python-fftw_0.2.2/ 0000755 0001750 0001750 00000000000 11671131447 013413 5 ustar jerome jerome python-fftw_0.2.2/PKG-INFO 0000644 0001750 0001750 00000001677 11667604566 014537 0 ustar jerome jerome Metadata-Version: 1.1
Name: PyFFTW3
Version: 0.2.2
Summary: PyFFTW: Python bindings to the FFTW3 C-library
Home-page: www.launchpad.net/pyfftw
Author: Jochen Schroeder
Author-email: cycomanic@gmail.com
License: GPL v3
Description: PyFFTW provieds Python bindings to the FFTW3 "Fastest Fourier Transform in
the West." C-library(http://www.fftw.org/) for computing discrete Fourier
transforms. It uses numpy and ctypes and includes a somewhat pythonic interface
to the FFTW routines, but leaves the concept of creating plans and executing
these plans intact.
Platform: any
Classifier: Development Status :: 4 - Beta
Classifier: Intended Audience :: Science/Research
Classifier: Intended Audience :: Developers
Classifier: License :: OSI Approved :: GNU General Public License (GPL)
Classifier: Operating System :: OS Independent
Classifier: Programming Language :: Python
Classifier: Topic :: Scientific/Engineering
python-fftw_0.2.2/setup.py 0000644 0001750 0001750 00000013141 11667604241 015127 0 ustar jerome jerome #!/usr/bin/env python
"""PyFFTW: Python bindings to the FFTW3 C-library
PyFFTW provieds Python bindings to the FFTW3 "Fastest Fourier Transform in
the West." C-library(http://www.fftw.org/) for computing discrete Fourier
transforms. It uses numpy and ctypes and includes a somewhat pythonic interface
to the FFTW routines, but leaves the concept of creating plans and executing
these plans intact.
"""
classifiers = """\
Development Status :: 4 - Beta
Intended Audience :: Science/Research
Intended Audience :: Developers
License :: OSI Approved :: GNU General Public License (GPL)
Operating System :: OS Independent
Programming Language :: Python
Topic :: Scientific/Engineering
"""
from distutils.core import setup
from distutils.log import warn
from distutils.command.build_py import build_py
import ctypes
from ctypes import util
import os
import platform
import sys
package_data = {}
if os.name=='nt' or platform.system()=='Windows':
# Assuming that the dll content of
# ftp://ftp.fftw.org/pub/fftw/fftw-3.2.2.pl1-dll32.zip
# is copied to the current working directory.
# FFTW_PATH should be either the final installation directory
# of the dll files or empty.
try:
FFTW_PATH = os.environ['FFTW_PATH']
except KeyError:
FFTW_PATH = r''
packages_library_names = {'fftw3': 'libfftw3-3.dll',
'fftw3f' : 'libfftw3f-3.dll',
'fftw3l': 'libfftw3l-3.dll'}
for l, dll in packages_library_names.items():
s = os.path.join (FFTW_PATH, dll)
package_data[l] = [s]
elif platform.system()=='Darwin':
try:
FFTW_PATH = os.environ['FFTW_PATH']
except KeyError:
FFTW_PATH=r'/sw/lib'
packages_library_names = {'fftw3': 'libfftw3.dylib', 'fftw3f' : 'libfftw3f.dylib',
'fftw3l': 'libfftw3l.dylib'}
else:
try:
FFTW_PATH = os.environ['FFTW_PATH']
except KeyError:
FFTW_PATH = r'/usr/lib/'
packages_library_names = {'fftw3': 'libfftw3.so', 'fftw3f' : 'libfftw3f.so',
'fftw3l': 'libfftw3l.so'}
_complex_typedict = {'fftw3':'complex', 'fftw3f': 'singlecomplex', 'fftw3l': 'longcomplex'}
_float_typedict = {'fftw3': 'double', 'fftw3f': 'single', 'fftw3l': 'longdouble'}
packages_0 = ['fftw3','fftw3f', 'fftw3l']
