("\n. Err in file %s at line %d\n\n",__FILE__,__LINE__);
Warn_And_Exit("\n");
}
}
else
{
tree->rates->t_prior_max[d->num] =
MIN(tree->rates->t_prior_max[v1->num],
tree->rates->t_prior_max[v2->num]);
}
}
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void TIMES_Set_All_Node_Priors_Top_Down(t_node *a, t_node *d, t_tree *tree)
{
if(d->tax) return;
else
{
int i;
if(tree->rates->t_has_prior[d->num] == YES)
{
tree->rates->t_prior_min[d->num] = MAX(tree->rates->t_prior_min[d->num],tree->rates->t_prior_min[a->num]);
if(tree->rates->t_prior_max[d->num] < tree->rates->t_prior_min[d->num])
{
PhyML_Printf("\n. prior_min=%f prior_max=%f",tree->rates->t_prior_min[d->num],tree->rates->t_prior_max[d->num]);
PhyML_Printf("\n. Inconsistency in the prior settings detected at t_node %d",d->num);
PhyML_Printf("\n. Err in file %s at line %d\n\n",__FILE__,__LINE__);
Warn_And_Exit("\n");
}
}
else
{
tree->rates->t_prior_min[d->num] = tree->rates->t_prior_min[a->num];
}
For(i,3)
{
if((d->v[i] != a) && (d->b[i] != tree->e_root))
{
TIMES_Set_All_Node_Priors_Top_Down(d,d->v[i],tree);
}
}
}
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void TIMES_Set_Floor(t_tree *tree)
{
TIMES_Set_Floor_Post(tree->n_root,tree->n_root->v[0],tree);
TIMES_Set_Floor_Post(tree->n_root,tree->n_root->v[1],tree);
tree->rates->t_floor[tree->n_root->num] = MIN(tree->rates->t_floor[tree->n_root->v[0]->num],
tree->rates->t_floor[tree->n_root->v[1]->num]);
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void TIMES_Set_Floor_Post(t_node *a, t_node *d, t_tree *tree)
{
if(d->tax)
{
tree->rates->t_floor[d->num] = tree->rates->nd_t[d->num];
d->rank_max = d->rank;
return;
}
else
{
int i;
t_node *v1,*v2;
v1 = v2 = NULL;
For(i,3)
{
if(d->v[i] != a && d->b[i] != tree->e_root)
{
TIMES_Set_Floor_Post(d,d->v[i],tree);
if(!v1) v1 = d->v[i];
else v2 = d->v[i];
}
}
tree->rates->t_floor[d->num] = MIN(tree->rates->t_floor[v1->num],
tree->rates->t_floor[v2->num]);
if(tree->rates->t_floor[v1->num] < tree->rates->t_floor[v2->num])
{
d->rank_max = v1->rank_max;
}
else if(tree->rates->t_floor[v2->num] < tree->rates->t_floor[v1->num])
{
d->rank_max = v2->rank_max;
}
else
{
d->rank_max = MAX(v1->rank_max,v2->rank_max);
}
}
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
/* Does it work for serial samples? */
phydbl TIMES_Log_Conditional_Uniform_Density(t_tree *tree)
{
phydbl min,max;
phydbl dens;
int i;
min = tree->rates->nd_t[tree->n_root->num];
dens = 0.0;
For(i,2*tree->n_otu-1)
{
if((tree->t_nodes[i]->tax == NO) && (tree->t_nodes[i] != tree->n_root))
{
max = tree->rates->t_floor[i];
dens += LOG(Dorder_Unif(tree->rates->nd_t[i],
tree->t_nodes[i]->rank-1,
tree->t_nodes[i]->rank_max-2,
min,max));
}
}
return dens;
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
// Returns the marginal density of tree height assuming the
// Yule model of speciation.
phydbl TIMES_Lk_Yule_Root_Marginal(t_tree *tree)
{
int n;
int j;
t_node *nd;
phydbl *t,*ts;
phydbl lbda;
phydbl T;
lbda = tree->rates->birth_rate;
t = tree->rates->nd_t;
ts = tree->rates->time_slice_lims;
T = ts[0] - t[tree->n_root->num];
n = 0;
nd = NULL;
For(j,2*tree->n_otu-2)
{
nd = tree->t_nodes[j];
if((t[nd->num] > ts[0] && t[nd->anc->num] < ts[0]) || // lineage that is crossing ts[0]
(nd->tax == YES && Are_Equal(t[nd->num],ts[0],1.E-6) == YES)) // tip that is lying on ts[0]
n++;
}
return LnGamma(n+1) + LOG(lbda) - 2.*lbda*T + (n-2.)*LOG(1. - EXP(-lbda*T));
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
// Returns the joint density of internal node heights assuming
// the Yule model of speciation.
phydbl TIMES_Lk_Yule_Joint(t_tree *tree)
{
int i,j;
phydbl loglk;
phydbl *t;
phydbl dt;
int n; // number of lineages at a given time point
phydbl lbda;
t_node *nd;
phydbl *ts,*tf;
int *tr;
phydbl eps;
int curr_ts;
phydbl top_t;
short int *interrupted;
phydbl sumdt;
interrupted = (short int *)mCalloc(tree->n_otu,sizeof(short int));
eps = 1.E-10;
t = tree->rates->nd_t;
ts = tree->rates->time_slice_lims;
tf = tree->rates->t_floor;
tr = tree->rates->t_ranked;
lbda = tree->rates->birth_rate;
curr_ts = 0;
TIMES_Update_Node_Ordering(tree);
For(j,tree->n_otu) interrupted[j] = NO;
loglk = .0;
sumdt = .0;
n = 1;
For(i,2*tree->n_otu-2) // t[tr[0]] is the oldest node, t[tr[1]], the second oldest and so on...
{
For(j,tree->n_otu)
if((t[j] < t[tr[i]]) && (interrupted[j] == NO))
{
interrupted[j] = YES;
n--; // How many lineages have stopped above t[tr[i]]?
}
top_t = t[tr[i+1]];
dt = top_t - t[tr[i]];
sumdt += dt;
/* printf("\n. %d node up=%d [%f] node do=%d [%f] dt=%f",i,tr[i],t[tr[i]],tr[i+1],t[tr[i+1]],dt); */
if(n<1)
{
PhyML_Printf("\n. i=%d tr[i]=%f",i,t[tr[i]]);
PhyML_Printf("\n. Err in file %s at line %d\n",__FILE__,__LINE__);
Exit("\n");
}
if(dt > 1.E-10) loglk += LOG((n+1)*lbda) - (n+1)*lbda*dt;
n++;
}
/* printf("\n. sumdt = %f th=%f",sumdt,tree->rates->nd_t[tree->n_root->num]); */
/* printf("\n0 loglk = %f",loglk); */
For(i,tree->rates->n_time_slices-1)
{
n = 0;
dt = 0.;
For(j,2*tree->n_otu-2)
{
nd = tree->t_nodes[j];
if(t[nd->num] > ts[i] && t[nd->anc->num] < ts[i]) // How many lineages are crossing this time slice limit?
{
n++;
if(t[nd->num] < dt) dt = t[nd->num]; // take the oldest node younger than the time slice
}
}
dt -= ts[i];
loglk += LOG(n*lbda) - n*lbda*dt;
}
/* printf("\n1 loglk = %f",loglk); */
Free(interrupted);
return loglk;
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
// Returns the conditional density of internal node heights
// given the tree height under the Yule model. Uses the order
// statistics 'simplification' as described in Yang and Rannala, 2005.
phydbl TIMES_Lk_Yule_Order(t_tree *tree)
{
int j;
phydbl *ts,*t,*tf;
t_node *n;
phydbl loglk;
phydbl loglbda;
phydbl lbda;
phydbl *tp_min,*tp_max;
phydbl lower_bound,upper_bound;
tp_min = tree->rates->t_prior_min;
tp_max = tree->rates->t_prior_max;
tf = tree->rates->t_floor;
ts = tree->rates->time_slice_lims;
t = tree->rates->nd_t;
n = NULL;
loglbda = LOG(tree->rates->birth_rate);
lbda = tree->rates->birth_rate;
lower_bound = -1.;
upper_bound = -1.;
loglk = 0.0;
For(j,2*tree->n_otu-2)
{
n = tree->t_nodes[j];
lower_bound = MAX(FABS(tf[j]),FABS(tp_max[j]));
upper_bound = MIN(FABS(t[tree->n_root->num]),FABS(tp_min[j]));
if(n->tax == NO)
{
loglk += (loglbda - lbda * FABS(t[j]));
loglk -= LOG(EXP(-lbda*lower_bound) - EXP(-lbda*upper_bound)); // incorporate calibration boundaries here.
}
}
return(loglk);
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
phydbl TIMES_Lk_Times(t_tree *tree)
{
phydbl condlogdens;
condlogdens = 0.0;
/* TIMES_Lk_Times_Trav(tree->n_root,tree->n_root->v[0], */
/* tree->rates->nd_t[tree->n_root->num], */
/* tree->rates->t_floor[tree->n_root->v[0]->num],&condlogdens,tree); */
/* TIMES_Lk_Times_Trav(tree->n_root,tree->n_root->v[1], */
/* tree->rates->nd_t[tree->n_root->num], */
/* tree->rates->t_floor[tree->n_root->v[1]->num],&condlogdens,tree); */
/* Count the number of internal node (minus the root node) in the deepest slice */
/* int i; */
/* int n_nodes = 0; */
/* For(i,2*tree->n_otu-2) */
/* { */
/* if(tree->t_nodes[i]->tax == NO && tree->t_nodes[i] != tree->n_root) */
/* { */
/* if(!(tree->rates->nd_t[i] > tree->rates->t_floor[tree->n_root->num])) */
/* { */
/* n_nodes++; */
/* } */
/* } */
/* } */
/* condlogdens = -(phydbl)(n_nodes)*LOG(tree->rates->t_floor[tree->n_root->num] - tree->rates->nd_t[tree->n_root->num]); */
/* int i; */
/* condlogdens = 0.0; */
/* birthr = tree->rates->birth_rate; */
/* For(i,2*tree->n_otu-1) */
/* { */
/* if(tree->t_nodes[i]->tax == NO && tree->t_nodes[i] != tree->n_root) */
/* { */
/* /\* condlogdens -= birthr*(tree->rates->t_floor[i] - tree->rates->nd_t[i]); *\/ */
/* /\* condlogdens -= LOG(1.-EXP(-birthr*(tree->rates->t_floor[i] - tree->rates->nd_t[tree->n_root->num]))); *\/ */
/* condlogdens -= birthr*( tree->rates->nd_t[i] - tree->rates->nd_t[tree->n_root->num]); */
/* /\* condlogdens -= LOG((1.-EXP(-birthr*( - tree->rates->nd_t[tree->n_root->num])))- *\/ */
/* /\* (1.-EXP(-birthr*( - tree->rates->t_floor[i] )))); *\/ */
/* condlogdens -= LOG((1.-EXP(-birthr*( - tree->rates->nd_t[tree->n_root->num])))); */
/* } */
/* } */
/* condlogdens += (tree->n_otu-2)*LOG(birthr); */
/* tree->rates->c_lnL_times = TIMES_Lk_Yule_Joint(tree); */
/* tree->rates->c_lnL_times -= TIMES_Lk_Yule_Root_Marginal(tree); */
/* phydbl v1 = tree->rates->c_lnL_times; */
/* tree->rates->nd_t[tree->n_root->num] = -5.; */
/* tree->rates->nd_t[4] = -2.0; */
/* tree->rates->nd_t[5] = -0.5; */
/* tree->rates->birth_rate = 2.; */
tree->rates->c_lnL_times = TIMES_Lk_Yule_Order(tree);
/* printf("\n. == %f [t1=%f; t2=%f; t0=%f; lbda=%f]", */
/* v2, */
/* tree->rates->nd_t[4], */
/* tree->rates->nd_t[5], */
/* tree->rates->nd_t[tree->n_root->num], */
/* tree->rates->birth_rate); */
/* Exit("\n"); */
/* phydbl loglk; */
/* phydbl lbda = tree->rates->birth_rate; */
/* phydbl *t = tree->rates->nd_t; */
/* phydbl num,denom; */
/* phydbl num1,num2; */
/* phydbl t0,t1,x,y; */
/* t0 = t[tree->n_root->num]; */
/* t1 = t[tree->n_otu]; */
/* x = t1 - t0; */
/* y = -t1; */
/* num1 = LOG(2*lbda) - 2*lbda*x; */
/* num2 = LOG(3*lbda) - 3*lbda*y; */
/* num = num1+num2; */
/* printf("\n. num = %f %f x=%f y=%f lbda=%f",num,TIMES_Lk_Yule_Joint(tree),x,y,lbda); */
/* denom = LOG(lbda) + LOG(1.-EXP(-lbda*(x+y))) - 2.*lbda*(x+y); */
/* printf("\n. denom = %f %f",denom,TIMES_Lk_Yule_Root_Marginal(tree)); */
/* loglk = LOG(lbda) - lbda*FABS(t1) - LOG(1.-EXP(-lbda*FABS(t0))); */
/* printf("\n. %f %f %f", */
/* tree->rates->c_lnL_times,loglk,num-denom); */
/* printf("\n. %f",tree->rates->c_lnL_times); */
/* int i; */
/* phydbl loglk; */
/* phydbl lbda = tree->rates->birth_rate; */
/* phydbl *t = tree->rates->nd_t; */
/* phydbl t0,t1,t2; */
/* phydbl x,y,z; */
/* phydbl num,denom; */
/* t0 = FABS(t[tree->n_root->num]); */
/* t1 = FABS(MIN(t[tree->n_otu],t[tree->n_otu+1])); */
/* t2 = FABS(MAX(t[tree->n_otu],t[tree->n_otu+1])); */
/* x = t0 - t1; */
/* y = t1 - t2; */
/* z = t2; */
/* num = LOG(2*lbda*EXP(-2.*lbda*x) * 3*lbda*EXP(-3.*lbda*y) * 4*lbda*EXP(-4.*lbda*z)); */
/* denom = LOG(lbda*(1.-EXP(-lbda*t0))*(EXP(-lbda*t0*3))); */
/* printf("\n. num = %f %f",num, TIMES_Lk_Yule_Joint(tree)); */
/* printf("\n. denom = %f %f",denom, TIMES_Lk_Yule_Root_Marginal(tree)); */
/* loglk = 0.; */
/* For(i,2*tree->n_otu-2) if(tree->t_nodes[i]->tax == NO) loglk -= lbda * FABS(t[i]); */
/* loglk += (tree->n_otu-2.)*LOG(lbda); */
/* loglk -= (tree->n_otu-2.)*LOG(1.-EXP(lbda*t[tree->n_root->num])); */
/* printf("\n. loglk=%f %f %f [%f %f]",loglk,tree->rates->c_lnL_times,loglk-tree->rates->c_lnL_times,lbda,t[tree->n_root->num]); */
return(tree->rates->c_lnL_times);
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void TIMES_Lk_Times_Trav(t_node *a, t_node *d, phydbl lim_inf, phydbl lim_sup, phydbl *logdens, t_tree *tree)
{
int i;
if(!d->tax)
{
/* if(tree->rates->nd_t[d->num] > lim_sup) */
/* { */
/* lim_inf = lim_sup; */
/* lim_sup = 0.0; */
/* For(i,2*tree->n_otu-2) */
/* if((tree->rates->t_floor[i] < lim_sup) && (tree->rates->t_floor[i] > tree->rates->nd_t[d->num])) */
/* lim_sup = tree->rates->t_floor[i]; */
/* } */
/* if(tree->rates->nd_t[d->num] < lim_inf || tree->rates->nd_t[d->num] > lim_sup) */
/* { */
/* PhyML_Printf("\n. nd_t = %f lim_inf = %f lim_sup = %f",tree->rates->nd_t[d->num],lim_inf,lim_sup); */
/* PhyML_Printf("\n. Err in file %s at line %d\n",__FILE__,__LINE__); */
/* Exit("\n"); */
/* } */
lim_inf = tree->rates->nd_t[tree->n_root->num];
lim_sup = tree->rates->t_floor[d->num];
*logdens = *logdens + LOG(lim_sup - lim_inf);
}
if(d->tax == YES) return;
else
{
For(i,3)
{
if(d->v[i] != a && d->b[i] != tree->e_root)
{
TIMES_Lk_Times_Trav(d,d->v[i],lim_inf,lim_sup,logdens,tree);
}
}
}
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
phydbl TIMES_Log_Number_Of_Ranked_Labelled_Histories(t_node *root, int per_slice, t_tree *tree)
{
int i;
phydbl logn;
t_node *v1,*v2;
int dir1r,dir2r;
int n1,n2;
TIMES_Update_Curr_Slice(tree);
logn = .0;
v1 = v2 = NULL;
if(root == tree->n_root)
{
TIMES_Log_Number_Of_Ranked_Labelled_Histories_Post(root,root->v[0],per_slice,&logn,tree);
TIMES_Log_Number_Of_Ranked_Labelled_Histories_Post(root,root->v[1],per_slice,&logn,tree);
v1 = root->v[0];
v2 = root->v[1];
}
else
{
For(i,3)
{
if(root->v[i] != root->anc && root->b[i] != tree->e_root)
{
TIMES_Log_Number_Of_Ranked_Labelled_Histories_Post(root,root->v[i],per_slice,&logn,tree);
if(!v1) v1 = root->v[i];
else v2 = root->v[i];
}
}
}
dir1r = dir2r = -1;
For(i,3) if(v1->v[i] == root || v1->b[i] == tree->e_root) { dir1r = i; break; }
For(i,3) if(v2->v[i] == root || v2->b[i] == tree->e_root) { dir2r = i; break; }
if(per_slice == NO)
{
n1 = tree->rates->n_tips_below[v1->num];
n2 = tree->rates->n_tips_below[v2->num];
}
else
{
if(tree->rates->curr_slice[v1->num] == tree->rates->curr_slice[root->num])
n1 = tree->rates->n_tips_below[v1->num];
else
n1 = 1;
if(tree->rates->curr_slice[v2->num] == tree->rates->curr_slice[root->num])
n2 = tree->rates->n_tips_below[v2->num];
else
n2 = 1;
}
tree->rates->n_tips_below[root->num] = n1+n2;
logn += Factln(n1+n2-2) - Factln(n1-1) - Factln(n2-1);
return(logn);
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void TIMES_Log_Number_Of_Ranked_Labelled_Histories_Post(t_node *a, t_node *d, int per_slice, phydbl *logn, t_tree *tree)
{
if(d->tax == YES)
{
tree->rates->n_tips_below[d->num] = 1;
return;
}
else
{
int i,n1,n2;
t_node *v1, *v2;
int dir1d,dir2d;
For(i,3)
{
if(d->v[i] != a && d->b[i] != tree->e_root)
{
TIMES_Log_Number_Of_Ranked_Labelled_Histories_Post(d,d->v[i],per_slice,logn,tree);
}
}
v1 = v2 = NULL;
dir1d = dir2d = -1;
For(i,3)
{
if(d->v[i] != a && d->b[i] != tree->e_root)
{
if(v1 == NULL) {v1 = d->v[i];}
else {v2 = d->v[i];}
}
}
For(i,3) if(v1->v[i] == d) {dir1d = i; break;}
For(i,3) if(v2->v[i] == d) {dir2d = i; break;}
if(per_slice == NO)
{
n1 = tree->rates->n_tips_below[v1->num];
n2 = tree->rates->n_tips_below[v2->num];
}
else
{
if(tree->rates->curr_slice[v1->num] == tree->rates->curr_slice[d->num])
n1 = tree->rates->n_tips_below[v1->num];
else
n1 = 1;
if(tree->rates->curr_slice[v2->num] == tree->rates->curr_slice[d->num])
n2 = tree->rates->n_tips_below[v2->num];
else
n2 = 1;
}
tree->rates->n_tips_below[d->num] = n1+n2;
(*logn) += Factln(n1+n2-2) - Factln(n1-1) - Factln(n2-1);
}
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void TIMES_Update_Curr_Slice(t_tree *tree)
{
int i,j;
For(i,2*tree->n_otu-1)
{
For(j,tree->rates->n_time_slices)
{
if(!(tree->rates->nd_t[i] > tree->rates->time_slice_lims[j])) break;
}
tree->rates->curr_slice[i] = j;
/* PhyML_Printf("\n. Node %3d [%12f] is in slice %3d.",i,tree->rates->nd_t[i],j); */
}
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
phydbl TIMES_Lk_Uniform_Core(t_tree *tree)
{
phydbl logn;
logn = TIMES_Log_Number_Of_Ranked_Labelled_Histories(tree->n_root,YES,tree);
tree->rates->c_lnL_times = 0.0;
TIMES_Lk_Uniform_Post(tree->n_root,tree->n_root->v[0],tree);
TIMES_Lk_Uniform_Post(tree->n_root,tree->n_root->v[1],tree);
/* printf("\n. ^ %f %f %f", */
/* (phydbl)(tree->rates->n_tips_below[tree->n_root->num]-2.), */
/* LOG(tree->rates->time_slice_lims[tree->rates->curr_slice[tree->n_root->num]] - */
/* tree->rates->nd_t[tree->n_root->num]), */
/* (phydbl)(tree->rates->n_tips_below[tree->n_root->num]-2.) * */
/* LOG(tree->rates->time_slice_lims[tree->rates->curr_slice[tree->n_root->num]] - */
/* tree->rates->nd_t[tree->n_root->num])); */
tree->rates->c_lnL_times +=
Factln(tree->rates->n_tips_below[tree->n_root->num]-2.) -
(phydbl)(tree->rates->n_tips_below[tree->n_root->num]-2.) *
LOG(tree->rates->time_slice_lims[tree->rates->curr_slice[tree->n_root->num]] -
tree->rates->nd_t[tree->n_root->num]);
tree->rates->c_lnL_times -= logn;
return(tree->rates->c_lnL_times);
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void TIMES_Get_Number_Of_Time_Slices(t_tree *tree)
{
int i;
tree->rates->n_time_slices=0;
TIMES_Get_Number_Of_Time_Slices_Post(tree->n_root,tree->n_root->v[0],tree);
TIMES_Get_Number_Of_Time_Slices_Post(tree->n_root,tree->n_root->v[1],tree);
Qksort(tree->rates->time_slice_lims,NULL,0,tree->rates->n_time_slices-1);
if(tree->rates->n_time_slices > 1)
{
PhyML_Printf("\n");
PhyML_Printf("\n. Sequences were collected at %d different time points.",tree->rates->n_time_slices);
For(i,tree->rates->n_time_slices) printf("\n+ [%3d] time point @ %12f ",i+1,tree->rates->time_slice_lims[i]);
}
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void TIMES_Get_Number_Of_Time_Slices_Post(t_node *a, t_node *d, t_tree *tree)
{
int i;
if(d->tax == YES)
{
For(i,tree->rates->n_time_slices)
if(Are_Equal(tree->rates->t_floor[d->num],tree->rates->time_slice_lims[i],1.E-6)) break;
if(i == tree->rates->n_time_slices)
{
tree->rates->time_slice_lims[i] = tree->rates->t_floor[d->num];
tree->rates->n_time_slices++;
}
return;
}
else
{
For(i,3)
if(d->v[i] != a && d->b[i] != tree->e_root)
TIMES_Get_Number_Of_Time_Slices_Post(d,d->v[i],tree);
}
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void TIMES_Get_N_Slice_Spans(t_tree *tree)
{
int i,j;
For(i,2*tree->n_otu-2)
{
if(tree->t_nodes[i]->tax == NO)
{
For(j,tree->rates->n_time_slices)
{
if(Are_Equal(tree->rates->t_floor[i],tree->rates->time_slice_lims[j],1.E-6))
{
tree->rates->n_time_slice_spans[i] = j+1;
/* PhyML_Printf("\n. Node %3d spans %3d slices [%12f].", */
/* i+1, */
/* tree->rates->n_slice_spans[i], */
/* tree->rates->t_floor[i]); */
break;
}
}
}
}
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void TIMES_Lk_Uniform_Post(t_node *a, t_node *d, t_tree *tree)
{
if(d->tax == YES) return;
else
{
int i;
For(i,3)
{
if(d->v[i] != a && d->b[i] != tree->e_root)
{
TIMES_Lk_Uniform_Post(d,d->v[i],tree);
}
}
if(tree->rates->curr_slice[a->num] != tree->rates->curr_slice[d->num])
{
tree->rates->c_lnL_times +=
Factln(tree->rates->n_tips_below[d->num]-1.) -
(phydbl)(tree->rates->n_tips_below[d->num]-1.) *
LOG(tree->rates->time_slice_lims[tree->rates->curr_slice[d->num]] -
tree->rates->nd_t[d->num]);
}
}
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
/* Set the root position so that most of the taxa in the outgroup
correspond to the most ancient time point.
*/
void TIMES_Set_Root_Given_Tip_Dates(t_tree *tree)
{
int i,j;
t_node *left,*rght;
int n_left_in, n_left_out;
int n_rght_in, n_rght_out;
t_edge *b,*best;
phydbl eps,score,max_score;
Free_Bip(tree);
Alloc_Bip(tree);
Get_Bip(tree->t_nodes[0],tree->t_nodes[0]->v[0],tree);
left = rght = NULL;
b = best = NULL;
n_left_in = n_left_out = -1;
n_rght_in = n_rght_out = -1;
eps = 1.E-6;
score = max_score = -1.;
For(i,2*tree->n_otu-3)
{
left = tree->t_edges[i]->left;
rght = tree->t_edges[i]->rght;
b = tree->t_edges[i];
n_left_in = 0;
For(j,left->bip_size[b->l_r])
if(FABS(tree->rates->nd_t[left->bip_node[b->l_r][j]->num] - tree->rates->time_slice_lims[0]) < eps)
n_left_in++;
n_left_out = left->bip_size[b->l_r]-n_left_in;
n_rght_in = 0;
For(j,rght->bip_size[b->r_l])
if(FABS(tree->rates->nd_t[rght->bip_node[b->r_l][j]->num] - tree->rates->time_slice_lims[0]) < eps)
n_rght_in++;
n_rght_out = rght->bip_size[b->r_l]-n_rght_in;
/* score = POW((phydbl)(n_left_in)/(phydbl)(n_left_in+n_left_out)- */
/* (phydbl)(n_rght_in)/(phydbl)(n_rght_in+n_rght_out),2); */
/* score = (phydbl)(n_left_in * n_rght_out + eps)/(n_left_out * n_rght_in + eps); */
/* score = (phydbl)(n_left_in * n_rght_out + eps); */
score = FABS((phydbl)((n_left_in+1.) * (n_rght_out+1.)) - (phydbl)((n_left_out+1.) * (n_rght_in+1.)));
if(score > max_score)
{
max_score = score;
best = b;
}
}
Add_Root(best,tree);
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void Get_Survival_Duration(t_tree *tree)
{
Get_Survival_Duration_Post(tree->n_root,tree->n_root->v[0],tree);
Get_Survival_Duration_Post(tree->n_root,tree->n_root->v[1],tree);
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void Get_Survival_Duration_Post(t_node *a, t_node *d, t_tree *tree)
{
if(d->tax)
{
tree->rates->survival_dur[d->num] = tree->rates->nd_t[d->num];
return;
}
else
{
int i;
t_node *v1, *v2;
For(i,3)
if(d->v[i] != a && d->b[i] != tree->e_root)
Get_Survival_Duration_Post(d,d->v[i],tree);
v1 = v2 = NULL;
For(i,3)
{
if(d->v[i] != a && d->b[i] != tree->e_root)
{
if(!v1) v1 = d->v[i];
else v2 = d->v[i];
}
}
tree->rates->survival_dur[d->num] = MAX(tree->rates->survival_dur[v1->num],
tree->rates->survival_dur[v2->num]);
}
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
/* Update the ranking of node heights. Use bubble sort algorithm */
void TIMES_Update_Node_Ordering(t_tree *tree)
{
int buff;
int i;
phydbl *t;
int swap = NO;
t = tree->rates->nd_t;
do
{
swap = NO;
For(i,2*tree->n_otu-2)
{
if(t[tree->rates->t_ranked[i]] > t[tree->rates->t_ranked[i+1]]) // Sort in ascending order
{
swap = YES;
buff = tree->rates->t_ranked[i];
tree->rates->t_ranked[i] = tree->rates->t_ranked[i+1];
tree->rates->t_ranked[i+1] = buff;
}
}
}
while(swap == YES);
/* For(i,2*tree->n_otu-1) */
/* { */
/* printf("\n. ..... %f",t[tree->rates->t_ranked[i]]); */
/* } */
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
phyml-20120412/src/utilities.c 0000644 0001750 0001750 00001336454 11741143316 013010 0000000 0000000 /*
PhyML: a program that computes maximum likelihood phylogenies from
DNA or AA homologous sequences.
Copyright (C) Stephane Guindon. Oct 2003 onward.
All parts of the source except where indicated are distributed under
the GNU public licence. See http://www.opensource.org for details.
*/
#include "utilities.h"
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
/* void Make_All_Edges_Light(t_node *a, t_node *d, int *curr_num_edge) */
/* { */
/* int i; */
/* Make_Edge_Light(a,d,*curr_num_edge); */
/* (*curr_num_edge)++; */
/* if(d->tax) return; */
/* else */
/* { */
/* For(i,3) */
/* { */
/* if(d->v[i] != a) */
/* Make_All_Edges_Light(d,d->v[i],curr_num_edge); */
/* } */
/* } */
/* } */
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void Make_All_Edges_Lk(t_node *a, t_node *d, t_tree *tree)
{
int i;
For(i,3) if((a->v[i]) && (a->v[i] == d)) Make_Edge_Lk(a->b[i],tree);
if(d->tax) return;
else
{
For(i,3)
{
if(d->v[i] != a)
Make_All_Edges_Lk(d,d->v[i],tree);
}
}
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
/* Tree parser function. We need to pass a pointer to the string of characters
since this string might be freed and then re-allocated by that function (i.e.,
its address in memory might change)
*/
t_tree *Read_Tree(char **s_tree)
{
char **subs;
int i,n_ext,n_int,n_otu;
t_tree *tree;
int degree,len;
t_node *root_node;
n_int = n_ext = 0;
n_otu=0;
For(i,(int)strlen((*s_tree))) if((*s_tree)[i] == ',') n_otu++;
n_otu+=1;
tree = Make_Tree_From_Scratch(n_otu,NULL);
subs = Sub_Trees((*s_tree),°ree);
Clean_Multifurcation(subs,degree,3);
if(degree == 2)
{
/* Unroot_Tree(subs); */
/* degree = 3; */
/* root_node = tree->t_nodes[n_otu]; */
root_node = tree->t_nodes[2*n_otu-2];
root_node->num = 2*n_otu-2;
tree->n_root = root_node;
n_int -= 1;
}
else
{
root_node = tree->t_nodes[n_otu];
root_node->num = n_otu;
tree->n_root = NULL;
}
if(degree > 3) /* Multifurcation at the root. Need to re-assemble the subtrees
since Clean_Multifurcation added sets of parenthesis and
the corresponding NULL edges */
{
degree = 3;
Free((*s_tree));
len = 0;
For(i,degree) len += (strlen(subs[i])+1);
len += 5;
(*s_tree) = (char *)mCalloc(len,sizeof(char));
(*s_tree)[0] = '('; (*s_tree)[1] = '\0';
For(i,degree)
{
strcat((*s_tree),subs[i]);
strcat((*s_tree),",\0");
}
sprintf((*s_tree)+strlen((*s_tree))-1,"%s",");\0");
For(i,NODE_DEG_MAX) Free(subs[i]);
Free(subs);
subs = Sub_Trees((*s_tree),°ree);
}
root_node->tax = 0;
tree->has_branch_lengths = 0;
tree->num_curr_branch_available = 0;
For(i,degree) R_rtree((*s_tree),subs[i],root_node,tree,&n_int,&n_ext);
for(i=degree;in_root)
{
tree->e_root = tree->t_edges[tree->num_curr_branch_available];
For(i,3) if(tree->n_root->v[0]->v[i] == tree->n_root) { tree->n_root->v[0]->v[i] = tree->n_root->v[1]; break; }
For(i,3) if(tree->n_root->v[1]->v[i] == tree->n_root) { tree->n_root->v[1]->v[i] = tree->n_root->v[0]; break; }
Connect_One_Edge_To_Two_Nodes(tree->n_root->v[0],
tree->n_root->v[1],
tree->e_root,
tree);
tree->e_root->l = tree->n_root->l[0] + tree->n_root->l[1];
if(tree->e_root->l > 0.0)
tree->n_root_pos = tree->n_root->l[0] / tree->e_root->l;
else
tree->n_root_pos = .5;
}
return tree;
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
/* 'a' in t_node a stands for ancestor. 'd' stands for descendant */
void R_rtree(char *s_tree_a, char *s_tree_d, t_node *a, t_tree *tree, int *n_int, int *n_ext)
{
int i;
t_node *d;
int n_otu = tree->n_otu;
if(strstr(s_tree_a," "))
{
PhyML_Printf("\n. [%s]",s_tree_a);
Warn_And_Exit("\n. Err: the tree must not contain a ' ' character\n");
}
if(s_tree_d[0] == '(')
{
char **subs;
int degree;
t_edge *b;
(*n_int)+=1;
if((*n_int + n_otu) == (2*n_otu-1))
{
PhyML_Printf("\n. The number of internal nodes in the tree exceeds the number of taxa minus one.");
PhyML_Printf("\n. There probably is a formating problem in the input tree.");
PhyML_Printf("\n. Err in file %s at line %d\n",__FILE__,__LINE__);
Exit("\n");
}
d = tree->t_nodes[n_otu+*n_int];
d->num = n_otu+*n_int;
d->tax = 0;
b = tree->t_edges[tree->num_curr_branch_available];
Read_Branch_Label(s_tree_d,s_tree_a,tree->t_edges[tree->num_curr_branch_available]);
Read_Branch_Length(s_tree_d,s_tree_a,tree);
For(i,3)
{
if(!a->v[i])
{
a->v[i]=d;
d->l[0]=tree->t_edges[tree->num_curr_branch_available]->l;
a->l[i]=tree->t_edges[tree->num_curr_branch_available]->l;
break;
}
}
d->v[0]=a;
if(a != tree->n_root)
{
Connect_One_Edge_To_Two_Nodes(a,d,tree->t_edges[tree->num_curr_branch_available],tree);
tree->num_curr_branch_available++;
}
subs=Sub_Trees(s_tree_d,°ree);
if(degree > 2)
{
Clean_Multifurcation(subs,degree,2);
Free(s_tree_d);
s_tree_d = (char *)mCalloc(strlen(subs[0])+strlen(subs[1])+5,sizeof(char));
strcat(s_tree_d,"(");
strcat(s_tree_d,subs[0]);
strcat(s_tree_d,",");
strcat(s_tree_d,subs[1]);
strcat(s_tree_d,")");
For(i,b->n_labels)
{
strcat(s_tree_d,"#");
strcat(s_tree_d,b->labels[i]);
}
For(i,NODE_DEG_MAX) Free(subs[i]);
Free(subs);
subs=Sub_Trees(s_tree_d,°ree);
}
R_rtree(s_tree_d,subs[0],d,tree,n_int,n_ext);
R_rtree(s_tree_d,subs[1],d,tree,n_int,n_ext);
for(i=2;it_nodes[*n_ext];
d->tax = 1;
Read_Node_Name(d,s_tree_d,tree);
Read_Branch_Label(s_tree_d,s_tree_a,tree->t_edges[tree->num_curr_branch_available]);
Read_Branch_Length(s_tree_d,s_tree_a,tree);
For(i,3)
{
if(!a->v[i])
{
a->v[i]=d;
d->l[0]=tree->t_edges[tree->num_curr_branch_available]->l;
a->l[i]=tree->t_edges[tree->num_curr_branch_available]->l;
break;
}
}
d->v[0]=a;
if(a != tree->n_root)
{
Connect_One_Edge_To_Two_Nodes(a,d,tree->t_edges[tree->num_curr_branch_available],tree);
tree->num_curr_branch_available++;
}
d->num=*n_ext;
(*n_ext)+=1;
}
Free(s_tree_d);
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void Read_Branch_Label(char *s_d, char *s_a, t_edge *b)
{
char *sub_tp;
char *p;
int i,posp,posl;
sub_tp = (char *)mCalloc(3+(int)strlen(s_d)+1,sizeof(char));
/* sub_tp = (char *)mCalloc(T_MAX_LINE,sizeof(char)); */
sub_tp[0] = '(';
sub_tp[1] = '\0';
strcat(sub_tp,s_d);
strcat(sub_tp,"#");
p = strstr(s_a,sub_tp);
if(!p)
{
sub_tp[0] = ',';
sub_tp[1] = '\0';
strcat(sub_tp,s_d);
strcat(sub_tp,"#");
p = strstr(s_a,sub_tp);
}
i = 0;
b->n_labels = 0;
if(p)
{
if(!(b->n_labels%BLOCK_LABELS)) Make_New_Edge_Label(b);
b->n_labels++;
posp = strlen(s_d);
while(p[posp] != '#') posp++;
posp++;
posl = 0;
do
{
b->labels[b->n_labels-1][posl] = p[posp];
posl++;
posp++;
if(p[posp] == '#')
{
b->labels[b->n_labels-1][posl] = '\0';
b->n_labels++;
if(!(b->n_labels%BLOCK_LABELS)) Make_New_Edge_Label(b);
posp++;
posl=0;
}
}
while((p[posp] != ':') &&
(p[posp] != ',') &&
(p[posp] != '('));
b->labels[b->n_labels-1][posl] = '\0';
}
if(p)
{
/* if(b->n_labels == 1) */
/* PhyML_Printf("\n. Read label '%s' on t_edge %3d.",b->labels[0],b->num); */
/* else */
/* { */
/* PhyML_Printf("\n. Read labels "); */
/* For(i,b->n_labels) PhyML_Printf("'%s' ",b->labels[i]); */
/* PhyML_Printf("on t_edge %3d.",b->num); */
/* } */
if(!strcmp(b->labels[0],"NULL"))
{
b->does_exist = NO;
}
}
/* else */
/* { */
/* PhyML_Printf("\n. No label found on %s",s_d); */
/* } */
Free(sub_tp);
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void Read_Branch_Length(char *s_d, char *s_a, t_tree *tree)
{
char *sub_tp;
char *p;
t_edge *b;
int i;
b = tree->t_edges[tree->num_curr_branch_available];
/* sub_tp = (char *)mCalloc(T_MAX_LINE,sizeof(char)); */
sub_tp = (char *)mCalloc(10+strlen(s_d)+1,sizeof(char));
For(i,b->n_labels)
{
strcat(s_d,"#");
strcat(s_d,b->labels[i]);
}
sub_tp[0] = '(';
sub_tp[1] = '\0';
strcat(sub_tp,s_d);
strcat(sub_tp,":");
p = strstr(s_a,sub_tp);
if(!p)
{
sub_tp[0] = ',';
sub_tp[1] = '\0';
strcat(sub_tp,s_d);
strcat(sub_tp,":");
p = strstr(s_a,sub_tp);
}
if(p)
{
b->l = atof((char *)p+(int)strlen(sub_tp));
tree->has_branch_lengths = YES;
b->does_exist = YES;
}
else
{
b->l = -1.;
}
Free(sub_tp);
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void Read_Node_Name(t_node *d, char *s_tree_d, t_tree *tree)
{
int i;
if(!tree->t_edges[tree->num_curr_branch_available]->n_labels)
{
d->name = (char *)mCalloc(strlen(s_tree_d)+1,sizeof(char ));
strcpy(d->name,s_tree_d);
}
else
{
i = 0;
do
{
d->name = (char *)realloc(d->name,(i+1)*sizeof(char ));
d->name[i] = s_tree_d[i];
i++;
}
while(s_tree_d[i] != '#');
d->name[i] = '\0';
}
d->ori_name = d->name;
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void Unroot_Tree(char **subtrees)
{
char **tmp_sub;
int degree,i,j;
PhyML_Printf("\n. Removing the root...\n");
tmp_sub = Sub_Trees(subtrees[0],°ree);
if(degree >= 2)
{
strcpy(subtrees[2],subtrees[1]);
Clean_Multifurcation(tmp_sub,degree,2);
For(j,2) strcpy(subtrees[j],tmp_sub[j]);
}
else
{
tmp_sub = Sub_Trees(subtrees[1],°ree);
strcpy(subtrees[2],subtrees[0]);
Clean_Multifurcation(tmp_sub,degree,2);
For(j,2) strcpy(subtrees[j],tmp_sub[j]);
}
For(i,degree) Free(tmp_sub[i]);
Free(tmp_sub);
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void Clean_Multifurcation(char **subtrees, int current_deg, int end_deg)
{
if(current_deg <= end_deg) return;
else
{
char *s_tmp;
int i;
/* s_tmp = (char *)mCalloc(T_MAX_LINE,sizeof(char)); */
s_tmp = (char *)mCalloc(10+
(int)strlen(subtrees[0])+1+
(int)strlen(subtrees[1])+1,
sizeof(char));
strcat(s_tmp,"(\0");
strcat(s_tmp,subtrees[0]);
strcat(s_tmp,",\0");
strcat(s_tmp,subtrees[1]);
strcat(s_tmp,")#NULL\0"); /* Add the label 'NULL' to identify a non-existing edge */
Free(subtrees[0]);
subtrees[0] = s_tmp;
for(i=1;in_otu) PhyML_Fprintf(fp,"\t%3d\t%s,\n",i+1,tree->t_nodes[i]->name);
PhyML_Fprintf(fp,"\tUTREE PAUP_1=\n");
PhyML_Fprintf(fp,"%s\n",s_tree);
PhyML_Fprintf(fp,"ENDBLOCK;");
}
Free(s_tree);
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
char *Write_Tree(t_tree *tree, int custom)
{
char *s;
int i,available;
int init_len,last_len;
init_len = 3*(int)T_MAX_NAME;
#ifndef MPI
s=(char *)mCalloc(init_len,sizeof(char));
available = init_len;
#elif defined MPI
s=(char *)mCalloc(T_MAX_LINE,sizeof(char));
#endif
s[0]='(';
last_len = 1;
if(custom == NO)
{
if(!tree->n_root)
{
i = 0;
while((!tree->t_nodes[tree->n_otu+i]->v[0]) ||
(!tree->t_nodes[tree->n_otu+i]->v[1]) ||
(!tree->t_nodes[tree->n_otu+i]->v[2])) i++;
R_wtree(tree->t_nodes[tree->n_otu+i],tree->t_nodes[tree->n_otu+i]->v[0],&available,&s,tree);
R_wtree(tree->t_nodes[tree->n_otu+i],tree->t_nodes[tree->n_otu+i]->v[1],&available,&s,tree);
R_wtree(tree->t_nodes[tree->n_otu+i],tree->t_nodes[tree->n_otu+i]->v[2],&available,&s,tree);
}
else
{
R_wtree(tree->n_root,tree->n_root->v[0],&available,&s,tree);
R_wtree(tree->n_root,tree->n_root->v[1],&available,&s,tree);
}
}
else
{
PhyML_Printf("\n. Err in file %s at line %d\n",__FILE__,__LINE__);
Exit("\n");
}
s[(int)strlen(s)-1]=')';
s[(int)strlen(s)]=';';
return s;
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void R_wtree(t_node *pere, t_node *fils, int *available, char **s_tree, t_tree *tree)
{
int i,p;
char *format;
int last_len;
format = (char *)mCalloc(100,sizeof(char));
sprintf(format,"%%.%df",tree->bl_ndigits);
p = -1;
if(fils->tax)
{
/* printf("\n- Writing on %p",*s_tree); */
/* ori_len = *pos; */
last_len = (int)strlen(*s_tree);
if(OUTPUT_TREE_FORMAT == NEWICK)
{
if(tree->write_tax_names == YES)
{
if(tree->io && tree->io->long_tax_names)
{
strcat(*s_tree,tree->io->long_tax_names[fils->num]);
}
else
{
strcat(*s_tree,fils->name);
}
}
else if(tree->write_tax_names == NO)
{
sprintf(*s_tree+(int)strlen(*s_tree),"%d",fils->num);
}
}
else if(OUTPUT_TREE_FORMAT == NEXUS)
{
sprintf(*s_tree+(int)strlen(*s_tree),"%d",fils->num+1);
}
else
{
PhyML_Printf("\n. Unknown tree format.");
PhyML_Printf("\n. Err in file %s at line %d\n",__FILE__,__LINE__);
PhyML_Printf("\n. s=%s\n",*s_tree);
}
if((fils->b) && (fils->b[0]) && (fils->b[0]->l > -1.))
{
(*s_tree)[(int)strlen(*s_tree)] = ':';
#ifndef PHYTIME
if(!tree->n_root)
{
sprintf(*s_tree+(int)strlen(*s_tree),format,fils->b[0]->l);
}
else
{
if(pere == tree->n_root)
{
phydbl root_pos = (fils == tree->n_root->v[0])?(tree->n_root_pos):(1.-tree->n_root_pos);
sprintf(*s_tree+(int)strlen(*s_tree),format,tree->e_root->l * root_pos);
}
else
{
sprintf(*s_tree+(int)strlen(*s_tree),format,fils->b[0]->l);
}
}
#else
if(!tree->n_root)
{
sprintf(*s_tree+(int)strlen(*s_tree),format,fils->b[0]->l);
}
else
{
sprintf(*s_tree+(int)strlen(*s_tree),format,tree->rates->cur_l[fils->num]);
}
#endif
}
/* strcat(*s_tree,","); */
(*s_tree)[(int)strlen(*s_tree)] = ',';
#ifndef MPI
(*available) -= ((int)strlen(*s_tree) - last_len);
/* printf("\n0 Available = %d [%d %d]",(*available),(int)strlen(*s_tree),last_len); */
/* printf("\n0 %s [%d,%d]",*s_tree,(int)(int)strlen(*s_tree),*available); */
if(*available < 0)
{
PhyML_Printf("\n. s=%s\n",*s_tree);
PhyML_Printf("\n. len=%d\n",(int)strlen(*s_tree));
PhyML_Printf("\n. The sequence names in your input file might be too long.");
PhyML_Printf("\n. Err in file %s at line %d\n",__FILE__,__LINE__);
Warn_And_Exit("");
}
if(*available < (int)T_MAX_NAME)
{
(*s_tree) = (char *)mRealloc(*s_tree,(int)strlen(*s_tree)+3*(int)T_MAX_NAME,sizeof(char));
For(i,3*(int)T_MAX_NAME) (*s_tree)[(int)strlen(*s_tree)+i] = '\0';
(*available) = 3*(int)T_MAX_NAME;
/* printf("\n. ++ 0 Available = %d",(*available)); */
}
#endif
}
else
{
(*s_tree)[(int)strlen(*s_tree)]='(';
#ifndef MPI
(*available) -= 1;
/* printf("\n1 Available = %d [%d %d]",(*available),(int)strlen(*s_tree),last_len); */
/* printf("\n1 %s [%d,%d]",*s_tree,(int)(int)strlen(*s_tree),*available); */
if(*available < (int)T_MAX_NAME)
{
(*s_tree) = (char *)mRealloc(*s_tree,(int)strlen(*s_tree)+3*(int)T_MAX_NAME,sizeof(char));
For(i,3*(int)T_MAX_NAME) (*s_tree)[(int)strlen(*s_tree)+i] = '\0';
(*available) = 3*(int)T_MAX_NAME;
/* printf("\n. ++ 1 Available = %d",(*available)); */
}
#endif
/* (*available)--; */
/* if(*available < (int)T_MAX_NAME/2) */
/* { */
/* (*s_tree) = (char *)mRealloc(*s_tree,*pos+(int)T_MAX_NAME,sizeof(char)); */
/* (*available) = (int)T_MAX_NAME; */
/* } */
if(tree->n_root)
{
For(i,3)
{
if((fils->v[i] != pere) && (fils->b[i] != tree->e_root))
R_wtree(fils,fils->v[i],available,s_tree,tree);
else p=i;
}
}
else
{
For(i,3)
{
if(fils->v[i] != pere)
R_wtree(fils,fils->v[i],available,s_tree,tree);
else p=i;
}
}
if(p < 0)
{
PhyML_Printf("\n. fils=%p root=%p root->v[0]=%p root->v[1]=%p",fils,tree->n_root,tree->n_root->v[0],tree->n_root->v[1]);
PhyML_Printf("\n. tree->e_root=%p fils->b[0]=%p fils->b[1]=%p fils->b[2]=%p",tree->e_root,fils->b[0],fils->b[1],fils->b[2]);
PhyML_Printf("\n. Err in file %s at line %d\n",__FILE__,__LINE__);
Warn_And_Exit("");
}
last_len = (int)strlen(*s_tree);
(*s_tree)[last_len-1] = ')';
if((fils->b) && (fils->b[p]->l > -1.))
{
if(tree->print_boot_val)
{
sprintf(*s_tree+(int)strlen(*s_tree),"%d",fils->b[p]->bip_score);
}
else if(tree->print_alrt_val)
{
sprintf(*s_tree+(int)strlen(*s_tree),"%f",fils->b[p]->ratio_test);
}
fflush(NULL);
(*s_tree)[(int)strlen(*s_tree)] = ':';
#ifndef PHYTIME
if(!tree->n_root)
{
sprintf(*s_tree+(int)strlen(*s_tree),format,fils->b[p]->l);
}
else
{
if(pere == tree->n_root)
{
phydbl root_pos = (fils == tree->n_root->v[0])?(tree->n_root_pos):(1.-tree->n_root_pos);
sprintf(*s_tree+(int)strlen(*s_tree),format,tree->e_root->l * root_pos);
}
else
{
sprintf(*s_tree+(int)strlen(*s_tree),format,fils->b[p]->l);
}
}
#else
if(!tree->n_root)
{
sprintf(*s_tree+(int)strlen(*s_tree),format,fils->b[p]->l);
}
else
{
sprintf(*s_tree+(int)strlen(*s_tree),format,tree->rates->cur_l[fils->num]);
}
#endif
}
/* strcat(*s_tree,","); */
(*s_tree)[(int)strlen(*s_tree)] = ',';
#ifndef MPI
(*available) -= ((int)strlen(*s_tree) - last_len);
/* printf("\n2 Available = %d [%d %d]",(*available),(int)strlen(*s_tree),last_len); */
/* printf("\n2 %s [%d,%d]",*s_tree,(int)(int)strlen(*s_tree),*available); */
if(*available < 0)
{
PhyML_Printf("\n. available = %d",*available);
PhyML_Printf("\n. Err in file %s at line %d\n",__FILE__,__LINE__);
Warn_And_Exit("");
}
if(*available < (int)T_MAX_NAME)
{
(*s_tree) = (char *)mRealloc(*s_tree,(int)strlen(*s_tree)+3*(int)T_MAX_NAME,sizeof(char));
For(i,3*(int)T_MAX_NAME) (*s_tree)[(int)strlen(*s_tree)+i] = '\0';
(*available) = 3*(int)T_MAX_NAME;
/* printf("\n. ++ 2 Available = %d",(*available)); */
}
#endif
/* if(*available < (int)T_MAX_NAME/2) */
/* { */
/* (*s_tree) = (char *)mRealloc(*s_tree,*pos+(int)T_MAX_NAME,sizeof(char)); */
/* (*available) = (int)T_MAX_NAME; */
/* } */
}
Free(format);
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void R_wtree_Custom(t_node *pere, t_node *fils, int *available, char **s_tree, int *pos, t_tree *tree)
{
int i,p,ori_len;
char *format;
format = (char *)mCalloc(100,sizeof(char));
sprintf(format,"%%.%df",tree->bl_ndigits);
/* strcpy(format,"%f"); */
p = -1;
if(fils->tax)
{
/* printf("\n- Writing on %p",*s_tree); */
ori_len = *pos;
if(OUTPUT_TREE_FORMAT == NEWICK)
{
if(tree->write_tax_names == YES)
{
if(tree->io && tree->io->long_tax_names)
{
strcat(*s_tree,tree->io->long_tax_names[fils->num]);
(*pos) += (int)strlen(tree->io->long_tax_names[fils->num]);
}
else
{
strcat(*s_tree,fils->name);
(*pos) += (int)strlen(fils->name);
}
}
else if(tree->write_tax_names == NO)
{
(*pos) += sprintf(*s_tree+*pos,"%d",fils->num);
}
}
else if(OUTPUT_TREE_FORMAT == NEXUS)
{
(*pos) += sprintf(*s_tree+*pos,"%d",fils->num+1);
}
else
{
PhyML_Printf("\n. Unknown tree format.");
PhyML_Printf("\n. Err in file %s at line %d\n",__FILE__,__LINE__);
PhyML_Printf("\n. s=%s\n",*s_tree);
}
if((fils->b) && (fils->b[0]) && (fils->b[0]->l > -1.))
{
/* if(tree->print_labels) */
/* { */
/* if(fils->b[0]->n_labels < 10) */
/* For(i,fils->b[0]->n_labels) */
/* { */
/* (*pos) += sprintf(*s_tree+*pos,"#%s",fils->b[0]->labels[i]); */
/* } */
/* else */
/* { */
/* (*pos) += sprintf(*s_tree+*pos,"#%d_labels",fils->b[0]->n_labels); */
/* } */
/* } */
strcat(*s_tree,":");
(*pos)++;
#ifndef PHYTIME
if(!tree->n_root)
{
(*pos) += sprintf(*s_tree+*pos,format,fils->b[0]->l);
}
else
{
if(pere == tree->n_root)
{
phydbl root_pos = (fils == tree->n_root->v[0])?(tree->n_root_pos):(1.-tree->n_root_pos);
(*pos) += sprintf(*s_tree+*pos,format,tree->e_root->l * root_pos);
}
else
{
(*pos) += sprintf(*s_tree+*pos,format,fils->b[0]->l);
}
}
#else
if(!tree->n_root)
{
(*pos) += sprintf(*s_tree+*pos,format,fils->b[0]->l);
}
else
{
(*pos) += sprintf(*s_tree+*pos,format,tree->rates->cur_l[fils->num]);
}
#endif
/* !!!!!!!!!!!!!!!!!!!!1 */
if(tree->print_labels)
{
if(fils->b[0]->n_labels < 10)
For(i,fils->b[0]->n_labels)
{
(*pos) += sprintf(*s_tree+*pos,"::%s",fils->b[0]->labels[i]);
}
else
{
(*pos) += sprintf(*s_tree+*pos,"::%d_labels",fils->b[0]->n_labels);
}
}
}
strcat(*s_tree,",");
(*pos)++;
(*available) = (*available) - (*pos - ori_len);
if(*available < 0)
{
PhyML_Printf("\n. s=%s\n",*s_tree);
PhyML_Printf("\n. len=%d\n",strlen(*s_tree));
PhyML_Printf("\n. The sequence names in your input file might be too long.");
PhyML_Printf("\n. Err in file %s at line %d\n",__FILE__,__LINE__);
Warn_And_Exit("");
}
if(*available < (int)T_MAX_NAME/2)
{
(*s_tree) = (char *)mRealloc(*s_tree,*pos+(int)T_MAX_NAME,sizeof(char));
(*available) = (int)T_MAX_NAME;
}
/* printf(" %s [%d,%d]",*s_tree,(int)strlen(*s_tree),*available); */
}
else
{
(*s_tree)[(*pos)]='(';
(*s_tree)[(*pos)+1]='\0';
(*pos)++;
(*available)--;
if(*available < (int)T_MAX_NAME/2)
{
(*s_tree) = (char *)mRealloc(*s_tree,*pos+(int)T_MAX_NAME,sizeof(char));
(*available) = (int)T_MAX_NAME;
}
if(tree->n_root)
{
For(i,3)
{
if((fils->v[i] != pere) && (fils->b[i] != tree->e_root))
R_wtree_Custom(fils,fils->v[i],available,s_tree,pos,tree);
else p=i;
}
}
else
{
For(i,3)
{
if(fils->v[i] != pere)
R_wtree_Custom(fils,fils->v[i],available,s_tree,pos,tree);
else p=i;
}
}
ori_len = *pos;
if(p < 0)
{
PhyML_Printf("\n. fils=%p root=%p root->v[0]=%p root->v[1]=%p",fils,tree->n_root,tree->n_root->v[0],tree->n_root->v[1]);
PhyML_Printf("\n. tree->e_root=%p fils->b[0]=%p fils->b[1]=%p fils->b[2]=%p",tree->e_root,fils->b[0],fils->b[1],fils->b[2]);
PhyML_Printf("\n. Err in file %s at line %d\n",__FILE__,__LINE__);
Warn_And_Exit("");
}
/* printf("\n+ Writing on %p",*s_tree); */
(*s_tree)[(*pos)-1] = ')';
(*s_tree)[(*pos)] = '\0';
if((fils->b) && (fils->b[p]->l > -1.))
{
if(tree->print_boot_val)
{
(*pos) += sprintf(*s_tree+*pos,"%d",fils->b[p]->bip_score);
}
else if(tree->print_alrt_val)
{
(*pos) += sprintf(*s_tree+*pos,"%f",fils->b[p]->ratio_test);
}
fflush(NULL);
/* if((tree->print_labels) && (fils->b[p]->labels != NULL)) */
/* { */
/* if(fils->b[p]->n_labels < 10) */
/* For(i,fils->b[p]->n_labels) */
/* { */
/* (*pos) += sprintf(*s_tree+*pos,"#%s",fils->b[p]->labels[i]); */
/* } */
/* else */
/* { */
/* (*pos) += sprintf(*s_tree+*pos,"#%d_labels",fils->b[p]->n_labels); */
/* } */
/* } */
strcat(*s_tree,":");
(*pos)++;
#ifndef PHYTIME
if(!tree->n_root)
{
(*pos) += sprintf(*s_tree+*pos,format,fils->b[p]->l);
}
else
{
if(pere == tree->n_root)
{
phydbl root_pos = (fils == tree->n_root->v[0])?(tree->n_root_pos):(1.-tree->n_root_pos);
(*pos) += sprintf(*s_tree+*pos,format,tree->e_root->l * root_pos);
}
else
{
(*pos) += sprintf(*s_tree+*pos,format,fils->b[p]->l);
}
}
#else
if(!tree->n_root)
{
(*pos) += sprintf(*s_tree+*pos,format,fils->b[p]->l);
}
else
{
(*pos) += sprintf(*s_tree+*pos,format,tree->rates->cur_l[fils->num]);
}
#endif
/* !!!!!!!!!!!!!!!!!!!!!!!!!!!!!1 */
if((tree->print_labels) && (fils->b[p]->labels != NULL))
{
if(fils->b[p]->n_labels < 10)
For(i,fils->b[p]->n_labels)
{
(*pos) += sprintf(*s_tree+*pos,"::%s",fils->b[p]->labels[i]);
}
else
{
(*pos) += sprintf(*s_tree+*pos,"::%d_labels",fils->b[p]->n_labels);
}
}
}
strcat(*s_tree,",");
(*pos)++;
(*available) = (*available) - (*pos - ori_len);
if(*available < 0)
{
PhyML_Printf("\n. Err in file %s at line %d\n",__FILE__,__LINE__);
Warn_And_Exit("");
}
if(*available < (int)T_MAX_NAME/2)
{
(*s_tree) = (char *)mRealloc(*s_tree,*pos+(int)T_MAX_NAME,sizeof(char));
(*available) = (int)T_MAX_NAME;
}
/* printf(" %s [%d,%d]",*s_tree,(int)strlen(*s_tree),*available); */
}
Free(format);
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void Init_Tree(t_tree *tree, int n_otu)
{
tree->n_otu = n_otu;
tree->mat = NULL;
tree->n_root = NULL;
tree->e_root = NULL;
tree->ps_tree = NULL;
tree->short_l = NULL;
tree->mutmap = NULL;
tree->nextree = NULL;
tree->prevtree = NULL;
tree->tree_num = 0;
tree->depth_curr_path = 0;
tree->has_bip = NO;
tree->n_moves = 0;
tree->n_improvements = 0;
tree->bl_from_node_stamps = 0;
tree->lock_topo = 0;
tree->ps_page_number = 0;
tree->init_lnL = UNLIKELY;
tree->best_lnL = UNLIKELY;
tree->old_lnL = UNLIKELY;
tree->c_lnL = UNLIKELY;
tree->sum_min_sum_scale = .0;
tree->n_swap = 0;
tree->best_pars = 1E+5;
tree->n_pattern = -1;
tree->n_root_pos = -1.;
tree->print_labels = 1;
tree->print_boot_val = 0;
tree->print_alrt_val = 0;
tree->num_curr_branch_available = 0;
tree->tip_order_score = .0;
tree->write_tax_names = YES;
tree->update_alias_subpatt = NO;
tree->bl_ndigits = 8;
tree->n_short_l = 100;
tree->norm_scale = 0.0;
tree->br_len_recorded = NO;
tree->max_spr_depth = 0;
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void Make_New_Edge_Label(t_edge *b)
{
int i;
b->labels = (char **)realloc(b->labels,(b->n_labels+BLOCK_LABELS)*sizeof(char *));
if(!b->labels)
{
PhyML_Printf("\n. Err in file %s at line %d\n",__FILE__,__LINE__);
Warn_And_Exit("");
}
else
{
for(i=b->n_labels;in_labels+BLOCK_LABELS;i++) b->labels[i] = (char *)mCalloc(T_MAX_LABEL,sizeof(char));
}
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
t_edge *Make_Edge_Light(t_node *a, t_node *d, int num)
{
t_edge *b;
b = (t_edge *)mCalloc(1,sizeof(t_edge));
Init_Edge_Light(b,num);
if(a && b)
{
b->left = a; b->rght = d;
if(a->tax) {b->rght = a; b->left = d;} /* root */
/* a tip is necessary on the right side of the t_edge */
(b->left == a)?
(Make_Edge_Dirs(b,a,d,NULL)):
(Make_Edge_Dirs(b,d,a,NULL));
b->l = a->l[b->l_r];
if(a->tax) b->l = a->l[b->r_l];
b->l_old = b->l;
}
else
{
b->left = NULL;
b->rght = NULL;
}
return b;
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void Init_Edge_Light(t_edge *b, int num)
{
b->num = num;
b->bip_score = 0;
b->dist_btw_edges = .0;
b->topo_dist_btw_edges = 0;
b->has_zero_br_len = NO;
b->n_jumps = 0;
b->gamma_prior_mean = 1.E-0;
b->gamma_prior_var = 1.E-1;
b->does_exist = YES;
b->l = -1.;
b->bin_cod_num = -1.;
b->p_lk_left = NULL;
b->p_lk_rght = NULL;
b->p_lk_loc_left = NULL;
b->p_lk_loc_rght = NULL;
b->Pij_rr = NULL;
b->labels = NULL;
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void Init_Node_Light(t_node *n, int num)
{
n->num = num;
n->tax = -1;
n->dist_to_root = .0;
n->common = 1;
n->ext_node = NULL;
n->name = NULL;
n->ori_name = NULL;
n->y_rank = 0.;
n->y_rank_ori = 0.;
n->y_rank_max = 0.;
n->y_rank_min = 0.;
n->anc = NULL;
n->rank = 0;
n->match_node = NULL;
n->id_rank = 0;
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void Make_Edge_Dirs(t_edge *b, t_node *a, t_node *d, t_tree *tree)
{
int i;
t_edge *e_root;
e_root = (tree)?(tree->e_root):(NULL);
if(a == b->rght)
{
PhyML_Printf("\n. a->num = %3d ; d->num = %3d",a->num,d->num);
PhyML_Printf("\n. Err in file %s at line %d\n",__FILE__,__LINE__);
Warn_And_Exit("");
}
if(d == b->left)
{
PhyML_Printf("\n. a->num = %3d ; d->num = %3d",a->num,d->num);
PhyML_Printf("\n. Err in file %s at line %d\n",__FILE__,__LINE__);
Warn_And_Exit("");
}
b->l_r = b->r_l = -1;
For(i,3)
{
/* if((a->v[i]) && ((a->v[i] == d) || (e_root && a->b[i] == e_root))) */
if((a->v[i]) && ((a->v[i] == d)))
{
b->l_r = i; /* we consider here that 'a' is on the left handside of 'b'*/
a->b[i] = b;
}
/* if((d->v[i]) && ((d->v[i] == a) || (e_root && d->b[i] == e_root))) */
if((d->v[i]) && ((d->v[i] == a)))
{
b->r_l = i; /* we consider here that 'd' is on the right handside of 'b'*/
d->b[i] = b;
}
}
if(a->tax) {b->r_l = 0; For(i,3) if(d->v[i]==a) {b->l_r = i; break;}}
b->l_v1 = b->l_v2 = b->r_v1 = b->r_v2 = -1;
For(i,3)
{
if(b->left->v[i] != b->rght)
{
if(b->l_v1 < 0) b->l_v1 = i;
else b->l_v2 = i;
}
if(b->rght->v[i] != b->left)
{
if(b->r_v1 < 0) b->r_v1 = i;
else b->r_v2 = i;
}
}
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void Make_Edge_Pars(t_edge *b, t_tree *tree)
{
/* int site; */
b->pars_l = (int *)mCalloc(tree->data->crunch_len,sizeof(int));
b->pars_r = (int *)mCalloc(tree->data->crunch_len,sizeof(int));
b->ui_l = (unsigned int *)mCalloc(tree->data->crunch_len,sizeof(unsigned int));
b->ui_r = (unsigned int *)mCalloc(tree->data->crunch_len,sizeof(unsigned int));
b->p_pars_l = (int *)mCalloc(tree->data->crunch_len*tree->mod->ns,sizeof(int ));
b->p_pars_r = (int *)mCalloc(tree->data->crunch_len*tree->mod->ns,sizeof(int ));
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void Make_Edge_Lk(t_edge *b, t_tree *tree)
{
int ns;
ns = -1;
ns = tree->mod->ns;
b->l_old = b->l;
b->div_post_pred_left = (short int *)mCalloc(ns,sizeof(short int));
b->div_post_pred_rght = (short int *)mCalloc(ns,sizeof(short int));
b->Pij_rr = (phydbl *)mCalloc(tree->mod->n_catg*tree->mod->ns*tree->mod->ns,sizeof(phydbl));
b->sum_scale_left_cat = (int *)mCalloc(tree->mod->n_catg,sizeof(int));
b->sum_scale_rght_cat = (int *)mCalloc(tree->mod->n_catg,sizeof(int));
if(!b->left->tax)
b->sum_scale_left = (int *)mCalloc(tree->data->crunch_len*tree->mod->n_catg,sizeof(int));
else
b->sum_scale_left = NULL;
if(!b->rght->tax)
b->sum_scale_rght = (int *)mCalloc(tree->data->crunch_len*tree->mod->n_catg,sizeof(int));
else
b->sum_scale_rght = NULL;
if((!b->left->tax) || (tree->mod->s_opt->greedy))
{
b->p_lk_left = (phydbl *)mCalloc(tree->data->crunch_len*tree->mod->n_catg*tree->mod->ns,sizeof(phydbl));
b->p_lk_tip_l = NULL;
}
else if(b->left->tax)
{
b->p_lk_left = NULL;
b->p_lk_tip_l = (short int *)mCalloc(tree->data->crunch_len*tree->mod->ns,sizeof(short int ));
}
if((!b->rght->tax) || (tree->mod->s_opt->greedy))
{
b->p_lk_rght = (phydbl *)mCalloc(tree->data->crunch_len*tree->mod->n_catg*tree->mod->ns,sizeof(phydbl));
b->p_lk_tip_r = NULL;
}
else if(b->rght->tax)
{
b->p_lk_rght = NULL;
b->p_lk_tip_r = (short int *)mCalloc(tree->data->crunch_len*tree->mod->ns,sizeof(short int));
}
b->patt_id_left = (int *)mCalloc(tree->data->crunch_len,sizeof(int));
b->patt_id_rght = (int *)mCalloc(tree->data->crunch_len,sizeof(int));
b->p_lk_loc_left = (int *)mCalloc(tree->data->crunch_len,sizeof(int));
b->p_lk_loc_rght = (int *)mCalloc(tree->data->crunch_len,sizeof(int));
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void Make_Edge_NNI(t_edge *b)
{
b->nni = Make_NNI();
b->nni->b = b;
b->nni->left = b->left;
b->nni->rght = b->rght;
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
nni *Make_NNI()
{
nni *a_nni;
a_nni = (nni *)mCalloc(1,sizeof(nni ));
Init_NNI(a_nni);
return a_nni;
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void Init_NNI(nni *a_nni)
{
a_nni->left = NULL;
a_nni->rght = NULL;
a_nni->b = NULL;
a_nni->init_l = -1.;
a_nni->init_lk = .0;
a_nni->score = +1.0;
a_nni->best_l = -1.;
a_nni->swap_node_v1 = NULL;
a_nni->swap_node_v2 = NULL;
a_nni->swap_node_v3 = NULL;
a_nni->swap_node_v4 = NULL;
a_nni->lk0 = UNLIKELY;
a_nni->lk1 = UNLIKELY;
a_nni->lk2 = UNLIKELY;
a_nni->l0 = -1.0;
a_nni->l1 = -1.0;
a_nni->l2 = -1.0;
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
t_node *Make_Node_Light(int num)
{
t_node *n;
n = (t_node *)mCalloc(1,sizeof(t_node));
n->v = (t_node **)mCalloc(3,sizeof(t_node *));
n->l = (phydbl *)mCalloc(3,sizeof(phydbl));
n->b = (t_edge **)mCalloc(3,sizeof(t_edge *));
n->score = (phydbl *)mCalloc(3,sizeof(phydbl));
n->s_ingrp = (int *)mCalloc(3,sizeof(int));
n->s_outgrp = (int *)mCalloc(3,sizeof(int));
Init_Node_Light(n,num);
return n;
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void Make_Node_Lk(t_node *n)
{
/* n->n_ex_nodes = (int *)mCalloc(2,sizeof(int)); */
return;
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void Detect_Align_File_Format(option *io)
{
int c;
fpos_t curr_pos;
fgetpos(io->fp_in_align,&curr_pos);
errno = 0;
while((c=fgetc(io->fp_in_align)) != EOF)
{
if(errno) io->data_file_format = PHYLIP;
else if(c == '#')
{
char s[10],t[6]="NEXUS";
if(!fgets(s,6,io->fp_in_align))
{
PhyML_Printf("\n. Err in file %s at line %d\n",__FILE__,__LINE__);
Warn_And_Exit("");
}
if(!strcmp(t,s))
{
fsetpos(io->fp_in_align,&curr_pos);
io->data_file_format = NEXUS;
return;
}
}
}
fsetpos(io->fp_in_align,&curr_pos);
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void Detect_Tree_File_Format(option *io)
{
int c;
fpos_t curr_pos;
fgetpos(io->fp_in_tree,&curr_pos);
errno = 0;
while((c=fgetc(io->fp_in_tree)) != EOF)
{
if(errno)
{
io->tree_file_format = PHYLIP;
PhyML_Printf("\n. Detected PHYLIP tree file format.");
}
else if(c == '#')
{
char s[10],t[6]="NEXUS";
if(!fgets(s,6,io->fp_in_tree))
{
PhyML_Printf("\n. Err in file %s at line %d\n",__FILE__,__LINE__);
Warn_And_Exit("");
}
if(!strcmp(t,s))
{
fsetpos(io->fp_in_tree,&curr_pos);
io->tree_file_format = NEXUS;
PhyML_Printf("\n. Detected NEXUS tree file format.");
return;
}
}
}
fsetpos(io->fp_in_tree,&curr_pos);
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
align **Get_Seq(option *io)
{
io->data = NULL;
Detect_Align_File_Format(io);
switch(io->data_file_format)
{
case PHYLIP:
{
io->data = Get_Seq_Phylip(io);
break;
}
case NEXUS:
{
io->nex_com_list = Make_Nexus_Com();
Init_Nexus_Format(io->nex_com_list);
Get_Nexus_Data(io->fp_in_align,io);
Free_Nexus(io);
break;
}
default:
{
PhyML_Printf("\n. Err in file %s at line %d\n",__FILE__,__LINE__);
Warn_And_Exit("");
break;
}
}
if(!io->data)
{
PhyML_Printf("\n. Err in file %s at line %d\n",__FILE__,__LINE__);
Warn_And_Exit("");
}
else
{
int i,j;
char **buff;
int *remove;
int n_unkn,n_removed,pos;
buff = (char **)mCalloc(io->n_otu,sizeof(char *));
For(i,io->n_otu) buff[i] = (char *)mCalloc(io->data[0]->len,sizeof(char));
remove = (int *)mCalloc(io->data[0]->len,sizeof(int));
n_removed = 0;
For(i,io->data[0]->len)
{
For(j,io->n_otu)
{
if((io->data[j]->state[i] == '?') || (io->data[j]->state[i] == '-')) io->data[j]->state[i] = 'X';
if((io->datatype == NT) && (io->data[j]->state[i] == 'N')) io->data[j]->state[i] = 'X';
if(io->data[j]->state[i] == 'U') io->data[j]->state[i] = 'T';
}
n_unkn = 0;
For(j,io->n_otu) if(io->data[j]->state[i] == 'X') n_unkn++;
if(n_unkn == io->n_otu)
{
remove[i] = 1;
n_removed++;
}
For(j,io->n_otu) buff[j][i] = io->data[j]->state[i];
}
pos = 0;
For(i,io->data[0]->len)
{
/* if(!remove[i]) */
/* { */
For(j,io->n_otu) io->data[j]->state[pos] = buff[j][i];
pos++;
/* } */
}
For(i,io->n_otu) io->data[i]->len = pos;
For(i,io->n_otu) Free(buff[i]);
Free(buff);
Free(remove);
}
return io->data;
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
/* align **Get_Seq_Nexus(option *io) */
/* { */
/* char *s,*ori_s; */
/* char *token; */
/* int in_comment; */
/* nexcom *curr_com; */
/* nexparm *curr_parm; */
/* int nxt_token_t,cur_token_t; */
/* s = (char *)mCalloc(T_MAX_LINE,sizeof(char)); */
/* token = (char *)mCalloc(T_MAX_TOKEN,sizeof(char)); */
/* ori_s = s; */
/* in_comment = NO; */
/* curr_com = NULL; */
/* curr_parm = NULL; */
/* nxt_token_t = NEXUS_COM; */
/* cur_token_t = -1; */
/* while(fgets(s,T_MAX_LINE,io->fp_in_align)) */
/* { */
/* do */
/* { */
/* Get_Token(&s,token); */
/* /\* PhyML_Printf("\n. Token: '%s' next_token=%d cur_token=%d",token,nxt_token_t,cur_token_t); *\/ */
/* if(token[0] == '\0') break; */
/* if(token[0] == ';') */
/* { */
/* curr_com = NULL; */
/* curr_parm = NULL; */
/* nxt_token_t = NEXUS_COM; */
/* cur_token_t = -1; */
/* break; /\* End of command *\/ */
/* } */
/* if(nxt_token_t == NEXUS_EQUAL) */
/* { */
/* cur_token_t = NEXUS_VALUE; */
/* nxt_token_t = NEXUS_PARM; */
/* continue; */
/* } */
/* if((nxt_token_t == NEXUS_COM) && (cur_token_t != NEXUS_VALUE)) */
/* { */
/* Find_Nexus_Com(token,&curr_com,&curr_parm,io->nex_com_list); */
/* if(curr_com) */
/* { */
/* nxt_token_t = curr_com->nxt_token_t; */
/* cur_token_t = curr_com->cur_token_t; */
/* } */
/* if(cur_token_t != NEXUS_VALUE) continue; */
/* } */
/* if((nxt_token_t == NEXUS_PARM) && (cur_token_t != NEXUS_VALUE)) */
/* { */
/* Find_Nexus_Parm(token,&curr_parm,curr_com); */
/* if(curr_parm) */
/* { */
/* nxt_token_t = curr_parm->nxt_token_t; */
/* cur_token_t = curr_parm->cur_token_t; */
/* } */
/* if(cur_token_t != NEXUS_VALUE) continue; */
/* } */
/* if(cur_token_t == NEXUS_VALUE) */
/* { */
/* if((curr_parm->fp)(token,curr_parm,io)) /\* Read in parameter value *\/ */
/* { */
/* nxt_token_t = NEXUS_PARM; */
/* cur_token_t = -1; */
/* } */
/* } */
/* } */
/* while(strlen(token) > 0); */
/* } */
/* Free(ori_s); */
/* Free(token); */
/* return io->data; */
/* } */
/* /\*********************************************************\/ */
void Get_Nexus_Data(FILE *fp, option *io)
{
char *token;
int in_comment;
nexcom *curr_com;
nexparm *curr_parm;
int nxt_token_t,cur_token_t;
token = (char *)mCalloc(T_MAX_TOKEN,sizeof(char));
in_comment = NO;
curr_com = NULL;
curr_parm = NULL;
nxt_token_t = NEXUS_COM;
cur_token_t = -1;
do
{
if(!Get_Token(fp,token)) break;
/* PhyML_Printf("\n+ Token: '%s' next_token=%d cur_token=%d",token,nxt_token_t,cur_token_t); */
if(token[0] == ';')
{
curr_com = NULL;
curr_parm = NULL;
nxt_token_t = NEXUS_COM;
cur_token_t = -1;
}
if(nxt_token_t == NEXUS_EQUAL)
{
cur_token_t = NEXUS_VALUE;
nxt_token_t = NEXUS_PARM;
continue;
}
if((nxt_token_t == NEXUS_COM) && (cur_token_t != NEXUS_VALUE))
{
Find_Nexus_Com(token,&curr_com,&curr_parm,io->nex_com_list);
if(curr_com)
{
nxt_token_t = curr_com->nxt_token_t;
cur_token_t = curr_com->cur_token_t;
}
if(cur_token_t != NEXUS_VALUE) continue;
}
if((nxt_token_t == NEXUS_PARM) && (cur_token_t != NEXUS_VALUE))
{
Find_Nexus_Parm(token,&curr_parm,curr_com);
if(curr_parm)
{
nxt_token_t = curr_parm->nxt_token_t;
cur_token_t = curr_parm->cur_token_t;
}
if(cur_token_t != NEXUS_VALUE) continue;
}
if(cur_token_t == NEXUS_VALUE)
{
if((curr_parm->fp)(token,curr_parm,io)) /* Read in parameter value */
{
nxt_token_t = NEXUS_PARM;
cur_token_t = -1;
}
}
}
while(strlen(token) > 0);
Free(token);
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
int Get_Token(FILE *fp, char *token)
{
char c;
c = ' ';
while(c == ' ' || c == '\t' || c == '\n')
{
c = fgetc(fp);
if(c == EOF) return 0;
}
if(c == '"')
{
do
{
*token = c;
token++;
c = fgetc(fp);
if(c == EOF) return 0;
}
while(c != '"');
*token = c;
c = fgetc(fp);
if(c == EOF) return 0;
*(token+1) = '\0';
return 1;
}
if(c == '[')
{
Skip_Comment(fp);
c = fgetc(fp);
if(c == EOF) return 0;
return 1;
}
if(c == '#') { *token = c; token++; }
else if(c == ';') { *token = c; token++; }
else if(c == ',') { *token = c; token++; }
else if(c == '.') { *token = c; token++; }
else if(c == '=') { *token = c; token++; }
else if(c == '(') { *token = c; token++; }
else if(c == ')') { *token = c; token++; }
else if(c == '{') { *token = c; token++; }
else if(c == '}') { *token = c; token++; }
else if(c == '?') { *token = c; token++; }
else if(c == '-') { *token = c; token++; }
else
{
while(isgraph(c) && c != ';' && c != '-' && c != ',')
{
*(token++) = c;
c = fgetc(fp);
if(c == EOF) return 0;
}
fseek(fp,-1*sizeof(char),SEEK_CUR);
}
*token = '\0';
return 1;
}
/* void Get_Token(char *line, char *token) */
/* { */
/* while(**line == ' ' || **line == '\t') (*line)++; */
/* if(**line == '"') */
/* { */
/* do { *token = **line; (*line)++; token++; } while(**line != '"'); */
/* *token = **line; */
/* (*line)++; */
/* *(token+1) = '\0'; */
/* return; */
/* } */
/* if(**line == '[') */
/* { */
/* int in_comment; */
/* in_comment = 1; */
/* do */
/* { */
/* (*line)++; */
/* if(**line == '[') */
/* { */
/* in_comment++; */
/* } */
/* else if(**line == ']') in_comment--; */
/* } */
/* while(in_comment); */
/* (*line)++; */
/* return; */
/* } */
/* if(**line == '#') {*token = **line; (*line)++; token++; } */
/* else if(**line == ';') {*token = **line; (*line)++; token++; } */
/* else if(**line == ',') {*token = **line; (*line)++; token++; } */
/* else if(**line == '.') {*token = **line; (*line)++; token++; } */
/* else if(**line == '=') {*token = **line; (*line)++; token++; } */
/* else if(**line == '(') {*token = **line; (*line)++; token++; } */
/* else if(**line == ')') {*token = **line; (*line)++; token++; } */
/* else if(**line == '{') {*token = **line; (*line)++; token++; } */
/* else if(**line == '}') {*token = **line; (*line)++; token++; } */
/* else if(**line == '?') {*token = **line; (*line)++; token++; } */
/* else if(**line == '-') {*token = **line; (*line)++; token++; } */
/* else */
/* { */
/* while(isgraph(**line) && **line != ';' && **line != '=' && **line != ',') */
/* { */
/* *(token++) = **line; */
/* (*line)++; */
/* } */
/* } */
/* *token = '\0'; */
/* } */
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
nexcom **Make_Nexus_Com()
{
nexcom **com;
int i;
com = (nexcom **)mCalloc(N_MAX_NEX_COM,sizeof(nexcom *));
For(i,N_MAX_NEX_COM)
{
com[i] = (nexcom *)mCalloc(1,sizeof(nexcom));
com[i]->name = (char *)mCalloc(T_MAX_NEX_COM,sizeof(char));
com[i]->parm = (nexparm **)mCalloc(N_MAX_NEX_PARM,sizeof(nexparm *));
}
return com;
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
nexparm *Make_Nexus_Parm()
{
nexparm *parm;
parm = (nexparm *)mCalloc(1,sizeof(nexparm));
parm->name = (char *)mCalloc(T_MAX_TOKEN,sizeof(char ));
parm->value = (char *)mCalloc(T_MAX_TOKEN,sizeof(char ));
return parm;
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void Init_Nexus_Format(nexcom **com)
{
/*****************************/
strcpy(com[0]->name,"dimensions");
com[0]->nparm = 2;
com[0]->nxt_token_t = NEXUS_PARM;
com[0]->cur_token_t = NEXUS_COM;
com[0]->parm[0] = Make_Nexus_Parm();
strcpy(com[0]->parm[0]->name,"ntax");
com[0]->parm[0]->fp = Read_Nexus_Dimensions;
com[0]->parm[0]->com = com[0];
com[0]->parm[0]->nxt_token_t = NEXUS_EQUAL;
com[0]->parm[0]->cur_token_t = NEXUS_PARM;
com[0]->parm[1] = Make_Nexus_Parm();
strcpy(com[0]->parm[1]->name,"nchar");
com[0]->parm[1]->fp = Read_Nexus_Dimensions;
com[0]->parm[1]->com = com[0];
com[0]->parm[1]->nxt_token_t = NEXUS_EQUAL;
com[0]->parm[1]->cur_token_t = NEXUS_PARM;
/*****************************/
strcpy(com[1]->name,"format");
com[1]->nparm = 11;
com[1]->nxt_token_t = NEXUS_PARM;
com[1]->cur_token_t = NEXUS_COM;
com[1]->parm[0] = Make_Nexus_Parm();
strcpy(com[1]->parm[0]->name,"datatype");
com[1]->parm[0]->fp = Read_Nexus_Format;
com[1]->parm[0]->com = com[1];
com[1]->parm[0]->nxt_token_t = NEXUS_EQUAL;
com[1]->parm[0]->cur_token_t = NEXUS_PARM;
com[1]->parm[1] = Make_Nexus_Parm();
strcpy(com[1]->parm[1]->name,"respectcase");
com[1]->parm[1]->fp = Read_Nexus_Format;
com[1]->parm[1]->com = com[1];
com[1]->parm[1]->nxt_token_t = NEXUS_PARM;
com[1]->parm[1]->cur_token_t = NEXUS_VALUE;
com[1]->parm[2] = Make_Nexus_Parm();
strcpy(com[1]->parm[2]->name,"missing");
com[1]->parm[2]->fp = Read_Nexus_Format;
com[1]->parm[2]->com = com[1];
com[1]->parm[2]->nxt_token_t = NEXUS_EQUAL;
com[1]->parm[2]->cur_token_t = NEXUS_PARM;
com[1]->parm[3] = Make_Nexus_Parm();
strcpy(com[1]->parm[3]->name,"gap");
com[1]->parm[3]->fp = Read_Nexus_Format;
com[1]->parm[3]->com = com[1];
com[1]->parm[3]->nxt_token_t = NEXUS_EQUAL;
com[1]->parm[3]->cur_token_t = NEXUS_PARM;
com[1]->parm[4] = Make_Nexus_Parm();
strcpy(com[1]->parm[4]->name,"symbols");
com[1]->parm[4]->fp = Read_Nexus_Format;
com[1]->parm[4]->com = com[1];
com[1]->parm[4]->nxt_token_t = NEXUS_EQUAL;
com[1]->parm[4]->cur_token_t = NEXUS_PARM;
com[1]->parm[5] = Make_Nexus_Parm();
strcpy(com[1]->parm[5]->name,"equate");
com[1]->parm[5]->fp = Read_Nexus_Format;
com[1]->parm[5]->com = com[1];
com[1]->parm[5]->nxt_token_t = NEXUS_EQUAL;
com[1]->parm[5]->cur_token_t = NEXUS_PARM;
com[1]->parm[6] = Make_Nexus_Parm();
strcpy(com[1]->parm[6]->name,"matchchar");
com[1]->parm[6]->fp = Read_Nexus_Format;
com[1]->parm[6]->com = com[1];
com[1]->parm[6]->nxt_token_t = NEXUS_EQUAL;
com[1]->parm[6]->cur_token_t = NEXUS_PARM;
com[1]->parm[7] = Make_Nexus_Parm();
strcpy(com[1]->parm[7]->name,"transpose");
com[1]->parm[7]->fp = Read_Nexus_Format;
com[1]->parm[7]->com = com[1];
com[1]->parm[7]->nxt_token_t = NEXUS_PARM;
com[1]->parm[7]->cur_token_t = NEXUS_VALUE;
com[1]->parm[8] = Make_Nexus_Parm();
strcpy(com[1]->parm[8]->name,"interleave");
com[1]->parm[8]->fp = Read_Nexus_Format;
com[1]->parm[8]->com = com[1];
com[1]->parm[8]->nxt_token_t = NEXUS_PARM;
com[1]->parm[8]->cur_token_t = NEXUS_VALUE;
com[1]->parm[9] = Make_Nexus_Parm();
strcpy(com[1]->parm[9]->name,"items");
com[1]->parm[9]->fp = Read_Nexus_Format;
com[1]->parm[9]->com = com[1];
com[1]->parm[9]->nxt_token_t = NEXUS_EQUAL;
com[1]->parm[9]->cur_token_t = NEXUS_PARM;
com[1]->parm[10] = Make_Nexus_Parm();
strcpy(com[1]->parm[10]->name,"statesformat");
com[1]->parm[10]->fp = Read_Nexus_Format;
com[1]->parm[10]->com = com[1];
com[1]->parm[10]->nxt_token_t = NEXUS_EQUAL;
com[1]->parm[10]->cur_token_t = NEXUS_PARM;
/*****************************/
strcpy(com[2]->name,"eliminate");
com[2]->nparm = 0;
com[2]->nxt_token_t = NEXUS_VALUE;
com[2]->cur_token_t = NEXUS_COM;
/*****************************/
strcpy(com[3]->name,"taxlabels");
com[3]->nparm = 0;
com[3]->nxt_token_t = -1;
com[3]->cur_token_t = -1;
/*****************************/
strcpy(com[4]->name,"charstatelabels");
com[4]->nparm = 0;
com[4]->nxt_token_t = -1;
com[4]->cur_token_t = -1;
/*****************************/
strcpy(com[5]->name,"charlabels");
com[5]->nparm = 0;
com[5]->nxt_token_t = -1;
com[5]->cur_token_t = -1;
/*****************************/
strcpy(com[6]->name,"statelabels");
com[6]->nparm = 0;
com[6]->nxt_token_t = -1;
com[6]->cur_token_t = -1;
/*****************************/
strcpy(com[7]->name,"matrix");
com[7]->nparm = 1;
com[7]->nxt_token_t = NEXUS_COM;
com[7]->cur_token_t = NEXUS_VALUE; /* This will allow us to skip directly
to the matrix reading function */
com[7]->parm[0] = Make_Nexus_Parm();
strcpy(com[7]->parm[0]->name,"matrix");
com[7]->parm[0]->fp = Read_Nexus_Matrix;
com[7]->parm[0]->com = com[7];
com[7]->parm[0]->nxt_token_t = NEXUS_COM;
com[7]->parm[0]->cur_token_t = -1;
/*****************************/
strcpy(com[8]->name,"begin");
com[8]->nparm = 3;
com[8]->nxt_token_t = NEXUS_PARM;
com[8]->cur_token_t = NEXUS_COM;
com[8]->parm[0] = Make_Nexus_Parm();
strcpy(com[8]->parm[0]->name,"data");
com[8]->parm[0]->fp = Read_Nexus_Begin;
com[8]->parm[0]->com = com[8];
com[8]->parm[0]->nxt_token_t = NEXUS_COM;
com[8]->parm[0]->cur_token_t = NEXUS_PARM;
com[8]->parm[1] = Make_Nexus_Parm();
strcpy(com[8]->parm[1]->name,"trees");
com[8]->parm[1]->fp = Read_Nexus_Begin;
com[8]->parm[1]->com = com[8];
com[8]->parm[1]->nxt_token_t = NEXUS_COM;
com[8]->parm[1]->cur_token_t = NEXUS_PARM;
com[8]->parm[2] = Make_Nexus_Parm();
strcpy(com[8]->parm[2]->name,"taxa");
com[8]->parm[2]->fp = Read_Nexus_Taxa;
com[8]->parm[2]->com = com[8];
com[8]->parm[2]->nxt_token_t = NEXUS_COM;
com[8]->parm[2]->cur_token_t = NEXUS_VALUE;
/*****************************/
strcpy(com[9]->name,"end");
com[9]->nparm = 0;
com[9]->nxt_token_t = -1;
com[9]->cur_token_t = -1;
/*****************************/
strcpy(com[10]->name,"translate");
com[10]->nparm = 1;
com[10]->nxt_token_t = NEXUS_COM;
com[10]->cur_token_t = NEXUS_VALUE;
com[10]->parm[0] = Make_Nexus_Parm();
strcpy(com[10]->parm[0]->name,"translate");
com[10]->parm[0]->fp = Read_Nexus_Translate;
com[10]->parm[0]->com = com[10];
com[10]->parm[0]->nxt_token_t = NEXUS_COM;
com[10]->parm[0]->cur_token_t = -1;
/*****************************/
strcpy(com[11]->name,"tree");
com[11]->nparm = 1;
com[11]->nxt_token_t = NEXUS_COM;
com[11]->cur_token_t = NEXUS_VALUE;
com[11]->parm[0] = Make_Nexus_Parm();
strcpy(com[11]->parm[0]->name,"tree");
com[11]->parm[0]->fp = Read_Nexus_Tree;
com[11]->parm[0]->com = com[11];
com[11]->parm[0]->nxt_token_t = -1;
com[11]->parm[0]->cur_token_t = -1;
/*****************************/
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void Find_Nexus_Com(char *token, nexcom **found_com, nexparm **default_parm, nexcom **com_list)
{
int i,j,tokenlen,ndiff;
For(i,N_MAX_NEX_COM)
{
tokenlen = strlen(token);
ndiff = -1;
if(tokenlen && (tokenlen == strlen(com_list[i]->name)))
{
ndiff = 0;
For(j,tokenlen)
{
Lowercase(token+j);
Lowercase(com_list[i]->name+j);
if(token[j] != com_list[i]->name[j]) ndiff++;
}
}
if(!ndiff) { *found_com = com_list[i]; break; }
}
if(*found_com && (*found_com)->nparm) *default_parm = (*found_com)->parm[0];
if(*found_com) PhyML_Printf("\n. Found command '%s'.\n",(*found_com)->name);
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void Find_Nexus_Parm(char *token, nexparm **found_parm, nexcom *curr_com)
{
int i,j;
int tokenlen;
int ndiff;
if(!curr_com)
{
PhyML_Printf("\n. Err in file %s at line %d\n",__FILE__,__LINE__);
Warn_And_Exit("");
}
For(i,curr_com->nparm)
{
tokenlen = strlen(token);
ndiff = -1;
if(tokenlen == strlen(curr_com->parm[i]->name))
{
ndiff = 0;
For(j,tokenlen)
{
Lowercase(token+j);
Lowercase(curr_com->parm[i]->name+j);
if(token[j] != curr_com->parm[i]->name[j]) ndiff++;
}
}
if(!ndiff) { *found_parm = curr_com->parm[i]; break; }
}
if(*found_parm) PhyML_Printf("\n. Found parameter '%s'.\n",(*found_parm)->name);
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
int Read_Nexus_Taxa(char *token, nexparm *curr_parm, option *io)
{
PhyML_Printf("\n. Skipping 'taxa' block");
do
{
Get_Token(io->fp_in_tree,token);
if(token[0] == ';') break;
}while(strlen(token) > 0);
fseek(io->fp_in_tree,-1*sizeof(char),SEEK_CUR);
return 1;
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
int Read_Nexus_Translate(char *token, nexparm *curr_parm, option *io)
{
int tax_num;
char *end;
PhyML_Printf("\n. Reading 'translate' block");
io->size_tax_names = 0;
do
{
Get_Token(io->fp_in_tree,token);
if(token[0] == ';') break;
tax_num = (int)strtol(token,&end,10);
if(*end =='\0' && token[0])
{
io->size_tax_names++;
io->short_tax_names = (char **)realloc(io->short_tax_names,io->size_tax_names*sizeof(char *));
io->short_tax_names[io->size_tax_names-1] = (char *)mCalloc(strlen(token)+1,sizeof(char));
sprintf(io->short_tax_names[io->size_tax_names-1],"%d",tax_num);
Get_Token(io->fp_in_tree,token);
io->long_tax_names = (char **)realloc(io->long_tax_names,io->size_tax_names*sizeof(char *));
io->long_tax_names[io->size_tax_names-1] = (char *)mCalloc(strlen(token)+1,sizeof(char));
strcpy(io->long_tax_names[io->size_tax_names-1],token);
/* printf("\n. Copying %s number %d",io->long_tax_names[io->size_long_tax_names-1],tax_num-1); */
}
}while(strlen(token) > 0);
fseek(io->fp_in_tree,-1*sizeof(char),SEEK_CUR);
return 1;
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
int Read_Nexus_Matrix(char *token, nexparm *curr_parm, option *io)
{
if(io->interleaved) io->data = Read_Seq_Interleaved(io);
else io->data = Read_Seq_Sequential(io);
fseek(io->fp_in_align,-1*sizeof(char),SEEK_CUR);
return 1;
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
int Read_Nexus_Tree(char *token, nexparm *curr_parm, option *io)
{
io->treelist->tree = (t_tree **)realloc(io->treelist->tree,(io->treelist->list_size+1)*sizeof(t_tree *));
io->tree = Read_Tree_File_Phylip(io->fp_in_tree);
if(!(io->treelist->list_size%10) && io->treelist->list_size > 1)
{
PhyML_Printf("\n. Reading tree %d",io->treelist->list_size);
if(io->tree->n_root) PhyML_Printf(" (that is a rooted tree)");
else PhyML_Printf(" (that is an unrooted tree)");
}
io->treelist->tree[io->treelist->list_size] = io->tree;
io->treelist->list_size++;
fseek(io->fp_in_tree,-1*sizeof(char),SEEK_CUR);
return 1;
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
int Read_Nexus_Begin(char *token, nexparm *curr_parm, option *io)
{
if(token[0] == '=') return 0;
if(!curr_parm)
{
PhyML_Printf("\n. Err in file %s at line %d\n",__FILE__,__LINE__);
Warn_And_Exit("");
}
if(!strcmp(curr_parm->name,"data") || !strcmp(curr_parm->name,"trees"))
PhyML_Printf("\n. Reading '%s' block.\n",curr_parm->value);
else
{
PhyML_Printf("\n. The '%s' block type is not supported by PhyML. Sorry.\n",curr_parm->name);
PhyML_Printf("\n. Err in file %s at line %d\n",__FILE__,__LINE__);
Warn_And_Exit("");
}
return 1;
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
int Read_Nexus_Dimensions(char *token, nexparm *curr_parm, option *io)
{
if(token[0] == '=') return 0;
if(!curr_parm)
{
PhyML_Printf("\n. Err in file %s at line %d\n",__FILE__,__LINE__);
Warn_And_Exit("");
}
strcpy(curr_parm->value,token);
if(!strcmp(curr_parm->name,"ntax"))
{
sscanf(curr_parm->value,"%d",&(io->n_otu));
}
if(!strcmp(curr_parm->name,"nchar"))
{
sscanf(curr_parm->value,"%d",&(io->init_len));
}
return 1;
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
int Read_Nexus_Format(char *token, nexparm *curr_parm, option *io)
{
int i;
if(token[0] == '=') return 0;
if(!curr_parm)
{
PhyML_Printf("\n. Err in file %s at line %d\n",__FILE__,__LINE__);
Warn_And_Exit("");
}
For(i,strlen(token)) Lowercase(token+i);
strcpy(curr_parm->value,token);
if(!strcmp(curr_parm->name,"datatype"))
{
if(!strcmp(curr_parm->value,"standard"))
{
io->datatype = GENERIC;
io->mod->whichmodel = JC69;
io->mod->s_opt->opt_kappa = NO;
io->mod->s_opt->opt_lambda = NO;
io->mod->ns = 2;
io->alphabet[0][0] = '0'; io->alphabet[0][1] = '\0';
io->alphabet[1][0] = '1'; io->alphabet[1][1] = '\0';
}
else if(!strcmp(curr_parm->value,"dna"))
{
io->datatype = NT;
io->mod->ns = 4;
}
else if(!strcmp(curr_parm->value,"rna"))
{
io->datatype = NT;
io->mod->ns = 4;
}
else if(!strcmp(curr_parm->value,"nucleotide"))
{
io->datatype = NT;
io->mod->ns = 4;
}
else if(!strcmp(curr_parm->value,"protein"))
{
io->datatype = AA;
io->mod->ns = 20;
}
else if(!strcmp(curr_parm->value,"continuous"))
{
PhyML_Printf("\n. The 'continuous' format is not supported by PhyML. Sorry.\n");
PhyML_Printf("\n. Err in file %s at line %d\n",__FILE__,__LINE__);
Warn_And_Exit("");
}
}
else if(!strcmp(curr_parm->name,"missing"))
{
PhyML_Printf("\n. The 'missing' subcommand is not supported by PhyML. Sorry.\n");
PhyML_Printf("\n. Err in file %s at line %d\n",__FILE__,__LINE__);
Warn_And_Exit("");
}
else if(!strcmp(curr_parm->name,"gap"))
{
PhyML_Printf("\n. The 'gap' subcommand is not supported by PhyML. Sorry.\n");
PhyML_Printf("\n. But the characters 'X', '?' and '-' will be considered as indels by default.\n");
PhyML_Printf("\n. Err in file %s at line %d\n",__FILE__,__LINE__);
Warn_And_Exit("");
}
else if(!strcmp(curr_parm->name,"symbols"))
{
if(*token != '"' || *(token+strlen(token)-1) != '"')
{
PhyML_Printf("\n. Symbols list is supposed to be displayed between quotation marks (e.g., \"ACTG\").\n");
PhyML_Printf("\n. Err in file %s at line %d\n",__FILE__,__LINE__);
Warn_And_Exit("");
}
int i,has_spaces,state_len;
i = 0;
has_spaces = 0;
token++; /* Get rid of the first '"' character */
while(token[i] != '"') { if(token[i] == ' ') { has_spaces = 1; break; } i++; }
io->mod->ns = 0;
if(!has_spaces)
{
while(token[i] != '"')
{
io->alphabet[io->mod->ns][0] = token[i];
io->alphabet[io->mod->ns][1] = '\0';
io->mod->ns++;
i++;
if(io->mod->ns > T_MAX_ALPHABET)
{
PhyML_Printf("\n. The alphabet cannot contain more than %d characters. Sorry.",T_MAX_ALPHABET);
PhyML_Printf("\n. Err in file %s at line %d\n",__FILE__,__LINE__);
Warn_And_Exit("");
}
}
}
else
{
i = 0;
do
{
state_len = 0;
while(token[i] != ' ' && token[i] != '"')
{
io->alphabet[io->mod->ns][state_len] = token[i];
state_len++;
i++;
if(state_len > T_MAX_STATE)
{
PhyML_Printf("\n. A state cannot contain more than %d characters. Sorry.\n",T_MAX_STATE);
PhyML_Printf("\n. Err in file %s at line %d\n",__FILE__,__LINE__);
Warn_And_Exit("");
}
}
io->alphabet[io->mod->ns][state_len] = '\0';
io->mod->ns++;
if(token[i] != '"') i++;
}
while(token[i] != '"');
}
int len;
len = strlen(io->alphabet[0]);
For(i,io->mod->ns)
{
if(strlen(io->alphabet[i]) != len)
{
PhyML_Printf("\n. All character states defined in the symbol list are supposed to have the same length.\n");
PhyML_Printf("\n. Err in file %s at line %d\n",__FILE__,__LINE__);
Warn_And_Exit("");
}
}
io->mod->state_len = len;
/* For(i,io->mod->ns) PhyML_Printf("\n. '%s'",io->alphabet[i]); */
}
else if(!strcmp(curr_parm->name,"equate"))
{
PhyML_Printf("\n. PhyML does not recognize the command '%s' yet. Sorry.",curr_parm->name);
PhyML_Printf("\n. Err in file %s at line %d\n",__FILE__,__LINE__);
Warn_And_Exit("");
}
else if(!strcmp(curr_parm->name,"matchchar"))
{
PhyML_Printf("\n. PhyML does not recognize the command '%s' yet. Sorry.",curr_parm->name);
PhyML_Printf("\n. Err in file %s at line %d\n",__FILE__,__LINE__);
Warn_And_Exit("");
}
else if(!strcmp(curr_parm->name,"items"))
{
PhyML_Printf("\n. PhyML does not recognize the command '%s' yet. Sorry.",curr_parm->name);
PhyML_Printf("\n. Err in file %s at line %d\n",__FILE__,__LINE__);
Warn_And_Exit("");
}
else if(!strcmp(curr_parm->name,"interleave"))
{
io->interleaved = 1;
}
return 1;
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
int Read_Nexus_Eliminate(char *token, nexparm *curr_parm, option *io)
{
if(token[0] == '=') return 0;
PhyML_Printf("\n. 'Eliminate' command is not supported by PhyML. Sorry.");
PhyML_Printf("\n. Err in file %s at line %d\n",__FILE__,__LINE__);
Warn_And_Exit("");
return 1;
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
int Read_Nexus_Taxlabel(char *token, nexparm *curr_parm, option *io)
{
if(token[0] == '=') return 0;
PhyML_Printf("\n. 'Taxlabels' command is not supported by PhyML. Sorry.");
PhyML_Printf("\n. Err in file %s at line %d\n",__FILE__,__LINE__);
Warn_And_Exit("");
return 1;
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
int Read_Nexus_Charstatelabels(char *token, nexparm *curr_parm, option *io)
{
if(token[0] == '=') return 0;
PhyML_Printf("\n. 'CharStateLabels' command is not supported by PhyML. Sorry.");
PhyML_Printf("\n. Err in file %s at line %d\n",__FILE__,__LINE__);
Warn_And_Exit("");
return 1;
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
int Read_Nexus_Charlabels(char *token, nexparm *curr_parm, option *io)
{
if(token[0] == '=') return 0;
PhyML_Printf("\n. 'CharLabels' command is not supported by PhyML. Sorry.");
PhyML_Printf("\n. Err in file %s at line %d\n",__FILE__,__LINE__);
Warn_And_Exit("");
return 1;
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
int Read_Nexus_Statelabels(char *token, nexparm *curr_parm, option *io)
{
if(token[0] == '=') return 0;
PhyML_Printf("\n. 'StateLabels' command is not supported by PhyML. Sorry.");
PhyML_Printf("\n. Err in file %s at line %d\n",__FILE__,__LINE__);
Warn_And_Exit("");
return 1;
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
align **Get_Seq_Phylip(option *io)
{
Read_Ntax_Len_Phylip(io->fp_in_align,&io->n_otu,&io->init_len);
if(io->n_otu > N_MAX_OTU)
{
PhyML_Printf("\n. The number of taxa should not exceed %d",N_MAX_OTU);
Exit("\n");
}
if(io->interleaved) io->data = Read_Seq_Interleaved(io);
else io->data = Read_Seq_Sequential(io);
return io->data;
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void Read_Ntax_Len_Phylip(FILE *fp ,int *n_otu, int *n_tax)
{
char *line;
int readok;
line = (char *)mCalloc(T_MAX_LINE,sizeof(char));
readok = 0;
do
{
if(fscanf(fp,"%s",line) == EOF)
{
Free(line);
PhyML_Printf("\n. Err in file %s at line %d\n",__FILE__,__LINE__);
Warn_And_Exit("");
}
else
{
if(strcmp(line,"\n") && strcmp(line,"\r") && strcmp(line,"\t"))
{
sscanf(line,"%d",n_otu);
if(*n_otu <= 0) Warn_And_Exit("\n. The number of taxa cannot be negative.\n");
if(!fscanf(fp,"%s",line)) Exit("\n");
sscanf(line,"%d",n_tax);
if(*n_tax <= 0) Warn_And_Exit("\n. The sequence length cannot be negative.\n");
else readok = 1;
}
}
}while(!readok);
Free(line);
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
align **Read_Seq_Sequential(option *io)
{
int i;
char *line;
align **data;
/* char c; */
char *format;
format = (char *)mCalloc(T_MAX_NAME,sizeof(char));
line = (char *)mCalloc(T_MAX_LINE,sizeof(char));
data = (align **)mCalloc(io->n_otu,sizeof(align *));
/* while((c=fgetc(in))!='\n'); */
/* while(((c=fgetc(io->fp_in_align))!='\n') && (c != ' ') && (c != '\r') && (c != '\t')); */
For(i,io->n_otu)
{
data[i] = (align *)mCalloc(1,sizeof(align));
data[i]->name = (char *)mCalloc(T_MAX_NAME,sizeof(char));
data[i]->state = (char *)mCalloc(io->init_len*io->mod->state_len+1,sizeof(char));
data[i]->is_ambigu = NULL;
data[i]->len = 0;
sprintf(format, "%%%ds", T_MAX_NAME);
if(!fscanf(io->fp_in_align,format,data[i]->name)) Exit("\n");
Check_Sequence_Name(data[i]->name);
while(data[i]->len < io->init_len * io->mod->state_len) Read_One_Line_Seq(&data,i,io->fp_in_align);
if(data[i]->len != io->init_len * io->mod->state_len)
{
PhyML_Printf("\n. Err: Problem with species %s's sequence (check the format).\n",data[i]->name);
PhyML_Printf("\n. Observed sequence length: %d, expected length: %d\n",data[i]->len, io->init_len * io->mod->state_len);
Warn_And_Exit("");
}
}
For(i,io->n_otu) data[i]->state[data[i]->len] = '\0';
Restrict_To_Coding_Position(data,io);
Free(format);
Free(line);
return data;
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
align **Read_Seq_Interleaved(option *io)
{
int i,end,num_block;
char *line;
align **data;
/* char c; */
char *format;
line = (char *)mCalloc(T_MAX_LINE,sizeof(char));
format = (char *)mCalloc(T_MAX_NAME, sizeof(char));
data = (align **)mCalloc(io->n_otu,sizeof(align *));
/* while(((c=fgetc(io->fp_in_align))!='\n') && (c != ' ') && (c != '\r') && (c != '\t')); */
end = 0;
For(i,io->n_otu)
{
data[i] = (align *)mCalloc(1,sizeof(align));
data[i]->name = (char *)mCalloc(T_MAX_NAME,sizeof(char));
data[i]->state = (char *)mCalloc(io->init_len*io->mod->state_len+1,sizeof(char));
data[i]->len = 0;
data[i]->is_ambigu = NULL;
sprintf(format, "%%%ds", T_MAX_NAME);
/* sprintf(format, "%%%ds", 10); */
if(!fscanf(io->fp_in_align,format,data[i]->name)) Exit("\n");
Check_Sequence_Name(data[i]->name);
if(!Read_One_Line_Seq(&data,i,io->fp_in_align))
{
end = 1;
if((i != io->n_otu) && (i != io->n_otu-1))
{
PhyML_Printf("\n. Err: Problem with species %s's sequence.\n",data[i]->name);
PhyML_Printf("\n. Observed sequence length: %d, expected length: %d\n",data[i]->len, io->init_len * io->mod->state_len);
Warn_And_Exit("");
}
break;
}
}
if(data[0]->len == io->init_len * io->mod->state_len) end = 1;
/* if(end) printf("\n. finished yet '%c'\n",fgetc(io->fp_in_align)); */
if(!end)
{
end = 0;
num_block = 1;
do
{
num_block++;
/* interblock */
if(!fgets(line,T_MAX_LINE,io->fp_in_align)) break;
if(line[0] != 13 && line[0] != 10)
{
PhyML_Printf("\n. One or more missing sequences in block %d.\n",num_block-1);
Warn_And_Exit("");
}
For(i,io->n_otu) if(data[i]->len != io->init_len * io->mod->state_len) break;
if(i == io->n_otu) break;
For(i,io->n_otu)
{
if(data[i]->len > io->init_len * io->mod->state_len)
{
PhyML_Printf("\n. Observed length=%d expected length=%d.\n",data[i]->len,io->init_len * io->mod->state_len);
PhyML_Printf("\n. Err: Problem with species %s's sequence.\n",data[i]->name);
Warn_And_Exit("");
}
else if(!Read_One_Line_Seq(&data,i,io->fp_in_align))
{
end = 1;
if((i != io->n_otu) && (i != io->n_otu-1))
{
PhyML_Printf("\n. Err: Problem with species %s's sequence.\n",data[i]->name);
PhyML_Printf("\n. Observed sequence length: %d, expected length: %d.\n",data[i]->len, io->init_len * io->mod->state_len);
Warn_And_Exit("");
}
break;
}
}
}while(!end);
}
For(i,io->n_otu) data[i]->state[data[i]->len] = '\0';
For(i,io->n_otu)
{
if(data[i]->len != io->init_len * io->mod->state_len)
{
PhyML_Printf("\n. Check sequence '%s' length (expected length: %d, observed length: %d) [OTU %d].\n",data[i]->name,io->init_len,data[i]->len,i+1);
Warn_And_Exit("");
}
}
Restrict_To_Coding_Position(data,io);
Free(format);
Free(line);
return data;
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void Restrict_To_Coding_Position(align **data, option *io)
{
int i,j,curr_pos;
if(io->codpos != -1)
{
For(i,io->n_otu)
{
curr_pos = 0;
for(j=io->codpos-1;jlen;j+=3)
{
data[i]->state[curr_pos] = data[i]->state[j];
curr_pos++;
}
data[i]->len /= 3;
}
}
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
int Read_One_Line_Seq(align ***data, int num_otu, FILE *in)
{
char c = ' ';
int nchar = 0;
while(1)
{
/* if((c == EOF) || (c == '\n') || (c == '\r')) break; */
if((c == 13) || (c == 10))
{
/* PhyML_Printf("[%d %d]\n",c,nchar); fflush(NULL); */
if(!nchar)
{
c=(char)fgetc(in);
continue;
}
else
{
/* PhyML_Printf("break\n"); */
break;
}
}
else if(c == EOF)
{
/* PhyML_Printf("EOL\n"); */
break;
}
else if((c == ' ') || (c == '\t') || (c == 32))
{
/* PhyML_Printf("[%d]",c); */
c=(char)fgetc(in);
continue;
}
nchar++;
Uppercase(&c);
if(c == '.')
{
c = (*data)[0]->state[(*data)[num_otu]->len];
if(!num_otu)
Warn_And_Exit("\n. Err: Symbol \".\" should not appear in the first sequence\n");
}
(*data)[num_otu]->state[(*data)[num_otu]->len]=c;
(*data)[num_otu]->len++;
/* PhyML_Printf("%c",c); */
c = (char)fgetc(in);
if(c == ';') break;
}
if(c == EOF) return 0;
else return 1;
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void Uppercase(char *ch)
{
/* convert ch to upper case -- either ASCII or EBCDIC */
*ch = isupper((int)*ch) ? *ch : toupper((int)*ch);
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void Lowercase(char *ch)
{
/* convert ch to upper case -- either ASCII or EBCDIC */
*ch = isupper((int)*ch) ? tolower((int)*ch) : *ch;
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
calign *Compact_Data(align **data, option *io)
{
calign *cdata_tmp,*cdata;
int i,j,k,site;
int n_patt,which_patt,n_invar;
char **sp_names;
int n_otu, n_sites;
pnode *proot;
int compress;
int n_ambigu,is_ambigu;
n_otu = io->n_otu;
n_patt = 0;
which_patt = 0;
sp_names = (char **)mCalloc(n_otu,sizeof(char *));
For(i,n_otu)
{
sp_names[i] = (char *)mCalloc(T_MAX_NAME,sizeof(char));
strcpy(sp_names[i],data[i]->name);
}
cdata_tmp = Make_Cseq(n_otu,data[0]->len,io->mod->state_len,data[0]->len,sp_names);
proot = (pnode *)Create_Pnode(T_MAX_ALPHABET);
For(i,n_otu) Free(sp_names[i]);
Free(sp_names);
if(data[0]->len%io->mod->state_len)
{
PhyML_Printf("\n. Sequence length is not a multiple of %d\n",io->mod->state_len);
Warn_And_Exit("");
}
compress = io->colalias;
n_ambigu = 0;
is_ambigu = 0;
if(!io->quiet && !compress)
{
PhyML_Printf("\n. WARNING: sequences are not compressed !\n");
}
Fors(site,data[0]->len,io->mod->state_len)
{
if(io->rm_ambigu)
{
is_ambigu = 0;
For(j,n_otu) if(Is_Ambigu(data[j]->state+site,io->datatype,io->mod->state_len)) break;
if(j != n_otu)
{
is_ambigu = 1;
n_ambigu++;
}
}
if(!is_ambigu)
{
if(compress)
{
which_patt = -1;
Traverse_Prefix_Tree(site,-1,&which_patt,&n_patt,data,io,proot);
if(which_patt == n_patt-1) /* New pattern found */
{
n_patt--;
k=n_patt;
}
else
{
k = n_patt-10;
}
}
else
{
k = n_patt;
}
if(k == n_patt) /* add a new site pattern */
{
For(j,n_otu)
Copy_One_State(data[j]->state+site,
cdata_tmp->c_seq[j]->state+n_patt*io->mod->state_len,
io->mod->state_len);
For(i,n_otu)
{
For(j,n_otu)
{
if(!(Are_Compatible(cdata_tmp->c_seq[i]->state+n_patt*io->mod->state_len,
cdata_tmp->c_seq[j]->state+n_patt*io->mod->state_len,
io->mod->state_len,
io->datatype))) break;
}
if(j != n_otu) break;
}
if((j == n_otu) && (i == n_otu)) /* all characters at that site are compatible with one another:
the site may be invariant */
{
For(j,n_otu)
{
cdata_tmp->invar[n_patt] = Assign_State(cdata_tmp->c_seq[j]->state+n_patt*io->mod->state_len,
io->datatype,
io->mod->state_len);
if(cdata_tmp->invar[n_patt] > -1.) break; /* It is not actually (at least one state in the column is ambiguous) */
}
}
else cdata_tmp->invar[n_patt] = -1;
cdata_tmp->sitepatt[site] = n_patt;
cdata_tmp->wght[n_patt] += 1;
n_patt += 1;
}
else
{
cdata_tmp->sitepatt[site] = which_patt;
cdata_tmp->wght[which_patt] += 1;
}
}
}
data[0]->len -= n_ambigu;
cdata_tmp->init_len = data[0]->len;
cdata_tmp->crunch_len = n_patt;
For(i,n_otu) cdata_tmp->c_seq[i]->len = n_patt;
if(!io->quiet) PhyML_Printf("\n. %d patterns found (out of a total of %d sites). \n",n_patt,data[0]->len);
if((io->rm_ambigu) && (n_ambigu)) PhyML_Printf("\n. Removed %d columns of the alignment as they contain ambiguous characters (e.g., gaps) \n",n_ambigu);
/* For(i,n_otu) */
/* { */
/* For(j,cdata_tmp->crunch_len) */
/* { */
/* printf("%c",cdata_tmp->c_seq[i]->state[j*io->mod->state_len+1]); */
/* } */
/* printf("\n"); */
/* } */
n_invar=0;
For(i,cdata_tmp->crunch_len)
{
if(cdata_tmp->invar[i] > -1.) n_invar+=(int)cdata_tmp->wght[i];
}
if(!io->quiet) PhyML_Printf("\n. %d sites without polymorphism (%.2f%c).\n",n_invar,100.*(phydbl)n_invar/data[0]->len,'%');
cdata_tmp->obs_pinvar = (phydbl)n_invar/data[0]->len;
n_sites = 0;
For(i,cdata_tmp->crunch_len) n_sites += cdata_tmp->wght[i];
if(n_sites != data[0]->len / io->mod->state_len)
{
PhyML_Printf("\n. Err in file %s at line %d\n",__FILE__,__LINE__);
Warn_And_Exit("");
}
if(io->datatype == NT) Get_Base_Freqs(cdata_tmp);
else if(io->datatype == AA) Get_AA_Freqs(cdata_tmp);
else {/* Uniform state frequency distribution.*/}
cdata = Copy_Cseq(cdata_tmp,io);
Free_Cseq(cdata_tmp);
Free_Prefix_Tree(proot,T_MAX_ALPHABET);
return cdata;
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
calign *Compact_Cdata(calign *data, option *io)
{
calign *cdata;
int i,j,k,site;
int n_patt,which_patt;
int n_otu;
n_otu = data->n_otu;
cdata = (calign *)mCalloc(1,sizeof(calign));
cdata->n_otu = n_otu;
cdata->c_seq = (align **)mCalloc(n_otu,sizeof(align *));
cdata->wght = (int *)mCalloc(data->crunch_len,sizeof(int));
cdata->b_frq = (phydbl *)mCalloc(io->mod->ns,sizeof(phydbl));
cdata->ambigu = (short int *)mCalloc(data->crunch_len,sizeof(short int));
cdata->invar = (short int *)mCalloc(data->crunch_len,sizeof(short int));
cdata->crunch_len = cdata->init_len = -1;
For(j,n_otu)
{
cdata->c_seq[j] = (align *)mCalloc(1,sizeof(align));
cdata->c_seq[j]->name = (char *)mCalloc(T_MAX_NAME,sizeof(char));
strcpy(cdata->c_seq[j]->name,data->c_seq[j]->name);
cdata->c_seq[j]->state = (char *)mCalloc(data->crunch_len,sizeof(char));
cdata->c_seq[j]->is_ambigu = (short int *)mCalloc(data->crunch_len,sizeof(short int));
cdata->c_seq[j]->state[0] = data->c_seq[j]->state[0];
}
n_patt = which_patt = 0;
For(site,data->crunch_len)
{
if(data->wght[site])
{
For(k,n_patt)
{
For(j,n_otu)
{
if(strncmp(cdata->c_seq[j]->state+k*io->mod->state_len,
data->c_seq[j]->state+site*io->mod->state_len,
io->mod->state_len))
break;
}
if(j == n_otu)
{
which_patt = k;
break;
}
}
/* /\* TO DO *\/ */
/* k = n_patt; */
if(k == n_patt)
{
For(j,n_otu) Copy_One_State(data->c_seq[j]->state+site*io->mod->state_len,
cdata->c_seq[j]->state+n_patt*io->mod->state_len,
io->mod->state_len);
For(i,n_otu)
{
For(j,n_otu)
{
if(!(Are_Compatible(cdata->c_seq[i]->state+n_patt*io->mod->state_len,
cdata->c_seq[j]->state+n_patt*io->mod->state_len,
io->mod->state_len,
io->datatype))) break;
}
if(j != n_otu) break;
}
if((j == n_otu) && (i == n_otu))
{
For(j,n_otu)
{
cdata->invar[n_patt] = Assign_State(cdata->c_seq[j]->state+n_patt*io->mod->state_len,
io->datatype,
io->mod->state_len);
if(cdata->invar[n_patt] > -1.) break;
}
}
else cdata->invar[n_patt] = -1;
cdata->wght[n_patt] += data->wght[site];
n_patt+=1;
}
else cdata->wght[which_patt] += data->wght[site];
/* Print_Site(cdata,k,n_otu,"\n",io->stepsize); */
}
}
cdata->init_len = data->crunch_len;
cdata->crunch_len = n_patt;
For(i,n_otu) cdata->c_seq[i]->len = n_patt;
if(io->datatype == NT) Get_Base_Freqs(cdata);
else if(io->datatype == AA) Get_AA_Freqs(cdata);
else {/* Not implemented yet */}
return cdata;
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void Traverse_Prefix_Tree(int site, int seqnum, int *patt_num, int *n_patt, align **data, option *io, pnode *n)
{
int ret_val;
ret_val = -1;
if(seqnum == io->n_otu-1)
{
n->weight++;
if(n->weight == 1)
{
n->num = *n_patt;
(*n_patt) += 1;
}
(*patt_num) = n->num;
return;
}
else
{
int next_state;
next_state = -1;
next_state = Assign_State_With_Ambiguity(data[seqnum+1]->state+site,
io->datatype,
io->mod->state_len);
if(!n->next[next_state]) n->next[next_state] = Create_Pnode(T_MAX_ALPHABET);
Traverse_Prefix_Tree(site,seqnum+1,patt_num,n_patt,data,io,n->next[next_state]);
}
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
pnode *Create_Pnode(int size)
{
pnode *n;
int i;
n = (pnode *)mCalloc(1,sizeof(pnode ));
n->next = (pnode **)mCalloc(size,sizeof(pnode *));
For(i,size) n->next[i] = NULL;
n->weight = 0;
n->num = -1;
return n;
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void Get_Base_Freqs(calign *data)
{
int i,j,k;
phydbl A,C,G,T;
phydbl fA,fC,fG,fT;
int w;
fA = fC = fG = fT = .25;
For(k,8)
{
A = C = G = T = .0;
For(i,data->n_otu)
{
For(j,data->crunch_len)
{
w = data->wght[j];
if(w)
{
switch(data->c_seq[i]->state[j])
{
case 'A' : A+=w;
break;
case 'C' : C+=w;
break;
case 'G' : G+=w;
break;
case 'T' : T+=w;
break;
case 'U' : T+=w;
break;
case 'M' : C+=w*fC/(fC+fA); A+=w*fA/(fA+fC);
break;
case 'R' : G+=w*fG/(fA+fG); A+=w*fA/(fA+fG);
break;
case 'W' : T+=w*fT/(fA+fT); A+=w*fA/(fA+fT);
break;
case 'S' : C+=w*fC/(fC+fG); G+=w*fG/(fC+fG);
break;
case 'Y' : C+=w*fC/(fC+fT); T+=w*fT/(fT+fC);
break;
case 'K' : G+=w*fG/(fG+fT); T+=w*fT/(fT+fG);
break;
case 'B' : C+=w*fC/(fC+fG+fT); G+=w*fG/(fC+fG+fT); T+=w*fT/(fC+fG+fT);
break;
case 'D' : A+=w*fA/(fA+fG+fT); G+=w*fG/(fA+fG+fT); T+=w*fT/(fA+fG+fT);
break;
case 'H' : A+=w*fA/(fA+fC+fT); C+=w*fC/(fA+fC+fT); T+=w*fT/(fA+fC+fT);
break;
case 'V' : A+=w*fA/(fA+fC+fG); C+=w*fC/(fA+fC+fG); G+=w*fG/(fA+fC+fG);
break;
case 'N' : case 'X' : case '?' : case 'O' : case '-' :
A+=w*fA; C+=w*fC; G+=w*fG; T+=w*fT; break;
default : break;
}
}
}
}
fA = A/(A+C+G+T);
fC = C/(A+C+G+T);
fG = G/(A+C+G+T);
fT = T/(A+C+G+T);
}
data->b_frq[0] = fA;
data->b_frq[1] = fC;
data->b_frq[2] = fG;
data->b_frq[3] = fT;
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void Get_AA_Freqs(calign *data)
{
int i,j,k;
phydbl A,C,D,E,F,G,H,I,K,L,M,N,P,Q,R,S,T,V,W,Y;
phydbl fA,fC,fD,fE,fF,fG,fH,fI,fK,fL,fM,fN,fP,fQ,fR,fS,fT,fV,fW,fY;
int w;
phydbl sum;
fA = fC = fD = fE = fF = fG = fH = fI = fK = fL =
fM = fN = fP = fQ = fR = fS = fT = fV = fW = fY = 1./20.;
For(k,8)
{
A = C = D = E = F = G = H = I = K = L =
M = N = P = Q = R = S = T = V = W = Y = .0;
For(i,data->n_otu)
{
For(j,data->crunch_len)
{
w = data->wght[j];
if(w)
{
switch(data->c_seq[i]->state[j])
{
case 'A' : A+=w; break;
case 'C' : C+=w; break;
case 'D' : D+=w; break;
case 'E' : E+=w; break;
case 'F' : F+=w; break;
case 'G' : G+=w; break;
case 'H' : H+=w; break;
case 'I' : I+=w; break;
case 'K' : K+=w; break;
case 'L' : L+=w; break;
case 'M' : M+=w; break;
case 'N' : N+=w; break;
case 'P' : P+=w; break;
case 'Q' : Q+=w; break;
case 'R' : R+=w; break;
case 'S' : S+=w; break;
case 'T' : T+=w; break;
case 'V' : V+=w; break;
case 'W' : W+=w; break;
case 'Y' : Y+=w; break;
case 'Z' : Q+=w; break;
case 'X' : case '?' : case 'O' : case '-' :
A+=w*fA;
C+=w*fC;
D+=w*fD;
E+=w*fE;
F+=w*fF;
G+=w*fG;
H+=w*fH;
I+=w*fI;
K+=w*fK;
L+=w*fL;
M+=w*fM;
N+=w*fN;
P+=w*fP;
Q+=w*fQ;
R+=w*fR;
S+=w*fS;
T+=w*fT;
V+=w*fV;
W+=w*fW;
Y+=w*fY;
break;
default : break;
}
}
}
}
sum = (A+C+D+E+F+G+H+I+K+L+M+N+P+Q+R+S+T+V+W+Y);
fA = A/sum; fC = C/sum; fD = D/sum; fE = E/sum;
fF = F/sum; fG = G/sum; fH = H/sum; fI = I/sum;
fK = K/sum; fL = L/sum; fM = M/sum; fN = N/sum;
fP = P/sum; fQ = Q/sum; fR = R/sum; fS = S/sum;
fT = T/sum; fV = V/sum; fW = W/sum; fY = Y/sum;
}
data->b_frq[0] = fA; data->b_frq[1] = fR; data->b_frq[2] = fN; data->b_frq[3] = fD;
data->b_frq[4] = fC; data->b_frq[5] = fQ; data->b_frq[6] = fE; data->b_frq[7] = fG;
data->b_frq[8] = fH; data->b_frq[9] = fI; data->b_frq[10] = fL; data->b_frq[11] = fK;
data->b_frq[12] = fM; data->b_frq[13] = fF; data->b_frq[14] = fP; data->b_frq[15] = fS;
data->b_frq[16] = fT; data->b_frq[17] = fW; data->b_frq[18] = fY; data->b_frq[19] = fV;
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
t_tree *Read_Tree_File(option *io)
{
t_tree *tree;
Detect_Tree_File_Format(io);
io->treelist->list_size = 0;
switch(io->tree_file_format)
{
case PHYLIP:
{
do
{
io->treelist->tree = (t_tree **)realloc(io->treelist->tree,(io->treelist->list_size+1)*sizeof(t_tree *));
io->tree = Read_Tree_File_Phylip(io->fp_in_tree);
if(!io->tree) break;
if(io->treelist->list_size > 1) PhyML_Printf("\n. Reading tree %d",io->treelist->list_size+1);
io->treelist->tree[io->treelist->list_size] = io->tree;
io->treelist->list_size++;
}while(io->tree);
break;
}
case NEXUS:
{
io->nex_com_list = Make_Nexus_Com();
Init_Nexus_Format(io->nex_com_list);
Get_Nexus_Data(io->fp_in_tree,io);
Free_Nexus(io);
break;
}
default:
{
PhyML_Printf("\n. Err in file %s at line %d\n",__FILE__,__LINE__);
Warn_And_Exit("");
break;
}
}
if(!io->long_tax_names)
{
int i;
tree = io->treelist->tree[0];
io->long_tax_names = (char **)mCalloc(tree->n_otu,sizeof(char *));
io->short_tax_names = (char **)mCalloc(tree->n_otu,sizeof(char *));
For(i,tree->n_otu)
{
io->long_tax_names[i] = (char *)mCalloc(strlen(tree->t_nodes[i]->name)+1,sizeof(char));
io->short_tax_names[i] = (char *)mCalloc(strlen(tree->t_nodes[i]->name)+1,sizeof(char));
strcpy(io->long_tax_names[i],tree->t_nodes[i]->name);
strcpy(io->short_tax_names[i],tree->t_nodes[i]->name);
}
}
return NULL;
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
char *Return_Tree_String_Phylip(FILE *fp_input_tree)
{
char *line;
int i;
char c;
int open,maxopen;
if(fp_input_tree == NULL)
{
PhyML_Printf("\n. Err in file %s at line %d\n",__FILE__,__LINE__);
Warn_And_Exit("");
}
do
{
c=fgetc(fp_input_tree);
}
while((c != '(') && (c != EOF));
if(c==EOF) return NULL;
line = (char *)mCalloc(1,sizeof(char));
open = 1;
maxopen = open;
i=0;
for(;;)
{
if((c == ' ') || (c == '\n'))
{
c=fgetc(fp_input_tree);
if(c == EOF || c == ';') break;
else continue;
}
if(c == '[')
{
Skip_Comment(fp_input_tree);
c = fgetc(fp_input_tree);
if(c == EOF || c == ';') break;
}
line = (char *)mRealloc(line,i+2,sizeof(char));
line[i]=c;
i++;
c=fgetc(fp_input_tree);
if(c==EOF || c==';') break;
if(c=='(') open++;
if(c==')') open--;
if(open>maxopen) maxopen = open;
}
line[i] = '\0';
/* if(maxopen == 1) return NULL; */
return line;
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
t_tree *Read_Tree_File_Phylip(FILE *fp_input_tree)
{
char *line;
t_tree *tree;
line = Return_Tree_String_Phylip(fp_input_tree);
tree = Read_Tree(&line);
Free(line);
return tree;
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
// Swap the nodes on the left and right of e1 with the nodes
// on the left and right of e2 respectively, or on the
// right and left of e2 if swap == YES
void Swap_Nodes_On_Edges(t_edge *e1, t_edge *e2, int swap, t_tree *tree)
{
t_node *buff;
e1->left->l[e1->l_r] = e1->l;
e1->rght->l[e1->r_l] = e1->l;
e2->left->l[e2->l_r] = e2->l;
e2->rght->l[e2->r_l] = e2->l;
printf("\n. Swap edge %d (%d %d) with %d (%d %d)",e1->num,e1->left->num,e1->rght->num,e2->num,e2->left->num,e2->rght->num);
if(swap == NO)
{
buff = e1->left;
e1->left = e2->left;
e2->left = buff;
buff = e1->rght;
e1->rght = e2->rght;
e2->rght = buff;
}
else
{
buff = e1->left;
e1->left = e2->rght;
e2->rght = buff;
buff = e1->rght;
e1->rght = e2->left;
e2->left = buff;
}
Connect_One_Edge_To_Two_Nodes(e1->left,e1->rght,e1,tree);
Connect_One_Edge_To_Two_Nodes(e2->left,e2->rght,e2,tree);
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void Connect_Edges_To_Nodes_Recur(t_node *a, t_node *d, t_tree *tree)
{
int i;
Connect_One_Edge_To_Two_Nodes(a,d,tree->t_edges[tree->num_curr_branch_available],tree);
tree->num_curr_branch_available += 1;
if(d->tax) return;
else For(i,3) if(d->v[i] != a) Connect_Edges_To_Nodes_Recur(d,d->v[i],tree);
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void Connect_One_Edge_To_Two_Nodes(t_node *a, t_node *d, t_edge *b, t_tree *tree)
{
int i,dir_a_d,dir_d_a;
dir_a_d = -1;
For(i,3) if(a->v[i] == d) {dir_a_d = i; break;}
dir_d_a = -1;
For(i,3) if(d->v[i] == a) {dir_d_a = i; break;}
if(dir_a_d == -1 || dir_d_a == -1)
{
PhyML_Printf("\n. Err in file %s at line %d\n",__FILE__,__LINE__);
Warn_And_Exit("");
}
a->b[dir_a_d] = b;
d->b[dir_d_a] = b;
b->num = tree->num_curr_branch_available;
b->left = a;
b->rght = d;
if(a->tax) {b->rght = a; b->left = d;} /* root */
/* a tip is necessary on the right hand side of the t_edge */
(b->left == a)?
(Make_Edge_Dirs(b,a,d,tree)):
(Make_Edge_Dirs(b,d,a,tree));
b->l = a->l[b->l_r];
if(a->tax) b->l = a->l[b->r_l];
b->l_old = b->l;
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void Update_Dirs(t_tree *tree)
{
int i;
int buff;
t_edge *b;
b = NULL;
buff = -1;
For(i,2*tree->n_otu-3)
{
b = tree->t_edges[i];
if((!b->left->tax) && (b->left->v[b->l_v1]->num < b->left->v[b->l_v2]->num))
{
buff = b->l_v1;
b->l_v1 = b->l_v2;
b->l_v2 = buff;
}
if((!b->rght->tax) && (b->rght->v[b->r_v1]->num < b->rght->v[b->r_v2]->num))
{
buff = b->r_v1;
b->r_v1 = b->r_v2;
b->r_v2 = buff;
}
}
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void Exit(char *message)
{
fflush(NULL);
PhyML_Fprintf(stderr,"%s",message);
exit(1);
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void *mCalloc(int nb, size_t size)
{
void *allocated;
if((allocated = calloc((size_t)nb,size)) != NULL)
/* if((allocated = malloc((size_t)nb*(size_t)size)) != NULL) */
{
return allocated;
}
else
Warn_And_Exit("\n. Err: low memory\n");
return NULL;
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void *mRealloc(void *p,int nb, size_t size)
{
if((p = realloc(p,(size_t)nb*size)) != NULL)
return p;
else
Warn_And_Exit("\n. Err: low memory\n");
return NULL;
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
/* t_tree *Make_Light_Tree_Struct(int n_otu) */
/* { */
/* t_tree *tree; */
/* int i; */
/* tree = (t_tree *)mCalloc(1,sizeof(t_tree )); */
/* tree->t_edges = (t_edge **)mCalloc(2*n_otu-3,sizeof(t_edge *)); */
/* tree->t_nodes = (t_node **)mCalloc(2*n_otu-2,sizeof(t_node *)); */
/* tree->n_otu = n_otu; */
/* For(i,2*n_otu-3) */
/* tree->t_edges[i] = Make_Edge_Light(NULL,NULL,i); */
/* For(i,2*n_otu-2) */
/* tree->t_nodes[i] = Make_Node_Light(i); */
/* return tree; */
/* } */
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
int Sort_Phydbl_Decrease(const void *a, const void *b)
{
if((*(phydbl *)(a)) >= (*(phydbl *)(b))) return -1;
else return 1;
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void Qksort_Int(int *A, int *B, int ilo, int ihi)
{
phydbl pivot; // pivot value for partitioning array
int ulo, uhi; // indices at ends of unpartitioned region
int ieq; // least index of array entry with value equal to pivot
int tempEntry; // temporary entry used for swapping
if (ilo >= ihi) {
return;
}
// Select a pivot value.
pivot = A[(ilo + ihi)/2];
// Initialize ends of unpartitioned region and least index of entry
// with value equal to pivot.
ieq = ulo = ilo;
uhi = ihi;
// While the unpartitioned region is not empty, try to reduce its size.
while (ulo <= uhi) {
if (A[uhi] > pivot) {
// Here, we can reduce the size of the unpartitioned region and
// try again.
uhi--;
} else {
// Here, A[uhi] <= pivot, so swap entries at indices ulo and
// uhi.
tempEntry = A[ulo];
A[ulo] = A[uhi];
A[uhi] = tempEntry;
if(B)
{
tempEntry = B[ulo];
B[ulo] = B[uhi];
B[uhi] = tempEntry;
}
// After the swap, A[ulo] <= pivot.
if (A[ulo] < pivot) {
// Swap entries at indices ieq and ulo.
tempEntry = A[ieq];
A[ieq] = A[ulo];
A[ulo] = tempEntry;
if(B)
{
tempEntry = B[ieq];
B[ieq] = B[ulo];
B[ulo] = tempEntry;
}
// After the swap, A[ieq] < pivot, so we need to change
// ieq.
ieq++;
// We also need to change ulo, but we also need to do
// that when A[ulo] = pivot, so we do it after this if
// statement.
}
// Once again, we can reduce the size of the unpartitioned
// region and try again.
ulo++;
}
}
// Now, all entries from index ilo to ieq - 1 are less than the pivot
// and all entries from index uhi to ihi + 1 are greater than the
// pivot. So we have two regions of the array that can be sorted
// recursively to put all of the entries in order.
Qksort_Int(A, B, ilo, ieq - 1);
Qksort_Int(A, B, uhi + 1, ihi);
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
/* Sort in ascending order. Elements in B (if provided) are also re-ordered according to the ordering of A */
void Qksort(phydbl *A, phydbl *B, int ilo, int ihi)
{
phydbl pivot; // pivot value for partitioning array
int ulo, uhi; // indices at ends of unpartitioned region
int ieq; // least index of array entry with value equal to pivot
phydbl tempEntry; // temporary entry used for swapping
if (ilo >= ihi) {
return;
}
// Select a pivot value.
pivot = A[(ilo + ihi)/2];
// Initialize ends of unpartitioned region and least index of entry
// with value equal to pivot.
ieq = ulo = ilo;
uhi = ihi;
// While the unpartitioned region is not empty, try to reduce its size.
while (ulo <= uhi) {
if (A[uhi] > pivot) {
// Here, we can reduce the size of the unpartitioned region and
// try again.
uhi--;
} else {
// Here, A[uhi] <= pivot, so swap entries at indices ulo and
// uhi.
tempEntry = A[ulo];
A[ulo] = A[uhi];
A[uhi] = tempEntry;
if(B)
{
tempEntry = B[ulo];
B[ulo] = B[uhi];
B[uhi] = tempEntry;
}
// After the swap, A[ulo] <= pivot.
if (A[ulo] < pivot) {
// Swap entries at indices ieq and ulo.
tempEntry = A[ieq];
A[ieq] = A[ulo];
A[ulo] = tempEntry;
if(B)
{
tempEntry = B[ieq];
B[ieq] = B[ulo];
B[ulo] = tempEntry;
}
// After the swap, A[ieq] < pivot, so we need to change
// ieq.
ieq++;
// We also need to change ulo, but we also need to do
// that when A[ulo] = pivot, so we do it after this if
// statement.
}
// Once again, we can reduce the size of the unpartitioned
// region and try again.
ulo++;
}
}
// Now, all entries from index ilo to ieq - 1 are less than the pivot
// and all entries from index uhi to ihi + 1 are greater than the
// pivot. So we have two regions of the array that can be sorted
// recursively to put all of the entries in order.
Qksort(A, B, ilo, ieq - 1);
Qksort(A, B, uhi + 1, ihi);
}
/********************************************************/
void Qksort_Matrix(phydbl **A, int col, int ilo, int ihi)
{
phydbl pivot; // pivot value for partitioning array
int ulo, uhi; // indices at ends of unpartitioned region
int ieq; // least index of array entry with value equal to pivot
phydbl *tempEntry; // temporary entry used for swapping
tempEntry = NULL;
if (ilo >= ihi) {
return;
}
// Select a pivot value.
pivot = A[(ilo + ihi)/2][col];
// Initialize ends of unpartitioned region and least index of entry
// with value equal to pivot.
ieq = ulo = ilo;
uhi = ihi;
// While the unpartitioned region is not empty, try to reduce its size.
while (ulo <= uhi) {
if (A[uhi][col] > pivot) {
// Here, we can reduce the size of the unpartitioned region and
// try again.
uhi--;
} else {
// Here, A[uhi] <= pivot, so swap entries at indices ulo and
// uhi.
tempEntry = A[ulo];
A[ulo] = A[uhi];
A[uhi] = tempEntry;
// After the swap, A[ulo] <= pivot.
if (A[ulo][col] < pivot) {
// Swap entries at indices ieq and ulo.
tempEntry = A[ieq];
A[ieq] = A[ulo];
A[ulo] = tempEntry;
// After the swap, A[ieq] < pivot, so we need to change
// ieq.
ieq++;
// We also need to change ulo, but we also need to do
// that when A[ulo] = pivot, so we do it after this if
// statement.
}
// Once again, we can reduce the size of the unpartitioned
// region and try again.
ulo++;
}
}
// Now, all entries from index ilo to ieq - 1 are less than the pivot
// and all entries from index uhi to ihi + 1 are greater than the
// pivot. So we have two regions of the array that can be sorted
// recursively to put all of the entries in order.
Qksort_Matrix(A, col, ilo, ieq - 1);
Qksort_Matrix(A, col, uhi + 1, ihi);
}
/********************************************************/
void Print_Site(calign *cdata, int num, int n_otu, char *sep, int stepsize)
{
int i,j;
For(i,n_otu)
{
PhyML_Printf("%s ",cdata->c_seq[i]->name);
For(j,stepsize)
PhyML_Printf("%c",cdata->c_seq[i]->state[num+j]);
PhyML_Printf("%s",sep);
}
PhyML_Fprintf(stderr,"%s",sep);
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void Print_Site_Lk(t_tree *tree, FILE *fp)
{
int site;
int catg;
char *s;
phydbl postmean;
if(!tree->io->print_site_lnl)
{
PhyML_Printf("\n. Err in file %s at line %d\n",__FILE__,__LINE__);
Warn_And_Exit("");
}
if(!tree->io->print_trace)
{
s = (char *)mCalloc(T_MAX_LINE,sizeof(char));
PhyML_Fprintf(fp,"Note : P(D|M) is the probability of site D given the model M (i.e., the site likelihood)\n");
if(tree->mod->n_catg > 1 || tree->mod->invar)
PhyML_Fprintf(fp,"P(D|M,rr[x]) is the probability of site D given the model M and the relative rate\nof evolution rr[x], where x is the class of rate to be considered.\nWe have P(D|M) = \\sum_x P(x) x P(D|M,rr[x]).\n");
PhyML_Fprintf(fp,"\n\n");
sprintf(s,"Site");
PhyML_Fprintf(fp, "%-7s",s);
sprintf(s,"P(D|M)");
PhyML_Fprintf(fp,"%-16s",s);
if(tree->mod->n_catg > 1)
{
For(catg,tree->mod->n_catg)
{
sprintf(s,"P(D|M,rr[%d]=%5.4f)",catg+1,tree->mod->gamma_rr->v[catg]);
PhyML_Fprintf(fp,"%-22s",s);
}
sprintf(s,"Posterior mean");
PhyML_Fprintf(fp,"%-22s",s);
}
if(tree->mod->invar)
{
sprintf(s,"P(D|M,rr[0]=0)");
PhyML_Fprintf(fp,"%-16s",s);
}
PhyML_Fprintf(fp,"\n");
For(site,tree->data->init_len)
{
PhyML_Fprintf(fp,"%-7d",site+1);
PhyML_Fprintf(fp,"%-16g",(phydbl)EXP(tree->cur_site_lk[tree->data->sitepatt[site]]));
if(tree->mod->n_catg > 1)
{
For(catg,tree->mod->n_catg)
PhyML_Fprintf(fp,"%-22g",(phydbl)EXP(tree->log_site_lk_cat[catg][tree->data->sitepatt[site]]));
postmean = .0;
For(catg,tree->mod->n_catg)
postmean +=
tree->mod->gamma_rr->v[catg] *
EXP(tree->log_site_lk_cat[catg][tree->data->sitepatt[site]]) *
tree->mod->gamma_r_proba->v[catg];
postmean /= EXP(tree->cur_site_lk[tree->data->sitepatt[site]]);
PhyML_Fprintf(fp,"%-22g",postmean);
}
if(tree->mod->invar)
{
if((phydbl)tree->data->invar[tree->data->sitepatt[site]] > -0.5)
PhyML_Fprintf(fp,"%-16g",tree->mod->pi->v[tree->data->invar[tree->data->sitepatt[site]]]);
else
PhyML_Fprintf(fp,"%-16g",0.0);
}
PhyML_Fprintf(fp,"\n");
}
Free(s);
}
else
{
For(site,tree->data->init_len)
PhyML_Fprintf(fp,"%.2f\t",tree->cur_site_lk[tree->data->sitepatt[site]]);
PhyML_Fprintf(fp,"\n");
}
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void Print_Seq(align **data, int n_otu)
{
int i,j;
PhyML_Printf("%d\t%d\n",n_otu,data[0]->len);
For(i,n_otu)
{
For(j,20)
{
if(j<(int)strlen(data[i]->name))
putchar(data[i]->name[j]);
else putchar(' ');
}
/* PhyML_Printf("%10d ",i); */
For(j,data[i]->len)
{
PhyML_Printf("%c",data[i]->state[j]);
}
PhyML_Printf("\n");
}
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void Print_CSeq(FILE *fp, int compressed, calign *cdata)
{
int i,j;
int n_otu;
n_otu = cdata->n_otu;
if(cdata->format == 0)
{
PhyML_Fprintf(fp,"%d\t%d\n",n_otu,cdata->init_len);
}
else
{
PhyML_Fprintf(fp,"#NEXUS\n");
PhyML_Fprintf(fp,"begin data\n");
PhyML_Fprintf(fp,"dimensions ntax=%d nchar=%d;\n",n_otu,cdata->init_len);
PhyML_Fprintf(fp,"format sequential datatype=dna;\n");
PhyML_Fprintf(fp,"matrix\n");
}
For(i,n_otu)
{
For(j,50)
{
if(j<(int)strlen(cdata->c_seq[i]->name))
fputc(cdata->c_seq[i]->name[j],fp);
else fputc(' ',fp);
}
if(compressed == YES) /* Print out compressed sequences */
PhyML_Fprintf(fp,"%s",cdata->c_seq[i]->state);
else /* Print out uncompressed sequences */
{
For(j,cdata->init_len)
{
PhyML_Fprintf(fp,"%c",cdata->c_seq[i]->state[cdata->sitepatt[j]]);
}
}
PhyML_Fprintf(fp,"\n");
}
PhyML_Fprintf(fp,"\n");
if(cdata->format == 1)
{
PhyML_Fprintf(fp,";\n");
PhyML_Fprintf(fp,"END;\n");
}
/* PhyML_Printf("\t"); */
/* For(j,cdata->crunch_len) */
/* PhyML_Printf("%.0f ",cdata->wght[j]); */
/* PhyML_Printf("\n"); */
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void Print_CSeq_Select(FILE *fp, int compressed, calign *cdata, t_tree *tree)
{
int i,j;
int n_otu;
phydbl eps;
int slice = 14;
eps = 1.E-6;
n_otu = 0;
For(i,cdata->n_otu)
if(tree->rates->nd_t[i] < tree->rates->time_slice_lims[slice] + eps)
n_otu++;
PhyML_Fprintf(fp,"%d\t%d\n",n_otu,cdata->init_len);
n_otu = cdata->n_otu;
For(i,n_otu)
{
if(tree->rates->nd_t[i] < tree->rates->time_slice_lims[slice] + eps)
{
For(j,50)
{
if(j<(int)strlen(cdata->c_seq[i]->name))
fputc(cdata->c_seq[i]->name[j],fp);
else fputc(' ',fp);
}
if(compressed == YES) /* Print out compressed sequences */
PhyML_Fprintf(fp,"%s",cdata->c_seq[i]->state);
else /* Print out uncompressed sequences */
{
For(j,cdata->init_len)
{
PhyML_Fprintf(fp,"%c",cdata->c_seq[i]->state[cdata->sitepatt[j]]);
}
}
PhyML_Fprintf(fp,"\n");
}
}
if(cdata->format == 1)
{
PhyML_Fprintf(fp,";\n");
PhyML_Fprintf(fp,"END;\n");
}
/* PhyML_Printf("\t"); */
/* For(j,cdata->crunch_len) */
/* PhyML_Printf("%.0f ",cdata->wght[j]); */
/* PhyML_Printf("\n"); */
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void Order_Tree_Seq(t_tree *tree, align **data)
{
int i,j,n_otu;
align *buff;
n_otu = tree->n_otu;
For(i,n_otu)
{
For(j,n_otu)
{
if(!strcmp(tree->t_nodes[i]->name,data[j]->name))
break;
}
buff = data[j];
data[j] = data[i];
data[i] = buff;
}
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
char *Add_Taxa_To_Constraint_Tree(FILE *fp, calign *cdata)
{
char *line,*long_line;
t_tree *tree;
int i,j;
rewind(fp);
line = Return_Tree_String_Phylip(fp);
tree = Read_Tree(&line);
long_line = (char *)mCalloc(T_MAX_LINE,sizeof(char));
strcpy(long_line,line);
long_line[strlen(line)-1] = '\0';
For(i,cdata->n_otu)
{
For(j,tree->n_otu)
{
if(!strcmp(tree->t_nodes[j]->name,cdata->c_seq[i]->name))
break;
}
if(j == tree->n_otu)
{
strcat(long_line,",");
strcat(long_line,cdata->c_seq[i]->name);
}
}
strcat(long_line,");");
Free_Tree(tree);
Free(line);
return long_line;
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void Check_Constraint_Tree_Taxa_Names(t_tree *tree, calign *cdata)
{
int i,j,n_otu_tree,n_otu_cdata;
n_otu_tree = tree->n_otu;
n_otu_cdata = cdata->n_otu;
For(i,n_otu_tree)
{
For(j,n_otu_cdata)
{
if(!strcmp(tree->t_nodes[i]->name,cdata->c_seq[j]->name))
break;
}
if(j==n_otu_cdata)
{
PhyML_Printf("\n. Err: '%s' is not found in sequence data set\n",tree->t_nodes[i]->name);
Warn_And_Exit("");
}
}
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void Order_Tree_CSeq(t_tree *tree, calign *cdata)
{
int i,j,n_otu_tree,n_otu_cdata;
align *buff;
n_otu_tree = tree->n_otu;
n_otu_cdata = cdata->n_otu;
if((n_otu_tree != n_otu_cdata) && (tree->io->fp_in_constraint_tree == NULL))
{
PhyML_Printf("\n. Number of taxa in the tree: %d, number of sequences: %d.",n_otu_tree,n_otu_cdata);
Warn_And_Exit("\n. The number of tips in the tree is not the same as the number of sequences\n");
}
For(i,MAX(n_otu_tree,n_otu_cdata))
{
For(j,MIN(n_otu_tree,n_otu_cdata))
{
if(!strcmp(tree->t_nodes[i]->name,cdata->c_seq[j]->name))
break;
}
if(j==MIN(n_otu_tree,n_otu_cdata))
{
PhyML_Printf("\n. Err: '%s' is not found in sequence data set\n",tree->t_nodes[i]->name);
Warn_And_Exit("");
}
buff = cdata->c_seq[j];
cdata->c_seq[j] = cdata->c_seq[i];
cdata->c_seq[i] = buff;
}
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
matrix *Make_Mat(int n_otu)
{
matrix *mat;
int i;
mat = (matrix *)mCalloc(1,sizeof(matrix));
mat->n_otu = n_otu;
mat->P = (phydbl **)mCalloc(n_otu,sizeof(phydbl *));
mat->Q = (phydbl **)mCalloc(n_otu,sizeof(phydbl *));
mat->dist = (phydbl **)mCalloc(n_otu,sizeof(phydbl *));
mat->on_off = (int *)mCalloc(n_otu,sizeof(int));
mat->name = (char **)mCalloc(n_otu,sizeof(char *));
mat->tip_node = (t_node **)mCalloc(n_otu,sizeof(t_node *));
For(i,n_otu)
{
mat->P[i] = (phydbl *)mCalloc(n_otu,sizeof(phydbl));
mat->Q[i] = (phydbl *)mCalloc(n_otu,sizeof(phydbl));
mat->dist[i] = (phydbl *)mCalloc(n_otu,sizeof(phydbl));
mat->name[i] = (char *)mCalloc(T_MAX_NAME,sizeof(char));
}
return mat;
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void Init_Mat(matrix *mat, calign *data)
{
int i;
mat->n_otu = data->n_otu;
mat->r = mat->n_otu;
mat->curr_int = mat->n_otu;
mat->method = 1;
For(i,data->n_otu)
{
strcpy(mat->name[i],data->c_seq[i]->name);
mat->on_off[i] = 1;
}
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
t_tree *Make_Tree_From_Scratch(int n_otu, calign *data)
{
t_tree *tree;
tree = Make_Tree(n_otu);
Init_Tree(tree,n_otu);
Make_All_Tree_Nodes(tree);
Make_All_Tree_Edges(tree);
Make_Tree_Path(tree);
if(data)
{
Copy_Tax_Names_To_Tip_Labels(tree,data);
tree->data = data;
}
return tree;
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
t_tree *Make_Tree(int n_otu)
{
t_tree *tree;
tree = (t_tree *)mCalloc(1,sizeof(t_tree ));
tree->t_dir = (short int *)mCalloc((2*n_otu-2)*(2*n_otu-2),sizeof(int));
return tree;
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void Make_Tree_Path(t_tree *tree)
{
tree->curr_path = (t_node **)mCalloc(tree->n_otu,sizeof(t_node *));
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void Make_All_Tree_Nodes(t_tree *tree)
{
int i;
tree->t_nodes = (t_node **)mCalloc(2*tree->n_otu-1,sizeof(t_node *));
For(i,2*tree->n_otu-1)
{
tree->t_nodes[i] = (t_node *)Make_Node_Light(i);
if(i < tree->n_otu) tree->t_nodes[i]->tax = 1;
else tree->t_nodes[i]->tax = 0;
}
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void Make_All_Tree_Edges(t_tree *tree)
{
int i;
tree->t_edges = (t_edge **)mCalloc(2*tree->n_otu-2,sizeof(t_edge *));
For(i,2*tree->n_otu-2) tree->t_edges[i] = (t_edge *)Make_Edge_Light(NULL,NULL,i);
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void Copy_Tax_Names_To_Tip_Labels(t_tree *tree, calign *data)
{
int i;
For(i,tree->n_otu)
{
tree->t_nodes[i]->name = (char *)mCalloc((int)strlen(data->c_seq[i]->name)+1,sizeof(char));
tree->t_nodes[i]->ori_name = tree->t_nodes[i]->name;
strcpy(tree->t_nodes[i]->name,data->c_seq[i]->name);
tree->t_nodes[i]->tax = 1;
tree->t_nodes[i]->num = i;
}
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void Print_Dist(matrix *mat)
{
int i,j;
For(i,mat->n_otu)
{
PhyML_Printf("%s ",mat->name[i]);
For(j,mat->n_otu)
PhyML_Printf("%9.6f ",mat->dist[i][j]);
PhyML_Printf("\n");
}
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void Print_Node(t_node *a, t_node *d, t_tree *tree)
{
int i;
int dir;
dir = -1;
For(i,3) if(a->v[i] == d) {dir = i; break;}
PhyML_Printf("Node nums = %3d %3d (dir=%d);",a->num,d->num,dir);
PhyML_Printf("Node names = '%s' '%s' ; ",a->name,d->name);
For(i,3) if(a->v[i] == d)
{
if(a->b[i])
{
PhyML_Printf("Branch num = %3d%c (%d %d) %f",
a->b[i]->num,a->b[i]==tree->e_root?'*':' ',a->b[i]->left->num,
a->b[i]->rght->num,a->b[i]->l);
if(a->b[i]->left->tax) PhyML_Printf(" WARNING LEFT->TAX!");
break;
}
}
PhyML_Printf("\n");
if(d->tax) return;
else
For(i,3)
if(d->v[i] != a) Print_Node(d,d->v[i],tree);
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void Share_Lk_Struct(t_tree *t_full, t_tree *t_empt)
{
int i,j,n_otu;
t_edge *b_e,*b_f;
t_node *n_e, *n_f;
n_otu = t_full->n_otu;
t_empt->n_root = t_full->n_root;
t_empt->e_root = t_full->e_root;
t_empt->c_lnL_sorted = t_full->c_lnL_sorted;
t_empt->log_site_lk_cat = t_full->log_site_lk_cat;
t_empt->cur_site_lk = t_full->cur_site_lk;
t_empt->old_site_lk = t_full->old_site_lk;
t_empt->triplet_struct = t_full->triplet_struct;
t_empt->log_lks_aLRT = t_full->log_lks_aLRT;
t_empt->site_lk_cat = t_full->site_lk_cat;
For(i,2*n_otu-3)
{
b_f = t_full->t_edges[i];
b_e = t_empt->t_edges[i];
b_e->Pij_rr = b_f->Pij_rr;
b_e->nni = b_f->nni;
}
for(i=n_otu;i<2*n_otu-2;i++)
{
n_f = t_full->t_nodes[i];
n_e = t_empt->t_nodes[i];
For(j,3)
{
if(n_f->b[j]->left == n_f)
{
if(n_e->b[j]->left == n_e)
{
n_e->b[j]->p_lk_left = n_f->b[j]->p_lk_left;
n_e->b[j]->p_lk_loc_left = n_f->b[j]->p_lk_loc_left;
n_e->b[j]->patt_id_left = n_f->b[j]->patt_id_left;
n_e->b[j]->sum_scale_left = n_f->b[j]->sum_scale_left;
n_e->b[j]->sum_scale_left_cat = n_f->b[j]->sum_scale_left_cat;
n_e->b[j]->p_lk_tip_l = n_f->b[j]->p_lk_tip_l;
}
else
{
n_e->b[j]->p_lk_rght = n_f->b[j]->p_lk_left;
n_e->b[j]->p_lk_loc_rght = n_f->b[j]->p_lk_loc_left;
n_e->b[j]->patt_id_rght = n_f->b[j]->patt_id_left;
n_e->b[j]->sum_scale_rght = n_f->b[j]->sum_scale_left;
n_e->b[j]->sum_scale_rght_cat = n_f->b[j]->sum_scale_left_cat;
n_e->b[j]->p_lk_tip_r = n_f->b[j]->p_lk_tip_l;
}
}
else
{
if(n_e->b[j]->rght == n_e)
{
n_e->b[j]->p_lk_rght = n_f->b[j]->p_lk_rght;
n_e->b[j]->p_lk_loc_rght = n_f->b[j]->p_lk_loc_rght;
n_e->b[j]->patt_id_rght = n_f->b[j]->patt_id_rght;
n_e->b[j]->sum_scale_rght = n_f->b[j]->sum_scale_rght;
n_e->b[j]->sum_scale_rght_cat = n_f->b[j]->sum_scale_rght_cat;
n_e->b[j]->p_lk_tip_r = n_f->b[j]->p_lk_tip_r;
}
else
{
n_e->b[j]->p_lk_left = n_f->b[j]->p_lk_rght;
n_e->b[j]->p_lk_loc_left = n_f->b[j]->p_lk_loc_rght;
n_e->b[j]->patt_id_left = n_f->b[j]->patt_id_rght;
n_e->b[j]->sum_scale_left = n_f->b[j]->sum_scale_rght;
n_e->b[j]->sum_scale_left_cat = n_f->b[j]->sum_scale_rght_cat;
n_e->b[j]->p_lk_tip_l = n_f->b[j]->p_lk_tip_r;
}
}
}
}
For(i,n_otu)
{
n_f = t_full->t_nodes[i];
n_e = t_empt->t_nodes[i];
if(n_f->b[0]->rght == n_f)
{
n_e->b[0]->p_lk_rght = n_f->b[0]->p_lk_rght;
n_e->b[0]->p_lk_loc_rght = n_f->b[0]->p_lk_loc_rght;
n_e->b[0]->patt_id_rght = n_f->b[0]->patt_id_rght;
n_e->b[0]->sum_scale_rght = n_f->b[0]->sum_scale_rght;
n_e->b[0]->sum_scale_rght_cat = n_f->b[0]->sum_scale_rght_cat;
n_e->b[0]->p_lk_tip_r = n_f->b[0]->p_lk_tip_r;
}
else
{
PhyML_Printf("\n. Err in file %s at line %d\n",__FILE__,__LINE__);
Warn_And_Exit("");
}
}
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void Share_Spr_Struct(t_tree *t_full, t_tree *t_empt)
{
t_empt->size_spr_list = t_full->size_spr_list;
t_empt->spr_list = t_full->spr_list;
t_empt->best_spr = t_full->best_spr;
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void Share_Pars_Struct(t_tree *t_full, t_tree *t_empt)
{
int i;
t_empt->site_pars = t_full->site_pars;
t_empt->step_mat = t_full->step_mat;
For(i,2*t_full->n_otu-3)
{
t_empt->t_edges[i]->ui_l = t_full->t_edges[i]->ui_l;
t_empt->t_edges[i]->ui_r = t_full->t_edges[i]->ui_r;
t_empt->t_edges[i]->pars_l = t_full->t_edges[i]->pars_l;
t_empt->t_edges[i]->pars_r = t_full->t_edges[i]->pars_r;
t_empt->t_edges[i]->p_pars_l = t_full->t_edges[i]->p_pars_l;
t_empt->t_edges[i]->p_pars_r = t_full->t_edges[i]->p_pars_r;
}
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void Print_Model(model *mod)
{
int i,j,k;
PhyML_Printf("\n. name=%s",mod->modelname);
PhyML_Printf("\n. string=%s",mod->custom_mod_string);
PhyML_Printf("\n. mod_num=%d",mod->mod_num);
PhyML_Printf("\n. ns=%d",mod->ns);
PhyML_Printf("\n. n_catg=%d",mod->n_catg);
PhyML_Printf("\n. kappa=%f",mod->kappa->v);
PhyML_Printf("\n. alpha=%f",mod->alpha->v);
PhyML_Printf("\n. lambda=%f",mod->lambda->v);
PhyML_Printf("\n. pinvar=%f",mod->pinvar->v);
PhyML_Printf("\n. br_len_multiplier=%f",mod->br_len_multiplier->v);
PhyML_Printf("\n. whichmodel=%d",mod->whichmodel);
PhyML_Printf("\n. update_eigen=%d",mod->update_eigen);
PhyML_Printf("\n. bootstrap=%d",mod->bootstrap);
PhyML_Printf("\n. n_diff_rr=%d",mod->n_diff_rr);
PhyML_Printf("\n. invar=%d",mod->invar);
PhyML_Printf("\n. use_m4mod=%d",mod->use_m4mod);
PhyML_Printf("\n. gamma_median=%d",mod->gamma_median);
PhyML_Printf("\n. state_len=%d",mod->state_len);
PhyML_Printf("\n. log_l=%d",mod->log_l);
PhyML_Printf("\n. l_min=%f",mod->l_min);
PhyML_Printf("\n. l_max=%f",mod->l_max);
PhyML_Printf("\n. free_mixt_rates=%d",mod->free_mixt_rates);
PhyML_Printf("\n. gamma_mgf_bl=%d",mod->gamma_mgf_bl);
PhyML_Printf("\n. Pi\n");
For(i,mod->ns) PhyML_Printf(" %f ",mod->pi->v[i]);
PhyML_Printf("\n");
For(i,mod->ns) PhyML_Printf(" %f ",mod->pi_unscaled->v[i]);
PhyML_Printf("\n. Rates\n");
For(i,mod->n_catg) PhyML_Printf(" %f ",mod->gamma_r_proba->v[i]);
PhyML_Printf("\n");
For(i,mod->n_catg) PhyML_Printf(" %f ",mod->gamma_r_proba_unscaled->v[i]);
PhyML_Printf("\n");
For(i,mod->n_catg) PhyML_Printf(" %f ",mod->gamma_rr->v[i]);
PhyML_Printf("\n");
For(i,mod->n_catg) PhyML_Printf(" %f ",mod->gamma_rr_unscaled->v[i]);
PhyML_Printf("\n. Qmat \n");
if(mod->whichmodel == CUSTOM)
{
fflush(NULL);
For(i,6) {PhyML_Printf(" %12f ",mod->rr->v[i]); fflush(NULL);}
For(i,6) {PhyML_Printf(" %12f ",mod->rr_val->v[i]); fflush(NULL);}
For(i,6) {PhyML_Printf(" %12d ",mod->rr_num->v[i]); fflush(NULL);}
For(i,6) {PhyML_Printf(" %12d ",mod->n_rr_per_cat->v[i]); fflush(NULL);}
}
For(i,mod->ns)
{
PhyML_Printf(" ");
For(j,4)
PhyML_Printf("%8.5f ",mod->qmat->v[i*4+j]);
PhyML_Printf("\n");
}
PhyML_Printf("\n. Freqs");
PhyML_Printf("\n");
For(i,mod->ns) PhyML_Printf(" %12f ",mod->user_b_freq->v[i]);
PhyML_Printf("\n");
For(i,mod->ns) PhyML_Printf(" %12f ",mod->pi->v[i]);
PhyML_Printf("\n");
For(i,mod->ns) PhyML_Printf(" %12f ",mod->pi_unscaled->v[i]);
PhyML_Printf("\n. Eigen\n");
For(i,2*mod->ns) PhyML_Printf(" %f ",mod->eigen->space[i]);
PhyML_Printf("\n");
For(i,2*mod->ns) PhyML_Printf(" %f ",mod->eigen->space_int[i]);
PhyML_Printf("\n");
For(i,mod->ns) PhyML_Printf(" %f ",mod->eigen->e_val[i]);
PhyML_Printf("\n");
For(i,mod->ns) PhyML_Printf(" %f ",mod->eigen->e_val_im[i]);
PhyML_Printf("\n");
For(i,mod->ns*mod->ns) PhyML_Printf(" %f ",mod->eigen->r_e_vect[i]);
PhyML_Printf("\n");
For(i,mod->ns*mod->ns) PhyML_Printf(" %f ",mod->eigen->r_e_vect[i]);
PhyML_Printf("\n");
For(i,mod->ns*mod->ns) PhyML_Printf(" %f ",mod->eigen->r_e_vect_im[i]);
PhyML_Printf("\n");
For(i,mod->ns*mod->ns) PhyML_Printf(" %f ",mod->eigen->l_e_vect[i]);
PhyML_Printf("\n");
For(i,mod->ns*mod->ns) PhyML_Printf(" %f ",mod->eigen->q[i]);
PhyML_Printf("\n");
PhyML_Printf("\n. Pij");
For(k,mod->n_catg)
{
PMat(0.01*mod->gamma_rr->v[k],mod,mod->ns*mod->ns*k,mod->Pij_rr->v);
PhyML_Printf("\n. l=%f\n",0.01*mod->gamma_rr->v[k]);
For(i,mod->ns)
{
PhyML_Printf(" ");
For(j,mod->ns)
PhyML_Printf("%8.5f ",mod->Pij_rr->v[k*mod->ns*mod->ns+i*mod->ns+j]);
PhyML_Printf("\n");
}
}
PhyML_Printf("\n");
fflush(NULL);
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void Print_Mat(matrix *mat)
{
int i,j;
PhyML_Printf("%d",mat->n_otu);
PhyML_Printf("\n");
For(i,mat->n_otu)
{
For(j,13)
{
if(j>=(int)strlen(mat->name[i])) putchar(' ');
else putchar(mat->name[i][j]);
}
For(j,mat->n_otu)
{
char s[2]="-";
if(mat->dist[i][j] < .0)
PhyML_Printf("%12s",s);
else
PhyML_Printf("%12f",mat->dist[i][j]);
}
PhyML_Printf("\n");
}
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
int Sort_Edges_NNI_Score(t_tree *tree, t_edge **sorted_edges, int n_elem)
{
int i,j;
t_edge *buff;
For(i,n_elem-1)
{
for(j=i+1;jnni->score < sorted_edges[i]->nni->score)
{
buff = sorted_edges[j];
sorted_edges[j] = sorted_edges[i];
sorted_edges[i] = buff;
}
}
}
return 1;
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
int Sort_Edges_Depth(t_tree *tree, t_edge **sorted_edges, int n_elem)
{
int i,j;
t_edge *buff;
phydbl *depth,buff_depth;
depth = (phydbl *)mCalloc(n_elem,sizeof(phydbl));
For(i,n_elem)
depth[i] =
sorted_edges[i]->left->bip_size[sorted_edges[i]->l_r] *
sorted_edges[i]->rght->bip_size[sorted_edges[i]->r_l] ;
For(i,n_elem-1)
{
for(j=i+1;j depth[j])
{
buff = sorted_edges[i];
sorted_edges[i] = sorted_edges[j];
sorted_edges[j] = buff;
buff_depth = depth[i];
depth[i] = depth[j];
depth[j] = buff_depth;
}
}
}
Free(depth);
return 1;
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void NNI(t_tree *tree, t_edge *b_fcus, int do_swap)
{
int l_r, r_l, l_v1, l_v2, r_v3, r_v4;
t_node *v1,*v2,*v3,*v4;
phydbl lk0, lk1, lk2;
phydbl lk0_init, lk1_init, lk2_init;
phydbl bl_init;
phydbl l0,l1,l2;
phydbl l_infa, l_infb, l_max;
/* phydbl lk_infa, lk_infb, lk_max; */
phydbl lk_init;
bl_init = b_fcus->l;
lk_init = tree->c_lnL;
b_fcus->nni->init_l = b_fcus->l;
b_fcus->nni->init_lk = tree->c_lnL;;
b_fcus->nni->best_conf = 0;
b_fcus->nni->score = +1.0;
lk0 = lk1 = lk2 = UNLIKELY;
v1 = v2 = v3 = v4 = NULL;
l_r = r_l = l_v1 = l_v2 = r_v3 = r_v4 = -1;
l_r = b_fcus->l_r;
r_l = b_fcus->r_l;
v1 = b_fcus->left->v[b_fcus->l_v1];
v2 = b_fcus->left->v[b_fcus->l_v2];
v3 = b_fcus->rght->v[b_fcus->r_v1];
v4 = b_fcus->rght->v[b_fcus->r_v2];
Record_Br_Len(tree);
if(v1->num < v2->num)
{
PhyML_Printf("\n. Err in file %s at line %d\n",__FILE__,__LINE__);
Warn_And_Exit("");
}
if(v3->num < v4->num)
{
PhyML_Printf("\n. Err in file %s at line %d\n",__FILE__,__LINE__);
Warn_And_Exit("");
}
l0 = l1 = l2 = -1.;
/***********/
Swap(v2,b_fcus->left,b_fcus->rght,v3,tree);
tree->both_sides = 1;
tree->update_alias_subpatt = YES;
lk1_init = Update_Lk_At_Given_Edge(b_fcus,tree);
tree->update_alias_subpatt = NO;
l_infa = 10.*b_fcus->l;
l_max = b_fcus->l;
l_infb = tree->mod->l_min;
if(tree->mod->s_opt->fast_nni)
{
Fast_Br_Len(b_fcus,tree,1);
lk1 = Lk_At_Given_Edge(b_fcus,tree);
}
else
{
lk1 = Br_Len_Brent(l_infa,l_max,l_infb,
tree->mod->s_opt->min_diff_lk_local,
b_fcus,tree,
tree->mod->s_opt->brent_it_max,
tree->mod->s_opt->quickdirty);
}
if(lk1 < lk1_init - tree->mod->s_opt->min_diff_lk_local)
{
PhyML_Printf("%f %f %f %G\n",l_infa,l_max,l_infb,b_fcus->l);
PhyML_Printf("%f -- %f \n",lk1_init,lk1);
PhyML_Printf("\n. Err. in NNI (1)\n");
}
l1 = b_fcus->l;
Swap(v3,b_fcus->left,b_fcus->rght,v2,tree);
/***********/
/***********/
Swap(v2,b_fcus->left,b_fcus->rght,v4,tree);
Restore_Br_Len(tree);
/* b_fcus->l = bl_init; */
tree->both_sides = 1;
tree->update_alias_subpatt = YES;
lk2_init = Update_Lk_At_Given_Edge(b_fcus,tree);
tree->update_alias_subpatt = NO;
l_infa = 10.*b_fcus->l;
l_max = b_fcus->l;
l_infb = tree->mod->l_min;
if(tree->mod->s_opt->fast_nni)
{
Fast_Br_Len(b_fcus,tree,1);
lk2 = Lk_At_Given_Edge(b_fcus,tree);
}
else
{
lk2 = Br_Len_Brent(l_infa,l_max,l_infb,
tree->mod->s_opt->min_diff_lk_local,
b_fcus,tree,
tree->mod->s_opt->brent_it_max,
tree->mod->s_opt->quickdirty);
}
if(lk2 < lk2_init - tree->mod->s_opt->min_diff_lk_local)
{
PhyML_Printf("%f %f %f %G\n",l_infa,l_max,l_infb,b_fcus->l);
PhyML_Printf("%f -- %f \n",lk2_init,lk2);
PhyML_Printf("\n. Err. in NNI (2)\n");
}
l2 = b_fcus->l;
Swap(v4,b_fcus->left,b_fcus->rght,v2,tree);
/***********/
/***********/
Restore_Br_Len(tree);
/* b_fcus->l = bl_init; */
tree->both_sides = 1;
tree->update_alias_subpatt = YES;
lk0_init = Update_Lk_At_Given_Edge(b_fcus,tree);
tree->update_alias_subpatt = NO;
if(FABS(lk0_init - lk_init) > tree->mod->s_opt->min_diff_lk_local)
{
PhyML_Printf("\n. lk_init = %f; lk = %f diff = %f l = %G\n",
lk_init,
lk0_init,
lk_init-lk0_init,
b_fcus->l);
PhyML_Printf("\n. Curr_lnL = %f\n",Lk(tree));
Warn_And_Exit("\n. Err. in NNI (3)\n");
}
l_infa = 10.*b_fcus->l;
l_max = b_fcus->l;
l_infb = tree->mod->l_min;
if(tree->mod->s_opt->fast_nni)
{
Fast_Br_Len(b_fcus,tree,1);
lk0 = Lk_At_Given_Edge(b_fcus,tree);
}
else
{
lk0 = Br_Len_Brent(l_infa,l_max,l_infb,
tree->mod->s_opt->min_diff_lk_local,
b_fcus,tree,
tree->mod->s_opt->brent_it_max,
tree->mod->s_opt->quickdirty);
}
if(lk0 < lk_init - tree->mod->s_opt->min_diff_lk_local)
{
PhyML_Printf("\n. %f %f %f %f",l_infa,l_max,l_infb,b_fcus->l);
PhyML_Printf("\n. %f -- %f",lk0_init,lk0);
PhyML_Printf("\n. Err. in NNI (3)\n");
Warn_And_Exit("\n");
}
l0 = b_fcus->l;
/***********/
b_fcus->nni->lk0 = lk0;
b_fcus->nni->lk1 = lk1;
b_fcus->nni->lk2 = lk2;
b_fcus->nni->l0 = l0;
b_fcus->nni->l1 = l1;
b_fcus->nni->l2 = l2;
b_fcus->nni->score = lk0 - MAX(lk1,lk2);
if((b_fcus->nni->score < tree->mod->s_opt->min_diff_lk_local) &&
(b_fcus->nni->score > -tree->mod->s_opt->min_diff_lk_local))
{
b_fcus->nni->score = .0;
b_fcus->nni->lk1 = b_fcus->nni->lk0;
b_fcus->nni->lk2 = b_fcus->nni->lk0;
}
if(lk0 > MAX(lk1,lk2))
{
b_fcus->nni->best_conf = 0;
b_fcus->nni->best_l = l0;
b_fcus->nni->swap_node_v1 = NULL;
b_fcus->nni->swap_node_v2 = NULL;
b_fcus->nni->swap_node_v3 = NULL;
b_fcus->nni->swap_node_v4 = NULL;
}
else if(lk1 > MAX(lk0,lk2))
{
b_fcus->nni->best_conf = 1;
b_fcus->nni->best_l = l1;
b_fcus->nni->swap_node_v1 = v2;
b_fcus->nni->swap_node_v2 = b_fcus->left;
b_fcus->nni->swap_node_v3 = b_fcus->rght;
b_fcus->nni->swap_node_v4 = v3;
}
else if(lk2 > MAX(lk0,lk1))
{
b_fcus->nni->best_conf = 2;
b_fcus->nni->best_l = l2;
b_fcus->nni->swap_node_v1 = v2;
b_fcus->nni->swap_node_v2 = b_fcus->left;
b_fcus->nni->swap_node_v3 = b_fcus->rght;
b_fcus->nni->swap_node_v4 = v4;
}
else
{
b_fcus->nni->score = +1.0;
b_fcus->nni->best_conf = 0;
b_fcus->nni->best_l = l0;
b_fcus->nni->swap_node_v1 = NULL;
b_fcus->nni->swap_node_v2 = NULL;
b_fcus->nni->swap_node_v3 = NULL;
b_fcus->nni->swap_node_v4 = NULL;
}
if((do_swap) && ((lk1 > lk0) || (lk2 > lk0)))
{
tree->n_swap++;
PhyML_Printf("Swap t_edge %d -> %f\n",b_fcus->num,MAX(lk1,lk2));
if(lk1 > lk2)
{
tree->best_lnL = lk1;
Swap(v2,b_fcus->left,b_fcus->rght,v3,tree);
b_fcus->l = l1;
tree->both_sides = 1;
Lk(tree);
}
else
{
tree->best_lnL = lk2;
Swap(v2,b_fcus->left,b_fcus->rght,v4,tree);
b_fcus->l = l2;
tree->both_sides = 1;
Lk(tree);
}
}
else
{
/* b_fcus->l = bl_init; */
Restore_Br_Len(tree);
Update_PMat_At_Given_Edge(b_fcus,tree);
tree->c_lnL = lk_init;
}
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void NNI_Pars(t_tree *tree, t_edge *b_fcus, int do_swap)
{
int l_r, r_l, l_v1, l_v2, r_v3, r_v4;
t_node *v1,*v2,*v3,*v4;
int pars0, pars1, pars2;
int pars_init;
pars_init = tree->c_pars;
b_fcus->nni->best_conf = 0;
b_fcus->nni->score = +1.0;
pars0 = pars1 = pars2 = 0;
v1 = v2 = v3 = v4 = NULL;
l_r = r_l = l_v1 = l_v2 = r_v3 = r_v4 = -1;
l_r = b_fcus->l_r;
r_l = b_fcus->r_l;
v1 = b_fcus->left->v[b_fcus->l_v1];
v2 = b_fcus->left->v[b_fcus->l_v2];
v3 = b_fcus->rght->v[b_fcus->r_v1];
v4 = b_fcus->rght->v[b_fcus->r_v2];
if(v1->num < v2->num)
{
PhyML_Printf("\n. Err in file %s at line %d\n",__FILE__,__LINE__);
Warn_And_Exit("");
}
if(v3->num < v4->num)
{
PhyML_Printf("\n. Err in file %s at line %d\n",__FILE__,__LINE__);
Warn_And_Exit("");
}
/***********/
Swap(v2,b_fcus->left,b_fcus->rght,v3,tree);
tree->both_sides = 1;
pars1 = Update_Pars_At_Given_Edge(b_fcus,tree);
Swap(v3,b_fcus->left,b_fcus->rght,v2,tree);
/***********/
/***********/
Swap(v2,b_fcus->left,b_fcus->rght,v4,tree);
tree->both_sides = 1;
pars2 = Update_Pars_At_Given_Edge(b_fcus,tree);
Swap(v4,b_fcus->left,b_fcus->rght,v2,tree);
/***********/
/***********/
tree->both_sides = 1;
pars0 = Update_Pars_At_Given_Edge(b_fcus,tree);
if(pars0 != pars_init)
{
PhyML_Printf("\n. pars_init = %d; pars0 = %d\n",
pars_init,
pars0);
Warn_And_Exit("\n. Err. in NNI (3)\n");
}
/***********/
tree->c_pars = pars0;
b_fcus->nni->score = MIN(pars1,pars2) - pars0;
if(pars0 < MIN(pars1,pars2))
{
b_fcus->nni->best_conf = 0;
b_fcus->nni->swap_node_v1 = NULL;
b_fcus->nni->swap_node_v2 = NULL;
b_fcus->nni->swap_node_v3 = NULL;
b_fcus->nni->swap_node_v4 = NULL;
}
else if(pars1 < MIN(pars0,pars2))
{
b_fcus->nni->best_conf = 1;
b_fcus->nni->swap_node_v1 = v2;
b_fcus->nni->swap_node_v2 = b_fcus->left;
b_fcus->nni->swap_node_v3 = b_fcus->rght;
b_fcus->nni->swap_node_v4 = v3;
}
else if(pars2 > MIN(pars0,pars1))
{
b_fcus->nni->best_conf = 2;
b_fcus->nni->swap_node_v1 = v2;
b_fcus->nni->swap_node_v2 = b_fcus->left;
b_fcus->nni->swap_node_v3 = b_fcus->rght;
b_fcus->nni->swap_node_v4 = v4;
}
else
{
b_fcus->nni->score = +1.0;
b_fcus->nni->swap_node_v1 = NULL;
b_fcus->nni->swap_node_v2 = NULL;
b_fcus->nni->swap_node_v3 = NULL;
b_fcus->nni->swap_node_v4 = NULL;
}
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void Swap(t_node *a, t_node *b, t_node *c, t_node *d, t_tree *tree)
{
int ab, ba, cd, dc, bc;
int i;
/* \ /d \ /a
* \ / \ /
* \b__...__c/ -> \b__...__c/
* / \ / \
* / \ / \
* /a \ /d \
*
* nodes b and c are not necessarily on the same branch
*/
if(tree->nextree) Swap(tree->nextree->t_nodes[a->num],
tree->nextree->t_nodes[b->num],
tree->nextree->t_nodes[c->num],
tree->nextree->t_nodes[d->num],
tree->nextree);
#ifdef DEBUG
if(!a || !b || !c || !d)
{
PhyML_Printf("\n. Err in file %s at line %d\n",__FILE__,__LINE__);
Warn_And_Exit("");
}
#endif
ab = ba = cd = dc = bc = -1;
For(i,3) if(a->v[i] == b) { ab = i; break; }
For(i,3) if(b->v[i] == a) { ba = i; break; }
For(i,3) if(c->v[i] == d) { cd = i; break; }
For(i,3) if(d->v[i] == c) { dc = i; break; }
For(i,3) if(b->v[i] == c) { bc = i; break; }
#ifdef DEBUG
if(ab < 0 || ba < 0 || cd < 0 || dc < 0)
{
PhyML_Printf("\n. Nodes %d %d %d %d\n",a->num,b->num,c->num,d->num);
PhyML_Printf("\n. Err in file %s at line %d\n",__FILE__,__LINE__);
Warn_And_Exit("");
}
#endif
a->v[ab] = c;
d->v[dc] = b;
b->v[ba] = d;
c->v[cd] = a;
b->b[ba] = d->b[dc];
c->b[cd] = a->b[ab];
(a->b[ab]->left == b)?
(a->b[ab]->left = c):
(a->b[ab]->rght = c);
(d->b[dc]->left == c)?
(d->b[dc]->left = b):
(d->b[dc]->rght = b);
For(i,3)
{
if(a->b[ab]->left->v[i] == a->b[ab]->rght) a->b[ab]->l_r = i;
if(a->b[ab]->rght->v[i] == a->b[ab]->left) a->b[ab]->r_l = i;
if(d->b[dc]->left->v[i] == d->b[dc]->rght) d->b[dc]->l_r = i;
if(d->b[dc]->rght->v[i] == d->b[dc]->left) d->b[dc]->r_l = i;
}
a->b[ab]->l_v1 = a->b[ab]->l_v2 =
a->b[ab]->r_v1 = a->b[ab]->r_v2 =
d->b[dc]->l_v1 = d->b[dc]->l_v2 =
d->b[dc]->r_v1 = d->b[dc]->r_v2 = -1;
For(i,3)
{
if(i != a->b[ab]->l_r)
{
if(a->b[ab]->l_v1 < 0) a->b[ab]->l_v1 = i;
else a->b[ab]->l_v2 = i;
}
if(i != a->b[ab]->r_l)
{
if(a->b[ab]->r_v1 < 0) a->b[ab]->r_v1 = i;
else a->b[ab]->r_v2 = i;
}
if(i != d->b[dc]->l_r)
{
if(d->b[dc]->l_v1 < 0) d->b[dc]->l_v1 = i;
else d->b[dc]->l_v2 = i;
}
if(i != d->b[dc]->r_l)
{
if(d->b[dc]->r_v1 < 0) d->b[dc]->r_v1 = i;
else d->b[dc]->r_v2 = i;
}
}
Update_Dirs(tree);
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void Update_All_Partial_Lk(t_edge *b_fcus, t_tree *tree)
{
Update_SubTree_Partial_Lk(b_fcus->left->b[b_fcus->l_v1],
b_fcus->left,
b_fcus->left->v[b_fcus->l_v1],
tree);
Update_SubTree_Partial_Lk(b_fcus->left->b[b_fcus->l_v2],
b_fcus->left,
b_fcus->left->v[b_fcus->l_v2],
tree);
Update_SubTree_Partial_Lk(b_fcus->rght->b[b_fcus->r_v1],
b_fcus->rght,
b_fcus->rght->v[b_fcus->r_v1],
tree);
Update_SubTree_Partial_Lk(b_fcus->rght->b[b_fcus->r_v2],
b_fcus->rght,
b_fcus->rght->v[b_fcus->r_v2],
tree);
tree->c_lnL = Lk_At_Given_Edge(b_fcus,tree);
if(tree->nextree) Update_All_Partial_Lk(tree->nextree->t_edges[b_fcus->num],
tree->nextree);
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void Update_SubTree_Partial_Lk(t_edge *b_fcus, t_node *a, t_node *d, t_tree *tree)
{
int i;
Update_P_Lk(tree,b_fcus,a);
if(d->tax) return;
else For(i,3) if(d->v[i] != a)
Update_SubTree_Partial_Lk(d->b[i],d,d->v[i],tree);
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
calign *Make_Cseq(int n_otu, int crunch_len, int state_len, int init_len, char **sp_names)
{
calign *cdata;
int j;
cdata = (calign *)mCalloc(1,sizeof(calign));
cdata->n_otu = n_otu;
cdata->c_seq = (align **)mCalloc(n_otu,sizeof(align *));
cdata->b_frq = (phydbl *)mCalloc(T_MAX_ALPHABET,sizeof(phydbl));
cdata->wght = (int *)mCalloc(crunch_len,sizeof(int));
cdata->ambigu = (short int *)mCalloc(crunch_len,sizeof(short int));
cdata->invar = (short int *)mCalloc(crunch_len,sizeof(short int));
cdata->sitepatt = (int *)mCalloc(init_len,sizeof(int ));
cdata->format = 0;
cdata->crunch_len = crunch_len;
cdata->init_len = init_len;
cdata->obs_pinvar = .0;
For(j,n_otu)
{
cdata->c_seq[j] = (align *)mCalloc(1,sizeof(align));
cdata->c_seq[j]->name = (char *)mCalloc((int)(strlen(sp_names[j])+1),sizeof(char));
strcpy(cdata->c_seq[j]->name,sp_names[j]);
cdata->c_seq[j]->state = (char *)mCalloc(crunch_len*state_len,sizeof(char));
cdata->c_seq[j]->is_ambigu = (short int *)mCalloc(crunch_len,sizeof(short int));
}
return cdata;
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
t_treelist *Make_Treelist(int list_size)
{
t_treelist *tlist;
tlist = (t_treelist *)mCalloc(1,sizeof(t_treelist));
tlist->list_size = list_size;
tlist->tree = (t_tree **)mCalloc(list_size,sizeof(t_tree *));
return tlist;
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void Copy_Seq_Names_To_Tip_Labels(t_tree *tree, calign *data)
{
int i;
For(i,tree->n_otu)
{
strcpy(tree->t_nodes[i]->name,data->c_seq[i]->name);
}
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
calign *Copy_Cseq(calign *ori, option *io)
{
calign *new;
int i,j,k,n_otu,c_len;
char **sp_names;
n_otu = ori->n_otu;
c_len = ori->crunch_len;
sp_names = (char **)mCalloc(n_otu,sizeof(char *));
For(i,n_otu)
{
sp_names[i] = (char *)mCalloc(strlen(ori->c_seq[i]->name)+1,sizeof(char));
strcpy(sp_names[i],ori->c_seq[i]->name);
}
new = Make_Cseq(n_otu,c_len+1,io->mod->state_len,ori->init_len,sp_names);
new->obs_pinvar = ori->obs_pinvar;
For(i,ori->init_len) new->sitepatt[i] = ori->sitepatt[i];
For(j,ori->crunch_len)
{
For(i,ori->n_otu)
{
For(k,io->mod->state_len)
{
new->c_seq[i]->state[j*io->mod->state_len+k] =
ori->c_seq[i]->state[j*io->mod->state_len+k];
}
new->c_seq[i]->is_ambigu[j] = ori->c_seq[i]->is_ambigu[j];
}
new->wght[j] = ori->wght[j];
new->ambigu[j] = ori->ambigu[j];
new->invar[j] = ori->invar[j];
}
For(i,ori->n_otu)
{
new->c_seq[i]->len = ori->c_seq[i]->len;
strcpy(new->c_seq[i]->name,ori->c_seq[i]->name);
}
For(i,ori->n_otu) new->c_seq[i]->state[c_len*io->mod->state_len] = '\0';
For(i,io->mod->ns) new->b_frq[i] = ori->b_frq[i];
new->init_len = ori->init_len;
new->clean_len = ori->clean_len;
new->crunch_len = ori->crunch_len;
new->n_otu = ori->n_otu;
For(i,n_otu) Free(sp_names[i]);
Free(sp_names);
return new;
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
optimiz *Make_Optimiz()
{
optimiz *s_opt;
s_opt = (optimiz *)mCalloc(1,sizeof(optimiz));
return s_opt;
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
int Filexists(char *filename)
{
FILE *fp;
fp =fopen(filename,"r");
if (fp) {
fclose(fp);
return 1;
} else
return 0;
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
FILE *Openfile(char *filename, int mode)
{
/* mode = 0 -> read */
/* mode = 1 -> write */
/* mode = 2 -> append */
FILE *fp;
char *s;
int open_test=0;
/* s = (char *)mCalloc(T_MAX_FILE,sizeof(char)); */
/* strcpy(s,filename); */
s = filename;
fp = NULL;
switch(mode)
{
case 0 :
{
while(!(fp = (FILE *)fopen(s,"r")) && ++open_test<10)
{
PhyML_Printf("\n. Can't open file '%s', enter a new name : ",s);
Getstring_Stdin(s);
}
break;
}
case 1 :
{
fp = (FILE *)fopen(s,"w");
break;
}
case 2 :
{
fp = (FILE *)fopen(s,"a");
break;
}
default : break;
}
/* Free(s); */
return fp;
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void Print_Fp_Out(FILE *fp_out, time_t t_beg, time_t t_end, t_tree *tree, option *io, int n_data_set, int num_tree)
{
char *s;
div_t hour,min;
int i;
/* For(i,2*tree->n_otu-3) fprintf(fp_out,"\n. * Edge %3d: %f",i,tree->t_edges[i]->l); */
if((!n_data_set) || (!num_tree))
{
rewind(fp_out);
Print_Banner_Small(fp_out);
}
PhyML_Fprintf(fp_out,"\n. Sequence filename: \t\t\t%s", Basename(io->in_align_file));
PhyML_Fprintf(fp_out,"\n. Data set: \t\t\t\t#%d",n_data_set);
if(io->mod->s_opt->random_input_tree)
PhyML_Fprintf(fp_out,"\n. Random init tree: \t\t\t#%d",num_tree+1);
else if(io->n_trees > 1)
PhyML_Fprintf(fp_out,"\n. Starting tree number: \t\t\t#%d",num_tree+1);
if(io->mod->s_opt->opt_topo)
{
if(io->mod->s_opt->topo_search == NNI_MOVE) PhyML_Fprintf(fp_out,"\n. Tree topology search : \t\tNNIs");
else if(io->mod->s_opt->topo_search == SPR_MOVE) PhyML_Fprintf(fp_out,"\n. Tree topology search : \t\tSPRs");
else if(io->mod->s_opt->topo_search == BEST_OF_NNI_AND_SPR) PhyML_Fprintf(fp_out,"\n. Tree topology search : \t\tBest of NNIs and SPRs");
}
else
{
PhyML_Fprintf(fp_out,"\n. Tree topology: \t\t\tfixed");
}
/* was after Sequence file ; moved here FLT */
s = (char *)mCalloc(T_MAX_LINE,sizeof(char));
if(io->in_tree == 2)
{
strcat(strcat(strcat(s,"user tree ("),io->in_tree_file),")");
}
else
{
if(!io->mod->s_opt->random_input_tree)
{
if(io->in_tree == 0)
strcat(s,"BioNJ");
if(io->in_tree == 1)
strcat(s,"parsimony");
}
else
{
strcat(s,"random tree");
}
}
PhyML_Fprintf(fp_out,"\n. Initial tree: \t\t\t%s",s);
Free(s);
if(tree->io->datatype == NT)
{
PhyML_Fprintf(fp_out,"\n. Model of nucleotides substitution: \t%s",io->mod->modelname);
if(io->mod->whichmodel == CUSTOM)
PhyML_Fprintf(fp_out," (%s)",io->mod->custom_mod_string);
}
else if(tree->io->datatype == AA)
{
PhyML_Fprintf(fp_out,"\n. Model of amino acids substitution: \t%s",io->mod->modelname);
if(io->mod->whichmodel == CUSTOMAA) PhyML_Fprintf(fp_out," (%s)",io->aa_rate_mat_file);
}
else
{
fprintf(fp_out,"\n. Substitution model: \t\t\t%s",io->mod->modelname);
}
PhyML_Fprintf(fp_out,"\n. Number of taxa: \t\t\t%d",tree->n_otu);/*added FLT*/
PhyML_Fprintf(fp_out,"\n. Log-likelihood: \t\t\t%.5f",tree->c_lnL);/*was last ; moved here FLT*/
Unconstraint_Lk(tree);
PhyML_Fprintf(fp_out,"\n. Unconstrained likelihood: \t\t%.5f",tree->unconstraint_lk);
PhyML_Fprintf(fp_out,"\n. Parsimony: \t\t\t\t%d",tree->c_pars);
PhyML_Fprintf(fp_out,"\n. Tree size: \t\t\t\t%.5f",tree->size);
if(tree->mod->n_catg > 1 && tree->mod->free_mixt_rates == NO)
{
PhyML_Fprintf(fp_out,"\n. Discrete gamma model: \t\t%s","Yes");
PhyML_Fprintf(fp_out,"\n - Number of categories: \t\t%d",tree->mod->n_catg);
PhyML_Fprintf(fp_out,"\n - Gamma shape parameter: \t\t%.3f",tree->mod->alpha->v);
}
else if(tree->mod->free_mixt_rates == YES)
{
PhyML_Fprintf(fp_out,"\n. Discrete gamma model: \t\t%s","No");
PhyML_Fprintf(fp_out,"\n - Number of categories: \t\t%d",tree->mod->n_catg);
For(i,tree->mod->n_catg)
{
PhyML_Fprintf(fp_out,"\n - Relative rate in class %d: \t\t%.5f [prop=%4f] \t\t",i+1,tree->mod->gamma_rr->v[i],tree->mod->gamma_r_proba->v[i]);
}
}
if(tree->mod->invar) PhyML_Fprintf(fp_out,"\n. Proportion of invariant: \t\t%.3f",tree->mod->pinvar->v);
/*was before Discrete gamma model ; moved here FLT*/
if((tree->mod->whichmodel == K80) ||
(tree->mod->whichmodel == HKY85) ||
(tree->mod->whichmodel == F84))
PhyML_Fprintf(fp_out,"\n. Transition/transversion ratio: \t%.3f",tree->mod->kappa->v);
else if(tree->mod->whichmodel == TN93)
{
PhyML_Fprintf(fp_out,"\n. Transition/transversion ratio for purines: \t\t\t%.3f",
tree->mod->kappa->v*2.*tree->mod->lambda->v/(1.+tree->mod->lambda->v));
PhyML_Fprintf(fp_out,"\n. Transition/transversion ratio for pyrimidines: \t\t\t%.3f",
tree->mod->kappa->v*2./(1.+tree->mod->lambda->v));
}
if(tree->io->datatype == NT)
{
PhyML_Fprintf(fp_out,"\n. Nucleotides frequencies:");
PhyML_Fprintf(fp_out,"\n - f(A)=%8.5f",tree->mod->pi->v[0]);
PhyML_Fprintf(fp_out,"\n - f(C)=%8.5f",tree->mod->pi->v[1]);
PhyML_Fprintf(fp_out,"\n - f(G)=%8.5f",tree->mod->pi->v[2]);
PhyML_Fprintf(fp_out,"\n - f(T)=%8.5f",tree->mod->pi->v[3]);
}
/*****************************************/
if((tree->mod->whichmodel == GTR) ||
(tree->mod->whichmodel == CUSTOM))
{
int i,j;
Update_Qmat_GTR(tree->mod->rr->v,
tree->mod->rr_val->v,
tree->mod->rr_num->v,
tree->mod->pi->v,
tree->mod->qmat->v);
PhyML_Fprintf(fp_out,"\n");
PhyML_Fprintf(fp_out,". GTR relative rate parameters : \n");
PhyML_Fprintf(fp_out," A <-> C %8.5f\n", tree->mod->rr->v[0]);
PhyML_Fprintf(fp_out," A <-> G %8.5f\n", tree->mod->rr->v[1]);
PhyML_Fprintf(fp_out," A <-> T %8.5f\n", tree->mod->rr->v[2]);
PhyML_Fprintf(fp_out," C <-> G %8.5f\n", tree->mod->rr->v[3]);
PhyML_Fprintf(fp_out," C <-> T %8.5f\n", tree->mod->rr->v[4]);
PhyML_Fprintf(fp_out," G <-> T %8.5f\n",tree->mod->rr->v[5]);
PhyML_Fprintf(fp_out,"\n. Instantaneous rate matrix : ");
PhyML_Fprintf(fp_out,"\n [A---------C---------G---------T------]\n");
For(i,4)
{
PhyML_Fprintf(fp_out," ");
For(j,4)
PhyML_Fprintf(fp_out,"%8.5f ",tree->mod->qmat->v[i*4+j]);
PhyML_Fprintf(fp_out,"\n");
}
PhyML_Fprintf(fp_out,"\n");
}
/*****************************************/
if(io->ratio_test == 1)
{
PhyML_Fprintf(fp_out,". aLRT statistics to test branches");
}
else if(io->ratio_test == 2)
{
PhyML_Fprintf(fp_out,". aLRT branch supports (cubic approximation, mixture of Chi2s distribution)");
}
PhyML_Fprintf(fp_out,"\n");
PhyML_Fprintf(fp_out,"\n. Run ID:\t\t\t\t%s", (io->appebr_run_ID) ? (io->run_id_string): ("none"));
PhyML_Fprintf(fp_out,"\n. Random seed:\t\t\t\t%d", io->r_seed);
PhyML_Fprintf(fp_out,"\n. Subtree patterns aliasing:\t\t%s",io->do_alias_subpatt?"yes":"no");
PhyML_Fprintf(fp_out,"\n. Version:\t\t\t\t%s", VERSION);
hour = div(t_end-t_beg,3600);
min = div(t_end-t_beg,60 );
min.quot -= hour.quot*60;
PhyML_Fprintf(fp_out,"\n. Time used:\t\t\t\t%dh%dm%ds (%d seconds)", hour.quot,min.quot,(int)(t_end-t_beg)%60,(int)(t_end-t_beg));
PhyML_Fprintf(fp_out,"\n\n");
PhyML_Fprintf(fp_out," oooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooo\n");
PhyML_Fprintf(fp_out," Suggested citations:\n");
PhyML_Fprintf(fp_out," S. Guindon, JF. Dufayard, V. Lefort, M. Anisimova, W. Hordijk, O. Gascuel\n");
PhyML_Fprintf(fp_out," \"New algorithms and methods to estimate maximum-likelihood phylogenies: assessing the performance of PhyML 3.0.\"\n");
PhyML_Fprintf(fp_out," Systematic Biology. 2010. 59(3):307-321.\n");
PhyML_Fprintf(fp_out,"\n");
PhyML_Fprintf(fp_out," S. Guindon & O. Gascuel\n");
PhyML_Fprintf(fp_out," \"A simple, fast, and accurate algorithm to estimate large phylogenies by maximum likelihood\"\n");
PhyML_Fprintf(fp_out," Systematic Biology. 2003. 52(5):696-704.\n");
PhyML_Fprintf(fp_out," oooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooo\n");
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
/*FLT wrote this function*/
void Print_Fp_Out_Lines(FILE *fp_out, time_t t_beg, time_t t_end, t_tree *tree, option *io, int n_data_set)
{
char *s;
/*div_t hour,min;*/
if (n_data_set==1)
{
PhyML_Fprintf(fp_out,". Sequence file : [%s]\n\n", Basename(io->in_align_file));
if((tree->io->datatype == NT) || (tree->io->datatype == AA))
{
(tree->io->datatype == NT)?
(PhyML_Fprintf(fp_out,". Model of nucleotides substitution : %s\n\n",io->mod->modelname)):
(PhyML_Fprintf(fp_out,". Model of amino acids substitution : %s\n\n",io->mod->modelname));
}
s = (char *)mCalloc(100,sizeof(char));
switch(io->in_tree)
{
case 0: { strcpy(s,"BioNJ"); break; }
case 1: { strcpy(s,"parsimony"); break; }
case 2: { strcpy(s,"user tree (");
strcat(s,io->in_tree_file);
strcat(s,")"); break; }
}
PhyML_Fprintf(fp_out,". Initial tree : [%s]\n\n",s);
Free(s);
PhyML_Fprintf(fp_out,"\n");
/*headline 1*/
PhyML_Fprintf(fp_out, ". Data\t");
PhyML_Fprintf(fp_out,"Nb of \t");
PhyML_Fprintf(fp_out,"Likelihood\t");
PhyML_Fprintf(fp_out, "Discrete \t");
if(tree->mod->n_catg > 1)
PhyML_Fprintf(fp_out, "Number of \tGamma shape\t");
PhyML_Fprintf(fp_out,"Proportion of\t");
if(tree->mod->whichmodel <= 6)
PhyML_Fprintf(fp_out,"Transition/ \t");
PhyML_Fprintf(fp_out,"Nucleotides frequencies \t");
if((tree->mod->whichmodel == GTR) ||
(tree->mod->whichmodel == CUSTOM))
PhyML_Fprintf(fp_out,"Instantaneous rate matrix \t");
/* PhyML_Fprintf(fp_out,"Time\t");*/
PhyML_Fprintf(fp_out, "\n");
/*headline 2*/
PhyML_Fprintf(fp_out, " set\t");
PhyML_Fprintf(fp_out,"taxa\t");
PhyML_Fprintf(fp_out,"loglk \t");
PhyML_Fprintf(fp_out, "gamma model\t");
if(tree->mod->n_catg > 1)
PhyML_Fprintf(fp_out, "categories\tparameter \t");
PhyML_Fprintf(fp_out,"invariant \t");
if(tree->mod->whichmodel <= 6)
PhyML_Fprintf(fp_out,"transversion\t");
PhyML_Fprintf(fp_out,"f(A) f(C) f(G) f(T) \t");
if((tree->mod->whichmodel == GTR) ||
(tree->mod->whichmodel == CUSTOM))
PhyML_Fprintf(fp_out,"[A---------C---------G---------T------]\t");
/* PhyML_PhyML_Fprintf(fp_out,"used\t");*/
PhyML_Fprintf(fp_out, "\n");
/*headline 3*/
if(tree->mod->whichmodel == TN93)
{
PhyML_Fprintf(fp_out," \t \t \t \t");
if(tree->mod->n_catg > 1) PhyML_Fprintf(fp_out," \t \t");
PhyML_Fprintf(fp_out," \t");
PhyML_Fprintf(fp_out,"purines pyrimid.\t");
PhyML_Fprintf(fp_out, "\n");
}
PhyML_Fprintf(fp_out, "\n");
}
/*line items*/
PhyML_Fprintf(fp_out," #%d\t",n_data_set);
PhyML_Fprintf(fp_out,"%d \t",tree->n_otu);
PhyML_Fprintf(fp_out,"%.5f\t",tree->c_lnL);
PhyML_Fprintf(fp_out,"%s \t",
(tree->mod->n_catg>1)?("Yes"):("No "));
if(tree->mod->n_catg > 1)
{
PhyML_Fprintf(fp_out,"%d \t",tree->mod->n_catg);
PhyML_Fprintf(fp_out,"%.3f \t",tree->mod->alpha->v);
}
/*if(tree->mod->invar)*/
PhyML_Fprintf(fp_out,"%.3f \t",tree->mod->pinvar->v);
if(tree->mod->whichmodel <= 5)
{
PhyML_Fprintf(fp_out,"%.3f \t",tree->mod->kappa->v);
}
else if(tree->mod->whichmodel == TN93)
{
PhyML_Fprintf(fp_out,"%.3f ",
tree->mod->kappa->v*2.*tree->mod->lambda->v/(1.+tree->mod->lambda->v));
PhyML_Fprintf(fp_out,"%.3f\t",
tree->mod->kappa->v*2./(1.+tree->mod->lambda->v));
}
if(tree->io->datatype == NT)
{
PhyML_Fprintf(fp_out,"%8.5f ",tree->mod->pi->v[0]);
PhyML_Fprintf(fp_out,"%8.5f ",tree->mod->pi->v[1]);
PhyML_Fprintf(fp_out,"%8.5f ",tree->mod->pi->v[2]);
PhyML_Fprintf(fp_out,"%8.5f\t",tree->mod->pi->v[3]);
}
/*
hour = div(t_end-t_beg,3600);
min = div(t_end-t_beg,60 );
min.quot -= hour.quot*60;
PhyML_Fprintf(fp_out,"%dh%dm%ds\t", hour.quot,min.quot,(int)(t_end-t_beg)%60);
if(t_end-t_beg > 60)
PhyML_Fprintf(fp_out,". -> %d seconds\t",(int)(t_end-t_beg));
*/
/*****************************************/
if((tree->mod->whichmodel == GTR) || (tree->mod->whichmodel == CUSTOM))
{
int i,j;
For(i,4)
{
if (i!=0) {
/*format*/
PhyML_Fprintf(fp_out," \t \t \t \t");
if(tree->mod->n_catg > 1) PhyML_Fprintf(fp_out," \t \t");
PhyML_Fprintf(fp_out," \t \t");
}
For(j,4)
PhyML_Fprintf(fp_out,"%8.5f ",tree->mod->qmat->v[i*4+j]);
if (i<3) PhyML_Fprintf(fp_out,"\n");
}
}
/*****************************************/
PhyML_Fprintf(fp_out, "\n\n");
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
matrix *K80_dist(calign *data, phydbl g_shape)
{
int i,j,k;
int diff;
phydbl unc_len;
matrix *mat;
phydbl **len;
len = (phydbl **)mCalloc(data->n_otu,sizeof(phydbl *));
For(i,data->n_otu)
len[i] = (phydbl *)mCalloc(data->n_otu,sizeof(phydbl));
unc_len = .0;
mat = Make_Mat(data->n_otu);
Init_Mat(mat,data);
For(i,data->c_seq[0]->len)
{
For(j,data->n_otu-1)
{
for(k=j+1;kn_otu;k++)
{
if(((data->c_seq[j]->state[i] == 'A' || data->c_seq[j]->state[i] == 'G') &&
(data->c_seq[k]->state[i] == 'C' || data->c_seq[k]->state[i] == 'T'))||
((data->c_seq[j]->state[i] == 'C' || data->c_seq[j]->state[i] == 'T') &&
(data->c_seq[k]->state[i] == 'A' || data->c_seq[k]->state[i] == 'G')))
{
diff++;
mat->Q[j][k]+=data->wght[i];
len[j][k]+=data->wght[i];
len[k][j]=len[j][k];
}
else
if(((data->c_seq[j]->state[i] == 'A' && data->c_seq[k]->state[i] == 'G') ||
(data->c_seq[j]->state[i] == 'G' && data->c_seq[k]->state[i] == 'A'))||
((data->c_seq[j]->state[i] == 'C' && data->c_seq[k]->state[i] == 'T') ||
(data->c_seq[j]->state[i] == 'T' && data->c_seq[k]->state[i] == 'C')))
{
diff++;
mat->P[j][k]+=data->wght[i];
len[j][k]+=data->wght[i];
len[k][j]=len[j][k];
}
else
if((data->c_seq[j]->state[i] == 'A' ||
data->c_seq[j]->state[i] == 'C' ||
data->c_seq[j]->state[i] == 'G' ||
data->c_seq[j]->state[i] == 'T')&&
(data->c_seq[k]->state[i] == 'A' ||
data->c_seq[k]->state[i] == 'C' ||
data->c_seq[k]->state[i] == 'G' ||
data->c_seq[k]->state[i] == 'T'))
{
len[j][k]+=data->wght[i];
len[k][j]=len[j][k];
}
}
}
}
For(i,data->n_otu-1)
for(j=i+1;jn_otu;j++)
{
if(len[i][j] > .0)
{
mat->P[i][j] /= len[i][j];
mat->Q[i][j] /= len[i][j];
}
else
{
mat->P[i][j] = .5;
mat->Q[i][j] = .5;
}
mat->P[j][i] = mat->P[i][j];
mat->Q[j][i] = mat->Q[i][j];
if((1-2*mat->P[i][j]-mat->Q[i][j] <= .0) || (1-2*mat->Q[i][j] <= .0))
{
mat->dist[i][j] = -1.;
mat->dist[j][i] = -1.;
continue;
}
mat->dist[i][j] = (g_shape/2)*
(POW(1-2*mat->P[i][j]-mat->Q[i][j],-1./g_shape) +
0.5*POW(1-2*mat->Q[i][j],-1./g_shape) - 1.5);
if(mat->dist[i][j] > DIST_MAX) mat->dist[i][j] = DIST_MAX;
mat->dist[j][i] = mat->dist[i][j];
}
For(i,data->n_otu) free(len[i]);
free(len);
return mat;
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
matrix *JC69_Dist(calign *data, model *mod)
{
int site,i,j,k;
phydbl unc_len;
matrix *mat;
phydbl **len;
int datatype;
len = (phydbl **)mCalloc(data->n_otu,sizeof(phydbl *));
For(i,data->n_otu)
len[i] = (phydbl *)mCalloc(data->n_otu,sizeof(phydbl));
unc_len = .0;
mat = Make_Mat(data->n_otu);
Init_Mat(mat,data);
datatype = mod->io->datatype;
For(site,data->c_seq[0]->len)
{
For(j,data->n_otu-1)
{
for(k=j+1;kn_otu;k++)
{
if((!Is_Ambigu(data->c_seq[j]->state+site*mod->io->mod->state_len,datatype,mod->io->mod->state_len)) &&
(!Is_Ambigu(data->c_seq[k]->state+site*mod->io->mod->state_len,datatype,mod->io->mod->state_len)))
{
len[j][k]+=data->wght[site];
len[k][j]=len[j][k];
if(strncmp(data->c_seq[j]->state+site*mod->io->mod->state_len,
data->c_seq[k]->state+site*mod->io->mod->state_len,mod->io->mod->state_len))
/* if(!Are_Compatible(data->c_seq[j]->state+site*mod->io->mod->state_len, */
/* data->c_seq[k]->state+site*mod->io->mod->state_len, */
/* mod->io->mod->state_len, */
/* mod->io->datatype)) */
mat->P[j][k]+=data->wght[site];
}
}
}
}
For(i,data->n_otu-1)
for(j=i+1;jn_otu;j++)
{
if(len[i][j] > .0) mat->P[i][j] /= len[i][j];
else mat->P[i][j] = 1.;
mat->P[j][i] = mat->P[i][j];
if((1.-(mod->ns)/(mod->ns-1.)*mat->P[i][j]) < .0) mat->dist[i][j] = -1.;
else
mat->dist[i][j] = -(mod->ns-1.)/(mod->ns)*(phydbl)LOG(1.-(mod->ns)/(mod->ns-1.)*mat->P[i][j]);
/* PhyML_Printf("\n. Incorrect JC distances"); */
/* mat->dist[i][j] = len[i][j]; */
if(mat->dist[i][j] > DIST_MAX) mat->dist[i][j] = DIST_MAX;
mat->dist[j][i] = mat->dist[i][j];
}
For(i,data->n_otu) free(len[i]);
free(len);
return mat;
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
matrix *Hamming_Dist(calign *data, model *mod)
{
int i,j,k;
phydbl unc_len;
matrix *mat;
phydbl **len;
int datatype;
len = (phydbl **)mCalloc(data->n_otu,sizeof(phydbl *));
For(i,data->n_otu)
len[i] = (phydbl *)mCalloc(data->n_otu,sizeof(phydbl));
unc_len = .0;
mat = Make_Mat(data->n_otu);
Init_Mat(mat,data);
datatype = mod->io->datatype;
For(i,data->crunch_len)
{
For(j,data->n_otu-1)
{
for(k=j+1;kn_otu;k++)
{
if((!Is_Ambigu(data->c_seq[j]->state+i*mod->io->mod->state_len,datatype,mod->io->mod->state_len)) &&
(!Is_Ambigu(data->c_seq[k]->state+i*mod->io->mod->state_len,datatype,mod->io->mod->state_len)))
{
len[j][k]+=data->wght[i];
len[k][j]=len[j][k];
/* if(data->c_seq[j]->state[i] != data->c_seq[k]->state[i]) */
if(!Are_Compatible(data->c_seq[j]->state+i*mod->io->mod->state_len,
data->c_seq[k]->state+i*mod->io->mod->state_len,
mod->io->mod->state_len,
mod->io->datatype))
{
mat->P[j][k]+=data->wght[i];
}
}
}
}
}
For(i,data->n_otu-1)
for(j=i+1;jn_otu;j++)
{
if(len[i][j] > .0)
{
mat->P[i][j] /= len[i][j];
}
else
{
mat->P[i][j] = 1.;
}
mat->P[j][i] = mat->P[i][j];
mat->dist[i][j] = mat->P[i][j];
if(mat->dist[i][j] > DIST_MAX)
{
mat->dist[i][j] = DIST_MAX;
}
mat->dist[j][i] = mat->dist[i][j];
}
For(i,data->n_otu) free(len[i]);
free(len);
return mat;
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
/* Test if the given site pattern is invariant. Does not handle ambiguities */
int Is_Invar(int patt_num, int stepsize, int datatype, calign *data)
{
int i, j;
For(i,data->n_otu)
{
For(j,data->n_otu)
{
if(!(Are_Compatible(data->c_seq[i]->state+patt_num,
data->c_seq[j]->state+patt_num,
stepsize,
datatype)))
{
break;
}
}
if(j != data->n_otu) break;
}
if(i == data->n_otu) return 1;
else return 0;
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
int Is_Ambigu(char *state, int datatype, int stepsize)
{
int val,i;
val = -1;
if(datatype == NT)
{
For(i,stepsize)
{
switch(state[i])
{
case 'A' : case 'C' : case 'G' : case 'T' : case 'U' : { val=0; break; }
default : { val=1; break; }
}
if(val == 1) break;
}
}
else if(datatype == AA)
{
switch(state[0])
{
case 'X' : case '?' : case '-' : case '.' : {val=1; break; }
default : { val=0; break; }
}
}
else if(datatype == GENERIC)
{
int i;
For(i,stepsize) if(!isdigit(state[i])) break;
if(i == stepsize) val = 0;
else val = 1;
}
return val;
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void Check_Ambiguities(calign *data, int datatype, int stepsize)
{
int i,j;
For(j,data->crunch_len)
{
For(i,data->n_otu)
{
data->ambigu[j] = 0;
data->c_seq[i]->is_ambigu[j] = 0;
}
For(i,data->n_otu)
{
if(Is_Ambigu(data->c_seq[i]->state+j*stepsize,
datatype,
stepsize))
{
data->ambigu[j] = 1;
data->c_seq[i]->is_ambigu[j] = 1;
}
}
}
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
int Get_State_From_Ui(int ui, int datatype)
{
if(datatype == NT)
{
switch(ui)
{
case 1 : {return 0; break;}
case 2 : {return 1; break;}
case 4 : {return 2; break;}
case 8 : {return 3; break;}
default :
{
PhyML_Printf("\n. ui=%d",ui);
PhyML_Printf("\n. Err in file %s at line %d\n",__FILE__,__LINE__);
Warn_And_Exit("");
break;
}
}
}
else if(datatype == AA)
{
switch(ui)
{
case 1 : {return 0; break;}
case 2 : {return 1; break;}
case 4 : {return 2; break;}
case 8 : {return 3; break;}
case 16 : {return 4; break;}
case 32 : {return 5; break;}
case 64 : {return 6; break;}
case 128 : {return 7; break;}
case 256 : {return 8; break;}
case 512 : {return 9; break;}
case 1024 : {return 10; break;}
case 2048 : {return 11; break;}
case 4096 : {return 12; break;}
case 8192 : {return 13; break;}
case 16384 : {return 14; break;}
case 32768 : {return 15; break;}
case 65536 : {return 16; break;}
case 131072 : {return 17; break;}
case 262144 : {return 18; break;}
case 524288 : {return 19; break;}
default :
{
PhyML_Printf("\n. ui=%d",ui);
PhyML_Printf("\n. Err in file %s at line %d\n",__FILE__,__LINE__);
Warn_And_Exit("");
}
}
}
else
{
PhyML_Printf("\n. Err in file %s at line %d\n",__FILE__,__LINE__);
Warn_And_Exit("");
}
return -1;
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
int Assign_State(char *c, int datatype, int stepsize)
{
int state[3];
int i;
state[0] = state[1] = state[2] = -1;
if(datatype == NT)
{
For(i,stepsize)
{
switch(c[i])
{
case 'A' : {state[i]=0; break;}
case 'C' : {state[i]=1; break;}
case 'G' : {state[i]=2; break;}
case 'T' : {state[i]=3; break;}
case 'U' : {state[i]=3; break;}
default : {state[i]=-1; break;}
}
}
return (stepsize>1)?(state[0]*16+state[1]*4+state[2]):(state[0]);
}
else if(datatype == AA)
{
switch(c[0])
{
case 'A' : {state[0]=0 ; break;}
case 'R' : {state[0]=1 ; break;}
case 'N' : {state[0]=2 ; break;}
case 'D' : {state[0]=3 ; break;}
case 'C' : {state[0]=4 ; break;}
case 'Q' : {state[0]=5 ; break;}
case 'E' : {state[0]=6 ; break;}
case 'G' : {state[0]=7 ; break;}
case 'H' : {state[0]=8 ; break;}
case 'I' : {state[0]=9 ; break;}
case 'L' : {state[0]=10; break;}
case 'K' : {state[0]=11; break;}
case 'M' : {state[0]=12; break;}
case 'F' : {state[0]=13; break;}
case 'P' : {state[0]=14; break;}
case 'S' : {state[0]=15; break;}
case 'T' : {state[0]=16; break;}
case 'W' : {state[0]=17; break;}
case 'Y' : {state[0]=18; break;}
case 'V' : {state[0]=19; break;}
case 'B' : {state[0] = 2; break;}
case 'Z' : {state[0] = 5; break;}
default : {state[0]=-1; break;}
}
return state[0];
}
else if(datatype == GENERIC)
{
char format[6];
int ret;
sprintf(format,"%%%dd",stepsize);
ret = sscanf(c,format,state);
if(!ret) state[0] = -1;
return state[0];
}
else
{
PhyML_Printf("\n. Not implemented yet.\n");
PhyML_Printf("\n. Err in file %s at line %d\n",__FILE__,__LINE__);
Warn_And_Exit("");
}
return -1;
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
char Reciproc_Assign_State(int i_state, int datatype)
{
if(datatype == NT)
{
i_state = i_state%4;
switch(i_state)
{
case 0 : {return 'A'; break;}
case 1 : {return 'C'; break;}
case 2 : {return 'G'; break;}
case 3 : {return 'T'; break;}
default :
{
PhyML_Printf("\n. i_state = %d",i_state);
PhyML_Printf("\n. Err in file %s at line %d\n",__FILE__,__LINE__);
Warn_And_Exit("");
break;
}
}
}
else if(datatype == AA)
{
i_state = i_state%20;
switch(i_state)
{
case 0 : {return 'A' ; break;}
case 1 : {return 'R' ; break;}
case 2 : {return 'N' ; break;}
case 3 : {return 'D' ; break;}
case 4 : {return 'C' ; break;}
case 5 : {return 'Q' ; break;}
case 6 : {return 'E' ; break;}
case 7 : {return 'G' ; break;}
case 8 : {return 'H' ; break;}
case 9 : {return 'I' ; break;}
case 10 : {return 'L'; break;}
case 11 : {return 'K'; break;}
case 12 : {return 'M'; break;}
case 13 : {return 'F'; break;}
case 14 : {return 'P'; break;}
case 15 : {return 'S'; break;}
case 16 : {return 'T'; break;}
case 17 : {return 'W'; break;}
case 18 : {return 'Y'; break;}
case 19 : {return 'V'; break;}
default :
{
PhyML_Printf("\n. Err in file %s at line %d\n",__FILE__,__LINE__);
Warn_And_Exit("");
break;
}
}
}
else if(datatype == GENERIC)
{
return (char)i_state;
}
return -1;
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
int Assign_State_With_Ambiguity(char *c, int datatype, int stepsize)
{
int state[3];
int i;
state[0] = state[1] = state[2] = -1;
if(datatype == NT)
{
For(i,stepsize)
{
switch(c[i])
{
case 'A' : {state[i]= 0; break;}
case 'C' : {state[i]= 1; break;}
case 'G' : {state[i]= 2; break;}
case 'T' : {state[i]= 3; break;}
case 'U' : {state[i]= 3; break;}
case 'M' : {state[i]= 4; break;}
case 'R' : {state[i]= 5; break;}
case 'W' : {state[i]= 6; break;}
case 'S' : {state[i]= 7; break;}
case 'Y' : {state[i]= 8; break;}
case 'K' : {state[i]= 9; break;}
case 'B' : {state[i]=10; break;}
case 'D' : {state[i]=11; break;}
case 'H' : {state[i]=12; break;}
case 'V' : {state[i]=13; break;}
case 'N' : case 'X' : case '?' : case 'O' : case '-' : {state[i]=T_MAX_ALPHABET-1; break;}
default :
{
PhyML_Printf("\n. Unknown character state : '%c'\n",c[i]);
Warn_And_Exit("\n. Init failed (check the data type)\n");
break;
}
}
return (stepsize>1)?(state[0]*16+state[1]*4+state[2]):(state[0]);
}
}
else if(datatype == AA)
{
switch(c[0])
{
case 'A' : {state[0]= 0; break;}
case 'R' : {state[0]= 1; break;}
case 'N' : {state[0]= 2; break;}
case 'D' : {state[0]= 3; break;}
case 'C' : {state[0]= 4; break;}
case 'Q' : {state[0]= 5; break;}
case 'E' : {state[0]= 6; break;}
case 'G' : {state[0]= 7; break;}
case 'H' : {state[0]= 8; break;}
case 'I' : {state[0]= 9; break;}
case 'L' : {state[0]=10; break;}
case 'K' : {state[0]=11; break;}
case 'M' : {state[0]=12; break;}
case 'F' : {state[0]=13; break;}
case 'P' : {state[0]=14; break;}
case 'S' : {state[0]=15; break;}
case 'T' : {state[0]=16; break;}
case 'W' : {state[0]=17; break;}
case 'Y' : {state[0]=18; break;}
case 'V' : {state[0]=19; break;}
case 'B' : {state[0]= 2; break;}
case 'Z' : {state[0]= 5; break;}
case 'X' : case '?' : case '-' : {state[0]=T_MAX_ALPHABET-1; break;}
default :
{
PhyML_Printf("\n. Unknown character state : %c\n",state[0]);
Warn_And_Exit("\n. Init failed (check the data type)\n");
break;
}
}
return state[0];
}
else if(datatype == GENERIC)
{
if(Is_Ambigu(c,GENERIC,stepsize)) state[0] = T_MAX_ALPHABET-1;
else
{
char format[6];
sprintf(format,"%%%dd",stepsize);
if(!sscanf(c,format,state))
{
PhyML_Printf("\n. Error reading character. Was expecting an integer, got '%c' instead.\n",c[0]);
PhyML_Printf("\n. Err in file %s at line %d\n",__FILE__,__LINE__);
Warn_And_Exit("");
}
}
return state[0];
}
return -1;
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void Clean_Tree_Connections(t_tree *tree)
{
int i;
For(i,2*tree->n_otu-2)
{
tree->t_nodes[i]->v[0] = NULL;
tree->t_nodes[i]->v[1] = NULL;
tree->t_nodes[i]->v[2] = NULL;
tree->t_nodes[i]->b[0] = NULL;
tree->t_nodes[i]->b[1] = NULL;
tree->t_nodes[i]->b[2] = NULL;
}
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void Bootstrap(t_tree *tree)
{
int *site_num, n_site;
int replicate,j,k;
int position,init_len;
calign *boot_data;
t_tree *boot_tree;
model *boot_mod;
matrix *boot_mat;
char *s;
/* phydbl rf; */
tree->print_boot_val = 1;
tree->print_alrt_val = 0;
boot_tree = NULL;
site_num = (int *)mCalloc(tree->data->init_len,sizeof(int));
Free_Bip(tree);
Alloc_Bip(tree);
Get_Bip(tree->t_nodes[0],tree->t_nodes[0]->v[0],tree);
n_site = 0;
For(j,tree->data->crunch_len) For(k,tree->data->wght[j])
{
site_num[n_site] = j;
n_site++;
}
boot_data = Copy_Cseq(tree->data,tree->io);
PhyML_Printf("\n\n. Non parametric bootstrap analysis \n\n");
PhyML_Printf(" [");
For(replicate,tree->mod->bootstrap)
{
For(j,boot_data->crunch_len) boot_data->wght[j] = 0;
init_len = 0;
For(j,boot_data->init_len)
{
position = Rand_Int(0,(int)(tree->data->init_len-1.0));
boot_data->wght[site_num[position]] += 1;
init_len++;
}
if(init_len != tree->data->init_len) Warn_And_Exit("\n. Pb when copying sequences\n");
init_len = 0;
For(j,boot_data->crunch_len) init_len += boot_data->wght[j];
if(init_len != tree->data->init_len) Warn_And_Exit("\n. Pb when copying sequences\n");
if(tree->io->datatype == NT) Get_Base_Freqs(boot_data);
else if(tree->io->datatype == AA) Get_AA_Freqs(boot_data);
if(tree->io->random_boot_seq_order) Randomize_Sequence_Order(boot_data);
boot_mod = Copy_Model(tree->mod);
boot_mod->s_opt = tree->mod->s_opt; /* WARNING: re-using the same address here instead of creating a copying
requires to leave the value of s_opt unchanged during the boostrap. */
boot_mod->io = tree->io; /* WARNING: re-using the same address here instead of creating a copying
requires to leave the value of io unchanged during the boostrap. */
Init_Model(boot_data,boot_mod,tree->io);
if(tree->io->mod->use_m4mod) M4_Init_Model(boot_mod->m4mod,boot_data,boot_mod);
if(tree->io->in_tree == 2)
{
rewind(tree->io->fp_in_tree);
boot_tree = Read_Tree_File_Phylip(tree->io->fp_in_tree);
}
else
{
boot_mat = ML_Dist(boot_data,boot_mod);
boot_mat->tree = Make_Tree_From_Scratch(boot_data->n_otu,boot_data);
Fill_Missing_Dist(boot_mat);
Bionj(boot_mat);
boot_tree = boot_mat->tree;
boot_tree->mat = boot_mat;
}
boot_tree->mod = boot_mod;
boot_tree->io = tree->io;
boot_tree->data = boot_data;
boot_tree->both_sides = 1;
boot_tree->mod->s_opt->print = 0;
boot_tree->n_pattern = boot_tree->data->crunch_len;
boot_tree->io->print_site_lnl = 0;
boot_tree->io->print_trace = 0;
if((boot_tree->mod->s_opt->random_input_tree) && (boot_tree->mod->s_opt->topo_search == SPR_MOVE)) Random_Tree(boot_tree);
Order_Tree_CSeq(boot_tree,boot_data);
Share_Lk_Struct(tree,boot_tree);
Share_Spr_Struct(tree,boot_tree);
Share_Pars_Struct(tree,boot_tree);
Fill_Dir_Table(boot_tree);
Update_Dirs(boot_tree);
if(tree->mod->s_opt->greedy) Init_P_Lk_Tips_Double(boot_tree);
else Init_P_Lk_Tips_Int(boot_tree);
Init_Ui_Tips(boot_tree);
Init_P_Pars_Tips(boot_tree);
Br_Len_Not_Involving_Invar(boot_tree);
if(boot_tree->io->do_alias_subpatt)
{
boot_tree->update_alias_subpatt = YES;
Lk(boot_tree);
boot_tree->update_alias_subpatt = NO;
}
if(boot_tree->mod->s_opt->opt_topo)
{
if(boot_tree->mod->s_opt->topo_search == NNI_MOVE)
{
Simu_Loop(boot_tree);
}
else if((boot_tree->mod->s_opt->topo_search == SPR_MOVE) ||
(boot_tree->mod->s_opt->topo_search == BEST_OF_NNI_AND_SPR))
{
Speed_Spr_Loop(boot_tree);
}
}
else
{
if(boot_tree->mod->s_opt->opt_subst_param || boot_tree->mod->s_opt->opt_bl)
Round_Optimize(boot_tree,boot_tree->data,ROUND_MAX);
else
Lk(boot_tree);
}
Free_Bip(boot_tree);
Alloc_Bip(boot_tree);
Match_Tip_Numbers(tree,boot_tree);
Get_Bip(boot_tree->t_nodes[0],
boot_tree->t_nodes[0]->v[0],
boot_tree);
Compare_Bip(tree,boot_tree,NO);
Br_Len_Involving_Invar(boot_tree);
if(tree->io->print_boot_trees)
{
s = Write_Tree(boot_tree,NO);
PhyML_Fprintf(tree->io->fp_out_boot_tree,"%s\n",s);
Free(s);
Print_Fp_Out_Lines(tree->io->fp_out_boot_stats,0,0,boot_tree,tree->io,replicate+1);
}
/* rf = .0; */
/* For(j,2*tree->n_otu-3) */
/* rf += tree->t_edges[j]->bip_score; */
PhyML_Printf(".");
#ifndef QUIET
fflush(stdout);
#endif
if(!((replicate+1)%tree->io->boot_prog_every))
{
PhyML_Printf("] %4d/%4d\n ",replicate+1,tree->mod->bootstrap);
if(replicate != tree->mod->bootstrap-1) PhyML_Printf("[");
}
if(boot_tree->mat) Free_Mat(boot_tree->mat);
Free_Tree(boot_tree);
Free_Model(boot_mod);
}
if(((replicate)%tree->io->boot_prog_every)) PhyML_Printf("] %4d/%4d\n ",replicate,tree->mod->bootstrap);
tree->lock_topo = 1; /* Topology should not be modified afterwards */
if(tree->io->print_boot_trees)
{
fclose(tree->io->fp_out_boot_tree);
fclose(tree->io->fp_out_boot_stats);
}
Free_Cseq(boot_data);
Free(site_num);
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void Br_Len_Involving_Invar(t_tree *tree)
{
int i;
For(i,2*tree->n_otu-3) tree->t_edges[i]->l *= (1.0-tree->mod->pinvar->v);
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void Br_Len_Not_Involving_Invar(t_tree *tree)
{
int i;
For(i,2*tree->n_otu-3) tree->t_edges[i]->l /= (1.0-tree->mod->pinvar->v);
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void Getstring_Stdin(char *s)
{
if(!fgets(s,T_MAX_LINE,stdin)) Exit("");
if (strchr(s, '\n') != NULL)
*strchr(s, '\n') = '\0';
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void Print_Freq(t_tree *tree)
{
switch(tree->io->datatype)
{
case NT:
{
PhyML_Printf("A : %f\n",tree->mod->pi->v[0]);
PhyML_Printf("C : %f\n",tree->mod->pi->v[1]);
PhyML_Printf("G : %f\n",tree->mod->pi->v[2]);
PhyML_Printf("T : %f\n",tree->mod->pi->v[3]);
PhyML_Printf("U : %f\n",tree->mod->pi->v[4]);
PhyML_Printf("M : %f\n",tree->mod->pi->v[5]);
PhyML_Printf("R : %f\n",tree->mod->pi->v[6]);
PhyML_Printf("W : %f\n",tree->mod->pi->v[7]);
PhyML_Printf("S : %f\n",tree->mod->pi->v[8]);
PhyML_Printf("Y : %f\n",tree->mod->pi->v[9]);
PhyML_Printf("K : %f\n",tree->mod->pi->v[10]);
PhyML_Printf("B : %f\n",tree->mod->pi->v[11]);
PhyML_Printf("D : %f\n",tree->mod->pi->v[12]);
PhyML_Printf("H : %f\n",tree->mod->pi->v[13]);
PhyML_Printf("V : %f\n",tree->mod->pi->v[14]);
PhyML_Printf("N : %f\n",tree->mod->pi->v[15]);
break;
}
case AA:
{
PhyML_Printf("A : %f\n",tree->mod->pi->v[0]);
PhyML_Printf("R : %f\n",tree->mod->pi->v[1]);
PhyML_Printf("N : %f\n",tree->mod->pi->v[2]);
PhyML_Printf("D : %f\n",tree->mod->pi->v[3]);
PhyML_Printf("C : %f\n",tree->mod->pi->v[4]);
PhyML_Printf("Q : %f\n",tree->mod->pi->v[5]);
PhyML_Printf("E : %f\n",tree->mod->pi->v[6]);
PhyML_Printf("G : %f\n",tree->mod->pi->v[7]);
PhyML_Printf("H : %f\n",tree->mod->pi->v[8]);
PhyML_Printf("I : %f\n",tree->mod->pi->v[9]);
PhyML_Printf("L : %f\n",tree->mod->pi->v[10]);
PhyML_Printf("K : %f\n",tree->mod->pi->v[11]);
PhyML_Printf("M : %f\n",tree->mod->pi->v[12]);
PhyML_Printf("F : %f\n",tree->mod->pi->v[13]);
PhyML_Printf("P : %f\n",tree->mod->pi->v[14]);
PhyML_Printf("S : %f\n",tree->mod->pi->v[15]);
PhyML_Printf("T : %f\n",tree->mod->pi->v[16]);
PhyML_Printf("W : %f\n",tree->mod->pi->v[17]);
PhyML_Printf("Y : %f\n",tree->mod->pi->v[18]);
PhyML_Printf("V : %f\n",tree->mod->pi->v[19]);
PhyML_Printf("N : %f\n",tree->mod->pi->v[20]);
break;
}
default : {break;}
}
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
phydbl Num_Derivatives_One_Param(phydbl (*func)(t_tree *tree), t_tree *tree,
phydbl f0, phydbl *param, phydbl stepsize,
phydbl *err, int precise)
{
int i,j;
phydbl errt,fac,hh,**a,ans;
int n_iter;
a = (phydbl **)mCalloc(11,sizeof(phydbl *));
For(i,11) a[i] = (phydbl *)mCalloc(11,sizeof(phydbl));
n_iter = 10; /* */
ans = .0;
if(stepsize < SMALL) Warn_And_Exit("\n. h must be nonzero in Dfridr.");
hh=stepsize;
if(!precise)
{
*param = *param+hh;
a[0][0] = (*func)(tree);
/* printf("\n. f0=%f f1=%f hh=%G",f0,a[0][0],hh); */
a[0][0] -= f0;
a[0][0] /= hh;
*param = *param-hh;
ans = a[0][0];
}
else
{
*param = *param+hh;
a[0][0] = (*func)(tree);
/* *param = *param-2*hh; */
/* a[0][0] -= (*func)(tree); */
/* a[0][0] /= (2.0*hh); */
/* *param = *param+hh; */
a[0][0] -= f0;
a[0][0] /= hh;
*param = *param-hh;
*err=1e30;
for(i=1;i= 2.0*(*err)) break;
}
}
For(i,11) Free(a[i]);
Free(a);
return ans;
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
int Num_Derivative_Several_Param(t_tree *tree, phydbl *param, int n_param, phydbl stepsize,
phydbl (*func)(t_tree *tree), phydbl *derivatives)
{
int i;
phydbl err,f0;
f0 = (*func)(tree);
For(i,n_param)
{
derivatives[i] = Num_Derivatives_One_Param(func,
tree,
f0,
param+i,
stepsize,
&err,
0
);
}
return 1;
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
int Compare_Two_States(char *state1, char *state2, int state_size)
{
/* 1 the two states are identical */
/* 0 the two states are different */
int i;
For(i,state_size) if(state1[i] != state2[i]) break;
return (i==state_size)?(1):(0);
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void Copy_One_State(char *from, char *to, int state_size)
{
int i;
For(i,state_size) to[i] = from[i];
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void Make_Custom_Model(model *mod)
{
mod->rr->v = (phydbl *)mCalloc(mod->ns*(mod->ns-1)/2,sizeof(phydbl));
mod->rr_val->v = (phydbl *)mCalloc(mod->ns*(mod->ns-1)/2,sizeof(phydbl));
mod->rr_num->v = (int *)mCalloc(mod->ns*(mod->ns-1)/2,sizeof(int *));
mod->n_rr_per_cat->v = (int *)mCalloc(mod->ns*(mod->ns-1)/2,sizeof(int));
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
model *Make_Model_Basic()
{
model *mod;
mod = (model *)mCalloc(1,sizeof(model));
mod->modelname = (char *)mCalloc(T_MAX_NAME,sizeof(char));
mod->custom_mod_string = (char *)mCalloc(T_MAX_OPTION,sizeof(char));
mod->pi = (vect_dbl *)mCalloc(1,sizeof(vect_dbl));
Init_Vect_Dbl(0,mod->pi);
mod->pi_unscaled = (vect_dbl *)mCalloc(1,sizeof(vect_dbl));
Init_Vect_Dbl(0,mod->pi_unscaled);
mod->gamma_r_proba = (vect_dbl *)mCalloc(1,sizeof(vect_dbl));
Init_Vect_Dbl(0,mod->gamma_r_proba);
mod->gamma_r_proba_unscaled = (vect_dbl *)mCalloc(1,sizeof(vect_dbl));
Init_Vect_Dbl(0,mod->gamma_r_proba_unscaled);
mod->gamma_rr = (vect_dbl *)mCalloc(1,sizeof(vect_dbl));
Init_Vect_Dbl(0,mod->gamma_rr);
mod->gamma_rr_unscaled = (vect_dbl *)mCalloc(1,sizeof(vect_dbl));
Init_Vect_Dbl(0,mod->gamma_rr_unscaled);
mod->rr = (vect_dbl *)mCalloc(1,sizeof(vect_dbl));
Init_Vect_Dbl(0,mod->rr);
mod->rr_val = (vect_dbl *)mCalloc(1,sizeof(vect_dbl));
Init_Vect_Dbl(0,mod->rr_val);
mod->Pij_rr = (vect_dbl *)mCalloc(1,sizeof(vect_dbl));
Init_Vect_Dbl(0,mod->Pij_rr);
mod->user_b_freq = (vect_dbl *)mCalloc(1,sizeof(vect_dbl));
Init_Vect_Dbl(0,mod->user_b_freq);
mod->qmat = (vect_dbl *)mCalloc(1,sizeof(vect_dbl));
Init_Vect_Dbl(0,mod->qmat);
mod->qmat_buff = (vect_dbl *)mCalloc(1,sizeof(vect_dbl));
Init_Vect_Dbl(0,mod->qmat_buff);
mod->rr_num = (vect_int *)mCalloc(1,sizeof(vect_int));
Init_Vect_Int(0,mod->rr_num);
mod->n_rr_per_cat = (vect_int *)mCalloc(1,sizeof(vect_int));
Init_Vect_Int(0,mod->n_rr_per_cat);
mod->kappa = (scalar_dbl *)mCalloc(1,sizeof(scalar_dbl));
Init_Scalar_Dbl(mod->kappa);
mod->lambda = (scalar_dbl *)mCalloc(1,sizeof(scalar_dbl));
Init_Scalar_Dbl(mod->lambda);
mod->alpha = (scalar_dbl *)mCalloc(1,sizeof(scalar_dbl));
Init_Scalar_Dbl(mod->alpha);
mod->pinvar = (scalar_dbl *)mCalloc(1,sizeof(scalar_dbl));
Init_Scalar_Dbl(mod->pinvar);
mod->alpha_old = (scalar_dbl *)mCalloc(1,sizeof(scalar_dbl));
Init_Scalar_Dbl(mod->alpha_old);
mod->kappa_old = (scalar_dbl *)mCalloc(1,sizeof(scalar_dbl));
Init_Scalar_Dbl(mod->kappa_old);
mod->lambda_old = (scalar_dbl *)mCalloc(1,sizeof(scalar_dbl));
Init_Scalar_Dbl(mod->lambda_old);
mod->pinvar_old = (scalar_dbl *)mCalloc(1,sizeof(scalar_dbl));
Init_Scalar_Dbl(mod->pinvar_old);
mod->br_len_multiplier = (scalar_dbl *)mCalloc(1,sizeof(scalar_dbl));
Init_Scalar_Dbl(mod->br_len_multiplier);
mod->mr = (scalar_dbl *)mCalloc(1,sizeof(scalar_dbl));
Init_Scalar_Dbl(mod->mr);
mod->user_b_freq->v = (phydbl *)mCalloc(T_MAX_OPTION,sizeof(phydbl));
return mod;
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void Make_Model_Complete(model *mod)
{
int i;
if(mod->use_m4mod == YES)
{
M4_Make_Complete(mod->m4mod->n_h,mod->m4mod->n_o,mod->m4mod);
mod->ns = mod->m4mod->n_o * mod->m4mod->n_h;
}
mod->pi->v = (phydbl *)mCalloc(mod->ns,sizeof(phydbl));
mod->pi_unscaled->v = (phydbl *)mCalloc(mod->ns,sizeof(phydbl));
mod->Pij_rr->v = (phydbl *)mCalloc(mod->n_catg*mod->ns*mod->ns,sizeof(phydbl));
mod->gamma_r_proba->v = (phydbl *)mCalloc(mod->n_catg,sizeof(phydbl));
mod->gamma_r_proba_unscaled->v = (phydbl *)mCalloc(mod->n_catg,sizeof(phydbl));
mod->gamma_rr->v = (phydbl *)mCalloc(mod->n_catg,sizeof(phydbl));
mod->gamma_rr_unscaled->v = (phydbl *)mCalloc(mod->n_catg,sizeof(phydbl));
mod->qmat->v = (phydbl *)mCalloc(mod->ns*mod->ns,sizeof(phydbl));
mod->qmat_buff->v = (phydbl *)mCalloc(mod->ns*mod->ns,sizeof(phydbl));
mod->eigen = (eigen *)Make_Eigen_Struct(mod->ns);
For(i,mod->n_catg) mod->gamma_rr->v[i] = 1.0;
For(i,mod->n_catg) mod->gamma_r_proba_unscaled->v[i] = 1.0;
For(i,mod->n_catg) mod->gamma_r_proba->v[i] = 1.0/(phydbl)mod->n_catg;
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void Copy_Dist(phydbl **cpy, phydbl **orig, int n)
{
int i,j;
For(i,n) For(j,n) cpy[i][j] = orig[i][j];
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
model *Copy_Model(model *ori)
{
model *cpy;
cpy = Make_Model_Basic();
cpy->ns = ori->ns;
cpy->n_catg = ori->n_catg;
Make_Model_Complete(cpy);
if((ori->whichmodel == GTR) || (ori->whichmodel == CUSTOM)) Make_Custom_Model(cpy);
Record_Model(ori,cpy);
cpy->m4mod = M4_Copy_M4_Model(ori, ori->m4mod);
return cpy;
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void Record_Model(model *ori, model *cpy)
{
int i;
cpy->ns = ori->ns;
cpy->n_catg = ori->n_catg;
cpy->pi->reflect = ori->pi->reflect;
cpy->pi_unscaled->reflect = ori->pi_unscaled->reflect;
cpy->gamma_r_proba->reflect = ori->gamma_r_proba->reflect;
cpy->gamma_r_proba_unscaled->reflect = ori->gamma_r_proba_unscaled->reflect;
cpy->gamma_rr->reflect = ori->gamma_rr->reflect;
cpy->gamma_rr_unscaled->reflect = ori->gamma_rr_unscaled->reflect;
cpy->kappa->reflect = ori->kappa->reflect ;
cpy->lambda->reflect = ori->lambda->reflect ;
cpy->alpha->reflect = ori->alpha->reflect ;
cpy->pinvar->reflect = ori->pinvar->reflect ;
cpy->alpha_old->reflect = ori->alpha_old->reflect ;
cpy->kappa_old->reflect = ori->kappa_old->reflect ;
cpy->lambda_old->reflect = ori->lambda_old->reflect ;
cpy->pinvar_old->reflect = ori->pinvar_old->reflect ;
cpy->br_len_multiplier->reflect = ori->br_len_multiplier->reflect ;
cpy->rr->reflect = ori->rr->reflect ;
cpy->rr_val->reflect = ori->rr_val->reflect ;
cpy->rr_num->reflect = ori->rr_num->reflect ;
cpy->n_rr_per_cat->reflect = ori->n_rr_per_cat->reflect ;
cpy->Pij_rr->reflect = ori->Pij_rr->reflect ;
cpy->mr->reflect = ori->mr->reflect ;
cpy->user_b_freq->reflect = ori->user_b_freq->reflect ;
cpy->qmat->reflect = ori->qmat->reflect ;
cpy->qmat_buff->reflect = ori->qmat_buff->reflect ;
cpy->eigen->reflect = ori->eigen->reflect;
if(cpy->alpha_old->reflect == YES) { cpy->alpha_old->v = ori->alpha_old->v;}
if(cpy->kappa_old->reflect == YES) { cpy->kappa_old->v = ori->alpha_old->v;}
if(cpy->lambda_old->reflect == YES) { cpy->lambda_old->v = ori->lambda_old->v;}
if(cpy->pinvar_old->reflect == YES) { cpy->pinvar_old->v = ori->pinvar_old->v;}
if(cpy->kappa->reflect == YES) { cpy->kappa->v = ori->kappa->v;}
if(cpy->alpha->reflect == YES) { cpy->alpha->v = ori->alpha->v;}
if(cpy->lambda->reflect == YES) { cpy->lambda->v = ori->lambda->v;}
if(cpy->pinvar->reflect == YES) { cpy->pinvar->v = ori->pinvar->v;}
if(cpy->br_len_multiplier->reflect == YES) { cpy->br_len_multiplier->v = ori->br_len_multiplier->v;}
strcpy(cpy->modelname,ori->modelname);
strcpy(cpy->custom_mod_string,ori->custom_mod_string);
cpy->mod_num = ori->mod_num;
cpy->whichmodel = ori->whichmodel;
cpy->update_eigen = ori->update_eigen;
cpy->bootstrap = ori->bootstrap;
cpy->invar = ori->invar;
cpy->n_diff_rr = ori->n_diff_rr;
cpy->l_min = ori->l_min;
cpy->l_max = ori->l_max;
cpy->log_l = ori->log_l;
cpy->free_mixt_rates = ori->free_mixt_rates;
cpy->state_len = ori->state_len;
cpy->gamma_median = ori->gamma_median;
cpy->prob = ori->prob;
cpy->unscaled_prob = ori->unscaled_prob;
if((ori->whichmodel == CUSTOM) || (ori->whichmodel == GTR))
{
For(i,ori->ns*(ori->ns-1)/2)
{
if(cpy->rr_num->reflect == YES) cpy->rr_num->v[i] = ori->rr_num->v[i];
if(cpy->rr_val->reflect == YES) cpy->rr_val->v[i] = ori->rr_val->v[i];
if(cpy->rr->reflect == YES) cpy->rr->v[i] = ori->rr->v[i];
if(cpy->n_rr_per_cat->reflect == YES) cpy->n_rr_per_cat->v[i] = ori->n_rr_per_cat->v[i];
}
}
For(i,cpy->ns)
{
if(cpy->pi->reflect == YES) cpy->pi->v[i] = ori->pi->v[i];
if(cpy->pi_unscaled->reflect == YES) cpy->pi_unscaled->v[i] = ori->pi_unscaled->v[i];
if(cpy->user_b_freq->reflect == YES) cpy->user_b_freq->v[i] = ori->user_b_freq->v[i];
}
if(cpy->qmat->reflect == YES)
For(i,cpy->ns*cpy->ns) cpy->qmat->v[i] = ori->qmat->v[i];
For(i,cpy->n_catg)
{
if(cpy->gamma_r_proba->reflect == YES) cpy->gamma_r_proba->v[i] = ori->gamma_r_proba->v[i];
if(cpy->gamma_rr->reflect == YES) cpy->gamma_rr->v[i] = ori->gamma_rr->v[i];
if(cpy->gamma_r_proba_unscaled->reflect == YES) cpy->gamma_r_proba_unscaled->v[i] = ori->gamma_r_proba_unscaled->v[i];
if(cpy->gamma_rr_unscaled->reflect == YES) cpy->gamma_rr_unscaled->v[i] = ori->gamma_rr_unscaled->v[i];
}
cpy->use_m4mod = ori->use_m4mod;
if(cpy->eigen->reflect)
{
cpy->eigen->size = ori->eigen->size;
For(i,2*ori->ns) cpy->eigen->space[i] = ori->eigen->space[i];
For(i,2*ori->ns) cpy->eigen->space_int[i] = ori->eigen->space_int[i];
For(i,ori->ns) cpy->eigen->e_val[i] = ori->eigen->e_val[i];
For(i,ori->ns) cpy->eigen->e_val_im[i] = ori->eigen->e_val_im[i];
For(i,ori->ns*ori->ns) cpy->eigen->r_e_vect[i] = ori->eigen->r_e_vect[i];
For(i,ori->ns*ori->ns) cpy->eigen->r_e_vect[i] = ori->eigen->r_e_vect[i];
For(i,ori->ns*ori->ns) cpy->eigen->r_e_vect_im[i] = ori->eigen->r_e_vect_im[i];
For(i,ori->ns*ori->ns) cpy->eigen->l_e_vect[i] = ori->eigen->l_e_vect[i];
For(i,ori->ns*ori->ns) cpy->eigen->q[i] = ori->eigen->q[i];
}
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
option *Make_Input()
{
int i;
option* io = (option *)mCalloc(1,sizeof(option));
io->in_align_file = (char *)mCalloc(T_MAX_FILE,sizeof(char));
io->in_tree_file = (char *)mCalloc(T_MAX_FILE,sizeof(char));
io->in_constraint_tree_file = (char *)mCalloc(T_MAX_FILE,sizeof(char));
io->out_tree_file = (char *)mCalloc(T_MAX_FILE,sizeof(char));
io->out_trees_file = (char *)mCalloc(T_MAX_FILE,sizeof(char));
io->out_boot_tree_file = (char *)mCalloc(T_MAX_FILE,sizeof(char));
io->out_boot_stats_file = (char *)mCalloc(T_MAX_FILE,sizeof(char));
io->out_stats_file = (char *)mCalloc(T_MAX_FILE,sizeof(char));
io->out_lk_file = (char *)mCalloc(T_MAX_FILE,sizeof(char));
io->out_ps_file = (char *)mCalloc(T_MAX_FILE,sizeof(char));
io->out_trace_file = (char *)mCalloc(T_MAX_FILE,sizeof(char));
io->nt_or_cd = (char *)mCalloc(T_MAX_FILE,sizeof(char));
io->run_id_string = (char *)mCalloc(T_MAX_OPTION,sizeof(char));
io->clade_list_file = (char *)mCalloc(T_MAX_FILE,sizeof(char));
io->aa_rate_mat_file = (char *)mCalloc(T_MAX_FILE,sizeof(char));
io->alphabet = (char **)mCalloc(T_MAX_ALPHABET,sizeof(char *));
For(i,T_MAX_ALPHABET) io->alphabet[i] = (char *)mCalloc(T_MAX_STATE,sizeof(char ));
io->treelist = (t_treelist *)mCalloc(1,sizeof(t_treelist));
io->mcmc = (t_mcmc *)MCMC_Make_MCMC_Struct();
io->rates = (t_rate *)RATES_Make_Rate_Struct(-1);
return io;
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void Set_Defaults_Input(option* io)
{
io->fp_in_align = NULL;
io->fp_in_tree = NULL;
io->fp_in_constraint_tree = NULL;
io->fp_out_tree = NULL;
io->fp_out_trees = NULL;
io->fp_out_boot_tree = NULL;
io->fp_out_boot_stats = NULL;
io->fp_out_stats = NULL;
io->long_tax_names = NULL;
io->short_tax_names = NULL;
io->lon = NULL;
io->lat = NULL;
io->z_scores = NULL;
io->cstr_tree = NULL;
io->tree = NULL;
io->mod = NULL;
strcpy(io->nt_or_cd,"nucleotides");
io->n_data_sets = 1;
io->interleaved = 1;
io->in_tree = 0;
io->out_tree_file_open_mode = 1;
io->out_stats_file_open_mode = 1;
io->init_len = -1;
io->n_otu = -1;
io->n_data_set_asked = -1;
io->print_boot_trees = 1;
io->n_part = 1;
io->ratio_test = 4;
io->multigene = 0;
io->config_multigene = 0;
io->curr_interface = 0;
io->r_seed = -1;
io->collapse_boot = 0;
io->random_boot_seq_order = 1;
io->print_trace = 0;
io->print_site_lnl = 0;
io->m4_model = NO;
io->rm_ambigu = 0;
io->appebr_run_ID = 0;
io->quiet = 0;
io->datatype = NT;
io->colalias = YES;
io->data_file_format = PHYLIP;
io->tree_file_format = PHYLIP;
io->boot_prog_every = 20;
io->mem_question = YES;
io->do_alias_subpatt = NO;
io->lk_approx = EXACT;
io->codpos = -1;
io->mutmap = NO;
MCMC_Init_MCMC_Struct(NULL,io,io->mcmc);
RATES_Init_Rate_Struct(io->rates,NULL,-1);
io->rates->model = GUINDON;
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void Set_Defaults_Model(model *mod)
{
strcpy(mod->modelname,"HKY85");
strcpy(mod->custom_mod_string,"000000");
mod->nextmod = NULL;
mod->whichmodel = HKY85;
mod->n_catg = 4;
mod->prob = 1.0;
mod->unscaled_prob = 1.0;
mod->mod_num = 0;
mod->kappa->v = 4.0;
mod->alpha->v = 1.0;
mod->lambda->v = 1.0;
mod->pinvar->v = 0.0;
mod->kappa_old->v = 4.0;
mod->alpha_old->v = 1.0;
mod->lambda_old->v = 1.0;
mod->pinvar_old->v = 0.0;
mod->bootstrap = 0;
mod->invar = NO;
mod->ns = 4;
mod->n_diff_rr = 0;
mod->use_m4mod = NO;
mod->gamma_median = 0;
mod->state_len = 1;
mod->m4mod = NULL;
mod->rr->v = NULL;
mod->rr_val->v = NULL;
mod->n_rr_per_cat->v = NULL;
mod->io = NULL;