# To used threads, p+'_threads' library must exist in the system where p in packages_0.
def create_source_from_template(tmplfile, outfile, lib, libname, _complex,
_float, location):
fp = open(tmplfile, 'r')
tmpl = fp.read()
fp.close()
mod = tmpl.replace('$libname$',libname).replace('$complex$',_complex).\
replace('$library$',packages_library_names[lib]).replace('$float$',_float).\
replace('$libraryfullpath$', location)
fp = open(outfile, 'w')
fp.write(mod)
fp.close()
print "build %s from template %s" %(outfile, tmplfile)
def check_libs(packages):
libs = {}
for name in packages[:]:
try:
libpath = os.path.join(FFTW_PATH, packages_library_names[name])
if libpath == None:
raise OSError
lib = ctypes.cdll.LoadLibrary(libpath)
print "found %s at %s" %(name, libpath)
except OSError, e:
warn("%s is not located at %s, trying util.find_library(%s)"
%(name, libpath, name))
try:
libpath = util.find_library(name)
if libpath == None:
raise OSError
lib = ctypes.cdll.LoadLibrary(libpath)
print "found %s at %s" %(name, libpath)
except (TypeError,OSError), e:
warn("Not installing bindings for %s, because could not load\
the library: %s\n if you know the library is installed\
you can specify the absolute path in setup.py" % (name, e))
packages.remove(name)
libs[name] = libpath
return packages, libs
packages, liblocation = check_libs(packages_0)
if len(packages) < 1:
packages = ['None']
class build_from_templates(build_py):
def build_module(self, module, module_file, package):
if package == 'None':
raise ValueError('no FFTW files found')
module, ext = os.path.splitext(module)
if not ext == '.tmpl':
outfile = self.get_module_outfile(self.build_lib, [package], module)
dir = os.path.dirname(outfile)
self.mkpath(dir)
return self.copy_file(module_file, outfile, preserve_mode=0)
else:
outfile = self.get_module_outfile(self.build_lib, [package], module)
dir = os.path.dirname(outfile)
self.mkpath(dir)
return create_source_from_template(module_file, outfile, package,
package.replace('3',''),
_complex_typedict[package],
_float_typedict[package],
liblocation[package])
doclines = __doc__.split("\n")
setup(name='PyFFTW3',
version = '0.2.2',
platforms = ["any"],
description = doclines[0],
classifiers = filter(None, classifiers.split("\n")),
long_description = "\n".join(doclines[2:]),
author = 'Jochen Schroeder',
author_email = 'cycomanic@gmail.com',
url = 'www.launchpad.net/pyfftw',
packages = packages,
package_dir = dict([(n, 'src/templates') for n in packages]),
package_data = {},
cmdclass = {"build_py": build_from_templates},
license ='GPL v3'
)
python-fftw_0.2.2/COPYING 0000644 0001750 0001750 00000104513 11335634621 014451 0 ustar jerome jerome GNU GENERAL PUBLIC LICENSE
Version 3, 29 June 2007
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.