mod->log_l = NO;
mod->free_mixt_rates = NO;
mod->gamma_mgf_bl = NO;
mod->br_len_multiplier->v = 1.0;
mod->prob = 0.0;
#ifndef PHYTIME
mod->l_min = 1.E-8;
mod->l_max = 100.0;
#else
mod->l_min = 1.E-8;
mod->l_max = 2.0;
#endif
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void Set_Defaults_Optimiz(optimiz *s_opt)
{
s_opt->print = 1;
s_opt->last_opt = 1;
s_opt->opt_subst_param = 1;
s_opt->opt_alpha = 1;
s_opt->opt_kappa = 1;
s_opt->opt_bl = 1;
s_opt->opt_lambda = 0;
s_opt->opt_pinvar = 0;
s_opt->opt_cov_delta = 0;
s_opt->opt_cov_alpha = 0;
s_opt->opt_cov_free_rates = 0;
s_opt->opt_rr = 0;
s_opt->init_lk = UNLIKELY;
s_opt->n_it_max = 1000;
s_opt->opt_topo = 1;
s_opt->topo_search = NNI_MOVE;
s_opt->random_input_tree = 0;
s_opt->n_rand_starts = 5;
s_opt->brent_it_max = 500;
s_opt->steph_spr = 1;
s_opt->user_state_freq = 0;
s_opt->min_diff_lk_local = 1.E-04;
s_opt->min_diff_lk_global = 1.E-03;
s_opt->min_diff_lk_move = 1.E-02;
s_opt->p_moves_to_examine = 0.15;
s_opt->fast_nni = 0;
s_opt->greedy = 0;
s_opt->general_pars = 0;
s_opt->tree_size_mult = 1;
s_opt->opt_five_branch = 1;
s_opt->pars_thresh = 5;
s_opt->hybrid_thresh = 0;
s_opt->quickdirty = 0;
s_opt->spr_pars = 1;
s_opt->spr_lnL = 0;
s_opt->min_depth_path = 0;
s_opt->max_depth_path = 20;
s_opt->deepest_path = 20;
s_opt->max_delta_lnL_spr = 50.;
s_opt->br_len_in_spr = 10;
s_opt->opt_free_mixt_rates = YES;
s_opt->constrained_br_len = NO;
s_opt->opt_gamma_br_len = NO;
s_opt->wim_n_rgrft = -1;
s_opt->wim_n_globl = -1;
s_opt->wim_max_dist = -1;
s_opt->wim_n_optim = -1;
s_opt->wim_n_best = -1;
s_opt->wim_inside_opt = 0;
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void Test_Node_Table_Consistency(t_tree *tree)
{
int i;
For(i,2*tree->n_otu-2)
{
if(tree->t_nodes[i]->num != i)
{
PhyML_Printf("\n. Node table is not consistent with node numbers.");
PhyML_Printf("\n. Err in file %s at line %d\n",__FILE__,__LINE__);
Warn_And_Exit("");
}
}
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void Get_Bip(t_node *a, t_node *d, t_tree *tree)
{
int i,j;
t_node *tmp;
int swapped;
if(d->tax)
{
if(d->common)
{
d->bip_node[0] = (t_node **)mCalloc(1,sizeof(t_node *));
d->bip_node[0][0] = d;
d->bip_size[0] = 1;
d->bip_size[1] = -1;
d->bip_size[2] = -1;
For(i,3)
{
if(a->v[i] == d)
{
a->bip_size[i] = 0;
For(j,tree->n_otu)
{
if(strcmp(tree->t_nodes[j]->name,d->name))
{
a->bip_node[i] = (t_node **)realloc(a->bip_node[i],(a->bip_size[i]+1)*sizeof(t_node *));
a->bip_node[i][a->bip_size[i]] = tree->t_nodes[j];
a->bip_size[i]++;
}
}
/* Sort bipartition */
do
{
swapped = NO;
For(j,a->bip_size[i]-1)
{
if(a->bip_node[i][j]->num > a->bip_node[i][j+1]->num)
{
swapped = YES;
tmp = a->bip_node[i][j];
a->bip_node[i][j] = a->bip_node[i][j+1];
a->bip_node[i][j+1] = tmp;
}
}
}while(swapped == YES);
break;
}
}
}
return;
}
else
{
int k;
int d_a;
d_a = -1;
For(i,3)
{
if(d->v[i] != a) Get_Bip(d,d->v[i],tree);
else if(d->v[i] == a) d_a = i;
}
d->bip_size[d_a] = 0;
For(i,3)
if(d->v[i] != a)
{
For(j,3)
{
if(d->v[i]->v[j] == d)
{
For(k,d->v[i]->bip_size[j])
{
d->bip_node[d_a] = (t_node **)realloc(d->bip_node[d_a],(d->bip_size[d_a]+1)*sizeof(t_node *));
d->bip_node[d_a][d->bip_size[d_a]] = d->v[i]->bip_node[j][k];
d->bip_size[d_a]++;
}
break;
}
}
}
do
{
swapped = NO;
For(j,d->bip_size[d_a]-1)
{
if(d->bip_node[d_a][j]->num > d->bip_node[d_a][j+1]->num)
{
swapped = YES;
tmp = d->bip_node[d_a][j];
d->bip_node[d_a][j] = d->bip_node[d_a][j+1];
d->bip_node[d_a][j+1] = tmp;
}
}
}while(swapped == YES);
For(i,3)
if(a->v[i] == d)
{
a->bip_size[i] = 0;
For(j,tree->n_otu)
{
For(k,d->bip_size[d_a])
{
if(d->bip_node[d_a][k] == tree->t_nodes[j])
break;
}
if((k == d->bip_size[d_a]) && (tree->t_nodes[j]->common))
{
a->bip_node[i] = (t_node **)realloc(a->bip_node[i],(a->bip_size[i]+1)*sizeof(t_node *));
a->bip_node[i][a->bip_size[i]] = tree->t_nodes[j];
a->bip_size[i]++;
}
}
do
{
swapped = NO;
For(j,a->bip_size[i]-1)
{
if(a->bip_node[i][j]->num > a->bip_node[i][j+1]->num)
{
swapped = YES;
tmp = a->bip_node[i][j];
a->bip_node[i][j] = a->bip_node[i][j+1];
a->bip_node[i][j+1] = tmp;
}
}
}while(swapped == YES);
if(a->bip_size[i] != tree->n_otu - d->bip_size[d_a])
{
PhyML_Printf("%d %d \n",a->bip_size[i],tree->n_otu - d->bip_size[d_a]);
Warn_And_Exit("\n. Problem in counting bipartitions \n");
}
break;
}
}
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void Alloc_Bip(t_tree *tree)
{
int i;
if(tree->has_bip) return;
tree->has_bip = YES;
For(i,2*tree->n_otu-2)
{
tree->t_nodes[i]->bip_size = (int *)mCalloc(3,sizeof(int));
tree->t_nodes[i]->bip_node = (t_node ***)mCalloc(3,sizeof(t_node **));
/* For(j,3) */
/* { */
/* tree->t_nodes[i]->bip_node[j] = (t_node **)mCalloc(tree->n_otu,sizeof(t_node *)); */
/* } */
}
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
int Sort_Phydbl_Increase(const void *a, const void *b)
{
if((*(phydbl *)(a)) <= (*(phydbl *)(b))) return -1;
else return 1;
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
int Sort_String(const void *a, const void *b)
{
return(strcmp((*(const char **)(a)), (*(const char **)(b))));
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
int Compare_Bip(t_tree *tree1, t_tree *tree2, int on_existing_edges_only)
{
int i,j,k;
t_edge *b1,*b2;
/* char **bip1,**bip2; */
/* int *bip1,*bip2; */
t_node **bip1, **bip2;
int bip_size1, bip_size2, bip_size;
int different,identical;
/* !!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!*/
/* WARNING: call Match_Tip_Numbers and Get_Bip before using this function. */
/* !!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!*/
identical = 0;
different = 0;
For(i,2*tree1->n_otu-3)
{
b1 = tree1->t_edges[i];
bip_size1 = MIN(b1->left->bip_size[b1->l_r],b1->rght->bip_size[b1->r_l]);
if(bip_size1 > 1 && ((on_existing_edges_only == YES && b1->does_exist) || (on_existing_edges_only == NO)))
{
For(j,2*tree2->n_otu-3)
{
b2 = tree2->t_edges[j];
bip_size2 = MIN(b2->left->bip_size[b2->l_r],b2->rght->bip_size[b2->r_l]);
if(bip_size2 > 1 && ((on_existing_edges_only == YES && b2->does_exist) || (on_existing_edges_only == NO)))
{
if(bip_size1 == bip_size2)
{
bip_size = bip_size1;
if(b1->left->bip_size[b1->l_r] == b1->rght->bip_size[b1->r_l])
{
/* if(b1->left->bip_name[b1->l_r][0][0] < b1->rght->bip_name[b1->r_l][0][0]) */
if(b1->left->bip_node[b1->l_r][0]->num < b1->rght->bip_node[b1->r_l][0]->num)
{
/* bip1 = b1->left->bip_name[b1->l_r]; */
bip1 = b1->left->bip_node[b1->l_r];
}
else
{
/* bip1 = b1->rght->bip_name[b1->r_l]; */
bip1 = b1->rght->bip_node[b1->r_l];
}
}
else if(b1->left->bip_size[b1->l_r] < b1->rght->bip_size[b1->r_l])
{
/* bip1 = b1->left->bip_name[b1->l_r]; */
bip1 = b1->left->bip_node[b1->l_r];
}
else
{
/* bip1 = b1->rght->bip_name[b1->r_l]; */
bip1 = b1->rght->bip_node[b1->r_l];
}
if(b2->left->bip_size[b2->l_r] == b2->rght->bip_size[b2->r_l])
{
/* if(b2->left->bip_name[b2->l_r][0][0] < b2->rght->bip_name[b2->r_l][0][0]) */
if(b2->left->bip_node[b2->l_r][0]->num < b2->rght->bip_node[b2->r_l][0]->num)
{
/* bip2 = b2->left->bip_name[b2->l_r]; */
bip2 = b2->left->bip_node[b2->l_r];
}
else
{
/* bip2 = b2->rght->bip_name[b2->r_l]; */
bip2 = b2->rght->bip_node[b2->r_l];
}
}
else if(b2->left->bip_size[b2->l_r] < b2->rght->bip_size[b2->r_l])
{
/* bip2 = b2->left->bip_name[b2->l_r]; */
bip2 = b2->left->bip_node[b2->l_r];
}
else
{
/* bip2 = b2->rght->bip_name[b2->r_l]; */
bip2 = b2->rght->bip_node[b2->r_l];
}
if(bip_size == 1) Warn_And_Exit("\n. Problem in Compare_Bip\n");
For(k,bip_size)
{
/* if(strcmp(bip1[k],bip2[k])) break; */
if(bip1[k]->num != bip2[k]->num) break;
}
if(k == bip_size) /* Branches b1 and b2 define the same bipartition */
{
b1->bip_score++;
b2->bip_score++;
identical++;
break;
}
else different++; // Bipartitions has identical size but distinct elements
}
else different++; // Biparition have different sizes
}
}
}
}
return different;
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
/* Modifiy the tip numbering in tree2 so that tips in
tree1 and tree2 corresponding to the same taxon name
also have the same tip numbering */
void Match_Tip_Numbers(t_tree *tree1, t_tree *tree2)
{
int i,j;
if(tree1->n_otu != tree2->n_otu)
{
PhyML_Printf("\n. tree1 and tree2 must have the same number of tips.");
/* Otherwise, if tree2->n_otu < tree->n_otu, then some tips in tree2
will have a number (->num) that is the same as the number of an
internal node in this tree */
PhyML_Printf("\n. Err in file %s at line %d\n",__FILE__,__LINE__);
Warn_And_Exit("");
}
For(i,tree1->n_otu)
{
For(j,tree2->n_otu)
{
if(!strcmp(tree1->t_nodes[i]->name,tree2->t_nodes[j]->name))
{
tree2->t_nodes[j]->num = tree1->t_nodes[i]->num;
break;
}
}
}
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void Test_Multiple_Data_Set_Format(option *io)
{
char *line;
line = (char *)mCalloc(T_MAX_LINE,sizeof(char));
io->n_trees = 0;
while(fgets(line,T_MAX_LINE,io->fp_in_tree)) if(strstr(line,";")) io->n_trees++;
Free(line);
if((io->mod->bootstrap > 1) && (io->n_trees > 1))
Warn_And_Exit("\n. Bootstrap option is not allowed with multiple input trees !\n");
rewind(io->fp_in_tree);
return;
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
int Are_Compatible(char *statea, char *stateb, int stepsize, int datatype)
{
int i,j;
char a,b;
if(datatype == NT)
{
For(i,stepsize)
{
a = statea[i];
For(j,stepsize)
{
b = stateb[j];
switch(a)
{
case 'A':
{
switch(b)
{
case 'A' :
case 'M' :
case 'R' :
case 'W' :
case 'D' :
case 'H' :
case 'V' :
case 'X' : {b=b; break;}
default : return 0;
}
break;
}
case 'G':
{
switch(b)
{
case 'G' :
case 'R' :
case 'S' :
case 'K' :
case 'B' :
case 'D' :
case 'V' :
case 'X' : {b=b; break;}
default : return 0;
}
break;
}
case 'C':
{
switch(b)
{
case 'C' :
case 'M' :
case 'S' :
case 'Y' :
case 'B' :
case 'H' :
case 'V' :
case 'X' : {b=b; break;}
default : return 0;
}
break;
}
case 'T':
{
switch(b)
{
case 'T' :
case 'W' :
case 'Y' :
case 'K' :
case 'B' :
case 'D' :
case 'H' :
case 'X' :
{b=b; break;}
default : return 0;
}
break;
}
case 'M' :
{
switch(b)
{
case 'M' :
case 'A' :
case 'C' :
case 'R' :
case 'W' :
case 'S' :
case 'Y' :
case 'B' :
case 'D' :
case 'H' :
case 'V' :
case 'X' :
{b=b; break;}
default : return 0;
}
break;
}
case 'R' :
{
switch(b)
{
case 'R' :
case 'A' :
case 'G' :
case 'M' :
case 'W' :
case 'S' :
case 'K' :
case 'B' :
case 'D' :
case 'H' :
case 'V' :
case 'X' : {b=b; break;}
default : return 0;
}
break;
}
case 'W' :
{
switch(b)
{
case 'W' :
case 'A' :
case 'T' :
case 'M' :
case 'R' :
case 'Y' :
case 'K' :
case 'B' :
case 'D' :
case 'H' :
case 'V' :
case 'X' : {b=b; break;}
default : return 0;
}
break;
}
case 'S' :
{
switch(b)
{
case 'S' :
case 'C' :
case 'G' :
case 'M' :
case 'R' :
case 'Y' :
case 'K' :
case 'B' :
case 'D' :
case 'H' :
case 'V' :
case 'X' : {b=b; break;}
default : return 0;
}
break;
}
case 'Y' :
{
switch(b)
{
case 'Y' :
case 'C' :
case 'T' :
case 'M' :
case 'W' :
case 'S' :
case 'K' :
case 'B' :
case 'D' :
case 'H' :
case 'V' :
case 'X' : {b=b; break;}
default : return 0;
}
break;
}
case 'K' :
{
switch(b)
{
case 'K' :
case 'G' :
case 'T' :
case 'R' :
case 'W' :
case 'S' :
case 'Y' :
case 'B' :
case 'D' :
case 'H' :
case 'V' :
case 'X' : {b=b; break;}
default : return 0;
}
break;
}
case 'B' :
{
switch(b)
{
case 'B' :
case 'C' :
case 'G' :
case 'T' :
case 'M' :
case 'R' :
case 'W' :
case 'S' :
case 'Y' :
case 'K' :
case 'D' :
case 'H' :
case 'V' :
case 'X' : {b=b; break;}
default : return 0;
}
break;
}
case 'D' :
{
switch(b)
{
case 'D' :
case 'A' :
case 'G' :
case 'T' :
case 'M' :
case 'R' :
case 'W' :
case 'S' :
case 'Y' :
case 'K' :
case 'B' :
case 'H' :
case 'V' :
case 'X' : {b=b; break;}
default : return 0;
}
break;
}
case 'H' :
{
switch(b)
{
case 'H' :
case 'A' :
case 'C' :
case 'T' :
case 'M' :
case 'R' :
case 'W' :
case 'S' :
case 'Y' :
case 'K' :
case 'B' :
case 'D' :
case 'V' :
case 'X' : {b=b; break;}
default : return 0;
}
break;
}
case 'V' :
{
switch(b)
{
case 'V' :
case 'A' :
case 'C' :
case 'G' :
case 'M' :
case 'R' :
case 'W' :
case 'S' :
case 'Y' :
case 'K' :
case 'B' :
case 'D' :
case 'H' :
case 'X' : {b=b; break;}
default : return 0;
}
break;
}
case 'X' :
{
switch(b)
{
case 'X' :
case 'A' :
case 'C' :
case 'G' :
case 'T' :
case 'M' :
case 'R' :
case 'W' :
case 'S' :
case 'Y' :
case 'K' :
case 'B' :
case 'D' :
case 'H' :
case 'V' : {b=b; break;}
default : return 0;
}
break;
}
default :
{
PhyML_Printf("\n. Err. in Are_Compatible\n");
PhyML_Printf("\n. Please check that characters `%c` and `%c`\n",a,b);
PhyML_Printf(" correspond to existing nucleotides.\n");
Warn_And_Exit("\n");
return 0;
}
}
}
}
}
else if(datatype == AA)
{
a = statea[0]; b = stateb[0];
switch(a)
{
case 'A' :
{
switch(b)
{
case 'A' :
case 'X' : {b=b; break;}
default : return 0;
}
break;
}
case 'R' :
{
switch(b)
{
case 'R' :
case 'X' : {b=b; break;}
default : return 0;
}
break;
}
case 'N' :
{
switch(b)
{
case 'N' :
case 'B' :
case 'X' : {b=b; break;}
default : return 0;
}
break;
}
case 'B' :
{
switch(b)
{
case 'N' :
case 'B' :
case 'X' : {b=b; break;}
default : return 0;
}
break;
}
case 'D' :
{
switch(b)
{
case 'D' :
case 'X' : {b=b; break;}
default : return 0;
}
break;
}
case 'C' :
{
switch(b)
{
case 'C' :
case 'X' : {b=b; break;}
default : return 0;
}
break;
}
case 'Q' :
{
switch(b)
{
case 'Q' :
case 'Z' :
case 'X' : {b=b; break;}
default : return 0;
}
break;
}
case 'Z' :
{
switch(b)
{
case 'Q' :
case 'Z' :
case 'X' : {b=b; break;}
default : return 0;
}
break;
}
case 'E' :
{
switch(b)
{
case 'E' :
case 'X' : {b=b; break;}
default : return 0;
}
break;
}
case 'G' :
{
switch(b)
{
case 'G' :
case 'X' : {b=b; break;}
default : return 0;
}
break;
}
case 'H' :
{
switch(b)
{
case 'H' :
case 'X' : {b=b; break;}
default : return 0;
}
break;
}
case 'I' :
{
switch(b)
{
case 'I' :
case 'X' : {b=b; break;}
default : return 0;
}
break;
}
case 'L' :
{
switch(b)
{
case 'L' :
case 'X' : {b=b; break;}
default : return 0;
}
break;
}
case 'K' :
{
switch(b)
{
case 'K' :
case 'X' : {b=b; break;}
default : return 0;
}
break;
}
case 'M' :
{
switch(b)
{
case 'M' :
case 'X' : {b=b; break;}
default : return 0;
}
break;
}
case 'F' :
{
switch(b)
{
case 'F' :
case 'X' : {b=b; break;}
default : return 0;
}
break;
}
case 'P' :
{
switch(b)
{
case 'P' :
case 'X' : {b=b; break;}
default : return 0;
}
break;
}
case 'S' :
{
switch(b)
{
case 'S' :
case 'X' : {b=b; break;}
default : return 0;
}
break;
}
case 'T' :
{
switch(b)
{
case 'T' :
case 'X' : {b=b; break;}
default : return 0;
}
break;
}
case 'W' :
{
switch(b)
{
case 'W' :
case 'X' : {b=b; break;}
default : return 0;
}
break;
}
case 'Y' :
{
switch(b)
{
case 'Y' :
case 'X' : {b=b; break;}
default : return 0;
}
break;
}
case 'V' :
{
switch(b)
{
case 'V' :
case 'X' : {b=b; break;}
default : return 0;
}
break;
}
case 'X' :
{
switch(b)
{
case 'A':case 'R':case 'N' :case 'B' :case 'D' :
case 'C':case 'Q':case 'Z' :case 'E' :case 'G' :
case 'H':case 'I':case 'L' :case 'K' :case 'M' :
case 'F':case 'P':case 'S' :case 'T' :case 'W' :
case 'Y':case 'V': case 'X' : {b=b; break;}
default : return 0;
}
break;
}
default :
{
PhyML_Printf("\n. Err. in Are_Compatible\n");
PhyML_Printf("\n. Please check that characters `%c` and `%c`\n",a,b);
PhyML_Printf(" correspond to existing amino-acids.\n");
Warn_And_Exit("\n");
return 0;
}
}
}
else if(datatype == GENERIC)
{
if(Is_Ambigu(statea,GENERIC,stepsize) || Is_Ambigu(stateb,GENERIC,stepsize)) return 1;
else
{
int a,b;
char format[6];
sprintf(format,"%%%dd",stepsize);
if(!sscanf(statea,format,&a))
{
PhyML_Printf("\n. statea = %s",statea);
PhyML_Printf("\n. Err in file %s at line %d\n",__FILE__,__LINE__);
Warn_And_Exit("");
}
if(!sscanf(stateb,format,&b))
{
PhyML_Printf("\n. statea = %s",stateb);
PhyML_Printf("\n. Err in file %s at line %d\n",__FILE__,__LINE__);
Warn_And_Exit("");
}
/* PhyML_Printf("\n. %s %d a=%d b=%d ",__FILE__,__LINE__,a,b); */
if(a == b) return 1;
}
return 0;
}
return 1;
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void Hide_Ambiguities(calign *data)
{
int i;
For(i,data->crunch_len) if(data->ambigu[i]) data->wght[i] = 0;
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void Copy_Tree(t_tree *ori, t_tree *cpy)
{
int i,j;
For(i,2*ori->n_otu-2)
{
For(j,3)
{
if(ori->t_nodes[i]->v[j])
{
cpy->t_nodes[i]->v[j] = cpy->t_nodes[ori->t_nodes[i]->v[j]->num];
cpy->t_nodes[i]->l[j] = ori->t_nodes[i]->l[j];
cpy->t_nodes[i]->b[j] = cpy->t_edges[ori->t_nodes[i]->b[j]->num];
}
else
{
cpy->t_nodes[i]->v[j] = NULL;
cpy->t_nodes[i]->b[j] = NULL;
}
}
}
For(i,2*ori->n_otu-3)
{
cpy->t_edges[i]->l = ori->t_edges[i]->l;
cpy->t_edges[i]->left = cpy->t_nodes[ori->t_edges[i]->left->num];
cpy->t_edges[i]->rght = cpy->t_nodes[ori->t_edges[i]->rght->num];
cpy->t_edges[i]->l_v1 = ori->t_edges[i]->l_v1;
cpy->t_edges[i]->l_v2 = ori->t_edges[i]->l_v2;
cpy->t_edges[i]->r_v1 = ori->t_edges[i]->r_v1;
cpy->t_edges[i]->r_v2 = ori->t_edges[i]->r_v2;
cpy->t_edges[i]->l_r = ori->t_edges[i]->l_r;
cpy->t_edges[i]->r_l = ori->t_edges[i]->r_l;
cpy->t_edges[i]->does_exist = ori->t_edges[i]->does_exist;
}
For(i,ori->n_otu)
{
cpy->t_nodes[i]->tax = YES;
if(!cpy->t_nodes[i]->name)
{
cpy->t_nodes[i]->name = (char *)mCalloc(strlen(ori->t_nodes[i]->name)+1,sizeof(char));
cpy->t_nodes[i]->ori_name = cpy->t_nodes[i]->name ;
}
strcpy(cpy->t_nodes[i]->name,ori->t_nodes[i]->name);
}
if(ori->n_root)
{
cpy->e_root = cpy->t_edges[ori->e_root->num];
cpy->n_root = cpy->t_nodes[ori->n_root->num];
Add_Root(cpy->e_root,cpy);
}
cpy->num_curr_branch_available = 0;
cpy->t_beg = ori->t_beg;
/* Connect_Edges_To_Nodes_Recur(cpy->t_nodes[0],cpy->t_nodes[0]->v[0],cpy); */
/* Update_Dirs(cpy); */
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void Prune_Subtree(t_node *a, t_node *d, t_edge **target, t_edge **residual, t_tree *tree)
{
t_node *v1, *v2;
t_edge *b1, *b2;
int dir_v1, dir_v2;
int i;
/* phydbl ***buff_p_lk; */
phydbl *buff_p_lk;
int *buff_scale;
int *buff_p_pars, *buff_pars, *buff_p_lk_loc, *buff_patt_id;
unsigned int *buff_ui;
short int *buff_p_lk_tip;
if(tree->nextree)
Prune_Subtree(tree->nextree->t_nodes[a->num],
tree->nextree->t_nodes[d->num],
tree->nextree->t_edges + (*target)->num,
tree->nextree->t_edges + (*residual)->num,
tree->nextree);
if(a->tax)
{
PhyML_Printf("\n. Err in file %s at line %d\n",__FILE__,__LINE__);
Warn_And_Exit("");
}
dir_v1 = dir_v2 = -1;
For(i,3)
{
if(a->v[i] != d)
{
if(dir_v1 < 0) dir_v1 = i;
else dir_v2 = i;
}
}
if(a->v[dir_v1]->num < a->v[dir_v2]->num)
{
v1 = a->v[dir_v1];
v2 = a->v[dir_v2];
b1 = a->b[dir_v1];
b2 = a->b[dir_v2];
}
else
{
v1 = a->v[dir_v2];
v2 = a->v[dir_v1];
b1 = a->b[dir_v2];
b2 = a->b[dir_v1];
}
if(v1->tax && v2->tax) PhyML_Printf("\n. Pruning is meaningless here.\n");
a->v[dir_v1] = NULL;
a->v[dir_v2] = NULL;
a->b[dir_v1] = NULL;
a->b[dir_v2] = NULL;
if(v1 == b1->left)
{
b1->rght = v2;
if(v2 == b2->left)
{
buff_p_lk = b1->p_lk_rght;
b1->p_lk_rght = b2->p_lk_left;
b2->p_lk_left = buff_p_lk;
buff_p_lk_tip = b1->p_lk_tip_r;
b1->p_lk_tip_r = b2->p_lk_tip_l;
b2->p_lk_tip_l = buff_p_lk_tip;
buff_scale = b1->sum_scale_rght;
b1->sum_scale_rght = b2->sum_scale_left;
b2->sum_scale_left = buff_scale;
buff_scale = b1->sum_scale_rght_cat;
b1->sum_scale_rght_cat = b2->sum_scale_left_cat;
b2->sum_scale_left_cat = buff_scale;
buff_pars = b1->pars_r;
b1->pars_r = b2->pars_l;
b2->pars_l = buff_pars;
buff_ui = b1->ui_r;
b1->ui_r = b2->ui_l;
b2->ui_l = buff_ui;
buff_p_pars = b1->p_pars_r;
b1->p_pars_r = b2->p_pars_l;
b2->p_pars_l = buff_p_pars;
buff_p_lk_loc = b1->p_lk_loc_rght;
b1->p_lk_loc_rght = b2->p_lk_loc_left;
b2->p_lk_loc_left = buff_p_lk_loc;
buff_patt_id = b1->patt_id_rght;
b1->patt_id_rght = b2->patt_id_left;
b2->patt_id_left = buff_patt_id;
}
else
{
buff_p_lk = b1->p_lk_rght; /* b1->p_lk_rght = NULL if b1->rght->tax */
b1->p_lk_rght = b2->p_lk_rght; /* b2->p_lk_rght = NULL if b2->rght->tax */
b2->p_lk_rght = buff_p_lk;
buff_p_lk_tip = b1->p_lk_tip_r;
b1->p_lk_tip_r = b2->p_lk_tip_r;
b2->p_lk_tip_r = buff_p_lk_tip;
buff_scale = b1->sum_scale_rght;
b1->sum_scale_rght = b2->sum_scale_rght;
b2->sum_scale_rght = buff_scale;
buff_pars = b1->pars_r;
b1->pars_r = b2->pars_r;
b2->pars_r = buff_pars;
buff_ui = b1->ui_r;
b1->ui_r = b2->ui_r;
b2->ui_r = buff_ui;
buff_p_pars = b1->p_pars_r;
b1->p_pars_r = b2->p_pars_r;
b2->p_pars_r = buff_p_pars;
buff_p_lk_loc = b1->p_lk_loc_rght;
b1->p_lk_loc_rght = b2->p_lk_loc_rght;
b2->p_lk_loc_rght = buff_p_lk_loc;
buff_patt_id = b1->patt_id_rght;
b1->patt_id_rght = b2->patt_id_rght;
b2->patt_id_rght = buff_patt_id;
}
}
else
{
b1->left = v2;
if(v2 == b2->left)
{
buff_p_lk = b1->p_lk_left;
b1->p_lk_left = b2->p_lk_left;
b2->p_lk_left = buff_p_lk;
buff_p_lk_tip = b1->p_lk_tip_l;
b1->p_lk_tip_l = b2->p_lk_tip_l;
b2->p_lk_tip_l = buff_p_lk_tip;
buff_scale = b1->sum_scale_left;
b1->sum_scale_left = b2->sum_scale_left;
b2->sum_scale_left = buff_scale;
buff_scale = b1->sum_scale_left_cat;
b1->sum_scale_left_cat = b2->sum_scale_left_cat;
b2->sum_scale_left_cat = buff_scale;
buff_pars = b1->pars_l;
b1->pars_l = b2->pars_l;
b2->pars_l = buff_pars;
buff_ui = b1->ui_l;
b1->ui_l = b2->ui_l;
b2->ui_l = buff_ui;
buff_p_pars = b1->p_pars_l;
b1->p_pars_l = b2->p_pars_l;
b2->p_pars_l = buff_p_pars;
buff_p_lk_loc = b1->p_lk_loc_left;
b1->p_lk_loc_left = b2->p_lk_loc_left;
b2->p_lk_loc_left = buff_p_lk_loc;
buff_patt_id = b1->patt_id_left;
b1->patt_id_left = b2->patt_id_left;
b2->patt_id_left = buff_patt_id;
}
else
{
buff_p_lk = b1->p_lk_left;
b1->p_lk_left = b2->p_lk_rght; /* b2->p_lk_rght = NULL if b2->rght->tax */
b2->p_lk_rght = buff_p_lk;
buff_p_lk_tip = b1->p_lk_tip_l;
b1->p_lk_tip_l = b2->p_lk_tip_r;
b2->p_lk_tip_r = buff_p_lk_tip;
buff_scale = b1->sum_scale_left;
b1->sum_scale_left = b2->sum_scale_rght;
b2->sum_scale_rght = buff_scale;
buff_scale = b1->sum_scale_left_cat;
b1->sum_scale_left_cat = b2->sum_scale_rght_cat;
b2->sum_scale_rght_cat = buff_scale;
buff_pars = b1->pars_l;
b1->pars_l = b2->pars_r;
b2->pars_r = buff_pars;
buff_ui = b1->ui_l;
b1->ui_l = b2->ui_r;
b2->ui_r = buff_ui;
buff_p_pars = b1->p_pars_l;
b1->p_pars_l = b2->p_pars_r;
b2->p_pars_r = buff_p_pars;
buff_p_lk_loc = b1->p_lk_loc_left;
b1->p_lk_loc_left = b2->p_lk_loc_rght;
b2->p_lk_loc_rght = buff_p_lk_loc;
buff_patt_id = b1->patt_id_left;
b1->patt_id_left = b2->patt_id_rght;
b2->patt_id_rght = buff_patt_id;
}
}
For(i,3)
if(v2->v[i] == a)
{
v2->v[i] = v1;
v2->b[i] = b1;
break;
}
#ifdef DEBUG
if(i == 3)
{
PhyML_Printf("\n. Err in file %s at line %d\n",__FILE__,__LINE__);
Warn_And_Exit("");
}
#endif
For(i,3)
if(v1->v[i] == a)
{
v1->v[i] = v2;
break;
}
#ifdef DEBUG
if(i == 3)
{
PhyML_Printf("\n. Err in file %s at line %d\n",__FILE__,__LINE__);
Warn_And_Exit("");
}
#endif
b1->l += b2->l;
(v1 == b1->left)?
(Make_Edge_Dirs(b1,v1,v2,tree)):
(Make_Edge_Dirs(b1,v2,v1,tree));
if(target) (*target) = b1;
if(residual) (*residual) = b2;
#ifdef DEBUG
if(b1->left->tax)
{
PhyML_Printf("\n. b1->left->num = %d",b1->left->num);
PhyML_Printf("\n. Err in file %s at line %d\n",__FILE__,__LINE__);
Warn_And_Exit("");
}
#endif
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void Graft_Subtree(t_edge *target, t_node *link, t_edge *residual, t_tree *tree)
{
t_node *v1, *v2;
int i, dir_v1, dir_v2;
phydbl *buff_p_lk;
int *buff_scale;
int *buff_p_pars, *buff_pars, *buff_p_lk_loc, *buff_patt_id;
short int *buff_p_lk_tip;
unsigned int *buff_ui;
t_edge *b_up;
if(tree->nextree) Graft_Subtree(tree->nextree->t_edges[target->num],
tree->nextree->t_nodes[link->num],
tree->nextree->t_edges[residual->num],
tree->nextree);
dir_v1 = dir_v2 = -1;
b_up = NULL;
For(i,3)
{
if(!link->v[i])
{
if(dir_v1 < 0) dir_v1 = i;
else dir_v2 = i;
}
else b_up = link->b[i];
}
if(target->left->num < target->rght->num)
{
v1 = target->left;
v2 = target->rght;
buff_p_lk = residual->p_lk_rght;
residual->p_lk_rght = target->p_lk_rght;
target->p_lk_rght = buff_p_lk;
buff_p_lk_tip = residual->p_lk_tip_r;
residual->p_lk_tip_r = target->p_lk_tip_r;
target->p_lk_tip_r = buff_p_lk_tip;
buff_scale = residual->sum_scale_rght;
residual->sum_scale_rght = target->sum_scale_rght;
target->sum_scale_rght = buff_scale;
buff_pars = residual->pars_r;
residual->pars_r = target->pars_r;
target->pars_r = buff_pars;
buff_ui = residual->ui_r;
residual->ui_r = target->ui_r;
target->ui_r = buff_ui;
buff_p_pars = residual->p_pars_r;
residual->p_pars_r = target->p_pars_r;
target->p_pars_r = buff_p_pars;
buff_p_lk_loc = residual->p_lk_loc_rght;
residual->p_lk_loc_rght = target->p_lk_loc_rght;
target->p_lk_loc_rght = buff_p_lk_loc;
buff_patt_id = residual->patt_id_rght;
residual->patt_id_rght = target->patt_id_rght;
target->patt_id_rght = buff_patt_id;
}
else
{
v1 = target->rght;
v2 = target->left;
buff_p_lk = residual->p_lk_rght;
residual->p_lk_rght = target->p_lk_left;
target->p_lk_left = buff_p_lk;
buff_p_lk_tip = residual->p_lk_tip_r;
residual->p_lk_tip_r = target->p_lk_tip_l;
target->p_lk_tip_l = buff_p_lk_tip;
buff_scale = residual->sum_scale_rght;
residual->sum_scale_rght = target->sum_scale_left;
target->sum_scale_left = buff_scale;
buff_scale = residual->sum_scale_rght_cat;
residual->sum_scale_rght_cat = target->sum_scale_left_cat;
target->sum_scale_left_cat = buff_scale;
buff_pars = residual->pars_r;
residual->pars_r = target->pars_l;
target->pars_l = buff_pars;
buff_ui = residual->ui_r;
residual->ui_r = target->ui_l;
target->ui_l = buff_ui;
buff_p_pars = residual->p_pars_r;
residual->p_pars_r = target->p_pars_l;
target->p_pars_l = buff_p_pars;
buff_p_lk_loc = residual->p_lk_loc_rght;
residual->p_lk_loc_rght = target->p_lk_loc_left;
target->p_lk_loc_left = buff_p_lk_loc;
buff_patt_id = residual->patt_id_rght;
residual->patt_id_rght = target->patt_id_left;
target->patt_id_left = buff_patt_id;
}
For(i,3)
if(v2->b[i] == target)
{
v2->v[i] = link;
v2->b[i] = residual;
break;
}
link->v[dir_v2] = v2;
link->b[dir_v2] = residual;
residual->left = link;
residual->rght = v2;
(v1 == target->left)?(target->rght = link):(target->left = link);
link->v[dir_v1] = v1;
link->b[dir_v1] = target;
For(i,3)
if(v1->v[i] == v2)
{
v1->v[i] = link;
break;
}
target->l /= 2.;
residual->l = target->l;
Make_Edge_Dirs(target,target->left,target->rght,tree);
Make_Edge_Dirs(residual,residual->left,residual->rght,tree);
Make_Edge_Dirs(b_up,b_up->left,b_up->rght,tree);
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void Reassign_Node_Nums(t_node *a, t_node *d, int *curr_ext_node, int *curr_int_node, t_tree *tree)
{
t_node *buff;
int i;
if(a->tax)
{
buff = tree->t_nodes[*curr_ext_node];
tree->t_nodes[*curr_ext_node] = a;
tree->t_nodes[a->num] = buff;
buff->num = a->num;
a->num = *curr_ext_node;
(*curr_ext_node)++;
}
if(d->tax)
{
buff = tree->t_nodes[*curr_ext_node];
tree->t_nodes[*curr_ext_node] = d;
tree->t_nodes[d->num] = buff;
buff->num = d->num;
d->num = *curr_ext_node;
(*curr_ext_node)++;
return;
}
else
{
buff = tree->t_nodes[*curr_int_node];
tree->t_nodes[*curr_int_node] = d;
tree->t_nodes[d->num] = buff;
buff->num = d->num;
d->num = *curr_int_node;
(*curr_int_node)++;
}
For(i,3)
{
if(d->v[i] != a)
Reassign_Node_Nums(d,d->v[i],curr_ext_node,curr_int_node,tree);
}
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void Reassign_Edge_Nums(t_node *a, t_node *d, int *curr_br, t_tree *tree)
{
t_edge *buff;
int i,j;
For(i,3)
if(a->v[i] == d)
{
buff = tree->t_edges[*curr_br];
For(j,2*N_MAX_OTU-3) if(tree->t_edges[j] == a->b[i]) break;
if(j == 2*N_MAX_OTU-3)
{
PhyML_Printf("\n. Err in file %s at line %d\n",__FILE__,__LINE__);
Warn_And_Exit("");
}
tree->t_edges[*curr_br] = a->b[i];
tree->t_edges[j] = buff;
a->b[i]->num = *curr_br;
(*curr_br)++;
break;
}
if(d->tax) return;
else
{
For(i,3)
if(d->v[i] != a)
Reassign_Edge_Nums(d,d->v[i],curr_br,tree);
}
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void Find_Mutual_Direction(t_node *n1, t_node *n2, short int *dir_n1_to_n2, short int *dir_n2_to_n1)
{
int scores[3][3];
int i,j,k,l;
if(n1 == n2) return;
For(i,3)
{
For(j,3)
{
scores[i][j] = 0;
For(k,n1->bip_size[i])
{
For(l,n2->bip_size[j])
{
if(n1->bip_node[i][k] == n2->bip_node[j][l])
{
scores[i][j]++;
break;
}
}
}
}
}
For(i,3)
{
For(j,3)
{
if(!scores[i][j])
{
*dir_n1_to_n2 = i;
*dir_n2_to_n1 = j;
return;
}
}
}
PhyML_Printf("\n. n1=%d n2=%d",n1->num,n2->num);
PhyML_Printf("\n. Err in file %s at line %d\n",__FILE__,__LINE__);
Warn_And_Exit("");
/* For(i,3) */
/* { */
/* n_zero_line = 0; */
/* For(j,3) */
/* { */
/* if(!scores[i][j]) n_zero_line++; */
/* } */
/* if(n_zero_line != 2) {*dir_n1_to_n2 = i; break;} */
/* } */
/* For(i,3) */
/* { */
/* n_zero_col = 0; */
/* For(j,3) */
/* { */
/* if(!scores[j][i]) n_zero_col++; */
/* } */
/* if(n_zero_col != 2) {*dir_n2_to_n1 = i; break;} */
/* } */
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void Update_Dir_To_Tips(t_node *a, t_node *d, t_tree *tree)
{
int i,j,k;
short int *inout;
int d_a;
int dim;
dim = 2*tree->n_otu-2;
inout = (short int *)mCalloc(tree->n_otu,sizeof(short int));
For(i,3)
{
if(a->v[i] == d)
{
For(j,tree->n_otu) inout[j] = 1;
For(k,a->bip_size[i]) inout[a->bip_node[i][k]->num] = 0;
For(j,tree->n_otu) if(inout[tree->t_nodes[j]->num]) tree->t_dir[a->num*dim+tree->t_nodes[j]->num] = i;
break;
}
}
if(!d->tax)
{
d_a = -1;
For(i,3)
{
if(d->v[i] != a) Update_Dir_To_Tips(d,d->v[i],tree);
else if(d->v[i] == a) d_a = i;
}
For(j,tree->n_otu) inout[j] = 1;
For(k,d->bip_size[d_a]) inout[d->bip_node[d_a][k]->num] = 0;
For(j,tree->n_otu) if(inout[tree->t_nodes[j]->num]) tree->t_dir[d->num*dim+tree->t_nodes[j]->num] = d_a;
}
Free(inout);
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void Fill_Dir_Table(t_tree *tree)
{
int i,j;
int dim;
dim = 2*tree->n_otu-2;
For(i,dim*dim) tree->t_dir[i] = 0;
Free_Bip(tree);
Alloc_Bip(tree);
Get_Bip(tree->t_nodes[0],tree->t_nodes[0]->v[0],tree);
Update_Dir_To_Tips(tree->t_nodes[0],tree->t_nodes[0]->v[0],tree);
for(i=tree->n_otu;i<2*tree->n_otu-2;i++)
for(j=i;j<2*tree->n_otu-2;j++)
{
Find_Mutual_Direction(tree->t_nodes[i],tree->t_nodes[j],
&(tree->t_dir[i*dim+j]),
&(tree->t_dir[j*dim+i]));
}
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
int Get_Subtree_Size(t_node *a, t_node *d)
{
int size,i;
if(d->tax) return 1;
else
{
size = 0;
For(i,3)
if(d->v[i] != a)
size += Get_Subtree_Size(d,d->v[i]);
}
return size;
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void Fast_Br_Len(t_edge *b, t_tree *tree, int approx)
{
phydbl sum;
phydbl *prob, *F;
int i, j, k, site;
phydbl v_rght;
int dim1,dim2,dim3;
phydbl eps_bl,old_l,new_l;
int n_iter;
phydbl scale_rght;
/* Br_Len_Brent(0.02*b->l,b->l,50.*b->l, */
/* tree->mod->s_opt->min_diff_lk_local, */
/* b,tree, */
/* tree->mod->s_opt->brent_it_max, */
/* tree->mod->s_opt->quickdirty); */
/* return; */
n_iter = 0;
dim1 = tree->mod->ns * tree->mod->n_catg;
dim2 = tree->mod->ns ;
dim3 = tree->mod->ns * tree->mod->ns;
eps_bl = tree->mod->l_min;
F = tree->triplet_struct->F_bc;
prob = tree->triplet_struct->F_cd;
Update_PMat_At_Given_Edge(b,tree);
For(i,dim1*dim2) F[i] = .0;
For(site,tree->n_pattern)
{
/* Joint probabilities of the states at the two ends of the t_edge */
v_rght = -1.;
For(i,tree->mod->ns)
{
For(j,tree->mod->ns)
{
For(k,tree->mod->n_catg)
{
v_rght = (b->rght->tax)?((phydbl)(b->p_lk_tip_r[site*dim2+j])):(b->p_lk_rght[site*dim1+k*dim2+j]);
scale_rght = (b->rght->tax)?(0.0):(b->sum_scale_rght[k*tree->n_pattern+site]);
prob[dim3*k+dim2*i+j] =
tree->mod->gamma_r_proba->v[k] *
tree->mod->pi->v[i] *
b->Pij_rr[k*dim3+i*dim2+j] *
b->p_lk_left[site*dim1+k*dim2+i] *
v_rght *
POW(2.,-(b->sum_scale_left[k*tree->n_pattern+site] + scale_rght));
}
}
}
/* Scaling */
sum = .0;
For(k,tree->mod->n_catg) For(i,tree->mod->ns) For(j,tree->mod->ns) sum += prob[dim3*k+dim2*i+j];
For(k,tree->mod->n_catg) For(i,tree->mod->ns) For(j,tree->mod->ns) prob[dim3*k+dim2*i+j] /= sum;
/* Expected number of each pair of states */
For(i,tree->mod->ns) For(j,tree->mod->ns) For(k,tree->mod->n_catg)
F[dim3*k+dim2*i+j] += tree->data->wght[site] * prob[dim3*k+dim2*i+j];
}
old_l = b->l;
Opt_Dist_F(&(b->l),F,tree->mod);
new_l = b->l;
n_iter++;
if(!approx)
Br_Len_Brent(0.02*b->l,b->l,50.*b->l,
tree->mod->s_opt->min_diff_lk_local,
b,tree,
tree->mod->s_opt->brent_it_max,
tree->mod->s_opt->quickdirty);
else
Lk_At_Given_Edge(b,tree);
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void Init_Eigen_Struct(eigen *this)
{
this->reflect = YES;
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
eigen *Make_Eigen_Struct(int ns)
{
eigen *eig;
eig = (eigen *)mCalloc(1,sizeof(eigen));
eig->size = ns;
eig->space = (phydbl *)mCalloc(2*ns,sizeof(phydbl));
eig->space_int = (int *)mCalloc(2*ns,sizeof(int));
eig->e_val = (phydbl *)mCalloc(ns,sizeof(phydbl));
eig->e_val_im = (phydbl *)mCalloc(ns,sizeof(phydbl));
eig->r_e_vect = (phydbl *)mCalloc(ns*ns,sizeof(phydbl));
eig->r_e_vect_im = (phydbl *)mCalloc(ns*ns,sizeof(phydbl));
eig->l_e_vect = (phydbl *)mCalloc(ns*ns,sizeof(phydbl));
eig->q = (phydbl *)mCalloc(ns*ns,sizeof(phydbl));
Init_Eigen_Struct(eig);
return eig;
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
triplet *Make_Triplet_Struct(model *mod)
{
int i,j,k;
triplet *triplet_struct;
triplet_struct = (triplet *)mCalloc(1,sizeof(triplet));
triplet_struct->size = mod->ns;
triplet_struct->pi_bc = (phydbl *)mCalloc(mod->ns,sizeof(phydbl ));
triplet_struct->pi_cd = (phydbl *)mCalloc(mod->ns,sizeof(phydbl ));
triplet_struct->pi_bd = (phydbl *)mCalloc(mod->ns,sizeof(phydbl ));
triplet_struct->F_bc = (phydbl *)mCalloc(mod->ns*mod->ns*mod->n_catg,sizeof(phydbl));
triplet_struct->F_cd = (phydbl *)mCalloc(mod->ns*mod->ns*mod->n_catg,sizeof(phydbl));
triplet_struct->F_bd = (phydbl *)mCalloc(mod->ns*mod->ns,sizeof(phydbl));
triplet_struct->core = (phydbl ****)mCalloc(mod->n_catg,sizeof(phydbl ***));
triplet_struct->p_one_site = (phydbl ***)mCalloc(mod->ns,sizeof(phydbl **));
triplet_struct->sum_p_one_site = (phydbl ***)mCalloc(mod->ns,sizeof(phydbl **));
triplet_struct->eigen_struct = (eigen *)Make_Eigen_Struct(mod->ns);
triplet_struct->mod = mod;
For(k,mod->n_catg)
{
triplet_struct->core[k] = (phydbl ***)mCalloc(mod->ns,sizeof(phydbl **));
For(i,mod->ns)
{
triplet_struct->core[k][i] = (phydbl **)mCalloc(mod->ns,sizeof(phydbl *));
For(j,mod->ns)
triplet_struct->core[k][i][j] = (phydbl *)mCalloc(mod->ns,sizeof(phydbl ));
}
}
For(i,mod->ns)
{
triplet_struct->p_one_site[i] = (phydbl **)mCalloc(mod->ns,sizeof(phydbl *));
For(j,mod->ns)
triplet_struct->p_one_site[i][j] = (phydbl *)mCalloc(mod->ns,sizeof(phydbl ));
}
For(i,mod->ns)
{
triplet_struct->sum_p_one_site[i] = (phydbl **)mCalloc(mod->ns,sizeof(phydbl *));
For(j,mod->ns)
triplet_struct->sum_p_one_site[i][j] = (phydbl *)mCalloc(mod->ns,sizeof(phydbl ));
}
return triplet_struct;
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
phydbl Triple_Dist(t_node *a, t_tree *tree, int approx)
{
if(a->tax) return UNLIKELY;
else
{
Update_PMat_At_Given_Edge(a->b[1],tree);
Update_PMat_At_Given_Edge(a->b[2],tree);
Update_P_Lk(tree,a->b[0],a);
Fast_Br_Len(a->b[0],tree,approx);
Update_P_Lk(tree,a->b[1],a);
Fast_Br_Len(a->b[1],tree,approx);
Update_P_Lk(tree,a->b[2],a);
Fast_Br_Len(a->b[2],tree,approx);
Update_P_Lk(tree,a->b[1],a);
Update_P_Lk(tree,a->b[0],a);
}
return tree->c_lnL;
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void Make_Symmetric(phydbl **F, int size)
{
int i,j;
For(i,size)
{
for(j=i+1;jmod->ns)
{
For(j,tree->mod->ns)
{
(*F)[tree->mod->ns*i+j] = RINT((*F)[tree->mod->ns*i+j]);
}
}
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
phydbl Get_Sum_Of_Cells(phydbl *F, t_tree *tree)
{
int i,j;
phydbl sum = .0;
For(i,tree->mod->ns)
For(j,tree->mod->ns)
sum += F[tree->mod->ns*i+j];
return sum;
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void Divide_Cells(phydbl **F, phydbl div, t_tree *tree)
{
int i,j;
For(i,tree->mod->ns)
For(j,tree->mod->ns)
(*F)[tree->mod->ns*i+j] /= div;
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void Divide_Mat_By_Vect(phydbl **F, phydbl *vect, int size)
{
int i,j;
For(i,size)
For(j,size)
(*F)[size*i+j] = (*F)[size*i+j] / vect[j];
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void Multiply_Mat_By_Vect(phydbl **F, phydbl *vect, int size)
{
int i,j;
For(i,size)
For(j,size)
(*F)[size*i+j] = (*F)[size*i+j] * vect[j];
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void Found_In_Subtree(t_node *a, t_node *d, t_node *target, int *match, t_tree *tree)
{
if(d->tax) return;
else
{
int i;
if(d == target) *match = 1;
For(i,3)
{
if(d->v[i] != a)
Found_In_Subtree(d,d->v[i],target,match,tree);
}
}
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void Get_List_Of_Target_Edges(t_node *a, t_node *d, t_edge **list, int *list_size, t_tree *tree)
{
int i;
For(i,3)
{
if(a->v[i] && a->v[i] == d)
{
list[*list_size] = a->b[i];
(*list_size)++;
}
}
if(d->tax) return;
else
{
For(i,3)
{
if(d->v[i] != a)
Get_List_Of_Target_Edges(d,d->v[i],list,list_size,tree);
}
}
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void Fix_All(t_tree *tree)
{
int i;
tree->mod->pinvar_old->v = tree->mod->pinvar->v;
tree->mod->alpha_old->v = tree->mod->alpha->v;
tree->mod->kappa_old->v = tree->mod->kappa->v;
tree->mod->lambda_old->v = tree->mod->lambda->v;
for(i=tree->n_otu;i<2*tree->n_otu-2;i++)
{
tree->t_nodes[i]->b[0]->l_old = tree->t_nodes[i]->b[0]->l;
tree->t_nodes[i]->b[1]->l_old = tree->t_nodes[i]->b[1]->l;
tree->t_nodes[i]->b[2]->l_old = tree->t_nodes[i]->b[2]->l;
}
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void Record_Br_Len(t_tree *tree)
{
int i;
if(tree->br_len_recorded == YES)
{
PhyML_Printf("\n. Overwriting recorded edge lengths.\n");
PhyML_Printf("\n. Err in file %s at line %d\n",__FILE__,__LINE__);
Exit("\n");
}
For(i,2*tree->n_otu-3)
{
tree->t_edges[i]->l_old = tree->t_edges[i]->l;
tree->t_edges[i]->gamma_prior_mean_old = tree->t_edges[i]->gamma_prior_mean;
tree->t_edges[i]->gamma_prior_var_old = tree->t_edges[i]->gamma_prior_var;
}
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void Restore_Br_Len(t_tree *tree)
{
int i;
tree->br_len_recorded = NO;
For(i,2*tree->n_otu-3)
{
tree->t_edges[i]->l = tree->t_edges[i]->l_old;
tree->t_edges[i]->gamma_prior_mean = tree->t_edges[i]->gamma_prior_mean_old;
tree->t_edges[i]->gamma_prior_var = tree->t_edges[i]->gamma_prior_var_old;
}
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void Get_Dist_Btw_Edges(t_node *a, t_node *d, t_tree *tree)
{
int i;
t_edge *b_fcus;
b_fcus = NULL;
For(i,3) if(a->v[i] == d) {b_fcus = a->b[i]; break;}
if(d->tax) return;
else
{
For(i,3)
if(d->v[i] != a)
{
d->b[i]->topo_dist_btw_edges = b_fcus->topo_dist_btw_edges + 1;
d->b[i]->dist_btw_edges = b_fcus->dist_btw_edges + d->b[i]->l / 2.;
Get_Dist_Btw_Edges(d,d->v[i],tree);
}
}
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void Detect_Polytomies(t_edge *b, phydbl l_thresh, t_tree *tree)
{
if((b->l < l_thresh) && (!b->left->tax) && (!b->rght->tax))
{
b->l = 0.0;
b->has_zero_br_len = YES;
}
else b->has_zero_br_len = NO;
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void Get_List_Of_Nodes_In_Polytomy(t_node *a, t_node *d, t_node ***list, int *size_list)
{
if(d->tax) return;
else
{
int i;
For(i,3)
{
if(d->v[i] != a)
{
if(!d->b[i]->has_zero_br_len)
{
(*list)[*size_list] = d->v[i];
(*size_list)++;
}
if(d->b[i]->has_zero_br_len)
Get_List_Of_Nodes_In_Polytomy(d,d->v[i],list,size_list);
}
}
}
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void Check_Path(t_node *a, t_node *d, t_node *target, t_tree *tree)
{
PhyML_Printf("path---------\n");
if(d==target) return;
else Check_Path(d,d->v[tree->t_dir[d->num*(2*tree->n_otu-2)+target->num]],target,tree);
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void Connect_Two_Nodes(t_node *a, t_node *d)
{
a->v[0] = d;
d->v[0] = a;
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void Get_List_Of_Adjacent_Targets(t_node *a, t_node *d, t_node ***node_list, t_edge ***edge_list, int *list_size)
{
int i;
For(i,3)
if(a->v[i] == d)
{
(*node_list)[*list_size] = a;
(*edge_list)[*list_size] = a->b[i];
(*list_size)++;
}
if(d->tax) return;
else
For(i,3)
if(d->v[i] != a) Get_List_Of_Adjacent_Targets(d,d->v[i],node_list,edge_list,list_size);
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void Sort_List_Of_Adjacent_Targets(t_edge ***list, int list_size)
{
t_edge *buff_edge;
int i,j;
buff_edge = NULL;
For(i,list_size-1)
{
for(j=i+1;jtopo_dist_btw_edges < (*list)[i]->topo_dist_btw_edges)
{
buff_edge = (*list)[j];
(*list)[j] = (*list)[i];
(*list)[i] = buff_edge;
}
}
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
t_node *Common_Nodes_Btw_Two_Edges(t_edge *a, t_edge *b)
{
if(a->left == b->left) return b->left;
else if(a->left == b->rght) return b->rght;
else if(a->rght == b->left) return b->left;
else if(a->rght == b->rght) return b->rght;
PhyML_Printf("\n. First t_edge = %d (%d %d); Second t_edge = %d (%d %d)\n",
a->num,a->left->num,a->rght->num,
b->num,b->left->num,b->rght->num);
PhyML_Printf("\n. Err in file %s at line %d\n",__FILE__,__LINE__);
Warn_And_Exit("");
return NULL;
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
int KH_Test(phydbl *site_lk_M1, phydbl *site_lk_M2, t_tree *tree)
{
phydbl *delta,mean,sd,obs_stat,threshold;
int i;
delta = (phydbl *)mCalloc(tree->data->init_len,sizeof(phydbl));
threshold = .0;
mean = .0;
obs_stat = .0;
For(i,tree->n_pattern)
{
delta[i] = site_lk_M1[i] - site_lk_M2[i];
mean += ((int)tree->data->wght[i])*delta[i];
}
obs_stat = mean;
mean /= tree->data->init_len;
For(i,tree->data->init_len) delta[i] -= mean;
sd = .0;
For(i,tree->data->init_len) sd += POW(delta[i],2);
sd /= (phydbl)(tree->data->init_len-1.);
/* threshold = tree->dnorm_thresh*SQRT(sd*tree->data->init_len); */
/* PhyML_Printf("\nObs stat = %f Threshold = %f\n",obs_stat,threshold); */
Free(delta);
if(obs_stat > threshold) return 1;
else return 0;
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void Random_Tree(t_tree *tree)
{
int *is_available,*list_of_nodes;
int i,node_num,step,n_available;
phydbl min_edge_len;
min_edge_len = 1.E-3;
if(tree->mod->s_opt && tree->mod->s_opt->print == YES) PhyML_Printf("\n. Randomising the tree...\n");
is_available = (int *)mCalloc(2*tree->n_otu-2,sizeof(int));
list_of_nodes = (int *)mCalloc(tree->n_otu, sizeof(int));
For(i,tree->n_otu) is_available[i] = 1;
For(i,tree->n_otu) list_of_nodes[i] = i;
step = 0;
do
{
/* node_num = (int)RINT(rand()/(phydbl)(RAND_MAX+1.0)*(tree->n_otu-1-step)); */
node_num = Rand_Int(0,tree->n_otu-1-step);
node_num = list_of_nodes[node_num];
is_available[node_num] = 0;
For(i,tree->n_otu) list_of_nodes[i] = -1;
n_available = 0;
For(i,2*tree->n_otu-2) if(is_available[i]) {list_of_nodes[n_available++] = i;}
tree->t_nodes[node_num]->v[0] = tree->t_nodes[tree->n_otu+step];
tree->t_nodes[tree->n_otu+step]->v[1] = tree->t_nodes[node_num];
/* node_num = (int)RINT(rand()/(phydbl)(RAND_MAX+1.0)*(tree->n_otu-2-step)); */
node_num = Rand_Int(0,tree->n_otu-2-step);
node_num = list_of_nodes[node_num];
is_available[node_num] = 0;
For(i,tree->n_otu) list_of_nodes[i] = -1;
n_available = 0;
For(i,2*tree->n_otu-2) if(is_available[i]) {list_of_nodes[n_available++] = i;}
tree->t_nodes[node_num]->v[0] = tree->t_nodes[tree->n_otu+step];
tree->t_nodes[tree->n_otu+step]->v[2] = tree->t_nodes[node_num];
is_available[tree->n_otu+step] = 1;
For(i,tree->n_otu) list_of_nodes[i] = -1;
n_available = 0;
For(i,2*tree->n_otu-2) if(is_available[i]) list_of_nodes[n_available++] = i;
step++;
}while(step < tree->n_otu-2);
tree->t_nodes[list_of_nodes[0]]->v[0] = tree->t_nodes[list_of_nodes[1]];
tree->t_nodes[list_of_nodes[1]]->v[0] = tree->t_nodes[list_of_nodes[0]];
tree->num_curr_branch_available = 0;
Connect_Edges_To_Nodes_Recur(tree->t_nodes[0],tree->t_nodes[0]->v[0],tree);
For(i,2*tree->n_otu-3) if(tree->t_edges[i]->l < min_edge_len) tree->t_edges[i]->l = min_edge_len;
Fill_Dir_Table(tree);
Update_Dirs(tree);
Free(is_available);
Free(list_of_nodes);
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
// Make sure internal edges have likelihood vectors on both
// sides and external edges have one likelihood vector on the
// lefthand side only
void Reorganize_Edges_Given_Lk_Struct(t_tree *tree)
{
int j,i;
For(i,2*tree->n_otu-3)
{
if(tree->t_edges[i]->p_lk_left && tree->t_edges[i]->left->tax == YES)
{
For(j,2*tree->n_otu-3)
{
if(!tree->t_edges[j]->p_lk_left && tree->t_edges[j]->left->tax == NO)
{
Swap_Nodes_On_Edges(tree->t_edges[i],tree->t_edges[j],NO,tree);
break;
}
if(!tree->t_edges[j]->p_lk_rght && tree->t_edges[j]->rght->tax == NO)
{
Swap_Nodes_On_Edges(tree->t_edges[i],tree->t_edges[j],YES,tree);
break;
}
}
}
if(tree->t_edges[i]->p_lk_rght && tree->t_edges[i]->rght->tax == YES)
{
For(j,2*tree->n_otu-3)
{
if(!tree->t_edges[j]->p_lk_left && tree->t_edges[j]->left->tax == NO)
{
Swap_Nodes_On_Edges(tree->t_edges[i],tree->t_edges[j],YES,tree);
break;
}
if(!tree->t_edges[j]->p_lk_rght && tree->t_edges[j]->rght->tax == NO)
{
Swap_Nodes_On_Edges(tree->t_edges[i],tree->t_edges[j],NO,tree);
break;
}
}
}
}
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void Random_NNI(int n_moves, t_tree *tree)
{
int i,j;
t_edge *b;
t_node *n1,*n2,*n_target;
n1 = n2 = NULL;
b = NULL;
For(i,n_moves)
{
n_target = tree->t_nodes[tree->n_otu + (int)((phydbl)rand()/RAND_MAX * (2*tree->n_otu-3-tree->n_otu))];
For(j,3) if(!n_target->v[j]->tax) {b = n_target->b[j]; break;}
For(j,3) if(b->left->v[j] != b->rght) {n1 = b->left->v[j]; break;}
For(j,3) if(b->rght->v[j] != b->left) {n2 = b->rght->v[j]; break;}
Swap(n1,b->left,b->rght,n2,tree);
}
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void Print_Settings(option *io)
{
int answer;
char *s;
s = (char *)mCalloc(100,sizeof(char));
PhyML_Printf("\n\n\n");
PhyML_Printf("\n\n");
PhyML_Printf(" .......................... \n");
PhyML_Printf(" ooooooooooooooooooooooooooooo CURRENT SETTINGS ooooooooooooooooooooooooooooooooooo\n");
PhyML_Printf(" .......................... \n");
PhyML_Printf("\n . Sequence filename:\t\t\t\t %s", Basename(io->in_align_file));
if(io->datatype == NT) strcpy(s,"dna");
else if(io->datatype == AA) strcpy(s,"aa");
else strcpy(s,"generic");
PhyML_Printf("\n . Data type:\t\t\t\t\t %s",s);
PhyML_Printf("\n . Alphabet size:\t\t\t\t %d",io->mod->ns);
PhyML_Printf("\n . Sequence format:\t\t\t\t %s", io->interleaved ? "interleaved": "sequential");
PhyML_Printf("\n . Number of data sets:\t\t\t\t %d", io->n_data_sets);
PhyML_Printf("\n . Nb of bootstrapped data sets:\t\t\t %d", io->mod->bootstrap);
if (io->mod->bootstrap > 0)
PhyML_Printf("\n . Compute approximate likelihood ratio test:\t no");
else
{
if(io->ratio_test == 1)
PhyML_Printf("\n . Compute approximate likelihood ratio test:\t yes (aLRT statistics)");
else if(io->ratio_test == 2)
PhyML_Printf("\n . Compute approximate likelihood ratio test:\t yes (Chi2-based parametric branch supports)");
else if(io->ratio_test == 3)
PhyML_Printf("\n . Compute approximate likelihood ratio test:\t yes (Minimum of SH-like and Chi2-based branch supports)");
else if(io->ratio_test == 4)
PhyML_Printf("\n . Compute approximate likelihood ratio test:\t yes (SH-like branch supports)");
else if(io->ratio_test == 5)
PhyML_Printf("\n . Compute approximate likelihood ratio test:\t yes (aBayes branch supports)");
}
PhyML_Printf("\n . Model name:\t\t\t\t\t %s", io->mod->modelname);
if(io->datatype == AA && io->mod->whichmodel == CUSTOMAA) PhyML_Printf(" (%s)",io->aa_rate_mat_file);
if (io->datatype == NT)
{
if ((io->mod->whichmodel == K80) ||
(io->mod->whichmodel == HKY85)||
(io->mod->whichmodel == F84) ||
(io->mod->whichmodel == TN93))
{
if (io->mod->s_opt->opt_kappa)
PhyML_Printf("\n . Ts/tv ratio:\t\t\t\t\t estimated");
else
PhyML_Printf("\n . Ts/tv ratio:\t\t\t\t\t %f", io->mod->kappa->v);
}
}
if (io->mod->s_opt->opt_pinvar)
PhyML_Printf("\n . Proportion of invariable sites:\t\t estimated");
else
PhyML_Printf("\n . Proportion of invariable sites:\t\t %f", io->mod->pinvar->v);
PhyML_Printf("\n . Number of subst. rate categs:\t\t\t %d", io->mod->n_catg);
if(io->mod->n_catg > 1)
{
if(io->mod->free_mixt_rates == NO)
{
if(io->mod->s_opt->opt_alpha)
PhyML_Printf("\n . Gamma distribution parameter:\t\t\t estimated");
else
PhyML_Printf("\n . Gamma distribution parameter:\t\t\t %f", io->mod->alpha->v);
PhyML_Printf("\n . 'Middle' of each rate class:\t\t\t %s",(io->mod->gamma_median)?("median"):("mean"));
}
}
if(io->datatype == AA)
PhyML_Printf("\n . Amino acid equilibrium frequencies:\t\t %s", (io->mod->s_opt->opt_state_freq) ? ("empirical"):("model"));
else if(io->datatype == NT)
{
if((io->mod->whichmodel != JC69) &&
(io->mod->whichmodel != K80) &&
(io->mod->whichmodel != F81))
{
if(!io->mod->s_opt->user_state_freq)
{
PhyML_Printf("\n . Nucleotide equilibrium frequencies:\t\t %s", (io->mod->s_opt->opt_state_freq) ? ("ML"):("empirical"));
}
else
{
PhyML_Printf("\n . Nucleotide equilibrium frequencies:\t\t %s","user-defined");
}
}
}
PhyML_Printf("\n . Optimise tree topology:\t\t\t %s", (io->mod->s_opt->opt_topo) ? "yes": "no");
switch(io->in_tree)
{
case 0: { strcpy(s,"BioNJ"); break; }
case 1: { strcpy(s,"parsimony"); break; }
case 2: { strcpy(s,"user tree (");
strcat(s,Basename(io->in_tree_file));
strcat(s,")"); break; }
}
if(io->mod->s_opt->opt_topo)
{
if(io->mod->s_opt->topo_search == NNI_MOVE) PhyML_Printf("\n . Tree topology search:\t\t\t\t NNIs");
else if(io->mod->s_opt->topo_search == SPR_MOVE) PhyML_Printf("\n . Tree topology search:\t\t\t\t SPRs");
else if(io->mod->s_opt->topo_search == BEST_OF_NNI_AND_SPR) PhyML_Printf("\n . Tree topology search:\t\t\t\t Best of NNIs and SPRs");
PhyML_Printf("\n . Starting tree:\t\t\t\t %s",s);
PhyML_Printf("\n . Add random input tree:\t\t\t %s", (io->mod->s_opt->random_input_tree) ? "yes": "no");
if(io->mod->s_opt->random_input_tree)
PhyML_Printf("\n . Number of random starting trees:\t\t %d", io->mod->s_opt->n_rand_starts);
}
else
if(!io->mod->s_opt->random_input_tree)
PhyML_Printf("\n . Evaluated tree:\t\t\t\t file \"%s\"",s);
PhyML_Printf("\n . Optimise branch lengths:\t\t\t %s", (io->mod->s_opt->opt_bl) ? "yes": "no");
answer = 0;
if(io->mod->s_opt->opt_alpha ||
io->mod->s_opt->opt_kappa ||
io->mod->s_opt->opt_lambda ||
io->mod->s_opt->opt_pinvar ||
io->mod->s_opt->opt_rr) answer = 1;
PhyML_Printf("\n . Optimise substitution model parameters:\t %s", (answer) ? "yes": "no");
PhyML_Printf("\n . Run ID:\t\t\t\t\t %s", (io->appebr_run_ID) ? (io->run_id_string): ("none"));
PhyML_Printf("\n . Random seed:\t\t\t\t\t %d", io->r_seed);
PhyML_Printf("\n . Subtree patterns aliasing:\t\t\t %s",io->do_alias_subpatt?"yes":"no");
PhyML_Printf("\n . Version:\t\t\t\t\t %s", VERSION);
PhyML_Printf("\n\n oooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooo\n");
PhyML_Printf("\n\n");
fflush(NULL);
Free(s);
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void Fill_Missing_Dist(matrix *mat)
{
int i,j;
For(i,mat->n_otu)
{
for(j=i+1;jn_otu;j++)
{
if(i != j)
{
if(mat->dist[i][j] < .0)
{
Fill_Missing_Dist_XY(i,j,mat);
mat->dist[j][i] = mat->dist[i][j];
}
}
}
}
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void Fill_Missing_Dist_XY(int x, int y, matrix *mat)
{
int i,j;
phydbl *local_mins,**S1S2;
int cpt;
int pos_best_estimate;
phydbl min_crit, curr_crit;
local_mins = (phydbl *)mCalloc(mat->n_otu*mat->n_otu,sizeof(phydbl ));
S1S2 = (phydbl **)mCalloc(mat->n_otu*mat->n_otu,sizeof(phydbl *));
For(i,mat->n_otu*mat->n_otu) S1S2[i] = (phydbl *)mCalloc(2,sizeof(phydbl));
cpt = 0;
For(i,mat->n_otu)
{
if((mat->dist[i][x] > .0) && (mat->dist[i][y] > .0))
{
For(j,mat->n_otu)
{
if((mat->dist[j][x] > .0) && (mat->dist[j][y] > .0))
{
if((i != j) && (i != x) && (i != y) && (j != x) && (j != y))
{
S1S2[cpt][0] = MIN(mat->dist[i][x] + mat->dist[j][y] - mat->dist[i][j] , mat->dist[i][y] + mat->dist[j][x] - mat->dist[i][j]);
S1S2[cpt][1] = MAX(mat->dist[i][x] + mat->dist[j][y] - mat->dist[i][j] , mat->dist[i][y] + mat->dist[j][x] - mat->dist[i][j]);
cpt++;
}
}
}
}
}
Qksort_Matrix(S1S2,0,0,cpt-1);
local_mins[0] = S1S2[0][1];
for(i=1;i S1S2[i][0]))
{
curr_crit = Least_Square_Missing_Dist_XY(x,y,local_mins[i],mat);
if(curr_crit < min_crit)
{
min_crit = curr_crit;
pos_best_estimate = i;
}
}
}
mat->dist[x][y] = local_mins[pos_best_estimate];
mat->dist[y][x] = mat->dist[x][y];
For(i,mat->n_otu*mat->n_otu) Free(S1S2[i]);
Free(S1S2);
Free(local_mins);
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
phydbl Least_Square_Missing_Dist_XY(int x, int y, phydbl dxy, matrix *mat)
{
int i,j;
phydbl fit;
fit = .0;
For(i,mat->n_otu)
{
if((mat->dist[i][x] > .0) && (mat->dist[i][y] > .0))
{
For(j,mat->n_otu)
{
if((mat->dist[j][x] > .0) && (mat->dist[j][y] > .0))
{
if((i != j) && (i != x) && (i != y) && (j != x) && (j != y))
{
if(dxy < MIN(mat->dist[i][x] + mat->dist[j][y] - mat->dist[i][j] , mat->dist[i][y] + mat->dist[j][x] - mat->dist[i][j]))
{
fit += POW((mat->dist[i][x] + mat->dist[j][y]) - (mat->dist[i][y] + mat->dist[j][x]),2);
}
else if((mat->dist[i][x] + mat->dist[j][y]) < (mat->dist[i][y] + mat->dist[j][x]))
{
fit += POW(dxy - (mat->dist[i][y] + mat->dist[j][x] - mat->dist[i][j]),2);
}
else
{
fit += POW(dxy - (mat->dist[i][x] + mat->dist[j][y] - mat->dist[i][j]),2);
}
}
}
}
}
}
return fit;
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void Print_Banner(FILE *fp)
{
PhyML_Fprintf(fp,"\n");
PhyML_Fprintf(fp," oooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooo\n");
PhyML_Fprintf(fp," \n");
PhyML_Fprintf(fp," --- PhyML %s --- \n",VERSION);
PhyML_Fprintf(fp," \n");
PhyML_Fprintf(fp," A simple, fast, and accurate algorithm to estimate large phylogenies by maximum likelihood \n");
PhyML_Fprintf(fp," Stephane Guindon & Olivier Gascuel \n");
PhyML_Fprintf(fp," \n");
PhyML_Fprintf(fp," http://www.atgc-montpellier.fr/phyml \n");
PhyML_Fprintf(fp," \n");
PhyML_Fprintf(fp," Copyright CNRS - Universite Montpellier II \n");
PhyML_Fprintf(fp," \n");
PhyML_Fprintf(fp," oooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooo\n");
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void Print_Banner_Small(FILE *fp)
{
PhyML_Fprintf(fp,"\n");
PhyML_Fprintf(fp," oooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooo\n");
PhyML_Fprintf(fp," --- PhyML %s --- \n",VERSION);
PhyML_Fprintf(fp," http://www.atgc-montpellier.fr/phyml \n");
PhyML_Fprintf(fp," Copyright CNRS - Universite Montpellier II \n");
PhyML_Fprintf(fp," oooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooo\n");
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void Print_Data_Set_Number(option *io, FILE *fp)
{
PhyML_Fprintf(fp,"\n");
PhyML_Fprintf(fp," \n");
PhyML_Fprintf(fp," [ Data set number %3d ] \n",io->curr_gt+1);
PhyML_Fprintf(fp," \n");
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void Check_Memory_Amount(t_tree *tree)
{
/* Rough estimate of the amount of memory that has to be used */
long int nbytes;
int n_otu;
model *mod;
mod = tree->mod;
n_otu = tree->io->n_otu;
nbytes = 0;
/* Partial Pars */
nbytes += (2*n_otu-3) * 2 * tree->data->crunch_len * sizeof(int);
nbytes += (2*n_otu-3) * 2 * tree->data->crunch_len * sizeof(unsigned int);
nbytes += (2*n_otu-3) * 2 * tree->data->crunch_len * mod->ns * sizeof(int);
/* Pmat */
nbytes += (2*n_otu-3) * mod->n_catg * mod->ns * mod->ns * sizeof(phydbl);
/* Partial Lk */
nbytes += ((2*n_otu-3) * 2 - tree->n_otu) * tree->data->crunch_len * mod->n_catg * mod->ns * sizeof(phydbl);
/* Scaling factors */
nbytes += ((2*n_otu-3) * 2 - tree->n_otu) * tree->data->crunch_len * sizeof(int);
if(((phydbl)nbytes/(1.E+06)) > 256.)
/* if(((phydbl)nbytes/(1.E+06)) > 0.) */
{
PhyML_Printf("\n\n. WARNING: this analysis requires at least %.0f MB of memory space.\n",(phydbl)nbytes/(1.E+06));
#ifndef BATCH
char answer;
if((!tree->io->quiet) && (tree->io->mem_question == YES))
{
PhyML_Printf("\n. Do you really want to proceed? [Y/n] ");
if(scanf("%c", &answer))
{
if(answer == '\n') answer = 'Y';
else if(answer == 'n' || answer == 'N') Warn_And_Exit("\n");
else getchar();
}
else
{
Warn_And_Exit("\n\n");
}
}
#endif
}
else if(((phydbl)nbytes/(1.E+06)) > 100.)
{
if(!tree->io->quiet) PhyML_Printf("\n\n. WARNING: this analysis will use at least %.0f Mo of memory space...\n",(phydbl)nbytes/(1.E+06));
}
else if(((phydbl)nbytes/(1.E+06)) > 1.)
{
if(!tree->io->quiet) PhyML_Printf("\n\n. This analysis requires at least %.0f Mo of memory space.\n",(phydbl)nbytes/(1.E+06));
}
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
int Get_State_From_P_Lk(phydbl *p_lk, int pos, t_tree *tree)
{
int i;
For(i,tree->mod->ns) if(p_lk[pos+i] > .0) return i;
return -1;
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
int Get_State_From_P_Pars(short int *p_pars, int pos, t_tree *tree)
{
int i;
For(i,tree->mod->ns) if(p_pars[pos+i] > .0) return i;
return -1;
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void Print_Lk(t_tree *tree, char *string)
{
time(&(tree->t_current));
PhyML_Printf("\n. (%5d sec) [%15.4f] %s",
(int)(tree->t_current-tree->t_beg),tree->c_lnL,
string);
#ifndef QUIET
fflush(NULL);
#endif
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void Print_Pars(t_tree *tree)
{
time(&(tree->t_current));
PhyML_Printf("\n. (%5d sec) [%5d]",(int)(tree->t_current-tree->t_beg),tree->c_pars);
#ifndef QUIET
fflush(NULL);
#endif
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void Print_Lk_And_Pars(t_tree *tree)
{
time(&(tree->t_current));
PhyML_Printf("\n. (%5d sec) [%15.4f] [%5d]",
(int)(tree->t_current-tree->t_beg),
tree->c_lnL,tree->c_pars);
#ifndef QUIET
fflush(NULL);
#endif
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void Check_Dirs(t_tree *tree)
{
int i;
For(i,2*tree->n_otu-3)
{
if(!tree->t_edges[i]->left->tax)
{
if(tree->t_edges[i]->left->v[tree->t_edges[i]->l_v1]->num <
tree->t_edges[i]->left->v[tree->t_edges[i]->l_v2]->num)
{
PhyML_Printf("\n. Edge %d ; v1=%d v2=%d",
tree->t_edges[i]->num,
tree->t_edges[i]->left->v[tree->t_edges[i]->l_v1]->num,
tree->t_edges[i]->left->v[tree->t_edges[i]->l_v2]->num);
PhyML_Printf("\n. Err in file %s at line %d\n",__FILE__,__LINE__);
Warn_And_Exit("");
}
}
if(!tree->t_edges[i]->rght->tax)
{
if(tree->t_edges[i]->rght->v[tree->t_edges[i]->r_v1]->num <
tree->t_edges[i]->rght->v[tree->t_edges[i]->r_v2]->num)
{
PhyML_Printf("\n. Edge %d ; v3=%d v4=%d",
tree->t_edges[i]->num,
tree->t_edges[i]->rght->v[tree->t_edges[i]->r_v1]->num,
tree->t_edges[i]->rght->v[tree->t_edges[i]->r_v2]->num);
PhyML_Printf("\n. Err in file %s at line %d\n",__FILE__,__LINE__);
Warn_And_Exit("");
}
}
}
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void Warn_And_Exit(char *s)
{
PhyML_Fprintf(stdout,"%s",s);
fflush(NULL);
#ifndef BATCH
/* if (! tree->io->quiet) { */
/* char c; */
PhyML_Fprintf(stdout,"\n. Type enter to exit.\n");
/* if(!fscanf(stdin,"%c",&c)) */
Exit("");
/* } */
#endif
Exit("\n");
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void Read_Qmat(phydbl *daa, phydbl *pi, FILE *fp)
{
int i,j;
phydbl sum;
double val;
rewind(fp);
for(i=1;i<20;i++)
{
For(j,19)
{
/* if(!fscanf(fp,"%lf",&(daa[i*20+j]))) Exit("\n"); */
if(!fscanf(fp,"%lf",&val))
{
PhyML_Printf("\n. Rate matrix file does not appear to have a proper format. Please refer to the documentation.");
Exit("\n");
}
daa[i*20+j] = (phydbl)val;
daa[j*20+i] = daa[i*20+j];
if(j == i-1) break;
}
}
For(i,20)
{
if(!fscanf(fp,"%lf",&val)) Exit("\n");
pi[i] = (phydbl)val;
}
sum = .0;
For(i,20) sum += pi[i];
if(FABS(sum - 1.) > 1.E-06)
{
PhyML_Printf("\n. Sum=%f",sum);
PhyML_Printf("\n. Scaling amino-acid frequencies...\n");
For(i,20) pi[i] /= sum;
}
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void Print_Qmat_AA(phydbl *daa, phydbl *pi)
{
int i,j,cpt;
cpt = 0;
For(i,20)
{
for(j=0;jn_otu)
{
buff_dbl = rand();
buff_dbl /= (RAND_MAX+1.);
buff_dbl *= cdata->n_otu;
exchange_with = (int)FLOOR(buff_dbl);
buff_name = cdata->c_seq[i]->name;
cdata->c_seq[i]->name = cdata->c_seq[exchange_with]->name;
cdata->c_seq[exchange_with]->name = buff_name;
buff_state = cdata->c_seq[i]->state;
cdata->c_seq[i]->state = cdata->c_seq[exchange_with]->state;
cdata->c_seq[exchange_with]->state = buff_state;
buff_ambigu = cdata->c_seq[i]->is_ambigu;
cdata->c_seq[i]->is_ambigu = cdata->c_seq[exchange_with]->is_ambigu;
cdata->c_seq[exchange_with]->is_ambigu = buff_ambigu;
}
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void Update_Root_Pos(t_tree *tree)
{
if(tree->n_root_pos > -1.0)
{
tree->n_root->l[0] = tree->e_root->l * tree->n_root_pos;
tree->n_root->l[1] = tree->e_root->l * (1.-tree->n_root_pos);
}
else
{
/* tree->n_root->l[0] = tree->e_root->l / 2.; */
/* tree->n_root->l[1] = tree->e_root->l / 2.; */
}
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void Add_Root(t_edge *target, t_tree *tree)
{
#ifndef PHYML
PhyML_Printf("\n. Adding root on t_edge %d left = %d right = %d\n.",target->num,target->left->num,target->rght->num); fflush(NULL);
#endif
tree->e_root = target;
/* Create the root t_node if it does not exist yet */
if((!tree->n_root) || (tree->n_root->num != 2*tree->n_otu-2))
{
tree->n_root = (t_node *)Make_Node_Light(2*tree->n_otu-2);
}
tree->t_nodes[2*tree->n_otu-2] = tree->n_root;
tree->n_root->tax = 0;
/* Set the position of the root */
tree->n_root->v[0] = tree->e_root->left;
tree->n_root->v[1] = tree->e_root->rght;
tree->n_root->b[0] = tree->e_root;
tree->n_root->b[1] = tree->e_root;
if(tree->n_root_pos > -1.0)
{
if(tree->n_root_pos < 1.E-6 && tree->n_root_pos > -1.E-6)
printf("\n. WARNING: you put the root at a weird position...");
/* tree->n_root->l[0] = tree->e_root->l * (tree->n_root_pos/(1.+tree->n_root_pos)); */
/* tree->n_root->l[1] = tree->e_root->l - tree->n_root->l[0]; */
tree->n_root->l[0] = tree->e_root->l * tree->n_root_pos;
tree->n_root->l[1] = tree->e_root->l * (1. - tree->n_root_pos);
}
else
{
tree->n_root->l[0] = tree->e_root->l / 2.;
tree->n_root->l[1] = tree->e_root->l / 2.;
tree->n_root_pos = 0.5;
}
Update_Ancestors(tree->n_root,tree->n_root->v[0],tree);
Update_Ancestors(tree->n_root,tree->n_root->v[1],tree);
tree->n_root->anc = NULL;
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void Update_Ancestors(t_node *a, t_node *d, t_tree *tree)
{
if(a == tree->n_root) a->anc = NULL;
d->anc = a;
if(d->tax) return;
else
{
int i;
For(i,3)
if((d->v[i] != d->anc) && (d->b[i] != tree->e_root))
Update_Ancestors(d,d->v[i],tree);
}
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
/* Generate a random unrooted tree with 'n_otu' OTUs */
#ifdef PHYTIME
t_tree *Generate_Random_Tree_From_Scratch(int n_otu, int rooted)
{
t_tree *tree;
int *connected,*nonconnected,*available_nodes;
int i,n_connected,n_nonconnected,n1,n2,new_n,n_internal,n_external,n_available;
t_node *root,*curr_n,**internal_nodes, **external_nodes;
phydbl *t,*tmp;
tree = Make_Tree_From_Scratch(n_otu,NULL);
tree->rates = RATES_Make_Rate_Struct(tree->n_otu);
RATES_Init_Rate_Struct(tree->rates,tree->io->rates,tree->n_otu);
For(i,2*tree->n_otu-2)
{
tree->t_nodes[i]->v[1] = NULL;
tree->t_nodes[i]->v[2] = NULL;
}
root = (t_node *)Make_Node_Light(2*tree->n_otu-2);
connected = (int *)mCalloc(2*tree->n_otu-2,sizeof(int));
nonconnected = (int *)mCalloc(2*tree->n_otu-2,sizeof(int));
available_nodes = (int *)mCalloc(2*tree->n_otu-2,sizeof(int));
internal_nodes = (t_node **)mCalloc(tree->n_otu-2,sizeof(t_node *));
external_nodes = (t_node **)mCalloc(tree->n_otu, sizeof(t_node *));
t = (phydbl *)mCalloc(tree->n_otu-1,sizeof(phydbl ));
tmp = (phydbl *)mCalloc(2*tree->n_otu-2,sizeof(phydbl ));
n_nonconnected = 2*n_otu-2;
For(i,2*tree->n_otu-2) nonconnected[i] = i;
available_nodes[0] = 2*n_otu-2;
/* Node times are generated according to a Birth-death process.
Formulae are as described by Yang and Rannala (1997) */
phydbl phi;
phydbl rho; /* sampling intensity */
phydbl mu; /* birth rate */
phydbl lambda; /* death rate */
phydbl u; /* random U[0,1] */
phydbl expval;
/* rho = 1.0 and mu = 0.0 correspond to the Yule process */
lambda = 6.7;
mu = 2.5;
rho = 9./150.;
expval = EXP(mu-lambda);
phi = (rho*lambda*(expval-1.) + (mu-lambda)*expval)/(expval-1.); /* Equation 16 */
For(i,tree->n_otu-1)
{
u = rand();
u /= RAND_MAX;
if(FABS(lambda - mu) > 1.E-4)
t[i] = (LOG(phi-u*rho*lambda) - LOG(phi-u*rho*lambda + u*(lambda-mu)))/(mu-lambda); /* Equation 15 */
else
t[i] = u / (1.+lambda*rho*(1-u)); /* Equation 17 */
}
Qksort(t,NULL,0,tree->n_otu-2); /* Node times ordering in ascending order */
For(i,tree->n_otu-1) tmp[i] = t[tree->n_otu-2-i];
For(i,tree->n_otu-1) t[i] = -tmp[i];
/* Rescale t_node times such that the time at the root t_node is -100 */
for(i=1;in_otu-1;i++)
{
t[i] /= -t[0];
t[i] *= 1.E+02;
}
t[0] = -1.E+02;
n_available = 1;
curr_n = root;
n_connected = 0;
do
{
n1 = Rand_Int(0,n_nonconnected-1);
n1 = nonconnected[n1];
connected[n1] = 1;
n_nonconnected = 0;
For(i,2*tree->n_otu-2) if(!connected[i]) {nonconnected[n_nonconnected++] = i;}
n2 = Rand_Int(0,n_nonconnected-1);
n2 = nonconnected[n2];
connected[n2] = 1;
n_nonconnected = 0;
For(i,2*tree->n_otu-2) if(!connected[i]) {nonconnected[n_nonconnected++] = i;}
curr_n->v[1] = tree->t_nodes[n1];
curr_n->v[2] = tree->t_nodes[n2];
tree->t_nodes[n1]->v[0] = curr_n;
tree->t_nodes[n2]->v[0] = curr_n;
tree->rates->nd_t[curr_n->num] = t[n_connected/2];
available_nodes[n_available] = tree->t_nodes[n1]->num;
For(i,n_available)
if(available_nodes[i] == curr_n->num)
{
available_nodes[i] = tree->t_nodes[n2]->num;
break;
}
n_available++;
new_n = Rand_Int(0,n_available-1);
curr_n = tree->t_nodes[available_nodes[new_n]];
n_connected+=2;
}while(n_connected < 2*tree->n_otu-2);
For(i,2*tree->n_otu-2) tmp[i] = tree->rates->nd_t[i];
/* Unroot the tree */
root->v[1]->v[0] = root->v[2];
root->v[2]->v[0] = root->v[1];
n_internal = n_external = 0;
For(i,2*tree->n_otu-2)
{
if(tree->t_nodes[i]->v[1]) internal_nodes[n_internal++] = tree->t_nodes[i];
else external_nodes[n_external++] = tree->t_nodes[i];
}
n_internal = n_external = 0;
For(i,2*tree->n_otu-2)
{
if(i < tree->n_otu)
{
tree->t_nodes[i] = external_nodes[n_external++];
tree->t_nodes[i]->tax = 1;
}
else
{
tree->rates->nd_t[i] = tmp[internal_nodes[n_internal]->num];
tree->t_nodes[i] = internal_nodes[n_internal++];
tree->t_nodes[i]->tax = 0;
}
tree->t_nodes[i]->num = i;
}
For(i,tree->n_otu) tree->rates->nd_t[i] = 0.0;
For(i,tree->n_otu)
{
if(!tree->t_nodes[i]->name) tree->t_nodes[i]->name = (char *)mCalloc(T_MAX_NAME,sizeof(char));
strcpy(tree->t_nodes[i]->name,"x");
sprintf(tree->t_nodes[i]->name+1,"%d",i);
}
tree->num_curr_branch_available = 0;
Connect_Edges_To_Nodes_Recur(tree->t_nodes[0],tree->t_nodes[0]->v[0],tree);
Fill_Dir_Table(tree);
Update_Dirs(tree);
/* Add root */
if(rooted)
{
For(i,2*tree->n_otu-3)
{
if(((tree->t_edges[i]->left == root->v[1]) || (tree->t_edges[i]->rght == root->v[1])) &&
((tree->t_edges[i]->left == root->v[2]) || (tree->t_edges[i]->rght == root->v[2])))
{
Add_Root(tree->t_edges[i],tree);
break;
}
}
}
/* Or not... */
else
{
Free_Node(root);
}
RATES_Random_Branch_Lengths(tree);
Free(available_nodes);
Free(connected);
Free(nonconnected);
Free(external_nodes);
Free(internal_nodes);
Free(t);
Free(tmp);
return tree;
}
#endif
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void Random_Lineage_Rates(t_node *a, t_node *d, t_edge *b, phydbl stick_prob, phydbl *rates, int curr_rate, int n_rates, t_tree *tree)
{
phydbl uni;
int new_rate;
int i;
if(b)
{
uni = rand();
uni /= RAND_MAX;
if(uni > stick_prob) /* Randomly pick a new rate */
{
uni = rand();
uni /= RAND_MAX;
uni = (phydbl)(uni * (n_rates-1));
if(uni-(int)(uni) > 0.5-BIG) new_rate = (int)(uni)+1;
else new_rate = (int)(uni);
}
else
{
new_rate = curr_rate;
}
For(i,3)
if(a->v[i] == d)
{
a->b[i]->l *= rates[new_rate];
break;
}
For(i,3)
if(a->v[i] == d)
{
if(!(a->b[i]->n_labels%BLOCK_LABELS)) Make_New_Edge_Label(a->b[i]);
if(rates[new_rate] > 1.0) strcpy(a->b[i]->labels[a->b[i]->n_labels],"FAST");
else if(rates[new_rate] < 1.0) strcpy(a->b[i]->labels[a->b[i]->n_labels],"SLOW");
else strcpy(a->b[i]->labels[a->b[i]->n_labels],"MEDIUM");
a->b[i]->n_labels++;
break;
}
curr_rate = new_rate;
}
if(d->tax) return;
else
{
For(i,3)
if(d->v[i] != a)
Random_Lineage_Rates(d,d->v[i],d->b[i],stick_prob,rates,curr_rate,n_rates,tree);
}
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
t_edge *Find_Edge_With_Label(char *label, t_tree *tree)
{
int i,j;
For(i,2*tree->n_otu-3)
{
For(j,tree->t_edges[i]->n_labels)
{
if(!strcmp(tree->t_edges[i]->labels[j],label)) return tree->t_edges[i];
}
}
return NULL;
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void Print_Square_Matrix_Generic(int n, phydbl *mat)
{
int i,j;
PhyML_Printf("\n");
For(i,n)
{
PhyML_Printf("[%3d]",i);
For(j,n)
{
PhyML_Printf("%7.1G ",mat[i*n+j]);
}
PhyML_Printf("\n");
}
PhyML_Printf("\n");
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void Evolve(calign *data, model *mod, t_tree *tree)
{
int root_state, root_rate_class;
int site,i;
data->n_otu = tree->n_otu;
if(mod->use_m4mod) tree->print_labels = 1;
/* Get the change probability matrices */
Set_Model_Parameters(mod);
For(i,2*tree->n_otu-3) Update_PMat_At_Given_Edge(tree->t_edges[i],tree);
For(site,data->init_len)
{
root_state = root_rate_class = -1;
/* Pick the root nucleotide/aa */
root_state = Pick_State(mod->ns,mod->pi->v);
data->c_seq[0]->state[site] = Reciproc_Assign_State(root_state,tree->io->datatype);
/* Pick the rate class */
root_rate_class = Pick_State(mod->n_catg,mod->gamma_r_proba->v);
/* tree->t_nodes[0] is considered as the root t_node */
Evolve_Recur(tree->t_nodes[0],
tree->t_nodes[0]->v[0],
tree->t_nodes[0]->b[0],
root_state,
root_rate_class,
site,
data,
mod,
tree);
/* PhyML_Printf("%s\n",Write_Tree(tree,NO)); */
data->wght[site] = 1;
}
data->crunch_len = data->init_len;
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
int Pick_State(int n, phydbl *prob)
{
int pos;
phydbl uni;
do
{
pos = rand();
pos = (pos % n);
uni = (phydbl)rand();
uni /= (phydbl)RAND_MAX;
if(uni < prob[pos]) break;
}
while(1);
return (int)pos;
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void Evolve_Recur(t_node *a, t_node *d, t_edge *b, int a_state, int r_class, int site_num, calign *gen_data, model *mod, t_tree *tree)
{
int d_state;
int dim1,dim2;
dim1 = tree->mod->ns * tree->mod->ns;
dim2 = tree->mod->ns;
d_state = Pick_State(mod->ns,b->Pij_rr+r_class*dim1+a_state*dim2);
/* PhyML_Printf("\n>> %c (%d,%d)",Reciproc_Assign_State(d_state,mod->io->datatype),d_state,(int)d_state/mod->m4mod->n_o); */
if(mod->use_m4mod)
{
phydbl rrate; /* relative rate of substitutions */
rrate = mod->m4mod->multipl[(int)d_state/mod->m4mod->n_o];
if(!(b->n_labels%BLOCK_LABELS)) Make_New_Edge_Label(b);
if(rrate > 1.0) strcpy(b->labels[b->n_labels],"FASTER");
else strcpy(b->labels[b->n_labels],"SLOWER");
b->n_labels++;
}
if(d->tax)
{
gen_data->c_seq[d->num]->state[site_num] = Reciproc_Assign_State(d_state,tree->io->datatype);
return;
}
else
{
int i;
For(i,3)
if(d->v[i] != a)
Evolve_Recur(d,d->v[i],d->b[i],
d_state,r_class,site_num,gen_data,
mod,tree);
}
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void Site_Diversity(t_tree *tree)
{
int i,j,k,ns;
int *div,sum;
ns = tree->mod->ns;
div = (int *)mCalloc(ns,sizeof(int));
Site_Diversity_Post(tree->t_nodes[0],tree->t_nodes[0]->v[0],tree->t_nodes[0]->b[0],tree);
Site_Diversity_Pre (tree->t_nodes[0],tree->t_nodes[0]->v[0],tree->t_nodes[0]->b[0],tree);
For(i,2*tree->n_otu-3)
{
For(j,ns)
{
tree->t_edges[i]->div_post_pred_left[j] = 0;
tree->t_edges[i]->div_post_pred_rght[j] = 0;
}
}
For(i,tree->n_pattern)
{
For(j,2*tree->n_otu-3)
{
Binary_Decomposition(tree->t_edges[j]->ui_l[i],div,ns);
sum = 0;
For(k,ns) sum += div[k];
tree->t_edges[j]->div_post_pred_left[sum-1] += tree->data->wght[i];
Binary_Decomposition(tree->t_edges[j]->ui_r[i],div,ns);
sum = 0;
For(k,ns) sum += div[k];
tree->t_edges[j]->div_post_pred_rght[sum-1] += tree->data->wght[i];
}
}
/* For(j,2*tree->n_otu-3) */
/* { */
/* PhyML_Printf("\n. Edge %4d div_left = %4d %4d %4d %4d -- div_rght = %4d %4d %4d %4d", */
/* j, */
/* tree->t_edges[j]->div_post_pred_left[0], */
/* tree->t_edges[j]->div_post_pred_left[1], */
/* tree->t_edges[j]->div_post_pred_left[2], */
/* tree->t_edges[j]->div_post_pred_left[3], */
/* tree->t_edges[j]->div_post_pred_rght[0], */
/* tree->t_edges[j]->div_post_pred_rght[1], */
/* tree->t_edges[j]->div_post_pred_rght[2], */
/* tree->t_edges[j]->div_post_pred_rght[3]); */
/* } */
Free(div);
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void Site_Diversity_Post(t_node *a, t_node *d, t_edge *b, t_tree *tree)
{
if(d->tax) return;
else
{
int i;
For(i,3)
if(d->v[i] != a)
Site_Diversity_Post(d,d->v[i],d->b[i],tree);
Subtree_Union(d,b,tree);
}
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void Site_Diversity_Pre(t_node *a, t_node *d, t_edge *b, t_tree *tree)
{
if(d->tax) return;
else
{
int i;
For(i,3)
if(d->v[i] != a)
{
Subtree_Union(d,d->b[i],tree);
Site_Diversity_Pre(d,d->v[i],d->b[i],tree);
}
}
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void Subtree_Union(t_node *n, t_edge *b_fcus, t_tree *tree)
{
/*
|
|<- b_cus
|
n
/ \
/ \
/ \
*/
int site;
unsigned int *ui, *ui_v1, *ui_v2;
ui = ui_v1 = ui_v2 = NULL;
if(n == b_fcus->left)
{
ui = b_fcus->ui_l;
ui_v1 =
(n == n->b[b_fcus->l_v1]->left)?
(n->b[b_fcus->l_v1]->ui_r):
(n->b[b_fcus->l_v1]->ui_l);
ui_v2 =
(n == n->b[b_fcus->l_v2]->left)?
(n->b[b_fcus->l_v2]->ui_r):
(n->b[b_fcus->l_v2]->ui_l);
}
else
{
ui = b_fcus->ui_r;
ui_v1 =
(n == n->b[b_fcus->r_v1]->left)?
(n->b[b_fcus->r_v1]->ui_r):
(n->b[b_fcus->r_v1]->ui_l);
ui_v2 =
(n == n->b[b_fcus->r_v2]->left)?
(n->b[b_fcus->r_v2]->ui_r):
(n->b[b_fcus->r_v2]->ui_l);
}
For(site,tree->n_pattern) ui[site] = ui_v1[site] | ui_v2[site];
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void Binary_Decomposition(int value, int *bit_vect, int size)
{
int i,cumul;
For(i,size) bit_vect[i] = 0;
cumul = 0;
for(i=size-1;i>=0;i--)
{
if(value - cumul < (int)POW(2,i))
{
bit_vect[i] = 0;
}
else
{
bit_vect[i] = 1;
cumul += (int)POW(2,i);
}
}
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void Print_Diversity_Header(FILE *fp, t_tree *tree)
{
/* PhyML_Fprintf(fp,"t_edge side mean\n"); */
PhyML_Fprintf(fp,"t_edge side diversity count\n");
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void Print_Diversity(FILE *fp, t_tree *tree)
{
int ns;
if(tree->io->datatype == NT) ns = 4;
else if(tree->io->datatype == AA) ns = 20;
Print_Diversity_Pre(tree->t_nodes[0],
tree->t_nodes[0]->v[0],
tree->t_nodes[0]->b[0],
fp,
tree);
/* mean_div_left = .0; */
/* For(k,ns) */
/* { */
/* mean_div_left += (k+1) * tree->t_edges[j]->div_post_pred_left[k]; */
/* } */
/* mean_div_rght = .0; */
/* For(k,ns) mean_div_rght += (k+1) * tree->t_edges[j]->div_post_pred_rght[k]; */
/* mean_div_left /= (phydbl)tree->data->init_len; */
/* mean_div_rght /= (phydbl)tree->data->init_len; */
/* PhyML_Fprintf(fp,"%4d 0 %f\n",j,mean_div_left); */
/* PhyML_Fprintf(fp,"%4d 1 %f\n",j,mean_div_rght); */
/* mean_div_left = .0; */
/* For(k,ns) mean_div_left += tree->t_edges[j]->div_post_pred_left[k]; */
/* mean_div_rght = .0; */
/* For(k,ns) */
/* { */
/* mean_div_rght += tree->t_edges[j]->div_post_pred_rght[k]; */
/* } */
/* if((mean_div_left != tree->data->init_len) || (mean_div_rght != tree->data->init_len)) */
/* { */
/* PhyML_Printf("\n. mean_div_left = %f mean_div_rght = %f init_len = %d", */
/* mean_div_left,mean_div_rght,tree->data->init_len); */
/* PhyML_Printf("\n. Err in file %s at line %d\n",__FILE__,__LINE__); */
/* Warn_And_Exit(""); */
/* } */
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void Print_Diversity_Pre(t_node *a, t_node *d, t_edge *b, FILE *fp, t_tree *tree)
{
int k,ns;
ns = -1;
if(d->tax) return;
else
{
if(tree->io->datatype == NT) ns = 4;
else if(tree->io->datatype == AA) ns = 20;
if(d == b->left) For(k,ns) PhyML_Fprintf(fp,"%4d 0 %2d %4d\n",b->num,k,b->div_post_pred_left[k]);
else For(k,ns) PhyML_Fprintf(fp,"%4d 1 %2d %4d\n",b->num,k,b->div_post_pred_rght[k]);
For(k,3) if(d->v[k] != a) Print_Diversity_Pre(d,d->v[k],d->b[k],fp,tree);
}
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
/* Estimation of density using kernel smoothing.
- where : point where I want to estimate the density,
- x : data vector,
- sample_size : number of data points in x
*/
phydbl Univariate_Kernel_Density_Estimate(phydbl where, phydbl *x, int sample_size)
{
phydbl sd,h;
phydbl density,sqrt2pi,cons;
int i;
sqrt2pi = 2.506628;
sd = SQRT(Var(x,sample_size));
h = 1.06 * sd * POW(sample_size,-1./5.); /* Quick and dirty way to set the bandwidth */
cons = (1./sample_size) * (1./h) * (1./sqrt2pi);
density = .0;
For(i,sample_size) density += EXP(-0.5 * POW((x[i] - where)/h,2));
density *= cons;
return density;
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
/* Estimation of a multivariate density using kernel smoothing.
- where : vector where I want to estimate the density,
- x : data matrix, i.e., sample of vectors,
- sample_size : number of vectors,
- vect_size : vector length.
See "Multivariate Density Estimation" by David Scott. pp 150.
*/
phydbl Multivariate_Kernel_Density_Estimate(phydbl *where, phydbl **x, int sample_size, int vect_size)
{
phydbl sd,*h,cons,density,tmp;
phydbl _2pi;
int i,j;
h = (phydbl *)mCalloc(vect_size,sizeof(phydbl));
_2pi = 6.283185;
For(i,vect_size)
{
sd = SQRT(Var(x[i],sample_size));
/* h[i] = POW(4./(vect_size+2.),1./(vect_size+4)) * sd * POW(sample_size,-1./(vect_size+4)); */
h[i] = sd * POW(sample_size,-1./(vect_size+4));
/* PhyML_Printf("\n. sd = %f, h[i] = %f",sd,h[i]); */
}
cons = sample_size;
For(i,vect_size) cons *= h[i];
cons *= POW(_2pi,vect_size/2.);
cons = 1./cons;
density = .0;
For(i,sample_size)
{
tmp = 1.0;
For(j,vect_size)
{
tmp *= EXP(-0.5 * POW((x[j][i] - where[j])/h[j],2));
}
density += tmp;
}
density *= cons;
Free(h);
return density;
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
phydbl Var(phydbl *x, int n)
{
phydbl mean, sum2;
int i;
mean = Mean(x,n);
sum2 = .0;
For(i,n) sum2 += x[i] * x[i];
return (1./n) * (sum2 - n * POW(mean,2));
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
phydbl Mean(phydbl *x, int n)
{
int i;
phydbl sum;
sum = .0;
For(i,n) sum += x[i];
return sum / n;
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void Best_Of_NNI_And_SPR(t_tree *tree)
{
if(tree->mod->s_opt->random_input_tree) Speed_Spr_Loop(tree); /* Don't do simultaneous NNIs if starting tree is random */
else
{
t_tree *ori_tree,*best_tree;
model *ori_mod,*best_mod;
phydbl *ori_bl,*best_bl;
phydbl best_lnL,ori_lnL,nni_lnL,spr_lnL;
int i;
ori_bl = (phydbl *)mCalloc(2*tree->n_otu-3,sizeof(phydbl));
best_bl = (phydbl *)mCalloc(2*tree->n_otu-3,sizeof(phydbl));
ori_mod = Copy_Model(tree->mod);
best_mod = Copy_Model(tree->mod);
ori_tree = Make_Tree_From_Scratch(tree->n_otu,tree->data);
/* ori_tree = Make_Tree(tree->n_otu); */
/* Init_Tree(ori_tree,ori_tree->n_otu); */
/* Make_All_Tree_Nodes(ori_tree); */
/* Make_All_Tree_Edges(ori_tree); */
best_tree = Make_Tree_From_Scratch(tree->n_otu,tree->data);
/* best_tree = Make_Tree(tree->n_otu); */
/* Init_Tree(best_tree,best_tree->n_otu); */
/* Make_All_Tree_Nodes(best_tree); */
/* Make_All_Tree_Edges(best_tree); */
Copy_Tree(tree,ori_tree);
Record_Br_Len(tree);
For(i,2*tree->n_otu-3) ori_bl[i] = tree->t_edges[i]->l;
best_lnL = UNLIKELY;
Lk(tree);
ori_lnL = tree->c_lnL; /* Record likelihood of the starting tree */
Simu_Loop(tree); /* Perform simultaneous NNIs */
best_lnL = tree->c_lnL; /* Record the likelihood */
nni_lnL = tree->c_lnL;
Copy_Tree(tree,best_tree); /* Record the tree topology and branch lengths */
Record_Br_Len(tree);
For(i,2*tree->n_otu-3) best_bl[i] = tree->t_edges[i]->l;
For(i,2*tree->n_otu-3) best_tree->t_edges[i]->l = best_bl[i];
Record_Model(tree->mod,best_mod);
Copy_Tree(ori_tree,tree); /* Back to the original tree topology */
For(i,2*tree->n_otu-3) tree->t_edges[i]->l = ori_bl[i]; /* Back to the original branch lengths */
Record_Model(ori_mod,tree->mod); /* Back to the original model */
/* Make sure the tree is in its original form */
Lk(tree);
if(FABS(tree->c_lnL - ori_lnL) > tree->mod->s_opt->min_diff_lk_global)
{
PhyML_Printf("\n. ori_lnL = %f, c_lnL = %f",ori_lnL,tree->c_lnL);
PhyML_Printf("\n. Err in file %s at line %d\n",__FILE__,__LINE__);
Warn_And_Exit("");
}
Speed_Spr_Loop(tree);
spr_lnL = tree->c_lnL;
if(tree->c_lnL > best_lnL)
{
best_lnL = tree->c_lnL;
Copy_Tree(tree,best_tree); /* Record tree topology, branch lengths and model parameters */
Record_Br_Len(tree);
For(i,2*tree->n_otu-3) best_bl[i] = tree->t_edges[i]->l;
For(i,2*tree->n_otu-3) best_tree->t_edges[i]->l = best_bl[i];
Record_Model(tree->mod,best_mod);
}
Copy_Tree(best_tree,tree);
Fill_Dir_Table(tree);
Update_Dirs(tree);
Init_P_Lk_Tips_Int(tree);
Init_Ui_Tips(tree);
Init_P_Pars_Tips(tree);
For(i,2*tree->n_otu-3) tree->t_edges[i]->l = best_bl[i];
Record_Model(best_mod,tree->mod);
/* Make sure the current tree has the best topology, branch lengths and model parameters */
Lk(tree);
if(FABS(tree->c_lnL - best_lnL) > tree->mod->s_opt->min_diff_lk_global)
{
PhyML_Printf("\n. best_lnL = %f, c_lnL = %f",best_lnL,tree->c_lnL);
PhyML_Printf("\n. Err in file %s at line %d\n",__FILE__,__LINE__);
Warn_And_Exit("");
}
if(tree->mod->s_opt->print)
{
PhyML_Printf("\n\n. Log likelihood obtained after NNI moves : %f",nni_lnL);
PhyML_Printf("\n. Log likelihood obtained after SPR moves : %f",spr_lnL);
}
Free(ori_bl);
Free(best_bl);
Free_Tree(ori_tree);
Free_Tree(best_tree);
Free_Model(ori_mod);
Free_Model(best_mod);
}
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
/* Polynomial interpolation. Adapted from "Numerical Recipes in C".
Press, Flannery, Teukolsky, Vetterling, 1988.
*/
int Polint(phydbl *xa, phydbl *ya, int n, phydbl x, phydbl *y, phydbl *dy)
{
int i,m,ns=1;
phydbl den,dif,dift,ho,hp,w;
phydbl *c,*d;
dif=FABS(x-xa[1]);
c = (phydbl *)mCalloc(n,sizeof(phydbl));
d = (phydbl *)mCalloc(n,sizeof(phydbl));
for(i=1;i<=n;i++)
{
if((dift=FABS(x-xa[i])) < dif)
{
ns=i;
dif=dift;
}
c[i]=ya[i];
d[i]=ya[i];
}
*y=ya[ns--];
for (m=1;m -SMALL )
{
/* Rprintf("\n. Error in routine POLINT.\n"); */
Exit("\n. Error in routine POLINT.\n");
return(-1);
}
den=w/den;
d[i]=hp*den;
c[i]=ho*den;
}
*y += (*dy=(2*ns < (n-m) ? c[ns+1] : d[ns--]));
}
Free(d);
Free(c);
return(0);
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void JF(t_tree *tree)
{
//printing loglk for each site, to compute SH-like tests */
phydbl sum=0.0;
PhyML_Printf("\n\nSITES LKS:\n");
int n_patterns = (int)FLOOR(tree->n_pattern);
int site=0;
For(site,n_patterns) {
int wei=0;
For(wei,tree->data->wght[site]) {
PhyML_Printf("%f\n",tree->c_lnL_sorted[site] / tree->data->wght[site]);
sum+=tree->c_lnL_sorted[site] / tree->data->wght[site];
}
}
PhyML_Printf("\n\nsum=%f\n\n",sum);
int i=0;
For(i,2*tree->n_otu-3)
{
if((!tree->t_edges[i]->left->tax) && (!tree->t_edges[i]->rght->tax))
{
PhyML_Printf("%3d %f %f %f\n",
tree->t_edges[i]->bip_score,tree->t_edges[i]->alrt_statistic, tree->t_edges[i]->ratio_test,tree->t_edges[i]->l);
}
}
/* //printing loglk for each site, to compute SH-like tests */
/* phydbl sum=0.0; */
/* PhyML_Printf("\n\nSITES LKS:\n"); */
/* int n_patterns = (int)FLOOR(tree->n_pattern); */
/* int site=0; */
/* For(site,n_patterns) { */
/* int wei=0; */
/* For(wei,tree->data->wght[site]) { */
/* PhyML_Printf("%f\n",tree->c_lnL_sorted[site] / tree->data->wght[site]); */
/* sum+=tree->c_lnL_sorted[site] / tree->data->wght[site]; */
/* } */
/* } */
/* PhyML_Printf("\n\nsum=%f\n\n",sum); */
/* int i=0; */
/* For(i,2*tree->n_otu-3) */
/* { */
/* if((!tree->t_edges[i]->left->tax) && (!tree->t_edges[i]->rght->tax)) */
/* { */
/* PhyML_Printf("%3d %f %f %f\n", */
/* tree->t_edges[i]->bip_score,tree->t_edges[i]->alrt_statistic, tree->t_edges[i]->ratio_test,tree->t_edges[i]->l); */
/* } */
/* } */
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
t_tree *Dist_And_BioNJ(calign *cdata, model *mod, option *io)
{
t_tree *tree;
matrix *mat;
if(!io->quiet) PhyML_Printf("\n. Computing pairwise distances...");
mat = ML_Dist(cdata,mod);
Fill_Missing_Dist(mat);
if(!io->quiet) PhyML_Printf("\n\n. Building BioNJ tree...");
mat->tree = Make_Tree_From_Scratch(cdata->n_otu,cdata);
Bionj(mat);
tree = mat->tree;
tree->mat = mat;
return tree;
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void Add_BioNJ_Branch_Lengths(t_tree *tree, calign *cdata, model *mod)
{
matrix *mat;
PhyML_Printf("\n");
PhyML_Printf("\n. Computing branch length estimates...\n");
Order_Tree_CSeq(tree,cdata);
mat = ML_Dist(cdata,mod);
mat->tree = tree;
mat->method = 0;
Bionj_Br_Length(mat);
Free_Mat(mat);
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
t_tree *Read_User_Tree(calign *cdata, model *mod, option *io)
{
t_tree *tree;
PhyML_Printf("\n. Reading tree..."); fflush(NULL);
if(io->n_trees == 1) rewind(io->fp_in_tree);
tree = Read_Tree_File_Phylip(io->fp_in_tree);
if(!tree) Exit("\n. Input tree not found...");
/* Add branch lengths if necessary */
if(!tree->has_branch_lengths) Add_BioNJ_Branch_Lengths(tree,cdata,mod);
return tree;
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void Print_Time_Info(time_t t_beg, time_t t_end)
{
div_t hour,min;
hour = div(t_end-t_beg,3600);
min = div(t_end-t_beg,60 );
min.quot -= hour.quot*60;
PhyML_Printf("\n. Time used %dh%dm%ds\n", hour.quot,min.quot,(int)(t_end-t_beg)%60);
PhyML_Printf("\noooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooo\n");
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
char *Bootstrap_From_String(char *s_tree, calign *cdata, model *mod, option *io)
{
t_tree *tree;
tree = Read_Tree(&s_tree);
if(!tree)
{
PhyML_Printf("\n. Err in file %s at line %d\n",__FILE__,__LINE__);
Warn_And_Exit("");
}
tree->mod = mod;
tree->io = io;
tree->data = cdata;
tree->both_sides = 1;
tree->n_pattern = tree->data->crunch_len;
Order_Tree_CSeq(tree,cdata);
if(tree->mod->s_opt->random_input_tree) Random_Tree(tree);
Fill_Dir_Table(tree);
Update_Dirs(tree);
Make_Tree_4_Pars(tree,cdata,cdata->init_len);
Make_Tree_4_Lk(tree,cdata,cdata->init_len);
tree->triplet_struct = Make_Triplet_Struct(mod);
Unscale_Br_Len_Multiplier_Tree(tree);
Br_Len_Not_Involving_Invar(tree);
Make_Spr_List(tree);
Make_Best_Spr(tree);
tree->both_sides = 1;
Lk(tree);
#ifdef MPI
Bootstrap_MPI(tree);
#else
Bootstrap(tree);
#endif
Free(s_tree);
s_tree = Write_Tree(tree,NO);
Free_Spr_List(tree);
Free_One_Spr(tree->best_spr);
Free_Triplet(tree->triplet_struct);
Free_Tree_Pars(tree);
Free_Tree_Lk(tree);
Free_Tree(tree);
return s_tree;
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
char *aLRT_From_String(char *s_tree, calign *cdata, model *mod, option *io)
{
t_tree *tree;
tree = Read_Tree(&s_tree);
if(!tree)
{
PhyML_Printf("\n. Err in file %s at line %d\n",__FILE__,__LINE__);
Warn_And_Exit("");
}
tree->mod = mod;
tree->io = io;
tree->data = cdata;
tree->both_sides = 1;
tree->n_pattern = tree->data->crunch_len;
Order_Tree_CSeq(tree,cdata);
if(tree->mod->s_opt->random_input_tree) Random_Tree(tree);
Fill_Dir_Table(tree);
Update_Dirs(tree);
Make_Tree_4_Pars(tree,cdata,cdata->init_len);
Make_Tree_4_Lk(tree,cdata,cdata->init_len);
tree->triplet_struct = Make_Triplet_Struct(mod);
Unscale_Br_Len_Multiplier_Tree(tree);
Br_Len_Not_Involving_Invar(tree);
Make_Spr_List(tree);
Make_Best_Spr(tree);
tree->both_sides = 1;
Lk(tree);
aLRT(tree);
Free(s_tree);
s_tree = Write_Tree(tree,NO);
Free_Spr_List(tree);
Free_One_Spr(tree->best_spr);
Free_Triplet(tree->triplet_struct);
Free_Tree_Pars(tree);
Free_Tree_Lk(tree);
Free_Tree(tree);
return s_tree;
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void Prepare_Tree_For_Lk(t_tree *tree)
{
Order_Tree_CSeq(tree,tree->data);
Fill_Dir_Table(tree);
Update_Dirs(tree);
Make_Tree_4_Pars(tree,tree->data,tree->data->init_len);
Make_Tree_4_Lk(tree,tree->data,tree->data->init_len);
tree->triplet_struct = Make_Triplet_Struct(tree->mod);
Br_Len_Not_Involving_Invar(tree);
Unscale_Br_Len_Multiplier_Tree(tree);
Make_Spr_List(tree);
Make_Best_Spr(tree);
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void PhyML_Printf(char *format, ...)