python-fftw_0.2.2/test/ 0000755 0001750 0001750 00000000000 11667604566 014406 5 ustar jerome jerome python-fftw_0.2.2/test/test_fftw3.py 0000644 0001750 0001750 00000016427 11377456151 017053 0 ustar jerome jerome import sys
sys.path.insert(0,'../build/lib')
sys.path.insert(0,'../build/lib.linux-x86_64-2.6')
import unittest
import time
import fftw3
import fftw3f
import fftw3l
from numpy.fft import fft,ifft,fftshift
import numpy as np
import fftw3.lib
import fftw3l.lib
import fftw3f.lib
import fftw3.planning
import fftw3l.planning
import fftw3f.planning
import os
h = 0.01
epsilon = 1e-1
beta = 1
N = 512
libs = [fftw3, fftw3f, fftw3l]
_complex = ['complex','singlecomplex','longcomplex']
_float = ['double','single','longdouble']
def fftw_propagation_aligned(N,repeats, lib, dtype):
t = np.linspace(-5,5,N)
dt = t[1]-t[0]
f = np.linspace(-1/dt/2.,1/dt/2.,N)
f = fftshift(f)
t = fftshift(t)
farray = lib.create_aligned_array(f.shape,dtype=dtype)
tarray = lib.create_aligned_array(t.shape,dtype=dtype)
fftplan = lib.Plan(tarray,farray,'forward')
ifftplan = lib.Plan(farray,tarray,'backward')
farray[:] = 0
tarray[:] = 0
tarray += np.exp(-t**2/0.5)
dispersion = np.exp(-1.j*h*beta*f)
ti = time.time()
for i in xrange(repeats):
fftplan()
farray *= dispersion/N
ifftplan()
to = time.time()-ti
return fftshift(t),fftshift(tarray),fftshift(f),fftshift(farray), to
def fftw_propagation(N,repeats,lib, dtype):
t = np.linspace(-5,5,N)
dt = t[1]-t[0]
f = np.linspace(-1/dt/2.,1/dt/2.,N)
f = fftshift(f)
t = fftshift(t)
farray = np.zeros(f.shape,dtype=dtype)
tarray = np.zeros(t.shape,dtype=dtype)
fftplan = lib.Plan(tarray,farray,'forward')
ifftplan = lib.Plan(farray,tarray,'backward')
farray[:] = 0
tarray[:] = 0
tarray += np.exp(-t**2/0.5)
dispersion = np.exp(-1.j*h*beta*f)
ti = time.time()
for i in xrange(repeats):
fftplan()
farray *= dispersion/N
ifftplan()
to = time.time()-ti
return fftshift(t),fftshift(tarray),fftshift(f),fftshift(farray), to
def np_propagation(N,repeats,dtype):
t = np.linspace(-5,5,N)
dt = t[1]-t[0]
f = np.linspace(-1/dt/2.,1/dt/2.,N)
f = fftshift(f)
t = fftshift(t)
tarray = np.zeros(t.shape,dtype)
tarray += np.exp(-t**2/0.5)
farray = np.zeros(tarray.shape,dtype)
dispersion = np.zeros(tarray.shape,dtype)
dispersion += np.exp(-1.j*h*beta*f)
ti = time.time()
for i in xrange(repeats):
farray = fft(tarray)
farray *= dispersion
tarray = ifft(farray)
to = time.time()-ti
return fftshift(t),fftshift(tarray),fftshift(f),fftshift(farray),to
def scipy_propagation(N,repeats, dtype):
try:
from scipy.fftpack import fft as sfft, ifft as sifft
except:
return None, None, None, None, np.NaN
t = np.linspace(-5,5,N)
dt = t[1]-t[0]
f = np.linspace(-1/dt/2.,1/dt/2.,N)
f = fftshift(f)
t = fftshift(t)
tarray = np.zeros(t.shape,dtype)
tarray += np.exp(-t**2/0.5)
farray = np.zeros(tarray.shape,dtype)
dispersion = np.zeros(tarray.shape,dtype)
dispersion += np.exp(-1.j*h*beta*f)
ti = time.time()
for i in xrange(repeats):
farray = sfft(tarray)
farray *= dispersion
tarray = sifft(tarray)
to = time.time()-ti
return fftshift(t),fftshift(tarray),fftshift(f),fftshift(farray),to
class ProductTestCase(unittest.TestCase):
def testSelect(self):
for lib in libs:
for plan in lib.lib._typelist:
if len(plan[1])>2:
plantype,(intype, outtype,length) = plan
shape = np.random.randint(2,5,length)
inputa = np.zeros(shape=shape, dtype=intype)
outputa = np.zeros(shape=shape, dtype=outtype)
else:
plantype, (intype,outtype) = plan
shape = np.random.randint(2,5,np.random.randint(4,8))
length = len(shape)
inputa = np.zeros(shape=shape, dtype=intype)
outputa = np.zeros(shape=shape, dtype=outtype)
func, name, types = lib.planning.select(inputa,outputa)
self.failUnless(name == plantype, "%s: select returned a "\
"wrong type for input array type=%s, output "\
"array type=%s, and dimension = %d" \
%(lib, inputa.dtype, outputa.dtype, length))
self.failUnless(func is getattr(lib.lib.lib, plantype), "%s: "\
"wrong library function for type %s"\
%(lib,plantype))
def testWisdom(self):
i=0
for lib in libs:
lib.forget_wisdom()
inputa = lib.create_aligned_array(1024,np.typeDict[_complex[i]])
outputa = lib.create_aligned_array(1024,np.typeDict[_complex[i]])
plan = lib.Plan(inputa,outputa,flags=['patient'])
soriginal = lib.export_wisdom_to_string()
lib.import_wisdom_from_string(soriginal)
lib.export_wisdom_to_file('test.wisdom')
lib.forget_wisdom()
lib.import_wisdom_from_file('test.wisdom')
os.remove('test.wisdom')
del inputa
del outputa
i+=1
def testPropagation(self):
#can only test for fftw3 because longdouble and single are not both implemented for scipy.fft and numpy.fft
Ns = [2**i for i in range(10,15)]
repeats = 2000
epsilon = 1e-3
times = []
for Nn in Ns:
t,A,f,B, ti = fftw_propagation(Nn,repeats, fftw3, _complex[0])
ft,fA,ff,fB, fti = fftw_propagation_aligned(Nn,repeats, fftw3, _complex[0])
nt,nA, nf, nB, nti = np_propagation(Nn,repeats, _complex[0])
st,sA, sf, sB, sti = scipy_propagation(Nn,repeats, _complex[0])
times.append((ti, fti,nti, sti))
self.failUnless(sum(abs(A)**2-abs(nA)**2)< epsilon, "Propagation "\
"of fftw3 and numpy gives "\
"different results")
self.failUnless(sum(abs(fA)**2-abs(nA)**2)< epsilon, "Propagation "\
"of aligned fftw3 and numpy gives "\
"different results")
print "Benchmark: %s" %fftw3
print "N fftw3 fftw3_aligned numpy scipy"
for i in range(len(Ns)):
print "%5d %5.2f %5.2f %5.2f %5.2f" %(Ns[i],\
times[i][0],\
times[i][1], \
times[i][2], \
times[i][3])
def test2D(self):
try:
from pylab import imread
except:
return
im = imread('Fourier2.png')
im = im[:,:,1]
a = np.zeros(im.shape, dtype=im.dtype)
a[:] = im[:]
b = np.zeros((im.shape[0],im.shape[1]/2+1),dtype=np.typeDict['singlecomplex'])
p = fftw3f.Plan(a,b,'forward')
ip = fftw3f.Plan(b,a,'backward')
p()
b/=np.prod(a.shape)
ip()
self.failUnless(a.sum()-im.sum() < epsilon, "2D fft and ifft did not "\
"reproduce the same image")
if __name__ == '__main__': unittest.main()
python-fftw_0.2.2/test/test_fftw3_threads.py 0000644 0001750 0001750 00000002001 11377456473 020553 0 ustar jerome jerome import sys
sys.path.append('../build/lib')
sys.path.append('../build/lib.linux-x86_64-2.6')
import unittest
import time
import fftw3f
import numpy as np
import fftw3f.lib
import fftw3f.planning
import os
MAX_THREADS = 10
class ProductTestCase(unittest.TestCase):
def test3D(self):
repeats = 10
shape = (256, 256, 16)
lib = fftw3f
tarray = np.random.random(shape).astype('f')
farray = np.random.random(shape).astype('F')
l = []
for nthreads in range(1,MAX_THREADS):
fftplan = lib.Plan(tarray,farray,'forward', nthreads=nthreads)
ifftplan = lib.Plan(farray,tarray,'backward', nthreads=nthreads)
ti = time.time()
for i in xrange(repeats):
fftplan()
ifftplan()
to = time.time()-ti
print '#threads:%s timing:%.3f speedup:%.3f'\
% (nthreads, to, l[0]/to if l else 1)
l.append(to)
if __name__ == '__main__':
unittest.main()
python-fftw_0.2.2/README.txt 0000644 0001750 0001750 00000012034 11335670520 015106 0 ustar jerome jerome PyFFTW-0.2
PyFFTW are python bindings for the FFTW3 (fastest Fourier transform in the West)
C-library written in python ctypes.