{
va_list ptr;
#ifdef MPI
if(Global_myRank == 0)
{
va_start (ptr, format);
vprintf (format, ptr);
va_end(ptr);
}
#else
va_start (ptr, format);
vprintf (format, ptr);
va_end(ptr);
#endif
fflush (NULL);
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void PhyML_Fprintf(FILE *fp, char *format, ...)
{
va_list ptr;
#ifdef MPI
if(Global_myRank == 0)
{
va_start (ptr, format);
vfprintf (fp,format, ptr);
va_end(ptr);
}
#else
va_start (ptr, format);
vfprintf (fp,format, ptr);
va_end(ptr);
#endif
fflush (NULL);
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void Find_Common_Tips(t_tree *tree1, t_tree *tree2)
{
int i,j;
For(i,tree1->n_otu) tree1->t_nodes[i]->common = 0;
For(i,tree2->n_otu) tree2->t_nodes[i]->common = 0;
For(i,tree1->n_otu)
{
For(j,tree2->n_otu)
{
if(!strcmp(tree1->t_nodes[i]->name,tree2->t_nodes[j]->name))
{
tree1->t_nodes[i]->common = 1;
tree2->t_nodes[j]->common = 1;
break;
}
}
}
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
phydbl Get_Tree_Size(t_tree *tree)
{
int i;
phydbl tree_size;
tree_size = 0.0;
For(i,2*tree->n_otu-3) tree_size += tree->t_edges[i]->l;
/* tree_size = 0.0; */
/* For(i,2*tree->n_otu-3) tree_size += tree->rates->u_cur_l[i]; */
/* For(i,2*tree->n_otu-3) */
/* tree_size += */
/* FABS(tree->rates->nd_t[tree->t_edges[i]->left->num] - */
/* tree->rates->nd_t[tree->t_edges[i]->rght->num]); */
tree->size = tree_size;
return tree_size;
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void Dist_To_Root_Pre(t_node *a, t_node *d, t_edge *b, t_tree *tree)
{
int i;
/* if(b) d->dist_to_root = a->dist_to_root + b->l; */
if(b) d->dist_to_root = a->dist_to_root + tree->rates->cur_l[d->num];
if(d->tax) return;
else
{
For(i,3)
if((d->v[i] != a) && (d->b[i] != tree->e_root))
Dist_To_Root_Pre(d,d->v[i],d->b[i],tree);
}
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void Dist_To_Root(t_node *n_root, t_tree *tree)
{
n_root->v[0]->dist_to_root = tree->rates->cur_l[n_root->v[0]->num];
n_root->v[1]->dist_to_root = tree->rates->cur_l[n_root->v[1]->num];
/* n_root->v[0]->dist_to_root = tree->e_root->l * tree->n_root_pos; */
/* n_root->v[1]->dist_to_root = tree->e_root->l * (1. - tree->n_root_pos); */
Dist_To_Root_Pre(n_root,n_root->v[0],NULL,tree);
Dist_To_Root_Pre(n_root,n_root->v[1],NULL,tree);
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
/* 'Borrowed' fromn libgen */
char *Basename(char *path)
{
char *p;
if( path == NULL || *path == '\0' ) return ".";
p = path + strlen(path) - 1;
while( *p == '/' )
{
if( p == path ) return path;
*p-- = '\0';
}
while( p >= path && *p != '/' ) p--;
return p + 1;
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
/* Find the Last Common Ancestor of n1 and n2 */
t_node *Find_Lca_Pair_Of_Nodes(t_node *n1, t_node *n2, t_tree *tree)
{
t_node **list1, **list2, *lca;
int size1, size2;
if(!tree->n_root)
{
PhyML_Printf("\n. The tree must be rooted in this function.");
PhyML_Printf("\n. Err in file %s at line %d\n",__FILE__,__LINE__);
Warn_And_Exit("");
}
list1 = (t_node **)mCalloc(2*tree->n_otu-1,sizeof(t_node *));
list2 = (t_node **)mCalloc(2*tree->n_otu-1,sizeof(t_node *));
Get_List_Of_Ancestors(n1,list1,&size1,tree);
Get_List_Of_Ancestors(n2,list2,&size2,tree);
while(list1[size1] == list2[size2])
{
size1--;
size2--;
if(size1 < 0 || size2 < 0) break;
}
lca = list1[size1+1];
Free(list1);
Free(list2);
return lca;
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
/* Find the Last Common Ancestor of all the nodes in node_list */
t_node *Find_Lca_Clade(t_node **node_list, int node_list_size, t_tree *tree)
{
t_node ***list, *lca;
int *size;
int i;
if(!tree->n_root)
{
PhyML_Printf("\n. The tree must be rooted in this function.");
PhyML_Printf("\n. Err in file %s at line %d\n",__FILE__,__LINE__);
Warn_And_Exit("");
}
list = (t_node ***)mCalloc(node_list_size,sizeof(t_node **));
For(i,node_list_size) list[i] = (t_node **)mCalloc(2*tree->n_otu-1,sizeof(t_node *));
size = (int *)mCalloc(node_list_size,sizeof(int));
For(i,node_list_size) Get_List_Of_Ancestors(node_list[i],list[i],size+i,tree);
do
{
For(i,node_list_size-1)
if(list[i][size[i]] != list[i+1][size[i+1]])
break;
if(i != node_list_size-1) break;
For(i,node_list_size)
{
size[i]--;
if(size[i] == 1) break; // We have reached the tip corresponding to node_list[i]
}
if(node_list_size == 1) break;
}while(1);
lca = list[0][size[0]+1];
For(i,node_list_size) Free(list[i]);
Free(list);
Free(size);
return lca;
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
/* Returns the list of the ancestors of ref_t_node from ref_t_node to the root included */
void Get_List_Of_Ancestors(t_node *ref_node, t_node **list, int *size, t_tree *tree)
{
t_node *n;
*size = 1;
n = ref_node;
list[0] = n;
while(n != tree->n_root)
{
n = n->anc;
*size = *size+1;
list[*size] = n;
}
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
int Edge_Num_To_Node_Num(int edge_num, t_tree *tree)
{
int node_num;
t_edge *b;
b = tree->t_edges[edge_num];
node_num = (b->left == b->rght->anc)?(b->rght->num):(b->left->num);
return node_num;
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void Branch_Lengths_To_Time_Lengths(t_tree *tree)
{
Branch_Lengths_To_Time_Lengths_Pre(tree->n_root,tree->n_root->v[0],tree);
Branch_Lengths_To_Time_Lengths_Pre(tree->n_root,tree->n_root->v[1],tree);
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void Branch_Lengths_To_Time_Lengths_Pre(t_node *a, t_node *d, t_tree *tree)
{
int i;
/* tree->rates->cur_l[d->num] = FABS(tree->rates->nd_t[d->num] - tree->rates->nd_t[a->num]); */
tree->rates->cur_l[d->num] = tree->rates->nd_t[d->num] - tree->rates->nd_t[a->num];
if(d->tax) return;
else
{
For(i,3)
if((d->v[i] != a) && (d->b[i] != tree->e_root))
Branch_Lengths_To_Time_Lengths_Pre(d,d->v[i],tree);
}
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void Branch_Lengths_To_Rate_Lengths(t_tree *tree)
{
Branch_Lengths_To_Rate_Lengths_Pre(tree->n_root,tree->n_root->v[0],tree);
Branch_Lengths_To_Rate_Lengths_Pre(tree->n_root,tree->n_root->v[1],tree);
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void Branch_Lengths_To_Rate_Lengths_Pre(t_node *a, t_node *d, t_tree *tree)
{
int i;
tree->rates->cur_l[d->num] =
tree->rates->br_r[d->num] *
tree->rates->clock_r *
tree->rates->norm_fact;
if(d->tax) return;
else
{
For(i,3)
if((d->v[i] != a) && (d->b[i] != tree->e_root))
Branch_Lengths_To_Rate_Lengths_Pre(d,d->v[i],tree);
}
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
int Find_Clade(char **tax_name_list, int list_size, t_tree *tree)
{
int *tax_num_list;
t_node **tax_node_list;
int i,j;
int n_matches;
t_node *lca;
tax_num_list = (int *)mCalloc(list_size,sizeof(int));
tax_node_list = (t_node **)mCalloc(list_size,sizeof(t_node *));
For(i,list_size) tax_num_list[i] = -1;
n_matches = 0;
For(i,list_size)
{
For(j,tree->n_otu)
{
if(!strcmp(tax_name_list[i],tree->t_nodes[j]->name))
{
tax_num_list[i] = tree->t_nodes[j]->num;
tax_node_list[i] = tree->t_nodes[j];
n_matches++;
}
}
}
lca = Find_Lca_Clade(tax_node_list,n_matches,tree);
if(lca) return lca->num;
else return -1;
/* if(list_size == tree->n_otu) /\* Root node *\/ */
/* { */
/* int i,j; */
/* int score; */
/* score = 0; */
/* For(i,list_size) */
/* { */
/* For(j,tree->n_otu) */
/* { */
/* /\* if(!strcmp(tax_name_list[i],tree->t_nodes[j]->name)) score++; *\/ */
/* if(tax_num_list[i] == tree->t_nodes[j]->num) score++; */
/* } */
/* } */
/* Free(tax_num_list); */
/* if(score == tree->n_otu) return tree->n_root->num; */
/* else return -1; */
/* } */
/* else */
/* { */
/* int num; */
/* num = -1; */
/* Free_Bip(tree); */
/* Alloc_Bip(tree); */
/* Get_Bip(tree->t_nodes[0],tree->t_nodes[0]->v[0],tree); */
/* Find_Clade_Pre(tree->n_root,tree->n_root->v[0],tax_num_list,list_size,&num,tree); */
/* Find_Clade_Pre(tree->n_root,tree->n_root->v[1],tax_num_list,list_size,&num,tree); */
/* Free(tax_num_list); */
/* return num; */
/* } */
Free(tax_node_list);
Free(tax_num_list);
return -1;
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void Find_Clade_Pre(t_node *a, t_node *d, int *tax_num_list, int list_size, int *num, t_tree *tree)
{
int i,j,k;
int score;
For(i,3)
if((d->v[i] == a) || (d->b[i] == tree->e_root))
{
if(list_size == d->bip_size[i])
{
score = 0;
For(j,d->bip_size[i])
{
For(k,list_size)
{
if(tax_num_list[k] == d->bip_node[i][j]->num)
{
score++;
break;
}
}
}
if(score == list_size) *num = d->num;
}
break;
}
if(d->tax) return;
else
For(i,3)
if((d->v[i] != a) && (d->b[i] != tree->e_root))
Find_Clade_Pre(d,d->v[i],tax_num_list,list_size,num,tree);
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void Read_Clade_Priors(char *file_name, t_tree *tree)
{
FILE *fp;
char *s,*line;
int n_clade_priors;
int clade_size;
char **clade_list;
int i,pos;
phydbl prior_low,prior_up;
int node_num;
PhyML_Printf("\n");
PhyML_Printf("\n. Reading prior on node ages.\n");
line = (char *)mCalloc(T_MAX_LINE,sizeof(char));
s = (char *)mCalloc(T_MAX_LINE,sizeof(char));
clade_list = (char **)mCalloc(tree->n_otu,sizeof(char *));
For(i,tree->n_otu) clade_list[i] = (char *)mCalloc(T_MAX_NAME,sizeof(char));
fp = Openfile(file_name,0);
n_clade_priors = 0;
do
{
if(!fgets(line,T_MAX_LINE,fp)) break;
clade_size = 0;
pos = 0;
do
{
i = 0;
while(line[pos] == ' ') pos++;
while((line[pos] != ' ') && (line[pos] != '\n') && line[pos] != '#')
{
s[i] = line[pos];
i++;
pos++;
}
s[i] = '\0';
/* PhyML_Printf("\n. s = %s\n",s); */
if(line[pos] == '\n' || line[pos] == '#') break;
pos++;
if(strcmp(s,"|"))
{
strcpy(clade_list[clade_size],s);
clade_size++;
}
else
break;
}
while(1);
if(line[pos] != '#' && line[pos] != '\n')
{
double val1, val2;
/* sscanf(line+pos,"%lf %lf",&prior_up,&prior_low); */
sscanf(line+pos,"%lf %lf",&val1,&val2);
prior_up = (phydbl)val1;
prior_low = (phydbl)val2;
node_num = -1;
if(!strcmp("@root@",clade_list[0])) node_num = tree->n_root->num;
else node_num = Find_Clade(clade_list, clade_size, tree);
n_clade_priors++;
if(node_num < 0)
{
PhyML_Printf("\n");
PhyML_Printf("\n");
PhyML_Printf("\n. .................................................................");
PhyML_Printf("\n. WARNING: could not find any clade in the tree referred to with the following taxon names:");
For(i,clade_size) PhyML_Printf("\n. \"%s\"",clade_list[i]);
PhyML_Printf("\n. .................................................................");
/* sleep(3); */
}
else
{
tree->rates->t_has_prior[node_num] = YES;
tree->rates->t_prior_min[node_num] = MIN(prior_low,prior_up);
tree->rates->t_prior_max[node_num] = MAX(prior_low,prior_up);
if(FABS(prior_low - prior_up) < 1.E-6 && tree->t_nodes[node_num]->tax == YES)
tree->rates->nd_t[node_num] = prior_low;
PhyML_Printf("\n");
PhyML_Printf("\n. [%3d]..................................................................",n_clade_priors);
PhyML_Printf("\n. Node %4d matches the clade referred to with the following taxon names:",node_num);
For(i,clade_size) PhyML_Printf("\n. - \"%s\"",clade_list[i]);
PhyML_Printf("\n. Lower bound set to: %15f time units.",MIN(prior_low,prior_up));
PhyML_Printf("\n. Upper bound set to: %15f time units.",MAX(prior_low,prior_up));
PhyML_Printf("\n. .......................................................................");
}
}
}
while(1);
PhyML_Printf("\n. Read prior information on %d %s.",n_clade_priors,n_clade_priors > 1 ? "clades":"clade");
if(!n_clade_priors)
{
PhyML_Printf("\n. PhyTime could not find any prior on node age.");
PhyML_Printf("\n. This is likely due to a problem in the calibration ");
PhyML_Printf("\n. file format. Make sure, for instance, that there is ");
PhyML_Printf("\n. a blank character between the end of the last name");
PhyML_Printf("\n. of each clade and the character `|'. Otherwise, ");
PhyML_Printf("\n. please refer to the example file.\n");
PhyML_Printf("\n. Err in file %s at line %d\n",__FILE__,__LINE__);
Warn_And_Exit("");
}
For(i,tree->n_otu) Free(clade_list[i]);
Free(clade_list);
Free(line);
Free(s);
fclose(fp);
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
t_edge *Find_Root_Edge(FILE *fp_input_tree, t_tree *tree)
{
char **subs;
int degree;
int i,j;
t_node *left, *rght;
int l_r, r_l;
int score;
char *line;
char c;
t_edge *root_edge;
line = (char *)mCalloc(T_MAX_LINE,sizeof(char));
rewind(fp_input_tree);
do c=fgetc(fp_input_tree);
while((c != '(') && (c != EOF));
if(c==EOF)
{
Free(line);
return NULL;
}
i=0;
for(;;)
{
if((c == ' ') || (c == '\n'))
{
c=fgetc(fp_input_tree);
if(c==EOF) break;
else continue;
}
line[i]=c;
i++;
c=fgetc(fp_input_tree);
if(c==EOF || c==';') break;
}
Free_Bip(tree);
Alloc_Bip(tree);
Get_Bip(tree->t_nodes[0],tree->t_nodes[0]->v[0],tree);
subs = Sub_Trees(line,°ree);
Clean_Multifurcation(subs,degree,3);
if(degree != 2)
{
PhyML_Printf("\n. The tree does not seem to be rooted...");
PhyML_Printf("\n. Err in file %s at line %d\n",__FILE__,__LINE__);
Warn_And_Exit("");
}
left = rght = NULL;
l_r = r_l = -1;
For(i,2*tree->n_otu-3)
{
left = tree->t_edges[i]->left;
rght = tree->t_edges[i]->rght;
l_r = tree->t_edges[i]->l_r;
r_l = tree->t_edges[i]->r_l;
score = 0;
For(j,left->bip_size[l_r]) if(strstr(subs[1],left->bip_node[l_r][j]->name)) score++;
if(score == left->bip_size[l_r]) break;
score = 0;
For(j,rght->bip_size[r_l]) if(strstr(subs[1],rght->bip_node[r_l][j]->name)) score++;
if(score == rght->bip_size[r_l]) break;
}
root_edge = tree->t_edges[i];
For(i,NODE_DEG_MAX) Free(subs[i]);
Free(subs);
Free(line);
if(i == 2*tree->n_otu-3)
{
PhyML_Printf("\n. Could not find the root edge...");
PhyML_Printf("\n. Err in file %s at line %d\n",__FILE__,__LINE__);
Warn_And_Exit("");
}
return root_edge;
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void Copy_Tree_Topology_With_Labels(t_tree *ori, t_tree *cpy)
{
int i,j;
For(i,2*ori->n_otu-2)
{
For(j,3)
{
if(ori->t_nodes[i]->v[j])
{
cpy->t_nodes[i]->v[j] = cpy->t_nodes[ori->t_nodes[i]->v[j]->num];
cpy->t_nodes[i]->l[j] = ori->t_nodes[i]->l[j];
}
else
cpy->t_nodes[i]->v[j] = NULL;
}
cpy->t_nodes[i]->num = ori->t_nodes[i]->num;
cpy->t_nodes[i]->tax = 0;
}
For(i,2*ori->n_otu-3)
{
cpy->t_edges[i]->l = ori->t_edges[i]->l;
}
For(i,ori->n_otu)
{
cpy->t_nodes[i]->tax = 1;
strcpy(cpy->t_nodes[i]->name,ori->t_nodes[i]->name);
}
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
option *Get_Input(int argc, char **argv)
{
option *io;
model *mod;
optimiz *s_opt;
m4 *m4mod;
io = (option *)Make_Input();
mod = (model *)Make_Model_Basic();
s_opt = (optimiz *)Make_Optimiz();
m4mod = (m4 *)M4_Make_Light();
Set_Defaults_Input(io);
Set_Defaults_Model(mod);
Set_Defaults_Optimiz(s_opt);
io->mod = mod;
io->mod->m4mod = m4mod;
mod->io = io;
mod->s_opt = s_opt;
#ifdef MPI
Read_Command_Line(io,argc,argv);
#elif defined (PHYTIME)
Read_Command_Line(io,argc,argv);
#else
putchar('\n');
switch (argc)
{
case 1:
{
Launch_Interface(io);
break;
}
/*
case 2:
Usage();
break;
*/
default:
Read_Command_Line(io,argc,argv);
}
#endif
return io;
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void Set_Model_Name(model *mod)
{
if(mod->io->datatype == NT)
{
switch(mod->whichmodel)
{
case JC69:
{
strcpy(mod->modelname, "JC69");
break;
}
case K80:
{
strcpy(mod->modelname, "K80");
break;
}
case F81:
{
strcpy(mod->modelname, "F81");
break;
}
case HKY85:
{
strcpy(mod->modelname, "HKY85");
break;
}
case F84:
{
strcpy(mod->modelname, "F84");
break;
}
case TN93:
{
strcpy(mod->modelname, "TN93");
break;
}
case GTR:
{
strcpy(mod->modelname, "GTR");
break;
}
case CUSTOM:
{
strcpy(mod->modelname, "Custom");
break;
}
default:
{
PhyML_Printf("\n. Unknown model name.\n");
PhyML_Printf("\n. Err in file %s at line %d\n",__FILE__,__LINE__);
Warn_And_Exit("");
break;
}
}
}
else if(mod->io->datatype == AA)
{
switch(mod->whichmodel)
{
case DAYHOFF:
{
strcpy(mod->modelname, "Dayhoff");
break;
}
case JTT:
{
strcpy(mod->modelname, "JTT");
break;
}
case MTREV:
{
strcpy(mod->modelname, "MtREV");
break;
}
case LG:
{
strcpy(mod->modelname, "LG");
break;
}
case WAG:
{
strcpy(mod->modelname, "WAG");
break;
}
case DCMUT:
{
strcpy(mod->modelname, "DCMut");
break;
}
case RTREV:
{
strcpy(mod->modelname, "RtREV");
break;
}
case CPREV:
{
strcpy(mod->modelname, "CpREV");
break;
}
case VT:
{
strcpy(mod->modelname, "VT");
break;
}
case BLOSUM62:
{
strcpy(mod->modelname, "Blosum62");
break;
}
case MTMAM:
{
strcpy(mod->modelname, "MtMam");
break;
}
case MTART:
{
strcpy(mod->modelname, "MtArt");
break;
}
case HIVW:
{
strcpy(mod->modelname, "HIVw");
break;
}
case HIVB:
{
strcpy(mod->modelname, "HIVb");
break;
}
case CUSTOMAA:
{
strcpy(mod->modelname, "Custom");
break;
}
default:
{
PhyML_Printf("\n. Unknown model name.\n");
PhyML_Printf("\n. Err in file %s at line %d\n",__FILE__,__LINE__);
Warn_And_Exit("");
break;
}
}
}
else if(mod->io->datatype == GENERIC)
{
strcpy(mod->modelname, "JC69");
}
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void Adjust_Min_Diff_Lk(t_tree *tree)
{
int exponent;
exponent = (int)FLOOR(log10(FABS(tree->c_lnL)));
if(sizeof(phydbl) == 4)
{
tree->mod->s_opt->min_diff_lk_global = POW(10.,exponent - FLT_DIG + 1);
tree->mod->s_opt->min_diff_lk_local = tree->mod->s_opt->min_diff_lk_global;
tree->mod->s_opt->min_diff_lk_move = tree->mod->s_opt->min_diff_lk_global;
}
/* PhyML_Printf("\n. Exponent = %d Precision = %E DIG = %d",exponent,tree->mod->s_opt->min_diff_lk_global,FLT_DIG); */
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
/*!
tree->t_nodes[i]->name is initially a number. It is translated into
a string of characters using the names provided in the tax_name
array.
*/
void Translate_Tax_Names(char **tax_names, t_tree *tree)
{
int i;
int tax_num;
For(i,tree->n_otu)
{
tax_num = strtol(tree->t_nodes[i]->name,NULL,10);
tree->t_nodes[i]->name = tax_names[tax_num-1];
}
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
/*!
Skip coment in NEXUS file.
*/
void Skip_Comment(FILE *fp)
{
int in_comment;
char c;
in_comment = 1;
do
{
c = fgetc(fp);
if(c == EOF) break;
if(c == '[') in_comment++;
else if(c == ']') in_comment--;
}
while(in_comment);
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
/*!
Determine the most appropriate position of the root if outgroup taxa are specified.
*/
void Get_Best_Root_Position(t_tree *tree)
{
int i,j;
phydbl eps;
phydbl s, s_max;
t_edge *best_edge;
int has_outgrp;
best_edge = NULL;
if(tree->n_root)
{
PhyML_Printf("\n. Tree already has a root.");
PhyML_Printf("\n. Err in file %s at line %d\n",__FILE__,__LINE__);
Warn_And_Exit("");
}
if(strstr(tree->t_nodes[0]->name,"*"))
{
/* PhyML_Printf("\n. Found outgroup taxon: %s",tree->t_nodes[0]->name); */
tree->t_nodes[0]->s_ingrp[0] = 0;
tree->t_nodes[0]->s_outgrp[0] = 1;
}
else
{
tree->t_nodes[0]->s_ingrp[0] = 1;
tree->t_nodes[0]->s_outgrp[0] = 0;
}
has_outgrp = NO;
Get_Best_Root_Position_Post(tree->t_nodes[0],tree->t_nodes[0]->v[0],&has_outgrp,tree);
Get_Best_Root_Position_Pre(tree->t_nodes[0],tree->t_nodes[0]->v[0],tree);
if(has_outgrp == YES)
{
eps = 1.E-10;
s = s_max = 0.0;
For(i,2*tree->n_otu-2)
{
For(j,3)
{
s = (tree->t_nodes[i]->s_outgrp[j]+eps) / (tree->t_nodes[i]->s_ingrp[j] + eps) ;
/* printf("\n. [%d %d] %d %d",i,j,tree->t_nodes[i]->s_outgrp[j],tree->t_nodes[i]->s_ingrp[j]); */
if(s > s_max)
{
s_max = s;
best_edge = tree->t_nodes[i]->b[j];
}
}
}
Add_Root(best_edge,tree);
}
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
/*!
Determine the most appropriate position of the root if outgroup taxa are specified.
Post-traversal.
*/
void Get_Best_Root_Position_Post(t_node *a, t_node *d, int *has_outgrp, t_tree *tree)
{
if(d->tax)
{
if(strstr(d->name,"*"))
{
*has_outgrp = YES;
/* PhyML_Printf("\n. Found outgroup taxon: %s",d->name); */
d->s_ingrp[0] = 0;
d->s_outgrp[0] = 1;
}
else
{
d->s_ingrp[0] = 1;
d->s_outgrp[0] = 0;
}
return;
}
else
{
int i;
For(i,3)
if(d->v[i] != a && (d->b[i] != tree->e_root))
Get_Best_Root_Position_Post(d,d->v[i],has_outgrp,tree);
Get_OutIn_Scores(a,d);
}
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
/*!
Determine the most appropriate position of the root if outgroup taxa are specified.
Pre-traversal.
*/
void Get_Best_Root_Position_Pre(t_node *a, t_node *d, t_tree *tree)
{
if(d->tax)
{
return;
}
else
{
int i;
For(i,3)
if(d->v[i] != a && (d->b[i] != tree->e_root))
{
Get_OutIn_Scores(d->v[i],d);
Get_Best_Root_Position_Pre(d,d->v[i],tree);
}
}
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
/*!
Determine the most appropriate position of the root if outgroup taxa are specified.
Core.
*/
void Get_OutIn_Scores(t_node *a, t_node *d)
{
int i,d_v1,d_v2,v1_d,v2_d,d_a;
d_a = v1_d = v2_d = -1;
d_v1 = d_v2 = -1;
For(i,3)
{
if(d->v[i] != a)
{
if(d_v1 < 0) d_v1 = i;
else d_v2 = i;
}
}
For(i,3) if(d->v[i] == a) { d_a = i; break; }
For(i,3) if(d->v[d_v1]->v[i] == d) { v1_d = i; break; }
For(i,3) if(d->v[d_v2]->v[i] == d) { v2_d = i; break; }
d->s_ingrp[d_a] =
d->v[d_v1]->s_ingrp[v1_d] +
d->v[d_v2]->s_ingrp[v2_d] ;
d->s_outgrp[d_a] =
d->v[d_v1]->s_outgrp[v1_d] +
d->v[d_v2]->s_outgrp[v2_d] ;
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
int Check_Sequence_Name(char *s)
{
int i;
/* if(rindex(s,':')) */
For(i,strlen(s))
{
if(s[i] == ':')
{
PhyML_Printf("\n. Character ':' is not permitted in sequence name (%s).",s);
PhyML_Printf("\n. Err in file %s at line %d",__FILE__,__LINE__);
Warn_And_Exit("");
}
}
/* if(rindex(s,',')) */
For(i,strlen(s))
{
if(s[i] == ',')
{
PhyML_Printf("\n. Character ',' is not permitted in sequence name (%s).",s);
PhyML_Printf("\n. Err in file %s at line %d",__FILE__,__LINE__);
Warn_And_Exit("");
}
}
/* if(rindex(s,' ')) */
For(i,strlen(s))
{
if(s[i] == ' ')
{
PhyML_Printf("\n. Character ' ' is not permitted in sequence name (%s).",s);
PhyML_Printf("\n. Err in file %s at line %d",__FILE__,__LINE__);
Warn_And_Exit("");
}
}
return 1;
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
int Scale_Subtree_Height(t_node *a, phydbl K, phydbl floor, int *n_nodes, t_tree *tree)
{
phydbl new_height;
*n_nodes = 0;
new_height = .0;
if(!(tree->rates->nd_t[a->num] > floor))
new_height = K*(tree->rates->nd_t[a->num]-floor)+floor;
if(a == tree->n_root)
{
tree->rates->nd_t[tree->n_root->num] = new_height;
*n_nodes = 1;
Scale_Node_Heights_Post(tree->n_root,tree->n_root->v[0],K,floor,n_nodes,tree);
Scale_Node_Heights_Post(tree->n_root,tree->n_root->v[1],K,floor,n_nodes,tree);
}
else
{
int i;
if(new_height < tree->rates->nd_t[a->anc->num]) return 0;
else
{
tree->rates->nd_t[a->num] = new_height;
*n_nodes = 1;
}
For(i,3)
if(a->v[i] != a->anc && a->b[i] != tree->e_root)
{
Scale_Node_Heights_Post(a,a->v[i],K,floor,n_nodes,tree);
}
}
return 1;
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void Scale_Node_Heights_Post(t_node *a, t_node *d, phydbl K, phydbl floor, int *n_nodes, t_tree *tree)
{
if(d == tree->n_root)
{
PhyML_Printf("\n. Err in file %s at line %d\n",__FILE__,__LINE__);
Warn_And_Exit("");
}
if(d->tax)
{
if(!(tree->rates->nd_t[d->num] > floor))
{
/* Scaling does not change the node height here
but, in theory this tip is among the scaled
nodes. Therefore needs to count it in for
working out correct Hastings ratios
*/
/* *n_nodes = *n_nodes+1; */
}
return;
}
else
{
int i;
/* It is tempting to set floor = tree->rates->t_prior_max[d->num]; but
it then becomes possible for nodes with different floor values
to have their orders interverted (i.e., ancestor below descendant)
*/
if(!(tree->rates->nd_t[d->num] > floor))
{
tree->rates->nd_t[d->num] = K*(tree->rates->nd_t[d->num]-floor)+floor;
*n_nodes = *n_nodes+1;
}
if(tree->rates->nd_t[d->num] < tree->rates->nd_t[a->num])
{
PhyML_Printf("\n. K = %f floor = %f t_prior_max(a) = %f t_prior_max(d) = %f a->t = %f d->t %f",
K,floor,tree->rates->t_prior_max[a->num],tree->rates->t_prior_max[d->num],
tree->rates->nd_t[a->num],tree->rates->nd_t[d->num]);
PhyML_Printf("\n. Err in file %s at line %d\n",__FILE__,__LINE__);
Warn_And_Exit("");
}
For(i,3)
if(d->v[i] != a && d->b[i] != tree->e_root)
Scale_Node_Heights_Post(d,d->v[i],K,floor,n_nodes,tree);
}
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
int Scale_Subtree_Rates(t_node *a, phydbl mult, int *n_nodes, t_tree *tree)
{
int res;
int i;
*n_nodes = 0;
res = 1;
if(a == tree->n_root)
{
res = Scale_Subtree_Rates_Post(a,a->v[0],mult,n_nodes,tree);
if(res) res = Scale_Subtree_Rates_Post(a,a->v[1],mult,n_nodes,tree);
return res;
}
else
{
For(i,3) if((a->v[i] != a->anc) &&
(a->b[i] != tree->e_root) &&
(res == 1)) res = Scale_Subtree_Rates_Post(a,a->v[i],mult,n_nodes,tree);
return res;
}
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void Check_Br_Len_Bounds(t_tree *tree)
{
int i;
t_edge *b;
b = NULL;
For(i,2*tree->n_otu-3)
{
b = tree->t_edges[i];
if(b->l > tree->mod->l_max) b->l = tree->mod->l_max;
if(b->l < tree->mod->l_min) b->l = tree->mod->l_min;
}
if(tree->rates)
{
For(i,2*tree->n_otu-3)
{
if(tree->rates->u_cur_l[i] > tree->mod->l_max) tree->rates->u_cur_l[i] = tree->mod->l_max;
if(tree->rates->u_cur_l[i] < tree->mod->l_min) tree->rates->u_cur_l[i] = tree->mod->l_min;
}
}
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
int Scale_Subtree_Rates_Post(t_node *a, t_node *d, phydbl mult, int *n_nodes, t_tree *tree)
{
if(tree->rates->model_log_rates == YES)
{
tree->rates->br_r[d->num] += LOG(mult);
}
else
{
tree->rates->br_r[d->num] *= mult;
}
*n_nodes = *n_nodes+1;
if(tree->rates->br_r[d->num] < tree->rates->min_rate) return 0;
if(tree->rates->br_r[d->num] > tree->rates->max_rate) return 0;
if(d->tax) return 1;
else
{
int i,res;
res = 1;
For(i,3)
{
if((d->v[i] != a) &&
(d->b[i] != tree->e_root) &&
(res == 1))
{
res = Scale_Subtree_Rates_Post(d,d->v[i],mult,n_nodes,tree);
}
}
return res;
}
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void Get_Node_Ranks(t_tree *tree)
{
tree->n_root->rank = 1;
Get_Node_Ranks_Pre(tree->n_root,tree->n_root->v[0],tree);
Get_Node_Ranks_Pre(tree->n_root,tree->n_root->v[1],tree);
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void Get_Node_Ranks_Pre(t_node *a, t_node *d,t_tree *tree)
{
d->rank = a->rank+1;
if(d->tax) return;
else
{
int i;
For(i,3)
{
if(d->v[i] != a && d->b[i] != tree->e_root)
{
Get_Node_Ranks_Pre(d,d->v[i],tree);
}
}
}
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void Log_Br_Len(t_tree *tree)
{
int i;
For(i,2*tree->n_otu-3) tree->t_edges[i]->l = LOG(tree->t_edges[i]->l);
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void Make_Short_L(t_tree *tree)
{
if(!tree->short_l)
tree->short_l = (phydbl *)mCalloc(tree->n_short_l,sizeof(phydbl));
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
phydbl Diff_Lk_Norm_At_Given_Edge(t_edge *b, t_tree *tree)
{
int i,dim,err;
phydbl lk_exact,lk_norm,sum;
Record_Br_Len(tree);
dim = 2*tree->n_otu-3;
sum = 0.0;
For(i,tree->n_short_l)
{
b->l = tree->short_l[i];
lk_exact = Lk_At_Given_Edge(b,tree);
lk_norm = tree->norm_scale + Log_Dnorm(b->l,tree->rates->mean_l[b->num],
tree->rates->cov_l[b->num*dim+b->num],&err);
if(err)
{
PhyML_Printf("\n. Err in file %s at line %d\n",__FILE__,__LINE__);
Warn_And_Exit("");
}
sum += pow(lk_exact - lk_norm,2);
}
Restore_Br_Len(tree);
Lk_At_Given_Edge(b,tree);
return(sum);
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void Adjust_Variances(t_tree *tree)
{
int i;
phydbl new_diff,curr_diff;
Make_Short_L(tree);
For(i,tree->n_short_l)
{
tree->short_l[i] = tree->mod->l_min + i*(0.1 - tree->mod->l_min)/tree->n_short_l;
}
For(i,2*tree->n_otu-3)
{
if(tree->t_edges[i]->l < 1.1*tree->mod->l_min)
{
tree->rates->mean_l[i] = -1.00;
tree->rates->cov_l[i*(2*tree->n_otu-3)+i] = 0.1;
tree->norm_scale = -100;
new_diff = curr_diff = 10.0;
do
{
curr_diff = new_diff;
Generic_Brent_Lk(&(tree->norm_scale),
-1E+6,
0.0,
1.E-10,
10000,
NO,
Wrap_Diff_Lk_Norm_At_Given_Edge,tree->t_edges[i],tree,NULL);
/* Generic_Brent_Lk(&(tree->rates->mean_l[0]), */
/* -100., */
/* 10*tree->mod->l_min, */
/* 1.E-3, */
/* 10000, */
/* NO, */
/* Wrap_Diff_Lk_Norm_At_Given_Edge,tree->t_edges[0],tree,NULL); */
Generic_Brent_Lk(&(tree->rates->cov_l[i*(2*tree->n_otu-3)+i]),
0.0,
10.0,
1.E-10,
10000,
NO,
Wrap_Diff_Lk_Norm_At_Given_Edge,tree->t_edges[i],tree,NULL);
new_diff = Diff_Lk_Norm_At_Given_Edge(tree->t_edges[i],tree);
}while(FABS(new_diff-curr_diff) > 1.E-3);
}
}
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
phydbl Effective_Sample_Size(phydbl first_val, phydbl last_val, phydbl sum, phydbl sumsq, phydbl sumcurnext, int n)
{
phydbl numerator,denom;
phydbl mean;
phydbl r;
mean = sum / n;
denom = sumsq - n * POW(mean,2);
numerator = sumcurnext - (n+1.)*POW(mean,2) + (first_val+last_val)*mean;
r = numerator/denom;
return (phydbl)n * (1.-r)/(1.+r);
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
phydbl Rescale_Free_Rate_Tree(t_tree *tree)
{
int i;
phydbl sum;
sum = 0.0;
For(i,tree->mod->n_catg) sum += tree->mod->gamma_rr->v[i]*tree->mod->gamma_r_proba->v[i];
For(i,tree->mod->n_catg) tree->mod->gamma_rr->v[i] /= sum;
For(i,2*tree->n_otu-3) tree->t_edges[i]->l *= sum;
return(-1.);
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
phydbl Rescale_Br_Len_Multiplier_Tree(t_tree *tree)
{
int i;
For(i,2*tree->n_otu-3) tree->t_edges[i]->l *= tree->mod->br_len_multiplier->v;
return(-1.);
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
phydbl Unscale_Free_Rate_Tree(t_tree *tree)
{
int i;
phydbl sum;
sum = 0.0;
For(i,tree->mod->n_catg) sum += tree->mod->gamma_rr->v[i]*tree->mod->gamma_r_proba->v[i];
For(i,tree->mod->n_catg) tree->mod->gamma_rr->v[i] *= sum;
For(i,2*tree->n_otu-3) tree->t_edges[i]->l /= sum;
return(-1.);
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
phydbl Unscale_Br_Len_Multiplier_Tree(t_tree *tree)
{
int i;
For(i,2*tree->n_otu-3) tree->t_edges[i]->l /= tree->mod->br_len_multiplier->v;
return(-1.);
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
phydbl Reflect(phydbl x, phydbl l, phydbl u)
{
int rounds;
phydbl tmp;
int k;
if(u < l)
{
tmp = u;
u = l;
l = tmp;
}
if(x < l) x = x + 2.*(l - x);
if(((x-u) > (u-l)) && (x > u))
{
k = (x - (2.*u-l))/(2.*(u-l));
x = x - 2.*k*(u-l);
}
rounds = 0;
do
{
rounds++;
/* printf("\n. l=%f u=%f x=%f",l,u,x); */
if(x > u || x < l)
{
if(x > u) x = x - 2.*(x - u);
else x = x + 2.*(l - x);
}
else break;
/* printf(" x'=%f",x); */
}
while(rounds < 100);
if(rounds == 100 && (x > u || x < l))
{
PhyML_Printf("\n. u=%f l=%f x=%f",u,l,x);
PhyML_Printf("\n. Err in file %s at line %d\n",__FILE__,__LINE__);
Exit("\n");
}
return x;
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
int Are_Equal(phydbl a, phydbl b, phydbl eps)
{
if(FABS(a-b) < eps) return TRUE; /* a==b */
else return FALSE;
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
/* Returns 1 if small_tree is displayed by big_tree, 0 otherwise
Does not account for the root positions, if any.
*/
int Check_Topo_Constraints(t_tree *big_tree, t_tree *small_tree)
{
if(!small_tree) return 1;
if(small_tree->n_otu < 4) return 1;
if(small_tree->n_otu > big_tree->n_otu)
{
PhyML_Printf("\n");
PhyML_Printf("\n. The tree that defines the topological constraints can not");
PhyML_Printf("\n. display more taxa than %d",big_tree->n_otu);
Exit("\n");
}
t_tree *big_tree_cpy;
int diffs,i;
big_tree_cpy = Make_Tree_From_Scratch(big_tree->n_otu,NULL);
Copy_Tree(big_tree,big_tree_cpy);
Prune_Tree(big_tree_cpy,small_tree);
/* For(i,2*small_tree->n_otu-3) printf("\nz %d . %d . %d", */
/* big_tree->t_edges[i]->does_exist, */
/* big_tree_cpy->t_edges[i]->does_exist, */
/* small_tree->t_edges[i]->does_exist); */
Free_Bip(small_tree);
Alloc_Bip(small_tree);
Get_Bip(small_tree->t_nodes[0],small_tree->t_nodes[0]->v[0],small_tree);
Free_Bip(big_tree_cpy);
Alloc_Bip(big_tree_cpy);
Match_Tip_Numbers(small_tree,big_tree_cpy);
Get_Bip(big_tree_cpy->t_nodes[0],big_tree_cpy->t_nodes[0]->v[0],big_tree_cpy);
For(i,2*big_tree_cpy->n_otu-3) big_tree_cpy->t_edges[i]->bip_score = 0;
For(i,2*small_tree->n_otu-3) small_tree->t_edges[i]->bip_score = 0;
diffs = Compare_Bip(small_tree,big_tree_cpy,YES);
/* printf("\n"); */
/* printf("\n. %s",Write_Tree(big_tree_cpy,NO)); */
/* printf("\n. %s",Write_Tree(small_tree,NO)); */
/* printf("\n. diffs=%d",diffs); */
Free_Tree(big_tree_cpy);
t_tree *big_tree_cpy_bis;
big_tree_cpy_bis = Make_Tree_From_Scratch(big_tree->n_otu,NULL);
Copy_Tree(big_tree,big_tree_cpy_bis);
Free_Tree(big_tree_cpy_bis);
if(diffs == 0) return 1; /* Constraint is satisfied */
else return 0;
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void Prune_Tree(t_tree *big_tree, t_tree *small_tree)
{
int i,j;
int curr_ext_node, curr_int_node, curr_br, n_pruned_nodes;;
t_node **pruned_nodes;
t_edge **residual_edges;
pruned_nodes = (t_node **)mCalloc(big_tree->n_otu,sizeof(t_node *));
residual_edges = (t_edge **)mCalloc(big_tree->n_otu,sizeof(t_edge *));
n_pruned_nodes = 0;
For(i,big_tree->n_otu)
{
For(j,small_tree->n_otu)
if(!strcmp(small_tree->t_nodes[j]->name,big_tree->t_nodes[i]->name))
break;
if(j == small_tree->n_otu)
{
Prune_Subtree(big_tree->t_nodes[i]->v[0],
big_tree->t_nodes[i],
NULL,&(residual_edges[n_pruned_nodes]),
big_tree);
pruned_nodes[n_pruned_nodes] = big_tree->t_nodes[i];
n_pruned_nodes++;
}
}
if(!n_pruned_nodes)
{
Free(pruned_nodes);
Free(residual_edges);
return;
}
Free(big_tree->t_dir);
big_tree->n_otu -= n_pruned_nodes;
curr_ext_node = 0;
curr_int_node = big_tree->n_otu;
curr_br = 0;
For(i,big_tree->n_otu+n_pruned_nodes)
{
For(j,n_pruned_nodes)
if(!strcmp(pruned_nodes[j]->name,big_tree->t_nodes[i]->name))
break;
if(j == n_pruned_nodes) /* That t_node still belongs to the tree */
{
Reassign_Node_Nums(big_tree->t_nodes[i],big_tree->t_nodes[i]->v[0],
&curr_ext_node,&curr_int_node,big_tree);
break;
}
}
Reassign_Edge_Nums(big_tree->t_nodes[0],big_tree->t_nodes[0]->v[0],&curr_br,big_tree);
big_tree->t_dir = (short int *)mCalloc((2*big_tree->n_otu-2)*(2*big_tree->n_otu-2),sizeof(short int));
For(i,n_pruned_nodes)
{
Free_Edge(residual_edges[i]);
Free_Edge(pruned_nodes[i]->b[0]);
Free_Node(pruned_nodes[i]->v[0]);
Free_Node(pruned_nodes[i]);
}
Free(pruned_nodes);
Free(residual_edges);
big_tree->t_edges[2*big_tree->n_otu-3] = big_tree->t_edges[2*(big_tree->n_otu+n_pruned_nodes)-3];
big_tree->t_nodes[2*big_tree->n_otu-2] = big_tree->t_nodes[2*(big_tree->n_otu+n_pruned_nodes)-2];
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
/* For every node in small_tree, find which node in big_tree
it corresponds to and initialize the variable match_node
accordingly (vice versa for big_tree)
*/
void Match_Nodes_In_Small_Tree(t_tree *small_tree, t_tree *big_tree)
{
int i,j,k,l,m,n,identical;
int *score;
if(small_tree->n_otu > big_tree->n_otu)
{
PhyML_Printf("\n. small_tree->n_otu=%d big_tree->n_otu=%d",small_tree->n_otu,big_tree->n_otu);
PhyML_Printf("\n. Err in file %s at line %d\n",__FILE__,__LINE__);
Exit("\n");
}
Free_Bip(big_tree);
Alloc_Bip(big_tree);
Get_Bip(big_tree->t_nodes[0],big_tree->t_nodes[0]->v[0],big_tree);
Free_Bip(small_tree);
Alloc_Bip(small_tree);
Get_Bip(small_tree->t_nodes[0],small_tree->t_nodes[0]->v[0],small_tree);
if(!Check_Topo_Constraints(big_tree,small_tree))
{
PhyML_Printf("\n. small_tree and big_tree cannot have distinct topologies.");
PhyML_Printf("\n. Err in file %s at line %d\n",__FILE__,__LINE__);
Exit("\n");
}
For(i,2*small_tree->n_otu-1) small_tree->t_nodes[i]->match_node = NULL;
For(i,2*big_tree->n_otu-1) big_tree->t_nodes[i]->match_node = NULL;
score = (int *)mCalloc(3,sizeof(int));
For(i,small_tree->n_otu)
{
For(j,big_tree->n_otu)
{
if(!strcmp(small_tree->t_nodes[i]->name,big_tree->t_nodes[j]->name))
{
small_tree->t_nodes[i]->match_node = big_tree->t_nodes[j];
big_tree->t_nodes[j]->match_node = small_tree->t_nodes[i];
break;
}
}
}
For(i,2*small_tree->n_otu-2)
{
if(small_tree->t_nodes[i]->tax == NO)
{
For(j,2*big_tree->n_otu-2)
{
if(big_tree->t_nodes[j]->tax == NO)
{
For(k,3) score[k] = 0;
For(k,3)
{
For(l,3)
{
identical = 0;
For(m,small_tree->t_nodes[i]->bip_size[k])
{
For(n,big_tree->t_nodes[j]->bip_size[l])
{
if(!strcmp(small_tree->t_nodes[i]->bip_node[k][m]->name,big_tree->t_nodes[j]->bip_node[l][n]->name))
{
identical++;
break;
}
}
}
if(identical == small_tree->t_nodes[i]->bip_size[k])
{
score[k]++;
}
}
}
/* printf("\n. [%d] [%d] %d %d %d -- %d %d %d",i,j, */
/* score[0],score[1],score[2], */
/* small_tree->t_nodes[i]->bip_size[0], */
/* small_tree->t_nodes[i]->bip_size[1], */
/* small_tree->t_nodes[i]->bip_size[2]); */
if(
score[0] == 1 &&
score[1] == 1 &&
score[2] == 1
)
{
small_tree->t_nodes[i]->match_node = big_tree->t_nodes[j];
big_tree->t_nodes[j]->match_node = small_tree->t_nodes[i];
break;
}
}
}
}
}
Free(score);
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void Find_Surviving_Edges_In_Small_Tree(t_tree *small_tree, t_tree *big_tree)
{
int i;
Match_Nodes_In_Small_Tree(small_tree,big_tree);
For(i,2*small_tree->n_otu-1) small_tree->rates->has_survived[i] = NO;
Find_Surviving_Edges_In_Small_Tree_Post(big_tree->n_root,big_tree->n_root->v[0],small_tree,big_tree);
Find_Surviving_Edges_In_Small_Tree_Post(big_tree->n_root,big_tree->n_root->v[1],small_tree,big_tree);
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void Find_Surviving_Edges_In_Small_Tree_Post(t_node *a, t_node *d, t_tree *small_tree, t_tree *big_tree)
{
if(d->match_node && !a->match_node)
{
small_tree->rates->has_survived[d->match_node->num] = YES;
}
if(d->tax == YES) return;
else
{
int i;
For(i,3)
{
if(d->v[i] != a && d->b[i] != big_tree->e_root)
{
Find_Surviving_Edges_In_Small_Tree_Post(d,d->v[i],small_tree,big_tree);
}
}
}
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void Set_Taxa_Id_Ranking(t_tree *tree)
{
int i,j;
For(i,tree->n_otu) tree->t_nodes[i]->id_rank = 0;
For(i,tree->n_otu)
{
for(j=i+1;jn_otu;j++)
{
if(strcmp(tree->t_nodes[i]->name,tree->t_nodes[j]->name) > 0)
tree->t_nodes[i]->id_rank++;
else
tree->t_nodes[j]->id_rank++;
}
}
/* For(i,tree->n_otu) PhyML_Printf("\n. %20s %4d",tree->t_nodes[i]->name,tree->t_nodes[i]->id_rank); */
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void Get_Edge_Binary_Coding_Number(t_tree *tree)
{
int i,j;
int list_size;
t_node **list;
t_edge *b;
int max_left,max_rght;
if(tree->n_otu > 1000)
{
PhyML_Printf("\n. Can't work out edge binary code if the number of taxa >1000.");
PhyML_Printf("\n. Err in file %s at line %d\n",__FILE__,__LINE__);
Warn_And_Exit("");
}
Free_Bip(tree);
Alloc_Bip(tree);
Get_Bip(tree->t_nodes[0],tree->t_nodes[0]->v[0],tree);
Set_Taxa_Id_Ranking(tree);
b = NULL;
For(i,2*tree->n_otu-3)
{
b = tree->t_edges[i];
max_left = 0;
For(j,b->left->bip_size[b->l_r])
if(b->left->bip_node[b->l_r][j]->id_rank > max_left)
max_left = b->left->bip_node[b->l_r][j]->id_rank;
max_rght = 0;
For(j,b->rght->bip_size[b->r_l])
if(b->rght->bip_node[b->r_l][j]->id_rank > max_rght)
max_rght = b->rght->bip_node[b->r_l][j]->id_rank;
if(max_left < max_rght)
{
list = b->left->bip_node[b->l_r];
list_size = b->left->bip_size[b->l_r];
}
else
{
list = b->rght->bip_node[b->r_l];
list_size = b->rght->bip_size[b->r_l];
}
b->bin_cod_num = 0.;
For(j,list_size) b->bin_cod_num += POW(2,list[j]->id_rank);
/* printf("\n. %f",b->bin_cod_num); */
}
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void Make_Ancestral_Seq(t_tree *tree)
{
int i;
char **sp_names;
sp_names = (char **)mCalloc(tree->n_otu,sizeof(char *));
For(i,tree->n_otu-1)
{
sp_names[i] = (char *)mCalloc(10,sizeof(char));
sprintf(sp_names[i],"anc%d",i+tree->n_otu);
}
tree->anc_data = Make_Cseq(tree->n_otu-1,
tree->data->init_len,
tree->mod->state_len,
tree->data->init_len,
sp_names);
For(i,tree->n_otu-1) Free(sp_names[i]);
Free(sp_names);
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void Make_MutMap(t_tree *tree)
{
// (# of edges) X (# of sites) X (# mutation types: A<->C A<->G A<->T C<->G C<->T G<->T)
tree->mutmap = (int *)mCalloc((2*tree->n_otu-3)*(tree->n_pattern)*6,sizeof(int));
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
int Get_Mutmap_Val(int edge, int site, int mut, t_tree *tree)
{
int dim1,dim2;
dim1 = (tree->n_pattern)*(2*tree->n_otu-3);
dim2 = (tree->n_pattern);
return tree->mutmap[mut*dim1 + edge*dim2 + site];
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void Get_Mutmap_Coord(int idx, int *edge, int *site, int *mut, t_tree *tree)
{
int dim1,dim2;
dim1 = (tree->n_pattern)*(2*tree->n_otu-3);
dim2 = (tree->n_pattern);
(*mut) = (int)idx/dim1;
(*edge) = (int)(idx - (*mut)*dim1)/dim2;
(*site) = (int)(idx - (*mut)*dim1 - (*edge)*dim2);
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void Make_Nextrees(int *n_trees, int n_tot_trees, t_tree *tree)
{
tree->nextree = Make_Tree_From_Scratch(tree->n_otu,NULL);
Copy_Tree(tree,tree->nextree);
tree->nextree->tree_num = tree->tree_num + 1;
tree->nextree->mod = tree->mod->nextmod;
tree->nextree->io = tree->io;
tree->nextree->data = tree->data;
tree->nextree->both_sides = tree->both_sides;
tree->nextree->n_pattern = tree->n_pattern;
tree->nextree->prevtree = tree;
Prepare_Tree_For_Lk(tree->nextree);
(*n_trees) = (*n_trees) + 1;
if(*n_trees < n_tot_trees) Make_Nextrees(n_trees, n_tot_trees, tree->nextree);
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void Make_Mixtmod(int n_classes, t_tree *tree)
{
int c_class;
c_class = 0;
Make_Nextmods(&c_class,n_classes,tree->mod);
c_class = 0;
Make_Nextrees(&c_class,n_classes,tree);
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void Make_Nextmods(int *n_mods, int n_tot_mods, model *mod)
{
mod->nextmod = Copy_Model(mod);
mod->nextmod->mod_num = mod->mod_num + 1;
mod->nextmod->s_opt = mod->s_opt;
mod->nextmod->io = mod->io;
(*n_mods) = (*n_mods) + 1;
if(*n_mods < n_tot_mods) Make_Nextmods(n_mods,n_tot_mods,mod->nextmod);
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void Copy_Edge_Lengths(t_tree *to, t_tree *from)
{
int i;
For(i,2*from->n_otu-3) to->t_edges[i]->l = from->t_edges[i]->l;
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void Init_Scalar_Dbl(scalar_dbl *p)
{
p->reflect = YES;
p->v = -1.;
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void Init_Scalar_Int(scalar_int *p)
{
p->reflect = YES;
p->v = -1.;
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void Init_Vect_Dbl(int len, vect_dbl *p)
{
p->reflect = YES;
p->len = len;
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void Init_Vect_Int(int len, vect_int *p)
{
p->reflect = YES;
p->len = len;
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
char *To_Lower_String(char *in)
{
char *out;
int i;
int len;
len = (int)strlen(in);
out = (char *)mCalloc(len+1,sizeof(char));
For(i,len)
{
out[i] = (char)tolower(in[i]);
}
out[len] = '\0';
return(out);
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
phyml-20120412/src/alrt.c 0000644 0001750 0001750 00000077446 11636323575 011753 0000000 0000000 /*
PHYML : a program that computes maximum likelihood phylogenies from
DNA or AA homologous sequences
Copyright (C) Stephane Guindon. Oct 2003 onward
All parts of the source except where indicated are distributed under
the GNU public licence. See http://www.opensource.org for details.
*/
/*
Implementation of aLRT branch tests, and 5-branchs NNI research optimization.
Authors : Jean-Francois Dufayard & Stephane Guindon.
*/
#include "alrt.h"
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
/*
* Check every testable branch of the tree,
* check for NNIs, optimizing 5 branches,
* param tree : the tree to check
*/
int Check_NNI_Five_Branches(t_tree *tree)
{
int best_edge;
phydbl best_gain;
int best_config;
int i;
int better_found; /* = 1 if a phylogeny with greater likelihood than current one was found */
int result;
phydbl init_lnL;
init_lnL = UNLIKELY;
better_found = 1;
//While there is at least one NNI to do...
while(better_found)
{
Update_Dirs(tree);
//Interface output
if((tree->mod->s_opt->print) && (!tree->io->quiet)) PhyML_Printf("\n\n. Checking for NNIs, optimizing five branches...\n");
better_found = 0;
result = -1;
best_edge = -1;
best_gain = 1.E+10;
best_config = -1;
tree->update_alias_subpatt = YES;
tree->both_sides = 1;
init_lnL = Lk(tree);
tree->update_alias_subpatt = NO;
//For every branch
For(i,2*tree->n_otu-3)
{
//if this branch is not terminal
if((!tree->t_edges[i]->left->tax) && (!tree->t_edges[i]->rght->tax))
{
result = -1;
//Try every NNIs for the tested branch
result = NNI_Neigh_BL(tree->t_edges[i],tree);
//Look for possible NNI to do, and check if it is the best one
switch(result)
{
case 1 : /* lk1 > lk0 > lk2 */
{
if((tree->t_edges[i]->nni->lk0 - tree->t_edges[i]->nni->lk1) < best_gain)
{
better_found = 1;
best_edge = i;
best_gain = tree->t_edges[i]->nni->lk0-tree->t_edges[i]->nni->lk1;
best_config = 1;
}
break;
}
case 2 : /* lk2 > lk0 > lk1 */
{
if((tree->t_edges[i]->nni->lk0 - tree->t_edges[i]->nni->lk2) < best_gain)
{
better_found = 1;
best_edge = i;
best_gain = tree->t_edges[i]->nni->lk0-tree->t_edges[i]->nni->lk2;
best_config = 2;
}
break;
}
case 3 : /* lk1 > lk2 > lk0 */
{
if((tree->t_edges[i]->nni->lk2 - tree->t_edges[i]->nni->lk1) < best_gain)
{
better_found = 1;
best_edge = i;
best_gain = tree->t_edges[i]->nni->lk2-tree->t_edges[i]->nni->lk1;
best_config = 1;
}
break;
}
case 4 : /* lk2 > lk1 > lk0 */
{
if((tree->t_edges[i]->nni->lk1 - tree->t_edges[i]->nni->lk2) < best_gain)
{
better_found = 1;
best_edge = i;
best_gain = tree->t_edges[i]->nni->lk1-tree->t_edges[i]->nni->lk2;
best_config = 2;
}
break;
}
default : /* lk2 = lk1 = lk0 */
{
if(best_gain > .0) best_gain = .0;
break;
}
}
}
}
if((tree->c_lnL < init_lnL - tree->mod->s_opt->min_diff_lk_local) || (tree->c_lnL > init_lnL + tree->mod->s_opt->min_diff_lk_local))
{
PhyML_Printf("\n\n. tree->c_lnL = %f init_lnL = %f.",tree->c_lnL,init_lnL);
PhyML_Printf("\n. Err in file %s at line %d\n\n.\n",__FILE__,__LINE__);
Warn_And_Exit("\n");
}
//Don't do any NNI if the user doesn't want to optimize topology
if(!tree->mod->s_opt->opt_topo) better_found = 0;
/* if(FABS(best_gain) <= tree->mod->s_opt->min_diff_lk_move) better_found = 0; */
//If there is one swap to do, make the best one.
if(better_found)
{
Make_Target_Swap(tree,tree->t_edges[best_edge],best_config);
tree->update_alias_subpatt = YES;
Lk(tree);
tree->update_alias_subpatt = NO;
if(tree->c_lnL < init_lnL)
{
PhyML_Printf("\n\n. tree->c_lnL = %f init_lnL = %f.",tree->c_lnL,init_lnL);
PhyML_Printf("\n. Err in file %s at line %d\n\n.\n",__FILE__,__LINE__);
Warn_And_Exit("\n");
}
if((tree->mod->s_opt->print) && (!tree->io->quiet)) Print_Lk(tree,"[Topology ]");
if(FABS(tree->c_lnL - init_lnL) < tree->mod->s_opt->min_diff_lk_move) return 0;
return 1;
}
}
return 0;
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
/* Compute aLRT supports */
void aLRT(t_tree *tree)
{
int i;
/* aLRT support will label each internal branch */
tree->print_alrt_val = 1;
/* The topology will not be modified when assessing the branch support. We make sure that it will
not be modified afterwards by locking the topology */
tree->update_alias_subpatt = YES;
tree->both_sides = 1;
Lk(tree);
tree->update_alias_subpatt = NO;
For(i,2*tree->n_otu-3)
if((!tree->t_edges[i]->left->tax) && (!tree->t_edges[i]->rght->tax))
{
/* Compute likelihoods for each of the three configuration */
NNI_Neigh_BL(tree->t_edges[i],tree);
/* Compute the corresponding statistical support */
Compute_Likelihood_Ratio_Test(tree->t_edges[i],tree);
}
tree->lock_topo = 1;
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
/*
* Launch one branch testing,
* analyse the result
* and convert supports as wished by the user.
* param tree : the tree to check
* param tested_t_edge : the tested t_edge of the tree
* param old_loglk : the initial likelihood, before any aLRT analysis
* param isBoot : 1 if used from the Bootstrap procedure, 0 if not
* return an integer, informative to analyse the results and potential NNIs to do
*/
int Compute_Likelihood_Ratio_Test(t_edge *tested_edge, t_tree *tree)
{
int result=0;
tested_edge->ratio_test = 0.0;
tested_edge->alrt_statistic = -1.0;
if((tested_edge->nni->lk0 > tested_edge->nni->lk1) && (tested_edge->nni->lk0 > tested_edge->nni->lk2))
{
if(tested_edge->nni->lk1 < tested_edge->nni->lk2)
{
//lk0 > lk2 > lk1
tested_edge->alrt_statistic = 2*(tested_edge->nni->lk0 - tested_edge->nni->lk2);
}
else
{
//lk0 > lk1 >= lk2
tested_edge->alrt_statistic = 2*(tested_edge->nni->lk0 - tested_edge->nni->lk1);
}
if (tested_edge->alrt_statistic < 0.0)
{
tested_edge->alrt_statistic = 0.0;
tested_edge->ratio_test = 0.0;
}
else
{
//aLRT statistic is valid, compute the branch support
if (tree->io->ratio_test == ALRTCHI2)
{
tested_edge->ratio_test = Statistics_To_Probabilities(tested_edge->alrt_statistic);
}
else if(tree->io->ratio_test == MINALRTCHI2SH)
{
phydbl sh_support;
phydbl param_support;
sh_support = Statistics_To_SH(tree);
param_support = Statistics_To_Probabilities(tested_edge->alrt_statistic);
if(sh_support < param_support) tested_edge->ratio_test = sh_support;
else tested_edge->ratio_test = param_support;
}
else if(tree->io->ratio_test == ALRTSTAT)
{
tested_edge->ratio_test=tested_edge->alrt_statistic;
}
else if(tree->io->ratio_test == SH)
{
tested_edge->ratio_test = Statistics_To_SH(tree);
}
else if(tree->io->ratio_test == ABAYES)
{
phydbl Kp0,Kp1,Kp2,logK;
logK = 1. - MAX(MAX(tested_edge->nni->lk0,tested_edge->nni->lk1),tested_edge->nni->lk2);
Kp0 = EXP(tested_edge->nni->lk0+logK);
Kp1 = EXP(tested_edge->nni->lk1+logK);
Kp2 = EXP(tested_edge->nni->lk2+logK);
tested_edge->ratio_test = Kp0/(Kp0+Kp1+Kp2);
}
}
}
//statistic is not valid, give the negative statistics if wished, or a zero support.
else if((tested_edge->nni->lk1 > tested_edge->nni->lk0) && (tested_edge->nni->lk1 > tested_edge->nni->lk2))
{
/* tested_edge->ratio_test = 2*(tested_edge->nni->lk0-tested_edge->nni->lk1); */
tested_edge->ratio_test = 0.0;
if(tree->io->ratio_test > 1) tested_edge->alrt_statistic = 0.0;
}
else if((tested_edge->nni->lk2 > tested_edge->nni->lk0) && (tested_edge->nni->lk2 > tested_edge->nni->lk1))
{
/* tested_edge->ratio_test = 2*(tested_edge->nni->lk0-tested_edge->nni->lk2); */
tested_edge->ratio_test = 0.0;
if(tree->io->ratio_test > 1) tested_edge->alrt_statistic = 0.0;
}
else // lk0 ~ lk1 ~ lk2
{
tested_edge->ratio_test = 0.0;
if(tree->io->ratio_test > 1) tested_edge->ratio_test = 0.0;
}
return result;
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
/*
* Test the 3 NNI positions for one branch.
* param tree : the tree to check
* param tested_t_edge : the tested t_edge of the tree
* param old_loglk : the initial likelihood, before any aLRT analysis
* param isBoot : 1 if used from the Bootstrap procedure, 0 if not
*/
int NNI_Neigh_BL(t_edge *b_fcus, t_tree *tree)
{
int n_patterns;
int l_r, r_l, l_v1, l_v2, r_v3, r_v4, site;
t_node *v1,*v2,*v3,*v4;
t_edge *e1,*e2,*e3,*e4;
phydbl len_e1,len_e2,len_e3,len_e4;
phydbl lk0, lk1, lk2;
phydbl bl_init;
phydbl l1,l2,l3;
phydbl l_infa, l_infb, l_max;
phydbl lk_init, lk_temp;
int i;
int result,counter,wei;
result = 0;
//Initialization
bl_init = b_fcus->l;
lk_init = tree->c_lnL;
lk_temp = UNLIKELY;
n_patterns = tree->n_pattern;
b_fcus->nni->score = .0;
lk0 = lk1 = lk2 = UNLIKELY;
v1 = v2 = v3 = v4 = NULL;
l_r = r_l = l_v1 = l_v2 = r_v3 = r_v4 = -1;
l_r = b_fcus->l_r;
r_l = b_fcus->r_l;
//vertices
v1 = b_fcus->left->v[b_fcus->l_v1];
v2 = b_fcus->left->v[b_fcus->l_v2];
v3 = b_fcus->rght->v[b_fcus->r_v1];
v4 = b_fcus->rght->v[b_fcus->r_v2];
if(v1->num < v2->num)
{
PhyML_Printf("\n. Err in file %s at line %d\n\n",__FILE__,__LINE__);
Warn_And_Exit("");
}
if(v3->num < v4->num)
{
PhyML_Printf("\n. Err in file %s at line %d\n\n",__FILE__,__LINE__);
Warn_And_Exit("");
}
l1 = l2 = l3 = -1.;
l1 = b_fcus->l;
//edges
e1 = b_fcus->left->b[b_fcus->l_v1];
e2 = b_fcus->left->b[b_fcus->l_v2];
e3 = b_fcus->rght->b[b_fcus->r_v1];
e4 = b_fcus->rght->b[b_fcus->r_v2];
//record initial branch lengths
len_e1 = e1->l;
len_e2 = e2->l;
len_e3 = e3->l;
len_e4 = e4->l;
//Optimize branch lengths and update likelihoods for
//the original configuration.
do
{
lk0 = lk_temp;
For(i,3)
if(b_fcus->left->v[i] != b_fcus->rght)
{
Update_P_Lk(tree,b_fcus->left->b[i],b_fcus->left);
l_infa = 10.*b_fcus->left->b[i]->l;
l_max = b_fcus->left->b[i]->l;
l_infb = tree->mod->l_min;
lk_temp = Br_Len_Brent(l_infa,l_max,l_infb,
tree->mod->s_opt->min_diff_lk_local,
b_fcus->left->b[i],tree,
tree->mod->s_opt->brent_it_max,0);
}
Update_P_Lk(tree,b_fcus,b_fcus->left);
l_infa = 10.*b_fcus->l;
l_max = b_fcus->l;
l_infb = tree->mod->l_min;
lk_temp = Br_Len_Brent(l_infa,l_max,l_infb,
tree->mod->s_opt->min_diff_lk_local,
b_fcus,tree,
tree->mod->s_opt->brent_it_max,0);
For(i,3)
if(b_fcus->rght->v[i] != b_fcus->left)
{
Update_P_Lk(tree,b_fcus->rght->b[i],b_fcus->rght);
l_infa = 10.*b_fcus->rght->b[i]->l;
l_max = b_fcus->rght->b[i]->l;
l_infb = tree->mod->l_min;
lk_temp = Br_Len_Brent(l_infa,l_max,l_infb,
tree->mod->s_opt->min_diff_lk_local,
b_fcus->rght->b[i],tree,
tree->mod->s_opt->brent_it_max,0);
}
Update_P_Lk(tree,b_fcus,b_fcus->rght);
if(lk_temp < lk0 - tree->mod->s_opt->min_diff_lk_local)
{
PhyML_Printf("\n. lk_temp = %f lk0 = %f\n",lk_temp,lk0);
PhyML_Printf("\n. Err in file %s at line %d\n\n",__FILE__,__LINE__);
Warn_And_Exit("");
}
}
while(FABS(lk_temp-lk0) > tree->mod->s_opt->min_diff_lk_global);
lk0 = tree->c_lnL;
counter=0;
For(site,n_patterns)
{
wei=0;
For(wei,tree->data->wght[site])
{
tree->log_lks_aLRT[0][counter]= tree->c_lnL_sorted[site] / tree->data->wght[site];
counter++;
}
}
/* Go back to initial branch lengths */
e1->l = len_e1;
e2->l = len_e2;
e3->l = len_e3;
e4->l = len_e4;
b_fcus->l = bl_init;
Update_PMat_At_Given_Edge(e1,tree);
Update_PMat_At_Given_Edge(e2,tree);
Update_PMat_At_Given_Edge(e3,tree);
Update_PMat_At_Given_Edge(e4,tree);
Update_PMat_At_Given_Edge(b_fcus,tree);
//Do first possible swap
Swap(v2,b_fcus->left,b_fcus->rght,v3,tree);
tree->update_alias_subpatt = YES;
tree->both_sides = 1;
lk1 = Update_Lk_At_Given_Edge(b_fcus,tree);
For(i,3)
if(b_fcus->left->v[i] != b_fcus->rght)
Update_P_Lk(tree,b_fcus->left->b[i],b_fcus->left);
For(i,3)
if(b_fcus->rght->v[i] != b_fcus->left)
Update_P_Lk(tree,b_fcus->rght->b[i],b_fcus->rght);
tree->update_alias_subpatt = NO;
//Optimize branch lengths and update likelihoods
lk_temp = UNLIKELY;
do
{
lk1 = lk_temp;
For(i,3)
if(b_fcus->left->v[i] != b_fcus->rght)
{
Update_P_Lk(tree,b_fcus->left->b[i],b_fcus->left);
l_infa = 10.*b_fcus->left->b[i]->l;
l_max = b_fcus->left->b[i]->l;
l_infb = tree->mod->l_min;
lk_temp = Br_Len_Brent(l_infa,l_max,l_infb,
tree->mod->s_opt->min_diff_lk_local,
b_fcus->left->b[i],tree,
tree->mod->s_opt->brent_it_max,0);
}
Update_P_Lk(tree,b_fcus,b_fcus->left);
l_infa = 10.*b_fcus->l;
l_max = b_fcus->l;
l_infb = tree->mod->l_min;
lk_temp = Br_Len_Brent(l_infa,l_max,l_infb,
tree->mod->s_opt->min_diff_lk_local,
b_fcus,tree,
tree->mod->s_opt->brent_it_max,0);
For(i,3)
if(b_fcus->rght->v[i] != b_fcus->left)
{
Update_P_Lk(tree,b_fcus->rght->b[i],b_fcus->rght);
l_infa = 10.*b_fcus->rght->b[i]->l;
l_max = b_fcus->rght->b[i]->l;
l_infb = tree->mod->l_min;
lk_temp = Br_Len_Brent(l_infa,l_max,l_infb,
tree->mod->s_opt->min_diff_lk_local,
b_fcus->rght->b[i],tree,
tree->mod->s_opt->brent_it_max,0);
}
Update_P_Lk(tree,b_fcus,b_fcus->rght);
if(lk_temp < lk1 - tree->mod->s_opt->min_diff_lk_local)
{
PhyML_Printf("\n. lk_temp = %f lk1 = %f\n",lk_temp,lk1);
PhyML_Printf("\n. Err in file %s at line %d\n\n",__FILE__,__LINE__);
Warn_And_Exit("");
}
}
while(FABS(lk_temp-lk1) > tree->mod->s_opt->min_diff_lk_global);
//until no significative improvement is detected
lk1 = tree->c_lnL;
//save likelihood of each sites, in order to compute branch supports
counter=0;
For(site,n_patterns)
{
wei=0;
For(wei,tree->data->wght[site])
{
tree->log_lks_aLRT[1][counter]= tree->c_lnL_sorted[site] / tree->data->wght[site];
counter++;
}
}
//save current length
l2 = b_fcus->l;
//undo the swap
Swap(v3,b_fcus->left,b_fcus->rght,v2,tree);
/* Go back to initial branch lengths */
e1->l = len_e1;
e2->l = len_e2;
e3->l = len_e3;
e4->l = len_e4;
b_fcus->l = bl_init;
Update_PMat_At_Given_Edge(e1,tree);
Update_PMat_At_Given_Edge(e2,tree);
Update_PMat_At_Given_Edge(e3,tree);
Update_PMat_At_Given_Edge(e4,tree);
Update_PMat_At_Given_Edge(b_fcus,tree);
/***********/
//do the second possible swap
Swap(v2,b_fcus->left,b_fcus->rght,v4,tree);
b_fcus->l = bl_init;
tree->both_sides = 1;
tree->update_alias_subpatt = YES;
lk2 = Update_Lk_At_Given_Edge(b_fcus,tree);
For(i,3)
if(b_fcus->left->v[i] != b_fcus->rght)
Update_P_Lk(tree,b_fcus->left->b[i],b_fcus->left);
For(i,3)
if(b_fcus->rght->v[i] != b_fcus->left)
Update_P_Lk(tree,b_fcus->rght->b[i],b_fcus->rght);
tree->update_alias_subpatt = NO;
//Optimize branch lengths and update likelihoods
lk_temp = UNLIKELY;
do
{
lk2 = lk_temp;
For(i,3)
if(b_fcus->left->v[i] != b_fcus->rght)
{
Update_P_Lk(tree,b_fcus->left->b[i],b_fcus->left);
l_infa = 10.*b_fcus->left->b[i]->l;
l_max = b_fcus->left->b[i]->l;
l_infb = tree->mod->l_min;
lk_temp = Br_Len_Brent(l_infa,l_max,l_infb,
tree->mod->s_opt->min_diff_lk_local,
b_fcus->left->b[i],tree,
tree->mod->s_opt->brent_it_max,0);
}
Update_P_Lk(tree,b_fcus,b_fcus->left);
l_infa = 10.*b_fcus->l;
l_max = b_fcus->l;
l_infb = tree->mod->l_min;
lk_temp = Br_Len_Brent(l_infa,l_max,l_infb,
tree->mod->s_opt->min_diff_lk_local,
b_fcus,tree,
tree->mod->s_opt->brent_it_max,0);
For(i,3)
if(b_fcus->rght->v[i] != b_fcus->left)
{
Update_P_Lk(tree,b_fcus->rght->b[i],b_fcus->rght);
l_infa = 10.*b_fcus->rght->b[i]->l;
l_max = b_fcus->rght->b[i]->l;
l_infb = tree->mod->l_min;
lk_temp = Br_Len_Brent(l_infa,l_max,l_infb,
tree->mod->s_opt->min_diff_lk_local,
b_fcus->rght->b[i],tree,
tree->mod->s_opt->brent_it_max,0);
}
Update_P_Lk(tree,b_fcus,b_fcus->rght);
if(lk_temp < lk2 - tree->mod->s_opt->min_diff_lk_local)
{
PhyML_Printf("\n. lk_temp = %f lk2 = %f\n",lk_temp,lk2);
PhyML_Printf("\n. Err in file %s at line %d\n\n",__FILE__,__LINE__);
Warn_And_Exit("");
}
}
while(FABS(lk_temp-lk2) > tree->mod->s_opt->min_diff_lk_global);
//until no significative improvement is detected
lk2 = tree->c_lnL;
//save likelihood of each sites, in order to compute branch supports
counter=0;
For(site,n_patterns)
{
wei=0;
For(wei,tree->data->wght[site])
{
tree->log_lks_aLRT[2][counter]= tree->c_lnL_sorted[site] / tree->data->wght[site];
counter++;
}
}
//save current length
l3 = b_fcus->l;
//undo the swap
Swap(v4,b_fcus->left,b_fcus->rght,v2,tree);
/***********/
//restore the initial branch length values
e1->l = len_e1;
e2->l = len_e2;
e3->l = len_e3;
e4->l = len_e4;
b_fcus->l = bl_init;
//recompute likelihoods
Update_PMat_At_Given_Edge(e1,tree);
Update_PMat_At_Given_Edge(e2,tree);
Update_PMat_At_Given_Edge(e3,tree);
Update_PMat_At_Given_Edge(e4,tree);
Update_PMat_At_Given_Edge(b_fcus,tree);
tree->update_alias_subpatt = YES;
Update_P_Lk(tree,b_fcus,b_fcus->rght);
Update_P_Lk(tree,b_fcus,b_fcus->left);
For(i,3)
if(b_fcus->left->v[i] != b_fcus->rght)
Update_P_Lk(tree,b_fcus->left->b[i],b_fcus->left);
For(i,3)
if(b_fcus->rght->v[i] != b_fcus->left)
Update_P_Lk(tree,b_fcus->rght->b[i],b_fcus->rght);
tree->update_alias_subpatt = NO;
lk_temp = Lk_At_Given_Edge(b_fcus,tree);
if((lk_temp > lk_init + tree->mod->s_opt->min_diff_lk_local) || (lk_temp < lk_init - tree->mod->s_opt->min_diff_lk_local))
{
PhyML_Printf("\n. lk_temp = %f lk_init = %f\n",lk_temp,lk_init);
PhyML_Printf("\n. Err in file %s at line %d\n\n",__FILE__,__LINE__);
Warn_And_Exit("");
}
//save likelihoods in NNI structures
b_fcus->nni->lk0 = lk0;
b_fcus->nni->lk1 = lk1;
b_fcus->nni->lk2 = lk2;
b_fcus->nni->score = lk0 - MAX(lk1,lk2);
if((b_fcus->nni->score < tree->mod->s_opt->min_diff_lk_local) &&
(b_fcus->nni->score > -tree->mod->s_opt->min_diff_lk_local))
{
b_fcus->nni->score = .0;
b_fcus->nni->lk1 = b_fcus->nni->lk2 = b_fcus->nni->lk0;
}
if((b_fcus->nni->lk1 > b_fcus->nni->lk0) && (b_fcus->nni->lk1 > b_fcus->nni->lk2))
{
if(b_fcus->nni->lk0 > b_fcus->nni->lk2) result = 1; //lk1 > lk0 > lk2
else result = 3; //lk1 > lk2 > lk0
}
else if((b_fcus->nni->lk2 > b_fcus->nni->lk0) && (b_fcus->nni->lk2 > b_fcus->nni->lk1))
{
if(b_fcus->nni->lk0 > b_fcus->nni->lk1) result = 2; //lk2 > lk0 > lk1
else result = 4; //lk2 > lk1 > lk0
}
/* int counter=0; */
/* For(site,n_patterns) */
/* { */
/* PhyML_Printf("%3d %3d %15f ",b_fcus->num,tree->data->wght[site],b_fcus->nni->score); */
/* PhyML_Printf("%15f %15f\n", */
/* tree->log_lks_aLRT[0][counter], */
/* (lk1 > lk2)?(tree->log_lks_aLRT[1][counter]):(tree->log_lks_aLRT[2][counter])); */
/* counter+=tree->data->wght[site]; */
/* } */
return result;
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
/*
* Make one target swap, optimizing five branches.
* param tree : the tree to check
* param tested_t_edge : the swaping t_edge of the tree
* param swapToDo : 1 or 2, to select the first or the second swap to do
*/
void Make_Target_Swap(t_tree *tree, t_edge *b_fcus, int swaptodo)
{
int l_r, r_l, l_v1, l_v2, r_v3, r_v4;
t_node *v1,*v2,*v3,*v4;
t_edge *e1,*e2,*e3,*e4;
phydbl lktodo;
phydbl bl_init;
phydbl l_infa, l_infb, l_max;
phydbl lk_init, lk_temp;
int i;
if(swaptodo < 0)
{
PhyML_Printf("\n. Err in file %s at line %d\n\n",__FILE__,__LINE__);
Warn_And_Exit("");
}
//Initialization
bl_init = b_fcus->l;
lk_init = tree->c_lnL;
b_fcus->nni->score = .0;
lktodo = UNLIKELY;
v1 = v2 = v3 = v4 = NULL;
l_r = r_l = l_v1 = l_v2 = r_v3 = r_v4 = -1;
l_r = b_fcus->l_r;
r_l = b_fcus->r_l;
v1 = b_fcus->left->v[b_fcus->l_v1];
v2 = b_fcus->left->v[b_fcus->l_v2];
v3 = b_fcus->rght->v[b_fcus->r_v1];
v4 = b_fcus->rght->v[b_fcus->r_v2];
if(v1->num < v2->num)
{
PhyML_Printf("\n. Err in file %s at line %d\n\n",__FILE__,__LINE__);
Warn_And_Exit("");
}
if(v3->num < v4->num)
{
PhyML_Printf("\n. Err in file %s at line %d\n\n",__FILE__,__LINE__);
Warn_And_Exit("");
}
e1 = b_fcus->left->b[b_fcus->l_v1];
e2 = b_fcus->left->b[b_fcus->l_v2];
e3 = b_fcus->rght->b[b_fcus->r_v1];
e4 = b_fcus->rght->b[b_fcus->r_v2];
/***********/
//make the selected swap
if(swaptodo==1)
{
Swap(v2,b_fcus->left,b_fcus->rght,v3,tree);
if(!Check_Topo_Constraints(tree,tree->io->cstr_tree)) Swap(v3,b_fcus->left,b_fcus->rght,v2,tree);
}
else
{
Swap(v2,b_fcus->left,b_fcus->rght,v4,tree);
if(!Check_Topo_Constraints(tree,tree->io->cstr_tree)) Swap(v4,b_fcus->left,b_fcus->rght,v2,tree);
}
tree->update_alias_subpatt = YES;
tree->both_sides = 1;
lktodo = Update_Lk_At_Given_Edge(b_fcus,tree);
For(i,3)
if(b_fcus->left->v[i] != b_fcus->rght)
Update_P_Lk(tree,b_fcus->left->b[i],b_fcus->left);
For(i,3)
if(b_fcus->rght->v[i] != b_fcus->left)
Update_P_Lk(tree,b_fcus->rght->b[i],b_fcus->rght);
tree->update_alias_subpatt = NO;
//Optimize branch lengths and update likelihoods
lk_temp = UNLIKELY;
do
{
lktodo = lk_temp;
For(i,3)
if(b_fcus->left->v[i] != b_fcus->rght)
{
Update_P_Lk(tree,b_fcus->left->b[i],b_fcus->left);
l_infa = 10.*b_fcus->left->b[i]->l;
l_max = b_fcus->left->b[i]->l;
l_infb = tree->mod->l_min;
lk_temp = Br_Len_Brent(l_infa,l_max,l_infb,
tree->mod->s_opt->min_diff_lk_local,
b_fcus->left->b[i],tree,
tree->mod->s_opt->brent_it_max,0);
}
Update_P_Lk(tree,b_fcus,b_fcus->left);
l_infa = 10.*b_fcus->l;
l_max = b_fcus->l;
l_infb = tree->mod->l_min;
lk_temp = Br_Len_Brent(l_infa,l_max,l_infb,
tree->mod->s_opt->min_diff_lk_local,
b_fcus,tree,
tree->mod->s_opt->brent_it_max,0);
For(i,3)
if(b_fcus->rght->v[i] != b_fcus->left)
{
Update_P_Lk(tree,b_fcus->rght->b[i],b_fcus->rght);
l_infa = 10.*b_fcus->rght->b[i]->l;
l_max = b_fcus->rght->b[i]->l;
l_infb = tree->mod->l_min;
lk_temp = Br_Len_Brent(l_infa,l_max,l_infb,
tree->mod->s_opt->min_diff_lk_local,
b_fcus->rght->b[i],tree,
tree->mod->s_opt->brent_it_max,0);
}
Update_P_Lk(tree,b_fcus,b_fcus->rght);
if(lk_temp < lktodo - tree->mod->s_opt->min_diff_lk_local)
{
PhyML_Printf("\n. Edge %3d lk_temp = %f lktodo = %f\n",b_fcus->num,lk_temp,lktodo);
PhyML_Printf("\n. Err in file %s at line %d\n\n",__FILE__,__LINE__);
Warn_And_Exit("");
}
}
while(FABS(lk_temp-lktodo) > tree->mod->s_opt->min_diff_lk_global);
//until no significative improvement is detected
/* PhyML_Printf("\n.<< [%3d] l=%f lk_init=%f tree->c_lnL=%f score=%12f v1=%3d v2=%3d v3=%3d v4=%3d >>", */
/* b_fcus->num, */
/* b_fcus->l, */
/* lk_init, */
/* tree->c_lnL, */
/* lk_init-tree->c_lnL, */
/* v1->num,v2->num,v3->num,v4->num); */
if(tree->c_lnL < lk_init - tree->mod->s_opt->min_diff_lk_global)
{
PhyML_Printf("\n. [%3d] v1=%d v2=%d v3=%d v4=%d",
b_fcus->num,v1->num,v2->num,v3->num,v4->num);
PhyML_Printf("\n. tree->c_lnL = %f lk_init = %f\n",tree->c_lnL,lk_init);
PhyML_Printf("\n. Err in file %s at line %d\n\n",__FILE__,__LINE__);
Warn_And_Exit("");
}
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
/**
* Convert an aLRT statistic to a none parametric support
* param in: the statistic
*/
phydbl Statistics_To_Probabilities(phydbl in)
{
phydbl rough_value=0.0;
phydbl a=0.0;
phydbl b=0.0;
phydbl fa=0.0;
phydbl fb=0.0;
if(in>=0.000000393 && in<0.00000157)
{
a=0.000000393;
b=0.00000157;
fa=0.0005;
fb=0.001;
}
else if(in>=0.00000157 && in<0.0000393)
{
a=0.00000157;
b=0.0000393;
fa=0.001;
fb=0.005;
}
else if(in>=0.0000393 && in<0.000157)
{
a=0.0000393;
b=0.000157;
fa=0.005;
fb=0.01;
}
else if(in>=0.000157 && in<0.000982)
{
a=0.000157;
b=0.000982;
fa=0.01;
fb=0.025;
}
else if(in>0.000982 && in<0.00393)
{
a=0.000982;
b=0.00393;
fa=0.025;
fb=0.05;
}
else if(in>=0.00393 && in<0.0158)
{
a=0.00393;
b=0.0158;
fa=0.05;
fb=0.1;
}
else if(in>=0.0158 && in<0.0642)
{
a=0.0158;
b=0.0642;
fa=0.1;
fb=0.2;
}
else if(in>=0.0642 && in<0.148)
{
a=0.0642;
b=0.148;
fa=0.2;
fb=0.3;
}
else if(in>=0.148 && in<0.275)
{
a=0.148;
b=0.275;
fa=0.3;
fb=0.4;
}
else if(in>=0.275 && in<0.455)
{
a=0.275;
b=0.455;
fa=0.4;
fb=0.5;
}
else if(in>=0.455 && in<0.708)
{
a=0.455;
b=0.708;
fa=0.5;
fb=0.6;
}
else if(in>=0.708 && in<1.074)
{
a=0.708;
b=1.074;
fa=0.6;
fb=0.7;
}
else if(in>=1.074 && in<1.642)
{
a=1.074;
b=1.642;
fa=0.7;
fb=0.8;
}
else if(in>=1.642 && in<2.706)
{
a=1.642;
b=2.706;
fa=0.8;
fb=0.9;
}
else if(in>=2.706 && in<3.841)
{
a=2.706;
b=3.841;
fa=0.9;
fb=0.95;
}
else if(in>=3.841 && in<5.024)
{
a=3.841;
b=5.024;
fa=0.95;
fb=0.975;
}
else if(in>=5.024 && in<6.635)
{
a=5.024;
b=6.635;
fa=0.975;
fb=0.99;
}
else if(in>=6.635 && in<7.879)
{
a=6.635;
b=7.879;
fa=0.99;
fb=0.995;
}
else if(in>=7.879 && in<10.828)
{
a=7.879;
b=10.828;
fa=0.995;
fb=0.999;
}
else if(in>=10.828 && in<12.116)
{
a=10.828;
b=12.116;
fa=0.999;
fb=0.9995;
}
if (in>=12.116)
{
rough_value=0.9999;
}
else if(in<0.000000393)
{
rough_value=0.0001;
}
else
{
rough_value=(b-in)/(b-a)*fa + (in - a)/(b-a)*fb;
}
rough_value=rough_value+(1.0-rough_value)/2.0;
rough_value=rough_value*rough_value*rough_value;
return rough_value;
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
/**
* deprecated
* Compute a RELL support, using the latest tested branch
* param tree: the tested tree
*/
phydbl Statistics_to_RELL(t_tree *tree)
{
int i;
int occurence=1000;
phydbl nb=0.0;
phydbl res;
int site;
phydbl lk0=0.0;
phydbl lk1=0.0;
phydbl lk2=0.0;
phydbl buff = -1.;
int position = -1;
//1000 times
For(i,occurence)
{
lk0=0.0;
lk1=0.0;
lk2=0.0;
//Shuffle the data and increment the support, if needed
For(site, tree->data->init_len)
{
buff = rand();
buff /= (RAND_MAX+1.);
/* buff *= tree->data->crunch_len; */
buff *= tree->data->init_len;
position = (int)FLOOR(buff);
lk0+=tree->log_lks_aLRT[0][position];
lk1+=tree->log_lks_aLRT[1][position];
lk2+=tree->log_lks_aLRT[2][position];
}
if (lk0>=lk1 && lk0>=lk2) nb++;
}
res= nb/(phydbl)occurence;
return res;
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
/**
* deprecated
* Compute a SH-like support, using the latest tested branch
* param tree: the tested tree
*/
phydbl Statistics_To_SH(t_tree *tree)
{
int i;
int occurence=1000;
phydbl nb=0.0;
phydbl res;
int site;
phydbl lk0=0.0;
phydbl lk1=0.0;
phydbl lk2=0.0;
phydbl c0=0.0;
phydbl c1=0.0;
phydbl c2=0.0;
phydbl buff=-1.;
int position=-1;
phydbl delta_local=-1.;
//Compute the total log-lk of each NNI position
For(site, tree->data->init_len)
{
c0+=tree->log_lks_aLRT[0][site];
c1+=tree->log_lks_aLRT[1][site];
c2+=tree->log_lks_aLRT[2][site];
}
phydbl delta=0.0;
if (c0>=c1 && c0>=c2)
{
if (c1>=c2)
{
delta=c0-c1;
}
else
{
delta=c0-c2;
}
}
else if(c1>=c0 && c1>=c2)
{
if (c0>=c2)
{
delta=c1-c0;
}
else
{
delta=c1-c2;
}
}
else
{
if (c1>=c0)
{
delta=c2-c1;
}
else
{
delta=c2-c0;
}
}
//1000 times
For(i,occurence)
{
lk0=0.0;
lk1=0.0;
lk2=0.0;
//Shuffle the data
For(site, tree->data->init_len)
{
buff = rand();
buff /= (RAND_MAX+1.);
buff *= tree->data->init_len;
position = (int)FLOOR(buff);
lk0+=tree->log_lks_aLRT[0][position];
lk1+=tree->log_lks_aLRT[1][position];
lk2+=tree->log_lks_aLRT[2][position];
}
//return to null hypothesis
lk0=lk0-c0;
lk1=lk1-c1;
lk2=lk2-c2;
//compute results and increment if needed
delta_local=0.0;
if (lk0>=lk1 && lk0>=lk2)
{
if (lk1>=lk2)
{
delta_local=lk0-lk1;
}
else
{
delta_local=lk0-lk2;
}
}
else if(lk1>=lk0 && lk1>=lk2)
{
if (lk0>=lk2)
{
delta_local=lk1-lk0;
}
else
{
delta_local=lk1-lk2;
}
}
else
{
if (lk1>=lk0)
{
delta_local=lk2-lk1;
}
else
{
delta_local=lk2-lk0;
}
}
if (delta>(delta_local+0.1)) {
nb++;
}
}
res= nb/occurence;
return res;
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
/**
* deprecated
* Compute one side likelihood
* param b_fcus : concerned edge
* param tree : b_fcus tree
* param exclude : side to exclude for computation
*/
phydbl Update_Lk_At_Given_Edge_Excluding(t_edge *b_fcus, t_tree *tree, t_node *exclude)
{
if((!b_fcus->left->tax) && (exclude == NULL || exclude != b_fcus->left))
Update_P_Lk(tree,b_fcus,b_fcus->left);
if((!b_fcus->rght->tax) && (exclude == NULL || exclude != b_fcus->rght))
Update_P_Lk(tree,b_fcus,b_fcus->rght);
tree->c_lnL = Lk_At_Given_Edge(b_fcus,tree);
return tree->c_lnL;
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
phyml-20120412/src/optimiz.c 0000644 0001750 0001750 00000210540 11727561523 012462 0000000 0000000 /*
PHYML : a program that computes maximum likelihood phyLOGenies from
DNA or AA homoLOGous sequences
Copyright (C) Stephane Guindon. Oct 2003 onward
All parts of the source except where indicated are distributed under
the GNU public licence. See http://www.opensource.org for details.