Requirements:
a shared library version of libfftw3 and the python numpy package.
Install:
To install the package type "python setup.py install" inside a terminal.
The buildscript automatically detects if the single precision and longdouble
precision versions of the fftw3 library are installed and creates the
appropriate python modules. The modules are called fftw3, fftw3f and
fftw3l for the double, single and longdouble precision versions of the
library respectively. You can specify the location of the fftw3 libraries using
a FFTW_PATH environment variable, the location from this variable is however
overridden if the install script finds the location differently. However the
variable can also be used at runtime, when it will override the location of the
found library. Currently there's no support for having the ffw3l, fftw3f and
fftw3 C-libraries in different directories.
Usage:
In order to use PyFFTW you should have a basic understanding of the
FFTW3 interface. For documentation about FFTW3 go to http://www.fftw.org
In order to achieve maximum performance FFTW3 requires a planning stage
where the actual FFT is created from an input and output array.
To perform the FFT between the input and output array the plan is then
executed. This interface is therefore significantly different from the
traditional A = fft(B) interface.
In contrast to the C-library PyFFTW utilizes the Plan class for planning.
To create a fftw plan one creates a Plan object using an input and output
array, and possible parameters. PyFFTW determines from the input and output
arrays the correct plan to create. To perform the FFT one can either
call the Plan directly or call the method execute() or pass the plan
to the execute function.
Example:
#create arrays
inputa = numpy.zeros((1024,3), dtype=complex)
outputa = numpy.zeros((1024,3), dtype=complex)
# create a forward and backward fft plan
fft = fftw3.Plan(inputa,outputa, direction='forward', flags=['measure'])
ifft = fftw3.Plan(outputa, inputa, direction='backward', flags=['measure'])
#initialize the input array
inputa[:] = 0
inputa += exp(-x**2/2)
#perform a forward transformation
fft() # alternatively fft.execute() or fftw.execute(fft)
# do some calculations with the output array
outputa *= D
#perform a backward transformation
ifft()
The planning functions expect aligned, contiguous input arrays of any shape.
Currently strides are not implemented. The dtype has to either be complex
or double. If you want to perform ffts on single or longdouble precision
arrays use the appropriate fftw3f or fftw3l module. FFTW overwrites the
arrays in the planning process, thus, if you use planning strategies
other than 'estimate' the arrays are going to be overwritten and have to
be reinitialized.
!IMPORTANT!
Because the plan uses pointers to the data of the arrays you cannot perform
operations on the arrays that change the data pointer. Therefore
a = zeros(1024, dtype=complex)
p = plan(a,b)
a = a+10
p()
does not work, i.e. the a object references different memory, however the
Fourier transform will be performed on the original memory (the plan actually
contains a reference to the orgininal data (p.inarray), otherwise this
operation could even result in a python segfault).
Aligned memory:
On many platforms using the SIMD units for part of the floating point
arithmetic significantly improves performance. FFTW can make use of the
SIMD operations, however the arrays have to be specifically aligned in memory.
PyFFTW provides a function which creates an numpy array which is aligned to
a specified boundary. In most circumstances the default alignment to 16 byte boundary is what you want. Note that the same precautions as above apply,
i.e. creating an aligned array and then doing something like a=a+1 will
result in new memory allocated by python which might not be aligned.
PyFFTW interface naming conventions:
All exposed fftw-functions do have the same names as the C-functions with the
leading fftw_ striped from the name.
Direct access to the C-functions is available by importing lib.lib, the usual
precautions for using C-functions from Python apply.
Advanced and Guru interface:
Currently only the execute_dft function from the fftw guru and advanced
interface is exposed.
It is explicitly name guru_execute_dft. You should only use
these if you know what you're doing, as no checking is done on these functions.
Threads:
It is possible to specify the number of threads to use for the fft functions,
by supplying the keyword nthreads to the Plan-Class. Note that your arrays
have to be sufficiently large to yield a speedup on multicore hardware. In
the case of small arrays the overhead for creating the threads is too large
resulting in slower execution times. You should therefore run some test.
Thanks:
Finally I would like to the Matteo Frigo and Stephen G. Johnson for creating
the outstanding fftw3 library. I also would like to thank Pearu Peterson for
writing the threading support.
python-fftw_0.2.2/src/ 0000755 0001750 0001750 00000000000 11667604566 014216 5 ustar jerome jerome python-fftw_0.2.2/src/templates/ 0000755 0001750 0001750 00000000000 11667604566 016214 5 ustar jerome jerome python-fftw_0.2.2/src/templates/planning.tmpl.py 0000644 0001750 0001750 00000042172 11547460203 021336 0 ustar jerome jerome # This file is part of PyFFTW.
#
# Copyright (C) 2009 Jochen Schroeder
# Email: jschrod@berlios.de
#
# PyFFTW 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 3 of the License, or
# (at your option) any later version.
#
# PyFFTW 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 PyFFTW. If not, see .
import numpy as np
from numpy import typeDict
from lib import lib, _typelist, PyFile_AsFile, PyBuffer_FromReadWriteMemory, lib_threads
from ctypes import byref, c_double, c_int
fftw_flags = {'measure':0,
'destroy input': 1,
'unaligned': 2,
'conserve memory':4,
'exhaustive':8,
'preserve input': 16,
'patient': 32,
'estimate': 64}
realfft_type = {'halfcomplex r2c':0,
'halfcomplex c2r':1,
'discrete hartley':2,
'realeven 00':3,
'realeven 01':4,
'realeven 10':5,
'realeven 11':6,
'realodd 00':7,
'realodd 01':8,
'realodd 10':9,
'realodd 11':10}
fft_direction = {'forward' : -1, 'backward': 1}
def create_aligned_array(shape, dtype=typeDict['$complex$'], boundary=16):
"""Create an array which is aligned in memory
Parameters:
shape -- the shape of the array
dtype -- the dtype of the array (default=typeDict['$complex$'])
boundary -- the byte boundary to align to (default=16)
"""
N = np.prod(shape)*np.array(1,dtype).nbytes
tmp = np.zeros(N+boundary, dtype=np.uint8)
address = tmp.__array_interface__['data'][0]
offset = (boundary - address % boundary)
return tmp [offset:offset + N].view(dtype=dtype).reshape(shape)
def execute(plan):
"""Execute fftw-plan, i.e. perform Fourier transform on the arrays given
when the plan was created"""
lib.$libname$_execute(plan)
def guru_execute_dft(plan, inarray, outarray):
"""Guru interface: perform Fourier transform on two arrays,
outarray=fft(inarray) using the given plan. Important: This function
does not perform any checks on the array shape and alignment for
performance reasons. It is therefore crucial to only provide arrays
with the same shape, dtype and alignment as the arrays used for planning,
failure to do so can lead to unexpected behaviour and even python
segfaulting.
"""
lib.$libname$_execute_dft(plan, inarray, outarray)
def destroy_plan(plan):
"""Delete the given plan"""
if isinstance(plan,Plan):
del plan
else:
lib.$libname$_destroy_plan(plan)
def select(inarray,outarray):
"""From a given input and output np array select the appropriate
fftw3 plan to create."""