*/
#include "optimiz.h"
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void Optimize_Single_Param_Generic(t_tree *tree, phydbl *param, phydbl lim_inf, phydbl lim_sup, phydbl tol, int n_max_iter, int quickdirty)
{
phydbl ax,bx,cx;
phydbl lk_init;
lk_init = tree->c_lnL;
ax = lim_inf;
bx = (*param);
cx = lim_sup;
Generic_Brent(ax,bx,cx,tol,param,tree,n_max_iter,quickdirty);
if(tree->c_lnL < lk_init - tree->mod->s_opt->min_diff_lk_global)
{
PhyML_Printf("\n. %.10f < %.10f --> diff=%.10f param value = %f initial value = %f\n",
tree->c_lnL,lk_init,
tree->c_lnL-lk_init,
*param,bx);
Exit("\n. Optimisation failed !\n");
}
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
int Generic_Brak(phydbl *param,
phydbl *ax, phydbl *bx, phydbl *cx,
phydbl *fa, phydbl *fb, phydbl *fc,
phydbl lim_inf, phydbl lim_sup,
t_tree *tree)
{
phydbl ulim,u,r,q,fu,dum;
u = 0.0;
*param = *ax;
if(*param > lim_sup) *param = lim_sup;
if(*param < lim_inf) *param = lim_inf;
*fa=-Lk(tree);
*param = *bx;
if(*param > lim_sup) *param = lim_sup;
if(*param < lim_inf) *param = lim_inf;
*fb=-Lk(tree);
if (*fb > *fa) {
SHFT(dum,*ax,*bx,dum)
SHFT(dum,*fb,*fa,dum)
}
*cx=(*bx)+MNBRAK_GOLD*(*bx-*ax);
*param = FABS(*cx);
if(*param > lim_sup) *param = lim_sup;
if(*param < lim_inf) *param = lim_inf;
*fc=-Lk(tree);
while (*fb > *fc)
{
if(*ax > lim_sup) *ax = lim_sup;
if(*ax < lim_inf) *ax = lim_inf;
if(*bx > lim_sup) *bx = lim_sup;
if(*bx < lim_inf) *bx = lim_inf;
if(*cx > lim_sup) *cx = lim_sup;
if(*cx < lim_inf) *cx = lim_inf;
if(u > lim_sup) u = lim_sup;
if(u < lim_inf) u = lim_inf;
r=(*bx-*ax)*(*fb-*fc);
q=(*bx-*cx)*(*fb-*fa);
u=(*bx)-((*bx-*cx)*q-(*bx-*ax)*r)/
(2.0*SIGN(MAX(FABS(q-r),MNBRAK_TINY),q-r));
ulim=(*bx)+MNBRAK_GLIMIT*(*cx-*bx);
if ((*bx-u)*(u-*cx) > lim_inf)
{
*param = FABS(u);
if(*param > lim_sup) {*param = u = lim_sup;}
if(*param < lim_inf) {*param = u = lim_inf;}
fu=-Lk(tree);
if (fu < *fc)
{
*ax=(*bx);
*bx=u;
*fa=(*fb);
*fb=fu;
(*ax)=FABS(*ax);
(*bx)=FABS(*bx);
(*cx)=FABS(*cx);
return(0);
}
else if (fu > *fb)
{
*cx=u;
*fc=fu;
(*ax)=FABS(*ax);
(*bx)=FABS(*bx);
(*cx)=FABS(*cx);
return(0);
}
u=(*cx)+MNBRAK_GOLD*(*cx-*bx);
*param = FABS(u);
if(*param > lim_sup) {*param = u = lim_sup;}
if(*param < lim_inf) {*param = u = lim_inf;}
fu=-Lk(tree);
}
else if ((*cx-u)*(u-ulim) > lim_inf)
{
*param = FABS(u);
if(*param > lim_sup) {*param = u = lim_sup;}
if(*param < lim_inf) {*param = u = lim_inf;}
fu=-Lk(tree);
if (fu < *fc)
{
SHFT(*bx,*cx,u,*cx+MNBRAK_GOLD*(*cx-*bx))
*param = FABS(u);
SHFT(*fb,*fc,fu,-Lk(tree))
}
}
else if ((u-ulim)*(ulim-*cx) >= lim_inf)
{
u=ulim;
*param = FABS(u);
if(*param > lim_sup) {*param = u = lim_sup;}
if(*param < lim_inf) {*param = u = lim_inf;}
fu=-Lk(tree);
}
else
{
u=(*cx)+MNBRAK_GOLD*(*cx-*bx);
*param = FABS(u);
if(*param > lim_sup) {*param = u = lim_sup;}
if(*param < lim_inf) {*param = u = lim_inf;}
fu=-Lk(tree);
}
SHFT(*ax,*bx,*cx,u)
SHFT(*fa,*fb,*fc,fu)
}
(*ax)=FABS(*ax);
(*bx)=FABS(*bx);
(*cx)=FABS(*cx);
return(0);
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
phydbl Generic_Brent(phydbl ax, phydbl bx, phydbl cx, phydbl tol,
phydbl *xmin, t_tree *tree, int n_iter_max,
int quickdirty)
{
int iter;
phydbl a,b,d,etemp,fu,fv,fw,fx,p,q,r,tol1,tol2,u,v,w,x,xm;
phydbl e=0.0;
phydbl old_lnL,init_lnL;
d=0.0;
a=((ax < cx) ? ax : cx);
b=((ax > cx) ? ax : cx);
x=w=v=bx;
old_lnL = UNLIKELY;
(*xmin) = FABS(bx);
fw=fv=fx=-Lk(tree);
init_lnL = -fw;
/* PhyML_Printf("\n. init_lnL = %f a=%f b=%f c=%f\n",init_lnL,ax,bx,cx); */
for(iter=1;iter<=BRENT_ITMAX;iter++)
{
xm=0.5*(a+b);
tol2=2.0*(tol1=tol*FABS(x)+BRENT_ZEPS);
if(FABS(x - xm) <= (tol2 - 0.5 * (b - a)))
{
*xmin = x;
Lk(tree);
if(tree->c_lnL < init_lnL - tree->mod->s_opt->min_diff_lk_local)
{
PhyML_Printf("\n. Err in file %s at line %d\n",__FILE__,__LINE__);
Warn_And_Exit("");
}
return tree->c_lnL;
}
if(FABS(e) > tol1)
{
r=(x-w)*(fx-fv);
q=(x-v)*(fx-fw);
p=(x-v)*q-(x-w)*r;
q=2.0*(q-r);
if(q > 0.0) p = -p;
q=FABS(q);
etemp=e;
e=d;
if(FABS(p) >= FABS(0.5*q*etemp) || p <= q*(a-x) || p >= q*(b-x))
{
d=BRENT_CGOLD*(e=(x >= xm ? a-x : b-x));
/* PhyML_Printf("Golden section step\n"); */
}
else
{
d=p/q;
u=x+d;
if (u-a < tol2 || b-u < tol2) d=SIGN(tol1,xm-x);
/* PhyML_Printf("Parabolic step [e=%f]\n",e); */
}
}
else
{
d=BRENT_CGOLD*(e=(x >= xm ? a-x : b-x));
/* PhyML_Printf("Golden section step (default) [e=%f tol1=%f a=%f b=%f d=%f]\n",e,tol1,a,b,d); */
}
u=(FABS(d) >= tol1 ? x+d : x+SIGN(tol1,d));
(*xmin) = FABS(u);
old_lnL = tree->c_lnL;
fu = -Lk(tree);
/* PhyML_Printf("\n. iter=%d/%d param=%f LOGlk=%f",iter,BRENT_ITMAX,*xmin,tree->c_lnL); */
/* if(fu <= fx) */
if(fu < fx)
{
/* if(u >= x) a=x; else b=x; */
if(u > x) a=x; else b=x;
SHFT(v,w,x,u)
SHFT(fv,fw,fx,fu)
}
else
{
if (u < x) a=u; else b=u;
/* if (fu <= fw || w == x) */
if (fu < fw || FABS(w-x) < SMALL)
{
v=w;
w=u;
fv=fw;
fw=fu;
}
/* else if (fu <= fv || v == x || v == w) */
else if (fu < fv || FABS(v-x) < SMALL || FABS(v-w) < SMALL)
{
v=u;
fv=fu;
}
}
}
Exit("\n. Too many iterations in BRENT !");
return(-1);
/* Not Reached ?? *xmin=x; */
/* Not Reached ?? return fx; */
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
phydbl RRparam_GTR_Golden(phydbl ax, phydbl bx, phydbl cx, phydbl tol,
phydbl *xmin, t_tree *tree, calign *cdata, phydbl *param, int n_iter_max)
{
phydbl f1,f2,x0,x1,x2,x3;
int n_iter;
x0=ax;
x3=cx;
if (FABS(cx-bx) > FABS(bx-ax))
{
x1=bx;
x2=bx+GOLDEN_C*(cx-bx);
}
else
{
x2=bx;
x1=bx-GOLDEN_C*(bx-ax);
}
(*param)=x1;
Lk(tree);
f1=-tree->c_lnL;
(*param)=x2;
Lk(tree);
f2=-tree->c_lnL;
n_iter = 0;
while (FABS(x3-x0) > tol*(FABS(x1)+FABS(x2)))
{
if (f2 < f1)
{
SHFT3(x0,x1,x2,GOLDEN_R*x1+GOLDEN_C*x3)
(*param)=x2;
Lk(tree);
SHFT2(f1,f2,-tree->c_lnL)
}
else
{
SHFT3(x3,x2,x1,GOLDEN_R*x2+GOLDEN_C*x0)
(*param)=x1;
Lk(tree);
SHFT2(f2,f1,-tree->c_lnL)
}
if(n_iter++ > n_iter_max) break;
/* PhyML_Printf("p=%E %f\n",(*param),tree->c_lnL); */
}
if (f1 < f2)
{
*xmin=x1;
return f1;
}
else
{
*xmin=x2;
return f2;
}
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
phydbl Br_Len_Golden(phydbl ax, phydbl bx, phydbl cx, phydbl tol,
phydbl *xmin, t_edge *b_fcus, t_tree *tree)
{
phydbl f1,f2,x0,x1,x2,x3;
x0=ax;
x3=cx;
if (FABS(cx-bx) > FABS(bx-ax))
{
x1=bx;
x2=bx+GOLDEN_C*(cx-bx);
}
else
{
x2=bx;
x1=bx-GOLDEN_C*(bx-ax);
}
b_fcus->l=x1;
f1 = -Lk_At_Given_Edge(b_fcus,tree);
b_fcus->l=x2;
f2 = -Lk_At_Given_Edge(b_fcus,tree);
while (FABS(x3-x0) > tol*(FABS(x1)+FABS(x2)))
{
if (f2 < f1)
{
SHFT3(x0,x1,x2,GOLDEN_R*x1+GOLDEN_C*x3)
b_fcus->l=x2;
SHFT2(f1,f2,-Lk_At_Given_Edge(b_fcus,tree))
}
else
{
SHFT3(x3,x2,x1,GOLDEN_R*x2+GOLDEN_C*x0)
b_fcus->l=x1;
SHFT2(f2,f1,-Lk_At_Given_Edge(b_fcus,tree))
}
}
if (f1 < f2)
{
*xmin=FABS(x1);
return -f1;
}
else
{
*xmin=FABS(x2);
return -f2;
}
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
int Br_Len_Brak(phydbl *ax, phydbl *bx, phydbl *cx,
phydbl *fa, phydbl *fb, phydbl *fc,
t_edge *b_fcus, t_tree *tree)
{
phydbl ulim,u,r,q,fu,dum;
b_fcus->l = *ax;
*fa=-Lk_At_Given_Edge(b_fcus,tree);
b_fcus->l = *bx;
*fb=-Lk_At_Given_Edge(b_fcus,tree);
if (*fb > *fa) {
SHFT(dum,*ax,*bx,dum)
SHFT(dum,*fb,*fa,dum)
}
*cx=(*bx)+MNBRAK_GOLD*(*bx-*ax);
b_fcus->l = *cx;
*fc=-Lk_At_Given_Edge(b_fcus,tree);
while (*fb > *fc + tree->mod->s_opt->min_diff_lk_local)
{
PhyML_Printf("fb=%f fc=%f\n",*fb,*fc);
r=(*bx-*ax)*(*fb-*fc);
q=(*bx-*cx)*(*fb-*fa);
u=(*bx)-((*bx-*cx)*q-(*bx-*ax)*r)/
(2.0*SIGN(MAX(FABS(q-r),MNBRAK_TINY),q-r));
ulim=(*bx)+MNBRAK_GLIMIT*(*cx-*bx);
if ((*bx-u)*(u-*cx) > 0.0)
{
b_fcus->l = u;
fu=-Lk_At_Given_Edge(b_fcus,tree);
if (fu < *fc)
{
*ax=(*bx);
*bx=u;
*fa=(*fb);
*fb=fu;
/* (*ax)=FABS(*ax); */
/* (*bx)=FABS(*bx); */
/* (*cx)=FABS(*cx); */
return(0);
}
else if (fu > *fb)
{
*cx=u;
*fc=fu;
/* (*ax)=FABS(*ax); */
/* (*bx)=FABS(*bx); */
/* (*cx)=FABS(*cx); */
return(0);
}
u=(*cx)+MNBRAK_GOLD*(*cx-*bx);
b_fcus->l = u;
fu=-Lk_At_Given_Edge(b_fcus,tree);
}
else if ((*cx-u)*(u-ulim) > 0.0)
{
b_fcus->l = FABS(u);
fu=-Lk_At_Given_Edge(b_fcus,tree);
if (fu < *fc)
{
SHFT(*bx,*cx,u,*cx+MNBRAK_GOLD*(*cx-*bx))
b_fcus->l = u;
SHFT(*fb,*fc,fu,-Lk_At_Given_Edge(b_fcus,tree))
}
}
else if ((u-ulim)*(ulim-*cx) >= 0.0)
{
u=ulim;
b_fcus->l = u;
fu=-Lk_At_Given_Edge(b_fcus,tree);
}
else
{
u=(*cx)+MNBRAK_GOLD*(*cx-*bx);
b_fcus->l = u;
fu=-Lk_At_Given_Edge(b_fcus,tree);
}
SHFT(*ax,*bx,*cx,u)
SHFT(*fa,*fb,*fc,fu)
}
(*ax)=FABS(*ax);
(*bx)=FABS(*bx);
(*cx)=FABS(*cx);
return(0);
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
phydbl Br_Len_Brent_Default(t_edge *b_fcus, t_tree *tree)
{
return Br_Len_Brent(10.*b_fcus->l,b_fcus->l,.10*b_fcus->l,tree->mod->s_opt->min_diff_lk_local,b_fcus,tree,1000,0);
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
phydbl Br_Len_Brent(phydbl ax, phydbl bx, phydbl cx, phydbl tol,
t_edge *b_fcus, t_tree *tree, int n_iter_max, int quickdirty)
{
int iter;
phydbl a,b,d,etemp,fu,fv,fw,fx,p,q,r,tol1,tol2,u,v,w,x,xm;
phydbl e=0.0;
phydbl old_lnL, init_lnL;
if(tree->mod->gamma_mgf_bl == YES)
{
Generic_Brent_Lk(&(b_fcus->gamma_prior_var),
0.0,1000.,
tree->mod->s_opt->min_diff_lk_local,
tree->mod->s_opt->brent_it_max,
tree->mod->s_opt->quickdirty,
Wrap_Lk_At_Given_Edge,b_fcus,tree,NULL);
}
d=0.0;
a=((ax < cx) ? ax : cx);
b=((ax > cx) ? ax : cx);
x=w=v=bx;
old_lnL = UNLIKELY;
b_fcus->l = bx;
fw=fv=fx=fu=-Lk_At_Given_Edge(b_fcus,tree);
init_lnL = -fw;
/* PhyML_Printf("\n. INIT BRENT t_edge %3d l=%f lnL=%20f",b_fcus->num,b_fcus->l,fu); */
for(iter=1;iter<=BRENT_ITMAX;iter++)
{
xm=0.5*(a+b);
tol2=2.0*(tol1=tol*x+BRENT_ZEPS);
if((tree->c_lnL > init_lnL + tol) && (quickdirty))
{
b_fcus->l = x;
Lk_At_Given_Edge(b_fcus,tree);
/* PhyML_Printf("\n> iter=%3d max=%3d v=%f lnL=%f init_lnL=%f tol=%f",iter,n_iter_max,(*xmin),tree->c_lnL,init_lnL,tol); */
/* Exit("\n"); */
return tree->c_lnL;
}
/* if(((FABS(tree->c_lnL-old_lnL) < tol) && (tree->c_lnL > init_lnL - tol)) || (iter > n_iter_max - 1)) */
if((FABS(tree->c_lnL-old_lnL) < tol) || (iter > n_iter_max - 1))
{
b_fcus->l=x;
Lk_At_Given_Edge(b_fcus,tree);
/* PhyML_Printf("\n. iter=%3d max=%3d l=%f lnL=%f init_lnL=%f",iter,n_iter_max,b_fcus->l,tree->c_lnL,init_lnL); */
/* Exit("\n"); */
return tree->c_lnL;
}
if(FABS(e) > tol1)
{
r=(x-w)*(fx-fv);
q=(x-v)*(fx-fw);
p=(x-v)*q-(x-w)*r;
q=2.0*(q-r);
if(q > 0.0) p = -p;
q=FABS(q);
etemp=e;
e=d;
if(FABS(p) >= FABS(0.5*q*etemp) || p <= q*(a-x) || p >= q*(b-x))
d=BRENT_CGOLD*(e=(x >= xm ? a-x : b-x));
else{
d=p/q;
u=x+d;
if (u-a < tol2 || b-u < tol2)
d=SIGN(tol1,xm-x);
}
}
else
{
d=BRENT_CGOLD*(e=(x >= xm ? a-x : b-x));
}
u=(FABS(d) >= tol1 ? x+d : x+SIGN(tol1,d));
/* if(ul_min) u = tree->l_min; */
b_fcus->l=u;
old_lnL = tree->c_lnL;
fu=-Lk_At_Given_Edge(b_fcus,tree);
/* PhyML_Printf("\n. BRENT t_edge %3d l=%f lnL=%20f iter=%3d",b_fcus->num,b_fcus->l,fu,iter); */
/* if(fu <= fx) */
if(fu < fx)
{
if(u > x) a=x; else b=x;
/* if(u >= x) a=x; else b=x; */
SHFT(v,w,x,u)
SHFT(fv,fw,fx,fu)
}
else
{
if (u < x) a=u; else b=u;
/* if (fu <= fw || w == x) */
if (fu < fw || FABS(w-x) < SMALL)
{
v=w;
w=u;
fv=fw;
fw=fu;
}
else if (fu < fv || FABS(v-x) < SMALL || FABS(v-w) < SMALL)
/* else if (fu <= fv || v == x || v == w) */
{
v=u;
fv=fu;
}
}
}
if(iter > BRENT_ITMAX) PhyML_Printf("\n. Too many iterations in BRENT (%d) (%f)",iter,b_fcus->l);
return(-1);
/* Not Reached ?? *xmin=x; */
/* Not Reached ?? return fx; */
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void Round_Optimize(t_tree *tree, calign *data, int n_round_max)
{
int n_round,each;
phydbl lk_old, lk_new, tol;
t_node *root;
lk_new = tree->c_lnL;
lk_old = UNLIKELY;
n_round = 0;
each = 0;
tol = 1.e-2;
root = tree->t_nodes[0];
tree->both_sides = 1;
Lk(tree);
while(n_round < n_round_max)
{
(!((n_round+2)%2))?(root=tree->t_nodes[0]):(root=tree->t_nodes[tree->n_otu-1]);
if((tree->mod->s_opt->opt_bl || tree->mod->s_opt->constrained_br_len) &&
(tree->mod->s_opt->print) &&
(!tree->io->quiet)) Print_Lk(tree,"[Branch lengths ]");
if(tree->mod->s_opt->opt_bl || tree->mod->s_opt->constrained_br_len)
Optimize_Br_Len_Serie(root,root->v[0],root->b[0],tree,data);
tree->both_sides = 1;
Lk(tree);
if(!each)
{
each = 1;
Optimiz_All_Free_Param(tree,(tree->io->quiet)?(0):(tree->mod->s_opt->print));
tree->both_sides = 1;
Lk(tree);
}
lk_new = tree->c_lnL;
if(lk_new < lk_old - tree->mod->s_opt->min_diff_lk_global)
{
PhyML_Printf("\n. lk_new = %f lk_old = %f diff = %f",lk_new,lk_old,lk_new-lk_old);
Exit("\n. Optimisation failed ! (Round_Optimize)\n");
}
if(FABS(lk_new - lk_old) < tree->mod->s_opt->min_diff_lk_global) break;
else lk_old = lk_new;
n_round++;
each--;
}
Optimiz_All_Free_Param(tree,(tree->io->quiet)?(0):(tree->mod->s_opt->print));
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void Optimize_Br_Len_Serie(t_node *a, t_node *d, t_edge *b_fcus, t_tree *tree, calign *cdata)
{
int i;
phydbl l_infa,l_max,l_infb;
phydbl lk_init;
lk_init = tree->c_lnL;
if(tree->mod->s_opt->constrained_br_len == YES)
{
Generic_Brent_Lk(&(tree->mod->br_len_multiplier->v),
1.E-2,1.E+1,
tree->mod->s_opt->min_diff_lk_global,
tree->mod->s_opt->brent_it_max,
tree->mod->s_opt->quickdirty,
Wrap_Lk,NULL,tree,NULL);
if(tree->c_lnL < lk_init - tree->mod->s_opt->min_diff_lk_local)
{
PhyML_Printf("\n. %f -- %f",lk_init,tree->c_lnL);
Warn_And_Exit("\n. Err. in Optimize_Br_Len_Serie\n");
}
return;
}
l_max = b_fcus->l;
l_infa = tree->mod->l_max;
l_infb = tree->mod->l_min;
if(tree->io->mod->s_opt->opt_bl == YES)
{
Br_Len_Brent(l_infa,l_max,l_infb,
tree->mod->s_opt->min_diff_lk_local,
b_fcus,tree,
tree->mod->s_opt->brent_it_max,
tree->mod->s_opt->quickdirty);
}
if(tree->mod->s_opt->opt_gamma_br_len == YES)
{
Generic_Brent_Lk(&(b_fcus->gamma_prior_var),
0.0,1000.,
tree->mod->s_opt->min_diff_lk_local,
tree->mod->s_opt->brent_it_max,
tree->mod->s_opt->quickdirty,
Wrap_Lk_At_Given_Edge,b_fcus,tree,NULL);
}
/* Generic_Brent_Lk(&(b_fcus->l), */
/* l_infa,l_infb, */
/* tree->mod->s_opt->min_diff_lk_local, */
/* tree->mod->s_opt->brent_it_max, */
/* tree->mod->s_opt->quickdirty, */
/* Wrap_Lk_At_Given_Edge,b_fcus,tree,NULL); */
if(tree->c_lnL < lk_init - tree->mod->s_opt->min_diff_lk_local)
{
PhyML_Printf("\n. %f %f %f %f",l_infa,l_max,l_infb,b_fcus->l);
PhyML_Printf("\n. %f -- %f",lk_init,tree->c_lnL);
Warn_And_Exit("\n. Err. in Optimize_Br_Len_Serie\n");
}
if(d->tax) return;
else For(i,3) if(d->v[i] != a)
{
Update_P_Lk(tree,d->b[i],d);
Optimize_Br_Len_Serie(d,d->v[i],d->b[i],tree,cdata);
}
For(i,3) if((d->v[i] == a) && !(d->v[i]->tax)) Update_P_Lk(tree,d->b[i],d);
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void Optimiz_Ext_Br(t_tree *tree)
{
int i;
t_edge *b;
phydbl l_infa,l_max,l_infb;
phydbl lk, lk_init,l_init;
lk_init = tree->c_lnL;
For(i,2*tree->n_otu-3)
{
b = tree->t_edges[i];
if((b->left->tax) || (b->rght->tax))
{
l_init = b->l;
/* Fast_Br_Len(b,tree); */
/* lk = Lk_At_Given_Edge(tree,b); */
l_infa = 10.*b->l;
l_max = b->l;
l_infb = tree->mod->l_min;
lk = Br_Len_Brent(l_infa,l_max,l_infb,
tree->mod->s_opt->min_diff_lk_local,
b,tree,
tree->mod->s_opt->brent_it_max,
tree->mod->s_opt->quickdirty);
b->nni->best_l = b->l;
b->nni->l0 = b->l;
b->nni->best_conf = 0;
b->l = l_init;
}
}
tree->c_lnL = lk_init;
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void Optimiz_All_Free_Param(t_tree *tree, int verbose)
{
int init_both_sides;
init_both_sides = tree->both_sides;
tree->both_sides = 0;
if((tree->mod->whichmodel == GTR) ||
((tree->mod->whichmodel == CUSTOM) &&
(tree->mod->s_opt->opt_rr) &&
(tree->mod->n_diff_rr > 1)))
{
int failed;
failed = 0;
tree->mod->update_eigen = 1;
BFGS(tree,tree->mod->rr_val->v,tree->mod->n_diff_rr,1.e-5,1.e-3,
&Return_Abs_Lk,
&Num_Derivative_Several_Param,
&Lnsrch_RR_Param,&failed);
if(failed)
{
int i;
For(i,tree->mod->n_diff_rr)
if(i != 5)
{
/* Optimize_Single_Param_Generic(tree,&(tree->mod->rr_val[i]), */
/* 1.E-2,1.E+2, */
/* tree->mod->s_opt->min_diff_lk_global, */
/* tree->mod->s_opt->brent_it_max, */
/* tree->mod->s_opt->quickdirty); */
Generic_Brent_Lk(&(tree->mod->rr_val->v[i]),
1.E-2,1.E+2,
tree->mod->s_opt->min_diff_lk_global,
tree->mod->s_opt->brent_it_max,
tree->mod->s_opt->quickdirty,
Wrap_Lk,NULL,tree,NULL);
}
}
if(verbose) Print_Lk(tree,"[GTR parameters ]");
tree->mod->update_eigen = 0;
}
if(tree->mod->s_opt->opt_kappa)
{
tree->mod->update_eigen = 1;
Generic_Brent_Lk(&(tree->mod->kappa->v),
0.1,100.,
tree->mod->s_opt->min_diff_lk_global,
tree->mod->s_opt->brent_it_max,
tree->mod->s_opt->quickdirty,
Wrap_Lk,NULL,tree,NULL);
if(verbose)
{
Print_Lk(tree,"[Ts/ts ratio ]");
PhyML_Printf("[%10f]",tree->mod->kappa->v);
}
tree->mod->update_eigen = 0;
}
if(tree->mod->s_opt->opt_lambda)
{
/* Optimize_Single_Param_Generic(tree,&(tree->mod->lambda->v),.001,100., */
/* tree->mod->s_opt->min_diff_lk_global, */
/* tree->mod->s_opt->brent_it_max, */
/* tree->mod->s_opt->quickdirty); */
Generic_Brent_Lk(&(tree->mod->lambda->v),
0.001,100.,
tree->mod->s_opt->min_diff_lk_global,
tree->mod->s_opt->brent_it_max,
tree->mod->s_opt->quickdirty,
Wrap_Lk,NULL,tree,NULL);
if(verbose)
{
Print_Lk(tree,"[Lambda ]");
PhyML_Printf("[%10f]",tree->mod->lambda->v);
}
}
if((tree->mod->s_opt->opt_pinvar) && (tree->mod->s_opt->opt_alpha))
{
Optimiz_Alpha_And_Pinv(tree);
if(verbose)
{
Print_Lk(tree,"[Alpha ]");
PhyML_Printf("[%10f]",tree->mod->alpha->v);
Print_Lk(tree,"[P-inv ]");
PhyML_Printf("[%10f]",tree->mod->pinvar->v);
}
}
else
{
if(tree->mod->s_opt->opt_pinvar)
{
/* Optimize_Single_Param_Generic(tree,&(tree->mod->pinvar->v), */
/* .0001,0.9999, */
/* tree->mod->s_opt->min_diff_lk_global, */
/* tree->mod->s_opt->brent_it_max, */
/* tree->mod->s_opt->quickdirty); */
Generic_Brent_Lk(&(tree->mod->pinvar->v),
0.0001,0.9999,
tree->mod->s_opt->min_diff_lk_global,
tree->mod->s_opt->brent_it_max,
tree->mod->s_opt->quickdirty,
Wrap_Lk,NULL,tree,NULL);
if(verbose)
{
Print_Lk(tree,"[P-inv ]");
PhyML_Printf("[%10f]",tree->mod->pinvar->v);
}
}
if(tree->mod->s_opt->opt_alpha && tree->mod->free_mixt_rates == NO)
{
if(tree->mod->n_catg > 1)
Generic_Brent_Lk(&(tree->mod->alpha->v),
tree->mod->alpha->v/2.,tree->mod->alpha->v*2.,
tree->mod->s_opt->min_diff_lk_global,
tree->mod->s_opt->brent_it_max,
tree->mod->s_opt->quickdirty,
Wrap_Lk,NULL,tree,NULL);
if(verbose)
{
Print_Lk(tree,"[Alpha ]");
PhyML_Printf("[%10f]",tree->mod->alpha->v);
}
}
}
if((tree->mod->s_opt->opt_state_freq) && (tree->io->datatype == NT))
{
int failed,i;
failed = 0;
tree->mod->update_eigen = 1;
BFGS(tree,tree->mod->pi_unscaled->v,tree->mod->ns,1.e-5,1.e-5,
&Return_Abs_Lk,
&Num_Derivative_Several_Param,
&Lnsrch_Nucleotide_Frequencies,&failed);
if(failed)
{
For(i,tree->mod->ns)
{
/* Optimize_Single_Param_Generic(tree,&(tree->mod->pi_unscaled[i]), */
/* -1000.,1000., */
/* tree->mod->s_opt->min_diff_lk_global, */
/* tree->mod->s_opt->brent_it_max, */
/* tree->mod->s_opt->quickdirty); */
Generic_Brent_Lk(&(tree->mod->pi_unscaled->v[i]),
-1000.,1000.,
tree->mod->s_opt->min_diff_lk_global,
tree->mod->s_opt->brent_it_max,
tree->mod->s_opt->quickdirty,
Wrap_Lk,NULL,tree,NULL);
}
}
if(verbose) Print_Lk(tree,"[Nucleotide freqs. ]");
tree->mod->update_eigen = 0;
}
if((tree->mod->s_opt->opt_free_mixt_rates) && (tree->mod->free_mixt_rates == YES))
{
/* int failed; */
int i;
/* failed = 0; */
/* tree->mod->update_eigen = 1; */
/* BFGS(tree,tree->mod->gamma_r_proba_unscaled,tree->mod->n_catg,1.e-5,1.e-5, */
/* &Return_Abs_Lk, */
/* &Num_Derivative_Several_Param, */
/* &Lnsrch_Free_Mixt_Rates,&failed); */
if(verbose) Print_Lk(tree,"[Rate class freqs. ]");
/* For(i,tree->mod->n_catg-1) */
/* { */
/* Generic_Brent_Lk(&(tree->mod->gamma_r_proba_unscaled->v[i]), */
/* 0., */
/* 100, */
/* tree->mod->s_opt->min_diff_lk_global, */
/* tree->mod->s_opt->brent_it_max, */
/* tree->mod->s_opt->quickdirty, */
/* Wrap_Lk,NULL,tree,NULL); */
/* } */
tree->mod->gamma_r_proba_unscaled->v[tree->mod->n_catg-1] = 100.;
For(i,tree->mod->n_catg-1)
{
if(!i)
Generic_Brent_Lk(&(tree->mod->gamma_r_proba_unscaled->v[i]),
0.,
tree->mod->gamma_r_proba_unscaled->v[i+1],
tree->mod->s_opt->min_diff_lk_global,
tree->mod->s_opt->brent_it_max,
tree->mod->s_opt->quickdirty,
Wrap_Lk,NULL,tree,NULL);
else
Generic_Brent_Lk(&(tree->mod->gamma_r_proba_unscaled->v[i]),
tree->mod->gamma_r_proba_unscaled->v[i-1],
tree->mod->gamma_r_proba_unscaled->v[i+1],
tree->mod->s_opt->min_diff_lk_global,
tree->mod->s_opt->brent_it_max,
tree->mod->s_opt->quickdirty,
Wrap_Lk,NULL,tree,NULL);
}
if(verbose) Print_Lk(tree,"[Rate class values ]");
For(i,tree->mod->n_catg)
{
Generic_Brent_Lk(&(tree->mod->gamma_rr_unscaled->v[i]),
0.,100.,
tree->mod->s_opt->min_diff_lk_global,
tree->mod->s_opt->brent_it_max,
tree->mod->s_opt->quickdirty,
Wrap_Lk,NULL,tree,NULL);
}
tree->mod->update_eigen = 0;
}
if(tree->mod->use_m4mod)
{
int failed,i;
if(tree->mod->s_opt->opt_cov_delta)
{
tree->mod->update_eigen = YES;
/* Optimize_Single_Param_Generic(tree,&(tree->mod->m4mod->delta), */
/* 0.01,10., */
/* tree->mod->s_opt->min_diff_lk_global, */
/* tree->mod->s_opt->brent_it_max, */
/* tree->mod->s_opt->quickdirty); */
Generic_Brent_Lk(&(tree->mod->m4mod->delta),
0.01,10.,
tree->mod->s_opt->min_diff_lk_global,
tree->mod->s_opt->brent_it_max,
tree->mod->s_opt->quickdirty,
Wrap_Lk,NULL,tree,NULL);
if(verbose)
{
Print_Lk(tree,"[Switching param. ]");
PhyML_Printf("[%10f]",tree->mod->m4mod->delta);
}
tree->mod->update_eigen = NO;
}
if(tree->mod->s_opt->opt_cov_free_rates)
{
int rcat;
tree->mod->update_eigen = YES;
For(rcat,tree->mod->m4mod->n_h)
{
/* Optimize_Single_Param_Generic(tree,&(tree->mod->m4mod->multipl_unscaled[rcat]), */
/* .01,10., */
/* tree->mod->s_opt->min_diff_lk_global, */
/* tree->mod->s_opt->brent_it_max, */
/* tree->mod->s_opt->quickdirty); */
Generic_Brent_Lk(&(tree->mod->m4mod->multipl_unscaled[rcat]),
0.1,100.,
tree->mod->s_opt->min_diff_lk_global,
tree->mod->s_opt->brent_it_max,
tree->mod->s_opt->quickdirty,
Wrap_Lk,NULL,tree,NULL);
if(verbose)
{
Print_Lk(tree,"[Rel. subst. rate ]");
PhyML_Printf("[%10f]",tree->mod->m4mod->multipl[rcat]);
}
}
For(rcat,tree->mod->m4mod->n_h)
{
/* Optimize_Single_Param_Generic(tree,&(tree->mod->m4mod->h_fq_unscaled[rcat]), */
/* .01,100., */
/* tree->mod->s_opt->min_diff_lk_global, */
/* tree->mod->s_opt->brent_it_max, */
/* tree->mod->s_opt->quickdirty); */
Generic_Brent_Lk(&(tree->mod->m4mod->h_fq_unscaled[rcat]),
0.1,100.,
tree->mod->s_opt->min_diff_lk_global,
tree->mod->s_opt->brent_it_max,
tree->mod->s_opt->quickdirty,
Wrap_Lk,NULL,tree,NULL);
if(verbose)
{
Print_Lk(tree,"[Subst. class freq ]");
PhyML_Printf("[%10f]",tree->mod->m4mod->h_fq[rcat]);
}
}
tree->mod->update_eigen = NO;
}
if(tree->mod->s_opt->opt_cov_alpha)
{
tree->mod->update_eigen = 1;
/* Optimize_Single_Param_Generic(tree,&(tree->mod->m4mod->alpha), */
/* .01,10., */
/* tree->mod->s_opt->min_diff_lk_global, */
/* tree->mod->s_opt->brent_it_max, */
/* tree->mod->s_opt->quickdirty); */
Generic_Brent_Lk(&(tree->mod->m4mod->alpha),
0.01,10.,
tree->mod->s_opt->min_diff_lk_global,
tree->mod->s_opt->brent_it_max,
tree->mod->s_opt->quickdirty,
Wrap_Lk,NULL,tree,NULL);
if(verbose)
{
Print_Lk(tree,"[Alpha (covarion) ]");
PhyML_Printf("[%10f]",tree->mod->m4mod->alpha);
}
tree->mod->update_eigen = 0;
}
/* Substitutions between nucleotides are considered to follow a
GTR model */
if(tree->mod->io->datatype == NT)
{
if(tree->mod->whichmodel == GTR ||
tree->mod->whichmodel == CUSTOM)
{
failed = 0;
tree->mod->update_eigen = 1;
BFGS(tree,tree->mod->m4mod->o_rr,5,1.e-5,1.e-5,
&Return_Abs_Lk,
&Num_Derivative_Several_Param,
&Lnsrch_RR_Cov_Param,&failed);
}
if(failed)
{
For(i,5)
{
/* Optimize_Single_Param_Generic(tree,&(tree->mod->m4mod->o_rr[i]), */
/* 1.E-20,1.E+10, */
/* tree->mod->s_opt->min_diff_lk_global, */
/* tree->mod->s_opt->brent_it_max, */
/* tree->mod->s_opt->quickdirty); */
Generic_Brent_Lk(&(tree->mod->m4mod->o_rr[i]),
1.E-20,1.E+10,
tree->mod->s_opt->min_diff_lk_global,
tree->mod->s_opt->brent_it_max,
tree->mod->s_opt->quickdirty,
Wrap_Lk,NULL,tree,NULL);
}
}
if(verbose) Print_Lk(tree,"[GTR parameters ]");
tree->mod->update_eigen = 0;
}
}
tree->both_sides = init_both_sides;
if(tree->both_sides) Lk(tree); /* Needed to update all partial likelihoods */
/* if(tree->nextree) Optimiz_All_Free_Param(tree->nextree,verbose); */
}
#define ITMAX 200
#define EPS 3.0e-8
#define TOLX (4*EPS)
#define STPMX 100.0
static phydbl sqrarg;
#define SQR(a) ((sqrarg=(a)) < SMALL ? 0.0 : sqrarg*sqrarg)
void BFGS(t_tree *tree,
phydbl *p,
int n,
phydbl gtol,
phydbl step_size,
phydbl(*func)(t_tree *tree),
int(*dfunc)(t_tree *tree,phydbl *param,int n_param,phydbl stepsize,phydbl(*func)(t_tree *tree),phydbl *derivatives),
int(*lnsrch)(t_tree *tree, int n, phydbl *xold, phydbl fold,phydbl *g, phydbl *p, phydbl *x,phydbl *f, phydbl stpmax, int *check),
int *failed)
{
int check,i,its,j;
phydbl den,fac,fad,fae,fp,stpmax,sum=0.0,sumdg,sumxi,temp,test,fret;
phydbl *dg,*g,*hdg,**hessin,*pnew,*xi;
hessin = (phydbl **)mCalloc(n,sizeof(phydbl *));
For(i,n) hessin[i] = (phydbl *)mCalloc(n,sizeof(phydbl));
dg = (phydbl *)mCalloc(n,sizeof(phydbl ));
g = (phydbl *)mCalloc(n,sizeof(phydbl ));
pnew = (phydbl *)mCalloc(n,sizeof(phydbl ));
hdg = (phydbl *)mCalloc(n,sizeof(phydbl ));
xi = (phydbl *)mCalloc(n,sizeof(phydbl ));
/* PhyML_Printf("\n. ENTER BFGS WITH: %f\n",Lk(tree)); */
fp=(*func)(tree);
(*dfunc)(tree,p,n,step_size,func,g);
for (i=0;i %f\n",tree->c_lnL); */
fp = fret;
for (i=0;i test) test=temp;
}
if (test < TOLX)
{
(*func)(tree);
For(i,n) Free(hessin[i]);
free(hessin);
free(xi);
free(pnew);
free(hdg);
free(g);
free(dg);
if(its == 1)
{
/* PhyML_Printf("\n. WARNING : BFGS failed ! \n"); */
*failed = 1;
}
return;
}
for (i=0;i test) test=temp;
}
if (test < gtol)
{
(*func)(tree);
For(i,n) Free(hessin[i]);
free(hessin);
free(xi);
free(pnew);
free(hdg);
free(g);
free(dg);
return;
}
for (i=0;i EPS*sumdg*sumxi)
{
fac=1.0/fac;
fad=1.0/fae;
for (i=0;i stpmax)
for(i=0;i test) test=temp;
}
alamin=TOLX/test;
alam=1.0;
for (;;)
{
for(i=0;imod->rr_val->v[i] = FABS(local_xold[i]+alam*p[i]);
}
/**/
if(i==n)
{
*f=Return_Abs_Lk(tree);
}
else *f=1.+fold+ALF*alam*slope;
if (alam < alamin)
{
for (i=0;imod->rr_val->v[i] = FABS(local_xold[i]);
}
/**/
*check=1;
For(i,n) xold[i] = local_xold[i];
Free(local_xold);
return 0;
}
else if (*f <= fold+ALF*alam*slope)
{
For(i,n) xold[i] = local_xold[i];
Free(local_xold);
return 0;
}
else
{
/* if (alam == 1.0) */
if ((alam < 1.0+SMALL) && (alam > 1.0-SMALL))
tmplam = -slope/(2.0*(*f-fold-slope));
else
{
rhs1 = *f-fold-alam*slope;
rhs2=f2-fold2-alam2*slope;
a=(rhs1/(alam*alam)-rhs2/(alam2*alam2))/(alam-alam2);
b=(-alam2*rhs1/(alam*alam)+alam*rhs2/(alam2*alam2))/(alam-alam2);
if (a < SMALL && a > -SMALL) tmplam = -slope/(2.0*b);
else
{
disc=b*b-3.0*a*slope;
if (disc<0.0) tmplam = 0.5*alam;
else if(b <= 0.0) tmplam=(-b+SQRT(disc))/(3.0*a);
else tmplam = -slope/(b+SQRT(disc));
}
if (tmplam>0.5*alam) tmplam=0.5*alam;
}
}
alam2=alam;
f2 = *f;
fold2=fold;
alam=MAX(tmplam,0.1*alam);
}
Free(local_xold);
return 1;
}
#undef ALF
#undef TOLX
#undef NRANSI
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
#define ALF 1.0e-4
#define TOLX 1.0e-7
int Lnsrch_RR_Cov_Param(t_tree *tree, int n, phydbl *xold, phydbl fold,
phydbl *g, phydbl *p, phydbl *x,
phydbl *f, phydbl stpmax, int *check)
{
int i;
phydbl a,alam,alam2,alamin,b,disc,f2,fold2,rhs1,rhs2,slope,sum,temp,test,tmplam;
phydbl *local_xold;
alam = alam2 = f2 = fold2 = tmplam = .0;
local_xold = (phydbl *)mCalloc(n,sizeof(phydbl));
For(i,n) local_xold[i] = xold[i];
*check=0;
for(sum=0.0,i=0;i stpmax)
for(i=0;i test) test=temp;
}
alamin=TOLX/test;
alam=1.0;
for (;;)
{
for(i=0;imod->m4mod->o_rr[i] = FABS(local_xold[i]+alam*p[i]);
}
/**/
if(i==n)
{
*f=Return_Abs_Lk(tree);
/* PhyML_Printf("LOGlk = %f\n",*f); */
}
else *f=1.+fold+ALF*alam*slope;
if (alam < alamin)
{
for (i=0;imod->m4mod->o_rr[i] = FABS(local_xold[i]);
}
/**/
*check=1;
For(i,n) xold[i] = local_xold[i];
Free(local_xold);
return 0;
}
else if (*f <= fold+ALF*alam*slope)
{
For(i,n) xold[i] = local_xold[i];
Free(local_xold);
return 0;
}
else
{
/* if (alam == 1.0) */
if ((alam < 1.0+SMALL) && (alam > 1.0-SMALL))
tmplam = -slope/(2.0*(*f-fold-slope));
else
{
rhs1 = *f-fold-alam*slope;
rhs2=f2-fold2-alam2*slope;
a=(rhs1/(alam*alam)-rhs2/(alam2*alam2))/(alam-alam2);
b=(-alam2*rhs1/(alam*alam)+alam*rhs2/(alam2*alam2))/(alam-alam2);
/* if (a == 0.0) tmplam = -slope/(2.0*b); */
if (a < SMALL && a > -SMALL) tmplam = -slope/(2.0*b);
else
{
disc=b*b-3.0*a*slope;
if (disc<0.0) tmplam = 0.5*alam;
else if(b <= 0.0) tmplam=(-b+SQRT(disc))/(3.0*a);
else tmplam = -slope/(b+SQRT(disc));
}
if (tmplam>0.5*alam) tmplam=0.5*alam;
}
}
alam2=alam;
f2 = *f;
fold2=fold;
alam=MAX(tmplam,0.1*alam);
}
Free(local_xold);
return 1;
}
#undef ALF
#undef TOLX
#undef NRANSI
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
#define ALF 1.0e-4
#define TOLX 1.0e-7
int Lnsrch_Nucleotide_Frequencies(t_tree *tree, int n, phydbl *xold, phydbl fold, phydbl *g, phydbl *p, phydbl *x,
phydbl *f, phydbl stpmax, int *check)
{
int i;
phydbl a,alam,alam2,alamin,b,disc,f2,fold2,rhs1,rhs2,slope,sum,temp,test,tmplam;
phydbl *local_xold;
alam = alam2 = f2 = fold2 = tmplam = .0;
local_xold = (phydbl *)mCalloc(n,sizeof(phydbl));
For(i,n) local_xold[i] = xold[i];
*check=0;
for(sum=0.0,i=0;i stpmax)
for(i=0;i test) test=temp;
}
alamin=TOLX/test;
alam=1.0;
for (;;)
{
for(i=0;imod->pi_unscaled->v[i]=FABS(local_xold[i]+alam*p[i]);
/* if( */
/* (tree->mod->pi[i] < 0.001) || */
/* (tree->mod->pi[i] > 0.999) */
/* ) */
/* break; */
}
/**/
if(i==n)
{
*f=Return_Abs_Lk(tree);
}
else *f=1.+fold+ALF*alam*slope;
if (alam < alamin)
{
for (i=0;imod->pi_unscaled->v[i]=local_xold[i];
*check=1;
For(i,n) xold[i] = local_xold[i];
Free(local_xold);
return 0;
}
else if (*f <= fold+ALF*alam*slope)
{
For(i,n) xold[i] = local_xold[i];
Free(local_xold);
return 0;
}
else
{
if ((alam < 1.0+SMALL) && (alam > 1.0-SMALL))
/* if (alam == 1.0) */
tmplam = -slope/(2.0*(*f-fold-slope));
else
{
rhs1 = *f-fold-alam*slope;
rhs2=f2-fold2-alam2*slope;
a=(rhs1/(alam*alam)-rhs2/(alam2*alam2))/(alam-alam2);
b=(-alam2*rhs1/(alam*alam)+alam*rhs2/(alam2*alam2))/(alam-alam2);
if (a < SMALL && a > -SMALL) tmplam = -slope/(2.0*b);
/* if (a == 0.0) tmplam = -slope/(2.0*b); */
else
{
disc=b*b-3.0*a*slope;
if (disc<0.0)
{
disc=b*b-3.0*a*slope;
if (disc<0.0) tmplam = 0.5*alam;
else if(b <= 0.0) tmplam=(-b+SQRT(disc))/(3.0*a);
else tmplam = -slope/(b+SQRT(disc));
}
else tmplam=(-b+SQRT(disc))/(3.0*a);
}
if (tmplam>0.5*alam) tmplam=0.5*alam;
}
}
alam2=alam;
f2 = *f;
fold2=fold;
alam=MAX(tmplam,0.1*alam);
}
Free(local_xold);
return 1;
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
#define ALF 1.0e-4
#define TOLX 1.0e-7
int Lnsrch_Free_Mixt_Rates(t_tree *tree, int n, phydbl *xold, phydbl fold, phydbl *g, phydbl *p, phydbl *x,
phydbl *f, phydbl stpmax, int *check)
{
int i;
phydbl a,alam,alam2,alamin,b,disc,f2,fold2,rhs1,rhs2,slope,sum,temp,test,tmplam;
phydbl *local_xold;
alam = alam2 = f2 = fold2 = tmplam = .0;
local_xold = (phydbl *)mCalloc(n,sizeof(phydbl));
For(i,n) local_xold[i] = xold[i];
*check=0;
for(sum=0.0,i=0;i stpmax)
for(i=0;i test) test=temp;
}
alamin=TOLX/test;
alam=1.0;
for (;;)
{
for(i=0;imod->gamma_r_proba->v[i]=FABS(local_xold[i]+alam*p[i]);
}
/**/
if(i==n)
{
*f=Return_Abs_Lk(tree);
}
else *f=1.+fold+ALF*alam*slope;
if (alam < alamin)
{
for (i=0;imod->gamma_r_proba->v[i]=local_xold[i];
*check=1;
For(i,n) xold[i] = local_xold[i];
Free(local_xold);
return 0;
}
else if (*f <= fold+ALF*alam*slope)
{
For(i,n) xold[i] = local_xold[i];
Free(local_xold);
return 0;
}
else
{
if ((alam < 1.0+SMALL) && (alam > 1.0-SMALL))
/* if (alam == 1.0) */
tmplam = -slope/(2.0*(*f-fold-slope));
else
{
rhs1 = *f-fold-alam*slope;
rhs2=f2-fold2-alam2*slope;
a=(rhs1/(alam*alam)-rhs2/(alam2*alam2))/(alam-alam2);
b=(-alam2*rhs1/(alam*alam)+alam*rhs2/(alam2*alam2))/(alam-alam2);
if (a < SMALL && a > -SMALL) tmplam = -slope/(2.0*b);
/* if (a == 0.0) tmplam = -slope/(2.0*b); */
else
{
disc=b*b-3.0*a*slope;
if (disc<0.0)
{
disc=b*b-3.0*a*slope;
if (disc<0.0) tmplam = 0.5*alam;
else if(b <= 0.0) tmplam=(-b+SQRT(disc))/(3.0*a);
else tmplam = -slope/(b+SQRT(disc));
}
else tmplam=(-b+SQRT(disc))/(3.0*a);
}
if (tmplam>0.5*alam) tmplam=0.5*alam;
}
}
alam2=alam;
f2 = *f;
fold2=fold;
alam=MAX(tmplam,0.1*alam);
}
Free(local_xold);
return 1;
}
/* void Optimize_Global_Rate(t_tree *tree) */
/* { */
/* PhyML_Printf("\n. Global rate (%f->)",tree->c_lnL); */
/* Optimize_Single_Param_Generic(tree,&(tree->tbl),tree->tbl,tree->l_min,1.E+4,100); */
/* PhyML_Printf("%f)\n",tree->c_lnL); */
/* } */
#undef ALF
#undef TOLX
#undef NRANSI
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
int Dist_F_Brak(phydbl *ax, phydbl *bx, phydbl *cx, phydbl *F, phydbl *param, model *mod)
{
phydbl ulim,u,r,q,dum;
phydbl fa, fb, fc, fu;
fa = -Lk_Dist(F,FABS(*ax),mod);
fb = -Lk_Dist(F,FABS(*bx),mod);
if(fb > fa)
{
SHFT(dum,*ax,*bx,dum)
SHFT(dum,fb,fa,dum)
}
*cx=(*bx)+MNBRAK_GOLD*(*bx-*ax);
fc = -Lk_Dist(F,FABS(*cx),mod);
while (fb > fc)
{
r=(*bx-*ax)*(fb-fc);
q=(*bx-*cx)*(fb-fa);
u=(*bx)-((*bx-*cx)*q-(*bx-*ax)*r)/
(2.0*SIGN(MAX(FABS(q-r),MNBRAK_TINY),q-r));
ulim=(*bx)+MNBRAK_GLIMIT*(*cx-*bx);
if ((*bx-u)*(u-*cx) > 0.0)
{
fu = -Lk_Dist(F,FABS(u),mod);
if (fu < fc)
{
*ax=(*bx);
*bx=u;
fa=fb;
fb=fu;
return(0);
}
else if (fu > fb)
{
*cx=u;
fc=fu;
return(0);
}
u=(*cx)+MNBRAK_GOLD*(*cx-*bx);
fu = -Lk_Dist(F,FABS(u),mod);
}
else if ((*cx-u)*(u-ulim) > 0.0)
{
fu = -Lk_Dist(F,FABS(u),mod);
if (fu < fc)
{
SHFT(*bx,*cx,u,*cx+MNBRAK_GOLD*(*cx-*bx))
SHFT(fb,fc,fu,-Lk_Dist(F,FABS(u),mod))
}
}
else if ((u-ulim)*(ulim-*cx) >= 0.0)
{
u = ulim;
fu = -Lk_Dist(F,FABS(u),mod);
}
else
{
u =(*cx)+MNBRAK_GOLD*(*cx-*bx);
fu = -Lk_Dist(F,FABS(u),mod);
}
SHFT(*ax,*bx,*cx,u)
SHFT(fa,fb,fc,fu)
}
return(0);
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
phydbl Dist_F_Brent(phydbl ax, phydbl bx, phydbl cx, phydbl tol, int n_iter_max,
phydbl *param, phydbl *F, model *mod)
{
int iter;
phydbl a,b,d,etemp,fu,fv,fw,fx,p,q,r,tol1,tol2,u,v,w,x,xm;
phydbl e=0.0;
phydbl old_lnL,init_lnL, curr_lnL;
d=0.0;
a=((ax < cx) ? ax : cx);
b=((ax > cx) ? ax : cx);
x = w = v = bx;
old_lnL = UNLIKELY;
fw = fv = fx = -Lk_Dist(F,FABS(bx),mod);
curr_lnL = init_lnL = -fw;
for(iter=1;iter<=BRENT_ITMAX;iter++)
{
xm=0.5*(a+b);
tol2=2.0*(tol1=tol*FABS(x)+BRENT_ZEPS);
if(
((FABS(curr_lnL-old_lnL) < mod->s_opt->min_diff_lk_local) &&
(curr_lnL > init_lnL - mod->s_opt->min_diff_lk_local)) ||
(iter > n_iter_max - 1)
)
{
*param = x;
curr_lnL = Lk_Dist(F,*param,mod);
return -curr_lnL;
}
if(FABS(e) > tol1)
{
r=(x-w)*(fx-fv);
q=(x-v)*(fx-fw);
p=(x-v)*q-(x-w)*r;
q=2.0*(q-r);
if(q > 0.0) p = -p;
q=FABS(q);
etemp=e;
e=d;
if(FABS(p) >= FABS(0.5*q*etemp) || p <= q*(a-x) || p >= q*(b-x))
{
d=BRENT_CGOLD*(e=(x >= xm ? a-x : b-x));
/* PhyML_Printf("Golden section step\n"); */
}
else
{
d=p/q;
u=x+d;
if (u-a < tol2 || b-u < tol2)
d=SIGN(tol1,xm-x);
/* PhyML_Printf("Parabolic step\n"); */
}
}
else
{
d=BRENT_CGOLD*(e=(x >= xm ? a-x : b-x));
/* PhyML_Printf("Golden section step (default)\n"); */
}
u=(FABS(d) >= tol1 ? x+d : x+SIGN(tol1,d));
(*param) = FABS(u);
old_lnL = curr_lnL;
fu = -Lk_Dist(F,FABS(u),mod);
curr_lnL = -fu;
/* PhyML_Printf("param=%f LOGlk=%f\n",*param,fu); */
/* if(fu <= fx) */
if(fu < fx)
{
if(iter > n_iter_max) return -fu;
if(u >= x) a=x; else b=x;
SHFT(v,w,x,u)
SHFT(fv,fw,fx,fu)
}
else
{
if (u < x) a=u; else b=u;
/* if (fu <= fw || w == x) */
if (fu < fw || FABS(w-x) < SMALL)
{
v=w;
w=u;
fv=fw;
fw=fu;
}
/* else if (fu <= fv || v == x || v == w) */
else if (fu < fv || FABS(v-x) < SMALL || FABS(v-w) < SMALL)
{
v=u;
fv=fu;
}
}
}
Exit("\n. Too many iterations in BRENT !");
return(-1);
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void Opt_Dist_F(phydbl *dist, phydbl *F, model *mod)
{
phydbl ax,bx,cx;
if(*dist < mod->l_min) *dist = mod->l_min;
ax = mod->l_min;
bx = (*dist);
cx = mod->l_max;
/* Dist_F_Brak(&ax,&bx,&cx,F,dist,mod); */
Dist_F_Brent(ax,bx,cx,1.E-10,1000,dist,F,mod);
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
int Missing_Dist_Brak(phydbl *ax, phydbl *bx, phydbl *cx, int x, int y, matrix *mat)
{
phydbl ulim,u,r,q,dum;
phydbl fa, fb, fc, fu;
fa = Least_Square_Missing_Dist_XY(x,y,FABS(*ax),mat);
fb = Least_Square_Missing_Dist_XY(x,y,FABS(*bx),mat);
if(fb > fa)
{
SHFT(dum,*ax,*bx,dum)
SHFT(dum,fb,fa,dum)
}
*cx=(*bx)+MNBRAK_GOLD*((*bx)-(*ax));
fc = Least_Square_Missing_Dist_XY(x,y,FABS(*cx),mat);
while (fb > fc)
{
r=((*bx)-(*ax))*(fb-fc);
q=((*bx)-(*cx))*(fb-fa);
u=(*bx)-(((*bx)-(*cx))*q-((*bx)-(*ax))*r)/
(2.0*SIGN(MAX(FABS(q-r),MNBRAK_TINY),q-r));
ulim=(*bx)+MNBRAK_GLIMIT*(*cx-*bx);
if ((*bx-u)*(u-*cx) > 0.0)
{
fu = Least_Square_Missing_Dist_XY(x,y,FABS(u),mat);
if (fu < fc)
{
*ax=(*bx);
*bx=u;
fa=fb;
fb=fu;
return(0);
}
else if (fu > fb)
{
*cx=u;
fc=fu;
return(0);
}
u=(*cx)+MNBRAK_GOLD*(*cx-*bx);
fu = Least_Square_Missing_Dist_XY(x,y,FABS(u),mat);
}
else if ((*cx-u)*(u-ulim) > 0.0)
{
fu = Least_Square_Missing_Dist_XY(x,y,FABS(u),mat);
if (fu < fc)
{
SHFT(*bx,*cx,u,*cx+MNBRAK_GOLD*(*cx-*bx))
SHFT(fb,fc,fu,Least_Square_Missing_Dist_XY(x,y,FABS(u),mat))
}
}
else if ((u-ulim)*(ulim-*cx) >= 0.0)
{
u = ulim;
fu = Least_Square_Missing_Dist_XY(x,y,FABS(u),mat);
}
else
{
u =(*cx)+MNBRAK_GOLD*(*cx-*bx);
fu = Least_Square_Missing_Dist_XY(x,y,FABS(u),mat);
}
SHFT(*ax,*bx,*cx,u)
SHFT(fa,fb,fc,fu)
}
return(0);
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
phydbl Missing_Dist_Brent(phydbl ax, phydbl bx, phydbl cx, phydbl tol, int n_iter_max,
int x, int y, matrix *mat)
{
int iter;
phydbl a,b,d,etemp,fu,fv,fw,fx,p,q,r,tol1,tol2,u,v,w,xx,xm;
phydbl e=0.0;
phydbl init_LOGlk, max_LOGlk;
phydbl bestx;
d=0.0;
a=((ax < cx) ? ax : cx);
b=((ax > cx) ? ax : cx);
xx=w=v=bx;
fx=Least_Square_Missing_Dist_XY(x,y,FABS(bx),mat);
fw=fv=-fx;
init_LOGlk = fw;
max_LOGlk = UNLIKELY;
bestx = bx;
for(iter=1;iter<=BRENT_ITMAX;iter++)
{
xm=0.5*(a+b);
tol2=2.0*(tol1=tol*FABS(xx)+BRENT_ZEPS);
if(FABS(xx-xm) <= (tol2-0.5*(b-a)))
{
mat->dist[x][y] = xx;
Least_Square_Missing_Dist_XY(x,y,mat->dist[x][y],mat);
return -fx;
}
if(FABS(e) > tol1)
{
r=(xx-w)*(fx-fv);
q=(xx-v)*(fx-fw);
p=(xx-v)*q-(xx-w)*r;
q=2.0*(q-r);
if(q > 0.0) p = -p;
q=FABS(q);
etemp=e;
e=d;
if(FABS(p) >= FABS(0.5*q*etemp) || p <= q*(a-xx) || p >= q*(b-xx))
{
d=BRENT_CGOLD*(e=(xx >= xm ? a-xx : b-xx));
/* PhyML_Printf("Golden section step\n"); */
}
else
{
d=p/q;
u=xx+d;
if (u-a < tol2 || b-u < tol2)
d=SIGN(tol1,xm-xx);
/* PhyML_Printf("Parabolic step\n"); */
}
}
else
{
d=BRENT_CGOLD*(e=(xx >= xm ? a-xx : b-xx));
/* PhyML_Printf("Golden section step (default)\n"); */
}
u=(FABS(d) >= tol1 ? xx+d : xx+SIGN(tol1,d));
fu = Least_Square_Missing_Dist_XY(x,y,FABS(u),mat);
/* PhyML_Printf("param=%f LOGlk=%f\n",u,fu); */
/* if(fu <= fx) */
if(fu < fx)
{
if(iter > n_iter_max) return -fu;
if(u >= xx) a=xx; else b=xx;
SHFT(v,w,xx,u)
SHFT(fv,fw,fx,fu)
}
else
{
if (u < xx) a=u; else b=u;
/* if (fu <= fw || w == xx) */
if (fu < fw || FABS(w-xx) < SMALL)
{
v=w;
w=u;
fv=fw;
fw=fu;
}
/* else if (fu <= fv || v == xx || v == w) */
else if (fu < fv || FABS(v-xx) < SMALL || FABS(v-w) < SMALL)
{
v=u;
fv=fu;
}
}
}
Exit("\n. Too many iterations in BRENT !");
return(-1);
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void Opt_Missing_Dist(int x, int y, matrix *mat)
{
phydbl ax,bx,cx;
ax = DIST_MAX;
bx = DIST_MAX/4.;
Missing_Dist_Brak(&ax,&bx,&cx,x,y,mat);
PhyML_Printf("ax=%f bx=%f cx=%f\n",FABS(ax),FABS(bx),FABS(cx));
Missing_Dist_Brent(FABS(ax),FABS(bx),FABS(cx),1.E-5,100,x,y,mat);
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
int Optimiz_Alpha_And_Pinv(t_tree *tree)
{
int iter;
phydbl best_alpha, best_pinv, best_mult;
phydbl slope, intercept;
phydbl lk_b, lk_a;
phydbl lk_init, lk_final;
phydbl f0,f1,f2,f3,x0,x1,x2,x3;
phydbl pinv0, pinv1;
phydbl a, b, c;
phydbl fa, fb, fc;
phydbl K;
phydbl alpha0, alpha1;
phydbl best_lnL;
lk_final = UNLIKELY;
lk_b = UNLIKELY;
lk_a = UNLIKELY;
/* PhyML_Printf("\n\n. Init lnL = %f alpha=%f pinv=%f", */
/* tree->c_lnL, */
/* tree->mod->alpha, */
/* tree->mod->pinvar->v); */
/* Two (full) steps to compute pinv_alpha_slope & pinv_alpha_intercept */
tree->both_sides = 1;
Lk(tree);
lk_b = tree->c_lnL;
Optimize_Br_Len_Serie(tree->t_nodes[0],tree->t_nodes[0]->v[0],
tree->t_nodes[0]->b[0],tree,tree->data);
tree->both_sides = 0;
Optimize_Single_Param_Generic(tree,&(tree->mod->alpha->v),.01,100.,
tree->mod->s_opt->min_diff_lk_global,
tree->mod->s_opt->brent_it_max,
tree->mod->s_opt->quickdirty);
Optimize_Single_Param_Generic(tree,&(tree->mod->pinvar->v),.0001,0.9999,
tree->mod->s_opt->min_diff_lk_global,
tree->mod->s_opt->brent_it_max,
tree->mod->s_opt->quickdirty);
pinv0 = tree->mod->pinvar->v;
alpha0 = tree->mod->alpha->v;
f0 = tree->c_lnL;
tree->both_sides = 1;
Lk(tree);
Optimize_Br_Len_Serie(tree->t_nodes[0],tree->t_nodes[0]->v[0],
tree->t_nodes[0]->b[0],tree,tree->data);
tree->both_sides = 0;
Optimize_Single_Param_Generic(tree,&(tree->mod->alpha->v),.01,100.,
tree->mod->s_opt->min_diff_lk_global,
tree->mod->s_opt->brent_it_max,
tree->mod->s_opt->quickdirty);
Optimize_Single_Param_Generic(tree,&(tree->mod->pinvar->v),.0001,0.9999,
tree->mod->s_opt->min_diff_lk_global,
tree->mod->s_opt->brent_it_max,
tree->mod->s_opt->quickdirty);
lk_a = tree->c_lnL;
pinv1 = tree->mod->pinvar->v;
alpha1 = tree->mod->alpha->v;
f1 = tree->c_lnL;
best_lnL = f1;
if(lk_a < lk_b - tree->mod->s_opt->min_diff_lk_local)
{
PhyML_Printf("\n. Err in file %s at line %d\n",__FILE__,__LINE__);
Warn_And_Exit("");
}
else if(FABS(lk_a - lk_b) < tree->mod->s_opt->min_diff_lk_local)
{
return 1;
}
Record_Br_Len(tree);
best_alpha = tree->mod->alpha->v;
best_pinv = tree->mod->pinvar->v;
best_mult = tree->mod->br_len_multiplier->v;
lk_init = tree->c_lnL;
/* PhyML_Printf("\n\n. Init lnL after std opt = %f [%f] best_alpha=%f best_pinv=%f",tree->c_lnL,Lk(tree),best_alpha,best_pinv); */
/* PhyML_Printf("\n. Best_lnL = %f",best_lnL); */
slope = (pinv1 - pinv0)/(alpha1 - alpha0);
intercept = pinv1 - slope * alpha1;
if((slope > 0.001) && (slope < 1./0.001))
{
/* PhyML_Printf("\n. pinv0 = %f, pinv1 = %f, alpha0 = %f, alpha1 = %f",pinv0,pinv1,alpha0,alpha1); */
/* PhyML_Printf("\n. slope = %f intercept = %f",slope,intercept); */
K = 0.381966;
if(alpha1 < alpha0)
{
c = alpha0;
b = alpha1;
fc = f0;
fb = f1;
a = (0.1 < alpha1)?(0.1):(0.5*alpha1);
tree->mod->alpha->v = a;
tree->mod->pinvar->v = slope * tree->mod->alpha->v + intercept;
if(tree->mod->pinvar->v > 1.0) tree->mod->pinvar->v = 0.9;
if(tree->mod->pinvar->v < 0.0) tree->mod->pinvar->v = 0.001;
tree->both_sides = 1;
Lk(tree);
Optimize_Br_Len_Serie(tree->t_nodes[0],tree->t_nodes[0]->v[0],
tree->t_nodes[0]->b[0],tree,tree->data);
fa = tree->c_lnL;
iter = 0;
/* PhyML_Printf("\n. a=%f, b=%f, c=%f, fa=%f, fb=%f, fc=%f (alpha=%f pinv=%f)",a,b,c,fa,fb,fc,tree->mod->alpha->v,tree->mod->pinvar->v); */
while(fa > fb)
{
a = a/5.;
tree->mod->alpha->v = a;
tree->mod->pinvar->v = slope * tree->mod->alpha->v + intercept;
if(tree->mod->pinvar->v > 1.0) tree->mod->pinvar->v = 0.9;
if(tree->mod->pinvar->v < 0.0) tree->mod->pinvar->v = 0.001;
tree->both_sides = 1;
Lk(tree);
Optimize_Br_Len_Serie(tree->t_nodes[0],tree->t_nodes[0]->v[0],
tree->t_nodes[0]->b[0],tree,tree->data);
fa = tree->c_lnL;
/* PhyML_Printf("\n1 a=%f, b=%f, c=%f, fa=%f, fb=%f, fc=%f",a,b,c,fa,fb,fc); */
if(iter++ > 10) return 0;
}
}
else
{
a = alpha0;
b = alpha1;
fa = f0;
fb = f1;
c = (alpha1 < 2.)?(2.0):(2.*alpha1);
tree->mod->alpha->v = c;
tree->mod->pinvar->v = slope * tree->mod->alpha->v + intercept;
if(tree->mod->pinvar->v > 1.0) tree->mod->pinvar->v = 0.9;
if(tree->mod->pinvar->v < 0.0) tree->mod->pinvar->v = 0.001;
tree->both_sides = 1;
Lk(tree);
Optimize_Br_Len_Serie(tree->t_nodes[0],tree->t_nodes[0]->v[0],
tree->t_nodes[0]->b[0],tree,tree->data);
fc = tree->c_lnL;
/* PhyML_Printf("\n. a=%f, b=%f, c=%f, fa=%f, fb=%f, fc=%f (alpha=%f pinv=%f)",a,b,c,fa,fb,fc,tree->mod->alpha->v,tree->mod->pinvar->v); */
iter = 0;
while(fc > fb)
{
c = c*2.;
tree->mod->alpha->v = c;
tree->mod->pinvar->v = slope * tree->mod->alpha->v + intercept;
if(tree->mod->pinvar->v > 1.0) tree->mod->pinvar->v = 0.9;
if(tree->mod->pinvar->v < 0.0) tree->mod->pinvar->v = 0.001;
tree->both_sides = 1;
Lk(tree);
Optimize_Br_Len_Serie(tree->t_nodes[0],tree->t_nodes[0]->v[0],
tree->t_nodes[0]->b[0],tree,tree->data);
fc = tree->c_lnL;
/* PhyML_Printf("\n2 a=%f, b=%f, c=%f, fa=%f, fb=%f, fc=%f",a,b,c,fa,fb,fc); */
if(iter++ > 10) return 0;
}
}
if(FABS(b - c) > FABS(a - b))
{
x0 = a; x1 = b; x3 = c;
x2 = b + K * FABS(b - c);
f0 = fa;
f1 = fb;
f3 = fc;
tree->mod->alpha->v = x2;
tree->mod->pinvar->v = slope * tree->mod->alpha->v + intercept;
if(tree->mod->pinvar->v > 1.0) tree->mod->pinvar->v = 0.9;
if(tree->mod->pinvar->v < 0.0) tree->mod->pinvar->v = 0.001;
tree->both_sides = 1;
Lk(tree);
Optimize_Br_Len_Serie(tree->t_nodes[0],tree->t_nodes[0]->v[0],
tree->t_nodes[0]->b[0],tree,tree->data);
f2 = tree->c_lnL;
}
else /* |b -c| < |a - b| */
{
x0 = a; x2 = b; x3 = c;
x1 = b - K * FABS(b - a);
f0 = fa;
f2 = fb;
f3 = fc;
tree->mod->alpha->v = x1;
tree->mod->pinvar->v = slope * tree->mod->alpha->v + intercept;
if(tree->mod->pinvar->v > 1.0) tree->mod->pinvar->v = 0.9;
if(tree->mod->pinvar->v < 0.0) tree->mod->pinvar->v = 0.001;
tree->both_sides = 1;
Lk(tree);
Optimize_Br_Len_Serie(tree->t_nodes[0],tree->t_nodes[0]->v[0],
tree->t_nodes[0]->b[0],tree,tree->data);
f1 = tree->c_lnL;
}
iter = 0;
do
{
/* PhyML_Printf("\n. x0=%f, x1=%f, x2=%f, x3=%f, f0=%f, f1=%f, f2=%f, f3=%f", */
/* x0,x1,x2,x3,f0,f1,f2,f3); */
if(f1 > f2)
{
x3 = x2;
x2 = x1;
x1 = x2 - K * FABS(x2 - x0);
f3 = f2;
f2 = f1;
tree->mod->alpha->v = x1;
tree->mod->pinvar->v = slope * tree->mod->alpha->v + intercept;
if(tree->mod->pinvar->v > 1.0) tree->mod->pinvar->v = 0.9;
if(tree->mod->pinvar->v < 0.0) tree->mod->pinvar->v = 0.001;
tree->both_sides = 1;
Lk(tree);
Optimize_Br_Len_Serie(tree->t_nodes[0],tree->t_nodes[0]->v[0],
tree->t_nodes[0]->b[0],tree,tree->data);
f1 = tree->c_lnL;
if(f1 > best_lnL)
{
Record_Br_Len(tree);
best_alpha = tree->mod->alpha->v;
best_pinv = tree->mod->pinvar->v;
best_mult = tree->mod->br_len_multiplier->v;
/* PhyML_Printf("\n>.< New alpha=%f pinv=%f",best_alpha,best_pinv); */
}
/* PhyML_Printf("\n> f1=%f",f1); */
}
else /* f1 < f2 */
{
x0 = x1;
x1 = x2;
x2 = x2 + K * FABS(x3 - x2);
f0 = f1;
f1 = f2;
tree->mod->alpha->v = x2;
tree->mod->pinvar->v = slope * tree->mod->alpha->v + intercept;
if(tree->mod->pinvar->v > 1.0) tree->mod->pinvar->v = 0.9;
if(tree->mod->pinvar->v < 0.0) tree->mod->pinvar->v = 0.001;
tree->both_sides = 1;
Lk(tree);
Optimize_Br_Len_Serie(tree->t_nodes[0],tree->t_nodes[0]->v[0],
tree->t_nodes[0]->b[0],tree,tree->data);
f2 = tree->c_lnL;
if(f2 > best_lnL)
{
Record_Br_Len(tree);
best_alpha = tree->mod->alpha->v;
best_pinv = tree->mod->pinvar->v;
best_mult = tree->mod->br_len_multiplier->v;
/* PhyML_Printf("\n>o< New alpha=%f pinv=%f",best_alpha,best_pinv); */
}
/* PhyML_Printf("\n> f2=%f",f2); */
}
if(FABS(f1 - f2) < 0.01) break;
iter++;
}while(iter < 100);
}
tree->mod->alpha->v = best_alpha;
tree->mod->pinvar->v = best_pinv;
tree->mod->br_len_multiplier->v = best_mult;
Restore_Br_Len(tree);
tree->both_sides = 1;
Lk(tree);
/* PhyML_Printf("\n\n. Init lnL after golden opt = %f [%f] best_alpha=%f best_pinv=%f",tree->c_lnL,Lk(tree),best_alpha,best_pinv); */
return 1;
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
phydbl Generic_Brent_Lk(phydbl *param, phydbl ax, phydbl cx, phydbl tol,
int n_iter_max, int quickdirty,
phydbl (*obj_func)(t_edge *,t_tree *,supert_tree *),
t_edge *branch, t_tree *tree, supert_tree *stree)
{
int iter;
phydbl a,b,d,etemp,fu,fv,fw,fx,p,q,r,tol1,tol2,u,v,w,x,xm;
phydbl e=0.0;
phydbl old_lnL,init_lnL;
phydbl bx = *param;
d=0.0;
a=((ax < cx) ? ax : cx);
b=((ax > cx) ? ax : cx);
x=w=v=bx;
old_lnL = UNLIKELY;
(*param) = bx;
fw=fv=fx=fu=-(*obj_func)(branch,tree,stree);
init_lnL = -fw;
/* PhyML_Printf("\n. init_lnL = %f a=%f b=%f c=%f",init_lnL,ax,bx,cx); */
for(iter=1;iter<=BRENT_ITMAX;iter++)
{
xm=0.5*(a+b);
tol2=2.0*(tol1=tol*x+BRENT_ZEPS);
if((fu > init_lnL + tol) && (quickdirty))
{
(*param) = x;
fu = (*obj_func)(branch,tree,stree);
/* Exit("\n"); */
return fu;
}
/* if(((FABS(cur_lnL-old_lnL) < tol) && (cur_lnL > init_lnL - tol)) || (iter > n_iter_max - 1)) */
if((FABS(fu-old_lnL) < tol) || (iter > n_iter_max - 1))
{
(*param) = x;
fu = (*obj_func)(branch,tree,stree);
/* Exit("\n"); */
return fu;
}
if(FABS(e) > tol1)
{
r=(x-w)*(fx-fv);
q=(x-v)*(fx-fw);
p=(x-v)*q-(x-w)*r;
q=2.0*(q-r);
if(q > 0.0) p = -p;
q=FABS(q);
etemp=e;
e=d;
if(FABS(p) >= FABS(0.5*q*etemp) || p <= q*(a-x) || p >= q*(b-x))
{
d=BRENT_CGOLD*(e=(x >= xm ? a-x : b-x));
/* PhyML_Printf(" Golden section step\n"); */
}
else
{
d=p/q;
u=x+d;
if (u-a < tol2 || b-u < tol2) d=SIGN(tol1,xm-x);
/* PhyML_Printf(" Parabolic step [e=%f]\n",e); */
}
}
else
{
d=BRENT_CGOLD*(e=(x >= xm ? a-x : b-x));
/* PhyML_Printf(" Golden section step (default) [e=%f tol1=%f a=%f b=%f d=%f]\n",e,tol1,a,b,d); */
}
u=(FABS(d) >= tol1 ? x+d : x+SIGN(tol1,d));
(*param) = u;
old_lnL = fu;
fu = -(*obj_func)(branch,tree,stree);
/* PhyML_Printf("\n. iter=%d/%d param=%f lnL=%f",iter,BRENT_ITMAX,*param,fu); */
if(fu <= fx)
{
if(u >= x) a=x; else b=x;
SHFT(v,w,x,u)
SHFT(fv,fw,fx,fu)
}
else
{
if (u < x) a=u; else b=u;
/* if (fu <= fw || w == x) */
if (fu < fw || FABS(w-x) < SMALL)
{
v=w;
w=u;
fv=fw;
fw=fu;
}
/* else if (fu <= fv || v == x || v == w) */
else if (fu < fv || FABS(v-x) < SMALL || FABS(v-w) < SMALL)
{
v=u;
fv=fu;
}
}
}
Exit("\n. Too many iterations in BRENT !");
return(-1);
/* Not Reached ?? *param=x; */
/* Not Reached ?? return fx; */
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
/* find ML erstimates of node heights given fixed substitution
rates on branches. Also optimizes the overall substitution
rate */
void Round_Optimize_Node_Heights(t_tree *tree)
{
phydbl cur_lnL, new_lnL;
int n_iter;
cur_lnL = UNLIKELY;
new_lnL = Lk(tree);
printf("\n. cur_lnL = %f new_lnL=%f",cur_lnL,new_lnL);
n_iter = 0;
while(fabs(new_lnL - cur_lnL) > tree->mod->s_opt->min_diff_lk_global)
{
cur_lnL = tree->c_lnL;
Opt_Node_Heights_Recurr(tree);
Generic_Brent_Lk(&(tree->rates->clock_r),
tree->rates->min_clock,
tree->rates->max_clock,
tree->mod->s_opt->min_diff_lk_global,
tree->mod->s_opt->brent_it_max,
tree->mod->s_opt->quickdirty,
Wrap_Lk,NULL,tree,NULL);
printf("\n. cur_lnL=%f new_lnL=%f clock_r=%G root height=%f",
cur_lnL,new_lnL,tree->rates->clock_r,tree->rates->nd_t[tree->n_root->num]);
new_lnL = tree->c_lnL;
n_iter++;
if(n_iter > 100) break;
}
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void Opt_Node_Heights_Recurr(t_tree *tree)
{
Opt_Node_Heights_Recurr_Pre(tree->n_root,tree->n_root->v[0],tree);
Opt_Node_Heights_Recurr_Pre(tree->n_root,tree->n_root->v[1],tree);
Generic_Brent_Lk(&(tree->rates->nd_t[tree->n_root->num]),
MIN(tree->rates->t_prior_max[tree->n_root->num],
MIN(tree->rates->nd_t[tree->n_root->v[0]->num],
tree->rates->nd_t[tree->n_root->v[1]->num])),
tree->rates->t_prior_min[tree->n_root->num],
tree->mod->s_opt->min_diff_lk_global,
tree->mod->s_opt->brent_it_max,
tree->mod->s_opt->quickdirty,
Wrap_Lk,NULL,tree,NULL);
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void Opt_Node_Heights_Recurr_Pre(t_node *a, t_node *d, t_tree *tree)
{
if(d->tax) return;
else
{
int i;
phydbl t0,t1,t2,t3;
phydbl t_min,t_max;
t_node *v2,*v3;
v2 = v3 = NULL;
For(i,3)
if((d->v[i] != a) && (d->b[i] != tree->e_root))
{
if(!v2) { v2 = d->v[i]; }
else { v3 = d->v[i]; }
}
Opt_Node_Heights_Recurr_Pre(d,v2,tree);
Opt_Node_Heights_Recurr_Pre(d,v3,tree);
t0 = tree->rates->nd_t[a->num];
t1 = tree->rates->nd_t[d->num];
t2 = tree->rates->nd_t[v2->num];
t3 = tree->rates->nd_t[v3->num];
t_min = t0;
t_max = MIN(t2,t3);
t_min = MAX(t_min,tree->rates->t_prior_min[d->num]);
t_max = MIN(t_max,tree->rates->t_prior_max[d->num]);
t_min += tree->rates->min_dt;
t_max -= tree->rates->min_dt;
if(t_min > t_max)
{
PhyML_Printf("\n. Err in file %s at line %d\n",__FILE__,__LINE__);
Warn_And_Exit("");
}
Generic_Brent_Lk(&(tree->rates->nd_t[d->num]),
t_min,t_max,
tree->mod->s_opt->min_diff_lk_global,
tree->mod->s_opt->brent_it_max,
tree->mod->s_opt->quickdirty,
Wrap_Lk,NULL,tree,NULL);
/* printf("\n. t%d = %f [%f;%f] lnL = %f",d->num,tree->rates->nd_t[d->num],t_min,t_max,tree->c_lnL); */
}
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
phyml-20120412/src/pars.h 0000644 0001750 0001750 00000002265 11637265635 011751 0000000 0000000 /*
PHYML : a program that computes maximum likelihood phylogenies from
DNA or AA homologous sequences
Copyright (C) Stephane Guindon. Oct 2003 onward
All parts of the source except where indicated are distributed under
the GNU public licence. See http://www.opensource.org for details.
*/
#include
#ifndef PARS_H
#define PARS_H
#include "utilities.h"
#include "lk.h"
#include "optimiz.h"
#include "models.h"
#include "free.h"
void Make_Tree_4_Pars(t_tree *tree, calign *cdata, int n_site);
int Pars(t_tree *tree);
void Post_Order_Pars(t_node *a, t_node *d, t_tree *tree);
void Pre_Order_Pars(t_node *a, t_node *d, t_tree *tree);
void Get_Partial_Pars(t_tree *tree, t_edge *b_fcus, t_node *a, t_node *d);
void Site_Pars(t_tree *tree);
void Init_Ui_Tips(t_tree *tree);
void Update_P_Pars(t_tree *tree, t_edge *b_fcus, t_node *n);
int Pars_At_Given_Edge(t_edge *b, t_tree *tree);
void Get_All_Partial_Pars(t_tree *tree, t_edge *b_fcus, t_node *a, t_node *d);
int Update_Pars_At_Given_Edge(t_edge *b_fcus, t_tree *tree);
void Init_P_Pars_Tips(t_tree *tree);
void Get_Step_Mat(t_tree *tree);
int Pars_Core(t_edge *b, t_tree *tree);
int One_Pars_Step(t_edge *b,t_tree *tree);
#endif
phyml-20120412/src/models.c 0000644 0001750 0001750 00000505140 11730172536 012251 0000000 0000000 /*
PHYML : a program that computes maximum likelihood phyLOGenies from
DNA or AA homoLOGous sequences
Copyright (C) Stephane Guindon. Oct 2003 onward
All parts of the source except where indicated are distributed under
the GNU public licence. See http://www.opensource.org for details.
*/
#include "models.h"
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
/* Handle any number of states (>1) */
void PMat_JC69(phydbl l, int pos, phydbl *Pij, model *mod)
{
int ns;
int i,j;
ns = mod->ns;
For(i,ns) Pij[pos+ ns*i+i] = 1. - ((ns - 1.)/ns)*(1. - EXP(-ns*l/(ns - 1.)));
For(i,ns-1)
for(j=i+1;j A*/
/*1 => C*/
/*2 => G*/
/*3 => T*/
/* Ts -> transition*/
/* Tv -> transversion*/
aux = -2*l/(kappa+2);
e1 = (phydbl)EXP(aux *2);
e2 = (phydbl)EXP(aux *(kappa+1));
Tv = .25*(1-e1);
Ts = .25*(1+e1-2*e2);
Pij[pos+ 4*0+0] = Pij[pos+ 4*1+1] =
Pij[pos+ 4*2+2] = Pij[pos+ 4*3+3] = 1.-Ts-2.*Tv;
Pij[pos+ 4*0+1] = Pij[pos+ 4*1+0] = Tv;
Pij[pos+ 4*0+2] = Pij[pos+ 4*2+0] = Ts;
Pij[pos+ 4*0+3] = Pij[pos+ 4*3+0] = Tv;
Pij[pos+ 4*1+2] = Pij[pos+ 4*2+1] = Tv;
Pij[pos+ 4*1+3] = Pij[pos+ 4*3+1] = Ts;
Pij[pos+ 4*2+3] = Pij[pos+ 4*3+2] = Tv;
For(i,4) For(j,4)
if(Pij[pos + 4*i+j] < SMALL_PIJ) Pij[pos + 4*i+j] = SMALL_PIJ;
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void PMat_TN93(phydbl l, model *mod, int pos, phydbl *Pij)
{
int i,j;
phydbl e1,e2,e3;
phydbl a1t,a2t,bt;
phydbl A,C,G,T,R,Y;
phydbl kappa1,kappa2;
A = mod->pi->v[0]; C = mod->pi->v[1]; G = mod->pi->v[2]; T = mod->pi->v[3];
R = A+G; Y = T+C;
if(mod->kappa->v < .0) mod->kappa->v = 1.0e-5;
if((mod->whichmodel != F84) && (mod->whichmodel != TN93)) mod->lambda->v = 1.;
else if(mod->whichmodel == F84)
{
mod->lambda->v = Get_Lambda_F84(mod->pi->v,&mod->kappa->v);
}
kappa2 = mod->kappa->v*2./(1.+mod->lambda->v);
kappa1 = kappa2 * mod->lambda->v;
bt = l/(2.*(A*G*kappa1+C*T*kappa2+R*Y));
a1t = kappa1;
a2t = kappa2;
a1t*=bt; a2t*=bt;
e1 = (phydbl)EXP(-a1t*R-bt*Y);
e2 = (phydbl)EXP(-a2t*Y-bt*R);
e3 = (phydbl)EXP(-bt);
/*A->A*/Pij[pos + 4*0+0] = A+Y*A/R*e3+G/R*e1;
/*A->C*/Pij[pos + 4*0+1] = C*(1-e3);
/*A->G*/Pij[pos + 4*0+2] = G+Y*G/R*e3-G/R*e1;
/*A->T*/Pij[pos + 4*0+3] = T*(1-e3);
/*C->A*/Pij[pos + 4*1+0] = A*(1-e3);
/*C->C*/Pij[pos + 4*1+1] = C+R*C/Y*e3+T/Y*e2;
/*C->G*/Pij[pos + 4*1+2] = G*(1-e3);
/*C->T*/Pij[pos + 4*1+3] = T+R*T/Y*e3-T/Y*e2;
/*G->A*/Pij[pos + 4*2+0] = A+Y*A/R*e3-A/R*e1;
/*G->C*/Pij[pos + 4*2+1] = C*(1-e3);
/*G->G*/Pij[pos + 4*2+2] = G+Y*G/R*e3+A/R*e1;
/*G->T*/Pij[pos + 4*2+3] = T*(1-e3);
/*T->A*/Pij[pos + 4*3+0] = A*(1-e3);
/*T->C*/Pij[pos + 4*3+1] = C+R*C/Y*e3-C/Y*e2;
/*T->G*/Pij[pos + 4*3+2] = G*(1-e3);
/*T->T*/Pij[pos + 4*3+3] = T+R*T/Y*e3+C/Y*e2;
For(i,4) For(j,4)
if(Pij[pos + 4*i+j] < SMALL_PIJ) Pij[pos + 4*i+j] = SMALL_PIJ;
/* /\*A->A*\/(*Pij)[0][0] = A+Y*A/R*e3+G/R*e1; */
/* /\*A->C*\/(*Pij)[0][1] = C*(1-e3); */
/* /\*A->G*\/(*Pij)[0][2] = G+Y*G/R*e3-G/R*e1; */
/* /\*A->T*\/(*Pij)[0][3] = T*(1-e3); */
/* /\*C->A*\/(*Pij)[1][0] = A*(1-e3); */
/* /\*C->C*\/(*Pij)[1][1] = C+R*C/Y*e3+T/Y*e2; */
/* /\*C->G*\/(*Pij)[1][2] = G*(1-e3); */
/* /\*C->T*\/(*Pij)[1][3] = T+R*T/Y*e3-T/Y*e2; */
/* /\*G->A*\/(*Pij)[2][0] = A+Y*A/R*e3-A/R*e1; */
/* /\*G->C*\/(*Pij)[2][1] = C*(1-e3); */
/* /\*G->G*\/(*Pij)[2][2] = G+Y*G/R*e3+A/R*e1; */
/* /\*G->T*\/(*Pij)[2][3] = T*(1-e3); */
/* /\*T->A*\/(*Pij)[3][0] = A*(1-e3); */
/* /\*T->C*\/(*Pij)[3][1] = C+R*C/Y*e3-C/Y*e2; */
/* /\*T->G*\/(*Pij)[3][2] = G*(1-e3); */
/* /\*T->T*\/(*Pij)[3][3] = T+R*T/Y*e3+C/Y*e2; */
/* For(i,4) For(j,4) */
/* if((*Pij)[i][j] < SMALL) (*Pij)[i][j] = SMALL; */
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
phydbl Get_Lambda_F84(phydbl *pi, phydbl *kappa)
{
phydbl A,C,G,T,R,Y,lambda;
int kappa_has_changed;
A = pi[0]; C = pi[1]; G = pi[2]; T = pi[3];
R = A+G; Y = T+C;
if(*kappa < .0) *kappa = 1.0e-5;
kappa_has_changed = NO;
do
{
lambda = (Y+(R-Y)/(2.*(*kappa)))/(R-(R-Y)/(2.*(*kappa)));
if(lambda < .0)
{
*kappa += *kappa/10.;
kappa_has_changed = YES;
}
}while(lambda < .0);
if(kappa_has_changed)
{
PhyML_Printf("\n. WARNING: This transition/transversion ratio\n");
PhyML_Printf(" is impossible with these base frequencies!\n");
PhyML_Printf(" The ratio is now set to %.3f\n",*kappa);
}
return lambda;
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
/********************************************************************/
/* void PMat_Empirical(phydbl l, model *mod, phydbl ***Pij) */
/* */
/* Computes the substitution probability matrix */
/* from the initial substitution rate matrix and frequency vector */
/* and one specific branch length */
/* */
/* input : l , branch length */
/* input : mod , choosen model parameters, qmat and pi */
/* ouput : Pij , substitution probability matrix */
/* */
/* matrix P(l) is computed as follows : */
/* P(l) = EXP(Q*t) , where : */
/* */
/* Q = substitution rate matrix = Vr*D*inverse(Vr) , where : */
/* */
/* Vr = right eigenvector matrix for Q */
/* D = diagonal matrix of eigenvalues for Q */
/* */
/* t = time interval = l / mr , where : */
/* */
/* mr = mean rate = branch length/time interval */
/* = sum(i)(pi[i]*p(i->j)) , where : */
/* */
/* pi = state frequency vector */
/* p(i->j) = subst. probability from i to a different state */
/* = -Q[ii] , as sum(j)(Q[ij]) +Q[ii] =0 */
/* */
/* the Taylor development of EXP(Q*t) gives : */
/* P(l) = Vr*EXP(D*t) *inverse(Vr) */
/* = Vr*POW(EXP(D/mr),l)*inverse(Vr) */
/* */
/* for performance we compute only once the following matrixes : */
/* Vr, inverse(Vr), EXP(D/mr) */
/* thus each time we compute P(l) we only have to : */
/* make 20 times the operation POW() */
/* make 2 20x20 matrix multiplications , that is : */
/* 16000 = 2x20x20x20 times the operation * */
/* 16000 = 2x20x20x20 times the operation + */
/* which can be reduced to (the central matrix being diagonal) : */
/* 8400 = 20x20 + 20x20x20 times the operation * */
/* 8000 = 20x20x20 times the operation + */
/********************************************************************/
void PMat_Empirical(phydbl l, model *mod, int pos, phydbl *Pij)
{
int n = mod->ns;
int i, j, k;
phydbl *U,*V,*R;
phydbl *expt;
phydbl *uexpt;
expt = mod->eigen->e_val_im;
uexpt = mod->eigen->r_e_vect_im;
U = mod->eigen->r_e_vect;
V = mod->eigen->l_e_vect;
R = mod->eigen->e_val; /* exponential of the eigen value matrix */
For(i,n) For(k,n) Pij[pos+mod->ns*i+k] = .0;
/* compute POW(EXP(D/mr),l) into mat_eDmrl */
For(k,n) expt[k] = (phydbl)POW(R[k],l);
/* multiply Vr*POW(EXP(D/mr),l)*Vi into Pij */
For (i,n) For (k,n) uexpt[i*n+k] = U[i*n+k] * expt[k];
For (i,n)
{
For (j,n)
{
For(k,n)
{
Pij[pos+mod->ns*i+j] += (uexpt[i*n+k] * V[k*n+j]);
}
/* if(Pij[pos+mod->ns*i+j] < SMALL) Pij[pos+mod->ns*i+j] = SMALL; */
if(Pij[pos+mod->ns*i+j] < SMALL_PIJ) Pij[pos+mod->ns*i+j] = SMALL_PIJ;
}
#ifndef PHYML
phydbl sum;
sum = .0;
For (j,n) sum += Pij[pos+mod->ns*i+j];
if((sum > 1.+.0001) || (sum < 1.-.0001))
{
PhyML_Printf("\n");
PhyML_Printf("\n. Q\n");
For(i,n) { For(j,n) PhyML_Printf("%7.3f ",mod->eigen->q[i*n+j]); PhyML_Printf("\n"); }
PhyML_Printf("\n. U\n");
For(i,n) { For(j,n) PhyML_Printf("%7.3f ",U[i*n+j]); PhyML_Printf("\n"); }
PhyML_Printf("\n");
PhyML_Printf("\n. V\n");
For(i,n) { For(j,n) PhyML_Printf("%7.3f ",V[i*n+j]); PhyML_Printf("\n"); }
PhyML_Printf("\n");
PhyML_Printf("\n. Eigen\n");
For(i,n) PhyML_Printf("%E ",expt[i]);
PhyML_Printf("\n");
PhyML_Printf("\n. Pij\n");
For(i,n) { For (j,n) PhyML_Printf("%f ",Pij[pos+mod->ns*i+j]); PhyML_Printf("\n"); }
PhyML_Printf("\n. sum = %f",sum);
if(mod->m4mod)
{
int i;
PhyML_Printf("\n. mod->m4mod->alpha = %f",mod->m4mod->alpha);
PhyML_Printf("\n. mod->m4mod->delta = %f",mod->m4mod->delta);
For(i,mod->m4mod->n_h)
{
PhyML_Printf("\n. mod->m4mod->multipl[%d] = %f",i,mod->m4mod->multipl[i]);
}
}
PhyML_Printf("\n. l=%f",l);
PhyML_Printf("\n. Err in file %s at line %d\n\n",__FILE__,__LINE__);
Warn_And_Exit("");
}
#endif
}
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void PMat_Gamma(phydbl l, model *mod, int pos, phydbl *Pij)
{
int n;
int i, j, k;
phydbl *U,*V,*R;
phydbl *expt;
phydbl *uexpt;
phydbl shape;
n = mod->ns;
expt = mod->eigen->e_val_im;
uexpt = mod->eigen->r_e_vect_im;
U = mod->eigen->r_e_vect;
V = mod->eigen->l_e_vect;
R = mod->eigen->e_val; /* exponential of the eigen value matrix */
if(mod->n_catg == 1) shape = 1.E+4;
else shape = mod->alpha->v;
For(i,n) For(k,n) Pij[pos+mod->ns*i+k] = .0;
if(shape < 1.E-10)
{
PhyML_Printf("\n. Err in file %s at line %d\n\n",__FILE__,__LINE__);
Warn_And_Exit("");
}
/* Formula 13.42, page 220 of Felsenstein's book ``Inferring PhyLOGenies'' */
For(k,n) expt[k] = POW(shape/(shape-LOG(R[k])*l),shape);
/* multiply Vr*expt*Vi into Pij */
For(i,n) For(k,n) uexpt[i*n+k] = U[i*n+k] * expt[k];
For (i,n)
{
For (j,n)
{
For(k,n)
{
Pij[pos+mod->ns*i+j] += (uexpt[i*n+k] * V[k*n+j]);
}
if(Pij[pos+mod->ns*i+j] < SMALL_PIJ) Pij[pos+mod->ns*i+j] = SMALL_PIJ;
}
#ifdef DEBUG
phydbl sum;
sum = .0;
For (j,n) sum += Pij[pos+mod->ns*i+j];
if((sum > 1.+.0001) || (sum < 1.-.0001))
{
PhyML_Printf("\n");
PhyML_Printf("\n. Q\n");
For(i,n) { For(j,n) PhyML_Printf("%7.3f ",mod->eigen->q[i*n+j]); PhyML_Printf("\n"); }
PhyML_Printf("\n. U\n");
For(i,n) { For(j,n) PhyML_Printf("%7.3f ",U[i*n+j]); PhyML_Printf("\n"); }
PhyML_Printf("\n");
PhyML_Printf("\n. V\n");
For(i,n) { For(j,n) PhyML_Printf("%7.3f ",V[i*n+j]); PhyML_Printf("\n"); }
PhyML_Printf("\n");
PhyML_Printf("\n. Eigen\n");
For(i,n) PhyML_Printf("%E ",expt[i]);
PhyML_Printf("\n");
PhyML_Printf("\n. Pij\n");
For(i,n) { For (j,n) PhyML_Printf("%f ",Pij[pos+mod->ns*i+j]); PhyML_Printf("\n"); }
PhyML_Printf("\n. sum = %f",sum);
if(mod->m4mod)
{
int i;
PhyML_Printf("\n. mod->m4mod->alpha = %f",mod->m4mod->alpha);
PhyML_Printf("\n. mod->m4mod->delta = %f",mod->m4mod->delta);
For(i,mod->m4mod->n_h)
{
PhyML_Printf("\n. mod->m4mod->multipl[%d] = %f",i,mod->m4mod->multipl[i]);
}
}
PhyML_Printf("\n. l=%f",l);
PhyML_Printf("\n. Err in file %s at line %d\n\n",__FILE__,__LINE__);
Warn_And_Exit("");
}
#endif
}
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void PMat_Zero_Br_Len(model *mod, int pos, phydbl *Pij)
{
int n = mod->ns;
int i, j;
For (i,n) For (j,n) Pij[pos+mod->ns*i+j] = .0;
For (i,n) Pij[pos+mod->ns*i+i] = 1.0;
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void PMat(phydbl l, model *mod, int pos, phydbl *Pij)
{
/* Warning: l is never the og of branch length here */
if(l < 0.0)
{
PMat_Zero_Br_Len(mod,pos,Pij);
}
else
{
switch(mod->io->datatype)
{
case NT :
{
if(mod->use_m4mod)
{
PMat_Empirical(l,mod,pos,Pij);
}
else
{
if((mod->whichmodel == JC69) ||
(mod->whichmodel == K80))
{
/* PMat_JC69(l,pos,Pij,mod); */
PMat_K80(l,mod->kappa->v,pos,Pij);
}
else
{
if(
(mod->whichmodel == F81) ||
(mod->whichmodel == HKY85) ||
(mod->whichmodel == F84) ||
(mod->whichmodel == TN93))
{
PMat_TN93(l,mod,pos,Pij);
}
else
{
PMat_Empirical(l,mod,pos,Pij);
}
}
break;
}
case AA :
{
PMat_Empirical(l,mod,pos,Pij);
break;
}
default:
{
PMat_JC69(l,pos,Pij,mod);
break;
/* PhyML_Printf("\n. Not implemented yet.\n"); */
/* PhyML_Printf("\n. Err in file %s at line %d\n",__FILE__,__LINE__); */
/* Warn_And_Exit(""); */
/* break; */
}
}
}
}
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
int GetDaa (phydbl *daa, phydbl *pi, char *file_name)
{
/* Get the amino acid distance (or substitution rate) matrix
(grantham, dayhoff, jones, etc).
*/
FILE * fdaa;
int i,j, naa;
phydbl dmax,dmin;
phydbl sum;
double val;
naa = 20;
dmax = .0;
dmin = 1.E+40;
fdaa = (FILE *)Openfile(file_name,0);
for(i=0; idaa[i*naa+j]) dmin=daa[i*naa+j];
}
For(i,naa)
{
/* if(fscanf(fdaa,"%lf",&pi[i])!=1) Exit("\n. err aaRatefile"); */
if(fscanf(fdaa,"%lf",&val)!=1) Exit("\n. err aaRatefile");
pi[i] = (phydbl)val;
}
sum = 0.0;
For(i, naa) sum += pi[i];
if (FABS(1-sum)>1e-4) {
PhyML_Printf("\nSum of freq. = %.6f != 1 in aaRateFile\n",sum);
exit(-1);
}
fclose (fdaa);
return (0);
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
int Init_Qmat_Dayhoff(phydbl *daa, phydbl *pi)
{
/* Dayhoff's model data
* Dayhoff, M.O., Schwartz, R.M., Orcutt, B.C. (1978)
* "A model of evolutionary change in proteins."
* Dayhoff, M.O.(ed.) Atlas of Protein Sequence Structur., Vol5, Suppl3.
* National Biomedical Research Foundation, Washington DC, pp.345-352.
*/
int i,j,naa;
naa = 20;
/* PhyML_Printf("\n\n. REMINDER : THIS IS NOT DAYHOFF !!!\n\n"); */
/* daa[1*20 + 0] = 0.538903; */
/* daa[2*20 + 0] = 0.412504; */
/* daa[2*20 + 1] = 0.736081; */
/* daa[3*20 + 0] = 0.586915; */
/* daa[3*20 + 1] = 0.108051; */
/* daa[3*20 + 2] = 5.446642; */
/* daa[4*20 + 0] = 2.189718; */
/* daa[4*20 + 1] = 0.830604; */
/* daa[4*20 + 2] = 0.573426; */
/* daa[4*20 + 3] = 0.077565; */
/* daa[5*20 + 0] = 1.08213; */
/* daa[5*20 + 1] = 2.950693; */
/* daa[5*20 + 2] = 1.739514; */
/* daa[5*20 + 3] = 0.559035; */
/* daa[5*20 + 4] = 0.111314; */
/* daa[6*20 + 0] = 1.386865; */
/* daa[6*20 + 1] = 0.358434; */
/* daa[6*20 + 2] = 0.541447; */
/* daa[6*20 + 3] = 5.406871; */
/* daa[6*20 + 4] = 0.003738; */
/* daa[6*20 + 5] = 4.124043; */
/* daa[7*20 + 0] = 2.085747; */
/* daa[7*20 + 1] = 0.453132; */
/* daa[7*20 + 2] = 1.815844; */
/* daa[7*20 + 3] = 1.08647; */
/* daa[7*20 + 4] = 0.526418; */
/* daa[7*20 + 5] = 0.347693; */
/* daa[7*20 + 6] = 0.438476; */
/* daa[8*20 + 0] = 0.407898; */
/* daa[8*20 + 1] = 2.689322; */
/* daa[8*20 + 2] = 5.386808; */
/* daa[8*20 + 3] = 0.884563; */
/* daa[8*20 + 4] = 0.658583; */
/* daa[8*20 + 5] = 4.588358; */
/* daa[8*20 + 6] = 0.386218; */
/* daa[8*20 + 7] = 0.368668; */
/* daa[9*20 + 0] = 0.10177; */
/* daa[9*20 + 1] = 0.104875; */
/* daa[9*20 + 2] = 0.16239; */
/* daa[9*20 + 3] = 0.011698; */
/* daa[9*20 + 4] = 0.253282; */
/* daa[9*20 + 5] = 0.083872; */
/* daa[9*20 + 6] = 0.041767; */
/* daa[9*20 + 7] = 0.009778; */
/* daa[9*20 + 8] = 0.1042; */
/* daa[10*20 + 0] = 0.248202; */
/* daa[10*20 + 1] = 0.375742; */
/* daa[10*20 + 2] = 0.093863; */
/* daa[10*20 + 3] = 0.019241; */
/* daa[10*20 + 4] = 0.572688; */
/* daa[10*20 + 5] = 0.703538; */
/* daa[10*20 + 6] = 0.071961; */
/* daa[10*20 + 7] = 0.03006; */
/* daa[10*20 + 8] = 0.418222; */
/* daa[10*20 + 9] = 3.702051; */
/* daa[11*20 + 0] = 0.652019; */
/* daa[11*20 + 1] = 5.940478; */
/* daa[11*20 + 2] = 2.352253; */
/* daa[11*20 + 3] = 0.231001; */
/* daa[11*20 + 4] = 0.027995; */
/* daa[11*20 + 5] = 3.646743; */
/* daa[11*20 + 6] = 1.507981; */
/* daa[11*20 + 7] = 0.331175; */
/* daa[11*20 + 8] = 0.698362; */
/* daa[11*20 + 9] = 0.140326; */
/* daa[11*20 + 10] = 0.171396; */
/* daa[12*20 + 0] = 0.694226; */
/* daa[12*20 + 1] = 0.419899; */
/* daa[12*20 + 2] = 0.326927; */
/* daa[12*20 + 3] = 0.039488; */
/* daa[12*20 + 4] = 0.844827; */
/* daa[12*20 + 5] = 1.394214; */
/* daa[12*20 + 6] = 0.133235; */
/* daa[12*20 + 7] = 0.085075; */
/* daa[12*20 + 8] = 0.347092; */
/* daa[12*20 + 9] = 4.051255; */
/* daa[12*20 + 10] = 6.650794; */
/* daa[12*20 + 11] = 0.617549; */
/* daa[13*20 + 0] = 0.155206; */
/* daa[13*20 + 1] = 0.057971; */
/* daa[13*20 + 2] = 0.09816; */
/* daa[13*20 + 3] = 0.020441; */
/* daa[13*20 + 4] = 0.904305; */
/* daa[13*20 + 5] = 0.052719; */
/* daa[13*20 + 6] = 0.0219; */
/* daa[13*20 + 7] = 0.046668; */
/* daa[13*20 + 8] = 0.890005; */
/* daa[13*20 + 9] = 0.844963; */
/* daa[13*20 + 10] = 2.348881; */
/* daa[13*20 + 11] = 0.028372; */
/* daa[13*20 + 12] = 1.671635; */
/* daa[14*20 + 0] = 1.433475; */
/* daa[14*20 + 1] = 0.328393; */
/* daa[14*20 + 2] = 0.173181; */
/* daa[14*20 + 3] = 0.431874; */
/* daa[14*20 + 4] = 0.09902; */
/* daa[14*20 + 5] = 0.592324; */
/* daa[14*20 + 6] = 0.488352; */
/* daa[14*20 + 7] = 0.23865; */
/* daa[14*20 + 8] = 0.462856; */
/* daa[14*20 + 9] = 0.057048; */
/* daa[14*20 + 10] = 0.233532; */
/* daa[14*20 + 11] = 0.387808; */
/* daa[14*20 + 12] = 0.096377; */
/* daa[14*20 + 13] = 0.079912; */
/* daa[15*20 + 0] = 4.887126; */
/* daa[15*20 + 1] = 0.883923; */
/* daa[15*20 + 2] = 4.627163; */
/* daa[15*20 + 3] = 1.122164; */
/* daa[15*20 + 4] = 3.186667; */
/* daa[15*20 + 5] = 1.085947; */
/* daa[15*20 + 6] = 0.569339; */
/* daa[15*20 + 7] = 1.993432; */
/* daa[15*20 + 8] = 0.867972; */
/* daa[15*20 + 9] = 0.070512; */
/* daa[15*20 + 10] = 0.163009; */
/* daa[15*20 + 11] = 0.718913; */
/* daa[15*20 + 12] = 0.301103; */
/* daa[15*20 + 13] = 0.32579; */
/* daa[15*20 + 14] = 1.449582; */
/* daa[16*20 + 0] = 2.030538; */
/* daa[16*20 + 1] = 0.639463; */
/* daa[16*20 + 2] = 2.076294; */
/* daa[16*20 + 3] = 0.377239; */
/* daa[16*20 + 4] = 1.42848; */
/* daa[16*20 + 5] = 0.979403; */
/* daa[16*20 + 6] = 0.647562; */
/* daa[16*20 + 7] = 0.145556; */
/* daa[16*20 + 8] = 0.493329; */
/* daa[16*20 + 9] = 0.973405; */
/* daa[16*20 + 10] = 0.271824; */
/* daa[16*20 + 11] = 1.20033; */
/* daa[16*20 + 12] = 1.659187; */
/* daa[16*20 + 13] = 0.1217; */
/* daa[16*20 + 14] = 0.571399; */
/* daa[16*20 + 15] = 6.641034; */
/* daa[17*20 + 0] = 0.131405; */
/* daa[17*20 + 1] = 0.552911; */
/* daa[17*20 + 2] = 0.079985; */
/* daa[17*20 + 3] = 0.060514; */
/* daa[17*20 + 4] = 0.633662; */
/* daa[17*20 + 5] = 0.21823; */
/* daa[17*20 + 6] = 0.074988; */
/* daa[17*20 + 7] = 0.169114; */
/* daa[17*20 + 8] = 0.847725; */
/* daa[17*20 + 9] = 0.10627; */
/* daa[17*20 + 10] = 0.622044; */
/* daa[17*20 + 11] = 0.060755; */
/* daa[17*20 + 12] = 0.719575; */
/* daa[17*20 + 13] = 3.14824; */
/* daa[17*20 + 14] = 0.077123; */
/* daa[17*20 + 15] = 0.276716; */
/* daa[17*20 + 16] = 0.148883; */
/* daa[18*20 + 0] = 0.165179; */
/* daa[18*20 + 1] = 0.224883; */
/* daa[18*20 + 2] = 0.528334; */
/* daa[18*20 + 3] = 0.121252; */
/* daa[18*20 + 4] = 1.174118; */
/* daa[18*20 + 5] = 0.177062; */
/* daa[18*20 + 6] = 0.074715; */
/* daa[18*20 + 7] = 0.042356; */
/* daa[18*20 + 8] = 5.911187; */
/* daa[18*20 + 9] = 0.192481; */
/* daa[18*20 + 10] = 0.321454; */
/* daa[18*20 + 11] = 0.090556; */
/* daa[18*20 + 12] = 0.406415; */
/* daa[18*20 + 13] = 10.908861; */
/* daa[18*20 + 14] = 0.070752; */
/* daa[18*20 + 15] = 0.328483; */
/* daa[18*20 + 16] = 0.181539; */
/* daa[18*20 + 17] = 3.823886; */
/* daa[19*20 + 0] = 1.78517; */
/* daa[19*20 + 1] = 0.166975; */
/* daa[19*20 + 2] = 0.106482; */
/* daa[19*20 + 3] = 0.041707; */
/* daa[19*20 + 4] = 1.876812; */
/* daa[19*20 + 5] = 0.22421; */
/* daa[19*20 + 6] = 0.247356; */
/* daa[19*20 + 7] = 0.06688; */
/* daa[19*20 + 8] = 0.1436; */
/* daa[19*20 + 9] = 9.60184; */
/* daa[19*20 + 10] = 1.599119; */
/* daa[19*20 + 11] = 0.17319; */
/* daa[19*20 + 12] = 1.645134; */
/* daa[19*20 + 13] = 0.438571; */
/* daa[19*20 + 14] = 0.252486; */
/* daa[19*20 + 15] = 0.105536; */
/* daa[19*20 + 16] = 1.789097; */
/* daa[19*20 + 17] = 0.147951; */
/* daa[19*20 + 18] = 0.200571; */
/* for (i=0; i 2664 (67% of the original 3933 positions)
The species included in the analysis were:
Harpiosquilla harpax [NCBI_TaxID 287944]
Ixodes uriae [NCBI_TaxID 59655]
Heptathela hangzhouensis [NCBI_TaxID 216259]
Triops longicaudatus [NCBI_TaxID 58777]
Gryllotalpa orientalis [NCBI_TaxID 213494]
lepidopsocid RS-2001 [NCBI_TaxID 159971]
Locusta migratoria [NCBI_TaxID 7004]
Drosophila yakuba [NCBI_TaxID 7245]
Ostrinia furnacalis [NCBI_TaxID 93504]
Megabalanus volcano [NCBI_TaxID 266495]
Periplaneta fuliginosa [NCBI_TaxID 36977]
Thermobia domestica [NCBI_TaxID 89055]
Aleurochiton aceris [NCBI_TaxID 266942]
Schizaphis graminum [NCBI_TaxID 13262]
Pteronarcys princeps [NCBI_TaxID 285953]
Aleurodicus dugesii [NCBI_TaxID 30099]
Pollicipes polymerus [NCBI_TaxID 36137]
Gomphiocephalus hodgsoni [NCBI_TaxID 221270]
Habronattus oregonensis [NCBI_TaxID 130930]
Speleonectes tulumensis [NCBI_TaxID 84346]
Hutchinsoniella macracantha [NCBI_TaxID 84335]
Haemaphysalis flava [NCBI_TaxID 181088]
Scutigera coleoptrata [NCBI_TaxID 29022]
Vargula hilgendorfii [NCBI_TaxID 6674]
Tricholepidion gertschi [NCBI_TaxID 89825]
Varroa destructor [NCBI_TaxID 109461]
Bombyx mandarina [NCBI_TaxID 7092]
Thyropygus sp. [NCBI_TaxID 174155]
Tribolium castaneum [NCBI_TaxID 7070]
Pagurus longicarpus [NCBI_TaxID 111067]
Limulus polyphemus [NCBI_TaxID 6850]
Tetrodontophora bielanensis [NCBI_TaxID 48717]
Penaeus monodon [NCBI_TaxID 6687]
Daphnia pulex [NCBI_TaxID 6669]
Apis mellifera [NCBI_TaxID 7469]
Anopheles gambiae [NCBI_TaxID 7165]
The topology used for inferring the model was:
(((Daph_pulex,Trio_longi),((((((Aleu_aceri,Aleu_duges),Schi_grami),lepi_RS_20),
((((Ostr_furna,Bomb_manda),(Dros_yakub,Anop_gambi)),Apis_melli),Trib_casta)),
((Gryl_orien,Locu_migra),(Pter_princ,Peri_fulig))),(Tric_gerts,Ther_domes)),
(Scut_coleo,Thyr_sp),Varg_hilge,Hutc_macra,((((Ixod_uriae,Haem_flava),Varr_destr),
(Habr_orego,Hept_hangz)),Limu_polyp),(Poll_polym,Mega_volca),(Gomp_hodgs,Tetr_biela),
((Pagu_longi,Pena_monod),Harp_harpa),Spel_tulum));
Note this is not the ML topoLOGy but the consensus one (based on morphoLOGical data,
phyLOGenetic reconstruction using nuclear genes, etc). Where relationships are
not clear, a polytomy was introduced (it contains quite a lot of polytomies!).
The model was estimated using (the great and helpful) Ziheng Yang's Paml software package.
A four-categorized gamma distribution was used to account for heterogeneity (alpha
was estimated to be 0.47821). Sites with ambiguity data were taken into account.
If you would like the data related to this matrix, please contact fabascal@uvigo.es.
Federico Abascal (c)2005.
*/
int i,j,naa;
naa = 20;
daa[1*20+ 0] = 0.2; daa[2*20+ 0] = 0.2; daa[2*20+ 1] = 0.2; daa[3*20+ 0] = 0.6;
daa[3*20+ 1] = 4.3; daa[3*20+ 2] = 500.2; daa[4*20+ 0] = 253.5; daa[4*20+ 1] = 35.5;
daa[4*20+ 2] = 98.2; daa[4*20+ 3] = 10.6; daa[5*20+ 0] = 0.2; daa[5*20+ 1] = 154.0;
daa[5*20+ 2] = 261.8; daa[5*20+ 3] = 0.2; daa[5*20+ 4] = 0.2; daa[6*20+ 0] = 0.2;
daa[6*20+ 1] = 0.2; daa[6*20+ 2] = 183.0; daa[6*20+ 3] = 861.8; daa[6*20+ 4] = 0.2;
daa[6*20+ 5] = 261.6; daa[7*20+ 0] = 199.8; daa[7*20+ 1] = 0.2; daa[7*20+ 2] = 120.5;
daa[7*20+ 3] = 12.5; daa[7*20+ 4] = 80.5; daa[7*20+ 5] = 2.6; daa[7*20+ 6] = 43.9;
daa[8*20+ 0] = 0.2; daa[8*20+ 1] = 41.3; daa[8*20+ 2] = 179.5; daa[8*20+ 3] = 0.2;
daa[8*20+ 4] = 12.4; daa[8*20+ 5] = 313.5; daa[8*20+ 6] = 15.2; daa[8*20+ 7] = 0.2;
daa[9*20+ 0] = 25.7; daa[9*20+ 1] = 1.8; daa[9*20+ 2] = 21.3; daa[9*20+ 3] = 6.6;
daa[9*20+ 4] = 63.0; daa[9*20+ 5] = 10.5; daa[9*20+ 6] = 6.8; daa[9*20+ 7] = 2.7;
daa[9*20+ 8] = 0.2; daa[10*20+ 0] = 3.7; daa[10*20+ 1] = 1.8; daa[10*20+ 2] = 12.6;
daa[10*20+ 3] = 1.2; daa[10*20+ 4] = 78.7; daa[10*20+ 5] = 16.3; daa[10*20+ 6] = 1.7;
daa[10*20+ 7] = 1.4; daa[10*20+ 8] = 5.5; daa[10*20+ 9] = 514.5; daa[11*20+ 0] = 0.2;
daa[11*20+ 1] = 208.6; daa[11*20+ 2] = 467.3; daa[11*20+ 3] = 1.7; daa[11*20+ 4] = 0.2;
daa[11*20+ 5] = 349.3; daa[11*20+ 6] = 106.3; daa[11*20+ 7] = 0.2; daa[11*20+ 8] = 0.2;
daa[11*20+ 9] = 3.5; daa[11*20+ 10] = 3.8; daa[12*20+ 0] = 120.6; daa[12*20+ 1] = 5.2;
daa[12*20+ 2] = 78.8; daa[12*20+ 3] = 0.2; daa[12*20+ 4] = 312.3; daa[12*20+ 5] = 67.3;
daa[12*20+ 6] = 0.2; daa[12*20+ 7] = 55.7; daa[12*20+ 8] = 0.2; daa[12*20+ 9] = 514.8;
daa[12*20+ 10] = 885.5; daa[12*20+ 11] = 105.6; daa[13*20+ 0] = 13.1; daa[13*20+ 1] = 4.7;
daa[13*20+ 2] = 19.7; daa[13*20+ 3] = 0.2; daa[13*20+ 4] = 184.1; daa[13*20+ 5] = 0.2;
daa[13*20+ 6] = 0.2; daa[13*20+ 7] = 0.8; daa[13*20+ 8] = 13.8; daa[13*20+ 9] = 117.9;
daa[13*20+ 10] = 262.6; daa[13*20+ 11] = 10.7; daa[13*20+ 12] = 321.6; daa[14*20+ 0] = 49.3;
daa[14*20+ 1] = 0.2; daa[14*20+ 2] = 16.5; daa[14*20+ 3] = 0.2; daa[14*20+ 4] = 0.2;
daa[14*20+ 5] = 39.3; daa[14*20+ 6] = 7.9; daa[14*20+ 7] = 0.2; daa[14*20+ 8] = 0.8;
daa[14*20+ 9] = 0.2; daa[14*20+ 10] = 12.2; daa[14*20+ 11] = 16.8; daa[14*20+ 12] = 5.3;
daa[14*20+ 13] = 14.6; daa[15*20+ 0] = 673.0; daa[15*20+ 1] = 2.7; daa[15*20+ 2] = 398.4;
daa[15*20+ 3] = 44.4; daa[15*20+ 4] = 664.2; daa[15*20+ 5] = 52.4; daa[15*20+ 6] = 31.5;
daa[15*20+ 7] = 226.0; daa[15*20+ 8] = 10.6; daa[15*20+ 9] = 7.2; daa[15*20+ 10] = 8.2;
daa[15*20+ 11] = 144.2; daa[15*20+ 12] = 111.7; daa[15*20+ 13] = 36.1; daa[15*20+ 14] = 86.5;
daa[16*20+ 0] = 243.9; daa[16*20+ 1] = 0.2; daa[16*20+ 2] = 165.9; daa[16*20+ 3] = 0.2;
daa[16*20+ 4] = 182.8; daa[16*20+ 5] = 43.7; daa[16*20+ 6] = 43.4; daa[16*20+ 7] = 0.2;
daa[16*20+ 8] = 18.6; daa[16*20+ 9] = 203.7; daa[16*20+ 10] = 47.8; daa[16*20+ 11] = 69.5;
daa[16*20+ 12] = 288.6; daa[16*20+ 13] = 13.5; daa[16*20+ 14] = 46.8; daa[16*20+ 15] = 660.4;
daa[17*20+ 0] = 0.2; daa[17*20+ 1] = 0.2; daa[17*20+ 2] = 7.7; daa[17*20+ 3] = 0.2;
daa[17*20+ 4] = 21.6; daa[17*20+ 5] = 6.7; daa[17*20+ 6] = 11.0; daa[17*20+ 7] = 1.9;
daa[17*20+ 8] = 0.2; daa[17*20+ 9] = 0.2; daa[17*20+ 10] = 21.1; daa[17*20+ 11] = 16.0;
daa[17*20+ 12] = 70.7; daa[17*20+ 13] = 53.7; daa[17*20+ 14] = 0.2; daa[17*20+ 15] = 2.4;
daa[17*20+ 16] = 0.2; daa[18*20+ 0] = 1.2; daa[18*20+ 1] = 3.9; daa[18*20+ 2] = 251.2;
daa[18*20+ 3] = 0.2; daa[18*20+ 4] = 72.0; daa[18*20+ 5] = 86.7; daa[18*20+ 6] = 7.7;
daa[18*20+ 7] = 8.6; daa[18*20+ 8] = 191.4; daa[18*20+ 9] = 12.3; daa[18*20+ 10] = 19.8;
daa[18*20+ 11] = 117.1; daa[18*20+ 12] = 70.9; daa[18*20+ 13] = 791.6; daa[18*20+ 14] = 18.4;
daa[18*20+ 15] = 30.5; daa[18*20+ 16] = 46.0; daa[18*20+ 17] = 37.7; daa[19*20+ 0] = 339.9;
daa[19*20+ 1] = 0.2; daa[19*20+ 2] = 22.6; daa[19*20+ 3] = 0.2; daa[19*20+ 4] = 350.4;
daa[19*20+ 5] = 0.2; daa[19*20+ 6] = 13.6; daa[19*20+ 7] = 2.6; daa[19*20+ 8] = 0.2;
daa[19*20+ 9] = 1854.5; daa[19*20+ 10] = 84.7; daa[19*20+ 11] = 26.1; daa[19*20+ 12] = 281.3;
daa[19*20+ 13] = 51.9; daa[19*20+ 14] = 31.7; daa[19*20+ 15] = 60.6; daa[19*20+ 16] = 544.1;
daa[19*20+ 17] = 0.2; daa[19*20+ 18] = 1.6;
/* MtArt.old: esta es la MtArt que hice con 26 secuencias (2 outgroups) con una topoLOGia incorrecta
daa[1*20+ 0] = 0.2; daa[2*20+ 0] = 0.2; daa[2*20+ 1] = 8.0; daa[3*20+ 0] = 0.2;
daa[3*20+ 1] = 0.2; daa[3*20+ 2] = 441.7; daa[4*20+ 0] = 287.9; daa[4*20+ 1] = 48.4;
daa[4*20+ 2] = 82.4; daa[4*20+ 3] = 0.2; daa[5*20+ 0] = 0.2; daa[5*20+ 1] = 149.9;
daa[5*20+ 2] = 278.6; daa[5*20+ 3] = 0.2; daa[5*20+ 4] = 21.7; daa[6*20+ 0] = 6.6;
daa[6*20+ 1] = 0.2; daa[6*20+ 2] = 213.9; daa[6*20+ 3] = 760.8; daa[6*20+ 4] = 0.2;
daa[6*20+ 5] = 292.9; daa[7*20+ 0] = 228.2; daa[7*20+ 1] = 0.2; daa[7*20+ 2] = 97.1;
daa[7*20+ 3] = 10.4; daa[7*20+ 4] = 98.4; daa[7*20+ 5] = 4.0; daa[7*20+ 6] = 48.7;
daa[8*20+ 0] = 0.2; daa[8*20+ 1] = 56.7; daa[8*20+ 2] = 156.4; daa[8*20+ 3] = 24.5;
daa[8*20+ 4] = 15.5; daa[8*20+ 5] = 328.6; daa[8*20+ 6] = 7.0; daa[8*20+ 7] = 8.4;
daa[9*20+ 0] = 26.4; daa[9*20+ 1] = 1.6; daa[9*20+ 2] = 40.1; daa[9*20+ 3] = 0.2;
daa[9*20+ 4] = 22.1; daa[9*20+ 5] = 13.8; daa[9*20+ 6] = 0.2; daa[9*20+ 7] = 3.6;
daa[9*20+ 8] = 0.2; daa[10*20+ 0] = 3.4; daa[10*20+ 1] = 0.6; daa[10*20+ 2] = 13.8;
daa[10*20+ 3] = 0.7; daa[10*20+ 4] = 76.9; daa[10*20+ 5] = 12.1; daa[10*20+ 6] = 5.4;
daa[10*20+ 7] = 2.5; daa[10*20+ 8] = 2.9; daa[10*20+ 9] = 542.6; daa[11*20+ 0] = 0.2;
daa[11*20+ 1] = 240.2; daa[11*20+ 2] = 602.8; daa[11*20+ 3] = 35.5; daa[11*20+ 4] = 0.2;
daa[11*20+ 5] = 357.6; daa[11*20+ 6] = 62.6; daa[11*20+ 7] = 0.2; daa[11*20+ 8] = 3.3;
daa[11*20+ 9] = 0.2; daa[11*20+ 10] = 17.5; daa[12*20+ 0] = 119.0; daa[12*20+ 1] = 0.2;
daa[12*20+ 2] = 91.4; daa[12*20+ 3] = 6.4; daa[12*20+ 4] = 332.3; daa[12*20+ 5] = 65.4;
daa[12*20+ 6] = 0.2; daa[12*20+ 7] = 60.4; daa[12*20+ 8] = 2.4; daa[12*20+ 9] = 492.5;
daa[12*20+ 10] = 815.8; daa[12*20+ 11] = 67.3; daa[13*20+ 0] = 8.2; daa[13*20+ 1] = 6.4;
daa[13*20+ 2] = 31.5; daa[13*20+ 3] = 3.4; daa[13*20+ 4] = 174.4; daa[13*20+ 5] = 5.7;
daa[13*20+ 6] = 5.7; daa[13*20+ 7] = 2.1; daa[13*20+ 8] = 11.0; daa[13*20+ 9] = 94.4;
daa[13*20+ 10] = 243.3; daa[13*20+ 11] = 12.3; daa[13*20+ 12] = 357.8; daa[14*20+ 0] = 62.5;
daa[14*20+ 1] = 0.4; daa[14*20+ 2] = 17.5; daa[14*20+ 3] = 0.2; daa[14*20+ 4] = 0.2;
daa[14*20+ 5] = 48.6; daa[14*20+ 6] = 17.7; daa[14*20+ 7] = 2.7; daa[14*20+ 8] = 0.2;
daa[14*20+ 9] = 0.2; daa[14*20+ 10] = 11.2; daa[14*20+ 11] = 21.7; daa[14*20+ 12] = 5.2;
daa[14*20+ 13] = 12.6; daa[15*20+ 0] = 659.0; daa[15*20+ 1] = 5.2; daa[15*20+ 2] = 469.8;
daa[15*20+ 3] = 52.3; daa[15*20+ 4] = 570.7; daa[15*20+ 5] = 47.8; daa[15*20+ 6] = 37.3;
daa[15*20+ 7] = 227.8; daa[15*20+ 8] = 12.7; daa[15*20+ 9] = 12.3; daa[15*20+ 10] = 7.4;
daa[15*20+ 11] = 189.0; daa[15*20+ 12] = 155.3; daa[15*20+ 13] = 43.8; daa[15*20+ 14] = 103.4;
daa[16*20+ 0] = 276.4; daa[16*20+ 1] = 1.6; daa[16*20+ 2] = 175.6; daa[16*20+ 3] = 0.2;
daa[16*20+ 4] = 96.2; daa[16*20+ 5] = 71.4; daa[16*20+ 6] = 37.4; daa[16*20+ 7] = 0.2;
daa[16*20+ 8] = 14.2; daa[16*20+ 9] = 212.5; daa[16*20+ 10] = 38.5; daa[16*20+ 11] = 97.4;
daa[16*20+ 12] = 254.7; daa[16*20+ 13] = 2.1; daa[16*20+ 14] = 41.6; daa[16*20+ 15] = 670.6;
daa[17*20+ 0] = 6.2; daa[17*20+ 1] = 0.2; daa[17*20+ 2] = 0.2; daa[17*20+ 3] = 5.6;
daa[17*20+ 4] = 0.2; daa[17*20+ 5] = 0.2; daa[17*20+ 6] = 3.1; daa[17*20+ 7] = 0.4;
daa[17*20+ 8] = 0.2; daa[17*20+ 9] = 15.2; daa[17*20+ 10] = 11.5; daa[17*20+ 11] = 32.6;
daa[17*20+ 12] = 82.4; daa[17*20+ 13] = 81.9; daa[17*20+ 14] = 0.2; daa[17*20+ 15] = 9.7;
daa[17*20+ 16] = 0.2; daa[18*20+ 0] = 1.6; daa[18*20+ 1] = 7.7; daa[18*20+ 2] = 242.5;
daa[18*20+ 3] = 0.2; daa[18*20+ 4] = 88.0; daa[18*20+ 5] = 93.1; daa[18*20+ 6] = 0.2;
daa[18*20+ 7] = 6.0; daa[18*20+ 8] = 113.7; daa[18*20+ 9] = 22.1; daa[18*20+ 10] = 17.2;
daa[18*20+ 11] = 138.5; daa[18*20+ 12] = 37.6; daa[18*20+ 13] = 770.2; daa[18*20+ 14] = 5.3;
daa[18*20+ 15] = 25.0; daa[18*20+ 16] = 55.5; daa[18*20+ 17] = 69.3; daa[19*20+ 0] = 307.8;
daa[19*20+ 1] = 2.2; daa[19*20+ 2] = 6.9; daa[19*20+ 3] = 0.2; daa[19*20+ 4] = 405.7;
daa[19*20+ 5] = 0.8; daa[19*20+ 6] = 20.2; daa[19*20+ 7] = 5.7; daa[19*20+ 8] = 0.2;
daa[19*20+ 9] = 1687.9; daa[19*20+ 10] = 49.4; daa[19*20+ 11] = 23.4; daa[19*20+ 12] = 329.9;
daa[19*20+ 13] = 86.3; daa[19*20+ 14] = 27.3; daa[19*20+ 15] = 95.0; daa[19*20+ 16] = 443.0;
daa[19*20+ 17] = 2.4; daa[19*20+ 18] = 0.2;
3*/
for (i=0; ins = io->mod->ns;
if(io->datatype == GENERIC) mod->whichmodel = JC69;
if(!mod->invar) For(i,data->crunch_len) data->invar[i] = 0;
dr = (phydbl *)mCalloc( mod->ns,sizeof(phydbl));
di = (phydbl *)mCalloc( mod->ns,sizeof(phydbl));
space = (phydbl *)mCalloc(2*mod->ns,sizeof(phydbl));
if(mod->log_l == YES)
{
mod->l_min = LOG(mod->l_min);
mod->l_max = LOG(mod->l_max);
}
For(i,mod->n_catg) mod->gamma_r_proba->v[i] = (phydbl)1./mod->n_catg;
For(i,mod->n_catg) mod->gamma_r_proba_unscaled->v[i] = (phydbl)i;
For(i,mod->n_catg) mod->gamma_rr->v[i] = (phydbl)i;
For(i,mod->n_catg) mod->gamma_rr_unscaled->v[i] = (phydbl)i;
mod->br_len_multiplier->v = 1.0;
For(i,mod->ns)
{
mod->pi->v[i] = data->b_frq[i];
mod->pi_unscaled->v[i] = mod->pi->v[i] * 100.;
}
if(io->datatype == NT)
{
/* Set the substitution parameters to their default values
when they are not fixed by the user */
if(mod->s_opt->opt_kappa)
{
mod->kappa->v = 4.0;
mod->lambda->v = 1.0;
}
if(mod->s_opt->opt_rr)
{
int i;
For(i,6)
{
mod->rr->v[i] = 1.0;
mod->rr_val->v[i] = 1.0;
}
}
}
if(mod->s_opt->opt_alpha) mod->alpha->v = 1.0;
if(mod->s_opt->opt_pinvar) mod->pinvar->v = 0.2;
if(io->datatype == NT) /* Nucleotides */
{
/* init for nucleotides */
mod->update_eigen = 1;
mod->lambda->v = 1.;
if(mod->whichmodel == JC69)
{
mod->pi->v[0] = mod->pi->v[1] = mod->pi->v[2] = mod->pi->v[3] = .25;
mod->kappa->v = 1.;
mod->s_opt->opt_state_freq = NO;
mod->s_opt->opt_kappa = NO;
mod->s_opt->opt_lambda = NO;
mod->update_eigen = NO;
}
if(mod->whichmodel == K80)
{
mod->pi->v[0] = mod->pi->v[1] = mod->pi->v[2] = mod->pi->v[3] = .25;
mod->s_opt->opt_state_freq = NO;
mod->s_opt->opt_lambda = NO;
mod->update_eigen = NO;
}
if(mod->whichmodel == F81)
{
mod->kappa->v = 1.;
mod->update_eigen = NO;
}
if(mod->whichmodel == F84)
{
aux = ((mod->pi->v[0]+mod->pi->v[2])-(mod->pi->v[1]+mod->pi->v[3]))/(2.*mod->kappa->v);
mod->lambda->v = ((mod->pi->v[1]+mod->pi->v[3]) + aux)/((mod->pi->v[0]+mod->pi->v[2]) - aux);
mod->update_eigen = NO;
}
if(mod->whichmodel == TN93)
{
mod->update_eigen = NO;
if(io->mod->s_opt->opt_kappa) io->mod->s_opt->opt_lambda = 1;
}
if(mod->whichmodel == GTR)
{
mod->kappa->v = 1.;
mod->update_eigen = YES;
io->mod->s_opt->opt_rr = YES;
}
if(mod->whichmodel == CUSTOM)
{
mod->kappa->v = 1.;
mod->update_eigen = YES;
/* io->mod->s_opt->opt_rr = YES; */ /* What if the user decided not to optimise the rates? */
}
if(mod->whichmodel == GTR)
{
mod->custom_mod_string[0] = '0';
mod->custom_mod_string[1] = '1';
mod->custom_mod_string[2] = '2';
mod->custom_mod_string[3] = '3';
mod->custom_mod_string[4] = '4';
mod->custom_mod_string[5] = '5';
Translate_Custom_Mod_String(mod);
}
if(mod->s_opt->user_state_freq)
For(i,4)
{
mod->pi->v[i] = mod->user_b_freq->v[i];
}
if(!mod->use_m4mod) Set_Model_Parameters(mod);
if((mod->whichmodel != GTR) &&
(mod->whichmodel != CUSTOM) &&
(mod->whichmodel != HKY85)) mod->update_eigen = 0;
}
else if(mod->io->datatype == AA)
{
/* init for amino-acids */
/* see comments of PMat_Empirical for details */
/* read pi and Q from file */
/* These initialisations are needed when analysing multiple
* data sets
*/
For(i,mod->ns*mod->ns) mod->qmat->v[i] = .0;
For(i,mod->ns ) mod->pi->v[i] = .0;
switch(mod->whichmodel)
{
case DAYHOFF :
{
Init_Qmat_Dayhoff(mod->qmat->v,mod->pi->v);
if(mod->s_opt->opt_state_freq)
For(i,mod->ns) mod->pi->v[i] = data->b_frq[i];
break;
}
case JTT :
{
Init_Qmat_JTT(mod->qmat->v,mod->pi->v);
if(mod->s_opt->opt_state_freq)
For(i,mod->ns) mod->pi->v[i] = data->b_frq[i];
break;
}
case MTREV :
{
Init_Qmat_MtREV(mod->qmat->v,mod->pi->v);
if(mod->s_opt->opt_state_freq)
For(i,mod->ns) mod->pi->v[i] = data->b_frq[i];
break;
}
case LG :
{
Init_Qmat_LG(mod->qmat->v,mod->pi->v);
if(mod->s_opt->opt_state_freq)
For(i,mod->ns) mod->pi->v[i] = data->b_frq[i];
break;
}
case WAG :
{
Init_Qmat_WAG(mod->qmat->v,mod->pi->v);
if(mod->s_opt->opt_state_freq)
For(i,mod->ns) mod->pi->v[i] = data->b_frq[i];
break;
}
case DCMUT :
{
Init_Qmat_DCMut(mod->qmat->v,mod->pi->v);
if(mod->s_opt->opt_state_freq)
For(i,mod->ns) mod->pi->v[i] = data->b_frq[i];
break;
}
case RTREV :
{
Init_Qmat_RtREV(mod->qmat->v,mod->pi->v);
if(mod->s_opt->opt_state_freq)
For(i,mod->ns) mod->pi->v[i] = data->b_frq[i];
break;
}
case CPREV :
{
Init_Qmat_CpREV(mod->qmat->v,mod->pi->v);
if(mod->s_opt->opt_state_freq)
For(i,mod->ns) mod->pi->v[i] = data->b_frq[i];
break;
}
case VT :
{
Init_Qmat_VT(mod->qmat->v,mod->pi->v);
if(mod->s_opt->opt_state_freq)
For(i,mod->ns) mod->pi->v[i] = data->b_frq[i];
break;
}
case BLOSUM62 :
{
Init_Qmat_Blosum62(mod->qmat->v,mod->pi->v);
if(mod->s_opt->opt_state_freq)
For(i,mod->ns) mod->pi->v[i] = data->b_frq[i];
break;
}
case MTMAM :
{
Init_Qmat_MtMam(mod->qmat->v,mod->pi->v);
if(mod->s_opt->opt_state_freq)
For(i,mod->ns) mod->pi->v[i] = data->b_frq[i];
break;
}
case MTART :
{
Init_Qmat_MtArt(mod->qmat->v,mod->pi->v);
if(mod->s_opt->opt_state_freq)
For(i,mod->ns) mod->pi->v[i] = data->b_frq[i];
break;
}
case HIVW :
{
Init_Qmat_HIVw(mod->qmat->v,mod->pi->v);
if(mod->s_opt->opt_state_freq)
For(i,mod->ns) mod->pi->v[i] = data->b_frq[i];
break;
}
case HIVB :
{
Init_Qmat_HIVb(mod->qmat->v,mod->pi->v);
if(mod->s_opt->opt_state_freq)
For(i,mod->ns) mod->pi->v[i] = data->b_frq[i];
break;
}
case CUSTOMAA :
{
Read_Qmat(mod->qmat->v,mod->pi->v,io->fp_aa_rate_mat);
/* Print_Qmat_AA(mod->qmat->v,mod->pi->v); */
if(mod->s_opt->opt_state_freq)
For(i,mod->ns) mod->pi->v[i] = data->b_frq[i];
break;
}
default : break;
}
/* /\* multiply the nth col of Q by the nth term of pi/100 just as in PAML *\/ */
For(i,mod->ns) For(j,mod->ns) mod->qmat->v[i*mod->ns+j] *= mod->pi->v[j] / 100.0;
/* compute diagonal terms of Q and mean rate mr = l/t */
mod->mr->v= .0;
For (i,mod->ns)
{
sum=.0;
For(j, mod->ns) sum += mod->qmat->v[i*mod->ns+j];
mod->qmat->v[i*mod->ns+i] = -sum;
mod->mr->v += mod->pi->v[i] * sum;
}
/* scale imod->nstantaneous rate matrix so that mu=1 */
For (i,mod->ns*mod->ns) mod->qmat->v[i] /= mod->mr->v;
/* compute eigenvectors/values */
result = 0;
For(i,mod->ns*mod->ns) mod->qmat_buff->v[i] = mod->qmat->v[i];
if(!Eigen(1,mod->qmat_buff->v,mod->eigen->size,mod->eigen->e_val,
mod->eigen->e_val_im,mod->eigen->r_e_vect,
mod->eigen->r_e_vect_im,mod->eigen->space))
{
/* compute inverse(Vr) into Vi */
For (i,mod->ns*mod->ns) mod->eigen->l_e_vect[i] = mod->eigen->r_e_vect[i];
if(!Matinv(mod->eigen->l_e_vect,mod->eigen->size,mod->eigen->size,YES))
{
PhyML_Printf("\n. Err in file %s at line %d.",__FILE__,__LINE__);
Exit("\n");
}
/* compute the diagonal terms of EXP(D) */
For(i,mod->ns) mod->eigen->e_val[i] = (phydbl)EXP(mod->eigen->e_val[i]);
}
else
{
if (result==-1) PhyML_Printf("\n. Eigenvalues/vectors computation does not converge : computation cancelled");
else if (result==1) PhyML_Printf("\n. Complex eigenvalues/vectors : computation cancelled");
}
}
else if(mod->io->datatype == GENERIC)
{
/* Uniform state frequencies */
For(i,mod->ns) mod->pi->v[i] = 1./(phydbl)mod->ns;
mod->kappa->v = 1;
mod->s_opt->opt_state_freq = NO;
mod->s_opt->opt_kappa = NO;
mod->s_opt->opt_lambda = NO;
mod->update_eigen = NO;
}
else
{
PhyML_Printf("\n. Not implemented yet.\n");
PhyML_Printf("\n. Err in file %s at line %d\n",__FILE__,__LINE__);
Warn_And_Exit("");
}
mod->alpha_old->v = mod->alpha->v;
mod->kappa_old->v = mod->kappa->v;
mod->lambda_old->v = mod->lambda->v;
mod->pinvar_old->v = mod->pinvar->v;
Init_Eigen_Struct(mod->eigen);
free(dr);free(di);free(space);
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void Update_Qmat_Generic(phydbl *rr, phydbl *pi, int ns, phydbl *qmat)
{
int i,j;
phydbl sum,mr;
For(i,ns*ns) qmat[i] = .0;
if(rr[(int)(ns*(ns-1)/2)-1] < 0.00001)
{
PhyML_Printf("\n. rr[%d]=%f",(int)(ns*(ns-1)/2)-1,rr[(int)(ns*(ns-1)/2)-1]);
PhyML_Printf("\n. Err in file %s at line %d\n\n",__FILE__,__LINE__);
Warn_And_Exit("");
}
/* PhyML_Printf("\n"); */
/* For(i,(int)(ns*(ns-1)/2)) */
/* { */
/* PhyML_Printf("\n> rr %d = %f",i,rr[i]); */
/* } */
For(i,(int)(ns*(ns-1)/2))
{
rr[i] /= rr[(int)(ns*(ns-1)/2)-1];
}
/* Fill the non-diagonal parts */
For(i,ns)
{
for(j=i+1;j C */ qmat[0*4+1] = (phydbl)(pi[1]);
/* A -> G */ qmat[0*4+2] = (phydbl)(kappa*pi[2]);
/* A -> T */ qmat[0*4+3] = (phydbl)(pi[3]);
/* C -> A */ qmat[1*4+0] = (phydbl)(pi[0]);
/* C -> G */ qmat[1*4+2] = (phydbl)(pi[2]);
/* C -> T */ qmat[1*4+3] = (phydbl)(kappa*pi[3]);
/* G -> A */ qmat[2*4+0] = (phydbl)(kappa*pi[0]);
/* G -> C */ qmat[2*4+1] = (phydbl)(pi[1]);
/* G -> T */ qmat[2*4+3] = (phydbl)(pi[3]);
/* T -> A */ qmat[3*4+0] = (phydbl)(pi[0]);
/* T -> C */ qmat[3*4+1] = (phydbl)(kappa*pi[1]);
/* T -> G */ qmat[3*4+2] = (phydbl)(pi[2]);
qmat[0*4+0] = (phydbl)(-(qmat[0*4+1]+qmat[0*4+2]+qmat[0*4+3]));
qmat[1*4+1] = (phydbl)(-(qmat[1*4+0]+qmat[1*4+2]+qmat[1*4+3]));
qmat[2*4+2] = (phydbl)(-(qmat[2*4+0]+qmat[2*4+1]+qmat[2*4+3]));
qmat[3*4+3] = (phydbl)(-(qmat[3*4+0]+qmat[3*4+1]+qmat[3*4+2]));
/* compute diagonal terms of Q and mean rate mr = l/t */
mr = .0;
For (i,4) mr += pi[i] * (-qmat[i*4+i]);
For(i,16) qmat[i] /= mr;
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void Translate_Custom_Mod_String(model *mod)
{
int i,j;
For(i,6) mod->n_rr_per_cat->v[i] = 0;
mod->n_diff_rr = 0;
For(i,6)
{
For(j,i)
{
if((mod->custom_mod_string[i] == mod->custom_mod_string[j]))
{
break;
}
}
if(i == j)
{
mod->rr_num->v[i] = mod->n_diff_rr;
mod->n_diff_rr++;
}
else
{
mod->rr_num->v[i] = mod->rr_num->v[j];
}
mod->n_rr_per_cat->v[mod->rr_num->v[j]]++;
}
/* PhyML_Printf("\n"); */
/* For(i,6) PhyML_Printf("%d ",mod->rr_param_num[i]); */
/* For(i,mod->n_diff_rr_param) PhyML_Printf("\n. Class %d size %d",i+1,mod->n_rr_param_per_cat[i]); */
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void Set_Model_Parameters(model *mod)
{
phydbl sum;
int i;
if(mod->free_mixt_rates == NO) DiscreteGamma(mod->gamma_r_proba->v,
mod->gamma_rr->v,
mod->alpha->v,
mod->alpha->v,
mod->n_catg,
mod->gamma_median);
else
{
/* /\* // Update class frequencies *\/ */
/* sum = .0; */
/* For(i,mod->n_catg) sum += FABS(mod->gamma_r_proba_unscaled->v[i]); */
/* For(i,mod->n_catg) mod->gamma_r_proba->v[i] = FABS(mod->gamma_r_proba_unscaled->v[i])/sum; */
/* // Update class rates */
/* do */
/* { */
/* sum = .0; */
/* For(i,mod->n_catg) */
/* { */
/* if(mod->gamma_r_proba->v[i] < 0.01) mod->gamma_r_proba->v[i]=0.01; */
/* if(mod->gamma_r_proba->v[i] > 0.99) mod->gamma_r_proba->v[i]=0.99; */
/* sum += mod->gamma_r_proba->v[i]; */
/* } */
/* For(i,mod->n_catg) mod->gamma_r_proba->v[i]/=sum; */
/* } */
/* while((sum > 1.01) || (sum < 0.99)); */
/* sum = .0; */
/* For(i,mod->n_catg) sum += mod->gamma_r_proba->v[i] * FABS(mod->gamma_rr_unscaled->v[i]); */
/* For(i,mod->n_catg) mod->gamma_rr->v[i] = FABS(mod->gamma_rr_unscaled->v[i])/sum; */
//
Qksort(mod->gamma_r_proba_unscaled->v,NULL,0,mod->n_catg-1); // Unscaled class frequencies sorted in increasing order
// Update class frequencies
For(i,mod->n_catg)
{
if(!i)
mod->gamma_r_proba->v[i] =
mod->gamma_r_proba_unscaled->v[i] / (mod->gamma_r_proba_unscaled->v[mod->n_catg-1]) ;
else
mod->gamma_r_proba->v[i] =
(mod->gamma_r_proba_unscaled->v[i] - mod->gamma_r_proba_unscaled->v[i-1]) / (mod->gamma_r_proba_unscaled->v[mod->n_catg-1]) ;
}
// Update class rates
do
{
sum = .0;
For(i,mod->n_catg)
{
if(mod->gamma_r_proba->v[i] < 0.01) mod->gamma_r_proba->v[i]=0.01;
if(mod->gamma_r_proba->v[i] > 0.99) mod->gamma_r_proba->v[i]=0.99;
sum += mod->gamma_r_proba->v[i];
}
For(i,mod->n_catg) mod->gamma_r_proba->v[i]/=sum;
}
while((sum > 1.01) || (sum < 0.99));
sum = .0;
For(i,mod->n_catg) sum += mod->gamma_r_proba->v[i] * FABS(mod->gamma_rr_unscaled->v[i]);
For(i,mod->n_catg) mod->gamma_rr->v[i] = FABS(mod->gamma_rr_unscaled->v[i])/sum;
/* sum = .0; */
/* For(i,mod->n_catg) sum += mod->gamma_r_proba->v[i] * FABS(mod->gamma_rr->v[i]); */
/* printf("\n. sum=%f",sum); */
}
if((mod->io->datatype == NT) && (mod->s_opt->opt_state_freq))
{
sum = .0;
For(i,mod->ns) sum += FABS(mod->pi_unscaled->v[i]);
For(i,mod->ns) mod->pi->v[i] = FABS(mod->pi_unscaled->v[i])/sum;
do
{
sum = .0;
For(i,mod->ns)
{
if(mod->pi->v[i] < 0.01) mod->pi->v[i]=0.01;
if(mod->pi->v[i] > 0.99) mod->pi->v[i]=0.99;
sum += mod->pi->v[i];
}
For(i,mod->ns) mod->pi->v[i]/=sum;
}
while((sum > 1.01) || (sum < 0.99));
}
Update_Eigen(mod);
/* printf("\n. Record %d to %d",mod->mod_num,mod->nextmod?mod->nextmod->mod_num:-1); */
if(mod->nextmod) Record_Model(mod,mod->nextmod);
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void Update_Eigen(model *mod)
{
int result, n_iter;
phydbl scalar;
int i;
if(mod->update_eigen)
{
if(!mod->use_m4mod)
{
if(mod->io->datatype == NT)
{
if(mod->whichmodel == GTR)
Update_Qmat_GTR(mod->rr->v, mod->rr_val->v, mod->rr_num->v, mod->pi->v, mod->qmat->v);
else if(mod->whichmodel == CUSTOM)
Update_Qmat_GTR(mod->rr->v, mod->rr_val->v, mod->rr_num->v, mod->pi->v, mod->qmat->v);
else if(mod->whichmodel == HKY85)
Update_Qmat_HKY(mod->kappa->v, mod->pi->v, mod->qmat->v);
else /* Any other nucleotide-based model */
Update_Qmat_HKY(mod->kappa->v, mod->pi->v, mod->qmat->v);
}
}
else
{
M4_Update_Qmat(mod->m4mod,mod);
}
scalar = 1.0;
n_iter = 0;
result = 0;
For(i,mod->ns*mod->ns) mod->qmat_buff->v[i] = mod->qmat->v[i];
/* compute eigenvectors/values */
/* if(!EigenRealGeneral(mod->eigen->size,mod->qmat,mod->eigen->e_val, */
/* mod->eigen->e_val_im, mod->eigen->r_e_vect, */
/* mod->eigen->space_int,mod->eigen->space)) */
if(!Eigen(1,mod->qmat_buff->v,mod->eigen->size,mod->eigen->e_val,
mod->eigen->e_val_im,mod->eigen->r_e_vect,
mod->eigen->r_e_vect_im,mod->eigen->space))
{
/* compute inverse(Vr) into Vi */
For (i,mod->ns*mod->ns) mod->eigen->l_e_vect[i] = mod->eigen->r_e_vect[i];
while(!Matinv(mod->eigen->l_e_vect, mod->eigen->size, mod->eigen->size,YES))
{
PhyML_Printf("\n. Trying Q<-Q*scalar and then Root<-Root/scalar to fix this...\n");
scalar += scalar / 3.;
For(i,mod->eigen->size*mod->eigen->size) mod->qmat_buff->v[i] = mod->qmat->v[i];
For(i,mod->eigen->size*mod->eigen->size) mod->qmat_buff->v[i] *= scalar;
result = Eigen(1,mod->qmat_buff->v,mod->eigen->size,mod->eigen->e_val,
mod->eigen->e_val_im,mod->eigen->r_e_vect,
mod->eigen->r_e_vect_im,mod->eigen->space);
if (result == -1)
Exit("\n. Eigenvalues/vectors computation did not converge: computation cancelled\n");
else if (result == 1)
Exit("\n. Complex eigenvalues/vectors: computation cancelled\n");
For (i,mod->eigen->size*mod->eigen->size) mod->eigen->l_e_vect[i] = mod->eigen->r_e_vect[i];
n_iter++;
if(n_iter > 100) Exit("\n. Cannot work out eigen vectors\n");
};
For(i,mod->eigen->size) mod->eigen->e_val[i] /= scalar;
/* compute the diagonal terms of EXP(D) */
For(i,mod->ns) mod->eigen->e_val[i] = (phydbl)EXP(mod->eigen->e_val[i]);
/* int j; */
/* double *U,*V,*R; */
/* double *expt; */
/* double *uexpt; */
/* int n; */
/* expt = mod->eigen->e_val_im; */
/* uexpt = mod->eigen->r_e_vect_im; */
/* U = mod->eigen->r_e_vect; */
/* V = mod->eigen->l_e_vect; */
/* R = mod->eigen->e_val; /\* exponential of the eigen value matrix *\/ */
/* n = mod->ns; */
/* PhyML_Printf("\n"); */
/* PhyML_Printf("\n. Q\n"); */
/* For(i,n) { For(j,n) PhyML_Printf("%7.3f ",mod->eigen->q[i*n+j]); PhyML_Printf("\n"); } */
/* PhyML_Printf("\n. U\n"); */
/* For(i,n) { For(j,n) PhyML_Printf("%7.3f ",U[i*n+j]); PhyML_Printf("\n"); } */
/* PhyML_Printf("\n"); */
/* PhyML_Printf("\n. V\n"); */
/* For(i,n) { For(j,n) PhyML_Printf("%7.3f ",V[i*n+j]); PhyML_Printf("\n"); } */
/* PhyML_Printf("\n"); */
/* PhyML_Printf("\n. Eigen\n"); */
/* For(i,n) PhyML_Printf("%E ",expt[i]); */
/* PhyML_Printf("\n"); */
/* Exit("\n"); */
}
else
{
PhyML_Printf("\n. Eigenvalues/vectors computation does not converge : computation cancelled");
Warn_And_Exit("\n");
}
}
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void Switch_From_M4mod_To_Mod(model *mod)
{
int i;
mod->use_m4mod = 0;
mod->ns = mod->m4mod->n_o;
For(i,mod->ns) mod->pi->v[i] = mod->m4mod->o_fq[i];
mod->eigen->size = mod->ns;
mod->update_eigen = 1;
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void Switch_From_Mod_To_M4mod(model *mod)
{
int i;
mod->use_m4mod = 1;
mod->ns = mod->m4mod->n_o * mod->m4mod->n_h;
For(i,mod->ns) mod->pi->v[i] = mod->m4mod->o_fq[i%mod->m4mod->n_o] * mod->m4mod->h_fq[i/mod->m4mod->n_o];
mod->eigen->size = mod->ns;
mod->update_eigen = 1;
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
phydbl General_Dist(phydbl *F, model *mod, eigen *eigen_struct)
{
phydbl *pi,*mod_pi;
int i,j,k;
phydbl dist;
phydbl sum;
phydbl sum_ev;
phydbl *F_phydbl;
/* TO DO : call eigen decomposition function for all nt models */
F_phydbl = (phydbl *)mCalloc(eigen_struct->size*eigen_struct->size,sizeof(phydbl));
pi = (phydbl *)mCalloc(eigen_struct->size,sizeof(phydbl));
mod_pi = (phydbl *)mCalloc(eigen_struct->size,sizeof(phydbl));
For(i,mod->ns) mod_pi[i] = mod->pi->v[i];
sum = .0;
For(i,eigen_struct->size)
{
For(j,eigen_struct->size)
{
pi[i] += (F[eigen_struct->size*i+j] + F[eigen_struct->size*j+i])/2.;
sum += F[eigen_struct->size*i+j];
}
}
Make_Symmetric(&F,eigen_struct->size);
Divide_Mat_By_Vect(&F,mod->pi->v,eigen_struct->size);
/* Eigen decomposition of pi^{-1} x F */
For(i,eigen_struct->size) For(j,eigen_struct->size) F_phydbl[eigen_struct->size*i+j] = F[eigen_struct->size*i+j];
if(Eigen(1,F_phydbl,mod->eigen->size,mod->eigen->e_val,
mod->eigen->e_val_im,mod->eigen->r_e_vect,
mod->eigen->r_e_vect_im,mod->eigen->space))
{
For(i,mod->ns) mod->pi->v[i] = mod_pi[i];
Update_Qmat_GTR(mod->rr->v, mod->rr_val->v, mod->rr_num->v, mod->pi->v, mod->qmat->v);
Free(pi);
Free(mod_pi);
return -1.;
}
/* Get the left eigen vector of pi^{-1} x F */
For(i,eigen_struct->size*eigen_struct->size) eigen_struct->l_e_vect[i] = eigen_struct->r_e_vect[i];
if(!Matinv(eigen_struct->l_e_vect,eigen_struct->size,eigen_struct->size,YES)<0)
{
For(i,mod->ns) mod->pi->v[i] = mod_pi[i];
Update_Qmat_GTR(mod->rr->v, mod->rr_val->v, mod->rr_num->v, mod->pi->v, mod->qmat->v);
Free(pi);
Free(mod_pi);
return -1.;
}
/* LOG of eigen values */
For(i,eigen_struct->size)
{
/* if(eigen_struct->e_val[i] < 0.0) eigen_struct->e_val[i] = 0.0001; */
eigen_struct->e_val[i] = (phydbl)LOG(eigen_struct->e_val[i]);
}
/* Matrix multiplications LOG(pi^{-1} x F) */
For(i,eigen_struct->size) For(j,eigen_struct->size)
eigen_struct->r_e_vect[eigen_struct->size*i+j] =
eigen_struct->r_e_vect[eigen_struct->size*i+j] *
eigen_struct->e_val[j];
For(i,eigen_struct->size) For(j,eigen_struct->size) F[eigen_struct->size*i+j] = .0;
For(i,eigen_struct->size) For(j,eigen_struct->size) For(k,eigen_struct->size)
F[eigen_struct->size*i+j] += eigen_struct->r_e_vect[eigen_struct->size*i+k] * eigen_struct->l_e_vect[eigen_struct->size*k+j];
/* Trace */
dist = .0;
For(i,eigen_struct->size) dist+=F[eigen_struct->size*i+i];
sum_ev = .0;
For(i,mod->ns) sum_ev += mod->eigen->e_val[i];
/* dist /= sum_ev; */
dist /= -4.;
/* For(i,mod->ns) mod->pi->v[i] = mod_pi[i]; */
/* Update_Qmat_GTR(mod); */
Free(pi);
Free(mod_pi);
Free(F_phydbl);
if(isnan(dist)) return -1.;
return dist;
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
phydbl GTR_Dist(phydbl *F, phydbl alpha, eigen *eigen_struct)
{
phydbl *pi;
int i,j,k;
phydbl dist;
phydbl sum;
phydbl *F_phydbl;
pi = (phydbl *)mCalloc(eigen_struct->size,sizeof(phydbl));
F_phydbl = (phydbl *)mCalloc(eigen_struct->size*eigen_struct->size,sizeof(phydbl));
/* /\* Waddell and Steel's example *\/ */
/* F[4*0+0] = 1415./4898.; F[4*0+1] = 8./4898.; F[4*0+2] = 55./4898.; F[4*0+3] = 2./4898.; */
/* F[4*1+0] = 4./4898.; F[4*1+1] = 1371./4898.; F[4*1+2] = 1./4898.; F[4*1+3] = 144./4898.; */
/* F[4*2+0] = 73./4898.; F[4*2+1] = 0./4898.; F[4*2+2] = 578./4898.; F[4*2+3] = 0./4898.; */
/* F[4*3+0] = 3./4898.; F[4*3+1] = 117./4898.; F[4*3+2] = 1./4898.; F[4*3+3] = 1126./4898.; */
For(i,eigen_struct->size)
{
For(j,eigen_struct->size)
{
pi[i] += (F[eigen_struct->size*i+j] + F[eigen_struct->size*j+i])/2.;
sum += F[eigen_struct->size*i+j];
}
}
/* /\* Jukes and Cantor correction *\/ */
/* sum = .0; */
/* For(i,eigen_struct->size) sum += F[eigen_struct->size*i+i]; */
/* sum = 1.-sum; */
/* For(i,eigen_struct->size*eigen_struct->size) F[i] = sum/12.; */
/* For(i,eigen_struct->size) F[eigen_struct->size*i+i] = (1.-sum)/4.; */
/* For(i,eigen_struct->size) pi[i] = 1./(phydbl)eigen_struct->size; */
Make_Symmetric(&F,eigen_struct->size);
Divide_Mat_By_Vect(&F,pi,eigen_struct->size);
/* Eigen decomposition of pi^{-1} x F */
For(i,eigen_struct->size) For(j,eigen_struct->size) F_phydbl[eigen_struct->size*i+j] = F[eigen_struct->size*i+j];
if(Eigen(1,F_phydbl,eigen_struct->size,eigen_struct->e_val,
eigen_struct->e_val_im,eigen_struct->r_e_vect,
eigen_struct->r_e_vect_im,eigen_struct->space))
{
Free(pi);
return -1.;
}
/* Get the left eigen vector of pi^{-1} x F */
For(i,eigen_struct->size*eigen_struct->size) eigen_struct->l_e_vect[i] = eigen_struct->r_e_vect[i];
if(!Matinv(eigen_struct->l_e_vect,eigen_struct->size,eigen_struct->size,YES)<0) {Free(pi); return -1.;}
/* Equation (3) + inverse of the moment generating function for the gamma distribution (see Waddell & Steel, 1997) */
For(i,eigen_struct->size)
{
if(eigen_struct->e_val[i] < 0.0)
{
eigen_struct->e_val[i] = 0.0001;
}
if(alpha < .0)
eigen_struct->e_val[i] = (phydbl)LOG(eigen_struct->e_val[i]);
else
eigen_struct->e_val[i] = alpha * (1. - (phydbl)POW(eigen_struct->e_val[i],-1./alpha));
}
/* Matrix multiplications pi x LOG(pi^{-1} x F) */
For(i,eigen_struct->size) For(j,eigen_struct->size)
eigen_struct->r_e_vect[eigen_struct->size*i+j] =
eigen_struct->r_e_vect[eigen_struct->size*i+j] * eigen_struct->e_val[j];
For(i,eigen_struct->size) For(j,eigen_struct->size) F[eigen_struct->size*i+j] = .0;
For(i,eigen_struct->size) For(j,eigen_struct->size) For(k,eigen_struct->size)
F[eigen_struct->size*i+j] += eigen_struct->r_e_vect[eigen_struct->size*i+k] * eigen_struct->l_e_vect[eigen_struct->size*k+j];
For(i,eigen_struct->size) For(j,eigen_struct->size) F[eigen_struct->size*i+j] *= pi[i];
/* Trace */
dist = .0;
For(i,eigen_struct->size) dist-=F[eigen_struct->size*i+i];
/* PhyML_Printf("\nDIST = %f\n",dist); Exit("\n"); */
Free(pi);
Free(F_phydbl);
if(isnan(dist)) return -1.;
return dist;
}
phyml-20120412/src/draw.h 0000644 0001750 0001750 00000002254 11637265506 011734 0000000 0000000 #include
#ifndef DRAW_H
#define DRAW_H
#include "utilities.h"
void DR_Dist_To_Root_Pre(t_node *a, t_node *d, t_edge *b, t_tree *tree);
void DR_Dist_To_Root(t_node *n_root, t_tree *tree);
void DR_Get_X_Coord_Pre(t_node *a, t_node *d, t_edge *b, tdraw *w, int fixed_tips, t_tree *tree);
void DR_Get_X_Coord(int fixed_tips, tdraw *w, t_tree *tree);
tdraw *DR_Make_Tdraw_Struct(t_tree *tree);
void DR_Init_Tdraw_Struct(tdraw *d);
void DR_Get_Tree_Box_Width(tdraw *w, t_tree *tree);
void DR_Get_Y_Coord_Post(t_node *a, t_node *d, t_edge *b, phydbl *next_y_slot, int fixed_tips, tdraw *w, t_tree *tree);
void DR_Get_Y_Coord(int fixed_tips, tdraw *w, t_tree *tree);
void DR_Get_Tree_Coord(t_tree *tree);
phydbl DR_Get_Max_Dist_To_Root(t_tree *tree);
void DR_Print_Tree_Postscript(int tree_num, int render_name,FILE *fp, t_tree *tree);
void DR_Print_Tree_Postscript_Pre(t_node *a, t_node *d, int render_name, FILE *fp, tdraw *w, t_tree *tree);
void DR_Print_Postscript_EOF(FILE *fp);
void DR_Print_Postscript_Header(int n_pages, FILE *fp);
void DR_Get_Tree_Coord_Scaled(tdraw *w, t_tree *tree);
void DR_Get_Cdf_Mat(t_tree *tree);
void DR_Draw_Tree(char *file_name, t_tree *tree);
#endif
phyml-20120412/src/xml.h 0000644 0001750 0001750 00000002343 11741176422 011570 0000000 0000000 #include
#ifndef XML_H
#define XML_H
#include "utilities.h"
#define T_MAX_XML_TAG 64
typedef struct __XML_node {
struct __XML_attr *attr; // Pointer to the first element of a list of attributes
int n_attr; // Number of attributes
struct __XML_node *next; // Next sibling
struct __XML_node *prev; // Previous sibling
struct __XML_node *parent; // Parent of this node
struct __XML_node *child; // Child of this node
char *id;
char *name;
char *value;
}xml_node;
typedef struct __XML_attr {
char *name;
char *value;
struct __XML_attr *next; // Next attribute
struct __XML_attr *prev; // Previous attribute
}xml_attr;
void XML_Load_File(FILE *fp, xml_node *top);
int XML_Add_Character(int c, char **bufptr, char **buffer, int *bufsize);
int XML_Parse_Element(FILE *fp, xml_node *n);
xml_node *XML_New_Node(xml_node *parent, char *name);
int XML_Set_Attribute(xml_node *n, char *attr_name, char *attr_value);
xml_attr *XML_Make_Attribute(xml_attr *prev, char *attr_name, char *attr_value);
void XML_Make_Node_Id(xml_node *n, char *id);
int XML_Set_Node_Id(xml_node *n, char *id);
int XML_Set_Node_Value(xml_node *n, char *val);
void XML_Make_Node_Value(xml_node *n, char *val);
#endif
phyml-20120412/src/Makefile.am 0000644 0001750 0001750 00000012522 11741250012 012637 0000000 0000000
DEFS = $(REVISION)
if WANT_PHYTIME
bin_PROGRAMS = phytime
PROG = PHYTIME
else
if WANT_PHYCONT
bin_PROGRAMS = phycont
PROG = PHYCONT
else
if WANT_PART
bin_PROGRAMS = part
PROG = PART
else
if WANT_RWRAP
PROG = RWRAP
else
if WANT_TIPORDER
bin_PROGRAMS = tiporder
PROG = TIPORDER
else
if WANT_M4
bin_PROGRAMS = m4
PROG = M4
else
if WANT_RF
bin_PROGRAMS = rf
PROG = RF
else
if WANT_MPI
bin_PROGRAMS = phyml-mpi
PROG = PHYML
else
if WANT_TEST
bin_PROGRAMS = test
PROG = TEST
else
bin_PROGRAMS = phyml
PROG = PHYML
endif
endif
endif
endif
endif
endif
endif
endif
endif
if WANT_PHYTIME
phytime_SOURCES = main.c \
utilities.c utilities.h\
optimiz.c optimiz.h\
lk.c lk.h\
bionj.c bionj.h\
models.c models.h\
free.c free.h\
help.c help.h\
simu.c simu.h\
eigen.c eigen.h\
pars.c pars.h\
alrt.c alrt.h\
interface.c interface.h\
cl.c cl.h\
spr.c spr.h\
times.c times.h\
m4.c m4.h\
draw.c draw.h\
rates.c rates.h\
mcmc.c mcmc.h\
stats.c stats.h\
mg.c mg.h\
tiporder.c tiporder.h
phytime_LDADD = -lm
else
if WANT_PHYCONT
phycont_SOURCES = main.c \
utilities.c utilities.h\
optimiz.c optimiz.h\
lk.c lk.h\
bionj.c bionj.h\
models.c models.h\
free.c free.h\
help.c help.h\
simu.c simu.h\
eigen.c eigen.h\
pars.c pars.h\
alrt.c alrt.h\
interface.c interface.h\
cl.c cl.h\
spr.c spr.h\
times.c times.h\
m4.c m4.h\
draw.c draw.h\
rates.c rates.h\
mcmc.c mcmc.h\
stats.c stats.h\
mg.c mg.h\
tiporder.c tiporder.h
# continuous.c continuous.h
phycont_LDADD = -lm
else
# if WANT_RWRAP
# lib_LTLIBRARIES = librwrap.la
# librwrap_la_SOURCES = main.c \
# utilities.c utilities.h\
# optimiz.c optimiz.h\
# lk.c lk.h\
# bionj.c bionj.h\
# models.c models.h\
# free.c free.h\
# help.c help.h\
# simu.c simu.h\
# eigen.c eigen.h\
# pars.c pars.h\
# alrt.c alrt.h\
# interface.c interface.h\
# cl.c cl.h\
# mg.c mg.h\
# spr.c spr.h\
# m4.c m4.h\
# draw.c draw.h\
# mcmc.c mcmc.h\
# stats.c stats.h\
# times.c times.h\
# tiporder.c tiporder.h\
# rates.c rates.h\
# rwrapper.c rwrapper.h
# librwrap_la_LIBADD = -lm
# librwrap_la_LDFLAGS = -I/Library/Frameworks/R.framework/Resources/include -I/Library/Frameworks/R.framework/Resources/include/i386 -I/usr/local/include -flat_namespace -undefined suppress -shared -module
# librwrap_la_CFLAGS=-std=gnu99 -fPIC
# else
if WANT_PART
part_SOURCES = main.c \
utilities.c utilities.h\
optimiz.c optimiz.h\
lk.c lk.h\
bionj.c bionj.h\
models.c models.h\
free.c free.h\
help.c help.h\
simu.c simu.h\
eigen.c eigen.h\
pars.c pars.h\
alrt.c alrt.h\
interface.c interface.h\
cl.c cl.h\
mg.c mg.h\
spr.c spr.h\
m4.c m4.h\
draw.c draw.h\
stats.c stats.h\
tiporder.c tiporder.h
part_LDADD = -lm
else
if WANT_TIPORDER
tiporder_SOURCES = main.c \
utilities.c utilities.h\
optimiz.c optimiz.h\
lk.c lk.h\
bionj.c bionj.h\
models.c models.h\
free.c free.h\
help.c help.h\
simu.c simu.h\
eigen.c eigen.h\
pars.c pars.h\
alrt.c alrt.h\
interface.c interface.h\
cl.c cl.h\
mg.c mg.h\
times.c times.h\
mcmc.c mcmc.h\
rates.c rates.h\
spr.c spr.h\
m4.c m4.h\
draw.c draw.h\
stats.c stats.h\
tiporder.c tiporder.h
tiporder_LDADD = -lm
else
if WANT_M4
m4_SOURCES = main.c \
utilities.c utilities.h\
optimiz.c optimiz.h\
lk.c lk.h\
bionj.c bionj.h\
models.c models.h\
free.c free.h\
help.c help.h\
simu.c simu.h\
eigen.c eigen.h\
pars.c pars.h\
alrt.c alrt.h\
interface.c interface.h\
cl.c cl.h\
mg.c mg.h\
times.c times.h\
mcmc.c mcmc.h\
rates.c rates.h\
spr.c spr.h\
draw.c draw.h\
stats.c stats.h\
tiporder.c tiporder.h\
m4.c m4.h
m4_LDADD = -lm
else
if WANT_RF
rf_SOURCES = main.c \
utilities.c utilities.h\
optimiz.c optimiz.h\
lk.c lk.h\
bionj.c bionj.h\
models.c models.h\
free.c free.h\
help.c help.h\
simu.c simu.h\
eigen.c eigen.h\
pars.c pars.h\
alrt.c alrt.h\
interface.c interface.h\
cl.c cl.h\
mg.c mg.h\
times.c times.h\
mcmc.c mcmc.h\
rates.c rates.h\
spr.c spr.h\
draw.c draw.h\
stats.c stats.h\
tiporder.c tiporder.h\
m4.c m4.h
rf_LDADD = -lm
else
if WANT_MPI
phyml_mpi_SOURCES = main.c \
utilities.c utilities.h\
optimiz.c optimiz.h\
lk.c lk.h\
bionj.c bionj.h\
models.c models.h\
free.c free.h\
help.c help.h\
simu.c simu.h\
eigen.c eigen.h\
pars.c pars.h\
alrt.c alrt.h\
interface.c interface.h\
cl.c cl.h\
spr.c spr.h\
draw.c draw.h\
mpi_boot.c mpi_boot.h\
stats.c stats.h\
rates.c rates.h\
mcmc.c mcmc.h\
times.c times.h\
tiporder.c tiporder.h\
mg.c mg.h\
m4.c m4.h\
xml.c xml.h
phyml_mpi_LDADD = -lm
else
if WANT_TEST
test_SOURCES = main.c \
utilities.c utilities.h\
optimiz.c optimiz.h\
lk.c lk.h\
bionj.c bionj.h\
models.c models.h\
free.c free.h\
help.c help.h\
simu.c simu.h\
eigen.c eigen.h\
pars.c pars.h\
alrt.c alrt.h\
interface.c interface.h\
cl.c cl.h\
spr.c spr.h\
draw.c draw.h\
stats.c stats.h\
rates.c rates.h\
mcmc.c mcmc.h\
times.c times.h\
tiporder.c tiporder.h\
mg.c mg.h\
m4.c m4.h\
xml.c xml.h
test_LDADD = -lm
else
phyml_SOURCES = main.c \
utilities.c utilities.h\
optimiz.c optimiz.h\
lk.c lk.h\
bionj.c bionj.h\
models.c models.h\
free.c free.h\
help.c help.h\
simu.c simu.h\
eigen.c eigen.h\
pars.c pars.h\
alrt.c alrt.h\
interface.c interface.h\
cl.c cl.h\
spr.c spr.h\
draw.c draw.h\
stats.c stats.h\
rates.c rates.h\
mcmc.c mcmc.h\
times.c times.h\
tiporder.c tiporder.h\
mg.c mg.h\
m4.c m4.h
phyml_LDADD = -lm
endif
endif
endif
endif
endif
endif
endif
endif
# all-am: intro $(bin_PROGRAMS)$(EXEEXT)
all-am: intro $(bin_PROGRAMS)
@echo ""
@echo "Done."
intro:
@echo ""
@echo ""
@echo ":: Building [$(bin_PROGRAMS)]. Version $(VERSION) ::"
@echo ""
@echo ""
phyml-20120412/src/simu.c 0000644 0001750 0001750 00000053411 11736700335 011742 0000000 0000000 /*
PHYML : a program that computes maximum likelihood phylogenies from
DNA or AA homologous sequences
Copyright (C) Stephane Guindon. Oct 2003 onward
All parts of the source except where indicated are distributed under
the GNU public licence. See http://www.opensource.org for details.
*/
#include "simu.h"
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void Simu_Loop(t_tree *tree)
{
phydbl lk_old;
phydbl ori_catg;
int ori_print;
tree->both_sides = 0;
Lk(tree);
if((tree->mod->s_opt->print) && (!tree->io->quiet)) PhyML_Printf("\n. Refining the input tree...\n");
ori_catg = tree->mod->n_catg;
ori_print = tree->mod->s_opt->print;
tree->mod->n_catg = MIN(2,ori_catg);
tree->mod->s_opt->print = NO;
Optimiz_All_Free_Param(tree,(tree->io->quiet)?(0):(tree->mod->s_opt->print));
tree->best_pars = 1E+8;
tree->mod->s_opt->spr_pars = 0;
tree->mod->s_opt->quickdirty = 0;
tree->best_lnL = tree->c_lnL;
tree->mod->s_opt->max_delta_lnL_spr = 0.;
tree->mod->s_opt->br_len_in_spr = 1;
tree->mod->s_opt->max_depth_path = 2*tree->n_otu-3;
tree->mod->s_opt->spr_lnL = NO;
do
{
lk_old = tree->c_lnL;
Speed_Spr(tree,1);
if((tree->n_improvements < 20) ||
(tree->max_spr_depth < 5) ||
(FABS(lk_old-tree->c_lnL) < 1.)) break;
}while(1);
tree->mod->n_catg = ori_catg;
tree->mod->s_opt->print = ori_print;
if((tree->mod->s_opt->print) && (!tree->io->quiet)) PhyML_Printf("\n. Maximizing likelihood (using NNI moves)...\n");
int n_tot_moves = 0;
do
{
lk_old = tree->c_lnL;
Optimiz_All_Free_Param(tree,(tree->io->quiet)?(0):(tree->mod->s_opt->print));
n_tot_moves = Simu(tree,10);
if(!n_tot_moves) break;
}
while(tree->c_lnL > lk_old + tree->mod->s_opt->min_diff_lk_global);
do
{
Round_Optimize(tree,tree->data,ROUND_MAX);
if(!Check_NNI_Five_Branches(tree)) break;
}while(1);
/*****************************/
if((tree->mod->s_opt->print) && (!tree->io->quiet)) PhyML_Printf("\n");
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
int Simu(t_tree *tree, int n_step_max)
{
phydbl old_loglk,n_iter,lambda;
int i,n_neg,n_tested,n_without_swap,n_tot_swap,step,it_lim_without_swap;
t_edge **sorted_b,**tested_b;
int opt_free_param;
int recurr;
sorted_b = (t_edge **)mCalloc(tree->n_otu-3,sizeof(t_edge *));
tested_b = (t_edge **)mCalloc(tree->n_otu-3,sizeof(t_edge *));
old_loglk = UNLIKELY;
tree->c_lnL = UNLIKELY;
n_iter = 1.0;
/* it_lim_without_swap = (tree->mod->invar)?(5):(2); */
it_lim_without_swap = (tree->mod->invar)?(1):(1);
n_tested = 0;
n_without_swap = 0;
step = 0;
lambda = .75;
n_tot_swap = 0;
opt_free_param = 0;
recurr = 0;
Update_Dirs(tree);
if(tree->lock_topo)
{
PhyML_Printf("\n. The tree topology is locked.");
PhyML_Printf("\n. Err in file %s at line %d\n",__FILE__,__LINE__);
Warn_And_Exit("");
}
do
{
++step;
if(n_tested || step == 1) tree->update_alias_subpatt = YES;
old_loglk = tree->c_lnL;
tree->both_sides = 1;
Lk(tree);
tree->update_alias_subpatt = NO;
if(tree->c_lnL < old_loglk)
{
if((tree->mod->s_opt->print) && (!tree->io->quiet)) PhyML_Printf("\n\n. Moving backward\n");
if(!Mov_Backward_Topo_Bl(tree,old_loglk,tested_b,n_tested))
Exit("\n. Err: mov_back failed\n");
if(!tree->n_swap) n_neg = 0;
For(i,2*tree->n_otu-3) tree->t_edges[i]->l_old = tree->t_edges[i]->l;
tree->both_sides = 1;
Lk(tree);
}
if(step > n_step_max) break;
if(tree->io->print_trace)
{
PhyML_Fprintf(tree->io->fp_out_trace,"[%f]%s\n",tree->c_lnL,Write_Tree(tree,NO)); fflush(tree->io->fp_out_trace);
if(tree->io->print_site_lnl) Print_Site_Lk(tree,tree->io->fp_out_lk); fflush(tree->io->fp_out_lk);
}
if((tree->mod->s_opt->print) && (!tree->io->quiet)) Print_Lk(tree,"[Topology ]");
/* if(((tree->c_lnL > old_loglk) && (FABS(old_loglk-tree->c_lnL) < tree->mod->s_opt->min_diff_lk_global)) || (n_without_swap > it_lim_without_swap)) break; */
if((FABS(old_loglk-tree->c_lnL) < tree->mod->s_opt->min_diff_lk_global) || (n_without_swap > it_lim_without_swap)) break;
Fill_Dir_Table(tree);
Fix_All(tree);
n_neg = 0;
For(i,2*tree->n_otu-3)
if((!tree->t_edges[i]->left->tax) &&
(!tree->t_edges[i]->rght->tax))
NNI(tree,tree->t_edges[i],0);
Select_Edges_To_Swap(tree,sorted_b,&n_neg);
Sort_Edges_NNI_Score(tree,sorted_b,n_neg);
Optimiz_Ext_Br(tree);
Update_Bl(tree,lambda);
n_tested = 0;
For(i,(int)CEIL((phydbl)n_neg*(lambda)))
tested_b[n_tested++] = sorted_b[i];
Make_N_Swap(tree,tested_b,0,n_tested);
if((tree->mod->s_opt->print) && (!tree->io->quiet)) PhyML_Printf("[# nnis=%3d]",n_tested);
n_tot_swap += n_tested;
if(n_tested > 0) n_without_swap = 0;
else n_without_swap++;
n_iter+=1.0;
}
while(1);
/* Round_Optimize(tree,tree->data); */
Free(sorted_b);
Free(tested_b);
return n_tot_swap;
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void Simu_Pars(t_tree *tree, int n_step_max)
{
phydbl old_pars,n_iter,lambda;
int i,n_neg,n_tested,n_without_swap,n_tot_swap,step;
t_edge **sorted_b,**tested_b;
int each;
sorted_b = (t_edge **)mCalloc(tree->n_otu-3,sizeof(t_edge *));
tested_b = (t_edge **)mCalloc(tree->n_otu-3,sizeof(t_edge *));
old_pars = 0;
tree->c_pars = 0;
n_iter = 1.0;
n_tested = 0;
n_without_swap = 0;
step = 0;
each = 4;
lambda = .75;
n_tot_swap = 0;
Update_Dirs(tree);
if((tree->mod->s_opt->print) && (!tree->io->quiet)) PhyML_Printf("\n. Starting simultaneous NNI moves (parsimony criterion)...\n");
do
{
++step;
if(step > n_step_max) break;
each--;
tree->both_sides = 1;
Pars(tree);
if((tree->mod->s_opt->print) && (!tree->io->quiet))
{
Print_Pars(tree);
if(step > 1) (n_tested > 1)?(printf("[%4d NNIs]",n_tested)):(printf("[%4d NNI ]",n_tested));
}
if(FABS(old_pars - tree->c_pars) < SMALL) break;
if((tree->c_pars > old_pars) && (step > 1))
{
if((tree->mod->s_opt->print) && (!tree->io->quiet))
PhyML_Printf("\n\n. Moving backward (topoLlogy) \n");
if(!Mov_Backward_Topo_Pars(tree,old_pars,tested_b,n_tested))
Exit("\n. Err: mov_back failed\n");
if(!tree->n_swap) n_neg = 0;
tree->both_sides = 1;
Pars(tree);
}
else
{
old_pars = tree->c_pars;
Fill_Dir_Table(tree);
n_neg = 0;
For(i,2*tree->n_otu-3)
if((!tree->t_edges[i]->left->tax) &&
(!tree->t_edges[i]->rght->tax))
NNI_Pars(tree,tree->t_edges[i],0);
Select_Edges_To_Swap(tree,sorted_b,&n_neg);
Sort_Edges_NNI_Score(tree,sorted_b,n_neg);
n_tested = 0;
For(i,(int)CEIL((phydbl)n_neg*(lambda)))
tested_b[n_tested++] = sorted_b[i];
Make_N_Swap(tree,tested_b,0,n_tested);
n_tot_swap += n_tested;
if(n_tested > 0) n_without_swap = 0;
else n_without_swap++;
}
n_iter+=1.0;
}
while(1);
Free(sorted_b);
Free(tested_b);
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void Select_Edges_To_Swap(t_tree *tree, t_edge **sorted_b, int *n_neg)
{
int i;
t_edge *b;
int min;
phydbl best_score;
*n_neg = 0;
min = 0;
For(i,2*tree->n_otu-3)
{
b = tree->t_edges[i];
best_score = b->nni->score;
if((!b->left->tax) && (!b->rght->tax) && (b->nni->score < -tree->mod->s_opt->min_diff_lk_move))
{
Check_NNI_Scores_Around(b->left,b->rght,b,&best_score,tree);
Check_NNI_Scores_Around(b->rght,b->left,b,&best_score,tree);
if(best_score < b->nni->score) continue;
sorted_b[*n_neg] = b;
(*n_neg)++;
}
}
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void Update_Bl(t_tree *tree, phydbl fact)
{
int i;
t_edge *b;
For(i,2*tree->n_otu-3)
{
b = tree->t_edges[i];
b->l = b->l_old + (b->nni->l0 - b->l_old)*fact;
}
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void Make_N_Swap(t_tree *tree,t_edge **b, int beg, int end)
{
int i;
int dim;
dim = 2*tree->n_otu-2;
/* PhyML_Printf("\n. Beg Actually performing swaps\n"); */
tree->n_swap = 0;
for(i=beg;inum, */
/* b[i]->nni->swap_node_v2->v[tree->t_dir[b[i]->nni->swap_node_v2->num*dim+b[i]->nni->swap_node_v1->num]]->num, */
/* b[i]->nni->swap_node_v2->num, */
/* b[i]->nni->swap_node_v3->num, */
/* b[i]->nni->swap_node_v3->v[tree->t_dir[b[i]->nni->swap_node_v3->num*dim+b[i]->nni->swap_node_v4->num]]->num); */
Swap(b[i]->nni->swap_node_v2->v[tree->t_dir[b[i]->nni->swap_node_v2->num*dim+b[i]->nni->swap_node_v1->num]],
b[i]->nni->swap_node_v2,
b[i]->nni->swap_node_v3,
b[i]->nni->swap_node_v3->v[tree->t_dir[b[i]->nni->swap_node_v3->num*dim+b[i]->nni->swap_node_v4->num]],
tree);
if(!Check_Topo_Constraints(tree,tree->io->cstr_tree))
{
/* Undo this swap as it violates one of the topological constraints
defined in the input constraint tree
*/
Swap(b[i]->nni->swap_node_v2->v[tree->t_dir[b[i]->nni->swap_node_v2->num*dim+b[i]->nni->swap_node_v1->num]],
b[i]->nni->swap_node_v2,
b[i]->nni->swap_node_v3,
b[i]->nni->swap_node_v3->v[tree->t_dir[b[i]->nni->swap_node_v3->num*dim+b[i]->nni->swap_node_v4->num]],
tree);
}
if(tree->n_root)
{
tree->n_root->v[0] = tree->e_root->left;
tree->n_root->v[1] = tree->e_root->rght;
}
b[i]->l = b[i]->nni->best_l;
tree->n_swap++;
}
/* PhyML_Printf("\n. End Actually performing swaps\n"); */
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
int Make_Best_Swap(t_tree *tree)
{
int i,j,return_value;
t_edge *b,**sorted_b;
int dim;
dim = 2*tree->n_otu-2;
sorted_b = (t_edge **)mCalloc(tree->n_otu-3,sizeof(t_edge *));
j=0;
For(i,2*tree->n_otu-3) if((!tree->t_edges[i]->left->tax) &&
(!tree->t_edges[i]->rght->tax))
sorted_b[j++] = tree->t_edges[i];
Sort_Edges_NNI_Score(tree,sorted_b,tree->n_otu-3);
if(sorted_b[0]->nni->score < -0.0)
{
b = sorted_b[0];
return_value = 1;
Swap(b->nni->swap_node_v2->v[tree->t_dir[b->nni->swap_node_v2->num*dim+b->nni->swap_node_v1->num]],
b->nni->swap_node_v2,
b->nni->swap_node_v3,
b->nni->swap_node_v3->v[tree->t_dir[b->nni->swap_node_v3->num*dim+b->nni->swap_node_v4->num]],
tree);
if(!Check_Topo_Constraints(tree,tree->io->cstr_tree))
{
/* Undo this swap as it violates one of the topological constraints
defined in the input constraint tree
*/
Swap(b->nni->swap_node_v2->v[tree->t_dir[b->nni->swap_node_v2->num*dim+b->nni->swap_node_v1->num]],
b->nni->swap_node_v2,
b->nni->swap_node_v3,
b->nni->swap_node_v3->v[tree->t_dir[b->nni->swap_node_v3->num*dim+b->nni->swap_node_v4->num]],
tree);
}
b->l = b->nni->best_l;
/* (b->nni->best_conf == 1)? */
/* (Swap(b->left->v[b->l_v2],b->left,b->rght,b->rght->v[b->r_v1],tree)): */
/* (Swap(b->left->v[b->l_v2],b->left,b->rght,b->rght->v[b->r_v2],tree)); */
/* b->l = */
/* (b->nni->best_conf == 1)? */
/* (b->nni->l1): */
/* (b->nni->l2); */
}
else return_value = 0;
Free(sorted_b);
return return_value;
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
int Mov_Backward_Topo_Bl(t_tree *tree, phydbl lk_old, t_edge **tested_b, int n_tested)
{
phydbl *l_init;
int i,step,beg,end;
t_edge *b;
l_init = (phydbl *)mCalloc(2*tree->n_otu-3,sizeof(phydbl));
For(i,2*tree->n_otu-3) l_init[i] = tree->t_edges[i]->l;
step = 2;
tree->both_sides = 0;
do
{
For(i,2*tree->n_otu-3)
{
b = tree->t_edges[i];
b->l = b->l_old + (1./step) * (l_init[i] - b->l_old);
}
beg = (int)FLOOR((phydbl)n_tested/(step-1));
end = 0;
Unswap_N_Branch(tree,tested_b,beg,end);
beg = 0;
end = (int)FLOOR((phydbl)n_tested/step);
Swap_N_Branch(tree,tested_b,beg,end);
if(!end) tree->n_swap = 0;
tree->both_sides = 0;
Lk(tree);
step++;
}while((tree->c_lnL < lk_old) && (step < 1000));
if(step == 1000)
{
if(tree->n_swap) Exit("\n. Err. in Mov_Backward_Topo_Bl (n_swap > 0)\n");
For(i,2*tree->n_otu-3)
{
b = tree->t_edges[i];
b->l = b->l_old;
}
tree->both_sides = 0;
Lk(tree);
}
Free(l_init);
tree->n_swap = 0;
For(i,2*tree->n_otu-3)
{
if(tree->t_edges[i]->nni->score < 0.0) tree->n_swap++;
tree->t_edges[i]->nni->score = +1.0;
}
if(tree->c_lnL > lk_old) return 1;
else if((tree->c_lnL > lk_old-tree->mod->s_opt->min_diff_lk_local) &&
(tree->c_lnL < lk_old+tree->mod->s_opt->min_diff_lk_local)) return -1;
else return 0;
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
int Mov_Backward_Topo_Pars(t_tree *tree, int pars_old, t_edge **tested_b, int n_tested)
{
int i,step,beg,end;
step = 2;
tree->both_sides = 0;
do
{
beg = (int)FLOOR((phydbl)n_tested/(step-1));
end = 0;
Unswap_N_Branch(tree,tested_b,beg,end);
beg = 0;
end = (int)FLOOR((phydbl)n_tested/step);
Swap_N_Branch(tree,tested_b,beg,end);
if(!end) tree->n_swap = 0;
tree->both_sides = 0;
Pars(tree);
step++;
}while((tree->c_pars > pars_old) && (step < 1000));
if(step == 1000)
{
if(tree->n_swap) Exit("\n. Err. in Mov_Backward_Topo_Bl (n_swap > 0)\n");
tree->both_sides = 0;
Pars(tree);
}
tree->n_swap = 0;
For(i,2*tree->n_otu-3)
{
if(tree->t_edges[i]->nni->score < 0.0) tree->n_swap++;
tree->t_edges[i]->nni->score = +1.0;
}
if(tree->c_pars < pars_old) return 1;
else if(tree->c_pars == pars_old) return -1;
else return 0;
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void Unswap_N_Branch(t_tree *tree, t_edge **b, int beg, int end)
{
int i;
int dim;
dim = 2*tree->n_otu-2;
if(end>beg)
{
for(i=beg;inum, */
/* b[i]->nni->swap_node_v2->v[tree->t_dir[b[i]->nni->swap_node_v2->num][b[i]->nni->swap_node_v1->num]]->num, */
/* b[i]->nni->swap_node_v4->num, */
/* b[i]->nni->swap_node_v2->num, */
/* b[i]->nni->swap_node_v3->num, */
/* b[i]->nni->swap_node_v3->v[tree->t_dir[b[i]->nni->swap_node_v3->num][b[i]->nni->swap_node_v4->num]]->num, */
/* b[i]->nni->swap_node_v1->num */
/* ); */
Swap(b[i]->nni->swap_node_v2->v[tree->t_dir[b[i]->nni->swap_node_v2->num*dim+b[i]->nni->swap_node_v1->num]],
b[i]->nni->swap_node_v2,
b[i]->nni->swap_node_v3,
b[i]->nni->swap_node_v3->v[tree->t_dir[b[i]->nni->swap_node_v3->num*dim+b[i]->nni->swap_node_v4->num]],
tree);
if(!Check_Topo_Constraints(tree,tree->io->cstr_tree))
{
/* Undo this swap as it violates one of the topological constraints
defined in the input constraint tree
*/
Swap(b[i]->nni->swap_node_v2->v[tree->t_dir[b[i]->nni->swap_node_v2->num*dim+b[i]->nni->swap_node_v1->num]],
b[i]->nni->swap_node_v2,
b[i]->nni->swap_node_v3,
b[i]->nni->swap_node_v3->v[tree->t_dir[b[i]->nni->swap_node_v3->num*dim+b[i]->nni->swap_node_v4->num]],
tree);
}
/* (b[i]->nni->best_conf == 1)? */
/* (Swap(b[i]->left->v[b[i]->l_v2],b[i]->left,b[i]->rght,b[i]->rght->v[b[i]->r_v1],tree)): */
/* (Swap(b[i]->left->v[b[i]->l_v2],b[i]->left,b[i]->rght,b[i]->rght->v[b[i]->r_v2],tree)); */
b[i]->l = b[i]->l_old;
}
}
else
{
for(i=beg-1;i>=end;i--)
{
Swap(b[i]->nni->swap_node_v2->v[tree->t_dir[b[i]->nni->swap_node_v2->num*dim+b[i]->nni->swap_node_v1->num]],
b[i]->nni->swap_node_v2,
b[i]->nni->swap_node_v3,
b[i]->nni->swap_node_v3->v[tree->t_dir[b[i]->nni->swap_node_v3->num*dim+b[i]->nni->swap_node_v4->num]],
tree);
if(!Check_Topo_Constraints(tree,tree->io->cstr_tree))
{
/* Undo this swap as it violates one of the topological constraints
defined in the input constraint tree
*/
Swap(b[i]->nni->swap_node_v2->v[tree->t_dir[b[i]->nni->swap_node_v2->num*dim+b[i]->nni->swap_node_v1->num]],
b[i]->nni->swap_node_v2,
b[i]->nni->swap_node_v3,
b[i]->nni->swap_node_v3->v[tree->t_dir[b[i]->nni->swap_node_v3->num*dim+b[i]->nni->swap_node_v4->num]],
tree);
}
b[i]->l = b[i]->l_old;
}
}
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void Swap_N_Branch(t_tree *tree,t_edge **b, int beg, int end)
{
int i;
int dim;
dim = 2*tree->n_otu-2;
if(end>beg)
{
for(i=beg;inni->swap_node_v2->v[tree->t_dir[b[i]->nni->swap_node_v2->num*dim+b[i]->nni->swap_node_v1->num]],
b[i]->nni->swap_node_v2,
b[i]->nni->swap_node_v3,
b[i]->nni->swap_node_v3->v[tree->t_dir[b[i]->nni->swap_node_v3->num*dim+b[i]->nni->swap_node_v4->num]],
tree);
if(!Check_Topo_Constraints(tree,tree->io->cstr_tree))
{
/* Undo this swap as it violates one of the topological constraints
defined in the input constraint tree
*/
Swap(b[i]->nni->swap_node_v2->v[tree->t_dir[b[i]->nni->swap_node_v2->num*dim+b[i]->nni->swap_node_v1->num]],
b[i]->nni->swap_node_v2,
b[i]->nni->swap_node_v3,
b[i]->nni->swap_node_v3->v[tree->t_dir[b[i]->nni->swap_node_v3->num*dim+b[i]->nni->swap_node_v4->num]],
tree);
}
b[i]->l = b[i]->nni->best_l;
}
}
else
{
for(i=beg-1;i>=end;i--)
{
Swap(b[i]->nni->swap_node_v2->v[tree->t_dir[b[i]->nni->swap_node_v2->num*dim+b[i]->nni->swap_node_v1->num]],
b[i]->nni->swap_node_v2,
b[i]->nni->swap_node_v3,
b[i]->nni->swap_node_v3->v[tree->t_dir[b[i]->nni->swap_node_v3->num*dim+b[i]->nni->swap_node_v4->num]],
tree);
if(!Check_Topo_Constraints(tree,tree->io->cstr_tree))
{
/* Undo this swap as it violates one of the topological constraints
defined in the input constraint tree
*/
Swap(b[i]->nni->swap_node_v2->v[tree->t_dir[b[i]->nni->swap_node_v2->num*dim+b[i]->nni->swap_node_v1->num]],
b[i]->nni->swap_node_v2,
b[i]->nni->swap_node_v3,
b[i]->nni->swap_node_v3->v[tree->t_dir[b[i]->nni->swap_node_v3->num*dim+b[i]->nni->swap_node_v4->num]],
tree);
}
b[i]->l = b[i]->nni->best_l;
}
}
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void Check_NNI_Scores_Around(t_node *a, t_node *d, t_edge *b, phydbl *best_score, t_tree *tree)
{
int i;
For(i,3)
{
if((d->v[i] != a) && (!d->v[i]->tax))
{
if((d->b[i]->nni->score > *best_score-1.E-10) &&
(d->b[i]->nni->score < *best_score+1.E-10)) /* ties */
{
d->b[i]->nni->score = *best_score+1.;
}
if(d->b[i]->nni->score < *best_score)
{
*best_score = d->b[i]->nni->score;
}
}
}
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
phyml-20120412/src/tiporder.c 0000644 0001750 0001750 00000111321 11644731721 012611 0000000 0000000 /*
PhyML: a program that computes maximum likelihood phyLOGenies from
DNA or AA homoLOGous sequences.
Copyright (C) Stephane Guindon. Oct 2003 onward.
All parts of the source except where indicated are distributed under
the GNU public licence. See http://www.opensource.org for details.
*/
/* Routines for molecular clock trees and molecular dating */
#include "tiporder.h"
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
/* int TIPO_main(int argc, char **argv) */
/* { */
/* t_tree **list_tree,*ref_tree,*tree; */
/* FILE *fp_ref_tree,*fp_list_tree,*fp_coord,*ps_tree; */
/* int i,j,k; */
/* int n_trees; */
/* option *ref_io,*list_io; */
/* char **name_table; */
/* int r_seed; */
/* r_seed = time(NULL); */
/* srand(r_seed); */
/* ref_io = (option *)Make_Input(); */
/* list_io = (option *)Make_Input(); */
/* fp_ref_tree = (FILE *)fopen(argv[1],"r"); */
/* fp_list_tree = (FILE *)fopen(argv[2],"r"); */
/* fp_coord = (FILE *)fopen(argv[3],"r"); */
/* if(!fp_ref_tree) */
/* { */
/* PhyML_Printf("\n. Can't find %s",argv[1]); */
/* PhyML_Printf("\n. Err in file %s at line %d\n\n",__FILE__,__LINE__); */
/* Warn_And_Exit(""); */
/* } */
/* if(!fp_list_tree) */
/* { */
/* PhyML_Printf("\n. Can't find %s",argv[2]); */
/* PhyML_Printf("\n. Err in file %s at line %d\n\n",__FILE__,__LINE__); */
/* Warn_And_Exit(""); */
/* } */
/* ref_io->fp_in_tree = fp_ref_tree; */
/* Read_Tree_File(ref_io); */
/* fclose(ref_io->fp_in_tree); */
/* ref_tree = ref_io->treelist->tree[0]; */
/* ref_tree->io = ref_io; */
/* list_io->fp_in_tree = fp_list_tree; */
/* Read_Tree_File(list_io); */
/* fclose(list_io->fp_in_tree); */
/* list_tree = list_io->treelist->tree; */
/* n_trees = list_io->treelist->list_size; */
/* PhyML_Printf("\n. Read %d trees\n",n_trees); */
/* For(i,n_trees) list_tree[i]->io = list_io; */
/* name_table = (char **)mCalloc(ref_tree->n_otu,sizeof(char **)); */
/* For(i,ref_tree->n_otu) name_table[i] = (char *)mCalloc(T_MAX_NAME,sizeof(char)); */
/* /\* Sort translation table such that tree->t_nodes[i]->name == tree->io->short_tax_name[i] for all i *\/ */
/* TIPO_Sort_Translation_Table(ref_tree); */
/* ref_tree->io->z_scores = (phydbl *)mCalloc(ref_tree->n_otu,sizeof(phydbl)); */
/* /\* TIPO_Read_Taxa_Zscores(fp_coord,ref_tree); *\/ */
/* For(i,ref_tree->n_otu) ref_tree->io->z_scores[i] = TIPO_Read_One_Taxon_Zscore(fp_coord,ref_tree->t_nodes[i]->name,ref_tree); */
/* TIPO_Normalize_Zscores(ref_tree); */
/* /\* Find matching tips *\/ */
/* For(i,n_trees) */
/* { */
/* TIPO_Sort_Translation_Table(list_tree[i]); */
/* For(j,ref_tree->n_otu) */
/* { */
/* For(k,ref_tree->n_otu) */
/* { */
/* if(!strcmp(ref_io->long_tax_names[j],list_io->long_tax_names[k])) */
/* { */
/* list_tree[i]->t_nodes[k]->ext_node = ref_tree->t_nodes[j]; */
/* break; */
/* } */
/* } */
/* if(k == ref_tree->n_otu) */
/* { */
/* PhyML_Printf("\n. Could not find matching tips for \"%s\" (tree %d)",ref_tree->t_nodes[j]->name,i); */
/* PhyML_Printf("\n. Err in file %s at line %d\n\n",__FILE__,__LINE__); */
/* Warn_And_Exit(""); */
/* } */
/* } */
/* } */
/* PhyML_Printf("\n. Getting ancestors"); fflush(NULL); */
/* Update_Ancestors(ref_tree->n_root,ref_tree->n_root->v[0],ref_tree); */
/* Update_Ancestors(ref_tree->n_root,ref_tree->n_root->v[1],ref_tree); */
/* For(i,n_trees) */
/* { */
/* Update_Ancestors(list_tree[i]->n_root,list_tree[i]->n_root->v[0],list_tree[i]); */
/* Update_Ancestors(list_tree[i]->n_root,list_tree[i]->n_root->v[1],list_tree[i]); */
/* list_tree[i]->n_root->anc = NULL; */
/* } */
/* PhyML_Printf("\n. Getting bipartitions"); fflush(NULL); */
/* Free_Bip(ref_tree); */
/* Alloc_Bip(ref_tree); */
/* Get_Bip(ref_tree->t_nodes[0], */
/* ref_tree->t_nodes[0]->v[0], */
/* ref_tree); */
/* For(i,n_trees) */
/* { */
/* if(!(i%10)) */
/* PhyML_Printf("\n. Getting bipartition for tree %d",i); */
/* Free_Bip(list_tree[i]); */
/* Alloc_Bip(list_tree[i]); */
/* Get_Bip(list_tree[i]->t_nodes[0], */
/* list_tree[i]->t_nodes[0]->v[0], */
/* list_tree[i]); */
/* } */
/* PhyML_Printf("\n. Getting tip ranks"); fflush(NULL); */
/* /\* TIPO_Get_Tips_Y_Rank(ref_tree); *\/ */
/* TIPO_Get_Tips_Y_Rank_From_Zscores(ref_tree); */
/* /\* PhyML_Printf("\n. Minimizing"); fflush(NULL); *\/ */
/* /\* TIPO_Minimize_Tip_Order_Score(n_trees,list_tree,ref_tree); *\/ */
/* PhyML_Printf("\n. N_OTU = %d",ref_tree->n_otu); */
/* TIPO_Untangle_Tree(ref_tree); */
/* PhyML_Printf("\n ** ORIGINAL %f",ref_tree->tip_order_score); */
/* /\* i = 0; *\/ */
/* /\* do *\/ */
/* /\* { *\/ */
/* /\* /\\* TIPO_Get_Tips_Y_Rank_From_Zscores(ref_tree); *\\/ *\/ */
/* /\* TIPO_Randomize_Tip_Y_Ranks(ref_tree); *\/ */
/* /\* TIPO_Untangle_Tree(ref_tree); *\/ */
/* /\* PhyML_Printf("\n ** %f",ref_tree->tip_order_score); *\/ */
/* /\* i++; *\/ */
/* /\* }while(i < 5000); *\/ */
/* Test_Node_Table_Consistency(ref_tree); */
/* ref_tree->ps_tree = DR_Make_Tdraw_Struct(ref_tree); */
/* DR_Get_Tree_Coord(ref_tree); */
/* For(j,ref_tree->n_otu) */
/* { */
/* ref_tree->ps_tree->ycoord[j] = */
/* (ref_tree->t_nodes[j]->y_rank/ref_tree->n_otu)* */
/* ref_tree->ps_tree->page_height; */
/* } */
/* ps_tree = (FILE *)fopen("order_tree.ps","w"); */
/* list_io->z_scores = (phydbl *)mCalloc(ref_tree->n_otu,sizeof(phydbl)); */
/* DR_Print_Postscript_Header(1,ps_tree); */
/* For(i,n_trees) */
/* { */
/* tree = list_tree[i]; */
/* Test_Node_Table_Consistency(tree); */
/* tree->rates = RATES_Make_Rate_Struct(tree->n_otu); */
/* RATES_Init_Rate_Struct(tree->rates,tree->n_otu); */
/* TIMES_Least_Square_Node_Times(tree->e_root,tree); */
/* TIMES_Adjust_Node_Times(tree); */
/* RATES_Update_Cur_Bl(tree); */
/* tree->ps_tree = DR_Make_Tdraw_Struct(tree); */
/* DR_Init_Tdraw_Struct(tree->ps_tree); */
/* DR_Get_Tree_Box_Width(tree->ps_tree,tree); */
/* Dist_To_Root(tree->n_root,tree); */
/* tree->ps_tree->max_dist_to_root = DR_Get_Max_Dist_To_Root(tree); */
/* For(j,ref_tree->n_otu) tree->io->z_scores[j] = ref_tree->io->z_scores[tree->t_nodes[j]->ext_node->num]; */
/* TIPO_Get_Tips_Y_Rank_From_Zscores(tree); */
/* TIPO_Untangle_Tree(tree); */
/* For(j,ref_tree->n_otu) tree->ps_tree->ycoord[j] = (tree->t_nodes[j]->y_rank/tree->n_otu)*tree->ps_tree->page_height; */
/* /\* For(j,ref_tree->n_otu) tree->ps_tree->ycoord[j] = ref_tree->ps_tree->ycoord[tree->t_nodes[j]->ext_node->num]; *\/ */
/* For(j,ref_tree->n_otu) list_io->z_scores[j] = ref_io->z_scores[tree->t_nodes[j]->ext_node->num]; */
/* DR_Get_Y_Coord(YES,tree->ps_tree,tree); */
/* DR_Get_X_Coord( NO,tree->ps_tree,tree); */
/* if(!i) DR_Print_Tree_Postscript(1,YES,ps_tree,tree); */
/* else DR_Print_Tree_Postscript(1, NO,ps_tree,tree); */
/* } */
/* DR_Print_Postscript_EOF(ps_tree); */
/* fclose(ps_tree); */
/* ps_tree = (FILE *)fopen("ref_tree.ps","w"); */
/* DR_Print_Postscript_Header(1,ps_tree); */
/* tree = ref_tree; */
/* tree->rates = RATES_Make_Rate_Struct(tree->n_otu); */
/* RATES_Init_Rate_Struct(tree->rates,tree->n_otu); */
/* TIMES_Least_Square_Node_Times(tree->e_root,tree); */
/* TIMES_Adjust_Node_Times(tree); */
/* RATES_Update_Cur_Bl(tree); */
/* DR_Init_Tdraw_Struct(tree->ps_tree); */
/* DR_Get_Tree_Box_Width(tree->ps_tree,tree); */
/* Dist_To_Root(tree->n_root,tree); */
/* tree->ps_tree->max_dist_to_root = DR_Get_Max_Dist_To_Root(tree); */
/* TIPO_Get_Tips_Y_Rank_From_Zscores(tree); */
/* /\* TIPO_Untangle_Tree(tree); *\/ */
/* For(j,tree->n_otu) tree->ps_tree->ycoord[j] = (tree->t_nodes[j]->y_rank/tree->n_otu)*tree->ps_tree->page_height; */
/* DR_Get_Y_Coord(YES,tree->ps_tree,tree); */
/* DR_Get_X_Coord( NO,tree->ps_tree,tree); */
/* DR_Print_Tree_Postscript(1,YES,ps_tree,tree); */
/* DR_Print_Postscript_EOF(ps_tree); */
/* fclose(ps_tree); */
/* PhyML_Printf("\n"); */
/* fclose(fp_ref_tree); */
/* fclose(fp_list_tree); */
/* fclose(fp_coord); */
/* } */
int TIPO_main(int argc, char **argv)
{
t_tree *tree;
option *io;
FILE *fp_tree_file, *fp_coord_file;
int i;
/* Rprintf("%s\n",tree_file_name[0]); */
/* Rprintf("%s\n",coord_file_name[0]); */
srand(time(NULL)); rand();
fp_tree_file = (FILE *)fopen(argv[1],"r");
fp_coord_file = (FILE *)fopen(argv[2],"r");
io = (option *)Make_Input();
io->fp_in_tree = fp_tree_file;
Read_Tree_File(io);
tree = io->treelist->tree[0];
tree->io = io;
tree->io->z_scores = (phydbl *)mCalloc(tree->n_otu,sizeof(phydbl));
For(i,tree->n_otu) tree->io->z_scores[i] = TIPO_Read_One_Taxon_Zscore(fp_coord_file,tree->t_nodes[i]->name,1,tree);
/* TIPO_Normalize_Zscores(tree); */
Free_Bip(tree);
Alloc_Bip(tree);
Get_Bip(tree->t_nodes[0],tree->t_nodes[0]->v[0],tree);
TIPO_Get_Tips_Y_Rank_From_Zscores(tree);
/* TIPO_Get_Tips_Y_Rank(tree); */
tree->geo_mig_sd = 0.1;
Generic_Brent_Lk(&(tree->geo_mig_sd),
1.E-3,1.E+2,1.E-6,
100,NO,
&Wrap_Geo_Lk,
NULL,tree,NULL);
PhyML_Printf("\n. sd=%f",tree->geo_mig_sd);
fclose(fp_tree_file);
fclose(fp_coord_file);
return 0;
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
/* Z_scores have already been recorder here */
void TIPO_Get_Min_Number_Of_Tip_Permut(t_tree *tree)
{
Update_Ancestors(tree->n_root,tree->n_root->v[0],tree);
Update_Ancestors(tree->n_root,tree->n_root->v[1],tree);
Free_Bip(tree);
Alloc_Bip(tree);
Get_Bip(tree->t_nodes[0],tree->t_nodes[0]->v[0],tree);
TIPO_Get_Tips_Y_Rank_From_Zscores(tree);
TIPO_Untangle_Tree(tree);
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void TIPO_Get_Tips_Y_Rank(t_tree *tree)
{
phydbl curr_rank;
curr_rank = .0;
TIPO_Get_Tips_Y_Rank_Pre(tree->n_root,tree->n_root->v[0],&curr_rank,tree);
TIPO_Get_Tips_Y_Rank_Pre(tree->n_root,tree->n_root->v[1],&curr_rank,tree);
if(curr_rank != tree->n_otu)
{
PhyML_Printf("\n. tree->n_otu = %d curr_rank = %d",tree->n_otu,curr_rank);
PhyML_Printf("\n. Err in file %s at line %d\n\n",__FILE__,__LINE__);
Warn_And_Exit("");
}
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void TIPO_Get_Tips_Y_Rank_Pre(t_node *a, t_node *d, phydbl *curr_rank, t_tree *tree)
{
if(d->tax)
{
d->y_rank = *curr_rank;
*curr_rank += 1.;
return;
}
else
{
int i;
For(i,3)
{
if(d->v[i] != a && d->b[i] != tree->e_root)
{
TIPO_Get_Tips_Y_Rank_Pre(d,d->v[i],curr_rank,tree);
}
}
}
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void TIPO_Get_All_Y_Rank(t_tree *tree)
{
tree->sum_y_dist_sq = .0;
tree->sum_y_dist = .0;
TIPO_Get_All_Y_Rank_Pre(tree->n_root,tree->n_root->v[0],tree);
TIPO_Get_All_Y_Rank_Pre(tree->n_root,tree->n_root->v[1],tree);
tree->n_root->y_rank = (tree->n_root->v[0]->y_rank+tree->n_root->v[1]->y_rank)/2.;
tree->n_root->y_rank_min = MIN(tree->n_root->v[0]->y_rank_min,tree->n_root->v[1]->y_rank_min);
tree->n_root->y_rank_max = MAX(tree->n_root->v[0]->y_rank_max,tree->n_root->v[1]->y_rank_max);
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void TIPO_Get_All_Y_Rank_Pre(t_node *a, t_node *d, t_tree *tree)
{
if(d->tax)
{
d->y_rank_min = d->y_rank;
d->y_rank_max = d->y_rank;
return;
}
else
{
int i;
int dir1,dir2;
phydbl v1,v2;
For(i,3)
{
if(d->v[i] != a && d->b[i] != tree->e_root)
{
TIPO_Get_All_Y_Rank_Pre(d,d->v[i],tree);
}
}
dir1 = dir2 = -1;
For(i,3)
{
if(d->v[i] != a && d->b[i] != tree->e_root)
{
if(dir1 < 0) dir1 = i;
else dir2 = i;
}
}
v1 = d->v[dir1]->y_rank;
v2 = d->v[dir2]->y_rank;
d->y_rank = (v1+v2)/2.;
tree->sum_y_dist_sq += POW(v1-v2,2);
tree->sum_y_dist += FABS(v1-v2);
d->y_rank_min = MIN(d->v[dir1]->y_rank_min,d->v[dir2]->y_rank_min);
d->y_rank_max = MAX(d->v[dir1]->y_rank_max,d->v[dir2]->y_rank_max);
}
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void TIPO_Swap_One_Node(t_node *d, t_tree *tree)
{
if(d->tax) return;
else
{
int i;
int dir1, dir2;
t_node *tmp_n;
t_edge *tmp_e;
if(d != tree->n_root)
{
dir1 = dir2 = -1;
For(i,3)
{
if((d->v[i] != d->anc) && (d->b[i] != tree->e_root))
{
if(dir1 < 0) dir1 = i;
else dir2 = i;
}
}
}
else
{
dir1 = 0;
dir2 = 1;
}
tmp_n = d->v[dir2];
d->v[dir2] = d->v[dir1];
d->v[dir1] = tmp_n;
tmp_e = d->b[dir2];
d->b[dir2] = d->b[dir1];
d->b[dir1] = tmp_e;
}
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void TIPO_Minimize_Tip_Order_Score(int n_trees, t_tree **list_tree, t_tree *ref_tree)
{
int i,j;
phydbl score,min_score,old_min_score;
phydbl diff,eps;
t_node **node_table;
int swapped;
t_node *tmp;
eps = 1.E-3;
old_min_score = min_score = score = INT_MAX;
/* TIPO_Print_Tip_Ordered(ref_tree); */
do
{
for(i=ref_tree->n_otu;i<2*ref_tree->n_otu-1;i++)
{
TIPO_Swap_One_Node(ref_tree->t_nodes[i],ref_tree);
TIPO_Get_Tips_Y_Rank(ref_tree);
score = (phydbl)TIPO_Untangle_Tree_List(n_trees,list_tree,ref_tree);
if(score == -1)
{
return;
}
if(score < min_score)
{
min_score = score;
PhyML_Printf("\n- Score = %f",score);
}
else
{
TIPO_Swap_One_Node(ref_tree->t_nodes[i],ref_tree);
TIPO_Get_Tips_Y_Rank(ref_tree);
/* PhyML_Printf("\n+ Score = %f",score); */
}
}
diff = fabs(old_min_score - min_score);
old_min_score = min_score;
}while(diff > eps);
PhyML_Printf("\n");
node_table = (t_node **)mCalloc(ref_tree->n_otu,sizeof(t_node *));
For(i,ref_tree->n_otu)
{
For(j,ref_tree->n_otu)
{
if(!strcmp(ref_tree->io->short_tax_names[i],ref_tree->t_nodes[j]->name))
{
Free(ref_tree->t_nodes[j]->name);
ref_tree->t_nodes[j]->name = (char *)mCalloc((int)strlen(ref_tree->io->long_tax_names[i])+1,sizeof(char));
strcpy(ref_tree->t_nodes[j]->name,ref_tree->io->long_tax_names[i]);
break;
}
}
}
For(i,ref_tree->n_otu) node_table[i] = ref_tree->t_nodes[i];
/* bubble sort of conflict nodes according to their y_rank */
do
{
swapped = NO;
For(i,ref_tree->n_otu-1)
{
if(node_table[i]->y_rank > node_table[i+1]->y_rank)
{
swapped = YES;
tmp = node_table[i];
node_table[i] = node_table[i+1];
node_table[i+1] = tmp;
}
}
}while(swapped == YES);
For(i,ref_tree->n_otu)
{
PhyML_Printf("\n%s",node_table[i]->name,node_table[i]->y_rank);
}
Free(node_table);
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void TIPO_Print_Tip_Ordered(t_tree *tree)
{
TIPO_Print_Tip_Ordered_Pre(tree->n_root,tree->n_root->v[0],tree);
TIPO_Print_Tip_Ordered_Pre(tree->n_root,tree->n_root->v[1],tree);
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void TIPO_Print_Tip_Ordered_Pre(t_node *a, t_node *d, t_tree *tree)
{
if(d->tax)
{
PhyML_Printf("\n. %f \"%s\"",d->y_rank,d->name);
}
else
{
int i,dir1,dir2;
dir1 = dir2 = -1;
For(i,3)
{
if((d->v[i] != a) && (d->b[i] != tree->e_root))
{
if(dir1 < 0) dir1 = i;
else dir2 = i;
}
}
if(d->v[dir1]->y_rank < d->v[dir2]->y_rank)
{
TIPO_Print_Tip_Ordered_Pre(d,d->v[dir1],tree);
TIPO_Print_Tip_Ordered_Pre(d,d->v[dir2],tree);
}
else
{
TIPO_Print_Tip_Ordered_Pre(d,d->v[dir2],tree);
TIPO_Print_Tip_Ordered_Pre(d,d->v[dir1],tree);
}
}
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
int TIPO_Untangle_Tree_List(int n_trees, t_tree **list_tree, t_tree *ref_tree)
{
int i,j;
int tree_score,score;
score = 0;
For(i,n_trees)
{
/* PhyML_Printf("\n. Untangling tree %3d",i); */
For(j,ref_tree->n_otu) list_tree[i]->t_nodes[j]->y_rank = list_tree[i]->t_nodes[j]->ext_node->y_rank;
tree_score = TIPO_Untangle_Tree(list_tree[i]);
/* PhyML_Printf(" score = %3d",tree_score); */
score += tree_score;
if(tree_score < 0)
{
return -1;
}
}
return score;
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
phydbl TIPO_Untangle_Tree(t_tree *tree)
{
int conflict;
int n_trials;
t_node **node_table;
int i,swapped;
t_node *tmp;
node_table = (t_node **)mCalloc(tree->n_otu,sizeof(t_node *));
For(i,tree->n_otu) node_table[i] = tree->t_nodes[i];
For(i,tree->n_otu) tree->t_nodes[i]->y_rank_ori = tree->t_nodes[i]->y_rank;
/* bubble sort of nodes according to their y_rank */
do
{
swapped = NO;
For(i,tree->n_otu-1)
{
if(node_table[i]->y_rank > node_table[i+1]->y_rank)
{
swapped = YES;
tmp = node_table[i];
node_table[i] = node_table[i+1];
node_table[i+1] = tmp;
}
}
}
while(swapped == YES);
/* Work out the y_rank values for every internal node given the external node ranks */
TIPO_Get_All_Y_Rank(tree);
tree->tip_order_score = .0;
n_trials = 0;
do
{
conflict= NO;
/* Recusrssive untangling of the tree */
TIPO_Untangle_Node(tree->n_root,tree->n_root->v[0],node_table,&conflict,tree);
TIPO_Untangle_Node(tree->n_root,tree->n_root->v[1],node_table,&conflict,tree);
n_trials++;
if(n_trials > 2) /* We should have been able to untangle the tree after just one tree traversal */
{
int i;
FILE *ps_tree;
PhyML_Printf("\n. Err in file %s at line %d\n\n",__FILE__,__LINE__);
ps_tree = (FILE *)fopen("failed_tree.ps","w");
Test_Node_Table_Consistency(tree);
tree->rates = RATES_Make_Rate_Struct(tree->n_otu);
RATES_Init_Rate_Struct(tree->rates,tree->io->rates,tree->n_otu);
TIMES_Least_Square_Node_Times(tree->e_root,tree);
TIMES_Adjust_Node_Times(tree);
RATES_Update_Cur_Bl(tree);
DR_Print_Postscript_Header(1,ps_tree);
tree->ps_tree = DR_Make_Tdraw_Struct(tree);
DR_Init_Tdraw_Struct(tree->ps_tree);
DR_Get_Tree_Box_Width(tree->ps_tree,tree);
Dist_To_Root(tree->n_root,tree);
tree->ps_tree->max_dist_to_root = DR_Get_Max_Dist_To_Root(tree);
For(i,tree->n_otu) tree->ps_tree->ycoord[i] = tree->t_nodes[i]->y_rank * (int)(tree->ps_tree->page_height / (tree->n_otu));
DR_Get_X_Coord(NO,tree->ps_tree,tree);
DR_Get_Y_Coord(YES,tree->ps_tree,tree);
DR_Print_Tree_Postscript(1,NO,ps_tree,tree);
DR_Print_Postscript_EOF(ps_tree);
fclose(ps_tree);
Warn_And_Exit("");
}
}while(conflict == YES);
Free(node_table);
return tree->tip_order_score;
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void TIPO_Untangle_Node(t_node *a, t_node *d, t_node **node_table, int *conflict, t_tree *tree)
{
if(d->tax) return;
else
{
int i,j;
int d_a;
int beg,end;
phydbl min,max;
t_node *lca;
t_node **conflict_tips, **anc_conflict;
int n_conflicts;
phydbl eps,tmp_rank;
t_node *tmp_node;
int n_moved;
int n_anc_conflicts;
anc_conflict = NULL;
d_a = -1;
/* It is a post order traversal */
For(i,3)
{
if((d->v[i] != d->anc) && (d->b[i] != tree->e_root))
{
TIPO_Untangle_Node(d,d->v[i],node_table,conflict,tree);
}
}
lca = NULL;
eps = 1.E-10;
/* Find direction fron node d ((d)escendant) to a ((a)ncestor) */
For(i,3)
{
if((d->v[i] == d->anc) || (d->b[i] == tree->e_root))
{
d_a = i;
break;
}
}
/* y_rank_min is the minimum rank among all the ranks of the tips that
can be reached when going from a to d */
min = d->y_rank_min;
max = d->y_rank_max;
/* Get the list of tip nodes which ranks are between d->y_rank_min and d->y_rank_max */
n_conflicts = 0;
For(i,tree->n_otu)
{
if((node_table[i]->y_rank > min - eps) && (node_table[i]->y_rank < max + eps))
{
n_conflicts++;
}
}
conflict_tips = NULL;
For(i,tree->n_otu)
{
if(node_table[i]->y_rank > min - eps)
{
conflict_tips = node_table+i;
break;
}
}
beg = 0;
end = n_conflicts;
n_moved = 0;
n_anc_conflicts = 0;
do
{
for(i=beg;ibip_size[d_a]) if(conflict_tips[i] == d->bip_node[d_a][j]) break;
if(j == d->bip_size[d_a])
/* conflict_tips[i] does not belong to the list of descendant of node d. It is
therefore responsible for a conflict */
{
*conflict = YES;
/* printf("\n. Moving %d with rank %f",conflict_tips[i]->num,conflict_tips[i]->y_rank); */
n_moved++;
/* Move from conflict_tips[i] towards the root as long as the rank of the node lca is between min and max */
lca = conflict_tips[i];
while(lca->y_rank_min > min && lca->y_rank_max < max) lca = lca->anc;
if(lca->y_rank_min > max && lca->y_rank_max > max)
{
PhyML_Printf("\n. lca = %d (%d)",lca->num,lca==tree->n_root);
PhyML_Printf("\n. Err in file %s at line %d",__FILE__,__LINE__);
Warn_And_Exit("");
}
if(lca->y_rank_min < min && lca->y_rank_max < min)
{
PhyML_Printf("\n. lca = %d (root ? %d) (tip ? %d)",lca->num,lca==tree->n_root,lca->tax);
PhyML_Printf("\n. lca->y_rank_min = %f lca->y_rank_max = %f",lca->y_rank_min,lca->y_rank_max);
PhyML_Printf("\n. min=%f max=%f",min,max);
PhyML_Printf("\n. Err in file %s at line %d",__FILE__,__LINE__);
Warn_And_Exit("");
}
if(lca->tax)
{
PhyML_Printf("\n. lca (%d) cannot be a tip.",lca->num);
PhyML_Printf("\n. lca->anc->y_rank=%f",lca->anc->y_rank);
PhyML_Printf("\n. lca->y_rank=%f",lca->y_rank);
PhyML_Printf("\n. lca->y_rank_min=%f lca=>y_rank_max=%f",lca->y_rank_min,lca->y_rank_max);
PhyML_Printf("\n. min=%f max=%f",min,max);
PhyML_Printf("\n. %p %p",lca,conflict_tips[i]);
PhyML_Printf("\n. Err in file %s at line %d",__FILE__,__LINE__);
Warn_And_Exit("");
}
/* Have you found lca previously ? */
For(j,n_anc_conflicts) if(anc_conflict[j] == lca) break;
if(j == n_anc_conflicts) /* if no, then update the tree score and the list of ancestral nodes at the origin of conflicts */
{
/* tree->tip_order_score+=1.; */
/* tree->tip_order_score+=(lca->y_rank_max-lca->y_rank_min); */
n_anc_conflicts++;
anc_conflict = (t_node **)realloc(anc_conflict,n_anc_conflicts*sizeof(t_node *));
anc_conflict[n_anc_conflicts-1] = lca;
}
/* PhyML_Printf("\n. Detected conflict for ``%s'' (rank:%f min=%f max=%f lca=%f)", */
/* conflict_tips[i]->name, */
/* conflict_tips[i]->y_rank, */
/* min,max,lca->y_rank); */
/* Solve the conflict by shifting tip nodes to the left or to the right */
if(lca->y_rank > d->y_rank)
{
end--;
/* max-=1.; */
max = conflict_tips[end-1]->y_rank;
/* printf("\n. max=%f %f",max,conflict_tips[end-1]->y_rank); */
for(j=i;jnum,conflict_tips[j+1]->num, */
/* conflict_tips[j]->y_rank,conflict_tips[j+1]->y_rank); */
tmp_rank = conflict_tips[j]->y_rank;
conflict_tips[j]->y_rank = conflict_tips[j+1]->y_rank;
conflict_tips[j+1]->y_rank = tmp_rank;
tmp_node = conflict_tips[j];
conflict_tips[j] = conflict_tips[j+1];
conflict_tips[j+1] = tmp_node;
tree->tip_order_score += fabs(conflict_tips[j]->y_rank - conflict_tips[j+1]->y_rank)/n_conflicts;
/* PhyML_Printf(" to (%d,%d) (%f,%f)", */
/* conflict_tips[j]->num,conflict_tips[j+1]->num, */
/* conflict_tips[j]->y_rank,conflict_tips[j+1]->y_rank); */
}
}
else
{
beg++;
/* min+=1.; */
min = conflict_tips[beg]->y_rank;
/* printf("\n. min=%f %f",min,conflict_tips[beg]->y_rank); */
for(j=i;j>0;j--)
{
/* PhyML_Printf("\n- Moved (%d,%d) from (%f,%f)", */
/* conflict_tips[j]->num,conflict_tips[j-1]->num, */
/* conflict_tips[j]->y_rank,conflict_tips[j-1]->y_rank); */
tmp_rank = conflict_tips[j]->y_rank;
conflict_tips[j]->y_rank = conflict_tips[j-1]->y_rank;
conflict_tips[j-1]->y_rank = tmp_rank;
tmp_node = conflict_tips[j];
conflict_tips[j] = conflict_tips[j-1];
conflict_tips[j-1] = tmp_node;
tree->tip_order_score += fabs(conflict_tips[j]->y_rank - conflict_tips[j+1]->y_rank)/n_conflicts;
/* PhyML_Printf(" to (%d,%d) (%f,%f)", */
/* conflict_tips[j]->num,conflict_tips[j-1]->num, */
/* conflict_tips[j]->y_rank,conflict_tips[j-1]->y_rank); */
}
}
/* printf("\n"); */
/* For(j,n_conflicts) printf("%.0f ",conflict_tips[j]->y_rank); */
/* printf("\n. min=%f max=%f",min,max); */
/* printf("\n. Node %d has now rank %f",c_node->num,c_node->y_rank); */
/* Update internal nodes y ranks */
TIPO_Get_All_Y_Rank(tree);
break;
}
}
}while(n_moved + d->bip_size[d_a] != n_conflicts);
For(i,tree->n_otu)
{
if((tree->t_nodes[i]->y_rank > min - eps) && (tree->t_nodes[i]->y_rank < max + eps))
{
For(j,d->bip_size[d_a])
{
if(tree->t_nodes[i] == d->bip_node[d_a][j]) break;
}
if(j == d->bip_size[d_a])
{
printf("\n. Conflict remaining for node %d (%d)",d->num,a->num);
PhyML_Printf("\n. Err in file %s at line %d",__FILE__,__LINE__);
Warn_And_Exit("");
}
}
}
if(anc_conflict) Free(anc_conflict);
return;
}
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
int TIPO_Check_Tip_Ranks(t_tree *tree)
{
int i,j;
phydbl eps;
eps = 1.E-6;
For(i,tree->n_otu-1)
{
for(j=i+1;jn_otu;j++)
{
if(fabs(tree->t_nodes[i]->y_rank - tree->t_nodes[j]->y_rank) < eps)
{
return 0;
}
}
}
return 1;
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void TIPO_Read_Taxa_Zscores(FILE *fp_coord, t_tree *tree)
{
char *name,*line;
phydbl z;
int i;
name = (char *)mCalloc(T_MAX_NAME,sizeof(char));
line = (char *)mCalloc(T_MAX_LINE,sizeof(char));
if(!fgets(line,T_MAX_LINE,fp_coord))
{
PhyML_Printf("\n. Err in file %s at line %d\n\n",__FILE__,__LINE__);
Warn_And_Exit("");
}
Free(line);
do
{
if(fscanf(fp_coord,"%s\t%lf\n",name,&z) == EOF) break;
PhyML_Printf("\n. Read %s. Z-score: %f",name,z);
For(i,tree->n_otu) if(!strcmp(tree->io->long_tax_names[i],name)) break;
if(i == tree->n_otu)
{
PhyML_Printf("\n. Could not find taxon '%s' in coordinate file.",name);
PhyML_Printf("\n. Err in file %s at line %d\n\n",__FILE__,__LINE__);
Warn_And_Exit("");
}
tree->io->z_scores[i] = z;
}while(1);
Free(name);
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void TIPO_Read_Taxa_Coordinates(FILE *fp_coord, t_tree *tree)
{
char *name,*line;
phydbl lon, lat;
int i;
name = (char *)mCalloc(T_MAX_NAME,sizeof(char));
line = (char *)mCalloc(T_MAX_LINE,sizeof(char));
if(!fgets(line,T_MAX_LINE,fp_coord))
{
PhyML_Printf("\n. Err in file %s at line %d\n\n",__FILE__,__LINE__);
Warn_And_Exit("");
}
Free(line);
tree->io->lat = (phydbl *)mCalloc(tree->n_otu,sizeof(phydbl));
tree->io->lon = (phydbl *)mCalloc(tree->n_otu,sizeof(phydbl));
do
{
if(fscanf(fp_coord,"%s\t%lf\t%lf\n",name,&lat,&lon) == EOF) break;
PhyML_Printf("\n. Read %s %f %f",name,lat,lon);
For(i,tree->n_otu) if(!strcmp(tree->io->long_tax_names[i],name)) break;
if(i == tree->n_otu)
{
PhyML_Printf("\n. Could not find taxon '%s' in coordinate file.",name);
PhyML_Printf("\n. Err in file %s at line %d\n\n",__FILE__,__LINE__);
Warn_And_Exit("");
}
tree->io->lat[i] = lat;
tree->io->lon[i] = lon;
}while(1);
Free(name);
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void TIPO_Get_Tips_Y_Rank_From_Zscores(t_tree *tree)
{
int i;
For(i,tree->n_otu) tree->t_nodes[i]->y_rank = .0;
/* Randomization in order to avoid ties */
For(i,tree->n_otu) tree->io->z_scores[i] += Rnorm(0.0,0.001);
For(i,tree->n_otu) tree->t_nodes[i]->y_rank = tree->io->z_scores[i];
/* For(i,tree->n_otu) tree->t_nodes[i]->y_rank = .0; */
/* For(i,tree->n_otu-1) */
/* { */
/* for(j=i+1;jn_otu;j++) */
/* { */
/* if(tree->io->z_scores[i] > tree->io->z_scores[j]) */
/* { */
/* tree->t_nodes[i]->y_rank += 1.0; */
/* } */
/* else */
/* if(tree->io->z_scores[i] < tree->io->z_scores[j]) */
/* { */
/* tree->t_nodes[j]->y_rank += 1.0; */
/* } */
/* else */
/* { */
/* PhyML_Printf("\n. Ties not allowed.\n"); */
/* PhyML_Printf("\n. Err in file %s at line %d\n\n",__FILE__,__LINE__); */
/* Warn_And_Exit(""); */
/* } */
/* } */
/* } */
/* For(i,tree->n_otu) printf("- %f\n",tree->t_nodes[i]->y_rank); */
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
/* Sort translation table such that tree->t_nodes[i]->name == tree->io->short_tax_name[i] for all i */
void TIPO_Sort_Translation_Table(t_tree *tree)
{
int i,j;
char *s;
Test_Node_Table_Consistency(tree);
For(i,tree->n_otu-1)
{
for(j=i+1;jn_otu;j++)
{
if(!strcmp(tree->t_nodes[i]->name,tree->io->short_tax_names[j]))
{
s = tree->io->short_tax_names[i];
tree->io->short_tax_names[i] = tree->io->short_tax_names[j];
tree->io->short_tax_names[j] = s;
s = tree->io->long_tax_names[i];
tree->io->long_tax_names[i] = tree->io->long_tax_names[j];
tree->io->long_tax_names[j] = s;
break;
}
}
}
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void TIPO_Randomize_Tip_Y_Ranks(t_tree *tree)
{
int i;
phydbl rk_tmp;
int rnd_node_num;
For(i,tree->n_otu) tree->t_nodes[i]->y_rank_ori = tree->t_nodes[i]->y_rank;
For(i,tree->n_otu)
{
rnd_node_num = Rand_Int(0,tree->n_otu-1);
rk_tmp = tree->t_nodes[rnd_node_num]->y_rank;
tree->t_nodes[rnd_node_num]->y_rank = tree->t_nodes[i]->y_rank;
tree->t_nodes[i]->y_rank = rk_tmp;
}
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
phydbl TIPO_Read_One_Taxon_Zscore(FILE *fp_coord, char *seqname_qry, int col, t_tree *tree)
{
char *line;
char *seqname, *place;
phydbl lat;
line = (char *)mCalloc(T_MAX_LINE,sizeof(char));
seqname = (char *)mCalloc(T_MAX_NAME,sizeof(char));
place = (char *)mCalloc(T_MAX_NAME,sizeof(char));
rewind(fp_coord);
/* skip first line */
/* if(!fgets(line,T_MAX_LINE,fp_coord)) */
/* { */
/* PhyML_Printf("\n. Err in file %s at line %d\n\n",__FILE__,__LINE__); */
/* Warn_And_Exit(""); */
/* } */
/* Free(line); */
do
{
/* if(fscanf(fp_coord,"%s\t%s\t%lf\t%lf\t%d\n",seqname,place,&lat,&lon,&year) == EOF) */
/* if(fscanf(fp_coord,"%s\t%s\t%lf\t%lf\n",seqname,place,&lat,&lon) == EOF) */
/* if(fscanf(fp_coord,"%s\t%lf\t%lf\n",seqname,&lat,&lon) == EOF) */
if(fscanf(fp_coord,"%s %lf\n",seqname,&lat) == EOF)
{
PhyML_Printf("\n. Could not find sequence '%s' in coordinate file",seqname_qry);
PhyML_Printf("\n. Err in file %s at line %d\n\n",__FILE__,__LINE__);
Warn_And_Exit("");
}
if(!strcmp(seqname,seqname_qry)) break;
}while(1);
/* PhyML_Printf("\n. Found %20s %s @ %10.2f %10.2f. Recording %10.2f",seqname,place,lat,lon,(col==1)?lat:lon); */
Free(seqname);
Free(place);
/* if(col == 1) return lat; */
/* else if(col == 2) return lon; */
/* else return -1.; */
return lat;
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void TIPO_Normalize_Zscores(t_tree *tree)
{
int i;
phydbl min_z,max_z;
phydbl eps;
eps = 1.E-10;
min_z = FLT_MAX;
For(i,tree->n_otu)
{
if(tree->io->z_scores[i] < min_z)
{
min_z = tree->io->z_scores[i];
}
}
max_z = -FLT_MAX;
For(i,tree->n_otu)
{
if(tree->io->z_scores[i] > max_z)
{
max_z = tree->io->z_scores[i];
}
}
For(i,tree->n_otu) tree->io->z_scores[i] = (tree->io->z_scores[i] - min_z)/(max_z-min_z+eps);
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
phydbl TIPO_Lk(t_tree *tree)
{
tree->geo_lnL = 0.0;
TIPO_Lk_Post(tree->n_root,tree->n_root->v[0],tree);
TIPO_Lk_Post(tree->n_root,tree->n_root->v[1],tree);
TIPO_Lk_Core(NULL,tree->n_root,tree);
return(tree->geo_lnL);
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
phydbl TIPO_Lk_Post(t_node *a, t_node *d, t_tree *tree)
{
if(!d->tax)
{
int i;
For(i,3)
{
if(d->v[i] != a && d->b[i] != tree->e_root)
{
TIPO_Lk_Post(d,d->v[i],tree);
}
}
TIPO_Lk_Core(a,d,tree);
}
return .0;
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
phydbl TIPO_Lk_Core(t_node *a, t_node *d, t_tree *tree)
{
int i,j;
int d_v1,d_v2,v1_d,v2_d;
t_node *v1, *v2;
phydbl dist,dens,min_dist;
if(d->tax)
{
PhyML_Printf("\n. Err in file %s at line %d\n\n",__FILE__,__LINE__);
Warn_And_Exit("");
}
if(d == tree->n_root)
{
d_v1 = 0;
d_v2 = 1;
}
else
{
d_v1 = d_v2 = -1;
For(i,3)
{
if(d->v[i] != a && d->b[i] != tree->e_root)
{
if(d_v1 < 0) d_v1 = i;
else d_v2 = i;
}
}
}
v1 = d->v[d_v1];
v2 = d->v[d_v2];
v1_d = v2_d = -1;
if(d == tree->n_root)
{
For(i,3)
{
if(v1->b[i] == tree->e_root) v1_d = i;
if(v2->b[i] == tree->e_root) v2_d = i;
}
}
else
{
For(i,3)
{
if(v1->v[i] == d) v1_d = i;
if(v2->v[i] == d) v2_d = i;
}
}
dens = 0.0;
min_dist = FLT_MAX;
For(i,v1->bip_size[v1_d])
{
For(j,v2->bip_size[v2_d])
{
dist = fabs(v1->bip_node[v1_d][i]->y_rank -
v2->bip_node[v2_d][j]->y_rank);
if(dist < min_dist) min_dist = dist;
dens += Dnorm(dist,0.0,tree->geo_mig_sd);
/* printf("\n. dist=%f dens=%f %f %f", */
/* dist,Dnorm(dist,0.0,tree->geo_mig_sd), */
/* v1->bip_node[v1_d][i]->y_rank, */
/* v2->bip_node[v2_d][j]->y_rank); */
}
}
/* printf("\n. min_dist=%f dens=%f", */
/* min_dist,Dnorm(dist,0.0,tree->geo_mig_sd)); */
/* dens = Dnorm(min_dist,0.0,tree->geo_mig_sd); */
tree->geo_lnL += LOG(dens);
return tree->geo_lnL;
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
phyml-20120412/src/mpi_boot.c 0000644 0001750 0001750 00000040667 11741127014 012577 0000000 0000000 /*
PhyML: a program that computes maximum likelihood phyLOGenies from
DNA or AA homologous sequences.
Copyright (C) Stephane Guindon. Oct 2003 onward.
All parts of the source except where indicated are distributed under
the GNU public licence. See http://www.opensource.org for details.
*/
#include "mpi_boot.h"
/* #ifdef MPI */
/*********************************************************/
void Bootstrap_MPI(t_tree *tree)
{
int *site_num, n_site;
int replicate,j,k;
int position, init_len, nbRep;
calign *boot_data;
t_tree *boot_tree;
model *boot_mod;
matrix *boot_mat;
char *s;
MPI_Status Stat;
int randomRecv, bootRecv, nbElem, i;
int *score_par, *score_tot;
char *bootStr, *t;
randomRecv = nbElem = bootRecv = 0;
tree->print_boot_val = 1;
tree->print_alrt_val = 0;
boot_tree = NULL;
site_num = (int *)mCalloc(tree->data->init_len,sizeof(int));
Free_Bip(tree);
Alloc_Bip(tree);
Get_Bip(tree->t_nodes[0],tree->t_nodes[0]->v[0],tree);
n_site = 0;
For(j,tree->data->crunch_len) For(k,tree->data->wght[j])
{
site_num[n_site] = j;
n_site++;
}
boot_data = Copy_Cseq(tree->data,tree->io);
if (Global_myRank == 0)
PhyML_Printf("\n. Non parametric bootstrap analysis \n");
//number of bootstraps for each process
if (tree->mod->bootstrap%Global_numTask != 0)
{
nbRep = (tree->mod->bootstrap / Global_numTask) + 1;
tree->mod->bootstrap = nbRep * Global_numTask;
if (Global_myRank == 0) {
PhyML_Printf("\n. The number of replicates is not a multiple of %d CPUs.\n", Global_numTask);
PhyML_Printf("\n. Will run %d replicates analysis.\n", tree->mod->bootstrap);
}
}
else
nbRep = tree->mod->bootstrap/Global_numTask;
//Bip score
if (Global_myRank == 0)
{
score_tot = (int *)mCalloc((2*tree->n_otu - 3),sizeof(int));
For(i,2*tree->n_otu-3)
score_tot[i] = 0;
}
else
score_tot = NULL;
score_par = (int *)mCalloc((2*tree->n_otu - 3),sizeof(int));
For(i,2*tree->n_otu-3)
score_par[i] = 0;
if (Global_myRank == 0)
PhyML_Printf("\n [");
For(replicate, nbRep)
{
For(j,boot_data->crunch_len) boot_data->wght[j] = 0;
// Send random data to other process
if (Global_myRank == 0) {
// Compute number of data to send
if (tree->mod->bootstrap - randomRecv > Global_numTask)
nbElem = Global_numTask;
else
nbElem = tree->mod->bootstrap - randomRecv;
For(i,nbElem) {
For(j,boot_data->crunch_len) boot_data->wght[j] = 0;
init_len = 0;
// Create random data
For(j,boot_data->init_len)
{
position = Rand_Int(0,(int)(tree->data->init_len-1.0));
boot_data->wght[site_num[position]] += 1;
init_len++;
}
if (init_len != tree->data->init_len) {
MPI_Finalize();
Warn_And_Exit("\n. Pb when copying sequences\n");
}
// Send random data to other process, not to current process
if (i < nbElem-1) {
MPI_Ssend (boot_data->wght, boot_data->crunch_len, MPI_INT, i+1, Global_myRank, MPI_COMM_WORLD);
#ifdef MPI_DEBUG
fprintf (stderr, "\ntask %d, sending random to %d done\n", Global_myRank, i+1);
fflush(stderr);
#endif
}
randomRecv++;
}
}
else {
MPI_Recv (boot_data->wght, boot_data->crunch_len, MPI_INT, 0, MPI_ANY_TAG, MPI_COMM_WORLD, &Stat);
#ifdef MPI_DEBUG
fprintf (stderr, "\ntask %d, receiving random from task %d done\n", Global_myRank, Stat.MPI_SOURCE);
fflush(stderr);
#endif
}
init_len = 0;
For(j,boot_data->crunch_len) init_len += boot_data->wght[j];
if(init_len != tree->data->init_len) {
MPI_Finalize();
Warn_And_Exit("\n. Pb when copying sequences\n");
}
(tree->mod->io->datatype == NT)?
(Get_Base_Freqs(boot_data)):
(Get_AA_Freqs(boot_data));
if(tree->io->random_boot_seq_order) Randomize_Sequence_Order(boot_data);
boot_mod = Copy_Model(tree->mod);
boot_mod->s_opt = tree->mod->s_opt; /* WARNING: re-using the same address here instead of creating a copying
requires to leave the value of s_opt unchanged during the boostrap. */
boot_mod->io = tree->io; /* WARNING: re-using the same address here instead of creating a copying
requires to leave the value of io unchanged during the boostrap. */
Init_Model(boot_data,boot_mod,tree->io);
if(tree->io->mod->use_m4mod) M4_Init_Model(boot_mod->m4mod,boot_data,boot_mod);
if(tree->io->in_tree == 2)
{
switch(tree->io->tree_file_format)
{
case PHYLIP:
{
rewind(tree->io->fp_in_tree);
boot_tree = Read_Tree_File_Phylip(tree->io->fp_in_tree);
break;
}
case NEXUS:
{
PhyML_Printf("\n. Unfortunately, PhyML cannot read NEXUS files and perform a bootstrap analysis.");
PhyML_Printf("\n. Please use the PHYLIP format..");
PhyML_Printf("\n. Err in file %s at line %d\n",__FILE__,__LINE__);
Warn_And_Exit("");
break;
}
default:
{
PhyML_Printf("\n. Err in file %s at line %d\n",__FILE__,__LINE__);
Warn_And_Exit("");
break;
}
}
}
else
{
boot_mat = ML_Dist(boot_data,boot_mod);
boot_mat->tree = Make_Tree_From_Scratch(boot_data->n_otu,boot_data);
Fill_Missing_Dist(boot_mat);
Bionj(boot_mat);
boot_tree = boot_mat->tree;
boot_tree->mat = boot_mat;
}
boot_tree->mod = boot_mod;
boot_tree->io = tree->io;
boot_tree->data = boot_data;
boot_tree->both_sides = 1;
boot_tree->mod->s_opt->print = 0;
boot_tree->n_pattern = boot_tree->data->crunch_len;
boot_tree->io->print_site_lnl = 0;
boot_tree->io->print_trace = 0;
if((boot_tree->mod->s_opt->random_input_tree) && (boot_tree->mod->s_opt->topo_search == SPR_MOVE)) Random_Tree(boot_tree);
Order_Tree_CSeq(boot_tree,boot_data);
Share_Lk_Struct(tree,boot_tree);
Share_Spr_Struct(tree,boot_tree);
Share_Pars_Struct(tree,boot_tree);
Fill_Dir_Table(boot_tree);
Update_Dirs(boot_tree);
if(tree->mod->s_opt->greedy) Init_P_Lk_Tips_Double(boot_tree);
else Init_P_Lk_Tips_Int(boot_tree);
Init_Ui_Tips(boot_tree);
Init_P_Pars_Tips(boot_tree);
Br_Len_Not_Involving_Invar(boot_tree);
if(boot_tree->mod->s_opt->opt_topo)
{
if(boot_tree->mod->s_opt->topo_search == NNI_MOVE)
{
Simu_Loop(boot_tree);
}
else if((boot_tree->mod->s_opt->topo_search == SPR_MOVE) ||
(boot_tree->mod->s_opt->topo_search == BEST_OF_NNI_AND_SPR))
{
Speed_Spr_Loop(boot_tree);
}
}
else
{
if(boot_tree->mod->s_opt->opt_subst_param || boot_tree->mod->s_opt->opt_bl)
Round_Optimize(boot_tree,boot_tree->data,ROUND_MAX);
else
Lk(boot_tree);
}
Free_Bip(boot_tree);
Alloc_Bip(boot_tree);
Match_Tip_Numbers(tree,boot_tree);
Get_Bip(boot_tree->t_nodes[0],
boot_tree->t_nodes[0]->v[0],
boot_tree);
Compare_Bip(tree,boot_tree,NO);
Br_Len_Involving_Invar(boot_tree);
if(tree->io->print_boot_trees)
{
s = Write_Tree(boot_tree,NO);
t=(char *)mCalloc(T_MAX_LINE,sizeof(char));
Print_Fp_Out_Lines_MPI(boot_tree, tree->io, replicate+1, t);
// Get bootstrap trees from other process and write to boot file
if (Global_myRank == 0) {
fprintf(tree->io->fp_out_boot_tree,"%s\n",s);
fprintf(tree->io->fp_out_boot_stats,"%s\n",t);
bootRecv++;
PhyML_Printf(".");
if(!((bootRecv)%tree->io->boot_prog_every))
{
PhyML_Printf("] %4d/%4d\n ",bootRecv,tree->mod->bootstrap);
if(bootRecv != tree->mod->bootstrap) PhyML_Printf("[");
}
// Compute number of bootstraps to receive
if (tree->mod->bootstrap - bootRecv > Global_numTask)
nbElem = Global_numTask;
else
nbElem = tree->mod->bootstrap - bootRecv + 1;
bootStr=(char *)mCalloc(T_MAX_LINE,sizeof(char));
for (i=1; iio->fp_out_boot_tree,"%s\n", bootStr);
if (Stat.MPI_TAG == BootStatTag)
fprintf(tree->io->fp_out_boot_stats,"%s\n", bootStr);
MPI_Recv (bootStr, T_MAX_LINE, MPI_CHAR, i, MPI_ANY_TAG, MPI_COMM_WORLD, &Stat);
#ifdef MPI_DEBUG
fprintf (stderr, "\ntask %d, receiving bootstrap from task %d tag %d done\n", Global_myRank, Stat.MPI_SOURCE, Stat.MPI_TAG);
fflush(stderr);
#endif
if (Stat.MPI_TAG == BootTreeTag)
fprintf(tree->io->fp_out_boot_tree,"%s\n", bootStr);
if (Stat.MPI_TAG == BootStatTag)
fprintf(tree->io->fp_out_boot_stats,"%s\n", bootStr);
bootRecv++;
PhyML_Printf(".");
if(!((bootRecv)%tree->io->boot_prog_every)) {
PhyML_Printf("] %4d/%4d\n ",bootRecv,tree->mod->bootstrap);
if(bootRecv != tree->mod->bootstrap) PhyML_Printf("[");
}
}
Free(bootStr);
}
else {
MPI_Ssend (s, T_MAX_LINE, MPI_CHAR, 0, BootTreeTag, MPI_COMM_WORLD);
MPI_Ssend (t, T_MAX_LINE, MPI_CHAR, 0, BootStatTag, MPI_COMM_WORLD);
#ifdef MPI_DEBUG
fprintf (stderr, "\ntask %d, sending bootstraps done\n", Global_myRank);
fflush(stderr);
#endif
}
Free (t);
Free(s);
}
#ifndef QUIET
fflush(stdout);
#endif
if(boot_tree->mat) Free_Mat(boot_tree->mat);
Free_Tree(boot_tree);
Free_Model(boot_mod);
//Each process computes the Bip score sum for all its bootstrap trees
For(i,2*tree->n_otu-3) score_par[i] = tree->t_edges[i]->bip_score;
//Each process sends its Bip score sum. The sums are summed.
MPI_Reduce(score_par, score_tot, 2*tree->n_otu - 3, MPI_INT, MPI_SUM, 0, MPI_COMM_WORLD);
}
if (Global_myRank == 0)
{
For(i,2*tree->n_otu-3)
tree->t_edges[i]->bip_score = score_tot[i];
Free (score_tot);
}
Free (score_par);
if (Global_myRank == 0)
if(((bootRecv)%tree->io->boot_prog_every)) PhyML_Printf("] %4d/%4d\n ",bootRecv,tree->mod->bootstrap);
tree->lock_topo = 1; /* TopoLOGy should not be modified afterwards */
if(tree->io->print_boot_trees)
{
fclose(tree->io->fp_out_boot_tree);
fclose(tree->io->fp_out_boot_stats);
}
Free_Cseq(boot_data);
Free(site_num);
}
/*********************************************************/
void Print_Fp_Out_Lines_MPI(t_tree *tree, option *io, int n_data_set, char *bootStr)
{
char *s, *tmp;
// Build a string to be sent to the writing process
s = (char *)mCalloc(T_MAX_LINE,sizeof(char));
tmp=(char *)mCalloc(T_MAX_LINE,sizeof(char));
if (Global_myRank == 0 && n_data_set == 1) {
snprintf(tmp, T_MAX_LINE, ". Sequence file : [%s]\n\n", Basename(io->in_align_file)); strncat (s, tmp, T_MAX_LINE);
(tree->mod->io->datatype == NT)?
(snprintf(tmp, T_MAX_LINE, ". Model of nucleotides substitution : %s\n\n", io->mod->modelname)):
(snprintf(tmp, T_MAX_LINE, ". Model of amino acids substitution : %s\n\n", io->mod->modelname));
strncat (s, tmp, T_MAX_LINE);
switch(io->in_tree)
{
case 0: { snprintf(tmp, T_MAX_LINE, ". Initial tree : [BioNJ]\n\n"); break; }
case 1: { snprintf(tmp, T_MAX_LINE, ". Initial tree : [parsimony]\n\n"); break; }
case 2: { snprintf(tmp, T_MAX_LINE, ". Initial tree : [%s]\n\n",io->in_tree_file); break; }
}
strncat (s, tmp, T_MAX_LINE);
strncat (s, "\n", T_MAX_LINE);
/*headline 1*/
strncat (s, ". Data\t", T_MAX_LINE);
strncat (s, "Nb of \t", T_MAX_LINE);
strncat (s, "Likelihood\t", T_MAX_LINE);
strncat (s, "Discrete \t", T_MAX_LINE);
if(tree->mod->n_catg > 1)
strncat (s, "Number of \tGamma shape\t", T_MAX_LINE);
strncat (s, "Proportion of\t", T_MAX_LINE);
if(tree->mod->whichmodel <= 6)
strncat (s, "Transition/ \t", T_MAX_LINE);
strncat (s, "Nucleotides frequencies \t", T_MAX_LINE);
if((tree->mod->whichmodel == GTR) ||
(tree->mod->whichmodel == CUSTOM))
strncat (s, "Instantaneous rate matrix \t", T_MAX_LINE);
strncat (s, "\n", T_MAX_LINE);
/*headline 2*/
strncat (s, " set\t", T_MAX_LINE);
strncat (s, "taxa\t", T_MAX_LINE);
strncat (s, "LOGlk \t", T_MAX_LINE);
strncat (s, "gamma model\t", T_MAX_LINE);
if(tree->mod->n_catg > 1)
strncat (s, "categories\tparameter \t", T_MAX_LINE);
strncat (s, "invariant \t", T_MAX_LINE);
if(tree->mod->whichmodel <= 6)
strncat (s, "transversion\t", T_MAX_LINE);
strncat (s, "f(A) f(C) f(G) f(T) \t", T_MAX_LINE);
if((tree->mod->whichmodel == GTR) ||
(tree->mod->whichmodel == CUSTOM))
strncat (s, "[A---------C---------G---------T------]\t", T_MAX_LINE);
strncat (s, "\n", T_MAX_LINE);
/*headline 3*/
if(tree->mod->whichmodel == TN93) {
strncat (s, " \t \t \t \t", T_MAX_LINE);
if(tree->mod->n_catg > 1)
strncat (s, " \t \t", T_MAX_LINE);
strncat (s, " \t", T_MAX_LINE);
strncat (s, "purines pyrimid.\t", T_MAX_LINE);
strncat (s, "\n", T_MAX_LINE);
}
strncat (s, "\n", T_MAX_LINE);
}
/*line items*/
snprintf(tmp, T_MAX_LINE, " #%d\t", (((n_data_set-1)*Global_numTask)+Global_myRank+1));
strncat (s, tmp, T_MAX_LINE);
snprintf(tmp, T_MAX_LINE, "%d \t",tree->n_otu); strncat (s, tmp, T_MAX_LINE);
snprintf(tmp, T_MAX_LINE, "%.5f\t",tree->c_lnL); strncat (s, tmp, T_MAX_LINE);
snprintf(tmp, T_MAX_LINE, "%s \t",
(tree->mod->n_catg>1)?("Yes"):("No ")); strncat (s, tmp, T_MAX_LINE);
if(tree->mod->n_catg > 1)
{
snprintf(tmp, T_MAX_LINE, "%d \t",tree->mod->n_catg); strncat (s, tmp, T_MAX_LINE);
snprintf(tmp, T_MAX_LINE, "%.3f \t",tree->mod->alpha->v); strncat (s, tmp, T_MAX_LINE);
}
snprintf(tmp, T_MAX_LINE, "%.3f \t",tree->mod->pinvar->v); strncat (s, tmp, T_MAX_LINE);
if(tree->mod->whichmodel <= 5)
{
snprintf(tmp, T_MAX_LINE, "%.3f \t",tree->mod->kappa->v); strncat (s, tmp, T_MAX_LINE);
}
else if(tree->mod->whichmodel == TN93)
{
snprintf(tmp, T_MAX_LINE, "%.3f ",
tree->mod->kappa->v*2.*tree->mod->lambda->v/(1.+tree->mod->lambda->v));
strncat (s, tmp, T_MAX_LINE);
snprintf(tmp, T_MAX_LINE, "%.3f\t",
tree->mod->kappa->v*2./(1.+tree->mod->lambda->v));
strncat (s, tmp, T_MAX_LINE);
}
if(tree->mod->io->datatype == NT)
{
snprintf(tmp, T_MAX_LINE, "%8.5f ",tree->mod->pi->v[0]); strncat (s, tmp, T_MAX_LINE);
snprintf(tmp, T_MAX_LINE, "%8.5f ",tree->mod->pi->v[1]); strncat (s, tmp, T_MAX_LINE);
snprintf(tmp, T_MAX_LINE, "%8.5f ",tree->mod->pi->v[2]); strncat (s, tmp, T_MAX_LINE);
snprintf(tmp, T_MAX_LINE, "%8.5f\t",tree->mod->pi->v[3]); strncat (s, tmp, T_MAX_LINE);
}
if((tree->mod->whichmodel == GTR) || (tree->mod->whichmodel == CUSTOM))
{
int i,j;
For(i,4)
{
if (i!=0) {
/*format*/
snprintf(tmp, T_MAX_LINE, " \t \t \t \t");
strncat (s, tmp, T_MAX_LINE);
if(tree->mod->n_catg > 1) {
snprintf(tmp, T_MAX_LINE, " \t \t");
strncat (s, tmp, T_MAX_LINE);
}
snprintf(tmp, T_MAX_LINE, " \t \t");
strncat (s, tmp, T_MAX_LINE);
}
For(j,4) {
snprintf(tmp, T_MAX_LINE, "%8.5f ",tree->mod->qmat->v[i*4+j]);
strncat (s, tmp, T_MAX_LINE);
}
if (i<3) {
snprintf(tmp, T_MAX_LINE, "\n");
strncat (s, tmp, T_MAX_LINE);
}
}
}
Free (tmp);
strncpy (bootStr, s, T_MAX_LINE);
Free (s);
return;
}
/* #endif */
phyml-20120412/src/mcmc.h 0000644 0001750 0001750 00000013171 11652341514 011705 0000000 0000000 /*
PhyML: a program that computes maximum likelihood phylogenies from
DNA or AA homologous sequences.
Copyright (C) Stephane Guindon. Oct 2003 onward.
All parts of the source except where indicated are distributed under
the GNU public licence. See http://www.opensource.org for details.
*/
#include
#ifndef MCMC_H
#define MCMC_H
#include "spr.h"
#include "utilities.h"
#include "lk.h"
#include "optimiz.h"
#include "bionj.h"
#include "models.h"
#include "free.h"
#include "help.h"
#include "simu.h"
#include "eigen.h"
#include "pars.h"
#include "alrt.h"
#include "times.h"
#include "m4.h"
#include "draw.h"
#include "rates.h"
#include "stats.h"
#include
#include
#include
#include
void MCMC_Lexp(t_tree *tree);
void MCMC_Print_Param(t_mcmc *mcmc, t_tree *tree);
t_mcmc *MCMC_Make_MCMC_Struct();
void MCMC_Free_MCMC(t_mcmc *mcmc);
void MCMC_Init_MCMC_Struct(char *filename, option *io,t_mcmc *mcmc);
void MCMC(t_tree *tree);
void MCMC_Alpha(t_tree *tree);
void MCMC_Randomize_Branch_Lengths(t_tree *tree);
void MCMC_Randomize_Node_Times(t_tree *tree);
void MCMC_Randomize_Node_Times_Pre(t_node *a, t_node *d, t_tree *tree);
void MCMC_Randomize_Lexp(t_tree *tree);
void MCMC_Randomize_Jumps(t_tree *tree);
void MCMC_Randomize_Alpha(t_tree *tree);
void MCMC_One_Rate(t_node *a, t_node *d, int traversal, t_tree *tree);
void MCMC_No_Change(t_tree *tree);
void MCMC_Nu(t_tree *tree);
void MCMC_Randomize_Nu(t_tree *tree);
t_node *MCMC_Select_Random_Node_Pair(phydbl t_sup, t_tree *tree);
void MCMC_Modify_Rates(t_tree *tree);
void MCMC_Modify_Subtree_Rate(t_node *a, t_node *d, phydbl new_rate, t_tree *tree);
void MCMC_Randomize_Rates(t_tree *tree);
void MCMC_Stick_Rates(t_tree *tree);
void MCMC_Stick_Rates_Pre(t_node *a, t_node *d, t_tree *tree);
void MCMC_Times_Global(t_tree *tree);
void MCMC_Times_Local(t_tree *tree);
void MCMC_One_Time(t_node *a, t_node *d, int traversal, t_tree *tree);
void MCMC_Rates_Global(t_tree *tree);
void MCMC_Rates_Local(t_tree *tree);
void MCMC_Rates_Pre(t_node *a, t_node *d, t_tree *tree);
void MCMC_Mixing_Step(t_tree *tree);
void MCMC_Jumps_Local(t_tree *tree);
void MCMC_Jumps_Pre(t_node *a, t_node *d, int local, t_tree *tree);
void MCMC_Randomize_Clock_Rate(t_tree *tree);
void MCMC_Clock_Rate(t_tree *tree);
void MCMC_Time_Root(t_tree *tree);
void MCMC_Randomize_Node_Times_Bottom_Up(t_node *a, t_node *d, t_tree *tree);
void MCMC_Randomize_Node_Times_Top_Down(t_node *a, t_node *d, t_tree *tree);
void MCMC_Randomize_Rates_Pre(t_node *a, t_node *d, t_tree *tree);
void MCMC_Print_Means(t_mcmc *mcmc, t_tree *tree);
void MCMC_Print_Last(t_mcmc *mcmc, t_tree *tree);
void MCMC_Close_MCMC(t_mcmc *mcmc);
void MCMC_Rates_Global(t_tree *tree);
void MCMC_Omega(t_tree *tree);
void MCMC_Adjust_Tuning_Parameter(int move, t_mcmc *mcmc);
void MCMC_Copy_MCMC_Struct(t_mcmc *ori, t_mcmc *cpy, char *filename);
void MCMC_Randomize_Node_Times_Bottom_Up(t_node *a, t_node *d, t_tree *tree);
void MCMC_One_Length(t_edge *b, t_tree *tree);
void MCMC_Br_Lens(t_tree *tree);
void MCMC_Br_Lens_Pre(t_node *a, t_node *d, t_edge *b, t_tree *tree);
void MCMC_Tree_Height(t_tree *tree);
void MCMC_Subtree_Height(t_tree *tree);
void MCMC_Swing(t_tree *tree);
void MCMC_Single_Param_Generic(phydbl *val,
phydbl lim_inf,
phydbl lim_sup,
int move_num,
phydbl *lnPrior,
phydbl *lnLike,
phydbl (*prior_func)(t_edge *,t_tree *,supert_tree *),
phydbl (*like_func)(t_edge *,t_tree *,supert_tree *),
int move_type, int _log,
t_edge *branch, t_tree *tree, supert_tree *stree);
void MCMC_Scale_Br_Lens(t_tree *tree);
void MCMC_Update_Mean_Br_Len(t_tree *tree);
void MCMC_Update_Cov_Br_Len(t_tree *tree);
void MCMC_Sim_Rate(t_node *a, t_node *d, t_tree *tree);
void Fill_All_Param(t_mcmc *mcmc, t_rate *rate, t_tree *tree);
int Get_Param_Num(t_mcmc *mcmc, phydbl *param);
void MCMC_Complete_MCMC(t_mcmc *mcmc, t_tree *tree);
void MCMC_Sample_Joint_Rates_Prior(t_tree *tree);
void MCMC_Sample_Joint_Rates_Posterior(t_tree *tree);
void MCMC_Pair_Rates_Constraint(t_node *a, t_node *d, int random, int traversal, t_tree *tree);
void MCMC_Times_And_Rates(t_node *a, t_node *d, int random, int traversal, t_tree *tree);
void MCMC_Tree_Rates(t_tree *tree);
void MCMC_Pause(t_mcmc *mcmc);
void MCMC_Print_Param_Stdin(t_mcmc *mcmc, t_tree *tree);
void MCMC_Subtree_Rates(t_tree *tree);
void MCMC_Get_Acc_Rates(t_mcmc *mcmc);
void MCMC_Update_Effective_Sample_Size(int move_num, t_mcmc *mcmc, t_tree *tree);
void MCMC_Initialize_Param_Val(t_mcmc *mcmc, t_tree *tree);
void MCMC_Terminate();
void MCMC_Copy_To_New_Param_Val(t_mcmc *mcmc, t_tree *tree);
void MCMC_Randomize_Node_Rates(t_tree *tree);
void MCMC_One_Node_Rate(t_node *a, t_node *d, int traversal, t_tree *tree);
void MCMC_Tree_Rates_Bis(t_tree *tree);
void MCMC_Slice_One_Rate(t_node *a, t_node *d, int traversal, t_tree *tree);
void MCMC_Updown_Nu_Cr(t_tree *tree);
void MCMC_All_Rates(t_tree *tree);
void MCMC_Alpha(t_tree *tree);
void MCMC_Kappa(t_tree *tree);
void MCMC_Rate_Across_Sites(t_tree *tree);
void MCMC_Free_Mixt_Rate(t_tree *tree);
void MCMC_Make_Move(phydbl *cur, phydbl *new, phydbl inf, phydbl sup, phydbl *loghr, phydbl tune, int move_type);
void MCMC_Randomize_Rate_Across_Sites(t_tree *tree);
void MCMC_Randomize_Kappa(t_tree *tree);
void MCMC_Updown_T_Cr(t_tree *tree);
void MCMC_Linreg_Par(t_tree *tree);
void MCMC_Covarion_Rates(t_tree *tree);
void MCMC_Covarion_Switch(t_tree *tree);
void MCMC_Randomize_Covarion_Rates(t_tree *tree);
void MCMC_Randomize_Covarion_Switch(t_tree *tree);
void MCMC_Read_Param_Vals(t_tree *tree);
void MCMC_Birth_Rate(t_tree *tree);
void MCMC_Randomize_Birth(t_tree *tree);
#endif
phyml-20120412/src/mcmc.c 0000644 0001750 0001750 00000341154 11731754431 011711 0000000 0000000 /*
PhyML: a program that computes maximum likelihood phylogenies from
DNA or AA homoLOGous sequences.
Copyright (C) Stephane Guindon. Oct 2003 onward.
All parts of the source except where indicated are distributed under
the GNU public licence. See http://www.opensource.org for details.
*/
#include "mcmc.h"
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void MCMC(t_tree *tree)
{
int move;
phydbl u;
int first,secod;
int i;
RATES_Set_Clock_And_Nu_Max(tree);
RATES_Set_Birth_Rate_Boundaries(tree);
if(tree->mcmc->randomize == YES)
{
MCMC_Randomize_Birth(tree);
MCMC_Randomize_Nu(tree);
MCMC_Randomize_Node_Times(tree);
MCMC_Sim_Rate(tree->n_root,tree->n_root->v[0],tree);
MCMC_Sim_Rate(tree->n_root,tree->n_root->v[1],tree);
MCMC_Randomize_Node_Rates(tree);
MCMC_Randomize_Clock_Rate(tree); /* Clock Rate must be the last parameter to be randomized */
MCMC_Randomize_Rate_Across_Sites(tree);
MCMC_Randomize_Kappa(tree);
MCMC_Randomize_Covarion_Rates(tree);
MCMC_Randomize_Covarion_Switch(tree);
}
else
{
MCMC_Read_Param_Vals(tree);
}
tree->mod->update_eigen = YES;
MCMC_Initialize_Param_Val(tree->mcmc,tree);
Update_Ancestors(tree->n_root,tree->n_root->v[0],tree);
Update_Ancestors(tree->n_root,tree->n_root->v[1],tree);
For(i,2*tree->n_otu-2) tree->rates->br_do_updt[i] = YES;
RATES_Update_Cur_Bl(tree);
RATES_Lk_Rates(tree);
TIMES_Lk_Times(tree);
tree->both_sides = NO;
if(tree->mcmc->use_data) Lk(tree);
else tree->c_lnL = 0.0;
tree->mod->update_eigen = NO;
MCMC_Print_Param(tree->mcmc,tree);
//////////////////
if(tree->io->mutmap == YES)
{
int j;
char *s,*t;
FILE *fp;
Make_Ancestral_Seq(tree);
Make_MutMap(tree);
For(j,tree->n_otu)
{
s = (char *)mCalloc(T_MAX_NAME,sizeof(char));
strcpy(s,tree->t_nodes[j]->name);
tree->t_nodes[j]->name = s;
}
s = (char *)mCalloc(T_MAX_NAME,sizeof(char));
t = (char *)mCalloc(T_MAX_NAME,sizeof(char));
tree->write_tax_names = YES;
For(i,tree->n_pattern)
{
For(j,tree->n_otu)
{
strcpy(t,tree->t_nodes[j]->name);
s[0]=tree->data->c_seq[j]->state[i];
s[1]='\0';
strcat(s,"--");
sprintf(s+strlen(s),"%.0f",tree->rates->nd_t[j]);
/* strcat(s,tree->t_nodes[j]->name); */
strcpy(tree->t_nodes[j]->name,s);
}
strcpy(s,"rosettatree.");
sprintf(s+strlen(s),"%d",i);
fp = fopen(s,"w");
s = Write_Tree(tree,NO);
PhyML_Fprintf(fp,"%s",s);
fclose(fp);
For(j,tree->n_otu) strcpy(tree->t_nodes[j]->name,t);
}
Free(s);
Free(t);
}
first = 0;
secod = 1;
do
{
/* if(tree->mcmc->ess[tree->mcmc->num_move_tree_height] > 100 && */
/* tree->mcmc->ess[tree->mcmc->num_move_nu] > 100 && */
/* tree->mcmc->ess[tree->mcmc->num_move_clock_r] > 100 && */
/* tree->mcmc->run > 1000) */
/* { */
/* FILE *fp; */
/* char *s; */
/* s = (char *)mCalloc(100,sizeof(char)); */
/* sprintf(s,"simul_par.%d",getpid()); */
/* fclose(tree->mcmc->out_fp_stats); */
/* tree->mcmc->out_fp_stats = fopen(s,"w"); */
/* tree->mcmc->run = 0; */
/* tree->mcmc->nd_t_digits = 4; */
/* MCMC_Print_Param(tree->mcmc,tree); */
/* RATES_Update_Cur_Bl(tree); */
/* printf("\n. %s",Write_Tree(tree,NO)); */
/* Evolve(tree->data,tree->mod,tree); */
/* sprintf(s,"simul_seq.%d",getpid()); */
/* fp = fopen(s,"w"); */
/* Print_CSeq(fp,NO,tree->data); */
/* fflush(NULL); */
/* fclose(fp); */
/* Free(s); */
/* Exit("\n"); */
/* } */
/* if(tree->mcmc->ess[tree->mcmc->num_move_tree_height] > 100 && */
/* tree->mcmc->ess[tree->mcmc->num_move_nu] > 100 && */
/* tree->mcmc->ess[tree->mcmc->num_move_clock_r] > 100 && */
/* tree->mcmc->run > 1000) */
/* { */
/* FILE *fp; */
/* char *s,*t; */
/* s = (char *)mCalloc(100,sizeof(char)); */
/* t = strrchr(tree->io->in_align_file,'.'); */
/* sprintf(s,"res%s",t); */
/* fp = fopen(s,"w"); */
/* fclose(tree->mcmc->out_fp_stats); */
/* tree->mcmc->out_fp_stats = fopen(s,"w"); */
/* tree->mcmc->run = 0; */
/* MCMC_Print_Param(tree->mcmc,tree); */
/* fclose(fp); */
/* Free(s); */
/* Exit("\n"); */
/* } */
u = Uni();
For(move,tree->mcmc->n_moves) if(tree->mcmc->move_weight[move] > u) break;
if(u < .5) { first = 0; secod = 1; }
else { first = 1; secod = 0; }
phydbl cur_lnL;
cur_lnL = tree->c_lnL;
/* printf("\n. [%15s] %15f ",tree->mcmc->move_name[move],tree->c_lnL); */
/* Clock rate */
if(!strcmp(tree->mcmc->move_name[move],"clock"))
{
For(i,2*tree->n_otu-2) tree->rates->br_do_updt[i] = YES;
MCMC_Single_Param_Generic(&(tree->rates->clock_r),tree->rates->min_clock,tree->rates->max_clock,move,
NULL,&(tree->c_lnL),
NULL,Wrap_Lk,tree->mcmc->move_type[move],NO,NULL,tree,NULL);
}
/* Nu */
else if(!strcmp(tree->mcmc->move_name[move],"nu"))
{
For(i,2*tree->n_otu-2) tree->rates->br_do_updt[i] = YES;
MCMC_Nu(tree);
}
/* Tree height */
else if(!strcmp(tree->mcmc->move_name[move],"tree_height"))
{
MCMC_Tree_Height(tree);
}
/* Subtree height */
else if(!strcmp(tree->mcmc->move_name[move],"subtree_height"))
{
MCMC_Subtree_Height(tree);
}
/* Subtree rates */
else if(!strcmp(tree->mcmc->move_name[move],"subtree_rates"))
{
MCMC_Subtree_Rates(tree);
}
/* Birth rate */
else if(!strcmp(tree->mcmc->move_name[move],"birth_rate"))
{
MCMC_Birth_Rate(tree);
}
/* Swing rates */
else if(!strcmp(tree->mcmc->move_name[move],"tree_rates"))
{
MCMC_Tree_Rates(tree);
}
else if(!strcmp(tree->mcmc->move_name[move],"updown_nu_cr"))
{
MCMC_Updown_Nu_Cr(tree);
}
else if(!strcmp(tree->mcmc->move_name[move],"updown_t_cr"))
{
MCMC_Updown_T_Cr(tree);
}
/* Ts/tv ratio */
else if(!strcmp(tree->mcmc->move_name[move],"kappa"))
{
MCMC_Kappa(tree);
}
/* Gamma shape parameter */
else if(!strcmp(tree->mcmc->move_name[move],"ras"))
{
MCMC_Rate_Across_Sites(tree);
}
/* Covarion model parameters */
else if(!strcmp(tree->mcmc->move_name[move],"cov_rates"))
{
MCMC_Covarion_Rates(tree);
}
/* Covarion model parameters */
else if(!strcmp(tree->mcmc->move_name[move],"cov_switch"))
{
MCMC_Covarion_Switch(tree);
}
/* Times */
else if(!strcmp(tree->mcmc->move_name[move],"time"))
{
tree->both_sides = YES;
if(tree->mcmc->use_data == YES) Lk(tree);
tree->both_sides = NO;
if(tree->mcmc->is == NO || tree->rates->model_log_rates == YES)
{
MCMC_One_Time(tree->n_root,tree->n_root->v[first],YES,tree);
MCMC_One_Time(tree->n_root,tree->n_root->v[secod],YES,tree);
}
else
{
/* MCMC_One_Time(tree->n_root,tree->n_root->v[first],YES,tree); */
/* MCMC_One_Time(tree->n_root,tree->n_root->v[secod],YES,tree); */
RATES_Posterior_One_Time(tree->n_root,tree->n_root->v[first],YES,tree);
RATES_Posterior_One_Time(tree->n_root,tree->n_root->v[secod],YES,tree);
}
}
/* Node Rates */
else if(!strcmp(tree->mcmc->move_name[move],"nd_rate"))
{
MCMC_One_Node_Rate(tree->n_root,tree->n_root->v[first],YES,tree);
MCMC_One_Node_Rate(tree->n_root,tree->n_root->v[secod],YES,tree);
}
/* Edge Rates */
else if(!strcmp(tree->mcmc->move_name[move],"br_rate"))
{
tree->both_sides = YES;
if(tree->mcmc->use_data == YES) Lk(tree);
tree->both_sides = NO;
if(tree->mcmc->is == NO)
{
/* MCMC_Slice_One_Rate(tree->n_root,tree->n_root->v[first],YES,tree); */
/* MCMC_Slice_One_Rate(tree->n_root,tree->n_root->v[secod],YES,tree); */
MCMC_One_Rate(tree->n_root,tree->n_root->v[first],YES,tree);
MCMC_One_Rate(tree->n_root,tree->n_root->v[secod],YES,tree);
}
else
{
RATES_Posterior_One_Rate(tree->n_root,tree->n_root->v[first],YES,tree);
RATES_Posterior_One_Rate(tree->n_root,tree->n_root->v[secod],YES,tree);
}
/* MCMC_Sim_Rate(tree->n_root,tree->n_root->v[0],tree); */
/* MCMC_Sim_Rate(tree->n_root,tree->n_root->v[1],tree); */
/* if(tree->mcmc->use_data == YES) Lk(tree); */
/* RATES_Lk_Rates(tree); */
}
tree->mcmc->run++;
MCMC_Get_Acc_Rates(tree->mcmc);
MCMC_Print_Param(tree->mcmc,tree);
MCMC_Print_Param_Stdin(tree->mcmc,tree);
if(tree->io->mutmap == YES)
{
if(!(tree->mcmc->run%tree->mcmc->sample_interval))
{
Sample_Ancestral_Seq(YES,!tree->mcmc->use_data,tree);
phydbl sum = 0.0;
int edge,site,mut;
char *s;
FILE *fp;
s = (char *)mCalloc(T_MAX_NAME,sizeof(char));
strcpy(s,tree->mcmc->io->in_align_file);
strcat(s,"_");
strcat(s,tree->mcmc->out_filename);
strcat(s,".mutmap");
fp = fopen(s,"w");
Free(s);
For(i,(2*tree->n_otu-3)*(tree->n_pattern)*6) sum += tree->mutmap[i];
PhyML_Fprintf(fp,"edge\t site\t mut\t count");
For(i,(2*tree->n_otu-3)*(tree->n_pattern)*6)
{
Get_Mutmap_Coord(i,&edge,&site,&mut,tree);
PhyML_Fprintf(fp,"\n%4d\t %4d\t %4d\t %10f",edge,site,mut,(phydbl)tree->mutmap[i]/sum);
}
fclose(fp);
}
}
(void)signal(SIGINT,MCMC_Terminate);
}
while(tree->mcmc->run < tree->mcmc->chain_len);
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void MCMC_Single_Param_Generic(phydbl *val,
phydbl lim_inf,
phydbl lim_sup,
int move_num,
phydbl *lnPrior,
phydbl *lnLike,
phydbl (*prior_func)(t_edge *,t_tree *,supert_tree *),
phydbl (*like_func)(t_edge *,t_tree *,supert_tree *),
int move_type,
int _log, /* _log == YES: the model describes the distribution of log(val) but the move applies to val. Need a correction factor */
t_edge *branch, t_tree *tree, supert_tree *stree)
{
phydbl cur_val,new_val,new_lnLike,new_lnPrior,cur_lnLike,cur_lnPrior;
phydbl u,alpha,ratio;
phydbl K,mult;
phydbl new_lnval, cur_lnval;
Record_Br_Len(tree);
cur_val = *val;
new_val = -1.0;
ratio = 0.0;
mult = -1.0;
K = tree->mcmc->tune_move[move_num];
cur_lnval = LOG(*val);
new_lnval = cur_lnval;
if(lnLike)
{
cur_lnLike = *lnLike;
new_lnLike = *lnLike;
}
else
{
cur_lnLike = 0.0;
new_lnLike = 0.0;
}
if(lnPrior)
{
cur_lnPrior = *lnPrior;
new_lnPrior = *lnPrior;
}
else
{
cur_lnPrior = 0.0;
new_lnPrior = 0.0;
}
MCMC_Make_Move(&cur_val,&new_val,lim_inf,lim_sup,&ratio,K,move_type);
if(new_val < lim_sup && new_val > lim_inf)
{
*val = new_val;
RATES_Update_Cur_Bl(tree);
if(_log == YES) ratio += (cur_lnval - new_lnval);
if(prior_func) /* Prior ratio */
{
new_lnPrior = (*prior_func)(branch,tree,stree);
ratio += (new_lnPrior - cur_lnPrior);
}
if(like_func && tree->mcmc->use_data == YES) /* Likelihood ratio */
{
new_lnLike = (*like_func)(branch,tree,stree);
ratio += (new_lnLike - cur_lnLike);
}
ratio = EXP(ratio);
alpha = MIN(1.,ratio);
u = Uni();
if(u > alpha) /* Reject */
{
*val = cur_val;
new_val = cur_val;
if(lnPrior) *lnPrior = cur_lnPrior;
if(lnLike) *lnLike = cur_lnLike;
Restore_Br_Len(tree);
if(tree->mod->update_eigen) Update_Eigen(tree->mod);
}
else /* Accept */
{
tree->mcmc->acc_move[move_num]++;
if(lnPrior) *lnPrior = new_lnPrior;
if(lnLike) *lnLike = new_lnLike;
}
}
tree->mcmc->run_move[move_num]++;
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void MCMC_Update_Effective_Sample_Size(int move_num, t_mcmc *mcmc, t_tree *tree)
{
phydbl new_val,cur_val;
mcmc->ess_run[move_num]++;
new_val = mcmc->new_param_val[move_num];
cur_val = mcmc->old_param_val[move_num];
if(mcmc->ess_run[move_num] == 1)
{
mcmc->first_val[move_num] = cur_val;
mcmc->sum_val[move_num] = cur_val;
mcmc->sum_valsq[move_num] = POW(cur_val,2);
return;
}
mcmc->sum_val[move_num] += new_val;
mcmc->sum_valsq[move_num] += POW(new_val,2);
mcmc->sum_curval_nextval[move_num] += cur_val * new_val;
mcmc->ess[move_num] =
Effective_Sample_Size(mcmc->first_val[move_num],
new_val,
mcmc->sum_val[move_num],
mcmc->sum_valsq[move_num],
mcmc->sum_curval_nextval[move_num],
mcmc->ess_run[move_num]);
mcmc->old_param_val[move_num] = new_val;
if(move_num == mcmc->num_move_nd_t+tree->n_root->num-tree->n_otu)
{
/* FILE *fp; */
/* fp = fopen("out","a"); */
/* fprintf(fp,"%f\n",new_val); */
/* fclose(fp); */
/* printf("\n. first=%G last=%G sum=%f sum_valsq=%f sum_cur_next=%f run=%d ess=%f", */
/* mcmc->first_val[move_num],new_val, */
/* mcmc->sum_val[move_num], */
/* mcmc->sum_valsq[move_num], */
/* mcmc->sum_curval_nextval[move_num], */
/* mcmc->run_move[move_num]+1, */
/* mcmc->ess[move_num] */
/* ); */
}
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void MCMC_Sample_Joint_Rates_Prior(t_tree *tree)
{
int i,dim;
phydbl T;
phydbl *r,*t,*lambda;
phydbl *min_r,*max_r;
phydbl k;
dim = 2*tree->n_otu-2;
lambda = tree->rates->_2n_vect1;
min_r = tree->rates->_2n_vect2;
max_r = tree->rates->_2n_vect3;
r = tree->rates->br_r;
t = tree->rates->nd_t;
For(i,dim) tree->rates->mean_r[i] = 1.0;
RATES_Fill_Lca_Table(tree);
RATES_Covariance_Mu(tree);
T = .0;
For(i,dim) T += (t[tree->t_nodes[i]->num] - t[tree->t_nodes[i]->anc->num]);
For(i,dim) lambda[i] = (t[tree->t_nodes[i]->num] - t[tree->t_nodes[i]->anc->num])/T;
For(i,dim) r[i] = 1.0;
For(i,dim) min_r[i] = tree->rates->min_rate;
For(i,dim) max_r[i] = tree->rates->max_rate;
k = 1.; /* We want \sum_i lambda[i] r[i] = 1 */
Rnorm_Multid_Trunc_Constraint(tree->rates->mean_r,
tree->rates->cov_r,
min_r,max_r,
lambda,
k,
r,
dim);
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void MCMC_One_Rate(t_node *a, t_node *d, int traversal, t_tree *tree)
{
t_edge *b;
int i;
phydbl u;
phydbl new_lnL_data, cur_lnL_data, new_lnL_rate, cur_lnL_rate;
phydbl ratio, alpha;
phydbl new_mu, cur_mu;
phydbl r_min, r_max;
phydbl K;
t_edge *b1,*b2,*b3;
t_node *v2,*v3;
phydbl nu,cr;
if(tree->rates->model == STRICTCLOCK) return;
b = NULL;
if(a == tree->n_root) b = tree->e_root;
else
For(i,3) if(d->v[i] == a) { b = d->b[i]; break; }
cur_mu = tree->rates->br_r[d->num];
cur_lnL_data = tree->c_lnL;
new_lnL_data = tree->c_lnL;
cur_lnL_rate = tree->rates->c_lnL_rates;
new_lnL_rate = tree->rates->c_lnL_rates;
r_min = tree->rates->min_rate;
r_max = tree->rates->max_rate;
K = tree->mcmc->tune_move[tree->mcmc->num_move_br_r+d->num];
ratio = 0.0;
nu = tree->rates->nu;
cr = tree->rates->clock_r;
Record_Br_Len(tree);
u = Uni();
/* MCMC_Make_Move(&cur_mu,&new_mu,r_min,r_max,&ratio,K,tree->mcmc->move_type[tree->mcmc->num_move_br_r+d->num]); */
phydbl dt,sd,mean;
int err;
dt = tree->rates->nd_t[d->num] - tree->rates->nd_t[a->num];
sd = SQRT(tree->rates->nu * dt);
mean = tree->rates->br_r[a->num] - 0.5*sd*sd;
new_mu = Rnorm_Trunc(mean,sd,r_min,r_max,&err);
ratio = Log_Dnorm_Trunc(cur_mu,mean,sd,r_min,r_max,&err) - Log_Dnorm_Trunc(new_mu,mean,sd,r_min,r_max,&err);
if(new_mu > r_min && new_mu < r_max)
{
tree->rates->br_r[d->num] = new_mu;
v2 = v3 = NULL;
For(i,3)
if((d->v[i] != a) && (d->b[i] != tree->e_root))
{
if(!v2) { v2 = d->v[i]; }
else { v3 = d->v[i]; }
}
b1 = NULL;
if(a == tree->n_root) b1 = tree->e_root;
else For(i,3) if(d->v[i] == a) { b1 = d->b[i]; break; }
b2 = b3 = NULL;
if(!d->tax)
{
For(i,3)
if((d->v[i] != a) && (d->b[i] != tree->e_root))
{
if(!b2) { b2 = d->b[i]; }
else { b3 = d->b[i]; }
}
}
tree->rates->br_do_updt[d->num] = YES;
if(!d->tax)
{
tree->rates->br_do_updt[v2->num] = YES;
tree->rates->br_do_updt[v3->num] = YES;
}
RATES_Update_Cur_Bl(tree);
/* printf("\n. r0=%f r1=%f cr=%f mean=%f var=%f nu=%f dt=%f", */
/* r0,r1,tree->rates->clock_r,b1->gamma_prior_mean,b1->gamma_prior_var,nu,t1-t0); */
if(tree->mcmc->use_data)
{
if(tree->io->lk_approx == EXACT)
{
Update_PMat_At_Given_Edge(b1,tree);
if(!d->tax)
{
Update_PMat_At_Given_Edge(b2,tree);
Update_PMat_At_Given_Edge(b3,tree);
}
Update_P_Lk(tree,b1,d);
}
new_lnL_data = Lk_At_Given_Edge(b1,tree);
/* tree->both_sides = NO; */
/* new_lnL_data = Lk(tree); */
}
new_lnL_rate = RATES_Lk_Rates(tree);
/* Likelihood ratio */
if(tree->mcmc->use_data) ratio += (new_lnL_data - cur_lnL_data);
/* Prior ratio */
ratio += (new_lnL_rate - cur_lnL_rate);
ratio = EXP(ratio);
alpha = MIN(1.,ratio);
u = Uni();
if(u > alpha) /* Reject */
{
tree->rates->br_r[d->num] = cur_mu;
tree->c_lnL = cur_lnL_data;
tree->rates->c_lnL_rates = cur_lnL_rate;
Restore_Br_Len(tree);
if(tree->mcmc->use_data && tree->io->lk_approx == EXACT)
{
Update_PMat_At_Given_Edge(b1,tree);
if(!d->tax)
{
Update_PMat_At_Given_Edge(b2,tree);
Update_PMat_At_Given_Edge(b3,tree);
}
Update_P_Lk(tree,b1,d);
}
/* tree->both_sides = YES; */
/* new_lnL_data = Lk(tree); */
/* tree->both_sides = NO; */
}
else
{
tree->mcmc->acc_move[tree->mcmc->num_move_br_r+d->num]++;
}
}
tree->mcmc->run_move[tree->mcmc->num_move_br_r+d->num]++;
if(traversal == YES)
{
if(d->tax == YES) return;
else
{
For(i,3)
if(d->v[i] != a && d->b[i] != tree->e_root)
{
if(tree->io->lk_approx == EXACT && tree->mcmc->use_data) Update_P_Lk(tree,d->b[i],d);
/* if(tree->io->lk_approx == EXACT && tree->mcmc->use_data) {tree->both_sides = YES; Lk(tree); } */
MCMC_One_Rate(d,d->v[i],YES,tree);
}
}
if(tree->io->lk_approx == EXACT && tree->mcmc->use_data) Update_P_Lk(tree,b,d);
/* if(tree->io->lk_approx == EXACT && tree->mcmc->use_data) {tree->both_sides = YES; Lk(tree); } */
}
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void MCMC_One_Node_Rate(t_node *a, t_node *d, int traversal, t_tree *tree)
{
t_edge *b;
int i;
b = NULL;
if(a == tree->n_root) b = tree->e_root;
else
For(i,3) if(d->v[i] == a) { b = d->b[i]; break; }
/* Only the LOG_RANDWALK move seems to work here. Change with caution then. */
tree->rates->br_do_updt[d->num] = YES;
MCMC_Single_Param_Generic(&(tree->rates->nd_r[d->num]),
tree->rates->min_rate,
tree->rates->max_rate,
tree->mcmc->num_move_nd_r+d->num,
&(tree->rates->c_lnL_rates),NULL,
Wrap_Lk_Rates,NULL,
tree->mcmc->move_type[tree->mcmc->num_move_nd_r+d->num],
NO,NULL,tree,NULL);
Update_PMat_At_Given_Edge(b,tree);
if(traversal == YES)
{
if(d->tax == YES) return;
else
{
For(i,3)
if(d->v[i] != a && d->b[i] != tree->e_root)
{
MCMC_One_Node_Rate(d,d->v[i],YES,tree);
}
}
}
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void MCMC_One_Time(t_node *a, t_node *d, int traversal, t_tree *tree)
{
phydbl u;
phydbl t_min,t_max;
phydbl t1_cur, t1_new;
phydbl cur_lnL_data, new_lnL_data;
phydbl cur_lnL_rate, new_lnL_rate;
phydbl cur_lnL_time, new_lnL_time;
phydbl ratio,alpha;
t_edge *b1,*b2,*b3;
int i;
phydbl t0,t2,t3;
t_node *v2,*v3;
phydbl K;
int move_num;
if(d->tax) return; /* Won't change time at tip */
if(d == tree->n_root) return; /* Won't change time at root. Use tree height move instead */
if(FABS(tree->rates->t_prior_min[d->num] - tree->rates->t_prior_max[d->num]) < 1.E-10) return;
Record_Br_Len(tree);
RATES_Record_Rates(tree);
RATES_Record_Times(tree);
move_num = d->num-tree->n_otu+tree->mcmc->num_move_nd_t;
K = tree->mcmc->tune_move[move_num];
cur_lnL_data = tree->c_lnL;
cur_lnL_rate = tree->rates->c_lnL_rates;
t1_cur = tree->rates->nd_t[d->num];
new_lnL_data = cur_lnL_data;
new_lnL_rate = cur_lnL_rate;
ratio = 0.0;
cur_lnL_time = tree->rates->c_lnL_times;
new_lnL_time = cur_lnL_time;
v2 = v3 = NULL;
For(i,3)
if((d->v[i] != a) && (d->b[i] != tree->e_root))
{
if(!v2) { v2 = d->v[i]; }
else { v3 = d->v[i]; }
}
b1 = NULL;
if(a == tree->n_root) b1 = tree->e_root;
else For(i,3) if(d->v[i] == a) { b1 = d->b[i]; break; }
b2 = b3 = NULL;
For(i,3)
if((d->v[i] != a) && (d->b[i] != tree->e_root))
{
if(!b2) { b2 = d->b[i]; }
else { b3 = d->b[i]; }
}
t0 = (a)?(tree->rates->nd_t[a->num]):(tree->rates->t_prior_min[d->num]);
t2 = tree->rates->nd_t[v2->num];
t3 = tree->rates->nd_t[v3->num];
t_min = MAX(t0,tree->rates->t_prior_min[d->num]);
t_max = MIN(MIN(t2,t3),tree->rates->t_prior_max[d->num]);
t_min += tree->rates->min_dt;
t_max -= tree->rates->min_dt;
if(t_min > t_max)
{
PhyML_Printf("\n. t_min = %f t_max = %f",t_min,t_max);
PhyML_Printf("\n. prior_min = %f prior_max = %f",tree->rates->t_prior_min[d->num],tree->rates->t_prior_max[d->num]);
PhyML_Printf("\n. Err in file %s at line %d\n",__FILE__,__LINE__);
/* Exit("\n"); */
}
MCMC_Make_Move(&t1_cur,&t1_new,t_min,t_max,&ratio,K,tree->mcmc->move_type[move_num]);
if(t1_new > t_min && t1_new < t_max)
{
tree->rates->nd_t[d->num] = t1_new;
/* Update branch lengths */
tree->rates->br_do_updt[d->num] = YES;
tree->rates->br_do_updt[v2->num] = YES;
tree->rates->br_do_updt[v3->num] = YES;
RATES_Update_Cur_Bl(tree);
if(tree->mcmc->use_data)
{
if(tree->io->lk_approx == EXACT)
{
Update_PMat_At_Given_Edge(b1,tree);
Update_PMat_At_Given_Edge(b2,tree);
Update_PMat_At_Given_Edge(b3,tree);
Update_P_Lk(tree,b1,d);
}
new_lnL_data = Lk_At_Given_Edge(b1,tree);
/* /\* !!!!!!!!!!!!!!!!!!!!1 *\/ */
/* if(FABS(Lk(tree) - new_lnL_data) > 1.E-5) */
/* { */
/* PhyML_Printf("\n. b1->l=%f b2->l=%f b3->l=%f",b1->l,b2->l,b3->l); */
/* PhyML_Printf("\n. a->num=%d d->num=%d root=%d (%d %d)",a->num,d->num,a==tree->n_root,tree->n_root->v[0]->num,tree->n_root->v[1]->num); */
/* PhyML_Printf("\n. t_min=%f t_max=%f",t_min,t_max); */
/* PhyML_Printf("\n. t1_new=%f t1_cur=%f",t1_new,t1_cur); */
/* PhyML_Printf("\n. %f %f",cur_lnL_data,tree->c_lnL); */
/* PhyML_Printf("\n. Err in file %s at line %d\n",__FILE__,__LINE__); */
/* Warn_And_Exit(""); */
/* } */
}
new_lnL_rate = RATES_Lk_Rates(tree);
new_lnL_time = TIMES_Lk_Times(tree);
if(tree->mcmc->use_data) ratio += (new_lnL_data - cur_lnL_data);
ratio += (new_lnL_rate - cur_lnL_rate);
ratio += (new_lnL_time - cur_lnL_time);
ratio = EXP(ratio);
alpha = MIN(1.,ratio);
u = Uni();
if(u > alpha) /* Reject */
{
tree->rates->nd_t[d->num] = t1_cur;
tree->c_lnL = cur_lnL_data;
tree->rates->c_lnL_rates = cur_lnL_rate;
tree->rates->c_lnL_times = cur_lnL_time;
Restore_Br_Len(tree);
RATES_Reset_Rates(tree);
RATES_Reset_Times(tree);
if(tree->io->lk_approx == EXACT && tree->mcmc->use_data)
{
Update_PMat_At_Given_Edge(b1,tree);
Update_PMat_At_Given_Edge(b2,tree);
Update_PMat_At_Given_Edge(b3,tree);
Update_P_Lk(tree,b1,d);
}
/* printf("\n. R new_lnL_data = %f cur_lnL_data = %f t_new=%f t_cur=%f tmin=%f tmax=%f", */
/* new_lnL_data,cur_lnL_data,t1_new,t1_cur,t_min,t_max); */
}
else
{
/* printf("\n. A new_lnL_data = %f cur_lnL_data = %f t_new=%f t_cur=%f tmin=%f tmax=%f", */
/* new_lnL_data,cur_lnL_data,t1_new,t1_cur,t_min,t_max); */
tree->mcmc->acc_move[move_num]++;
}
if(t1_new < t0)
{
t1_new = t0+1.E-4;
PhyML_Printf("\n");
PhyML_Printf("\n. a is root -> %s",(a == tree->n_root)?("YES"):("NO"));
PhyML_Printf("\n. t0 = %f t1_new = %f",t0,t1_new);
PhyML_Printf("\n. t_min=%f t_max=%f",t_min,t_max);
PhyML_Printf("\n. (t1-t0)=%f (t2-t1)=%f",t1_cur-t0,t2-t1_cur);
PhyML_Printf("\n. Err in file %s at line %d\n",__FILE__,__LINE__);
/* Exit("\n"); */
}
if(t1_new > MIN(t2,t3))
{
PhyML_Printf("\n");
PhyML_Printf("\n. a is root -> %s",(a == tree->n_root)?("YES"):("NO"));
PhyML_Printf("\n. t0 = %f t1_new = %f t1 = %f t2 = %f t3 = %f MIN(t2,t3)=%f",t0,t1_new,t1_cur,t2,t3,MIN(t2,t3));
PhyML_Printf("\n. t_min=%f t_max=%f",t_min,t_max);
PhyML_Printf("\n. (t1-t0)=%f (t2-t1)=%f",t1_cur-t0,t2-t1_cur);
PhyML_Printf("\n. Err in file %s at line %d\n",__FILE__,__LINE__);
/* Exit("\n"); */
}
if(isnan(t1_new))
{
PhyML_Printf("\n. run=%d",tree->mcmc->run);
PhyML_Printf("\n. Err in file %s at line %d\n",__FILE__,__LINE__);
/* Exit("\n"); */
}
}
tree->mcmc->run_move[move_num]++;
if(traversal == YES)
{
if(d->tax == YES) return;
else
For(i,3)
if(d->v[i] != a && d->b[i] != tree->e_root)
{
if(tree->io->lk_approx == EXACT && tree->mcmc->use_data) Update_P_Lk(tree,d->b[i],d);
/* if(tree->io->lk_approx == EXACT && tree->mcmc->use_data) {tree->both_sides = YES; Lk(tree); } */
MCMC_One_Time(d,d->v[i],YES,tree);
}
if(tree->io->lk_approx == EXACT && tree->mcmc->use_data) Update_P_Lk(tree,b1,d);
/* if(tree->io->lk_approx == EXACT && tree->mcmc->use_data) {tree->both_sides = YES; Lk(tree); } */
}
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void MCMC_Tree_Height(t_tree *tree)
{
int i;
phydbl K,mult,u,alpha,ratio;
phydbl cur_lnL_data,new_lnL_data;
phydbl cur_lnL_rate,new_lnL_rate;
phydbl cur_lnL_time,new_lnL_time;
phydbl floor;
int n_nodes;
phydbl cur_height, new_height;
phydbl min_t,max_t;
if(FABS(tree->rates->t_prior_max[tree->n_root->num] - tree->rates->t_prior_min[tree->n_root->num]) < 1.E-10) return;
RATES_Record_Times(tree);
Record_Br_Len(tree);
K = tree->mcmc->tune_move[tree->mcmc->num_move_tree_height];
cur_lnL_data = tree->c_lnL;
new_lnL_data = tree->c_lnL;
ratio = 0.0;
cur_lnL_rate = tree->rates->c_lnL_rates;
new_lnL_rate = tree->rates->c_lnL_rates;
cur_height = tree->rates->nd_t[tree->n_root->num];
cur_lnL_time = tree->rates->c_lnL_times;
min_t = tree->rates->t_prior_min[tree->n_root->num];
max_t = tree->rates->t_prior_max[tree->n_root->num];
u = Uni();
mult = EXP(K*(u-0.5));
/* WARNING: It must not be floor = tree->rates->t_prior_max[tree->n_root->num];
floor is the maximum value a node height can take when one ignores the
calibration nodes, i.e., floor is set by the height of the tips
*/
/* floor = 0.0; */
floor = tree->rates->t_floor[tree->n_root->num];
/* floor = tree->rates->t_prior_max[tree->n_root->num]; */
Scale_Subtree_Height(tree->n_root,mult,floor,&n_nodes,tree);
new_height = tree->rates->nd_t[tree->n_root->num];
For(i,2*tree->n_otu-1)
{
if(tree->rates->nd_t[i] > tree->rates->t_prior_max[i] ||
tree->rates->nd_t[i] < tree->rates->t_prior_min[i])
{
RATES_Reset_Times(tree);
Restore_Br_Len(tree);
tree->mcmc->run_move[tree->mcmc->num_move_tree_height]++;
return;
}
}
For(i,2*tree->n_otu-2) tree->rates->br_do_updt[i] = YES;
RATES_Update_Cur_Bl(tree);
if(tree->mcmc->use_data) new_lnL_data = Lk(tree);
new_lnL_rate = RATES_Lk_Rates(tree);
new_lnL_time = TIMES_Lk_Times(tree);
/* The Hastings ratio is actually mult^(n) when changing the absolute
node heights. When considering the relative heights, this ratio combined
to the Jacobian for the change of variable ends up to being equal to mult.
*/
/* ratio += LOG(mult); */
ratio += (phydbl)(n_nodes)*LOG(mult);
/* Likelihood ratio */
if(tree->mcmc->use_data) ratio += (new_lnL_data - cur_lnL_data);
/* Prior ratio */
ratio += (new_lnL_rate - cur_lnL_rate);
ratio += (new_lnL_time - cur_lnL_time);
/* printf("\n. [%f %f] [%f %f] [%f %f] [%f]", */
/* new_lnL_rate , cur_lnL_rate, */
/* new_lnL_time , cur_lnL_time, */
/* cur_height,new_height,mult); */
/* phydbl diff = (new_lnL_time - cur_lnL_time)+(phydbl)(n_nodes-1.)*LOG(mult); */
/* printf("\n. diff_lk = %12f -(n-1)*log(mult) = %12f n_nodes=%d [%12f] log(mult)=%f", */
/* (new_lnL_time - cur_lnL_time), */
/* -(phydbl)(n_nodes-1.)*LOG(mult), */
/* n_nodes, */
/* diff, */
/* LOG(mult)); */
/* !!!!!!!!!!!! */
/* ratio += LOG(Dexp(FABS(new_height-floor),1./10.) / Dexp(FABS(cur_height-floor),1./10.)); */
ratio = EXP(ratio);
alpha = MIN(1.,ratio);
u = Uni();
if(u > alpha)
{
RATES_Reset_Times(tree);
Restore_Br_Len(tree);
tree->c_lnL = cur_lnL_data;
tree->rates->c_lnL_rates = cur_lnL_rate;
tree->rates->c_lnL_times = cur_lnL_time;
}
else
{
tree->mcmc->acc_move[tree->mcmc->num_move_tree_height]++;
tree->mcmc->acc_move[tree->mcmc->num_move_nd_t+tree->n_root->num-tree->n_otu]++;
}
tree->mcmc->run_move[tree->mcmc->num_move_tree_height]++;
tree->mcmc->run_move[tree->mcmc->num_move_nd_t+tree->n_root->num-tree->n_otu]++;
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void MCMC_Updown_T_Cr(t_tree *tree)
{
int i;
phydbl K,mult,u,alpha,ratio;
phydbl cur_lnL_data,new_lnL_data;
phydbl cur_lnL_rate,new_lnL_rate;
phydbl cur_lnL_time,new_lnL_time;
phydbl floor;
int n_nodes;
if(FABS(tree->rates->t_prior_max[tree->n_root->num] - tree->rates->t_prior_min[tree->n_root->num]) < 1.E-10) return;
RATES_Record_Times(tree);
Record_Br_Len(tree);
K = tree->mcmc->tune_move[tree->mcmc->num_move_updown_t_cr];
cur_lnL_data = tree->c_lnL;
new_lnL_data = tree->c_lnL;
ratio = 0.0;
cur_lnL_rate = tree->rates->c_lnL_rates;
new_lnL_rate = tree->rates->c_lnL_rates;
cur_lnL_time = tree->rates->c_lnL_times;
u = Uni();
mult = EXP(K*(u-0.5));
floor = 0.0;
Scale_Subtree_Height(tree->n_root,mult,floor,&n_nodes,tree);
For(i,2*tree->n_otu-1)
{
if(tree->rates->nd_t[i] > tree->rates->t_prior_max[i] ||
tree->rates->nd_t[i] < tree->rates->t_prior_min[i])
{
RATES_Reset_Times(tree);
Restore_Br_Len(tree);
tree->mcmc->run_move[tree->mcmc->num_move_updown_t_cr]++;
return;
}
}
if(RATES_Check_Node_Times(tree))
{
PhyML_Printf("\n. Err in file %s at line %d\n",__FILE__,__LINE__);
Warn_And_Exit("");
}
tree->rates->clock_r /= mult;
if(tree->rates->clock_r < tree->rates->min_clock || tree->rates->clock_r > tree->rates->max_clock)
{
tree->rates->clock_r *= mult;
RATES_Reset_Times(tree);
Restore_Br_Len(tree);
tree->mcmc->run_move[tree->mcmc->num_move_updown_t_cr]++;
return;
}
For(i,2*tree->n_otu-2) tree->rates->br_do_updt[i] = YES;
RATES_Update_Cur_Bl(tree);
if(tree->mcmc->use_data) new_lnL_data = Lk(tree);
new_lnL_rate = RATES_Lk_Rates(tree);
new_lnL_time = TIMES_Lk_Times(tree);
/* The Hastings ratio is actually mult^(n) when changing the absolute
node heights. When considering the relative heights, this ratio combined
to the Jacobian for the change of variable ends up to being equal to mult.
*/
ratio += (n_nodes - 1)*LOG(mult);
/* ratio += -LOG(mult) + LOG(Dgamma(1./mult,1./K,K)/Dgamma(mult,1./K,K)); */
/* Likelihood ratio */
if(tree->mcmc->use_data) ratio += (new_lnL_data - cur_lnL_data);
/* Prior ratio */
ratio += (new_lnL_rate - cur_lnL_rate);
ratio += (new_lnL_time - cur_lnL_time);
/* !!!!!!!!!!!!1 */
/* ratio += LOG(Dexp(FABS(new_height-floor),1./10.) / Dexp(FABS(cur_height-floor),1./10.)); */
ratio = EXP(ratio);
alpha = MIN(1.,ratio);
u = Uni();
if(u > alpha)
{
RATES_Reset_Times(tree);
tree->rates->clock_r *= mult;
Restore_Br_Len(tree);
tree->c_lnL = cur_lnL_data;
tree->rates->c_lnL_rates = cur_lnL_rate;
tree->rates->c_lnL_times = cur_lnL_time;
}
else
{
tree->mcmc->acc_move[tree->mcmc->num_move_updown_t_cr]++;
}
tree->mcmc->run_move[tree->mcmc->num_move_updown_t_cr]++;
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void MCMC_Subtree_Height(t_tree *tree)
{
int i;
phydbl K,mult,u,alpha,ratio;
phydbl cur_lnL_data,new_lnL_data;
phydbl cur_lnL_rate,new_lnL_rate;
phydbl cur_lnL_time,new_lnL_time;
phydbl cur_height,new_height;
phydbl floor;
int target;
int n_nodes;
RATES_Record_Times(tree);
Record_Br_Len(tree);
K = tree->mcmc->tune_move[tree->mcmc->num_move_subtree_height];
cur_lnL_data = tree->c_lnL;
new_lnL_data = tree->c_lnL;
cur_lnL_rate = tree->rates->c_lnL_rates;
new_lnL_rate = tree->rates->c_lnL_rates;
ratio = 0.0;
cur_lnL_time = tree->rates->c_lnL_times;
u = Uni();
mult = EXP(K*(u-0.5));
/* mult = Rgamma(1./K,K); */
target = Rand_Int(tree->n_otu,2*tree->n_otu-3);
cur_height = tree->rates->nd_t[target];
floor = tree->rates->t_floor[target];
if(tree->t_nodes[target] == tree->n_root)
{
PhyML_Printf("\n. Err in file %s at line %d\n",__FILE__,__LINE__);
Warn_And_Exit("");
}
if(!Scale_Subtree_Height(tree->t_nodes[target],mult,floor,&n_nodes,tree))
{
RATES_Reset_Times(tree);
Restore_Br_Len(tree);
tree->mcmc->run_move[tree->mcmc->num_move_subtree_height]++;
return;
}
new_height = tree->rates->nd_t[target];
For(i,2*tree->n_otu-1)
{
if(tree->rates->nd_t[i] > tree->rates->t_prior_max[i] ||
tree->rates->nd_t[i] < tree->rates->t_prior_min[i])
{
RATES_Reset_Times(tree);
Restore_Br_Len(tree);
tree->mcmc->run_move[tree->mcmc->num_move_subtree_height]++;
return;
}
}
For(i,2*tree->n_otu-2) tree->rates->br_do_updt[i] = YES;
RATES_Update_Cur_Bl(tree);
if(tree->mcmc->use_data) new_lnL_data = Lk(tree);
new_lnL_rate = RATES_Lk_Rates(tree);
new_lnL_time = TIMES_Lk_Times(tree);
/* The Hastings ratio here is mult^(n_nodes) and the ratio of the prior joint densities
of the modified node heigths given the unchanged one is 1. This is different from the
case where all the nodes, including the root node, are scaled.
*/
ratio += (phydbl)(n_nodes)*LOG(mult);
/* Likelihood ratio */
if(tree->mcmc->use_data) ratio += (new_lnL_data - cur_lnL_data);
/* Prior ratio */
ratio += (new_lnL_rate - cur_lnL_rate);
ratio += (new_lnL_time - cur_lnL_time);
ratio = EXP(ratio);
alpha = MIN(1.,ratio);
u = Uni();
if(u > alpha)
{
RATES_Reset_Times(tree);
Restore_Br_Len(tree);
tree->c_lnL = cur_lnL_data;
tree->rates->c_lnL_rates = cur_lnL_rate;
tree->rates->c_lnL_times = cur_lnL_time;
}
else
{
tree->mcmc->acc_move[tree->mcmc->num_move_subtree_height]++;
}
tree->mcmc->run_move[tree->mcmc->num_move_subtree_height]++;
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void MCMC_Tree_Rates(t_tree *tree)
{
phydbl K,mult,u,alpha,ratio;
phydbl cur_lnL_rate,new_lnL_rate;
phydbl cur_lnL_data,new_lnL_data;
int n_nodes;
phydbl init_clock;
if(tree->rates->model == STRICTCLOCK) return;
RATES_Record_Rates(tree);
Record_Br_Len(tree);
K = tree->mcmc->tune_move[tree->mcmc->num_move_tree_rates];
cur_lnL_data = tree->c_lnL;
new_lnL_data = tree->c_lnL;
cur_lnL_rate = tree->rates->c_lnL_rates;
new_lnL_rate = tree->rates->c_lnL_rates;
init_clock = tree->rates->clock_r;
ratio = 0.0;
u = Uni();
mult = EXP(K*(u-0.5));
/* mult = Rgamma(1./K,K); */
/* Multiply branch rates (or add to log of rates) */
if(!Scale_Subtree_Rates(tree->n_root,mult,&n_nodes,tree))
{
RATES_Reset_Rates(tree);
Restore_Br_Len(tree);
tree->mcmc->run_move[tree->mcmc->num_move_tree_rates]++;
return;
}
if(n_nodes != 2*tree->n_otu-2)
{
PhyML_Printf("\n. Err in file %s at line %d\n",__FILE__,__LINE__);
Warn_And_Exit("");
}
/* Divide clock_r */
tree->rates->clock_r /= mult;
if(tree->rates->clock_r < tree->rates->min_clock || tree->rates->clock_r > tree->rates->max_clock)
{
tree->rates->clock_r = init_clock;
RATES_Reset_Rates(tree);
Restore_Br_Len(tree);
tree->mcmc->run_move[tree->mcmc->num_move_tree_rates]++;
return;
}
/* if(tree->rates->model == GUINDON) */
/* { */
int i;
For(i,2*tree->n_otu-2) tree->rates->br_do_updt[i] = YES;
RATES_Update_Cur_Bl(tree);
if(tree->mcmc->use_data) new_lnL_data = Lk(tree);
/* } */
new_lnL_rate = RATES_Lk_Rates(tree);
/* Proposal ratio: 2n-2=> number of multiplications, 1=>number of divisions */
ratio += (+(2*tree->n_otu-2)-1)*LOG(mult);
/* ratio += (+(2*tree->n_otu-2)-1-2)*LOG(mult) + LOG(Dgamma(1./mult,1./K,K)/Dgamma(mult,1./K,K)); */
/* If modelling log of rates instead of rates */
if(tree->rates->model_log_rates == YES) ratio -= (2*tree->n_otu-2)*LOG(mult);
/* Prior density ratio */
ratio += (new_lnL_rate - cur_lnL_rate);
/* Likelihood density ratio */
ratio += (new_lnL_data - cur_lnL_data);
ratio = EXP(ratio);
alpha = MIN(1.,ratio);
u = Uni();
/* printf("\n. cur_lnL=%f new_lnL=%f ratio=%f mult=%f %f [%f %f]", */
/* cur_lnL_rate,new_lnL_rate,ratio,mult,(+(2*tree->n_otu-2)-1-2)*LOG(mult) + LOG(Dgamma(1./mult,1./K,K)/Dgamma(mult,1./K,K)),new_lnL_data,cur_lnL_data); */
if(u > alpha)
{
/* PhyML_Printf("\n. Reject mult=%f",mult); */
tree->rates->clock_r = init_clock;
RATES_Reset_Rates(tree);
Restore_Br_Len(tree);
tree->rates->c_lnL_rates = cur_lnL_rate;
tree->c_lnL = cur_lnL_data;
}
else
{
/* PhyML_Printf("\n. Accept mult=%f",mult); */
tree->mcmc->acc_move[tree->mcmc->num_move_tree_rates]++;
}
tree->mcmc->run_move[tree->mcmc->num_move_tree_rates]++;
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void MCMC_Subtree_Rates(t_tree *tree)
{ phydbl K,mult,u,alpha,ratio;
phydbl cur_lnL_rate,new_lnL_rate;
phydbl cur_lnL_data,new_lnL_data;
int target;
int n_nodes;
if(tree->rates->model == STRICTCLOCK) return;
RATES_Record_Rates(tree);
Record_Br_Len(tree);
K = tree->mcmc->tune_move[tree->mcmc->num_move_subtree_rates];
cur_lnL_rate = tree->rates->c_lnL_rates;
new_lnL_rate = cur_lnL_rate;
cur_lnL_data = tree->c_lnL;
new_lnL_data = cur_lnL_data;
ratio = 0.0;
u = Uni();
mult = EXP(K*(u-0.5));
/* mult = Rgamma(1./K,K); */
target = Rand_Int(tree->n_otu,2*tree->n_otu-3);
/* Multiply branch rates */
if(!Scale_Subtree_Rates(tree->t_nodes[target],mult,&n_nodes,tree))
{
RATES_Reset_Rates(tree);
Restore_Br_Len(tree);
tree->mcmc->run_move[tree->mcmc->num_move_subtree_rates]++;
return;
}
new_lnL_rate = RATES_Lk_Rates(tree);
if(tree->mcmc->use_data) new_lnL_data = Lk(tree);
/* Proposal ratio: 2n-2=> number of multiplications, 1=>number of divisions */
ratio += (+n_nodes)*LOG(mult);
/* ratio += (n_nodes-2)*LOG(mult) + LOG(Dgamma(1./mult,1./K,K)/Dgamma(mult,1./K,K)); */
/* If modelling log of rates instead of rates */
if(tree->rates->model_log_rates == YES) ratio -= (n_nodes)*LOG(mult);
/* Prior density ratio */
ratio += (new_lnL_rate - cur_lnL_rate);
/* Likelihood density ratio */
ratio += (new_lnL_data - cur_lnL_data);
ratio = EXP(ratio);
alpha = MIN(1.,ratio);
u = Uni();
if(u > alpha)
{
RATES_Reset_Rates(tree);
Restore_Br_Len(tree);
tree->rates->c_lnL_rates = cur_lnL_rate;
tree->c_lnL = cur_lnL_data;
}
else
{
tree->mcmc->acc_move[tree->mcmc->num_move_subtree_rates]++;
}
tree->mcmc->run_move[tree->mcmc->num_move_subtree_rates]++;
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void MCMC_Swing(t_tree *tree)
{
int i;
phydbl K,mult,u,alpha,ratio;
phydbl cur_lnL_data,new_lnL_data;
phydbl cur_lnL_rate,new_lnL_rate;
if(tree->rates->model == STRICTCLOCK) return;
RATES_Record_Times(tree);
RATES_Record_Rates(tree);
Record_Br_Len(tree);
K = 3.;
cur_lnL_data = tree->c_lnL;
new_lnL_data = cur_lnL_data;
cur_lnL_rate = tree->rates->c_lnL_rates;
new_lnL_rate = cur_lnL_rate;
ratio = 0.0;
u = Uni();
/* mult = EXP(K*(u-0.5)); */
mult = u*(K - 1./K) + 1./K;
For(i,2*tree->n_otu-1)
{
if(tree->t_nodes[i]->tax == NO)
{
tree->rates->nd_t[i] *= mult;
}
if(tree->rates->nd_t[i] > tree->rates->t_prior_max[i] ||
tree->rates->nd_t[i] < tree->rates->t_prior_min[i])
{
RATES_Reset_Times(tree);
Restore_Br_Len(tree);
return;
}
}
For(i,2*tree->n_otu-2)
{
tree->rates->br_r[i] /= mult;
if(tree->rates->br_r[i] > tree->rates->max_rate ||
tree->rates->br_r[i] < tree->rates->min_rate)
{
RATES_Reset_Times(tree);
RATES_Reset_Rates(tree);
Restore_Br_Len(tree);
return;
}
}
For(i,2*tree->n_otu-2) tree->rates->br_do_updt[i] = YES;
RATES_Update_Cur_Bl(tree);
if(tree->mcmc->use_data) new_lnL_data = Lk(tree);
new_lnL_rate = RATES_Lk_Rates(tree);
ratio += (-(tree->n_otu-1.)-2.)*LOG(mult);
ratio += (new_lnL_rate - cur_lnL_rate);
if(tree->mcmc->use_data) ratio += (new_lnL_data - cur_lnL_data);
ratio = EXP(ratio);
alpha = MIN(1.,ratio);
u = Uni();
if(u > alpha)
{
RATES_Reset_Times(tree);
RATES_Reset_Rates(tree);
Restore_Br_Len(tree);
tree->c_lnL = cur_lnL_data;
tree->rates->c_lnL_rates = cur_lnL_rate;
/* printf("\n. Reject %8f",mult); */
}
else
{
/* printf("\n. Accept %8f",mult); */
}
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void MCMC_Updown_Nu_Cr(t_tree *tree)
{
phydbl K,mult,u,alpha,ratio;
phydbl cur_lnL_rate,new_lnL_rate;
phydbl cur_lnL_data,new_lnL_data;
int i;
int n_nodes;
RATES_Record_Rates(tree);
Record_Br_Len(tree);
K = tree->mcmc->tune_move[tree->mcmc->num_move_updown_nu_cr];
cur_lnL_data = tree->c_lnL;
new_lnL_data = tree->c_lnL;
cur_lnL_rate = tree->rates->c_lnL_rates;
new_lnL_rate = tree->rates->c_lnL_rates;
n_nodes = 0;
u = Uni();
mult = EXP(K*(u-0.5));
/* Multiply branch rates */
/* if(!Scale_Subtree_Rates(tree->n_root,mult,&n_nodes,tree)) */
/* { */
/* RATES_Reset_Rates(tree); */
/* Restore_Br_Len(tree); */
/* tree->mcmc->run_move[tree->mcmc->num_move_updown_nu_cr]++; */
/* return; */
/* } */
tree->rates->clock_r /= mult;
if(tree->rates->clock_r < tree->rates->min_clock || tree->rates->clock_r > tree->rates->max_clock)
{
tree->rates->clock_r *= mult;
RATES_Reset_Rates(tree);
Restore_Br_Len(tree);
tree->mcmc->run_move[tree->mcmc->num_move_updown_nu_cr]++;
return;
}
tree->rates->nu *= mult;
if(tree->rates->nu < tree->rates->min_nu || tree->rates->nu > tree->rates->max_nu)
{
tree->rates->nu /= mult;
tree->rates->clock_r *= mult;
RATES_Reset_Rates(tree);
Restore_Br_Len(tree);
tree->mcmc->run_move[tree->mcmc->num_move_updown_nu_cr]++;
return;
}
For(i,2*tree->n_otu-2) tree->rates->br_do_updt[i] = YES;
RATES_Update_Cur_Bl(tree);
if(tree->mcmc->use_data) new_lnL_data = Lk(tree);
new_lnL_rate = RATES_Lk_Rates(tree);
ratio = 0.0;
/* Proposal ratio: 2n-2=> number of multiplications, 1=>number of divisions */
/* ratio += n_nodes*LOG(mult); /\* (1-1)*LOG(mult); *\/ */
ratio += 0.0*LOG(mult); /* (1-1)*LOG(mult); */
/* Prior density ratio */
ratio += (new_lnL_rate - cur_lnL_rate);
/* Likelihood density ratio */
ratio += (new_lnL_data - cur_lnL_data);
ratio = EXP(ratio);
alpha = MIN(1.,ratio);
u = Uni();
if(u > alpha)
{
tree->rates->clock_r *= mult;
tree->rates->nu /= mult;
RATES_Reset_Rates(tree);
Restore_Br_Len(tree);
tree->rates->c_lnL_rates = cur_lnL_rate;
tree->c_lnL = cur_lnL_data;
}
else
{
tree->mcmc->acc_move[tree->mcmc->num_move_updown_nu_cr]++;
}
tree->mcmc->run_move[tree->mcmc->num_move_updown_nu_cr]++;
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void MCMC_Print_Param_Stdin(t_mcmc *mcmc, t_tree *tree)
{
time_t cur_time;
phydbl min;
int i;
time(&cur_time);
min = MDBL_MAX;
For(i,tree->n_otu-1)
{
/* printf("\n. %d %f %f %f %f",i, */
/* tree->mcmc->new_param_val[tree->mcmc->num_move_nd_t+i], */
/* tree->mcmc->old_param_val[tree->mcmc->num_move_nd_t+i], */
/* tree->mcmc->ess[tree->mcmc->num_move_nd_t+i], */
/* tree->mcmc->sum_val[tree->mcmc->num_move_nd_t+i]); */
if(tree->mcmc->ess[tree->mcmc->num_move_nd_t+i] < min)
min = tree->mcmc->ess[tree->mcmc->num_move_nd_t+i];
}
if(mcmc->run == 1)
{
PhyML_Printf("\n\n");
PhyML_Printf("\t%7s","Run");
PhyML_Printf("\t%5s","Time");
PhyML_Printf("\t%10s","Likelihood");
PhyML_Printf("\t%10s","Prior");
PhyML_Printf("\t%17s","SubstRate[ESS]");
PhyML_Printf("\t%15s","TreeHeight[ESS]");
if(tree->rates->model == THORNE || tree->rates->model == GUINDON) PhyML_Printf("\t%14s","AutoCor[ESS]");
else PhyML_Printf("\t%14s","RateVar[ESS]");
PhyML_Printf("\t%13s","BirthR[ESS]");
PhyML_Printf("\t%7s","MinESS");
}
if((cur_time - mcmc->t_last_print) > mcmc->print_every)
{
mcmc->t_last_print = cur_time;
PhyML_Printf("\n");
PhyML_Printf("\t%7d",tree->mcmc->run);
PhyML_Printf("\t%5d",(int)(cur_time-mcmc->t_beg));
PhyML_Printf("\t%10.2f",tree->c_lnL);
PhyML_Printf("\t%10.2f",tree->rates->c_lnL_rates+tree->rates->c_lnL_times);
PhyML_Printf("\t%12.6f[%3.0f]",RATES_Average_Substitution_Rate(tree),tree->mcmc->ess[tree->mcmc->num_move_clock_r]);
/* PhyML_Printf("\t%12.6f[%4.0f]",tree->rates->clock_r,tree->mcmc->ess[tree->mcmc->num_move_clock_r]); */
PhyML_Printf("\t%10.1f[%3.0f]",tree->rates->nd_t[tree->n_root->num],tree->mcmc->ess[tree->mcmc->num_move_nd_t+tree->n_root->num-tree->n_otu]);
PhyML_Printf("\t%9.4G[%3.0f]",tree->rates->nu,tree->mcmc->ess[tree->mcmc->num_move_nu]);
PhyML_Printf("\t%8.4G[%3.0f]",tree->rates->birth_rate,tree->mcmc->ess[tree->mcmc->num_move_birth_rate]);
PhyML_Printf("\t%7.0f",min);
}
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void MCMC_Print_Param(t_mcmc *mcmc, t_tree *tree)
{
int i;
FILE *fp;
char *s;
int orig_approx;
phydbl orig_lnL;
char *s_tree;
if(tree->mcmc->run > mcmc->chain_len) return;
s = (char *)mCalloc(100,sizeof(char));
fp = mcmc->out_fp_stats;
/* if(tree->mcmc->run == 0) */
/* { */
/* PhyML_Fprintf(stdout," ["); */
/* fflush(NULL); */
/* } */
/* if(!(mcmc->run%(mcmc->chain_len/10))) */
/* { */
/* PhyML_Fprintf(stdout,"."); */
/* fflush(NULL); */
/* } */
/* if(tree->mcmc->run == mcmc->chain_len) */
/* { */
/* PhyML_Fprintf(stdout,"]"); */
/* fflush(NULL); */
/* } */
/* MCMC_Print_Means(mcmc,tree); */
/* MCMC_Print_Last(mcmc,tree); */
if(!(mcmc->run%mcmc->sample_interval))
{
MCMC_Copy_To_New_Param_Val(tree->mcmc,tree);
For(i,tree->mcmc->n_moves)
{
if((tree->mcmc->acc_rate[i] > .1) && (tree->mcmc->start_ess[i] == NO)) tree->mcmc->start_ess[i] = YES;
if(tree->mcmc->start_ess[i] == YES) MCMC_Update_Effective_Sample_Size(i,tree->mcmc,tree);
if(tree->mcmc->run > (int) tree->mcmc->chain_len * 0.1) tree->mcmc->adjust_tuning[i] = NO;
}
if(tree->mcmc->run == 0)
{
time(&(mcmc->t_beg));
time(&(mcmc->t_last_print));
PhyML_Fprintf(fp,"# Random seed: %d",tree->io->r_seed);
PhyML_Fprintf(fp,"\n");
PhyML_Fprintf(fp,"Run\t");
/* PhyML_Fprintf(fp,"Time\t"); */
/* PhyML_Fprintf(fp,"MeanRate\t"); */
/* PhyML_Fprintf(fp,"NormFact\t"); */
/* For(i,mcmc->n_moves) */
/* { */
/* strcpy(s,"Acc."); */
/* PhyML_Fprintf(fp,"%s%d\t",strcat(s,mcmc->move_name[i]),i); */
/* } */
/* For(i,mcmc->n_moves) */
/* { */
/* strcpy(s,"Tune."); */
/* PhyML_Fprintf(fp,"%s%d\t",strcat(s,mcmc->move_name[i]),i); */
/* } */
/* For(i,mcmc->n_moves) */
/* { */
/* strcpy(s,"Run."); */
/* PhyML_Fprintf(fp,"%s\t",strcat(s,mcmc->move_name[i])); */
/* } */
PhyML_Fprintf(fp,"LnLike[Exact]\t");
PhyML_Fprintf(fp,"LnLike[Approx]\t");
PhyML_Fprintf(fp,"LnRates\t");
PhyML_Fprintf(fp,"LnTimes\t");
PhyML_Fprintf(fp,"LnPosterior\t");
PhyML_Fprintf(fp,"ClockRate\t");
PhyML_Fprintf(fp,"EvolRate\t");
PhyML_Fprintf(fp,"Nu\t");
PhyML_Fprintf(fp,"BirthRate\t");
PhyML_Fprintf(fp,"TsTv\t");
if(tree->mod->n_catg > 1)
{
if(tree->mod->free_mixt_rates == NO) PhyML_Fprintf(fp,"Alpha\t");
else
{
For(i,tree->mod->n_catg) PhyML_Fprintf(fp,"p%d\t",i);
For(i,tree->mod->n_catg) PhyML_Fprintf(fp,"r%d\t",i);
}
}
if(tree->mod->m4mod->n_h > 1 && tree->mod->use_m4mod == YES)
{
For(i,tree->mod->m4mod->n_h) PhyML_Fprintf(fp,"cov_p%d\t",i);
For(i,tree->mod->m4mod->n_h) PhyML_Fprintf(fp,"cov_r%d\t",i);
PhyML_Fprintf(fp,"cov_switch\t");
}
if(fp != stdout)
{
for(i=tree->n_otu;i<2*tree->n_otu-1;i++)
{
if(tree->t_nodes[i] == tree->n_root->v[0])
PhyML_Fprintf(fp,"T%d%s\t",i,"[LeftRoot]");
else if(tree->t_nodes[i] == tree->n_root->v[1])
PhyML_Fprintf(fp,"T%d%s\t",i,"[RightRoot]");
else if(tree->t_nodes[i] == tree->n_root)
PhyML_Fprintf(fp,"T%d%s\t",i,"[Root]");
else
PhyML_Fprintf(fp,"T%d[%d]\t",i,tree->t_nodes[i]->anc->num);
}
}
/* if(fp != stdout) */
/* { */
/* For(i,2*tree->n_otu-1) */
/* { */
/* if(tree->t_nodes[i] == tree->n_root->v[0]) */
/* PhyML_Fprintf(fp,"R%d[LeftRoot]\t",i); */
/* else if(tree->t_nodes[i] == tree->n_root->v[1]) */
/* PhyML_Fprintf(fp,"R%d[RightRoot]\t",i); */
/* else if(tree->t_nodes[i] != tree->n_root) */
/* PhyML_Fprintf(fp," R%d[%d]\t",i,tree->t_nodes[i]->anc->num); */
/* else */
/* PhyML_Fprintf(fp," R%d[Root]\t",i); */
/* /\* PhyML_Fprintf(fp," R%d[%f]\t",i,tree->rates->mean_l[i]); *\/ */
/* } */
/* } */
if(fp != stdout)
{
For(i,2*tree->n_otu-2)
{
if(tree->t_nodes[i] == tree->n_root->v[0])
PhyML_Fprintf(fp,"B%d[LeftRoot]\t",i);
else if(tree->t_nodes[i] == tree->n_root->v[1])
PhyML_Fprintf(fp,"B%d[RightRoot]\t",i);
else
PhyML_Fprintf(fp," B%d[%d]\t",i,tree->t_nodes[i]->anc->num);
/* PhyML_Fprintf(fp," R%d[%f]\t",i,tree->rates->mean_l[i]); */
}
}
/* if(fp != stdout) */
/* { */
/* For(i,2*tree->n_otu-2) */
/* { */
/* if(tree->t_nodes[i] == tree->n_root->v[0]) */
/* PhyML_Fprintf(fp,"G%d[LeftRoot]\t",i); */
/* else if(tree->t_nodes[i] == tree->n_root->v[1]) */
/* PhyML_Fprintf(fp,"G%d[RightRoot]\t",i); */
/* else */
/* PhyML_Fprintf(fp," G%d[%f]\t",i,tree->rates->ml_l[i]); */
/* /\* PhyML_Fprintf(fp," R%d[%f]\t",i,tree->rates->mean_l[i]); *\/ */
/* } */
/* } */
if(fp != stdout)
{
For(i,2*tree->n_otu-3)
{
if(tree->t_edges[i] == tree->e_root)
PhyML_Fprintf(fp,"*L[%f]%d\t",i,tree->rates->u_ml_l[i]);
else
PhyML_Fprintf(fp," L[%f]%d\t",i,tree->rates->u_ml_l[i]);
}
}
PhyML_Fprintf(mcmc->out_fp_trees,"#NEXUS\n");
PhyML_Fprintf(mcmc->out_fp_trees,"BEGIN TREES;\n");
PhyML_Fprintf(mcmc->out_fp_trees,"\tTRANSLATE\n");
For(i,tree->n_otu-1) PhyML_Fprintf(mcmc->out_fp_trees,"\t%3d\t%s,\n",tree->t_nodes[i]->num,tree->t_nodes[i]->name);
PhyML_Fprintf(mcmc->out_fp_trees,"\t%3d\t%s;\n",tree->t_nodes[i]->num,tree->t_nodes[i]->name);
tree->write_tax_names = NO;
}
PhyML_Fprintf(fp,"\n");
PhyML_Fprintf(fp,"%6d\t",tree->mcmc->run);
/* time(&mcmc->t_cur); */
/* PhyML_Fprintf(fp,"%6d\t",(int)(mcmc->t_cur-mcmc->t_beg)); */
/* RATES_Update_Cur_Bl(tree); */
/* PhyML_Fprintf(fp,"%f\t",RATES_Check_Mean_Rates(tree)); */
/* PhyML_Fprintf(fp,"%f\t",tree->rates->norm_fact); */
/* For(i,tree->mcmc->n_moves) PhyML_Fprintf(fp,"%f\t",tree->mcmc->acc_rate[i]); */
/* For(i,tree->mcmc->n_moves) PhyML_Fprintf(fp,"%f\t",(phydbl)(tree->mcmc->tune_move[i])); */
/* For(i,tree->mcmc->n_moves) PhyML_Fprintf(fp,"%d\t",(int)(tree->mcmc->run_move[i])); */
orig_approx = tree->io->lk_approx;
orig_lnL = tree->c_lnL;
tree->io->lk_approx = EXACT;
if(tree->mcmc->use_data) Lk(tree); else tree->c_lnL = 0.0;
PhyML_Fprintf(fp,"%.1f\t",tree->c_lnL);
tree->io->lk_approx = NORMAL;
tree->c_lnL = 0.0;
if(tree->mcmc->use_data) Lk(tree); else tree->c_lnL = 0.0;
PhyML_Fprintf(fp,"%.1f\t",tree->c_lnL);
tree->io->lk_approx = orig_approx;
tree->c_lnL = orig_lnL;
/* PhyML_Fprintf(fp,"0\t0\t"); */
PhyML_Fprintf(fp,"%G\t",tree->rates->c_lnL_rates);
PhyML_Fprintf(fp,"%G\t",tree->rates->c_lnL_times);
PhyML_Fprintf(fp,"%G\t",tree->c_lnL+tree->rates->c_lnL_rates+tree->rates->c_lnL_times);
PhyML_Fprintf(fp,"%G\t",tree->rates->clock_r);
PhyML_Fprintf(fp,"%G\t",RATES_Average_Substitution_Rate(tree));
PhyML_Fprintf(fp,"%G\t",tree->rates->nu);
PhyML_Fprintf(fp,"%G\t",tree->rates->birth_rate);
PhyML_Fprintf(fp,"%G\t",tree->mod->kappa->v);
if(tree->mod->n_catg > 1)
{
if(tree->mod->free_mixt_rates == NO)
PhyML_Fprintf(fp,"%G\t",tree->mod->alpha);
else
{
For(i,tree->mod->n_catg) PhyML_Fprintf(fp,"%G\t",tree->mod->gamma_r_proba->v[i]);
For(i,tree->mod->n_catg) PhyML_Fprintf(fp,"%G\t",tree->mod->gamma_rr->v[i]);
/* For(i,tree->mod->n_catg) PhyML_Fprintf(fp,"%G\t",tree->mod->gamma_r_proba_unscaled[i]); */
/* For(i,tree->mod->n_catg) PhyML_Fprintf(fp,"%G\t",tree->mod->gamma_rr_unscaled[i]); */
}
}
if(tree->mod->m4mod->n_h > 1 && tree->mod->use_m4mod == YES)
{
For(i,tree->mod->m4mod->n_h) PhyML_Fprintf(fp,"%G\t",tree->mod->m4mod->h_fq[i]);
For(i,tree->mod->m4mod->n_h) PhyML_Fprintf(fp,"%G\t",tree->mod->m4mod->multipl[i]);
PhyML_Fprintf(fp,"%G\t",tree->mod->m4mod->delta);
}
char *format = (char *)mCalloc(100,sizeof(char));
sprintf(format,"%%.%df\t",tree->mcmc->nd_t_digits);
for(i=tree->n_otu;i<2*tree->n_otu-1;i++) PhyML_Fprintf(fp,format,tree->rates->nd_t[i]);
Free(format);
/* for(i=0;i<2*tree->n_otu-1;i++) PhyML_Fprintf(fp,"%.4f\t",LOG(tree->rates->nd_r[i])); */
// Average rate along edges: length divided by elapsed time
For(i,2*tree->n_otu-2)
PhyML_Fprintf(fp,"%.4f\t",
tree->rates->cur_l[i]/(tree->rates->nd_t[tree->t_nodes[i]->num] - tree->rates->nd_t[tree->t_nodes[i]->anc->num]));
/* fp_pred = fopen("predict.txt","a"); */
/* for(i=0;i<2*tree->n_otu-2;i++) */
/* PhyML_Fprintf(fp_pred,"B%d\t%12f\t%12f\t%4d\n",i,EXP(tree->rates->br_r[i]),tree->rates->nd_t[i],tree->rates->has_survived[i]); */
/* fclose(fp_pred); */
/* phydbl p,sd,mean; */
/* for(i=0;i<2*tree->n_otu-2;i++) */
/* { */
/* sd = tree->rates->nu * (tree->rates->nd_t[i] - tree->rates->nd_t[tree->t_nodes[i]->anc->num]); */
/* mean = tree->rates->br_r[tree->t_nodes[i]->anc->num] - .5*sd*sd; */
/* p = Pnorm(tree->rates->br_r[i],mean,sd); */
/* PhyML_Fprintf(fp,"%f\t",p); */
/* tree->rates->mean_r[i] += p; */
/* } */
/* for(i=0;i<2*tree->n_otu-2;i++) PhyML_Fprintf(fp,"%.4f\t",tree->rates->cur_gamma_prior_mean[i]); */
/* if(fp != stdout) for(i=tree->n_otu;i<2*tree->n_otu-1;i++) PhyML_Fprintf(fp,"%G\t",tree->rates->t_prior[i]); */
/* For(i,2*tree->n_otu-3) PhyML_Fprintf(fp,"%f\t",EXP(tree->t_edges[i]->l)); */
RATES_Update_Cur_Bl(tree);
For(i,2*tree->n_otu-3) PhyML_Fprintf(fp,"%f\t",tree->t_edges[i]->l);
For(i,2*tree->n_otu-2) tree->rates->mean_r[i] = EXP(tree->rates->br_r[i]);
For(i,2*tree->n_otu-1) tree->rates->mean_t[i] = tree->rates->nd_t[i];
/* Branch_Lengths_To_Time_Lengths(tree); */
/* char *s; */
/* s = (char *)mCalloc(T_MAX_NAME,sizeof(char)); */
/* strcpy(s,mcmc->io->in_align_file); */
/* strcat(s,"_"); */
/* strcat(s,mcmc->out_filename); */
/* strcat(s,".ps"); */
/* DR_Draw_Tree(s,tree); */
/* Free(s); */
/* FILE *fp; */
/* int j; */
/* t_node *d, *v1, *v2; */
/* int n1, n2; */
/* phydbl r1, r2; */
/* s = (char *)mCalloc(T_MAX_NAME,sizeof(char)); */
/* strcpy(s,mcmc->io->in_align_file); */
/* strcat(s,"_"); */
/* strcat(s,mcmc->out_filename); */
/* strcat(s,".corr"); */
/* fp = fopen(s,"w"); */
/* n1 = n2 = 0; */
/* r1 = r2 = 0.f; */
/* For(i,2*tree->n_otu-3) */
/* { */
/* if(tree->t_nodes[i]->tax == NO) */
/* { */
/* d = tree->t_nodes[i]; */
/* v1 = v2 = NULL; */
/* For(j,3) */
/* { */
/* if(d->v[j] != d->anc && d->b[j] != tree->e_root) */
/* { */
/* if(!v1) v1 = d->v[j]; */
/* else v2 = d->v[j]; */
/* } */
/* } */
/* For(j,3) */
/* { */
/* if(v1->v[j] && v1->v[j] == d) */
/* { */
/* n1 = v1->bip_size[j]; */
/* /\* r1 = RATES_Get_Mean_Rate_In_Subtree(v1,tree); *\/ */
/* r1 = EXP(tree->rates->br_r[v1->num]); */
/* break; */
/* } */
/* } */
/* For(j,3) */
/* { */
/* if(v2->v[j] && v2->v[j] == d) */
/* { */
/* n2 = v2->bip_size[j]; */
/* /\* r2 = RATES_Get_Mean_Rate_In_Subtree(v2,tree); *\/ */
/* r2 = EXP(tree->rates->br_r[v2->num]); */
/* break; */
/* } */
/* } */
/* fprintf(fp,"\n%4d %4d %15f %15f",n1,n2,r1,r2); */
/* } */
/* } */
/* fclose(fp); */
// TREES
Branch_Lengths_To_Time_Lengths(tree);
tree->bl_ndigits = 3;
s_tree = Write_Tree(tree,NO);
tree->bl_ndigits = 7;
PhyML_Fprintf(mcmc->out_fp_trees,"TREE %8d [%f] = [&R] %s\n",mcmc->run,tree->c_lnL,s_tree);
Free(s_tree);
}
if(tree->mcmc->run == mcmc->chain_len) PhyML_Fprintf(mcmc->out_fp_trees,"END;\n");
fflush(NULL);
Free(s);
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void MCMC_Print_Means(t_mcmc *mcmc, t_tree *tree)
{
if(!(mcmc->run%mcmc->sample_interval))
{
int i;
char *s;
s = (char *)mCalloc(T_MAX_FILE,sizeof(char));
strcpy(s,tree->mcmc->out_filename);
strcat(s,".means");
fclose(mcmc->out_fp_means);
mcmc->out_fp_means = fopen(s,"w");
PhyML_Fprintf(mcmc->out_fp_means,"#");
for(i=tree->n_otu;i<2*tree->n_otu-1;i++) PhyML_Fprintf(mcmc->out_fp_means,"T%d\t",i);
PhyML_Fprintf(mcmc->out_fp_means,"\n");
for(i=tree->n_otu;i<2*tree->n_otu-1;i++) tree->rates->t_mean[i] *= (phydbl)(mcmc->run / mcmc->sample_interval);
for(i=tree->n_otu;i<2*tree->n_otu-1;i++)
{
tree->rates->t_mean[i] += tree->rates->nd_t[i];
tree->rates->t_mean[i] /= (phydbl)(mcmc->run / mcmc->sample_interval + 1);
/* PhyML_Fprintf(tree->mcmc->out_fp_means,"%d\t",tree->mcmc->run / tree->mcmc->sample_interval); */
PhyML_Fprintf(tree->mcmc->out_fp_means,"%.1f\t",tree->rates->t_mean[i]);
}
PhyML_Fprintf(tree->mcmc->out_fp_means,"\n");
fflush(NULL);
Free(s);
}
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void MCMC_Print_Last(t_mcmc *mcmc, t_tree *tree)
{
if(!(mcmc->run%mcmc->sample_interval))
{
int i;
char *s;
s = (char *)mCalloc(T_MAX_FILE,sizeof(char));
strcpy(s,tree->mcmc->out_filename);
strcat(s,".lasts");
fclose(mcmc->out_fp_last);
mcmc->out_fp_last = fopen(s,"w");
/* rewind(mcmc->out_fp_last); */
PhyML_Fprintf(mcmc->out_fp_last,"#");
PhyML_Fprintf(tree->mcmc->out_fp_last,"Time\t");
for(i=tree->n_otu;i<2*tree->n_otu-1;i++)
PhyML_Fprintf(tree->mcmc->out_fp_last,"T%d\t",i);
PhyML_Fprintf(tree->mcmc->out_fp_last,"\n");
if(mcmc->run)
{
time(&(mcmc->t_cur));
PhyML_Fprintf(tree->mcmc->out_fp_last,"%d\t",(int)(mcmc->t_cur-mcmc->t_beg));
/* PhyML_Fprintf(tree->mcmc->out_fp_last,"%d\t",(int)(mcmc->t_beg)); */
}
for(i=tree->n_otu;i<2*tree->n_otu-1;i++) PhyML_Fprintf(tree->mcmc->out_fp_last,"%.1f\t",tree->rates->nd_t[i]);
PhyML_Fprintf(tree->mcmc->out_fp_last,"\n");
fflush(NULL);
Free(s);
}
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
t_mcmc *MCMC_Make_MCMC_Struct()
{
t_mcmc *mcmc;
mcmc = (t_mcmc *)mCalloc(1,sizeof(t_mcmc));
mcmc->out_filename = (char *)mCalloc(T_MAX_FILE,sizeof(char));
return(mcmc);
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void MCMC_Free_MCMC(t_mcmc *mcmc)
{
int i;
Free(mcmc->move_type);
Free(mcmc->adjust_tuning);
Free(mcmc->out_filename);
Free(mcmc->move_weight);
Free(mcmc->acc_move);
Free(mcmc->run_move);
Free(mcmc->prev_acc_move);
Free(mcmc->prev_run_move);
Free(mcmc->acc_rate);
Free(mcmc->tune_move);
For(i,mcmc->n_moves) Free(mcmc->move_name[i]);
Free(mcmc->move_name);
Free(mcmc->ess_run);
Free(mcmc->start_ess);
Free(mcmc->ess);
Free(mcmc->sum_val);
Free(mcmc->sum_valsq);
Free(mcmc->sum_curval_nextval);
Free(mcmc->first_val);
Free(mcmc->old_param_val);
Free(mcmc->new_param_val);
Free(mcmc);
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void MCMC_Pause(t_mcmc *mcmc)
{
char choice;
char *s;
int len;
s = (char *)mCalloc(100,sizeof(char));
if(!(mcmc->run%mcmc->chain_len) && (mcmc->is_burnin == NO))
{
PhyML_Printf("\n. Do you wish to stop the analysis [N/y] ");
if(!scanf("%c",&choice)) Exit("\n");
if(choice == '\n') choice = 'N';
else getchar(); /* \n */
Uppercase(&choice);
switch(choice)
{
case 'N':
{
len = 1E+4;
PhyML_Printf("\n. How many extra generations is required [default: 1E+4] ");
Getstring_Stdin(s);
if(s[0] == '\0') len = 1E+4;
else len = (int)atof(s);
if(len < 0)
{
PhyML_Printf("\n. The value entered must be an integer greater than 0.\n");
Exit("\n");
}
mcmc->chain_len += len;
break;
}
case 'Y':
{
PhyML_Printf("\n. Ok. Done.\n");
Exit("\n");
break;
}
default:
{
PhyML_Printf("\n. Please enter 'Y' or 'N'.\n");
Exit("\n");
}
}
}
Free(s);
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void MCMC_Terminate()
{
char choice;
PhyML_Printf("\n\n. Do you really want to terminate [Y/n]: ");
if(!scanf("%c",&choice)) Exit("\n");
if(choice == '\n') choice = 'Y';
else getchar(); /* \n */
Uppercase(&choice);
if(choice == 'Y') raise(SIGTERM);
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void MCMC_Init_MCMC_Struct(char *filename, option *io, t_mcmc *mcmc)
{
int pid;
mcmc->io = io;
mcmc->is = NO;
mcmc->use_data = YES;
mcmc->run = 0;
mcmc->sample_interval = 1E+3;
mcmc->chain_len = 1E+6;
mcmc->chain_len_burnin = 1E+5;
mcmc->randomize = YES;
mcmc->norm_freq = 1E+3;
mcmc->max_tune = 1.E+20;
mcmc->min_tune = 1.E-10;
mcmc->print_every = 2;
mcmc->is_burnin = NO;
mcmc->nd_t_digits = 1;
if(filename)
{
char *s;
s = (char *)mCalloc(T_MAX_NAME,sizeof(char));
strcpy(mcmc->out_filename,filename);
pid = getpid();
sprintf(mcmc->out_filename+strlen(mcmc->out_filename),".%d",pid);
strcpy(s,mcmc->io->in_align_file);
strcat(s,"_");
strcat(s,mcmc->out_filename);
strcat(s,".stats");
mcmc->out_fp_stats = fopen(s,"w");
strcpy(s,mcmc->io->in_align_file);
strcat(s,"_");
strcat(s,mcmc->out_filename);
strcat(s,".trees");
mcmc->out_fp_trees = fopen(s,"w");
strcpy(s,mcmc->io->in_align_file);
strcat(s,"_");
strcat(s,mcmc->out_filename);
strcat(s,".constree");
mcmc->out_fp_constree = fopen(s,"w");
/* strcpy(s,tree->mcmc->out_filename); */
/* strcat(s,".means"); */
/* tree->mcmc->out_fp_means = fopen(s,"w"); */
/* strcpy(s,tree->mcmc->out_filename); */
/* strcat(s,".lasts"); */
/* tree->mcmc->out_fp_last = fopen(s,"w"); */
Free(s);
}
else
{
mcmc->out_fp_stats = stderr;
mcmc->out_fp_trees = stderr;
/* tree->mcmc->out_fp_means = stderr; */
/* tree->mcmc->out_fp_last = stderr; */
}
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void MCMC_Copy_MCMC_Struct(t_mcmc *ori, t_mcmc *cpy, char *filename)
{
int pid;
int i;
cpy->use_data = ori->use_data ;
cpy->sample_interval = ori->sample_interval ;
cpy->chain_len = ori->chain_len ;
cpy->randomize = ori->randomize ;
cpy->norm_freq = ori->norm_freq ;
cpy->n_moves = ori->n_moves ;
cpy->max_tune = ori->max_tune ;
cpy->min_tune = ori->min_tune ;
cpy->print_every = ori->print_every ;
cpy->is_burnin = ori->is_burnin ;
cpy->is = ori->is ;
cpy->io = ori->io ;
cpy->in_fp_par = ori->in_fp_par ;
cpy->nd_t_digits = ori->nd_t_digits ;
For(i,cpy->n_moves)
{
cpy->old_param_val[i] = ori->old_param_val[i];
cpy->new_param_val[i] = ori->new_param_val[i];
cpy->start_ess[i] = ori->start_ess[i];
cpy->ess_run[i] = ori->ess_run[i];
cpy->ess[i] = ori->ess[i];
cpy->sum_val[i] = ori->sum_val[i];
cpy->sum_valsq[i] = ori->sum_valsq[i];
cpy->first_val[i] = ori->first_val[i];
cpy->sum_curval_nextval[i] = ori->sum_curval_nextval[i];
cpy->move_weight[i] = ori->move_weight[i];
cpy->run_move[i] = ori->run_move[i];
cpy->acc_move[i] = ori->acc_move[i];
cpy->prev_run_move[i] = ori->prev_run_move[i];
cpy->prev_acc_move[i] = ori->prev_acc_move[i];
cpy->acc_rate[i] = ori->acc_rate[i];
cpy->tune_move[i] = ori->tune_move[i];
strcpy(cpy->move_name[i],ori->move_name[i]);
cpy->adjust_tuning[i] = ori->adjust_tuning[i];
}
if(filename)
{
char *s;
s = (char *)mCalloc(T_MAX_NAME,sizeof(char));
strcpy(cpy->out_filename,filename);
pid = getpid();
sprintf(cpy->out_filename+strlen(cpy->out_filename),".%d",pid);
strcpy(s,cpy->io->in_align_file);
strcat(s,"_");
strcat(s,cpy->out_filename);
strcat(s,".stats");
cpy->out_fp_stats = fopen(s,"w");
strcpy(s,cpy->io->in_align_file);
strcat(s,"_");
strcat(s,cpy->out_filename);
strcat(s,".trees");
cpy->out_fp_trees = fopen(s,"w");
strcpy(s,cpy->io->in_align_file);
strcat(s,"_");
strcat(s,cpy->out_filename);
strcat(s,".constree");
cpy->out_fp_constree = fopen(s,"w");
Free(s);
}
else
{
cpy->out_fp_stats = stderr;
cpy->out_fp_trees = stderr;
}
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void MCMC_Close_MCMC(t_mcmc *mcmc)
{
fclose(mcmc->out_fp_trees);
fclose(mcmc->out_fp_stats);
fclose(mcmc->out_fp_constree);
/* fclose(mcmc->out_fp_means); */
/* fclose(mcmc->out_fp_last); */
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void MCMC_Randomize_Kappa(t_tree *tree)
{
tree->mod->kappa->v = Uni()*5.;
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void MCMC_Randomize_Rate_Across_Sites(t_tree *tree)
{
if(tree->mod->n_catg == 1) return;
if(tree->mod->free_mixt_rates == YES)
{
int i;
For(i,tree->mod->n_catg-1) tree->mod->gamma_r_proba_unscaled->v[i] = Uni()*100.;
tree->mod->gamma_r_proba_unscaled->v[tree->mod->n_catg-1] = 100.;
For(i,tree->mod->n_catg) tree->mod->gamma_rr_unscaled->v[i] = (phydbl)i+1.; /* Do not randomize those as their ordering matter */
}
else
{
tree->mod->alpha->v = Uni()*5.;
}
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void MCMC_Randomize_Covarion_Rates(t_tree *tree)
{
if(tree->mod->use_m4mod == NO) return;
if(tree->mod->m4mod->n_h == 1) return;
int i;
For(i,tree->mod->m4mod->n_h)
{
tree->mod->m4mod->multipl_unscaled[i] = (phydbl)i+1.;
tree->mod->m4mod->h_fq_unscaled[i] = Uni()*(100.-0.01) + 0.01;
}
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void MCMC_Randomize_Covarion_Switch(t_tree *tree)
{
if(tree->mod->use_m4mod == NO) return;
tree->mod->m4mod->delta = Uni()*(10.-0.01)+0.01;
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void MCMC_Randomize_Branch_Lengths(t_tree *tree)
{
int i;
if(tree->mod->log_l == NO)
For(i,2*tree->n_otu-3) tree->t_edges[i]->l = Rexp(10.);
else
For(i,2*tree->n_otu-3) tree->t_edges[i]->l = -4* Uni();
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void MCMC_Randomize_Node_Rates(t_tree *tree)
{
int i,err;
phydbl mean_r, var_r;
phydbl min_r, max_r;
mean_r = 1.0;
var_r = 0.5;
min_r = tree->rates->min_rate;
max_r = tree->rates->max_rate;
For(i,2*tree->n_otu-2)
if(tree->t_nodes[i] != tree->n_root)
tree->rates->nd_r[i] = Rnorm_Trunc(mean_r,SQRT(var_r),min_r,max_r,&err);
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void MCMC_Randomize_Rates(t_tree *tree)
{
/* Should be called once t_node times have been determined */
int i;
phydbl u;
phydbl r_min,r_max;
For(i,2*tree->n_otu-2) tree->rates->br_r[i] = 1.0;
r_min = 0.9;
r_max = 1.1;
u = 0.0;
/* For(i,2*tree->n_otu-2) */
/* { */
/* u = Uni(); */
/* u = u * (r_max-r_min) + r_min; */
/* tree->rates->br_r[i] = u; */
/* if(tree->rates->br_r[i] < tree->rates->min_rate) tree->rates->br_r[i] = tree->rates->min_rate; */
/* if(tree->rates->br_r[i] > tree->rates->max_rate) tree->rates->br_r[i] = tree->rates->max_rate; */
/* } */
MCMC_Randomize_Rates_Pre(tree->n_root,tree->n_root->v[0],tree);
MCMC_Randomize_Rates_Pre(tree->n_root,tree->n_root->v[1],tree);
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void MCMC_Randomize_Rates_Pre(t_node *a, t_node *d, t_tree *tree)
{
int i;
phydbl mean_r, var_r;
phydbl min_r, max_r;
int err;
/* mean_r = tree->rates->br_r[a->num]; */
/* var_r = tree->rates->nu * (tree->rates->nd_t[d->num] - tree->rates->nd_t[a->num]); */
mean_r = 1.0;
var_r = 0.5;
min_r = tree->rates->min_rate;
max_r = tree->rates->max_rate;
tree->rates->br_r[d->num] = Rnorm_Trunc(mean_r,SQRT(var_r),min_r,max_r,&err);
if(d->tax) return;
else
{
For(i,3)
if(d->v[i] != a && d->b[i] != tree->e_root)
MCMC_Randomize_Rates_Pre(d,d->v[i],tree);
}
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void MCMC_Randomize_Birth(t_tree *tree)
{
phydbl min_b,max_b;
phydbl u;
min_b = tree->rates->birth_rate_min;
max_b = tree->rates->birth_rate_max;
u = Uni();
tree->rates->birth_rate = (max_b - min_b) * u + min_b;
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void MCMC_Randomize_Nu(t_tree *tree)
{
phydbl min_nu,max_nu;
phydbl u;
/* It is preferable to start with small values of nu
as if is difficult for the MCMC sampler to sample
equal rates on edge (i.e., molecular clock) since
such combination of rate lies on the boundary of
the space of all edge rate combination. We give
here a bit of help to the sampler by considering
starting points close to the molecular clock
constraint.
*/
min_nu = tree->rates->min_nu;
max_nu = tree->rates->max_nu/10.;
u = Uni();
tree->rates->nu = (max_nu - min_nu) * u + min_nu;
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void MCMC_Randomize_Clock_Rate(t_tree *tree)
{
phydbl u;
u = Uni();
tree->rates->clock_r = u * (tree->rates->max_clock - tree->rates->min_clock) + tree->rates->min_clock;
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void MCMC_Randomize_Alpha(t_tree *tree)
{
phydbl u;
u = Uni();
tree->rates->alpha = u*6.0+1.0;
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void MCMC_Randomize_Node_Times(t_tree *tree)
{
phydbl t_sup, t_inf;
phydbl u;
int iter;
int i;
phydbl dt,min_dt;
int min_node;
t_inf = tree->rates->t_prior_min[tree->n_root->num];
t_sup = tree->rates->t_prior_max[tree->n_root->num];
u = Uni();
u *= (t_sup - t_inf);
u += t_inf;
tree->rates->nd_t[tree->n_root->num] = u;
MCMC_Randomize_Node_Times_Top_Down(tree->n_root,tree->n_root->v[0],tree);
MCMC_Randomize_Node_Times_Top_Down(tree->n_root,tree->n_root->v[1],tree);
min_node = -1;
iter = 0;
do
{
min_dt = MDBL_MAX;
For(i,2*tree->n_otu-2)
{
dt = tree->rates->nd_t[i] - tree->rates->nd_t[tree->t_nodes[i]->anc->num];
if(dt < min_dt)
{
min_dt = dt;
min_node = i;
}
}
if(min_dt > .1 * FABS(tree->rates->nd_t[tree->n_root->num])/(phydbl)(tree->n_otu-1)) break;
RATES_Record_Times(tree);
For(i,2*tree->n_otu-1)
{
if(tree->t_nodes[i]->tax == NO)
tree->rates->nd_t[i] -= 0.1*FABS(tree->rates->nd_t[tree->n_root->num])/(phydbl)(tree->n_otu-1);
if(tree->rates->nd_t[i] < tree->rates->t_prior_min[i] ||
tree->rates->nd_t[i] > tree->rates->t_prior_max[i])
{
RATES_Reset_Times(tree);
break;
}
}
MCMC_Randomize_Node_Times_Bottom_Up(tree->n_root,tree->n_root->v[0],tree);
MCMC_Randomize_Node_Times_Bottom_Up(tree->n_root,tree->n_root->v[1],tree);
iter++;
}
while(iter < 1000);
if(iter == 1000)
{
PhyML_Printf("\n. min_dt = %f",min_dt);
PhyML_Printf("\n. min->t=%f min->anc->t=%f",tree->rates->nd_t[min_node],tree->rates->nd_t[tree->t_nodes[min_node]->anc->num]);
PhyML_Printf("\n. up=%f down=%f",tree->rates->t_prior_min[min_node],tree->rates->t_floor[tree->t_nodes[min_node]->anc->num]);
PhyML_Printf("\n. min_node = %d",min_node);
PhyML_Printf("\n. Err in file %s at line %d\n",__FILE__,__LINE__);
Warn_And_Exit("");
}
/* PhyML_Printf("\n. Needed %d iterations to randomize node heights.",iter); */
/* TIMES_Print_Node_Times(tree->n_root,tree->n_root->v[0],tree); */
/* TIMES_Print_Node_Times(tree->n_root,tree->n_root->v[1],tree); */
if(RATES_Check_Node_Times(tree))
{
PhyML_Printf("\n. Err in file %s at line %d\n",__FILE__,__LINE__);
Warn_And_Exit("");
}
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void MCMC_Randomize_Node_Times_Bottom_Up(t_node *a, t_node *d, t_tree *tree)
{
if(d->tax) return;
else
{
int i;
phydbl u;
phydbl t_inf, t_sup;
t_node *v1, *v2;
For(i,3)
{
if((d->v[i] != a) && (d->b[i] != tree->e_root))
{
MCMC_Randomize_Node_Times_Bottom_Up(d,d->v[i],tree);
}
}
v1 = v2 = NULL;
For(i,3)
{
if(d->v[i] != a && d->b[i] != tree->e_root)
{
if(!v1) v1 = d->v[i];
else v2 = d->v[i];
}
}
t_sup = MIN(tree->rates->nd_t[v1->num],tree->rates->nd_t[v2->num]);
t_inf = tree->rates->nd_t[a->num];
u = Uni();
u *= (t_sup - t_inf);
u += t_inf;
if(u > tree->rates->t_prior_min[d->num] && u < tree->rates->t_prior_max[d->num])
tree->rates->nd_t[d->num] = u;
}
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void MCMC_Randomize_Node_Times_Top_Down(t_node *a, t_node *d, t_tree *tree)
{
if(d->tax) return;
else
{
int i;
phydbl u;
phydbl t_inf, t_sup;
t_inf = MAX(tree->rates->nd_t[a->num],tree->rates->t_prior_min[d->num]);
t_sup = tree->rates->t_prior_max[d->num];
u = Uni();
u *= (t_sup - t_inf);
u += t_inf;
tree->rates->nd_t[d->num] = u;
For(i,3)
{
if((d->v[i] != a) && (d->b[i] != tree->e_root))
{
MCMC_Randomize_Node_Times_Top_Down(d,d->v[i],tree);
}
}
}
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void MCMC_Get_Acc_Rates(t_mcmc *mcmc)
{
int i;
phydbl eps;
int lag;
if(mcmc->run < (int)(0.01*mcmc->chain_len)) lag = 100;
else lag = 100;
eps = 1.E-6;
For(i,mcmc->n_moves)
{
if(mcmc->run_move[i] - mcmc->prev_run_move[i] > lag)
{
mcmc->acc_rate[i] =
(phydbl)(mcmc->acc_move[i] - mcmc->prev_acc_move[i] + eps) /
(phydbl)(mcmc->run_move[i] - mcmc->prev_run_move[i] + eps) ;
mcmc->prev_run_move[i] = mcmc->run_move[i];
mcmc->prev_acc_move[i] = mcmc->acc_move[i];
MCMC_Adjust_Tuning_Parameter(i,mcmc);
}
}
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void MCMC_Adjust_Tuning_Parameter(int move, t_mcmc *mcmc)
{
if(mcmc->adjust_tuning[move])
{
phydbl scale;
phydbl rate;
phydbl rate_inf,rate_sup;
if(mcmc->run < (int)(0.01*mcmc->chain_len)) scale = 1.5;
else scale = 1.2;
if(!strcmp(mcmc->move_name[move],"tree_height"))
{
rate_inf = 0.3;
rate_sup = 0.3;
/* rate_inf = 0.7; */
/* rate_sup = 0.7; */
}
else if(!strcmp(mcmc->move_name[move],"subtree_height"))
{
rate_inf = 0.2;
rate_sup = 0.2;
}
/* if(!strcmp(mcmc->move_name[move],"tree_rates")) */
/* { */
/* rate_inf = 0.05; */
/* rate_sup = 0.05; */
/* } */
else
{
rate_inf = 0.3;
rate_sup = 0.3;
}
/* PhyML_Printf("\n. %s acc=%d run=%d tune=%f", */
/* mcmc->move_name[move], */
/* mcmc->acc_move[move], */
/* mcmc->run_move[move], */
/* mcmc->tune_move[move]); */
rate = mcmc->acc_rate[move];
if(rate < rate_inf)
{
mcmc->tune_move[move] /= scale;
}
else if(rate > rate_sup)
{
mcmc->tune_move[move] *= scale;
}
if(mcmc->tune_move[move] > mcmc->max_tune) mcmc->tune_move[move] = mcmc->max_tune;
if(mcmc->tune_move[move] < mcmc->min_tune) mcmc->tune_move[move] = mcmc->min_tune;
}
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void MCMC_One_Length(t_edge *b, t_tree *tree)
{
phydbl u;
phydbl new_lnL_data, cur_lnL_data;
phydbl ratio, alpha;
phydbl new_l, cur_l;
phydbl K,mult;
cur_l = b->l;
cur_lnL_data = tree->c_lnL;
K = 0.1;
u = Uni();
mult = EXP(K*(u-0.5));
/* mult = u*(K-1./K)+1./K; */
new_l = cur_l * mult;
if(new_l < tree->mod->l_min || new_l > tree->mod->l_max) return;
b->l = new_l;
new_lnL_data = Lk_At_Given_Edge(b,tree);
/* tree->both_sides = NO; */
/* new_lnL_data = Lk(tree); */
ratio =
(new_lnL_data - cur_lnL_data) +
(LOG(mult));
ratio = EXP(ratio);
alpha = MIN(1.,ratio);
u = Uni();
if(u > alpha) /* Reject */
{
b->l = cur_l;
Update_PMat_At_Given_Edge(b,tree);
tree->c_lnL = cur_lnL_data;
}
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void MCMC_Scale_Br_Lens(t_tree *tree)
{
phydbl u;
phydbl new_lnL_data, cur_lnL_data;
phydbl ratio, alpha;
phydbl K,mult;
int i;
Record_Br_Len(tree);
cur_lnL_data = tree->c_lnL;
K = 1.2;
u = Uni();
mult = u*(K-1./K)+1./K;
For(i,2*tree->n_otu-3)
{
tree->t_edges[i]->l *= mult;
if(tree->t_edges[i]->l < tree->mod->l_min ||
tree->t_edges[i]->l > tree->mod->l_max) return;
}
tree->both_sides = NO;
new_lnL_data = Lk(tree);
ratio =
(new_lnL_data - cur_lnL_data) +
(2*tree->n_otu-5) * (LOG(mult));
ratio = EXP(ratio);
alpha = MIN(1.,ratio);
u = Uni();
if(u > alpha) /* Reject */
{
Restore_Br_Len(tree);
tree->c_lnL = cur_lnL_data;
}
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void MCMC_Br_Lens(t_tree *tree)
{
MCMC_Br_Lens_Pre(tree->t_nodes[0],
tree->t_nodes[0]->v[0],
tree->t_nodes[0]->b[0],tree);
/* int i; */
/* For(i,2*tree->n_otu-3) */
/* { */
/* MCMC_One_Length(tree->t_edges[Rand_Int(0,2*tree->n_otu-4)],acc,run,tree); */
/* } */
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void MCMC_Br_Lens_Pre(t_node *a, t_node *d, t_edge *b, t_tree *tree)
{
int i;
if(a == tree->n_root || d == tree->n_root)
{
PhyML_Printf("\n. Err in file %s at line %d\n",__FILE__,__LINE__);
Exit("\n");
}
MCMC_One_Length(b,tree);
if(d->tax) return;
else
{
For(i,3)
if(d->v[i] != a)
{
Update_P_Lk(tree,d->b[i],d);
MCMC_Br_Lens_Pre(d,d->v[i],d->b[i],tree);
}
Update_P_Lk(tree,b,d);
}
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void MCMC_Kappa(t_tree *tree)
{
int change,i;
change = NO;
tree->mod->update_eigen = YES;
if(tree->io->lk_approx == NORMAL)
{
tree->io->lk_approx = EXACT;
if(tree->mcmc->use_data == YES) Lk(tree);
change = YES;
}
For(i,2*tree->n_otu-2) tree->rates->br_do_updt[i] = NO;
MCMC_Single_Param_Generic(&(tree->mod->kappa->v),0.,15.,tree->mcmc->num_move_kappa,
NULL,&(tree->c_lnL),
NULL,Wrap_Lk,tree->mcmc->move_type[tree->mcmc->num_move_kappa],NO,NULL,tree,NULL);
if(change == YES)
{
tree->io->lk_approx = NORMAL;
if(tree->mcmc->use_data == YES) Lk(tree);
}
tree->mod->update_eigen = NO;
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void MCMC_Rate_Across_Sites(t_tree *tree)
{
if(tree->mod->n_catg == 1) return;
if(tree->mod->free_mixt_rates == YES)
{
MCMC_Free_Mixt_Rate(tree);
}
else
{
MCMC_Alpha(tree);
}
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void MCMC_Alpha(t_tree *tree)
{
int i;
For(i,2*tree->n_otu-2) tree->rates->br_do_updt[i] = NO;
MCMC_Single_Param_Generic(&(tree->mod->alpha->v),0.,100.,tree->mcmc->num_move_ras,
NULL,&(tree->c_lnL),
NULL,Wrap_Lk,tree->mcmc->move_type[tree->mcmc->num_move_ras],NO,NULL,tree,NULL);
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void MCMC_Free_Mixt_Rate(t_tree *tree)
{
phydbl num,denom;
phydbl Jnow,Jthen;
phydbl *z,*y;
phydbl y_cur,z_cur;
phydbl low_bound,up_bound;
int c,i;
int c2updt;
phydbl u;
phydbl hr;
int n_moves;
phydbl cur_lnL_data, new_lnL_data;
phydbl ratio,alpha;
cur_lnL_data = tree->c_lnL;
new_lnL_data = tree->c_lnL;
c = tree->mod->n_catg;
z = tree->mod->gamma_rr_unscaled->v;
y = tree->mod->gamma_r_proba_unscaled->v;
num = z[c-1]*(y[c-1]-y[c-2]);
denom = z[0]*y[0];
for(i=1;imcmc->use_data == YES) ratio += (new_lnL_data - cur_lnL_data);
ratio += LOG(hr);
ratio = EXP(ratio);
alpha = MIN(1.,ratio);
/* printf("\n. class=%d new_val=%f cur_val=%f ratio=%f hr=%f y=%f denom=%f",c2updt,y[c2updt],y_cur,ratio,Jthen/Jnow,y[c-1],denom); */
u = Uni();
if(u > alpha) // Reject
{
y[c2updt] = y_cur;
tree->c_lnL = cur_lnL_data;
}
else // Accept
{
cur_lnL_data = new_lnL_data;
// Update the Jacobian
num = z[c-1]*(y[c-1]-y[c-2]);
denom = z[0]*y[0];
for(i=1;imod->n_catg-1);
// Proposal move.
u = Uni();
/* K = tree->mcmc->tune_move[tree->mcmc->num_move_ras+c2updt+c]; */
/* z_cur = z[c2updt]; */
/* mult = EXP(K*(u-0.5)); */
/* z[c2updt] *= mult; */
u = Uni();
low_bound = (c2updt==0)?(.0):(z[c2updt-1]);
up_bound = (c2updt==c-1)?(100.0):(z[c2updt+1]);
z_cur = z[c2updt];
z[c2updt] = low_bound + u*(up_bound - low_bound);
// Calculate the Jacobian for the change of variable from unscaled
// frequencies to the frequencies themselves.
num = z[c-1]*(y[c-1]-y[c-2]);
denom = z[0]*y[0];
for(i=1;imcmc->use_data == YES) ratio += (new_lnL_data - cur_lnL_data);
ratio += LOG(hr);
/* ratio += LOG(mult); */
ratio = EXP(ratio);
alpha = MIN(1.,ratio);
u = Uni();
if(u > alpha)
{
z[c2updt] = z_cur;
tree->c_lnL = cur_lnL_data;
}
else
{
cur_lnL_data = new_lnL_data;
// Update the Jacobian
num = z[c-1]*(y[c-1]-y[c-2]);
denom = z[0]*y[0];
for(i=1;imod->use_m4mod == NO) return;
tree->mod->update_eigen = YES;
For(i,2*tree->n_otu-2) tree->rates->br_do_updt[i] = YES;
class = Rand_Int(0,tree->mod->m4mod->n_h-1);
min = 0.01;
max = 100.;
u = Uni();
if(u < .5)
{
if(!class)
{
min = 0.01;
max = tree->mod->m4mod->multipl_unscaled[1];
}
else if(class == tree->mod->m4mod->n_h-1)
{
min = tree->mod->m4mod->multipl_unscaled[tree->mod->m4mod->n_h-2];
max = +100.;
}
else
{
min = MIN(tree->mod->m4mod->multipl_unscaled[class-1],tree->mod->m4mod->multipl_unscaled[class+1]);
max = MAX(tree->mod->m4mod->multipl_unscaled[class-1],tree->mod->m4mod->multipl_unscaled[class+1]);
}
MCMC_Single_Param_Generic(&(tree->mod->m4mod->multipl_unscaled[class]),min,max,tree->mcmc->num_move_cov_rates+class+tree->mod->m4mod->n_h,
NULL,&(tree->c_lnL),
NULL,Wrap_Lk,tree->mcmc->move_type[tree->mcmc->num_move_cov_rates+class+tree->mod->m4mod->n_h],NO,NULL,tree,NULL);
}
else
{
MCMC_Single_Param_Generic(&(tree->mod->m4mod->h_fq_unscaled[class]),0.01,+100.,tree->mcmc->num_move_cov_rates+class,
NULL,&(tree->c_lnL),
NULL,Wrap_Lk,tree->mcmc->move_type[tree->mcmc->num_move_cov_rates+class],NO,NULL,tree,NULL);
}
tree->mod->update_eigen = NO;
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void MCMC_Covarion_Switch(t_tree *tree)
{
if(tree->mod->use_m4mod == NO) return;
tree->mod->update_eigen = YES;
MCMC_Single_Param_Generic(&(tree->mod->m4mod->delta),0.01,+100.,tree->mcmc->num_move_cov_switch,
NULL,&(tree->c_lnL),
NULL,Wrap_Lk,tree->mcmc->move_type[tree->mcmc->num_move_cov_switch],NO,NULL,tree,NULL);
tree->mod->update_eigen = NO;
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void MCMC_Birth_Rate(t_tree *tree)
{
MCMC_Single_Param_Generic(&(tree->rates->birth_rate),
tree->rates->birth_rate_min,
tree->rates->birth_rate_max,
tree->mcmc->num_move_birth_rate,
&(tree->rates->c_lnL_times),NULL,
Wrap_Lk_Times,NULL,tree->mcmc->move_type[tree->mcmc->num_move_birth_rate],NO,NULL,tree,NULL);
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void MCMC_Nu(t_tree *tree)
{
phydbl cur_nu,new_nu,cur_lnL_rate,new_lnL_rate;
phydbl u,alpha,ratio;
phydbl min_nu,max_nu;
phydbl K;
phydbl cur_lnL_data, new_lnL_data;
int i;
Record_Br_Len(tree);
cur_nu = -1.0;
new_nu = -1.0;
ratio = 0.0;
K = tree->mcmc->tune_move[tree->mcmc->num_move_nu];
cur_lnL_rate = tree->rates->c_lnL_rates;
new_lnL_rate = tree->rates->c_lnL_rates;
cur_lnL_data = tree->c_lnL;
new_lnL_data = tree->c_lnL;
cur_nu = tree->rates->nu;
min_nu = tree->rates->min_nu;
max_nu = tree->rates->max_nu;
MCMC_Make_Move(&cur_nu,&new_nu,min_nu,max_nu,&ratio,K,tree->mcmc->move_type[tree->mcmc->num_move_nu]);
if(new_nu < max_nu && new_nu > min_nu)
{
tree->rates->nu = new_nu;
new_lnL_rate = RATES_Lk_Rates(tree);
if((tree->rates->model == GUINDON) && (tree->mcmc->use_data))
{
For(i,2*tree->n_otu-2) tree->rates->br_do_updt[i] = YES;
new_lnL_data = Lk(tree);
}
ratio +=
(new_lnL_rate - cur_lnL_rate);
ratio +=
(new_lnL_data - cur_lnL_data);
/* !!!!!!!!!!!!!!!! */
/* Modelling exp(nu) and making move on nu */
/* ratio += (new_nu - cur_nu); */
/* Exponential prior on nu */
/* ratio += LOG(Dexp(new_nu,10.) / Dexp(cur_nu,10.)); */
ratio = EXP(ratio);
alpha = MIN(1.,ratio);
u = Uni();
if(u > alpha) /* Reject */
{
tree->rates->nu = cur_nu;
tree->rates->c_lnL_rates = cur_lnL_rate;
tree->c_lnL = cur_lnL_data;
Restore_Br_Len(tree);
}
else
{
tree->mcmc->acc_move[tree->mcmc->num_move_nu]++;
}
}
tree->mcmc->run_move[tree->mcmc->num_move_nu]++;
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void MCMC_All_Rates(t_tree *tree)
{
phydbl cur_lnL_data, new_lnL_data, cur_lnL_rate;
phydbl u, ratio, alpha;
new_lnL_data = tree->c_lnL;
cur_lnL_data = tree->c_lnL;
cur_lnL_rate = tree->rates->c_lnL_rates;
ratio = 0.0;
Record_Br_Len(tree);
RATES_Record_Rates(tree);
MCMC_Sim_Rate(tree->n_root,tree->n_root->v[0],tree);
MCMC_Sim_Rate(tree->n_root,tree->n_root->v[1],tree);
new_lnL_data = Lk(tree);
ratio += (new_lnL_data - cur_lnL_data);
ratio = EXP(ratio);
alpha = MIN(1.,ratio);
u = Uni();
if(u > alpha) /* Reject */
{
Restore_Br_Len(tree);
RATES_Reset_Rates(tree);
tree->rates->c_lnL_rates = cur_lnL_rate;
}
else
{
tree->rates->c_lnL_rates = RATES_Lk_Rates(tree);;
}
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
/* Only works when simulating from prior */
void MCMC_Sim_Rate(t_node *a, t_node *d, t_tree *tree)
{
int err;
phydbl mean,sd,br_r_a,dt_d;
br_r_a = tree->rates->br_r[a->num];
dt_d = tree->rates->nd_t[d->num] - tree->rates->nd_t[a->num];
sd = SQRT(dt_d*tree->rates->nu);
if(tree->rates->model_log_rates == YES)
{
mean = br_r_a - .5*sd*sd;
}
else
{
mean = br_r_a;
}
if(tree->rates->model == STRICTCLOCK) tree->rates->br_r[d->num] = 1.0;
else
tree->rates->br_r[d->num] = Rnorm_Trunc(mean,sd,tree->rates->min_rate,tree->rates->max_rate,&err);
if(d->tax) return;
else
{
int i;
For(i,3)
if(d->v[i] != a && d->b[i] != tree->e_root)
MCMC_Sim_Rate(d,d->v[i],tree);
}
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void MCMC_Complete_MCMC(t_mcmc *mcmc, t_tree *tree)
{
int i;
phydbl sum;
mcmc->io = tree->io;
mcmc->n_moves = 0;
mcmc->num_move_nd_r = mcmc->n_moves;
mcmc->n_moves += 2*tree->n_otu-1;
mcmc->num_move_br_r = mcmc->n_moves;
mcmc->n_moves += 2*tree->n_otu-2;
mcmc->num_move_nd_t = mcmc->n_moves;
mcmc->n_moves += tree->n_otu-1;
mcmc->num_move_nu = mcmc->n_moves; mcmc->n_moves += 1;
mcmc->num_move_clock_r = mcmc->n_moves; mcmc->n_moves += 1;
mcmc->num_move_tree_height = mcmc->n_moves; mcmc->n_moves += 1;
mcmc->num_move_subtree_height = mcmc->n_moves; mcmc->n_moves += 1;
mcmc->num_move_kappa = mcmc->n_moves; mcmc->n_moves += 1;
mcmc->num_move_tree_rates = mcmc->n_moves; mcmc->n_moves += 1;
mcmc->num_move_subtree_rates = mcmc->n_moves; mcmc->n_moves += 1;
mcmc->num_move_updown_nu_cr = mcmc->n_moves; mcmc->n_moves += 1;
mcmc->num_move_ras = mcmc->n_moves; mcmc->n_moves += 2*tree->mod->n_catg;
mcmc->num_move_updown_t_cr = mcmc->n_moves; mcmc->n_moves += 1;
mcmc->num_move_cov_rates = mcmc->n_moves; mcmc->n_moves += 2*tree->mod->m4mod->n_h;
mcmc->num_move_cov_switch = mcmc->n_moves; mcmc->n_moves += 1;
mcmc->num_move_birth_rate = mcmc->n_moves; mcmc->n_moves += 1;
mcmc->run_move = (int *)mCalloc(mcmc->n_moves,sizeof(int));
mcmc->acc_move = (int *)mCalloc(mcmc->n_moves,sizeof(int));
mcmc->prev_run_move = (int *)mCalloc(mcmc->n_moves,sizeof(int));
mcmc->prev_acc_move = (int *)mCalloc(mcmc->n_moves,sizeof(int));
mcmc->acc_rate = (phydbl *)mCalloc(mcmc->n_moves,sizeof(phydbl));
mcmc->move_weight = (phydbl *)mCalloc(mcmc->n_moves,sizeof(phydbl));
mcmc->move_type = (int *)mCalloc(mcmc->n_moves,sizeof(int));
/* TO DO: instead of n_moves here we should have something like n_param */
mcmc->sum_val = (phydbl *)mCalloc(mcmc->n_moves,sizeof(phydbl));
mcmc->first_val = (phydbl *)mCalloc(mcmc->n_moves,sizeof(phydbl));
mcmc->sum_valsq = (phydbl *)mCalloc(mcmc->n_moves,sizeof(phydbl));
mcmc->sum_curval_nextval = (phydbl *)mCalloc(mcmc->n_moves,sizeof(phydbl));
mcmc->ess = (phydbl *)mCalloc(mcmc->n_moves,sizeof(phydbl));
mcmc->ess_run = (int *)mCalloc(mcmc->n_moves,sizeof(int));
mcmc->start_ess = (int *)mCalloc(mcmc->n_moves,sizeof(int));
mcmc->new_param_val = (phydbl *)mCalloc(mcmc->n_moves,sizeof(phydbl));
mcmc->old_param_val = (phydbl *)mCalloc(mcmc->n_moves,sizeof(phydbl));
mcmc->adjust_tuning = (int *)mCalloc(mcmc->n_moves,sizeof(int));
mcmc->tune_move = (phydbl *)mCalloc(mcmc->n_moves,sizeof(phydbl));
mcmc->move_name = (char **)mCalloc(mcmc->n_moves,sizeof(char *));
For(i,mcmc->n_moves) mcmc->move_name[i] = (char *)mCalloc(50,sizeof(char));
For(i,mcmc->n_moves) mcmc->adjust_tuning[i] = YES;
for(i=mcmc->num_move_br_r;inum_move_br_r+2*tree->n_otu-2;i++) strcpy(mcmc->move_name[i],"br_rate");
for(i=mcmc->num_move_nd_r;inum_move_nd_r+2*tree->n_otu-1;i++) strcpy(mcmc->move_name[i],"nd_rate");
for(i=mcmc->num_move_nd_t;inum_move_nd_t+tree->n_otu-1;i++) strcpy(mcmc->move_name[i],"time");
strcpy(mcmc->move_name[mcmc->num_move_nu],"nu");
strcpy(mcmc->move_name[mcmc->num_move_clock_r],"clock");
strcpy(mcmc->move_name[mcmc->num_move_tree_height],"tree_height");
strcpy(mcmc->move_name[mcmc->num_move_subtree_height],"subtree_height");
strcpy(mcmc->move_name[mcmc->num_move_kappa],"kappa");
strcpy(mcmc->move_name[mcmc->num_move_tree_rates],"tree_rates");
strcpy(mcmc->move_name[mcmc->num_move_subtree_rates],"subtree_rates");
strcpy(mcmc->move_name[mcmc->num_move_updown_nu_cr],"updown_nu_cr");
for(i=mcmc->num_move_ras;inum_move_ras+2*tree->mod->n_catg;i++)
strcpy(mcmc->move_name[i],"ras");
strcpy(mcmc->move_name[mcmc->num_move_updown_t_cr],"updown_t_cr");
for(i=mcmc->num_move_cov_rates;inum_move_cov_rates+2*tree->mod->m4mod->n_h;i++)
strcpy(mcmc->move_name[i],"cov_rates");
strcpy(mcmc->move_name[mcmc->num_move_cov_switch],"cov_switch");
strcpy(mcmc->move_name[mcmc->num_move_birth_rate],"birth_rate");
if(tree->rates->model_log_rates == YES)
for(i=mcmc->num_move_br_r;inum_move_br_r+2*tree->n_otu-2;i++) mcmc->move_type[i] = MCMC_MOVE_RANDWALK_NORMAL;
else
for(i=mcmc->num_move_br_r;inum_move_br_r+2*tree->n_otu-2;i++) mcmc->move_type[i] = MCMC_MOVE_SCALE_THORNE;
for(i=mcmc->num_move_nd_r;inum_move_nd_r+2*tree->n_otu-1;i++) mcmc->move_type[i] = MCMC_MOVE_SCALE_THORNE;
for(i=mcmc->num_move_nd_t;inum_move_nd_t+tree->n_otu-1;i++) mcmc->move_type[i] = MCMC_MOVE_RANDWALK_UNIFORM;
/* for(i=mcmc->num_move_nd_t;inum_move_nd_t+tree->n_otu-1;i++) mcmc->move_type[i] = MCMC_MOVE_SCALE_THORNE; */
mcmc->move_type[mcmc->num_move_nu] = MCMC_MOVE_SCALE_THORNE;
mcmc->move_type[mcmc->num_move_clock_r] = MCMC_MOVE_SCALE_THORNE;
mcmc->move_type[mcmc->num_move_tree_height] = MCMC_MOVE_SCALE_THORNE;
mcmc->move_type[mcmc->num_move_subtree_height] = MCMC_MOVE_SCALE_THORNE;
mcmc->move_type[mcmc->num_move_kappa] = MCMC_MOVE_SCALE_THORNE;
mcmc->move_type[mcmc->num_move_tree_rates] = MCMC_MOVE_SCALE_THORNE;
mcmc->move_type[mcmc->num_move_subtree_rates] = MCMC_MOVE_SCALE_THORNE;
mcmc->move_type[mcmc->num_move_updown_nu_cr] = MCMC_MOVE_RANDWALK_NORMAL;
for(i=mcmc->num_move_ras;inum_move_ras+2*tree->mod->n_catg;i++) mcmc->move_type[i] = MCMC_MOVE_RANDWALK_NORMAL;
mcmc->move_type[mcmc->num_move_updown_t_cr] = MCMC_MOVE_SCALE_THORNE;
for(i=mcmc->num_move_cov_rates;inum_move_cov_rates+2*tree->mod->m4mod->n_h;i++) mcmc->move_type[i] = MCMC_MOVE_SCALE_THORNE;
mcmc->move_type[mcmc->num_move_cov_switch] = MCMC_MOVE_SCALE_THORNE;
mcmc->move_type[mcmc->num_move_birth_rate] = MCMC_MOVE_SCALE_THORNE;
/* We start with small tuning parameter values in order to have inflated ESS
for clock_r */
For(i,mcmc->n_moves)
{
switch(mcmc->move_type[i])
{
case MCMC_MOVE_RANDWALK_NORMAL:
{
mcmc->tune_move[i] = 1.E-1;
break;
}
case MCMC_MOVE_RANDWALK_UNIFORM:
{
mcmc->tune_move[i] = 2.0;
break;
}
case MCMC_MOVE_SCALE_GAMMA:
{
mcmc->tune_move[i] = 1.0;
break;
}
case MCMC_MOVE_SCALE_THORNE:
{
mcmc->tune_move[i] = 1.0;
break;
}
}
}
for(i=mcmc->num_move_br_r;inum_move_br_r+2*tree->n_otu-2;i++) mcmc->move_weight[i] = (phydbl)(1./(2.*tree->n_otu-2)); /* Rates */
for(i=mcmc->num_move_nd_r;inum_move_nd_r+2*tree->n_otu-1;i++) mcmc->move_weight[i] = 0.0; /* Node rates */
for(i=mcmc->num_move_nd_t;inum_move_nd_t+tree->n_otu-1;i++) mcmc->move_weight[i] = (phydbl)(1./(tree->n_otu-1)); /* Times */
mcmc->move_weight[mcmc->num_move_clock_r] = 1.0;
mcmc->move_weight[mcmc->num_move_tree_height] = 10.0;
mcmc->move_weight[mcmc->num_move_subtree_height] = 0.0;
mcmc->move_weight[mcmc->num_move_nu] = 2.0;
mcmc->move_weight[mcmc->num_move_kappa] = 0.5;
mcmc->move_weight[mcmc->num_move_tree_rates] = 1.0;
mcmc->move_weight[mcmc->num_move_subtree_rates] = 0.5;
mcmc->move_weight[mcmc->num_move_updown_nu_cr] = 0.0;
for(i=mcmc->num_move_ras;inum_move_ras+2*tree->mod->n_catg;i++) mcmc->move_weight[i] = 0.5*(1./(phydbl)tree->mod->n_catg);
mcmc->move_weight[mcmc->num_move_updown_t_cr] = 0.0; /* Does not seem to work well (does not give uniform prior on root height
when sampling from prior) */
for(i=mcmc->num_move_cov_rates;inum_move_cov_rates+2*tree->mod->m4mod->n_h;i++) mcmc->move_weight[i] = 0.5*(1./(phydbl)tree->mod->m4mod->n_h);
mcmc->move_weight[mcmc->num_move_cov_switch] = 1.0;
mcmc->move_weight[mcmc->num_move_birth_rate] = 1.0;
/* for(i=mcmc->num_move_br_r;inum_move_br_r+2*tree->n_otu-2;i++) mcmc->move_weight[i] = 0.0; /\* Rates *\/ */
/* for(i=mcmc->num_move_nd_r;inum_move_nd_r+2*tree->n_otu-1;i++) mcmc->move_weight[i] = 0.0; /\* Node rates *\/ */
/* for(i=mcmc->num_move_nd_t;inum_move_nd_t+tree->n_otu-1;i++) mcmc->move_weight[i] = (phydbl)(1./(tree->n_otu-1)); /\* Times *\/ */
/* mcmc->move_weight[mcmc->num_move_clock_r] = 1.0; */
/* mcmc->move_weight[mcmc->num_move_tree_height] = 0.0; */
/* mcmc->move_weight[mcmc->num_move_subtree_height] = 0.0; */
/* mcmc->move_weight[mcmc->num_move_nu] = 0.0; */
/* mcmc->move_weight[mcmc->num_move_kappa] = 0.0; */
/* mcmc->move_weight[mcmc->num_move_tree_rates] = 0.0; */
/* mcmc->move_weight[mcmc->num_move_subtree_rates] = 0.0; */
/* mcmc->move_weight[mcmc->num_move_updown_nu_cr] = 0.0; */
/* for(i=mcmc->num_move_ras;inum_move_ras+2*tree->mod->n_catg;i++) mcmc->move_weight[i] = 0.5*(1./(phydbl)tree->mod->n_catg);; */
/* mcmc->move_weight[mcmc->num_move_updown_t_cr] = 0.0; /\* Does not seem to work well (does not give uniform prior on root height */
/* when sampling from prior) *\/ */
/* for(i=mcmc->num_move_cov_rates;inum_move_cov_rates+2*tree->mod->m4mod->n_h;i++) mcmc->move_weight[i] = 0.0; */
/* mcmc->move_weight[mcmc->num_move_cov_switch] = 0.0; */
sum = 0.0;
For(i,mcmc->n_moves) sum += mcmc->move_weight[i];
For(i,mcmc->n_moves) mcmc->move_weight[i] /= sum;
for(i=1;in_moves;i++) mcmc->move_weight[i] += mcmc->move_weight[i-1];
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void MCMC_Initialize_Param_Val(t_mcmc *mcmc, t_tree *tree)
{
int i;
mcmc->old_param_val[mcmc->num_move_nu] = tree->rates->nu;
mcmc->old_param_val[mcmc->num_move_clock_r] = tree->rates->clock_r;
mcmc->old_param_val[mcmc->num_move_tree_height] = tree->rates->nd_t[tree->n_root->num];
mcmc->old_param_val[mcmc->num_move_kappa] = tree->mod->kappa->v;
For(i,2*tree->n_otu-2)
mcmc->old_param_val[mcmc->num_move_br_r+i] = tree->rates->br_r[i];
For(i,tree->n_otu-1)
mcmc->old_param_val[mcmc->num_move_nd_t+i] = tree->rates->nd_t[tree->n_otu+i];
For(i,2*tree->n_otu-1)
mcmc->old_param_val[mcmc->num_move_nd_r+i] = tree->rates->nd_r[i];
For(i,mcmc->n_moves) tree->mcmc->new_param_val[i] = tree->mcmc->old_param_val[i];
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void MCMC_Copy_To_New_Param_Val(t_mcmc *mcmc, t_tree *tree)
{
int i;
mcmc->new_param_val[mcmc->num_move_nu] = tree->rates->nu;
mcmc->new_param_val[mcmc->num_move_clock_r] = tree->rates->clock_r;
mcmc->new_param_val[mcmc->num_move_tree_height] = tree->rates->nd_t[tree->n_root->num];
mcmc->new_param_val[mcmc->num_move_kappa] = tree->mod->kappa->v;
mcmc->new_param_val[mcmc->num_move_birth_rate] = tree->rates->birth_rate;
For(i,2*tree->n_otu-2)
mcmc->new_param_val[mcmc->num_move_br_r+i] = tree->rates->br_r[i];
For(i,tree->n_otu-1)
mcmc->new_param_val[mcmc->num_move_nd_t+i] = tree->rates->nd_t[tree->n_otu+i];
For(i,2*tree->n_otu-1)
mcmc->new_param_val[mcmc->num_move_nd_r+i] = tree->rates->nd_r[i];
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void MCMC_Slice_One_Rate(t_node *a, t_node *d, int traversal, t_tree *tree)
{
phydbl L,R; /* Left and Right limits of the slice */
phydbl w; /* window width */
phydbl u;
phydbl x0,x1;
phydbl logy;
t_edge *b;
int i;
b = NULL;
if(a == tree->n_root) b = tree->e_root;
else For(i,3) if(d->v[i] == a) { b = d->b[i]; break; }
w = 0.05;
/* w = 10.; */
x0 = tree->rates->br_r[d->num];
logy = tree->c_lnL+tree->rates->c_lnL_rates - Rexp(1.);
u = Uni();
L = x0 - w*u;
R = L + w;
do
{
tree->rates->br_r[d->num] = L;
tree->rates->br_do_updt[d->num] = YES;
RATES_Update_Cur_Bl(tree);
Lk_At_Given_Edge(b,tree);
RATES_Lk_Rates(tree);
if(L < tree->rates->min_rate) { L = tree->rates->min_rate - w; break;}
L = L - w;
}
while(tree->c_lnL + tree->rates->c_lnL_rates > logy);
L = L + w;
do
{
tree->rates->br_r[d->num] = R;
tree->rates->br_do_updt[d->num] = YES;
RATES_Update_Cur_Bl(tree);
Lk_At_Given_Edge(b,tree);
RATES_Lk_Rates(tree);
if(R > tree->rates->max_rate) { R = tree->rates->max_rate + w; break;}
R = R + w;
}
while(tree->c_lnL + tree->rates->c_lnL_rates > logy);
R = R - w;
for(;;)
{
u = Uni();
x1 = L + u*(R-L);
tree->rates->br_r[d->num] = x1;
tree->rates->br_do_updt[d->num] = YES;
RATES_Update_Cur_Bl(tree);
Lk_At_Given_Edge(b,tree);
RATES_Lk_Rates(tree);
if(tree->c_lnL + tree->rates->c_lnL_rates > logy) break;
if(x1 < x0) L = x1;
else R = x1;
}
if(traversal == YES)
{
if(d->tax == YES) return;
else
{
For(i,3)
if(d->v[i] != a && d->b[i] != tree->e_root)
{
if(tree->io->lk_approx == EXACT && tree->mcmc->use_data) Update_P_Lk(tree,d->b[i],d);
/* if(tree->io->lk_approx == EXACT && tree->mcmc->use_data) { tree->both_sides = YES; Lk(tree); } */
MCMC_Slice_One_Rate(d,d->v[i],YES,tree);
}
}
if(tree->io->lk_approx == EXACT && tree->mcmc->use_data) Update_P_Lk(tree,b,d);
/* if(tree->io->lk_approx == EXACT && tree->mcmc->use_data) { tree->both_sides = YES; Lk(tree); } */
}
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void MCMC_Make_Move(phydbl *cur, phydbl *new, phydbl inf, phydbl sup, phydbl *loghr, phydbl tune, int move_type)
{
phydbl u;
switch(move_type)
{
case MCMC_MOVE_RANDWALK_NORMAL:
{
*new = *cur + Rnorm(0.0,tune);
/* Do not use reflection here */
*loghr = 0.0;
break;
}
case MCMC_MOVE_RANDWALK_UNIFORM:
{
u = Uni();
/* *new = u * (2.*tune) + (*cur) - tune; */
/* *new = Reflect(*new,inf,sup); */
*new = u*(sup-inf)+inf;
*loghr = 0.0;
break;
}
case MCMC_MOVE_SCALE_THORNE:
{
u = Uni();
*new = (*cur) * EXP(tune*(u-.5));
*loghr = LOG((*new)/(*cur));
break;
}
case MCMC_MOVE_SCALE_GAMMA:
{
phydbl r;
*new = (*cur) * Rgamma(1./tune,tune);
r = (*new)/(*cur);
*loghr = -LOG(r) + LOG(Dgamma(1./r,1./tune,tune)/Dgamma(r,1./tune,tune));
break;
}
default :
{
PhyML_Printf("\n. Move not implemented");
Exit("");
break;
}
}
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
void MCMC_Read_Param_Vals(t_tree *tree)
{
char *token;
int sizemax;
FILE *in_fp;
phydbl val;
int i,v;
in_fp = tree->mcmc->in_fp_par;
sizemax = T_MAX_LINE;
token = (char *)mCalloc(sizemax,sizeof(char));
if(fgets(token,sizemax,in_fp)); // Skip first line
if(fgets(token,sizemax,in_fp)); // Skip second
v=fscanf(in_fp,"%lf\t",&val); // Run
/* PhyML_Printf("\n. Run = %d",(int)val); */
v=fscanf(in_fp,"%lf\t",&val); // LnLike[Exact]
/* PhyML_Printf("\n. LnLike = %f",val); */
v=fscanf(in_fp,"%lf\t",&val); // LnLike[Approx]
/* PhyML_Printf("\n. LnLike = %f",val); */
v=fscanf(in_fp,"%lf\t",&val); // LnPriorRate
/* PhyML_Printf("\n. LnPrior = %f",val); */
v=fscanf(in_fp,"%lf\t",&val); // LnPriorTime
/* PhyML_Printf("\n. LnPrior = %f",val); */
v=fscanf(in_fp,"%lf\t",&val); // LnPosterior
/* PhyML_Printf("\n. LnPost = %f",val); */
v=fscanf(in_fp,"%lf\t",&val); // ClockRate
tree->rates->clock_r = val;
/* PhyML_Printf("\n. Clock = %f",val); */
v=fscanf(in_fp,"%lf\t",&val); // EvolRate
v=fscanf(in_fp,"%lf\t",&val); // Nu
tree->rates->nu = val;
/* PhyML_Printf("\n. Nu = %f",val); */
v=fscanf(in_fp,"%lf\t",&val); // Birth rate
tree->rates->birth_rate = val;
v=fscanf(in_fp,"%lf\t",&val); // TsTv
tree->mod->kappa->v = val;
/* PhyML_Printf("\n. TsTv = %f",val); */
For(i,tree->n_otu-1)
{
v=fscanf(in_fp,"%lf\t",&val); // Node heights
tree->rates->nd_t[i+tree->n_otu] = val;
}
For(i,2*tree->n_otu-2)
{
v=fscanf(in_fp,"%lf\t",&val); // Edge average rates
tree->rates->br_r[i] = LOG(val);
}
Free(token);
}
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////
phyml-20120412/src/optimiz.h 0000644 0001750 0001750 00000016041 11637265627 012475 0000000 0000000 /*
PHYML : a program that computes maximum likelihood phylogenies from
DNA or AA homologous sequences
Copyright (C) Stephane Guindon. Oct 2003 onward
All parts of the source except where indicated are distributed under
the GNU public licence. See http://www.opensource.org for details.
*/
#include
#ifndef OPTIMIZ_H
#define OPTIMIZ_H
#include "utilities.h"
#include "lk.h"
#include "free.h"
#include "models.h"
#include "mg.h"
#include "tiporder.h"
void Optimiz_Ext_Br(t_tree *tree);
void Optimize_Alpha(t_tree *tree);
void Optimize_Kappa(t_tree *tree);
void Optimize_Lambda(t_tree *tree);
void Optimize_Param_Parall(t_tree *tree);
phydbl Optimize_Branch_Quad(t_tree *tree, calign *cdata, t_edge *b_fcus);
void Optimize_After_Hide(t_tree *tree, calign *cdata, t_node *h);
void Round_Optimize(t_tree *tree, calign *data, int n_round_max);
int Dist_Seq_Brak(phydbl *ax, phydbl *bx, phydbl *cx,
phydbl *fa, phydbl *fb, phydbl *fc,
calign *data, int num1, int num2, model *mod);
phydbl Dist_Seq_Brent(phydbl ax, phydbl bx, phydbl cx, phydbl tol,
phydbl *xmin, calign *data,
int num1, int num2, model *mod);
phydbl Kappa_Golden(phydbl ax, phydbl bx, phydbl cx, phydbl tol,
phydbl *xmin, t_tree *tree, calign *cdata);
phydbl Lambda_Golden(phydbl ax, phydbl bx, phydbl cx, phydbl tol,
phydbl *xmin, t_tree *tree, calign *cdata);
phydbl Alpha_Golden_Br_Opt(phydbl ax, phydbl bx, phydbl cx, phydbl tol,
phydbl *xmin, t_tree *tree, calign *cdata,
int n_opt, phydbl *init_l);
phydbl Alpha_Golden(phydbl ax, phydbl bx, phydbl cx, phydbl tol,phydbl *xmin,
t_tree *tree, calign *cdata);
phydbl Br_Len_Golden(phydbl ax, phydbl bx, phydbl cx, phydbl tol,
phydbl *xmin, t_edge *b_fcus, t_tree *tree);
phydbl Br_Len_Brent(phydbl ax, phydbl bx, phydbl cx, phydbl tol,
t_edge *b_fcus, t_tree *tree, int n_iter_max, int quickdirty);
int Br_Len_Brak(phydbl *ax, phydbl *bx, phydbl *cx,
phydbl *fa, phydbl *fb, phydbl *fc,
t_edge *b_fcus, t_tree *tree);
phydbl Optimize_Path_Length(model *mod, calign *cdata, t_edge *a,
int lra, t_edge *b, int lrb, phydbl i_len);
void Optimize_Param_Serie(t_node *a, t_node *d, t_edge *b_fcus, t_tree *tree,
calign *cdata, int n_passes);
phydbl Optimize_Dist(model *mod, phydbl init, calign *twoseqs);
phydbl Pinvar_Golden(phydbl ax, phydbl bx, phydbl cx, phydbl tol,
phydbl *xmin, t_tree *tree, calign *cdata, int n_iter_max);
void Optimize_Pinvar(t_tree *tree);
int Lambda_Brak(phydbl *ax, phydbl *bx, phydbl *cx,
phydbl *fa, phydbl *fb, phydbl *fc,
t_tree *tree);
int Kappa_Brak(phydbl *ax, phydbl *bx, phydbl *cx,
phydbl *fa, phydbl *fb, phydbl *fc,
t_tree *tree);
int Alpha_Brak(phydbl *ax, phydbl *bx, phydbl *cx,
phydbl *fa, phydbl *fb, phydbl *fc,
t_tree *tree);
int Pinvar_Brak(phydbl *ax, phydbl *bx, phydbl *cx,
phydbl *fa, phydbl *fb, phydbl *fc,
t_tree *tree);
void Optimiz_All_Free_Param(t_tree *tree, int verbose);
void Optimiz_RRparam_GTR(t_tree *tree, int num_param);
phydbl RRparam_GTR_Golden(phydbl ax, phydbl bx, phydbl cx, phydbl tol,
phydbl *xmin, t_tree *tree, calign *cdata, phydbl *param, int n_iter_max);
int Powell_GTR_Param(t_tree *tree, phydbl *p, int n, phydbl ftol);
phydbl Linmin_GTR_Param(t_tree *tree,phydbl *p, phydbl *xi, int n);
phydbl F1dim(t_tree *tree, phydbl x, phydbl *p, phydbl *xi, phydbl n);
int Mnbrak_1dim(phydbl *ax, phydbl *bx, phydbl *cx,
phydbl *fa, phydbl *fb, phydbl *fc,
t_tree *tree,
phydbl *p, phydbl *xi, phydbl n);
phydbl Brent_1dim(phydbl ax, phydbl bx, phydbl cx,
phydbl tol, phydbl *xmin,
t_tree *tree,
phydbl *p, phydbl *xi, phydbl n);
int Min_With_Derivatives(t_tree *tree, phydbl *p, int n, phydbl ftol, phydbl step_size,
phydbl (*func) (), void (*dfunc)(), phydbl (*linmin)());
void BFGS(t_tree *tree,
phydbl *p,
int n,
phydbl gtol,
phydbl step_size,
phydbl(*func)(t_tree *tree),
int(*dfunc)(t_tree *tree,phydbl *param,int n_param,phydbl stepsize,phydbl(*func)(t_tree *tree),phydbl *derivatives),
int(*lnsrch)(t_tree *tree, int n, phydbl *xold, phydbl fold,phydbl *g, phydbl *p, phydbl *x,phydbl *f, phydbl stpmax, int *check),
int *failed);
int Lnsrch_RR_Param(t_tree *tree, int n, phydbl *xold, phydbl fold, phydbl *g, phydbl *p, phydbl *x,
phydbl *f, phydbl stpmax, int *check);
void Optimize_Single_Param_Generic(t_tree *tree, phydbl *param, phydbl lim_inf, phydbl lim_sup, phydbl tol, int n_max_iter, int quickdirty);
int Generic_Brak(phydbl *param,
phydbl *ax, phydbl *bx, phydbl *cx,
phydbl *fa, phydbl *fb, phydbl *fc,
phydbl lim_inf, phydbl lim_sup,
t_tree *tree);
phydbl Generic_Brent(phydbl ax, phydbl bx, phydbl cx, phydbl tol,
phydbl *xmin, t_tree *tree, int n_iter_max,int quickdirty);
void Optimize_Br_Len_Serie(t_node *a, t_node *d, t_edge *b_fcus, t_tree *tree,calign *cdata);
int Lnsrch_Nucleotide_Frequencies(t_tree *tree, int n, phydbl *xold,
phydbl fold, phydbl *g, phydbl *p, phydbl *x,
phydbl *f, phydbl stpmax, int *check);
void Optimize_Global_Rate(t_tree *tree);
phydbl Br_Len_Brent_Default(t_edge *b_fcus, t_tree *tree);
void EM_Dist(model *mod, calign *data);
phydbl Dist_F_Brent(phydbl ax, phydbl bx, phydbl cx, phydbl tol, int n_iter_max,
phydbl *param, phydbl *F, model *mod);
int Dist_F_Brak(phydbl *ax, phydbl *bx, phydbl *cx, phydbl *F, phydbl *param, model *mod);
void Opt_Dist_F(phydbl *dist, phydbl *F, model *mod);
phydbl Missing_Dist_Brent(phydbl ax, phydbl bx, phydbl cx, phydbl tol, int n_iter_max,
int x, int y, matrix *mat);
int Missing_Dist_Brak(phydbl *ax, phydbl *bx, phydbl *cx, int x, int y, matrix *mat);
void Opt_Missing_Dist(int x, int y, matrix *mat);
int Optimiz_Alpha_And_Pinv(t_tree *tree);
int Lnsrch_RR_Cov_Param(t_tree *tree, int n, phydbl *xold, phydbl fold,
phydbl *g, phydbl *p, phydbl *x,
phydbl *f, phydbl stpmax, int *check);
phydbl Node_Time_Brent(phydbl ax, phydbl bx, phydbl cx, phydbl tol,
t_node *anc, t_node *des, t_tree *tree, int n_iter_max);
phydbl Time_Stamps_Mult_Brent(phydbl ax, phydbl bx, phydbl cx, phydbl tol,
t_tree *tree, int n_iter_max);
phydbl Branch_Rate_Shape_Brent(phydbl ax, phydbl bx, phydbl cx, phydbl tol,
phydbl *xmin, t_tree *tree, int n_iter_max);
phydbl Node_Time_Brent_Fixed_Br_Len(phydbl ax, phydbl bx, phydbl cx, phydbl tol,
t_node *n, t_tree *tree, int n_iter_max);
phydbl Generic_Brent_Lk(phydbl *param, phydbl ax, phydbl cx, phydbl tol,
int n_iter_max, int quickdirty,
phydbl (*obj_func)(t_edge *,t_tree *,supert_tree *),
t_edge *branch, t_tree *tree, supert_tree *stree);
void Round_Optimize_Node_Heights(t_tree *tree);
void Opt_Node_Heights_Recurr_Pre(t_node *a, t_node *d, t_tree *tree);
void Opt_Node_Heights_Recurr(t_tree *tree);
int Lnsrch_Free_Mixt_Rates(t_tree *tree, int n, phydbl *xold, phydbl fold, phydbl *g, phydbl *p, phydbl *x,
phydbl *f, phydbl stpmax, int *check);
#endif
phyml-20120412/src/interface.h 0000644 0001750 0001750 00000001445 11637265540 012736 0000000 0000000 /*
PhyML: a program that computes maximum likelihood phylogenies from
DNA or AA homologous sequences.
Copyright (C) Stephane Guindon. Oct 2003 onward.
All parts of the source except where indicated are distributed under
the GNU public licence. See http://www.opensource.org for details.
*/
#include
#ifndef INTERFACE_H
#define INTERFACE_H
#include "utilities.h"
#include "help.h"
#include "models.h"
#include "free.h"
#include "help.h"
void Launch_Interface(option *input);
void Clear();
void Launch_Interface_Input(option *input);
void Launch_Interface_Data_Type(option *input);
void Launch_Interface_Model(option *input);
void Launch_Interface_Topo_Search(option *input);
void Launch_Interface_Branch_Support(option *input);
void Launch_Interface_Multigene(option *input);
#endif
phyml-20120412/COPYING 0000755 0001750 0001750 00000043110 11321753770 011064 0000000 0000000 GNU GENERAL PUBLIC LICENSE
Version 2, June 1991
Copyright (C) 1989, 1991 Free Software Foundation, Inc.
59 Temple Place, Suite 330, Boston, MA 02111-1307 USA
Everyone is permitted to copy and distribute verbatim copies
of this license document, but changing it is not allowed.
Preamble
The licenses for most software are designed to take away your
freedom to share and change it. By contrast, the GNU General Public
License is intended to guarantee your freedom to share and change free
software--to make sure the software is free for all its users. This
General Public License applies to most of the Free Software
Foundation's software and to any other program whose authors commit to
using it. (Some other Free Software Foundation software is covered by
the GNU Library General Public License instead.) You can apply it to
your programs, too.
When we speak of free software, we are referring to freedom, not
price. Our General Public Licenses are designed to make sure that you
have the freedom to distribute copies of free software (and charge for
this service if you wish), that you receive source code or can get it
if you want it, that you can change the software or use pieces of it
in new free programs; and that you know you can do these things.
To protect your rights, we need to make restrictions that forbid
anyone to deny you these rights or to ask you to surrender the rights.
These restrictions translate to certain responsibilities for you if you
distribute copies of the software, or if you modify it.
For example, if you distribute copies of such a program, whether
gratis or for a fee, you must give the recipients all the rights that
you have. You must make sure that they, too, receive or can get the
source code. And you must show them these terms so they know their
rights.
We protect your rights with two steps: (1) copyright the software, and
(2) offer you this license which gives you legal permission to copy,
distribute and/or modify the software.
Also, for each author's protection and ours, we want to make certain
that everyone understands that there is no warranty for this free
software. If the software is modified by someone else and passed on, we
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Finally, any free program is threatened constantly by software
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program will individually obtain patent licenses, in effect making the
program proprietary. To prevent this, we have made it clear that any
patent must be licensed for everyone's free use or not licensed at all.
The precise terms and conditions for copying, distribution and
modification follow.
GNU GENERAL PUBLIC LICENSE
TERMS AND CONDITIONS FOR COPYING, DISTRIBUTION AND MODIFICATION
0. This License applies to any program or other work which contains
a notice placed by the copyright holder saying it may be distributed
under the terms of this General Public License. The "Program", below,
refers to any such program or work, and a "work based on the Program"
means either the Program or any derivative work under copyright law:
that is to say, a work containing the Program or a portion of it,
either verbatim or with modifications and/or translated into another
language. (Hereinafter, translation is included without limitation in
the term "modification".) Each licensee is addressed as "you".
Activities other than copying, distribution and modification are not
covered by this License; they are outside its scope. The act of
running the Program is not restricted, and the output from the Program
is covered only if its contents constitute a work based on the
Program (independent of having been made by running the Program).
Whether that is true depends on what the Program does.
1. You may copy and distribute verbatim copies of the Program's
source code as you receive it, in any medium, provided that you
conspicuously and appropriately publish on each copy an appropriate
copyright notice and disclaimer of warranty; keep intact all the
notices that refer to this License and to the absence of any warranty;
and give any other recipients of the Program a copy of this License
along with the Program.
You may charge a fee for the physical act of transferring a copy, and
you may at your option offer warranty protection in exchange for a fee.
2. You may modify your copy or copies of the Program or any portion
of it, thus forming a work based on the Program, and copy and
distribute such modifications or work under the terms of Section 1
above, provided that you also meet all of these conditions:
a) You must cause the modified files to carry prominent notices
stating that you changed the files and the date of any change.
b) You must cause any work that you distribute or publish, that in
whole or in part contains or is derived from the Program or any
part thereof, to be licensed as a whole at no charge to all third
parties under the terms of this License.
c) If the modified program normally reads commands interactively
when run, you must cause it, when started running for such
interactive use in the most ordinary way, to print or display an
announcement including an appropriate copyright notice and a
notice that there is no warranty (or else, saying that you provide
a warranty) and that users may redistribute the program under
these conditions, and telling the user how to view a copy of this
License. (Exception: if the Program itself is interactive but
does not normally print such an announcement, your work based on
the Program is not required to print an announcement.)
These requirements apply to the modified work as a whole. If
identifiable sections of that work are not derived from the Program,
and can be reasonably considered independent and separate works in
themselves, then this License, and its terms, do not apply to those
sections when you distribute them as separate works. But when you
distribute the same sections as part of a whole which is a work based
on the Program, the distribution of the whole must be on the terms of
this License, whose permissions for other licensees extend to the
entire whole, and thus to each and every part regardless of who wrote it.
Thus, it is not the intent of this section to claim rights or contest
your rights to work written entirely by you; rather, the intent is to
exercise the right to control the distribution of derivative or
collective works based on the Program.
In addition, mere aggregation of another work not based on the Program
with the Program (or with a work based on the Program) on a volume of
a storage or distribution medium does not bring the other work under
the scope of this License.
3. You may copy and distribute the Program (or a work based on it,
under Section 2) in object code or executable form under the terms of
Sections 1 and 2 above provided that you also do one of the following:
a) Accompany it with the complete corresponding machine-readable
source code, which must be distributed under the terms of Sections
1 and 2 above on a medium customarily used for software interchange; or,
b) Accompany it with a written offer, valid for at least three
years, to give any third party, for a charge no more than your
cost of physically performing source distribution, a complete
machine-readable copy of the corresponding source code, to be
distributed under the terms of Sections 1 and 2 above on a medium
customarily used for software interchange; or,
c) Accompany it with the information you received as to the offer
to distribute corresponding source code. (This alternative is
allowed only for noncommercial distribution and only if you
received the program in object code or executable form with such
an offer, in accord with Subsection b above.)
The source code for a work means the preferred form of the work for
making modifications to it. For an executable work, complete source
code means all the source code for all modules it contains, plus any
associated interface definition files, plus the scripts used to
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anything that is normally distributed (in either source or binary
form) with the major components (compiler, kernel, and so on) of the
operating system on which the executable runs, unless that component
itself accompanies the executable.
If distribution of executable or object code is made by offering
access to copy from a designated place, then offering equivalent
access to copy the source code from the same place counts as
distribution of the source code, even though third parties are not
compelled to copy the source along with the object code.
4. You may not copy, modify, sublicense, or distribute the Program
except as expressly provided under this License. Any attempt
otherwise to copy, modify, sublicense or distribute the Program is
void, and will automatically terminate your rights under this License.
However, parties who have received copies, or rights, from you under
this License will not have their licenses terminated so long as such
parties remain in full compliance.
5. You are not required to accept this License, since you have not
signed it. However, nothing else grants you permission to modify or
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prohibited by law if you do not accept this License. Therefore, by
modifying or distributing the Program (or any work based on the
Program), you indicate your acceptance of this License to do so, and
all its terms and conditions for copying, distributing or modifying
the Program or works based on it.
6. Each time you redistribute the Program (or any work based on the
Program), the recipient automatically receives a license from the
original licensor to copy, distribute or modify the Program subject to
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You are not responsible for enforcing compliance by third parties to
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infringement or for any other reason (not limited to patent issues),
conditions are imposed on you (whether by court order, agreement or
otherwise) that contradict the conditions of this License, they do not
excuse you from the conditions of this License. If you cannot
distribute so as to satisfy simultaneously your obligations under this
License and any other pertinent obligations, then as a consequence you
may not distribute the Program at all. For example, if a patent
license would not permit royalty-free redistribution of the Program by
all those who receive copies directly or indirectly through you, then
the only way you could satisfy both it and this License would be to
refrain entirely from distribution of the Program.
If any portion of this section is held invalid or unenforceable under
any particular circumstance, the balance of the section is intended to
apply and the section as a whole is intended to apply in other
circumstances.
It is not the purpose of this section to induce you to infringe any
patents or other property right claims or to contest validity of any
such claims; this section has the sole purpose of protecting the
integrity of the free software distribution system, which is
implemented by public license practices. Many people have made
generous contributions to the wide range of software distributed
through that system in reliance on consistent application of that
system; it is up to the author/donor to decide if he or she is willing
to distribute software through any other system and a licensee cannot
impose that choice.
This section is intended to make thoroughly clear what is believed to
be a consequence of the rest of this License.
8. If the distribution and/or use of the Program is restricted in
certain countries either by patents or by copyrighted interfaces, the
original copyright holder who places the Program under this License
may add an explicit geographical distribution limitation excluding
those countries, so that distribution is permitted only in or among
countries not thus excluded. In such case, this License incorporates
the limitation as if written in the body of this License.
9. The Free Software Foundation may publish revised and/or new versions
of the General Public License from time to time. Such new versions will
be similar in spirit to the present version, but may differ in detail to
address new problems or concerns.
Each version is given a distinguishing version number. If the Program
specifies a version number of this License which applies to it and "any
later version", you have the option of following the terms and conditions
either of that version or of any later version published by the Free
Software Foundation. If the Program does not specify a version number of
this License, you may choose any version ever published by the Free Software
Foundation.
10. If you wish to incorporate parts of the Program into other free
programs whose distribution conditions are different, write to the author
to ask for permission. For software which is copyrighted by the Free
Software Foundation, write to the Free Software Foundation; we sometimes
make exceptions for this. Our decision will be guided by the two goals
of preserving the free status of all derivatives of our free software and
of promoting the sharing and reuse of software generally.
NO WARRANTY
11. BECAUSE THE PROGRAM IS LICENSED FREE OF CHARGE, THERE IS NO WARRANTY
FOR THE PROGRAM, TO THE EXTENT PERMITTED BY APPLICABLE LAW. EXCEPT WHEN
OTHERWISE STATED IN WRITING THE COPYRIGHT HOLDERS AND/OR OTHER PARTIES
PROVIDE THE PROGRAM "AS IS" WITHOUT WARRANTY OF ANY KIND, EITHER EXPRESSED
OR IMPLIED, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF
MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE. THE ENTIRE RISK AS
TO THE QUALITY AND PERFORMANCE OF THE PROGRAM IS WITH YOU. SHOULD THE
PROGRAM PROVE DEFECTIVE, YOU ASSUME THE COST OF ALL NECESSARY SERVICING,
REPAIR OR CORRECTION.
12. IN NO EVENT UNLESS REQUIRED BY APPLICABLE LAW OR AGREED TO IN WRITING
WILL ANY COPYRIGHT HOLDER, OR ANY OTHER PARTY WHO MAY MODIFY AND/OR
REDISTRIBUTE THE PROGRAM AS PERMITTED ABOVE, BE LIABLE TO YOU FOR DAMAGES,
INCLUDING ANY GENERAL, SPECIAL, INCIDENTAL OR CONSEQUENTIAL DAMAGES ARISING
OUT OF THE USE OR INABILITY TO USE THE PROGRAM (INCLUDING BUT NOT LIMITED
TO LOSS OF DATA OR DATA BEING RENDERED INACCURATE OR LOSSES SUSTAINED BY
YOU OR THIRD PARTIES OR A FAILURE OF THE PROGRAM TO OPERATE WITH ANY OTHER
PROGRAMS), EVEN IF SUCH HOLDER OR OTHER PARTY HAS BEEN ADVISED OF THE
POSSIBILITY OF SUCH DAMAGES.
END OF TERMS AND CONDITIONS
How to Apply These Terms to Your New Programs
If you develop a new program, and you want it to be of the greatest
possible use to the public, the best way to achieve this is to make it
free software which everyone can redistribute and change under these terms.
To do so, attach the following notices to the program. It is safest
to attach them to the start of each source file to most effectively
convey the exclusion of warranty; and each file should have at least
the "copyright" line and a pointer to where the full notice is found.
Copyright (C)
This program is free software; you can redistribute it and/or modify
it under the terms of the GNU General Public License as published by
the Free Software Foundation; either version 2 of the License, or
(at your option) any later version.
This program is distributed in the hope that it will be useful,
but WITHOUT ANY WARRANTY; without even the implied warranty of
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
GNU General Public License for more details.
You should have received a copy of the GNU General Public License
along with this program; if not, write to the Free Software
Foundation, Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA
Also add information on how to contact you by electronic and paper mail.
If the program is interactive, make it output a short notice like this
when it starts in an interactive mode:
Gnomovision version 69, Copyright (C) year name of author
Gnomovision comes with ABSOLUTELY NO WARRANTY; for details type `show w'.
This is free software, and you are welcome to redistribute it
under certain conditions; type `show c' for details.
The hypothetical commands `show w' and `show c' should show the appropriate
parts of the General Public License. Of course, the commands you use may
be called something other than `show w' and `show c'; they could even be
mouse-clicks or menu items--whatever suits your program.
You should also get your employer (if you work as a programmer) or your
school, if any, to sign a "copyright disclaimer" for the program, if
necessary. Here is a sample; alter the names:
Yoyodyne, Inc., hereby disclaims all copyright interest in the program
`Gnomovision' (which makes passes at compilers) written by James Hacker.
, 1 April 1989
Ty Coon, President of Vice
This General Public License does not permit incorporating your program into
proprietary programs. If your program is a subroutine library, you may
consider it more useful to permit linking proprietary applications with the
library. If this is what you want to do, use the GNU Library General
Public License instead of this License.
phyml-20120412/config.sub 0000755 0001750 0001750 00000102425 11274160642 012013 0000000 0000000 #! /bin/sh
# Configuration validation subroutine script.
# Copyright (C) 1992, 1993, 1994, 1995, 1996, 1997, 1998, 1999,
# 2000, 2001, 2002, 2003, 2004, 2005, 2006, 2007, 2008, 2009
# Free Software Foundation, Inc.
timestamp='2009-06-11'
# This file is (in principle) common to ALL GNU software.
# The presence of a machine in this file suggests that SOME GNU software
# can handle that machine. It does not imply ALL GNU software can.
#
# This file is free software; you can redistribute it and/or modify
# it under the terms of the GNU General Public License as published by
# the Free Software Foundation; either version 2 of the License, or
# (at your option) any later version.
#
# This program is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
# GNU General Public License for more details.
#
# You should have received a copy of the GNU General Public License
# along with this program; if not, write to the Free Software
# Foundation, Inc., 51 Franklin Street - Fifth Floor, Boston, MA
# 02110-1301, USA.
#
# As a special exception to the GNU General Public License, if you
# distribute this file as part of a program that contains a
# configuration script generated by Autoconf, you may include it under
# the same distribution terms that you use for the rest of that program.
# Please send patches to . Submit a context
# diff and a properly formatted ChangeLog entry.
#
# Configuration subroutine to validate and canonicalize a configuration type.
# Supply the specified configuration type as an argument.
# If it is invalid, we print an error message on stderr and exit with code 1.
# Otherwise, we print the canonical config type on stdout and succeed.
# This file is supposed to be the same for all GNU packages
# and recognize all the CPU types, system types and aliases
# that are meaningful with *any* GNU software.
# Each package is responsible for reporting which valid configurations
# it does not support. The user should be able to distinguish
# a failure to support a valid configuration from a meaningless
# configuration.
# The goal of this file is to map all the various variations of a given
# machine specification into a single specification in the form:
# CPU_TYPE-MANUFACTURER-OPERATING_SYSTEM
# or in some cases, the newer four-part form:
# CPU_TYPE-MANUFACTURER-KERNEL-OPERATING_SYSTEM
# It is wrong to echo any other type of specification.
me=`echo "$0" | sed -e 's,.*/,,'`
usage="\
Usage: $0 [OPTION] CPU-MFR-OPSYS
$0 [OPTION] ALIAS
Canonicalize a configuration name.
Operation modes:
-h, --help print this help, then exit
-t, --time-stamp print date of last modification, then exit
-v, --version print version number, then exit
Report bugs and patches to ."
version="\
GNU config.sub ($timestamp)
Copyright (C) 1992, 1993, 1994, 1995, 1996, 1997, 1998, 1999, 2000, 2001,
2002, 2003, 2004, 2005, 2006, 2007, 2008 Free Software Foundation, Inc.
This is free software; see the source for copying conditions. There is NO
warranty; not even for MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE."
help="
Try \`$me --help' for more information."
# Parse command line
while test $# -gt 0 ; do
case $1 in
--time-stamp | --time* | -t )
echo "$timestamp" ; exit ;;
--version | -v )
echo "$version" ; exit ;;
--help | --h* | -h )
echo "$usage"; exit ;;
-- ) # Stop option processing
shift; break ;;
- ) # Use stdin as input.
break ;;
-* )
echo "$me: invalid option $1$help"
exit 1 ;;
*local*)
# First pass through any local machine types.
echo $1
exit ;;
* )
break ;;
esac
done
case $# in
0) echo "$me: missing argument$help" >&2
exit 1;;
1) ;;
*) echo "$me: too many arguments$help" >&2
exit 1;;
esac
# Separate what the user gave into CPU-COMPANY and OS or KERNEL-OS (if any).
# Here we must recognize all the valid KERNEL-OS combinations.
maybe_os=`echo $1 | sed 's/^\(.*\)-\([^-]*-[^-]*\)$/\2/'`
case $maybe_os in
nto-qnx* | linux-gnu* | linux-dietlibc | linux-newlib* | linux-uclibc* | \
uclinux-uclibc* | uclinux-gnu* | kfreebsd*-gnu* | knetbsd*-gnu* | netbsd*-gnu* | \
kopensolaris*-gnu* | \
storm-chaos* | os2-emx* | rtmk-nova*)
os=-$maybe_os
basic_machine=`echo $1 | sed 's/^\(.*\)-\([^-]*-[^-]*\)$/\1/'`
;;
*)
basic_machine=`echo $1 | sed 's/-[^-]*$//'`
if [ $basic_machine != $1 ]
then os=`echo $1 | sed 's/.*-/-/'`
else os=; fi
;;
esac
### Let's recognize common machines as not being operating systems so
### that things like config.sub decstation-3100 work. We also
### recognize some manufacturers as not being operating systems, so we
### can provide default operating systems below.
case $os in
-sun*os*)
# Prevent following clause from handling this invalid input.
;;
-dec* | -mips* | -sequent* | -encore* | -pc532* | -sgi* | -sony* | \
-att* | -7300* | -3300* | -delta* | -motorola* | -sun[234]* | \
-unicom* | -ibm* | -next | -hp | -isi* | -apollo | -altos* | \
-convergent* | -ncr* | -news | -32* | -3600* | -3100* | -hitachi* |\
-c[123]* | -convex* | -sun | -crds | -omron* | -dg | -ultra | -tti* | \
-harris | -dolphin | -highlevel | -gould | -cbm | -ns | -masscomp | \
-apple | -axis | -knuth | -cray)
os=
basic_machine=$1
;;
-bluegene*)
os=-cnk
;;
-sim | -cisco | -oki | -wec | -winbond)
os=
basic_machine=$1
;;
-scout)
;;
-wrs)
os=-vxworks
basic_machine=$1
;;
-chorusos*)
os=-chorusos
basic_machine=$1
;;
-chorusrdb)
os=-chorusrdb
basic_machine=$1
;;
-hiux*)
os=-hiuxwe2
;;
-sco6)
os=-sco5v6
basic_machine=`echo $1 | sed -e 's/86-.*/86-pc/'`
;;
-sco5)
os=-sco3.2v5
basic_machine=`echo $1 | sed -e 's/86-.*/86-pc/'`
;;
-sco4)
os=-sco3.2v4
basic_machine=`echo $1 | sed -e 's/86-.*/86-pc/'`
;;
-sco3.2.[4-9]*)
os=`echo $os | sed -e 's/sco3.2./sco3.2v/'`
basic_machine=`echo $1 | sed -e 's/86-.*/86-pc/'`
;;
-sco3.2v[4-9]*)
# Don't forget version if it is 3.2v4 or newer.
basic_machine=`echo $1 | sed -e 's/86-.*/86-pc/'`
;;
-sco5v6*)
# Don't forget version if it is 3.2v4 or newer.
basic_machine=`echo $1 | sed -e 's/86-.*/86-pc/'`
;;
-sco*)
os=-sco3.2v2
basic_machine=`echo $1 | sed -e 's/86-.*/86-pc/'`
;;
-udk*)
basic_machine=`echo $1 | sed -e 's/86-.*/86-pc/'`
;;
-isc)
os=-isc2.2
basic_machine=`echo $1 | sed -e 's/86-.*/86-pc/'`
;;
-clix*)
basic_machine=clipper-intergraph
;;
-isc*)
basic_machine=`echo $1 | sed -e 's/86-.*/86-pc/'`
;;
-lynx*)
os=-lynxos
;;
-ptx*)
basic_machine=`echo $1 | sed -e 's/86-.*/86-sequent/'`
;;
-windowsnt*)
os=`echo $os | sed -e 's/windowsnt/winnt/'`
;;
-psos*)
os=-psos
;;
-mint | -mint[0-9]*)
basic_machine=m68k-atari
os=-mint
;;
esac
# Decode aliases for certain CPU-COMPANY combinations.
case $basic_machine in
# Recognize the basic CPU types without company name.
# Some are omitted here because they have special meanings below.
1750a | 580 \
| a29k \
| alpha | alphaev[4-8] | alphaev56 | alphaev6[78] | alphapca5[67] \
| alpha64 | alpha64ev[4-8] | alpha64ev56 | alpha64ev6[78] | alpha64pca5[67] \
| am33_2.0 \
| arc | arm | arm[bl]e | arme[lb] | armv[2345] | armv[345][lb] | avr | avr32 \
| bfin \
| c4x | clipper \
| d10v | d30v | dlx | dsp16xx \
| fido | fr30 | frv \
| h8300 | h8500 | hppa | hppa1.[01] | hppa2.0 | hppa2.0[nw] | hppa64 \
| i370 | i860 | i960 | ia64 \
| ip2k | iq2000 \
| lm32 \
| m32c | m32r | m32rle | m68000 | m68k | m88k \
| maxq | mb | microblaze | mcore | mep | metag \
| mips | mipsbe | mipseb | mipsel | mipsle \
| mips16 \
| mips64 | mips64el \
| mips64octeon | mips64octeonel \
| mips64orion | mips64orionel \
| mips64r5900 | mips64r5900el \
| mips64vr | mips64vrel \
| mips64vr4100 | mips64vr4100el \
| mips64vr4300 | mips64vr4300el \
| mips64vr5000 | mips64vr5000el \
| mips64vr5900 | mips64vr5900el \
| mipsisa32 | mipsisa32el \
| mipsisa32r2 | mipsisa32r2el \
| mipsisa64 | mipsisa64el \
| mipsisa64r2 | mipsisa64r2el \
| mipsisa64sb1 | mipsisa64sb1el \
| mipsisa64sr71k | mipsisa64sr71kel \
| mipstx39 | mipstx39el \
| mn10200 | mn10300 \
| moxie \
| mt \
| msp430 \
| nios | nios2 \
| ns16k | ns32k \
| or32 \
| pdp10 | pdp11 | pj | pjl \
| powerpc | powerpc64 | powerpc64le | powerpcle | ppcbe \
| pyramid \
| score \
| sh | sh[1234] | sh[24]a | sh[24]aeb | sh[23]e | sh[34]eb | sheb | shbe | shle | sh[1234]le | sh3ele \
| sh64 | sh64le \
| sparc | sparc64 | sparc64b | sparc64v | sparc86x | sparclet | sparclite \
| sparcv8 | sparcv9 | sparcv9b | sparcv9v \
| spu | strongarm \
| tahoe | thumb | tic4x | tic80 | tron \
| v850 | v850e \
| we32k \
| x86 | xc16x | xscale | xscalee[bl] | xstormy16 | xtensa \
| z8k | z80)
basic_machine=$basic_machine-unknown
;;
m6811 | m68hc11 | m6812 | m68hc12)
# Motorola 68HC11/12.
basic_machine=$basic_machine-unknown
os=-none
;;
m88110 | m680[12346]0 | m683?2 | m68360 | m5200 | v70 | w65 | z8k)
;;
ms1)
basic_machine=mt-unknown
;;
# We use `pc' rather than `unknown'
# because (1) that's what they normally are, and
# (2) the word "unknown" tends to confuse beginning users.
i*86 | x86_64)
basic_machine=$basic_machine-pc
;;
# Object if more than one company name word.
*-*-*)
echo Invalid configuration \`$1\': machine \`$basic_machine\' not recognized 1>&2
exit 1
;;
# Recognize the basic CPU types with company name.
580-* \
| a29k-* \
| alpha-* | alphaev[4-8]-* | alphaev56-* | alphaev6[78]-* \
| alpha64-* | alpha64ev[4-8]-* | alpha64ev56-* | alpha64ev6[78]-* \
| alphapca5[67]-* | alpha64pca5[67]-* | arc-* \
| arm-* | armbe-* | armle-* | armeb-* | armv*-* \
| avr-* | avr32-* \
| bfin-* | bs2000-* \
| c[123]* | c30-* | [cjt]90-* | c4x-* | c54x-* | c55x-* | c6x-* \
| clipper-* | craynv-* | cydra-* \
| d10v-* | d30v-* | dlx-* \
| elxsi-* \
| f30[01]-* | f700-* | fido-* | fr30-* | frv-* | fx80-* \
| h8300-* | h8500-* \
| hppa-* | hppa1.[01]-* | hppa2.0-* | hppa2.0[nw]-* | hppa64-* \
| i*86-* | i860-* | i960-* | ia64-* \
| ip2k-* | iq2000-* \
| lm32-* \
| m32c-* | m32r-* | m32rle-* \
| m68000-* | m680[012346]0-* | m68360-* | m683?2-* | m68k-* \
| m88110-* | m88k-* | maxq-* | mcore-* | metag-* \
| mips-* | mipsbe-* | mipseb-* | mipsel-* | mipsle-* \
| mips16-* \
| mips64-* | mips64el-* \
| mips64octeon-* | mips64octeonel-* \
| mips64orion-* | mips64orionel-* \
| mips64r5900-* | mips64r5900el-* \
| mips64vr-* | mips64vrel-* \
| mips64vr4100-* | mips64vr4100el-* \
| mips64vr4300-* | mips64vr4300el-* \
| mips64vr5000-* | mips64vr5000el-* \
| mips64vr5900-* | mips64vr5900el-* \
| mipsisa32-* | mipsisa32el-* \
| mipsisa32r2-* | mipsisa32r2el-* \
| mipsisa64-* | mipsisa64el-* \
| mipsisa64r2-* | mipsisa64r2el-* \
| mipsisa64sb1-* | mipsisa64sb1el-* \
| mipsisa64sr71k-* | mipsisa64sr71kel-* \
| mipstx39-* | mipstx39el-* \
| mmix-* \
| mt-* \
| msp430-* \
| nios-* | nios2-* \
| none-* | np1-* | ns16k-* | ns32k-* \
| orion-* \
| pdp10-* | pdp11-* | pj-* | pjl-* | pn-* | power-* \
| powerpc-* | powerpc64-* | powerpc64le-* | powerpcle-* | ppcbe-* \
| pyramid-* \
| romp-* | rs6000-* \
| sh-* | sh[1234]-* | sh[24]a-* | sh[24]aeb-* | sh[23]e-* | sh[34]eb-* | sheb-* | shbe-* \
| shle-* | sh[1234]le-* | sh3ele-* | sh64-* | sh64le-* \
| sparc-* | sparc64-* | sparc64b-* | sparc64v-* | sparc86x-* | sparclet-* \
| sparclite-* \
| sparcv8-* | sparcv9-* | sparcv9b-* | sparcv9v-* | strongarm-* | sv1-* | sx?-* \
| tahoe-* | thumb-* \
| tic30-* | tic4x-* | tic54x-* | tic55x-* | tic6x-* | tic80-* | tile-* \
| tron-* \
| v850-* | v850e-* | vax-* \
| we32k-* \
| x86-* | x86_64-* | xc16x-* | xps100-* | xscale-* | xscalee[bl]-* \
| xstormy16-* | xtensa*-* \
| ymp-* \
| z8k-* | z80-*)
;;
# Recognize the basic CPU types without company name, with glob match.
xtensa*)
basic_machine=$basic_machine-unknown
;;
# Recognize the various machine names and aliases which stand
# for a CPU type and a company and sometimes even an OS.
386bsd)
basic_machine=i386-unknown
os=-bsd
;;
3b1 | 7300 | 7300-att | att-7300 | pc7300 | safari | unixpc)
basic_machine=m68000-att
;;
3b*)
basic_machine=we32k-att
;;
a29khif)
basic_machine=a29k-amd
os=-udi
;;
abacus)
basic_machine=abacus-unknown
;;
adobe68k)
basic_machine=m68010-adobe
os=-scout
;;
alliant | fx80)
basic_machine=fx80-alliant
;;
altos | altos3068)
basic_machine=m68k-altos
;;
am29k)
basic_machine=a29k-none
os=-bsd
;;
amd64)
basic_machine=x86_64-pc
;;
amd64-*)
basic_machine=x86_64-`echo $basic_machine | sed 's/^[^-]*-//'`
;;
amdahl)
basic_machine=580-amdahl
os=-sysv
;;
amiga | amiga-*)
basic_machine=m68k-unknown
;;
amigaos | amigados)
basic_machine=m68k-unknown
os=-amigaos
;;
amigaunix | amix)
basic_machine=m68k-unknown
os=-sysv4
;;
apollo68)
basic_machine=m68k-apollo
os=-sysv
;;
apollo68bsd)
basic_machine=m68k-apollo
os=-bsd
;;
aros)
basic_machine=i386-pc
os=-aros
;;
aux)
basic_machine=m68k-apple
os=-aux
;;
balance)
basic_machine=ns32k-sequent
os=-dynix
;;
blackfin)
basic_machine=bfin-unknown
os=-linux
;;
blackfin-*)
basic_machine=bfin-`echo $basic_machine | sed 's/^[^-]*-//'`
os=-linux
;;
bluegene*)
basic_machine=powerpc-ibm
os=-cnk
;;
c90)
basic_machine=c90-cray
os=-unicos
;;
cegcc)
basic_machine=arm-unknown
os=-cegcc
;;
convex-c1)
basic_machine=c1-convex
os=-bsd
;;
convex-c2)
basic_machine=c2-convex
os=-bsd
;;
convex-c32)
basic_machine=c32-convex
os=-bsd
;;
convex-c34)
basic_machine=c34-convex
os=-bsd
;;
convex-c38)
basic_machine=c38-convex
os=-bsd
;;
cray | j90)
basic_machine=j90-cray
os=-unicos
;;
craynv)
basic_machine=craynv-cray
os=-unicosmp
;;
cr16)
basic_machine=cr16-unknown
os=-elf
;;
crds | unos)
basic_machine=m68k-crds
;;
crisv32 | crisv32-* | etraxfs*)
basic_machine=crisv32-axis
;;
cris | cris-* | etrax*)
basic_machine=cris-axis
;;
crx)
basic_machine=crx-unknown
os=-elf
;;
da30 | da30-*)
basic_machine=m68k-da30
;;
decstation | decstation-3100 | pmax | pmax-* | pmin | dec3100 | decstatn)
basic_machine=mips-dec
;;
decsystem10* | dec10*)
basic_machine=pdp10-dec
os=-tops10
;;
decsystem20* | dec20*)
basic_machine=pdp10-dec
os=-tops20
;;
delta | 3300 | motorola-3300 | motorola-delta \
| 3300-motorola | delta-motorola)
basic_machine=m68k-motorola
;;
delta88)
basic_machine=m88k-motorola
os=-sysv3
;;
dicos)
basic_machine=i686-pc
os=-dicos
;;
djgpp)
basic_machine=i586-pc
os=-msdosdjgpp
;;
dpx20 | dpx20-*)
basic_machine=rs6000-bull
os=-bosx
;;
dpx2* | dpx2*-bull)
basic_machine=m68k-bull
os=-sysv3
;;
ebmon29k)
basic_machine=a29k-amd
os=-ebmon
;;
elxsi)
basic_machine=elxsi-elxsi
os=-bsd
;;
encore | umax | mmax)
basic_machine=ns32k-encore
;;
es1800 | OSE68k | ose68k | ose | OSE)
basic_machine=m68k-ericsson
os=-ose
;;
fx2800)
basic_machine=i860-alliant
;;
genix)
basic_machine=ns32k-ns
;;
gmicro)
basic_machine=tron-gmicro
os=-sysv
;;
go32)
basic_machine=i386-pc
os=-go32
;;
h3050r* | hiux*)
basic_machine=hppa1.1-hitachi
os=-hiuxwe2
;;
h8300hms)
basic_machine=h8300-hitachi
os=-hms
;;
h8300xray)
basic_machine=h8300-hitachi
os=-xray
;;
h8500hms)
basic_machine=h8500-hitachi
os=-hms
;;
harris)
basic_machine=m88k-harris
os=-sysv3
;;
hp300-*)
basic_machine=m68k-hp
;;
hp300bsd)
basic_machine=m68k-hp
os=-bsd
;;
hp300hpux)
basic_machine=m68k-hp
os=-hpux
;;
hp3k9[0-9][0-9] | hp9[0-9][0-9])
basic_machine=hppa1.0-hp
;;
hp9k2[0-9][0-9] | hp9k31[0-9])
basic_machine=m68000-hp
;;
hp9k3[2-9][0-9])
basic_machine=m68k-hp
;;
hp9k6[0-9][0-9] | hp6[0-9][0-9])
basic_machine=hppa1.0-hp
;;
hp9k7[0-79][0-9] | hp7[0-79][0-9])
basic_machine=hppa1.1-hp
;;
hp9k78[0-9] | hp78[0-9])
# FIXME: really hppa2.0-hp
basic_machine=hppa1.1-hp
;;
hp9k8[67]1 | hp8[67]1 | hp9k80[24] | hp80[24] | hp9k8[78]9 | hp8[78]9 | hp9k893 | hp893)
# FIXME: really hppa2.0-hp
basic_machine=hppa1.1-hp
;;
hp9k8[0-9][13679] | hp8[0-9][13679])
basic_machine=hppa1.1-hp
;;
hp9k8[0-9][0-9] | hp8[0-9][0-9])
basic_machine=hppa1.0-hp
;;
hppa-next)
os=-nextstep3
;;
hppaosf)
basic_machine=hppa1.1-hp
os=-osf
;;
hppro)
basic_machine=hppa1.1-hp
os=-proelf
;;
i370-ibm* | ibm*)
basic_machine=i370-ibm
;;
# I'm not sure what "Sysv32" means. Should this be sysv3.2?
i*86v32)
basic_machine=`echo $1 | sed -e 's/86.*/86-pc/'`
os=-sysv32
;;
i*86v4*)
basic_machine=`echo $1 | sed -e 's/86.*/86-pc/'`
os=-sysv4
;;
i*86v)
basic_machine=`echo $1 | sed -e 's/86.*/86-pc/'`
os=-sysv
;;
i*86sol2)
basic_machine=`echo $1 | sed -e 's/86.*/86-pc/'`
os=-solaris2
;;
i386mach)
basic_machine=i386-mach
os=-mach
;;
i386-vsta | vsta)
basic_machine=i386-unknown
os=-vsta
;;
iris | iris4d)
basic_machine=mips-sgi
case $os in
-irix*)
;;
*)
os=-irix4
;;
esac
;;
isi68 | isi)
basic_machine=m68k-isi
os=-sysv
;;
m68knommu)
basic_machine=m68k-unknown
os=-linux
;;
m68knommu-*)
basic_machine=m68k-`echo $basic_machine | sed 's/^[^-]*-//'`
os=-linux
;;
m88k-omron*)
basic_machine=m88k-omron
;;
magnum | m3230)
basic_machine=mips-mips
os=-sysv
;;
merlin)
basic_machine=ns32k-utek
os=-sysv
;;
mingw32)
basic_machine=i386-pc
os=-mingw32
;;
mingw32ce)
basic_machine=arm-unknown
os=-mingw32ce
;;
miniframe)
basic_machine=m68000-convergent
;;
*mint | -mint[0-9]* | *MiNT | *MiNT[0-9]*)
basic_machine=m68k-atari
os=-mint
;;
mips3*-*)
basic_machine=`echo $basic_machine | sed -e 's/mips3/mips64/'`
;;
mips3*)
basic_machine=`echo $basic_machine | sed -e 's/mips3/mips64/'`-unknown
;;
monitor)
basic_machine=m68k-rom68k
os=-coff
;;
morphos)
basic_machine=powerpc-unknown
os=-morphos
;;
msdos)
basic_machine=i386-pc
os=-msdos
;;
ms1-*)
basic_machine=`echo $basic_machine | sed -e 's/ms1-/mt-/'`
;;
mvs)
basic_machine=i370-ibm
os=-mvs
;;
ncr3000)
basic_machine=i486-ncr
os=-sysv4
;;
netbsd386)
basic_machine=i386-unknown
os=-netbsd
;;
netwinder)
basic_machine=armv4l-rebel
os=-linux
;;
news | news700 | news800 | news900)
basic_machine=m68k-sony
os=-newsos
;;
news1000)
basic_machine=m68030-sony
os=-newsos
;;
news-3600 | risc-news)
basic_machine=mips-sony
os=-newsos
;;
necv70)
basic_machine=v70-nec
os=-sysv
;;
next | m*-next )
basic_machine=m68k-next
case $os in
-nextstep* )
;;
-ns2*)
os=-nextstep2
;;
*)
os=-nextstep3
;;
esac
;;
nh3000)
basic_machine=m68k-harris
os=-cxux
;;
nh[45]000)
basic_machine=m88k-harris
os=-cxux
;;
nindy960)
basic_machine=i960-intel
os=-nindy
;;
mon960)
basic_machine=i960-intel
os=-mon960
;;
nonstopux)
basic_machine=mips-compaq
os=-nonstopux
;;
np1)
basic_machine=np1-gould
;;
nsr-tandem)
basic_machine=nsr-tandem
;;
op50n-* | op60c-*)
basic_machine=hppa1.1-oki
os=-proelf
;;
openrisc | openrisc-*)
basic_machine=or32-unknown
;;
os400)
basic_machine=powerpc-ibm
os=-os400
;;
OSE68000 | ose68000)
basic_machine=m68000-ericsson
os=-ose
;;
os68k)
basic_machine=m68k-none
os=-os68k
;;
pa-hitachi)
basic_machine=hppa1.1-hitachi
os=-hiuxwe2
;;
paragon)
basic_machine=i860-intel
os=-osf
;;
parisc)
basic_machine=hppa-unknown
os=-linux
;;
parisc-*)
basic_machine=hppa-`echo $basic_machine | sed 's/^[^-]*-//'`
os=-linux
;;
pbd)
basic_machine=sparc-tti
;;
pbb)
basic_machine=m68k-tti
;;
pc532 | pc532-*)
basic_machine=ns32k-pc532
;;
pc98)
basic_machine=i386-pc
;;
pc98-*)
basic_machine=i386-`echo $basic_machine | sed 's/^[^-]*-//'`
;;
pentium | p5 | k5 | k6 | nexgen | viac3)
basic_machine=i586-pc
;;
pentiumpro | p6 | 6x86 | athlon | athlon_*)
basic_machine=i686-pc
;;
pentiumii | pentium2 | pentiumiii | pentium3)
basic_machine=i686-pc
;;
pentium4)
basic_machine=i786-pc
;;
pentium-* | p5-* | k5-* | k6-* | nexgen-* | viac3-*)
basic_machine=i586-`echo $basic_machine | sed 's/^[^-]*-//'`
;;
pentiumpro-* | p6-* | 6x86-* | athlon-*)
basic_machine=i686-`echo $basic_machine | sed 's/^[^-]*-//'`
;;
pentiumii-* | pentium2-* | pentiumiii-* | pentium3-*)
basic_machine=i686-`echo $basic_machine | sed 's/^[^-]*-//'`
;;
pentium4-*)
basic_machine=i786-`echo $basic_machine | sed 's/^[^-]*-//'`
;;
pn)
basic_machine=pn-gould
;;
power) basic_machine=power-ibm
;;
ppc) basic_machine=powerpc-unknown
;;
ppc-*) basic_machine=powerpc-`echo $basic_machine | sed 's/^[^-]*-//'`
;;
ppcle | powerpclittle | ppc-le | powerpc-little)
basic_machine=powerpcle-unknown
;;
ppcle-* | powerpclittle-*)
basic_machine=powerpcle-`echo $basic_machine | sed 's/^[^-]*-//'`
;;
ppc64) basic_machine=powerpc64-unknown
;;
ppc64-*) basic_machine=powerpc64-`echo $basic_machine | sed 's/^[^-]*-//'`
;;
ppc64le | powerpc64little | ppc64-le | powerpc64-little)
basic_machine=powerpc64le-unknown
;;
ppc64le-* | powerpc64little-*)
basic_machine=powerpc64le-`echo $basic_machine | sed 's/^[^-]*-//'`
;;
ps2)
basic_machine=i386-ibm
;;
pw32)
basic_machine=i586-unknown
os=-pw32
;;
rdos)
basic_machine=i386-pc
os=-rdos
;;
rom68k)
basic_machine=m68k-rom68k
os=-coff
;;
rm[46]00)
basic_machine=mips-siemens
;;
rtpc | rtpc-*)
basic_machine=romp-ibm
;;
s390 | s390-*)
basic_machine=s390-ibm
;;
s390x | s390x-*)
basic_machine=s390x-ibm
;;
sa29200)
basic_machine=a29k-amd
os=-udi
;;
sb1)
basic_machine=mipsisa64sb1-unknown
;;
sb1el)
basic_machine=mipsisa64sb1el-unknown
;;
sde)
basic_machine=mipsisa32-sde
os=-elf
;;
sei)
basic_machine=mips-sei
os=-seiux
;;
sequent)
basic_machine=i386-sequent
;;
sh)
basic_machine=sh-hitachi
os=-hms
;;
sh5el)
basic_machine=sh5le-unknown
;;
sh64)
basic_machine=sh64-unknown
;;
sparclite-wrs | simso-wrs)
basic_machine=sparclite-wrs
os=-vxworks
;;
sps7)
basic_machine=m68k-bull
os=-sysv2
;;
spur)
basic_machine=spur-unknown
;;
st2000)
basic_machine=m68k-tandem
;;
stratus)
basic_machine=i860-stratus
os=-sysv4
;;
sun2)
basic_machine=m68000-sun
;;
sun2os3)
basic_machine=m68000-sun
os=-sunos3
;;
sun2os4)
basic_machine=m68000-sun
os=-sunos4
;;
sun3os3)
basic_machine=m68k-sun
os=-sunos3
;;
sun3os4)
basic_machine=m68k-sun
os=-sunos4
;;
sun4os3)
basic_machine=sparc-sun
os=-sunos3
;;
sun4os4)
basic_machine=sparc-sun
os=-sunos4
;;
sun4sol2)
basic_machine=sparc-sun
os=-solaris2
;;
sun3 | sun3-*)
basic_machine=m68k-sun
;;
sun4)
basic_machine=sparc-sun
;;
sun386 | sun386i | roadrunner)
basic_machine=i386-sun
;;
sv1)
basic_machine=sv1-cray
os=-unicos
;;
symmetry)
basic_machine=i386-sequent
os=-dynix
;;
t3e)
basic_machine=alphaev5-cray
os=-unicos
;;
t90)
basic_machine=t90-cray
os=-unicos
;;
tic54x | c54x*)
basic_machine=tic54x-unknown
os=-coff
;;
tic55x | c55x*)
basic_machine=tic55x-unknown
os=-coff
;;
tic6x | c6x*)
basic_machine=tic6x-unknown
os=-coff
;;
tile*)
basic_machine=tile-unknown
os=-linux-gnu
;;
tx39)
basic_machine=mipstx39-unknown
;;
tx39el)
basic_machine=mipstx39el-unknown
;;
toad1)
basic_machine=pdp10-xkl
os=-tops20
;;
tower | tower-32)
basic_machine=m68k-ncr
;;
tpf)
basic_machine=s390x-ibm
os=-tpf
;;
udi29k)
basic_machine=a29k-amd
os=-udi
;;
ultra3)
basic_machine=a29k-nyu
os=-sym1
;;
v810 | necv810)
basic_machine=v810-nec
os=-none
;;
vaxv)
basic_machine=vax-dec
os=-sysv
;;
vms)
basic_machine=vax-dec
os=-vms
;;
vpp*|vx|vx-*)
basic_machine=f301-fujitsu
;;
vxworks960)
basic_machine=i960-wrs
os=-vxworks
;;
vxworks68)
basic_machine=m68k-wrs
os=-vxworks
;;
vxworks29k)
basic_machine=a29k-wrs
os=-vxworks
;;
w65*)
basic_machine=w65-wdc
os=-none
;;
w89k-*)
basic_machine=hppa1.1-winbond
os=-proelf
;;
xbox)
basic_machine=i686-pc
os=-mingw32
;;
xps | xps100)
basic_machine=xps100-honeywell
;;
ymp)
basic_machine=ymp-cray
os=-unicos
;;
z8k-*-coff)
basic_machine=z8k-unknown
os=-sim
;;
z80-*-coff)
basic_machine=z80-unknown
os=-sim
;;
none)
basic_machine=none-none
os=-none
;;
# Here we handle the default manufacturer of certain CPU types. It is in
# some cases the only manufacturer, in others, it is the most popular.
w89k)
basic_machine=hppa1.1-winbond
;;
op50n)
basic_machine=hppa1.1-oki
;;
op60c)
basic_machine=hppa1.1-oki
;;
romp)
basic_machine=romp-ibm
;;
mmix)
basic_machine=mmix-knuth
;;
rs6000)
basic_machine=rs6000-ibm
;;
vax)
basic_machine=vax-dec
;;
pdp10)
# there are many clones, so DEC is not a safe bet
basic_machine=pdp10-unknown
;;
pdp11)
basic_machine=pdp11-dec
;;
we32k)
basic_machine=we32k-att
;;
sh[1234] | sh[24]a | sh[24]aeb | sh[34]eb | sh[1234]le | sh[23]ele)
basic_machine=sh-unknown
;;
sparc | sparcv8 | sparcv9 | sparcv9b | sparcv9v)
basic_machine=sparc-sun
;;
cydra)
basic_machine=cydra-cydrome
;;
orion)
basic_machine=orion-highlevel
;;
orion105)
basic_machine=clipper-highlevel
;;
mac | mpw | mac-mpw)
basic_machine=m68k-apple
;;
pmac | pmac-mpw)
basic_machine=powerpc-apple
;;
*-unknown)
# Make sure to match an already-canonicalized machine name.
;;
*)
echo Invalid configuration \`$1\': machine \`$basic_machine\' not recognized 1>&2
exit 1
;;
esac
# Here we canonicalize certain aliases for manufacturers.
case $basic_machine in
*-digital*)
basic_machine=`echo $basic_machine | sed 's/digital.*/dec/'`
;;
*-commodore*)
basic_machine=`echo $basic_machine | sed 's/commodore.*/cbm/'`
;;
*)
;;
esac
# Decode manufacturer-specific aliases for certain operating systems.
if [ x"$os" != x"" ]
then
case $os in
# First match some system type aliases
# that might get confused with valid system types.
# -solaris* is a basic system type, with this one exception.
-solaris1 | -solaris1.*)
os=`echo $os | sed -e 's|solaris1|sunos4|'`
;;
-solaris)
os=-solaris2
;;
-svr4*)
os=-sysv4
;;
-unixware*)
os=-sysv4.2uw
;;
-gnu/linux*)
os=`echo $os | sed -e 's|gnu/linux|linux-gnu|'`
;;
# First accept the basic system types.
# The portable systems comes first.
# Each alternative MUST END IN A *, to match a version number.
# -sysv* is not here because it comes later, after sysvr4.
-gnu* | -bsd* | -mach* | -minix* | -genix* | -ultrix* | -irix* \
| -*vms* | -sco* | -esix* | -isc* | -aix* | -cnk* | -sunos | -sunos[34]*\
| -hpux* | -unos* | -osf* | -luna* | -dgux* | -solaris* | -sym* \
| -kopensolaris* \
| -amigaos* | -amigados* | -msdos* | -newsos* | -unicos* | -aof* \
| -aos* | -aros* \
| -nindy* | -vxsim* | -vxworks* | -ebmon* | -hms* | -mvs* \
| -clix* | -riscos* | -uniplus* | -iris* | -rtu* | -xenix* \
| -hiux* | -386bsd* | -knetbsd* | -mirbsd* | -netbsd* \
| -openbsd* | -solidbsd* \
| -ekkobsd* | -kfreebsd* | -freebsd* | -riscix* | -lynxos* \
| -bosx* | -nextstep* | -cxux* | -aout* | -elf* | -oabi* \
| -ptx* | -coff* | -ecoff* | -winnt* | -domain* | -vsta* \
| -udi* | -eabi* | -lites* | -ieee* | -go32* | -aux* \
| -chorusos* | -chorusrdb* | -cegcc* \
| -cygwin* | -pe* | -psos* | -moss* | -proelf* | -rtems* \
| -mingw32* | -linux-gnu* | -linux-newlib* | -linux-uclibc* \
| -uxpv* | -beos* | -mpeix* | -udk* \
| -interix* | -uwin* | -mks* | -rhapsody* | -darwin* | -opened* \
| -openstep* | -oskit* | -conix* | -pw32* | -nonstopux* \
| -storm-chaos* | -tops10* | -tenex* | -tops20* | -its* \
| -os2* | -vos* | -palmos* | -uclinux* | -nucleus* \
| -morphos* | -superux* | -rtmk* | -rtmk-nova* | -windiss* \
| -powermax* | -dnix* | -nx6 | -nx7 | -sei* | -dragonfly* \
| -skyos* | -haiku* | -rdos* | -toppers* | -drops*)
# Remember, each alternative MUST END IN *, to match a version number.
;;
-qnx*)
case $basic_machine in
x86-* | i*86-*)
;;
*)
os=-nto$os
;;
esac
;;
-nto-qnx*)
;;
-nto*)
os=`echo $os | sed -e 's|nto|nto-qnx|'`
;;
-sim | -es1800* | -hms* | -xray | -os68k* | -none* | -v88r* \
| -windows* | -osx | -abug | -netware* | -os9* | -beos* | -haiku* \
| -macos* | -mpw* | -magic* | -mmixware* | -mon960* | -lnews*)
;;
-mac*)
os=`echo $os | sed -e 's|mac|macos|'`
;;
-linux-dietlibc)
os=-linux-dietlibc
;;
-linux*)
os=`echo $os | sed -e 's|linux|linux-gnu|'`
;;
-sunos5*)
os=`echo $os | sed -e 's|sunos5|solaris2|'`
;;
-sunos6*)
os=`echo $os | sed -e 's|sunos6|solaris3|'`
;;
-opened*)
os=-openedition
;;
-os400*)
os=-os400
;;
-wince*)
os=-wince
;;
-osfrose*)
os=-osfrose
;;
-osf*)
os=-osf
;;
-utek*)
os=-bsd
;;
-dynix*)
os=-bsd
;;
-acis*)
os=-aos
;;
-atheos*)
os=-atheos
;;
-syllable*)
os=-syllable
;;
-386bsd)
os=-bsd
;;
-ctix* | -uts*)
os=-sysv
;;
-nova*)
os=-rtmk-nova
;;
-ns2 )
os=-nextstep2
;;
-nsk*)
os=-nsk
;;
# Preserve the version number of sinix5.
-sinix5.*)
os=`echo $os | sed -e 's|sinix|sysv|'`
;;
-sinix*)
os=-sysv4
;;
-tpf*)
os=-tpf
;;
-triton*)
os=-sysv3
;;
-oss*)
os=-sysv3
;;
-svr4)
os=-sysv4
;;
-svr3)
os=-sysv3
;;
-sysvr4)
os=-sysv4
;;
# This must come after -sysvr4.
-sysv*)
;;
-ose*)
os=-ose
;;
-es1800*)
os=-ose
;;
-xenix)
os=-xenix
;;
-*mint | -mint[0-9]* | -*MiNT | -MiNT[0-9]*)
os=-mint
;;
-aros*)
os=-aros
;;
-kaos*)
os=-kaos
;;
-zvmoe)
os=-zvmoe
;;
-dicos*)
os=-dicos
;;
-none)
;;
*)
# Get rid of the `-' at the beginning of $os.
os=`echo $os | sed 's/[^-]*-//'`
echo Invalid configuration \`$1\': system \`$os\' not recognized 1>&2
exit 1
;;
esac
else
# Here we handle the default operating systems that come with various machines.
# The value should be what the vendor currently ships out the door with their
# machine or put another way, the most popular os provided with the machine.
# Note that if you're going to try to match "-MANUFACTURER" here (say,
# "-sun"), then you have to tell the case statement up towards the top
# that MANUFACTURER isn't an operating system. Otherwise, code above
# will signal an error saying that MANUFACTURER isn't an operating
# system, and we'll never get to this point.
case $basic_machine in
score-*)
os=-elf
;;
spu-*)
os=-elf
;;
*-acorn)
os=-riscix1.2
;;
arm*-rebel)
os=-linux
;;
arm*-semi)
os=-aout
;;
c4x-* | tic4x-*)
os=-coff
;;
# This must come before the *-dec entry.
pdp10-*)
os=-tops20
;;
pdp11-*)
os=-none
;;
*-dec | vax-*)
os=-ultrix4.2
;;
m68*-apollo)
os=-domain
;;
i386-sun)
os=-sunos4.0.2
;;
m68000-sun)
os=-sunos3
# This also exists in the configure program, but was not the
# default.
# os=-sunos4
;;
m68*-cisco)
os=-aout
;;
mep-*)
os=-elf
;;
mips*-cisco)
os=-elf
;;
mips*-*)
os=-elf
;;
or32-*)
os=-coff
;;
*-tti) # must be before sparc entry or we get the wrong os.
os=-sysv3
;;
sparc-* | *-sun)
os=-sunos4.1.1
;;
*-be)
os=-beos
;;
*-haiku)
os=-haiku
;;
*-ibm)
os=-aix
;;
*-knuth)
os=-mmixware
;;
*-wec)
os=-proelf
;;
*-winbond)
os=-proelf
;;
*-oki)
os=-proelf
;;
*-hp)
os=-hpux
;;
*-hitachi)
os=-hiux
;;
i860-* | *-att | *-ncr | *-altos | *-motorola | *-convergent)
os=-sysv
;;
*-cbm)
os=-amigaos
;;
*-dg)
os=-dgux
;;
*-dolphin)
os=-sysv3
;;
m68k-ccur)
os=-rtu
;;
m88k-omron*)
os=-luna
;;
*-next )
os=-nextstep
;;
*-sequent)
os=-ptx
;;
*-crds)
os=-unos
;;
*-ns)
os=-genix
;;
i370-*)
os=-mvs
;;
*-next)
os=-nextstep3
;;
*-gould)
os=-sysv
;;
*-highlevel)
os=-bsd
;;
*-encore)
os=-bsd
;;
*-sgi)
os=-irix
;;
*-siemens)
os=-sysv4
;;
*-masscomp)
os=-rtu
;;
f30[01]-fujitsu | f700-fujitsu)
os=-uxpv
;;
*-rom68k)
os=-coff
;;
*-*bug)
os=-coff
;;
*-apple)
os=-macos
;;
*-atari*)
os=-mint
;;
*)
os=-none
;;
esac
fi
# Here we handle the case where we know the os, and the CPU type, but not the
# manufacturer. We pick the logical manufacturer.
vendor=unknown
case $basic_machine in
*-unknown)
case $os in
-riscix*)
vendor=acorn
;;
-sunos*)
vendor=sun
;;
-cnk*|-aix*)
vendor=ibm
;;
-beos*)
vendor=be
;;
-hpux*)
vendor=hp
;;
-mpeix*)
vendor=hp
;;
-hiux*)
vendor=hitachi
;;
-unos*)
vendor=crds
;;
-dgux*)
vendor=dg
;;
-luna*)
vendor=omron
;;
-genix*)
vendor=ns
;;
-mvs* | -opened*)
vendor=ibm
;;
-os400*)
vendor=ibm
;;
-ptx*)
vendor=sequent
;;
-tpf*)
vendor=ibm
;;
-vxsim* | -vxworks* | -windiss*)
vendor=wrs
;;
-aux*)
vendor=apple
;;
-hms*)
vendor=hitachi
;;
-mpw* | -macos*)
vendor=apple
;;
-*mint | -mint[0-9]* | -*MiNT | -MiNT[0-9]*)
vendor=atari
;;
-vos*)
vendor=stratus
;;
esac
basic_machine=`echo $basic_machine | sed "s/unknown/$vendor/"`
;;
esac
echo $basic_machine$os
exit
# Local variables:
# eval: (add-hook 'write-file-hooks 'time-stamp)
# time-stamp-start: "timestamp='"
# time-stamp-format: "%:y-%02m-%02d"
# time-stamp-end: "'"
# End:
phyml-20120412/configure 0000755 0001750 0001750 00000554156 11741362653 011760 0000000 0000000 #! /bin/sh
# Guess values for system-dependent variables and create Makefiles.
# Generated by GNU Autoconf 2.65 for PhyML 20120412.
#
# Report bugs to .
#
#
# Copyright (C) 1992, 1993, 1994, 1995, 1996, 1998, 1999, 2000, 2001,
# 2002, 2003, 2004, 2005, 2006, 2007, 2008, 2009 Free Software Foundation,
# Inc.
#
#
# This configure script is free software; the Free Software Foundation
# gives unlimited permission to copy, distribute and modify it.
## -------------------- ##
## M4sh Initialization. ##
## -------------------- ##
# Be more Bourne compatible
DUALCASE=1; export DUALCASE # for MKS sh
if test -n "${ZSH_VERSION+set}" && (emulate sh) >/dev/null 2>&1; then :
emulate sh
NULLCMD=:
# Pre-4.2 versions of Zsh do word splitting on ${1+"$@"}, which
# is contrary to our usage. Disable this feature.
alias -g '${1+"$@"}'='"$@"'
setopt NO_GLOB_SUBST
else
case `(set -o) 2>/dev/null` in #(
*posix*) :
set -o posix ;; #(
*) :
;;
esac
fi
as_nl='
'
export as_nl
# Printing a long string crashes Solaris 7 /usr/bin/printf.
as_echo='\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\'
as_echo=$as_echo$as_echo$as_echo$as_echo$as_echo
as_echo=$as_echo$as_echo$as_echo$as_echo$as_echo$as_echo
# Prefer a ksh shell builtin over an external printf program on Solaris,
# but without wasting forks for bash or zsh.
if test -z "$BASH_VERSION$ZSH_VERSION" \
&& (test "X`print -r -- $as_echo`" = "X$as_echo") 2>/dev/null; then
as_echo='print -r --'
as_echo_n='print -rn --'
elif (test "X`printf %s $as_echo`" = "X$as_echo") 2>/dev/null; then
as_echo='printf %s\n'
as_echo_n='printf %s'
else
if test "X`(/usr/ucb/echo -n -n $as_echo) 2>/dev/null`" = "X-n $as_echo"; then
as_echo_body='eval /usr/ucb/echo -n "$1$as_nl"'
as_echo_n='/usr/ucb/echo -n'
else
as_echo_body='eval expr "X$1" : "X\\(.*\\)"'
as_echo_n_body='eval
arg=$1;
case $arg in #(
*"$as_nl"*)
expr "X$arg" : "X\\(.*\\)$as_nl";
arg=`expr "X$arg" : ".*$as_nl\\(.*\\)"`;;
esac;
expr "X$arg" : "X\\(.*\\)" | tr -d "$as_nl"
'
export as_echo_n_body
as_echo_n='sh -c $as_echo_n_body as_echo'
fi
export as_echo_body
as_echo='sh -c $as_echo_body as_echo'
fi
# The user is always right.
if test "${PATH_SEPARATOR+set}" != set; then
PATH_SEPARATOR=:
(PATH='/bin;/bin'; FPATH=$PATH; sh -c :) >/dev/null 2>&1 && {
(PATH='/bin:/bin'; FPATH=$PATH; sh -c :) >/dev/null 2>&1 ||
PATH_SEPARATOR=';'
}
fi
# IFS
# We need space, tab and new line, in precisely that order. Quoting is
# there to prevent editors from complaining about space-tab.
# (If _AS_PATH_WALK were called with IFS unset, it would disable word
# splitting by setting IFS to empty value.)
IFS=" "" $as_nl"
# Find who we are. Look in the path if we contain no directory separator.
case $0 in #((
*[\\/]* ) as_myself=$0 ;;
*) as_save_IFS=$IFS; IFS=$PATH_SEPARATOR
for as_dir in $PATH
do
IFS=$as_save_IFS
test -z "$as_dir" && as_dir=.
test -r "$as_dir/$0" && as_myself=$as_dir/$0 && break
done
IFS=$as_save_IFS
;;
esac
# We did not find ourselves, most probably we were run as `sh COMMAND'
# in which case we are not to be found in the path.
if test "x$as_myself" = x; then
as_myself=$0
fi
if test ! -f "$as_myself"; then
$as_echo "$as_myself: error: cannot find myself; rerun with an absolute file name" >&2
exit 1
fi
# Unset variables that we do not need and which cause bugs (e.g. in
# pre-3.0 UWIN ksh). But do not cause bugs in bash 2.01; the "|| exit 1"
# suppresses any "Segmentation fault" message there. '((' could
# trigger a bug in pdksh 5.2.14.
for as_var in BASH_ENV ENV MAIL MAILPATH
do eval test x\${$as_var+set} = xset \
&& ( (unset $as_var) || exit 1) >/dev/null 2>&1 && unset $as_var || :
done
PS1='$ '
PS2='> '
PS4='+ '
# NLS nuisances.
LC_ALL=C
export LC_ALL
LANGUAGE=C
export LANGUAGE
# CDPATH.
(unset CDPATH) >/dev/null 2>&1 && unset CDPATH
if test "x$CONFIG_SHELL" = x; then
as_bourne_compatible="if test -n \"\${ZSH_VERSION+set}\" && (emulate sh) >/dev/null 2>&1; then :
emulate sh
NULLCMD=:
# Pre-4.2 versions of Zsh do word splitting on \${1+\"\$@\"}, which
# is contrary to our usage. Disable this feature.
alias -g '\${1+\"\$@\"}'='\"\$@\"'
setopt NO_GLOB_SUBST
else
case \`(set -o) 2>/dev/null\` in #(
*posix*) :
set -o posix ;; #(
*) :
;;
esac
fi
"
as_required="as_fn_return () { (exit \$1); }
as_fn_success () { as_fn_return 0; }
as_fn_failure () { as_fn_return 1; }
as_fn_ret_success () { return 0; }
as_fn_ret_failure () { return 1; }
exitcode=0
as_fn_success || { exitcode=1; echo as_fn_success failed.; }
as_fn_failure && { exitcode=1; echo as_fn_failure succeeded.; }
as_fn_ret_success || { exitcode=1; echo as_fn_ret_success failed.; }
as_fn_ret_failure && { exitcode=1; echo as_fn_ret_failure succeeded.; }
if ( set x; as_fn_ret_success y && test x = \"\$1\" ); then :
else
exitcode=1; echo positional parameters were not saved.
fi
test x\$exitcode = x0 || exit 1"
as_suggested=" as_lineno_1=";as_suggested=$as_suggested$LINENO;as_suggested=$as_suggested" as_lineno_1a=\$LINENO
as_lineno_2=";as_suggested=$as_suggested$LINENO;as_suggested=$as_suggested" as_lineno_2a=\$LINENO
eval 'test \"x\$as_lineno_1'\$as_run'\" != \"x\$as_lineno_2'\$as_run'\" &&
test \"x\`expr \$as_lineno_1'\$as_run' + 1\`\" = \"x\$as_lineno_2'\$as_run'\"' || exit 1
test \$(( 1 + 1 )) = 2 || exit 1"
if (eval "$as_required") 2>/dev/null; then :
as_have_required=yes
else
as_have_required=no
fi
if test x$as_have_required = xyes && (eval "$as_suggested") 2>/dev/null; then :
else
as_save_IFS=$IFS; IFS=$PATH_SEPARATOR
as_found=false
for as_dir in /bin$PATH_SEPARATOR/usr/bin$PATH_SEPARATOR$PATH
do
IFS=$as_save_IFS
test -z "$as_dir" && as_dir=.
as_found=:
case $as_dir in #(
/*)
for as_base in sh bash ksh sh5; do
# Try only shells that exist, to save several forks.
as_shell=$as_dir/$as_base
if { test -f "$as_shell" || test -f "$as_shell.exe"; } &&
{ $as_echo "$as_bourne_compatible""$as_required" | as_run=a "$as_shell"; } 2>/dev/null; then :
CONFIG_SHELL=$as_shell as_have_required=yes
if { $as_echo "$as_bourne_compatible""$as_suggested" | as_run=a "$as_shell"; } 2>/dev/null; then :
break 2
fi
fi
done;;
esac
as_found=false
done
$as_found || { if { test -f "$SHELL" || test -f "$SHELL.exe"; } &&
{ $as_echo "$as_bourne_compatible""$as_required" | as_run=a "$SHELL"; } 2>/dev/null; then :
CONFIG_SHELL=$SHELL as_have_required=yes
fi; }
IFS=$as_save_IFS
if test "x$CONFIG_SHELL" != x; then :
# We cannot yet assume a decent shell, so we have to provide a
# neutralization value for shells without unset; and this also
# works around shells that cannot unset nonexistent variables.
BASH_ENV=/dev/null
ENV=/dev/null
(unset BASH_ENV) >/dev/null 2>&1 && unset BASH_ENV ENV
export CONFIG_SHELL
exec "$CONFIG_SHELL" "$as_myself" ${1+"$@"}
fi
if test x$as_have_required = xno; then :
$as_echo "$0: This script requires a shell more modern than all"
$as_echo "$0: the shells that I found on your system."
if test x${ZSH_VERSION+set} = xset ; then
$as_echo "$0: In particular, zsh $ZSH_VERSION has bugs and should"
$as_echo "$0: be upgraded to zsh 4.3.4 or later."
else
$as_echo "$0: Please tell bug-autoconf@gnu.org and
$0: s.guindon@auckland.ac.nz about your system, including
$0: any error possibly output before this message. Then
$0: install a modern shell, or manually run the script
$0: under such a shell if you do have one."
fi
exit 1
fi
fi
fi
SHELL=${CONFIG_SHELL-/bin/sh}
export SHELL
# Unset more variables known to interfere with behavior of common tools.
CLICOLOR_FORCE= GREP_OPTIONS=
unset CLICOLOR_FORCE GREP_OPTIONS
## --------------------- ##
## M4sh Shell Functions. ##
## --------------------- ##
# as_fn_unset VAR
# ---------------
# Portably unset VAR.
as_fn_unset ()
{
{ eval $1=; unset $1;}
}
as_unset=as_fn_unset
# as_fn_set_status STATUS
# -----------------------
# Set $? to STATUS, without forking.
as_fn_set_status ()
{
return $1
} # as_fn_set_status
# as_fn_exit STATUS
# -----------------
# Exit the shell with STATUS, even in a "trap 0" or "set -e" context.
as_fn_exit ()
{
set +e
as_fn_set_status $1
exit $1
} # as_fn_exit
# as_fn_mkdir_p
# -------------
# Create "$as_dir" as a directory, including parents if necessary.
as_fn_mkdir_p ()
{
case $as_dir in #(
-*) as_dir=./$as_dir;;
esac
test -d "$as_dir" || eval $as_mkdir_p || {
as_dirs=
while :; do
case $as_dir in #(
*\'*) as_qdir=`$as_echo "$as_dir" | sed "s/'/'\\\\\\\\''/g"`;; #'(
*) as_qdir=$as_dir;;
esac
as_dirs="'$as_qdir' $as_dirs"
as_dir=`$as_dirname -- "$as_dir" ||
$as_expr X"$as_dir" : 'X\(.*[^/]\)//*[^/][^/]*/*$' \| \
X"$as_dir" : 'X\(//\)[^/]' \| \
X"$as_dir" : 'X\(//\)$' \| \
X"$as_dir" : 'X\(/\)' \| . 2>/dev/null ||
$as_echo X"$as_dir" |
sed '/^X\(.*[^/]\)\/\/*[^/][^/]*\/*$/{
s//\1/
q
}
/^X\(\/\/\)[^/].*/{
s//\1/
q
}
/^X\(\/\/\)$/{
s//\1/
q
}
/^X\(\/\).*/{
s//\1/
q
}
s/.*/./; q'`
test -d "$as_dir" && break
done
test -z "$as_dirs" || eval "mkdir $as_dirs"
} || test -d "$as_dir" || as_fn_error "cannot create directory $as_dir"
} # as_fn_mkdir_p
# as_fn_append VAR VALUE
# ----------------------
# Append the text in VALUE to the end of the definition contained in VAR. Take
# advantage of any shell optimizations that allow amortized linear growth over
# repeated appends, instead of the typical quadratic growth present in naive
# implementations.
if (eval "as_var=1; as_var+=2; test x\$as_var = x12") 2>/dev/null; then :
eval 'as_fn_append ()
{
eval $1+=\$2
}'
else
as_fn_append ()
{
eval $1=\$$1\$2
}
fi # as_fn_append
# as_fn_arith ARG...
# ------------------
# Perform arithmetic evaluation on the ARGs, and store the result in the
# global $as_val. Take advantage of shells that can avoid forks. The arguments
# must be portable across $(()) and expr.
if (eval "test \$(( 1 + 1 )) = 2") 2>/dev/null; then :
eval 'as_fn_arith ()
{
as_val=$(( $* ))
}'
else
as_fn_arith ()
{
as_val=`expr "$@" || test $? -eq 1`
}
fi # as_fn_arith
# as_fn_error ERROR [LINENO LOG_FD]
# ---------------------------------
# Output "`basename $0`: error: ERROR" to stderr. If LINENO and LOG_FD are
# provided, also output the error to LOG_FD, referencing LINENO. Then exit the
# script with status $?, using 1 if that was 0.
as_fn_error ()
{
as_status=$?; test $as_status -eq 0 && as_status=1
if test "$3"; then
as_lineno=${as_lineno-"$2"} as_lineno_stack=as_lineno_stack=$as_lineno_stack
$as_echo "$as_me:${as_lineno-$LINENO}: error: $1" >&$3
fi
$as_echo "$as_me: error: $1" >&2
as_fn_exit $as_status
} # as_fn_error
if expr a : '\(a\)' >/dev/null 2>&1 &&
test "X`expr 00001 : '.*\(...\)'`" = X001; then
as_expr=expr
else
as_expr=false
fi
if (basename -- /) >/dev/null 2>&1 && test "X`basename -- / 2>&1`" = "X/"; then
as_basename=basename
else
as_basename=false
fi
if (as_dir=`dirname -- /` && test "X$as_dir" = X/) >/dev/null 2>&1; then
as_dirname=dirname
else
as_dirname=false
fi
as_me=`$as_basename -- "$0" ||
$as_expr X/"$0" : '.*/\([^/][^/]*\)/*$' \| \
X"$0" : 'X\(//\)$' \| \
X"$0" : 'X\(/\)' \| . 2>/dev/null ||
$as_echo X/"$0" |
sed '/^.*\/\([^/][^/]*\)\/*$/{
s//\1/
q
}
/^X\/\(\/\/\)$/{
s//\1/
q
}
/^X\/\(\/\).*/{
s//\1/
q
}
s/.*/./; q'`
# Avoid depending upon Character Ranges.
as_cr_letters='abcdefghijklmnopqrstuvwxyz'
as_cr_LETTERS='ABCDEFGHIJKLMNOPQRSTUVWXYZ'
as_cr_Letters=$as_cr_letters$as_cr_LETTERS
as_cr_digits='0123456789'
as_cr_alnum=$as_cr_Letters$as_cr_digits
as_lineno_1=$LINENO as_lineno_1a=$LINENO
as_lineno_2=$LINENO as_lineno_2a=$LINENO
eval 'test "x$as_lineno_1'$as_run'" != "x$as_lineno_2'$as_run'" &&
test "x`expr $as_lineno_1'$as_run' + 1`" = "x$as_lineno_2'$as_run'"' || {
# Blame Lee E. McMahon (1931-1989) for sed's syntax. :-)
sed -n '
p
/[$]LINENO/=
' <$as_myself |
sed '
s/[$]LINENO.*/&-/
t lineno
b
:lineno
N
:loop
s/[$]LINENO\([^'$as_cr_alnum'_].*\n\)\(.*\)/\2\1\2/
t loop
s/-\n.*//
' >$as_me.lineno &&
chmod +x "$as_me.lineno" ||
{ $as_echo "$as_me: error: cannot create $as_me.lineno; rerun with a POSIX shell" >&2; as_fn_exit 1; }
# Don't try to exec as it changes $[0], causing all sort of problems
# (the dirname of $[0] is not the place where we might find the
# original and so on. Autoconf is especially sensitive to this).
. "./$as_me.lineno"
# Exit status is that of the last command.
exit
}
ECHO_C= ECHO_N= ECHO_T=
case `echo -n x` in #(((((
-n*)
case `echo 'xy\c'` in
*c*) ECHO_T=' ';; # ECHO_T is single tab character.
xy) ECHO_C='\c';;
*) echo `echo ksh88 bug on AIX 6.1` > /dev/null
ECHO_T=' ';;
esac;;
*)
ECHO_N='-n';;
esac
rm -f conf$$ conf$$.exe conf$$.file
if test -d conf$$.dir; then
rm -f conf$$.dir/conf$$.file
else
rm -f conf$$.dir
mkdir conf$$.dir 2>/dev/null
fi
if (echo >conf$$.file) 2>/dev/null; then
if ln -s conf$$.file conf$$ 2>/dev/null; then
as_ln_s='ln -s'
# ... but there are two gotchas:
# 1) On MSYS, both `ln -s file dir' and `ln file dir' fail.
# 2) DJGPP < 2.04 has no symlinks; `ln -s' creates a wrapper executable.
# In both cases, we have to default to `cp -p'.
ln -s conf$$.file conf$$.dir 2>/dev/null && test ! -f conf$$.exe ||
as_ln_s='cp -p'
elif ln conf$$.file conf$$ 2>/dev/null; then
as_ln_s=ln
else
as_ln_s='cp -p'
fi
else
as_ln_s='cp -p'
fi
rm -f conf$$ conf$$.exe conf$$.dir/conf$$.file conf$$.file
rmdir conf$$.dir 2>/dev/null
if mkdir -p . 2>/dev/null; then
as_mkdir_p='mkdir -p "$as_dir"'
else
test -d ./-p && rmdir ./-p
as_mkdir_p=false
fi
if test -x / >/dev/null 2>&1; then
as_test_x='test -x'
else
if ls -dL / >/dev/null 2>&1; then
as_ls_L_option=L
else
as_ls_L_option=
fi
as_test_x='
eval sh -c '\''
if test -d "$1"; then
test -d "$1/.";
else
case $1 in #(
-*)set "./$1";;
esac;
case `ls -ld'$as_ls_L_option' "$1" 2>/dev/null` in #((
???[sx]*):;;*)false;;esac;fi
'\'' sh
'
fi
as_executable_p=$as_test_x
# Sed expression to map a string onto a valid CPP name.
as_tr_cpp="eval sed 'y%*$as_cr_letters%P$as_cr_LETTERS%;s%[^_$as_cr_alnum]%_%g'"
# Sed expression to map a string onto a valid variable name.
as_tr_sh="eval sed 'y%*+%pp%;s%[^_$as_cr_alnum]%_%g'"
test -n "$DJDIR" || exec 7<&0 &1
# Name of the host.
# hostname on some systems (SVR3.2, Linux) returns a bogus exit status,
# so uname gets run too.
ac_hostname=`(hostname || uname -n) 2>/dev/null | sed 1q`
#
# Initializations.
#
ac_default_prefix=/usr/local
ac_clean_files=
ac_config_libobj_dir=.
LIBOBJS=
cross_compiling=no
subdirs=
MFLAGS=
MAKEFLAGS=
# Identity of this package.
PACKAGE_NAME='PhyML'
PACKAGE_TARNAME='phyml'
PACKAGE_VERSION='20120412'
PACKAGE_STRING='PhyML 20120412'
PACKAGE_BUGREPORT='s.guindon@auckland.ac.nz'
PACKAGE_URL=''
ac_unique_file="src/simu.c"
# Factoring default headers for most tests.
ac_includes_default="\
#include
#ifdef HAVE_SYS_TYPES_H
# include
#endif
#ifdef HAVE_SYS_STAT_H
# include
#endif
#ifdef STDC_HEADERS
# include
# include
#else
# ifdef HAVE_STDLIB_H
# include
# endif
#endif
#ifdef HAVE_STRING_H
# if !defined STDC_HEADERS && defined HAVE_MEMORY_H
# include
# endif
# include
#endif
#ifdef HAVE_STRINGS_H
# include
#endif
#ifdef HAVE_INTTYPES_H
# include
#endif
#ifdef HAVE_STDINT_H
# include
#endif
#ifdef HAVE_UNISTD_H
# include
#endif"
ac_subst_vars='am__EXEEXT_FALSE
am__EXEEXT_TRUE
LTLIBOBJS
WANT_TEST_FALSE
WANT_TEST_TRUE
WANT_RF_FALSE
WANT_RF_TRUE
WANT_M4_FALSE
WANT_M4_TRUE
WANT_PHYCONT_FALSE
WANT_PHYCONT_TRUE
WANT_RWRAP_FALSE
WANT_RWRAP_TRUE
WANT_PART_FALSE
WANT_PART_TRUE
WANT_TIPORDER_FALSE
WANT_TIPORDER_TRUE
WANT_PHYTIME_FALSE
WANT_PHYTIME_TRUE
WANT_MPI_FALSE
WANT_MPI_TRUE
LIBOBJS
EGREP
GREP
CPP
am__fastdepCC_FALSE
am__fastdepCC_TRUE
CCDEPMODE
AMDEPBACKSLASH
AMDEP_FALSE
AMDEP_TRUE
am__quote
am__include
DEPDIR
OBJEXT
EXEEXT
ac_ct_CC
CPPFLAGS
LDFLAGS
CFLAGS
CC
host_os
host_vendor
host_cpu
host
build_os
build_vendor
build_cpu
build
AM_BACKSLASH
AM_DEFAULT_VERBOSITY
am__untar
am__tar
AMTAR
am__leading_dot
SET_MAKE
AWK
mkdir_p
MKDIR_P
INSTALL_STRIP_PROGRAM
STRIP
install_sh
MAKEINFO
AUTOHEADER
AUTOMAKE
AUTOCONF
ACLOCAL
VERSION
PACKAGE
CYGPATH_W
am__isrc
INSTALL_DATA
INSTALL_SCRIPT
INSTALL_PROGRAM
target_alias
host_alias
build_alias
LIBS
ECHO_T
ECHO_N
ECHO_C
DEFS
mandir
localedir
libdir
psdir
pdfdir
dvidir
htmldir
infodir
docdir
oldincludedir
includedir
localstatedir
sharedstatedir
sysconfdir
datadir
datarootdir
libexecdir
sbindir
bindir
program_transform_name
prefix
exec_prefix
PACKAGE_URL
PACKAGE_BUGREPORT
PACKAGE_STRING
PACKAGE_VERSION
PACKAGE_TARNAME
PACKAGE_NAME
PATH_SEPARATOR
SHELL'
ac_subst_files=''
ac_user_opts='
enable_option_checking
enable_silent_rules
enable_dependency_tracking
enable_debug
enable_mpi
enable_phytime
enable_tiporder
enable_part
enable_rwrap
enable_phycont
enable_m4
enable_rf
enable_test
'
ac_precious_vars='build_alias
host_alias
target_alias
CC
CFLAGS
LDFLAGS
LIBS
CPPFLAGS
CPP'
# Initialize some variables set by options.
ac_init_help=
ac_init_version=false
ac_unrecognized_opts=
ac_unrecognized_sep=
# The variables have the same names as the options, with
# dashes changed to underlines.
cache_file=/dev/null
exec_prefix=NONE
no_create=
no_recursion=
prefix=NONE
program_prefix=NONE
program_suffix=NONE
program_transform_name=s,x,x,
silent=
site=
srcdir=
verbose=
x_includes=NONE
x_libraries=NONE
# Installation directory options.
# These are left unexpanded so users can "make install exec_prefix=/foo"
# and all the variables that are supposed to be based on exec_prefix
# by default will actually change.
# Use braces instead of parens because sh, perl, etc. also accept them.
# (The list follows the same order as the GNU Coding Standards.)
bindir='${exec_prefix}/bin'
sbindir='${exec_prefix}/sbin'
libexecdir='${exec_prefix}/libexec'
datarootdir='${prefix}/share'
datadir='${datarootdir}'
sysconfdir='${prefix}/etc'
sharedstatedir='${prefix}/com'
localstatedir='${prefix}/var'
includedir='${prefix}/include'
oldincludedir='/usr/include'
docdir='${datarootdir}/doc/${PACKAGE_TARNAME}'
infodir='${datarootdir}/info'
htmldir='${docdir}'
dvidir='${docdir}'
pdfdir='${docdir}'
psdir='${docdir}'
libdir='${exec_prefix}/lib'
localedir='${datarootdir}/locale'
mandir='${datarootdir}/man'
ac_prev=
ac_dashdash=
for ac_option
do
# If the previous option needs an argument, assign it.
if test -n "$ac_prev"; then
eval $ac_prev=\$ac_option
ac_prev=
continue
fi
case $ac_option in
*=*) ac_optarg=`expr "X$ac_option" : '[^=]*=\(.*\)'` ;;
*) ac_optarg=yes ;;
esac
# Accept the important Cygnus configure options, so we can diagnose typos.
case $ac_dashdash$ac_option in
--)
ac_dashdash=yes ;;
-bindir | --bindir | --bindi | --bind | --bin | --bi)
ac_prev=bindir ;;
-bindir=* | --bindir=* | --bindi=* | --bind=* | --bin=* | --bi=*)
bindir=$ac_optarg ;;
-build | --build | --buil | --bui | --bu)
ac_prev=build_alias ;;
-build=* | --build=* | --buil=* | --bui=* | --bu=*)
build_alias=$ac_optarg ;;
-cache-file | --cache-file | --cache-fil | --cache-fi \
| --cache-f | --cache- | --cache | --cach | --cac | --ca | --c)
ac_prev=cache_file ;;
-cache-file=* | --cache-file=* | --cache-fil=* | --cache-fi=* \
| --cache-f=* | --cache-=* | --cache=* | --cach=* | --cac=* | --ca=* | --c=*)
cache_file=$ac_optarg ;;
--config-cache | -C)
cache_file=config.cache ;;
-datadir | --datadir | --datadi | --datad)
ac_prev=datadir ;;
-datadir=* | --datadir=* | --datadi=* | --datad=*)
datadir=$ac_optarg ;;
-datarootdir | --datarootdir | --datarootdi | --datarootd | --dataroot \
| --dataroo | --dataro | --datar)
ac_prev=datarootdir ;;
-datarootdir=* | --datarootdir=* | --datarootdi=* | --datarootd=* \
| --dataroot=* | --dataroo=* | --dataro=* | --datar=*)
datarootdir=$ac_optarg ;;
-disable-* | --disable-*)
ac_useropt=`expr "x$ac_option" : 'x-*disable-\(.*\)'`
# Reject names that are not valid shell variable names.
expr "x$ac_useropt" : ".*[^-+._$as_cr_alnum]" >/dev/null &&
as_fn_error "invalid feature name: $ac_useropt"
ac_useropt_orig=$ac_useropt
ac_useropt=`$as_echo "$ac_useropt" | sed 's/[-+.]/_/g'`
case $ac_user_opts in
*"
"enable_$ac_useropt"
"*) ;;
*) ac_unrecognized_opts="$ac_unrecognized_opts$ac_unrecognized_sep--disable-$ac_useropt_orig"
ac_unrecognized_sep=', ';;
esac
eval enable_$ac_useropt=no ;;
-docdir | --docdir | --docdi | --doc | --do)
ac_prev=docdir ;;
-docdir=* | --docdir=* | --docdi=* | --doc=* | --do=*)
docdir=$ac_optarg ;;
-dvidir | --dvidir | --dvidi | --dvid | --dvi | --dv)
ac_prev=dvidir ;;
-dvidir=* | --dvidir=* | --dvidi=* | --dvid=* | --dvi=* | --dv=*)
dvidir=$ac_optarg ;;
-enable-* | --enable-*)
ac_useropt=`expr "x$ac_option" : 'x-*enable-\([^=]*\)'`
# Reject names that are not valid shell variable names.
expr "x$ac_useropt" : ".*[^-+._$as_cr_alnum]" >/dev/null &&
as_fn_error "invalid feature name: $ac_useropt"
ac_useropt_orig=$ac_useropt
ac_useropt=`$as_echo "$ac_useropt" | sed 's/[-+.]/_/g'`
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\`configure' configures PhyML 20120412 to adapt to many kinds of systems.
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PhyML configure 20120412
generated by GNU Autoconf 2.65
Copyright (C) 2009 Free Software Foundation, Inc.
This configure script is free software; the Free Software Foundation
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esac
eval ac_try_echo="\"\$as_me:${as_lineno-$LINENO}: $ac_try_echo\""
$as_echo "$ac_try_echo"; } >&5
(eval "$ac_compile") 2>conftest.err
ac_status=$?
if test -s conftest.err; then
grep -v '^ *+' conftest.err >conftest.er1
cat conftest.er1 >&5
mv -f conftest.er1 conftest.err
fi
$as_echo "$as_me:${as_lineno-$LINENO}: \$? = $ac_status" >&5
test $ac_status = 0; } && {
test -z "$ac_c_werror_flag" ||
test ! -s conftest.err
} && test -s conftest.$ac_objext; then :
ac_retval=0
else
$as_echo "$as_me: failed program was:" >&5
sed 's/^/| /' conftest.$ac_ext >&5
ac_retval=1
fi
eval $as_lineno_stack; test "x$as_lineno_stack" = x && { as_lineno=; unset as_lineno;}
as_fn_set_status $ac_retval
} # ac_fn_c_try_compile
# ac_fn_c_try_link LINENO
# -----------------------
# Try to link conftest.$ac_ext, and return whether this succeeded.
ac_fn_c_try_link ()
{
as_lineno=${as_lineno-"$1"} as_lineno_stack=as_lineno_stack=$as_lineno_stack
rm -f conftest.$ac_objext conftest$ac_exeext
if { { ac_try="$ac_link"
case "(($ac_try" in
*\"* | *\`* | *\\*) ac_try_echo=\$ac_try;;
*) ac_try_echo=$ac_try;;
esac
eval ac_try_echo="\"\$as_me:${as_lineno-$LINENO}: $ac_try_echo\""
$as_echo "$ac_try_echo"; } >&5
(eval "$ac_link") 2>conftest.err
ac_status=$?
if test -s conftest.err; then
grep -v '^ *+' conftest.err >conftest.er1
cat conftest.er1 >&5
mv -f conftest.er1 conftest.err
fi
$as_echo "$as_me:${as_lineno-$LINENO}: \$? = $ac_status" >&5
test $ac_status = 0; } && {
test -z "$ac_c_werror_flag" ||
test ! -s conftest.err
} && test -s conftest$ac_exeext && {
test "$cross_compiling" = yes ||
$as_test_x conftest$ac_exeext
}; then :
ac_retval=0
else
$as_echo "$as_me: failed program was:" >&5
sed 's/^/| /' conftest.$ac_ext >&5
ac_retval=1
fi
# Delete the IPA/IPO (Inter Procedural Analysis/Optimization) information
# created by the PGI compiler (conftest_ipa8_conftest.oo), as it would
# interfere with the next link command; also delete a directory that is
# left behind by Apple's compiler. We do this before executing the actions.
rm -rf conftest.dSYM conftest_ipa8_conftest.oo
eval $as_lineno_stack; test "x$as_lineno_stack" = x && { as_lineno=; unset as_lineno;}
as_fn_set_status $ac_retval
} # ac_fn_c_try_link
# ac_fn_c_try_cpp LINENO
# ----------------------
# Try to preprocess conftest.$ac_ext, and return whether this succeeded.
ac_fn_c_try_cpp ()
{
as_lineno=${as_lineno-"$1"} as_lineno_stack=as_lineno_stack=$as_lineno_stack
if { { ac_try="$ac_cpp conftest.$ac_ext"
case "(($ac_try" in
*\"* | *\`* | *\\*) ac_try_echo=\$ac_try;;
*) ac_try_echo=$ac_try;;
esac
eval ac_try_echo="\"\$as_me:${as_lineno-$LINENO}: $ac_try_echo\""
$as_echo "$ac_try_echo"; } >&5
(eval "$ac_cpp conftest.$ac_ext") 2>conftest.err
ac_status=$?
if test -s conftest.err; then
grep -v '^ *+' conftest.err >conftest.er1
cat conftest.er1 >&5
mv -f conftest.er1 conftest.err
fi
$as_echo "$as_me:${as_lineno-$LINENO}: \$? = $ac_status" >&5
test $ac_status = 0; } >/dev/null && {
test -z "$ac_c_preproc_warn_flag$ac_c_werror_flag" ||
test ! -s conftest.err
}; then :
ac_retval=0
else
$as_echo "$as_me: failed program was:" >&5
sed 's/^/| /' conftest.$ac_ext >&5
ac_retval=1
fi
eval $as_lineno_stack; test "x$as_lineno_stack" = x && { as_lineno=; unset as_lineno;}
as_fn_set_status $ac_retval
} # ac_fn_c_try_cpp
# ac_fn_c_try_run LINENO
# ----------------------
# Try to link conftest.$ac_ext, and return whether this succeeded. Assumes
# that executables *can* be run.
ac_fn_c_try_run ()
{
as_lineno=${as_lineno-"$1"} as_lineno_stack=as_lineno_stack=$as_lineno_stack
if { { ac_try="$ac_link"
case "(($ac_try" in
*\"* | *\`* | *\\*) ac_try_echo=\$ac_try;;
*) ac_try_echo=$ac_try;;
esac
eval ac_try_echo="\"\$as_me:${as_lineno-$LINENO}: $ac_try_echo\""
$as_echo "$ac_try_echo"; } >&5
(eval "$ac_link") 2>&5
ac_status=$?
$as_echo "$as_me:${as_lineno-$LINENO}: \$? = $ac_status" >&5
test $ac_status = 0; } && { ac_try='./conftest$ac_exeext'
{ { case "(($ac_try" in
*\"* | *\`* | *\\*) ac_try_echo=\$ac_try;;
*) ac_try_echo=$ac_try;;
esac
eval ac_try_echo="\"\$as_me:${as_lineno-$LINENO}: $ac_try_echo\""
$as_echo "$ac_try_echo"; } >&5
(eval "$ac_try") 2>&5
ac_status=$?
$as_echo "$as_me:${as_lineno-$LINENO}: \$? = $ac_status" >&5
test $ac_status = 0; }; }; then :
ac_retval=0
else
$as_echo "$as_me: program exited with status $ac_status" >&5
$as_echo "$as_me: failed program was:" >&5
sed 's/^/| /' conftest.$ac_ext >&5
ac_retval=$ac_status
fi
rm -rf conftest.dSYM conftest_ipa8_conftest.oo
eval $as_lineno_stack; test "x$as_lineno_stack" = x && { as_lineno=; unset as_lineno;}
as_fn_set_status $ac_retval
} # ac_fn_c_try_run
# ac_fn_c_check_header_mongrel LINENO HEADER VAR INCLUDES
# -------------------------------------------------------
# Tests whether HEADER exists, giving a warning if it cannot be compiled using
# the include files in INCLUDES and setting the cache variable VAR
# accordingly.
ac_fn_c_check_header_mongrel ()
{
as_lineno=${as_lineno-"$1"} as_lineno_stack=as_lineno_stack=$as_lineno_stack
if { as_var=$3; eval "test \"\${$as_var+set}\" = set"; }; then :
{ $as_echo "$as_me:${as_lineno-$LINENO}: checking for $2" >&5
$as_echo_n "checking for $2... " >&6; }
if { as_var=$3; eval "test \"\${$as_var+set}\" = set"; }; then :
$as_echo_n "(cached) " >&6
fi
eval ac_res=\$$3
{ $as_echo "$as_me:${as_lineno-$LINENO}: result: $ac_res" >&5
$as_echo "$ac_res" >&6; }
else
# Is the header compilable?
{ $as_echo "$as_me:${as_lineno-$LINENO}: checking $2 usability" >&5
$as_echo_n "checking $2 usability... " >&6; }
cat confdefs.h - <<_ACEOF >conftest.$ac_ext
/* end confdefs.h. */
$4
#include <$2>
_ACEOF
if ac_fn_c_try_compile "$LINENO"; then :
ac_header_compiler=yes
else
ac_header_compiler=no
fi
rm -f core conftest.err conftest.$ac_objext conftest.$ac_ext
{ $as_echo "$as_me:${as_lineno-$LINENO}: result: $ac_header_compiler" >&5
$as_echo "$ac_header_compiler" >&6; }
# Is the header present?
{ $as_echo "$as_me:${as_lineno-$LINENO}: checking $2 presence" >&5
$as_echo_n "checking $2 presence... " >&6; }
cat confdefs.h - <<_ACEOF >conftest.$ac_ext
/* end confdefs.h. */
#include <$2>
_ACEOF
if ac_fn_c_try_cpp "$LINENO"; then :
ac_header_preproc=yes
else
ac_header_preproc=no
fi
rm -f conftest.err conftest.$ac_ext
{ $as_echo "$as_me:${as_lineno-$LINENO}: result: $ac_header_preproc" >&5
$as_echo "$ac_header_preproc" >&6; }
# So? What about this header?
case $ac_header_compiler:$ac_header_preproc:$ac_c_preproc_warn_flag in #((
yes:no: )
{ $as_echo "$as_me:${as_lineno-$LINENO}: WARNING: $2: accepted by the compiler, rejected by the preprocessor!" >&5
$as_echo "$as_me: WARNING: $2: accepted by the compiler, rejected by the preprocessor!" >&2;}
{ $as_echo "$as_me:${as_lineno-$LINENO}: WARNING: $2: proceeding with the compiler's result" >&5
$as_echo "$as_me: WARNING: $2: proceeding with the compiler's result" >&2;}
;;
no:yes:* )
{ $as_echo "$as_me:${as_lineno-$LINENO}: WARNING: $2: present but cannot be compiled" >&5
$as_echo "$as_me: WARNING: $2: present but cannot be compiled" >&2;}
{ $as_echo "$as_me:${as_lineno-$LINENO}: WARNING: $2: check for missing prerequisite headers?" >&5
$as_echo "$as_me: WARNING: $2: check for missing prerequisite headers?" >&2;}
{ $as_echo "$as_me:${as_lineno-$LINENO}: WARNING: $2: see the Autoconf documentation" >&5
$as_echo "$as_me: WARNING: $2: see the Autoconf documentation" >&2;}
{ $as_echo "$as_me:${as_lineno-$LINENO}: WARNING: $2: section \"Present But Cannot Be Compiled\"" >&5
$as_echo "$as_me: WARNING: $2: section \"Present But Cannot Be Compiled\"" >&2;}
{ $as_echo "$as_me:${as_lineno-$LINENO}: WARNING: $2: proceeding with the compiler's result" >&5
$as_echo "$as_me: WARNING: $2: proceeding with the compiler's result" >&2;}
( cat <<\_ASBOX
## --------------------------------------- ##
## Report this to s.guindon@auckland.ac.nz ##
## --------------------------------------- ##
_ASBOX
) | sed "s/^/$as_me: WARNING: /" >&2
;;
esac
{ $as_echo "$as_me:${as_lineno-$LINENO}: checking for $2" >&5
$as_echo_n "checking for $2... " >&6; }
if { as_var=$3; eval "test \"\${$as_var+set}\" = set"; }; then :
$as_echo_n "(cached) " >&6
else
eval "$3=\$ac_header_compiler"
fi
eval ac_res=\$$3
{ $as_echo "$as_me:${as_lineno-$LINENO}: result: $ac_res" >&5
$as_echo "$ac_res" >&6; }
fi
eval $as_lineno_stack; test "x$as_lineno_stack" = x && { as_lineno=; unset as_lineno;}
} # ac_fn_c_check_header_mongrel
# ac_fn_c_check_header_compile LINENO HEADER VAR INCLUDES
# -------------------------------------------------------
# Tests whether HEADER exists and can be compiled using the include files in
# INCLUDES, setting the cache variable VAR accordingly.
ac_fn_c_check_header_compile ()
{
as_lineno=${as_lineno-"$1"} as_lineno_stack=as_lineno_stack=$as_lineno_stack
{ $as_echo "$as_me:${as_lineno-$LINENO}: checking for $2" >&5
$as_echo_n "checking for $2... " >&6; }
if { as_var=$3; eval "test \"\${$as_var+set}\" = set"; }; then :
$as_echo_n "(cached) " >&6
else
cat confdefs.h - <<_ACEOF >conftest.$ac_ext
/* end confdefs.h. */
$4
#include <$2>
_ACEOF
if ac_fn_c_try_compile "$LINENO"; then :
eval "$3=yes"
else
eval "$3=no"
fi
rm -f core conftest.err conftest.$ac_objext conftest.$ac_ext
fi
eval ac_res=\$$3
{ $as_echo "$as_me:${as_lineno-$LINENO}: result: $ac_res" >&5
$as_echo "$ac_res" >&6; }
eval $as_lineno_stack; test "x$as_lineno_stack" = x && { as_lineno=; unset as_lineno;}
} # ac_fn_c_check_header_compile
# ac_fn_c_check_type LINENO TYPE VAR INCLUDES
# -------------------------------------------
# Tests whether TYPE exists after having included INCLUDES, setting cache
# variable VAR accordingly.
ac_fn_c_check_type ()
{
as_lineno=${as_lineno-"$1"} as_lineno_stack=as_lineno_stack=$as_lineno_stack
{ $as_echo "$as_me:${as_lineno-$LINENO}: checking for $2" >&5
$as_echo_n "checking for $2... " >&6; }
if { as_var=$3; eval "test \"\${$as_var+set}\" = set"; }; then :
$as_echo_n "(cached) " >&6
else
eval "$3=no"
cat confdefs.h - <<_ACEOF >conftest.$ac_ext
/* end confdefs.h. */
$4
int
main ()
{
if (sizeof ($2))
return 0;
;
return 0;
}
_ACEOF
if ac_fn_c_try_compile "$LINENO"; then :
cat confdefs.h - <<_ACEOF >conftest.$ac_ext
/* end confdefs.h. */
$4
int
main ()
{
if (sizeof (($2)))
return 0;
;
return 0;
}
_ACEOF
if ac_fn_c_try_compile "$LINENO"; then :
else
eval "$3=yes"
fi
rm -f core conftest.err conftest.$ac_objext conftest.$ac_ext
fi
rm -f core conftest.err conftest.$ac_objext conftest.$ac_ext
fi
eval ac_res=\$$3
{ $as_echo "$as_me:${as_lineno-$LINENO}: result: $ac_res" >&5
$as_echo "$ac_res" >&6; }
eval $as_lineno_stack; test "x$as_lineno_stack" = x && { as_lineno=; unset as_lineno;}
} # ac_fn_c_check_type
# ac_fn_c_check_func LINENO FUNC VAR
# ----------------------------------
# Tests whether FUNC exists, setting the cache variable VAR accordingly
ac_fn_c_check_func ()
{
as_lineno=${as_lineno-"$1"} as_lineno_stack=as_lineno_stack=$as_lineno_stack
{ $as_echo "$as_me:${as_lineno-$LINENO}: checking for $2" >&5
$as_echo_n "checking for $2... " >&6; }
if { as_var=$3; eval "test \"\${$as_var+set}\" = set"; }; then :
$as_echo_n "(cached) " >&6
else
cat confdefs.h - <<_ACEOF >conftest.$ac_ext
/* end confdefs.h. */
/* Define $2 to an innocuous variant, in case declares $2.
For example, HP-UX 11i declares gettimeofday. */
#define $2 innocuous_$2
/* System header to define __stub macros and hopefully few prototypes,
which can conflict with char $2 (); below.
Prefer to if __STDC__ is defined, since
exists even on freestanding compilers. */
#ifdef __STDC__
# include
#else
# include
#endif
#undef $2
/* Override any GCC internal prototype to avoid an error.
Use char because int might match the return type of a GCC
builtin and then its argument prototype would still apply. */
#ifdef __cplusplus
extern "C"
#endif
char $2 ();
/* The GNU C library defines this for functions which it implements
to always fail with ENOSYS. Some functions are actually named
something starting with __ and the normal name is an alias. */
#if defined __stub_$2 || defined __stub___$2
choke me
#endif
int
main ()
{
return $2 ();
;
return 0;
}
_ACEOF
if ac_fn_c_try_link "$LINENO"; then :
eval "$3=yes"
else
eval "$3=no"
fi
rm -f core conftest.err conftest.$ac_objext \
conftest$ac_exeext conftest.$ac_ext
fi
eval ac_res=\$$3
{ $as_echo "$as_me:${as_lineno-$LINENO}: result: $ac_res" >&5
$as_echo "$ac_res" >&6; }
eval $as_lineno_stack; test "x$as_lineno_stack" = x && { as_lineno=; unset as_lineno;}
} # ac_fn_c_check_func
cat >config.log <<_ACEOF
This file contains any messages produced by compilers while
running configure, to aid debugging if configure makes a mistake.
It was created by PhyML $as_me 20120412, which was
generated by GNU Autoconf 2.65. Invocation command line was
$ $0 $@
_ACEOF
exec 5>>config.log
{
cat <<_ASUNAME
## --------- ##
## Platform. ##
## --------- ##
hostname = `(hostname || uname -n) 2>/dev/null | sed 1q`
uname -m = `(uname -m) 2>/dev/null || echo unknown`
uname -r = `(uname -r) 2>/dev/null || echo unknown`
uname -s = `(uname -s) 2>/dev/null || echo unknown`
uname -v = `(uname -v) 2>/dev/null || echo unknown`
/usr/bin/uname -p = `(/usr/bin/uname -p) 2>/dev/null || echo unknown`
/bin/uname -X = `(/bin/uname -X) 2>/dev/null || echo unknown`
/bin/arch = `(/bin/arch) 2>/dev/null || echo unknown`
/usr/bin/arch -k = `(/usr/bin/arch -k) 2>/dev/null || echo unknown`
/usr/convex/getsysinfo = `(/usr/convex/getsysinfo) 2>/dev/null || echo unknown`
/usr/bin/hostinfo = `(/usr/bin/hostinfo) 2>/dev/null || echo unknown`
/bin/machine = `(/bin/machine) 2>/dev/null || echo unknown`
/usr/bin/oslevel = `(/usr/bin/oslevel) 2>/dev/null || echo unknown`
/bin/universe = `(/bin/universe) 2>/dev/null || echo unknown`
_ASUNAME
as_save_IFS=$IFS; IFS=$PATH_SEPARATOR
for as_dir in $PATH
do
IFS=$as_save_IFS
test -z "$as_dir" && as_dir=.
$as_echo "PATH: $as_dir"
done
IFS=$as_save_IFS
} >&5
cat >&5 <<_ACEOF
## ----------- ##
## Core tests. ##
## ----------- ##
_ACEOF
# Keep a trace of the command line.
# Strip out --no-create and --no-recursion so they do not pile up.
# Strip out --silent because we don't want to record it for future runs.
# Also quote any args containing shell meta-characters.
# Make two passes to allow for proper duplicate-argument suppression.
ac_configure_args=
ac_configure_args0=
ac_configure_args1=
ac_must_keep_next=false
for ac_pass in 1 2
do
for ac_arg
do
case $ac_arg in
-no-create | --no-c* | -n | -no-recursion | --no-r*) continue ;;
-q | -quiet | --quiet | --quie | --qui | --qu | --q \
| -silent | --silent | --silen | --sile | --sil)
continue ;;
*\'*)
ac_arg=`$as_echo "$ac_arg" | sed "s/'/'\\\\\\\\''/g"` ;;
esac
case $ac_pass in
1) as_fn_append ac_configure_args0 " '$ac_arg'" ;;
2)
as_fn_append ac_configure_args1 " '$ac_arg'"
if test $ac_must_keep_next = true; then
ac_must_keep_next=false # Got value, back to normal.
else
case $ac_arg in
*=* | --config-cache | -C | -disable-* | --disable-* \
| -enable-* | --enable-* | -gas | --g* | -nfp | --nf* \
| -q | -quiet | --q* | -silent | --sil* | -v | -verb* \
| -with-* | --with-* | -without-* | --without-* | --x)
case "$ac_configure_args0 " in
"$ac_configure_args1"*" '$ac_arg' "* ) continue ;;
esac
;;
-* ) ac_must_keep_next=true ;;
esac
fi
as_fn_append ac_configure_args " '$ac_arg'"
;;
esac
done
done
{ ac_configure_args0=; unset ac_configure_args0;}
{ ac_configure_args1=; unset ac_configure_args1;}
# When interrupted or exit'd, cleanup temporary files, and complete
# config.log. We remove comments because anyway the quotes in there
# would cause problems or look ugly.
# WARNING: Use '\'' to represent an apostrophe within the trap.
# WARNING: Do not start the trap code with a newline, due to a FreeBSD 4.0 bug.
trap 'exit_status=$?
# Save into config.log some information that might help in debugging.
{
echo
cat <<\_ASBOX
## ---------------- ##
## Cache variables. ##
## ---------------- ##
_ASBOX
echo
# The following way of writing the cache mishandles newlines in values,
(
for ac_var in `(set) 2>&1 | sed -n '\''s/^\([a-zA-Z_][a-zA-Z0-9_]*\)=.*/\1/p'\''`; do
eval ac_val=\$$ac_var
case $ac_val in #(
*${as_nl}*)
case $ac_var in #(
*_cv_*) { $as_echo "$as_me:${as_lineno-$LINENO}: WARNING: cache variable $ac_var contains a newline" >&5
$as_echo "$as_me: WARNING: cache variable $ac_var contains a newline" >&2;} ;;
esac
case $ac_var in #(
_ | IFS | as_nl) ;; #(
BASH_ARGV | BASH_SOURCE) eval $ac_var= ;; #(
*) { eval $ac_var=; unset $ac_var;} ;;
esac ;;
esac
done
(set) 2>&1 |
case $as_nl`(ac_space='\'' '\''; set) 2>&1` in #(
*${as_nl}ac_space=\ *)
sed -n \
"s/'\''/'\''\\\\'\'''\''/g;
s/^\\([_$as_cr_alnum]*_cv_[_$as_cr_alnum]*\\)=\\(.*\\)/\\1='\''\\2'\''/p"
;; #(
*)
sed -n "/^[_$as_cr_alnum]*_cv_[_$as_cr_alnum]*=/p"
;;
esac |
sort
)
echo
cat <<\_ASBOX
## ----------------- ##
## Output variables. ##
## ----------------- ##
_ASBOX
echo
for ac_var in $ac_subst_vars
do
eval ac_val=\$$ac_var
case $ac_val in
*\'\''*) ac_val=`$as_echo "$ac_val" | sed "s/'\''/'\''\\\\\\\\'\'''\''/g"`;;
esac
$as_echo "$ac_var='\''$ac_val'\''"
done | sort
echo
if test -n "$ac_subst_files"; then
cat <<\_ASBOX
## ------------------- ##
## File substitutions. ##
## ------------------- ##
_ASBOX
echo
for ac_var in $ac_subst_files
do
eval ac_val=\$$ac_var
case $ac_val in
*\'\''*) ac_val=`$as_echo "$ac_val" | sed "s/'\''/'\''\\\\\\\\'\'''\''/g"`;;
esac
$as_echo "$ac_var='\''$ac_val'\''"
done | sort
echo
fi
if test -s confdefs.h; then
cat <<\_ASBOX
## ----------- ##
## confdefs.h. ##
## ----------- ##
_ASBOX
echo
cat confdefs.h
echo
fi
test "$ac_signal" != 0 &&
$as_echo "$as_me: caught signal $ac_signal"
$as_echo "$as_me: exit $exit_status"
} >&5
rm -f core *.core core.conftest.* &&
rm -f -r conftest* confdefs* conf$$* $ac_clean_files &&
exit $exit_status
' 0
for ac_signal in 1 2 13 15; do
trap 'ac_signal='$ac_signal'; as_fn_exit 1' $ac_signal
done
ac_signal=0
# confdefs.h avoids OS command line length limits that DEFS can exceed.
rm -f -r conftest* confdefs.h
$as_echo "/* confdefs.h */" > confdefs.h
# Predefined preprocessor variables.
cat >>confdefs.h <<_ACEOF
#define PACKAGE_NAME "$PACKAGE_NAME"
_ACEOF
cat >>confdefs.h <<_ACEOF
#define PACKAGE_TARNAME "$PACKAGE_TARNAME"
_ACEOF
cat >>confdefs.h <<_ACEOF
#define PACKAGE_VERSION "$PACKAGE_VERSION"
_ACEOF
cat >>confdefs.h <<_ACEOF
#define PACKAGE_STRING "$PACKAGE_STRING"
_ACEOF
cat >>confdefs.h <<_ACEOF
#define PACKAGE_BUGREPORT "$PACKAGE_BUGREPORT"
_ACEOF
cat >>confdefs.h <<_ACEOF
#define PACKAGE_URL "$PACKAGE_URL"
_ACEOF
# Let the site file select an alternate cache file if it wants to.
# Prefer an explicitly selected file to automatically selected ones.
ac_site_file1=NONE
ac_site_file2=NONE
if test -n "$CONFIG_SITE"; then
ac_site_file1=$CONFIG_SITE
elif test "x$prefix" != xNONE; then
ac_site_file1=$prefix/share/config.site
ac_site_file2=$prefix/etc/config.site
else
ac_site_file1=$ac_default_prefix/share/config.site
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for ac_site_file in "$ac_site_file1" "$ac_site_file2"
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{ $as_echo "$as_me:${as_lineno-$LINENO}: loading site script $ac_site_file" >&5
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. "$ac_site_file"
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{ $as_echo "$as_me:${as_lineno-$LINENO}: creating cache $cache_file" >&5
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ac_cache_corrupted=false
for ac_var in $ac_precious_vars; do
eval ac_old_set=\$ac_cv_env_${ac_var}_set
eval ac_new_set=\$ac_env_${ac_var}_set
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set,)
{ $as_echo "$as_me:${as_lineno-$LINENO}: error: \`$ac_var' was set to \`$ac_old_val' in the previous run" >&5
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ac_cache_corrupted=: ;;
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{ $as_echo "$as_me:${as_lineno-$LINENO}: error: \`$ac_var' was not set in the previous run" >&5
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ac_cache_corrupted=: ;;
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ac_cache_corrupted=:
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{ $as_echo "$as_me:${as_lineno-$LINENO}: warning: ignoring whitespace changes in \`$ac_var' since the previous run:" >&5
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eval $ac_var=\$ac_old_val
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{ $as_echo "$as_me:${as_lineno-$LINENO}: former value: \`$ac_old_val'" >&5
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if $ac_cache_corrupted; then
{ $as_echo "$as_me:${as_lineno-$LINENO}: error: in \`$ac_pwd':" >&5
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{ $as_echo "$as_me:${as_lineno-$LINENO}: error: changes in the environment can compromise the build" >&5
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## -------------------- ##
## Main body of script. ##
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ac_ext=c
ac_cpp='$CPP $CPPFLAGS'
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ac_link='$CC -o conftest$ac_exeext $CFLAGS $CPPFLAGS $LDFLAGS conftest.$ac_ext $LIBS >&5'
ac_compiler_gnu=$ac_cv_c_compiler_gnu
am__api_version='1.11'
ac_aux_dir=
for ac_dir in "$srcdir" "$srcdir/.." "$srcdir/../.."; do
for ac_t in install-sh install.sh shtool; do
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as_fn_error "cannot find install-sh, install.sh, or shtool in \"$srcdir\" \"$srcdir/..\" \"$srcdir/../..\"" "$LINENO" 5
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# These three variables are undocumented and unsupported,
# and are intended to be withdrawn in a future Autoconf release.
# They can cause serious problems if a builder's source tree is in a directory
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ac_config_guess="$SHELL $ac_aux_dir/config.guess" # Please don't use this var.
ac_config_sub="$SHELL $ac_aux_dir/config.sub" # Please don't use this var.
ac_configure="$SHELL $ac_aux_dir/configure" # Please don't use this var.
# Find a good install program. We prefer a C program (faster),
# so one script is as good as another. But avoid the broken or
# incompatible versions:
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# SunOS /usr/etc/install
# IRIX /sbin/install
# AIX /bin/install
# AmigaOS /C/install, which installs bootblocks on floppy discs
# AIX 4 /usr/bin/installbsd, which doesn't work without a -g flag
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# SVR4 /usr/ucb/install, which tries to use the nonexistent group "staff"
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{ $as_echo "$as_me:${as_lineno-$LINENO}: checking for a BSD-compatible install" >&5
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./ | .// | /[cC]/* | \
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then
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fi
fi
done
done
;;
esac
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IFS=$as_save_IFS
rm -rf conftest.one conftest.two conftest.dir
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if test "${ac_cv_path_install+set}" = set; then
INSTALL=$ac_cv_path_install
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# As a last resort, use the slow shell script. Don't cache a
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{ $as_echo "$as_me:${as_lineno-$LINENO}: result: $INSTALL" >&5
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{ $as_echo "$as_me:${as_lineno-$LINENO}: result: yes" >&5
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# Installed binaries are usually stripped using `strip' when the user
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ac_status=$?
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{ { $as_echo "$as_me:${as_lineno-$LINENO}: error: in \`$ac_pwd':" >&5
$as_echo "$as_me: error: in \`$ac_pwd':" >&2;}
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{ $as_echo "$as_me:${as_lineno-$LINENO}: result: $cross_compiling" >&5
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ac_clean_files=$ac_clean_files_save
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rm -f conftest.o conftest.obj
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choke me
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;
return 0;
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if ac_fn_c_try_compile "$LINENO"; then :
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return 0;
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if ac_fn_c_try_compile "$LINENO"; then :
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int
main ()
{
;
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if ac_fn_c_try_compile "$LINENO"; then :
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rm -f core conftest.err conftest.$ac_objext conftest.$ac_ext
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/* end confdefs.h. */
#include
#include
#include
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struct buf { int x; };
FILE * (*rcsopen) (struct buf *, struct stat *, int);
static char *e (p, i)
char **p;
int i;
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struct s1 {int (*f) (int a);};
struct s2 {int (*f) (double a);};
int pairnames (int, char **, FILE *(*)(struct buf *, struct stat *, int), int, int);
int argc;
char **argv;
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msvisualcpp | msvcmsys)
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# When given -MP, icc 7.0 and 7.1 complain thusly:
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msvisualcpp | msvcmsys)
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if ac_fn_c_try_link "$LINENO"; then :
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# exists even on freestanding compilers.
# On the NeXT, cc -E runs the code through the compiler's parser,
# not just through cpp. "Syntax error" is here to catch this case.
cat confdefs.h - <<_ACEOF >conftest.$ac_ext
/* end confdefs.h. */
#ifdef __STDC__
# include