if inarray.shape != outarray.shape:
if inarray.dtype == outarray.dtype:
raise TypeError, "Input array and output array must have the same "\
"shape if they have the same dtype"
elif inarray.dtype == typeDict['$complex$'] and outarray.dtype == typeDict['$float$']:
inshape = list(outarray.shape)
inshape[-1] = inshape[-1]/2 + 1
if inarray.shape != tuple(inshape):
raise TypeError, "For complex to real transforms the complex "\
"array must be of shape (n1 x n2 x...x "\
"(n-1)/2 +1"
elif inarray.dtype == typeDict['$float$'] and outarray.dtype == typeDict['$complex$']:
outshape = list(inarray.shape)
outshape[-1] = outshape[-1]/2 + 1
if outarray.shape != tuple(outshape):
raise TypeError, "For real to complex transforms the complex "\
"array must be of shape (n1 x n2 x...x "\
"(n-1)/2 +1"
if inarray.dtype != typeDict['$float$'] and inarray.dtype != typeDict['$complex$']:
raise TypeError, "Input array has to be either floating point or"\
" complex"
elif outarray.dtype != typeDict['$float$'] and outarray.dtype != typeDict['$complex$']:
raise TypeError, "Output array has to be either floating point "\
"or complex"
i = 0
while(i < len(_typelist)):
name, types = _typelist[i]
if inarray.dtype != types[0]:
i += 8
continue
elif outarray.dtype != types[1]:
i += 4
continue
elif i in [3,7,11,15]:
return getattr(lib, name), name, types
elif len(inarray.shape) != types[2]:
i += 1
continue
else:
return getattr(lib, name), name, types
def _create_complex2real_plan(inarray, outarray, flags):
"""Internal function to create complex fft plan given an input and output
np array and the direction and flags integers"""
func, name, types = select(inarray,outarray)
#this is necessary because the r2c and c2r transforms always use the
#shape of the larger array (the real one)
if np.prod(inarray.shape) < np.prod(outarray.shape):
shape = outarray.shape
else:
shape = inarray.shape
if len(types) < 3:
plan = func(len(shape), np.asarray(shape, dtype=c_int),
inarray, outarray, flags)
if plan is None:
raise Exception, "Error creating $libname$ plan %s for the given "\
"parameters" %name
else:
return plan, name
elif types[2] == 1:
plan = func(shape[0], inarray, outarray, flags)
if plan is None:
raise Exception, "Error creating $libname$ plan %s for the given "\
"parameters" %name
else:
return plan, name
elif types[2] == 2:
plan = func(shape[0], shape[1], inarray, outarray, flags)
if plan is None:
raise Exception, "Error creating $libname$ plan %s for the given "\
"parameters" %name
else:
return plan, name
elif types[2] == 3:
plan = func(shape[0], shape[1], shape[2],inarray, outarray, flags)
if plan is None:
raise Exception, "Error creating $libname$ plan %s for the given "\
"parameters" %name
else:
return plan, name
else:
raise ValueError, 'the dimensions are not correct'
def _create_complex_plan(inarray, outarray, direction, flags):
"""Internal function to create complex fft plan given an input and output
np array and the direction and flags integers"""
func, name, types = select(inarray,outarray)
#this is necessary because the r2c and c2r transforms always use the
#shape of the larger array (the real one)
if np.prod(inarray.shape) < np.prod(outarray.shape):
shape = outarray.shape
else:
shape = inarray.shape
if len(types) < 3:
plan = func(len(shape),
np.asarray(shape, dtype=c_int),
inarray, outarray, direction, flags)
if plan is None:
raise Exception, "Error creating $libname$ plan %s for the given "\
"parameters" %name
else:
return plan, name
elif types[2] == 1:
plan = func(shape[0], inarray, outarray, direction, flags)
if plan is None:
raise Exception, "Error creating $libname$ plan %s for the given "\
"parameters" %name
else:
return plan, name
elif types[2] == 2:
plan = func(shape[0], shape[1], inarray, outarray,\
direction, flags)
if plan is None:
raise Exception, "Error creating $libname$ plan %s for the given "\
"parameters" %name
else:
return plan, name
elif types[2] == 3:
plan = func(shape[0], shape[1], shape[2],\
inarray, outarray, direction, flags)
if plan is None:
raise Exception, "Error creating $libname$ plan %s for the given "\
"parameters" %name
else:
return plan, name
else:
raise ValueError, 'the dimensions are not correct'
def _create_real_plan(inarray, outarray, realtype, flags):
"""Internal function to create real fft plan given an input and output
np array and the realtype and flags integers"""
if realtype == None:
raise ValueError, "Two real input arrays but no realtype list given"
func, name, types = select(inarray,outarray)
if len(types) < 3:
plan = func(len(inarray.shape), np.asarray(inarray.shape,dtype=c_int),\
inarray, outarray, np.asarray(realtype), flags)
if plan is None:
raise Exception, "Error creating $libname$ plan %s for the given "\
"parameters" %name
else:
return plan, name
elif types[2] == 1:
plan = func(inarray.shape[0], inarray, outarray, realtype[0], flags)
if plan is None:
raise Exception, "Error creating $libname$ plan %s for the given "\
"parameters" %name
else:
return plan, name
elif types[2] == 2:
plan = func(inarray.shape[0], inarray.shape[1], inarray, outarray,\
realtype[0], realtype[1], flags)
if plan is None:
raise Exception, "Error creating $libname$ plan %s for the given "\
"parameters" %name
else:
return plan, name
elif types[2] == 3:
plan = func(inarray.shape[0], inarray.shape[1],inarray.shape[2], \
inarray, outarray, realtype[0], realtype[1], \
realtype[2], flags)
if plan is None:
raise Exception, "Error creating $libname$ plan %s for the given "\
"parameters" %name
else:
return plan, name
else:
raise ValueError, 'the dimensions are not correct'
def _create_plan(inarray, outarray, direction='forward', flags=['estimate'],
realtypes=None, nthreads=1):
"""Internal function to create a complex fft plan given an input and output
np array and the direction and flags integers"""
if lib_threads is not None:
lib_threads.$libname$_plan_with_nthreads(nthreads)
elif nthreads > 1:
raise ValueError, "Cannot use more than 1 thread for non-threaded $libname$: %s" % (nthreads)
if inarray.dtype == np.typeDict['$complex$'] and \
outarray.dtype == np.typeDict['$complex$']:
return _create_complex_plan(inarray,outarray, fft_direction[direction],
_cal_flag_value(flags))
elif inarray.dtype == np.typeDict['$complex$'] or \
outarray.dtype == np.typeDict['$complex$']:
return _create_complex2real_plan(inarray,outarray,
_cal_flag_value(flags))
elif inarray.dtype == np.typeDict['$float$'] and \
outarray.dtype == np.typeDict['$float$']:
return _create_real_plan(inarray,outarray, \
[realfft_type[r] for r in realtypes],\
_cal_flag_value(flags))
else:
raise TypeError, "The input or output array has a dtype which is not supported by $libname$: %r, %r"\
% (inarray.dtype, outarray.dtype)
def _cal_flag_value(flags):
"""Calculate the integer flag value from a list of string flags"""
ret = 0
for f in flags:
ret += fftw_flags[f]
return ret
def print_plan(plan):
"""Print a nerd-readable version of the plan to stdout"""
lib.$libname$_print_plan(plan)
def fprint_plan(plan, filename):
"""Print a nerd-readable version of the plan to the given filename"""
fp = open(filename, 'w')
c_fp = PyFile_AsFile(fp)
lib.$libname$_fprint_plan(plan, c_fp)
fp.close()
class Plan(object):
"""Object representing a fftw plan used to execute Fourier transforms in
fftw
Attributes:
shape -- the shape of the input and output arrays, i.e. the FFT
flags -- a list of the fft flags used in the planning
direction -- the direction of the FFT
ndim -- the dimensionality of the FFT
inarray -- the input array
outarray -- the output array
"""
def __init__(self, inarray=None, outarray=None, direction='forward',
flags=['estimate'], realtypes=None, create_plan=True,
nthreads = 1):
"""Initialize the fftw plan.
Parameters:
inarray -- array to be transformed (default=None)
outarray -- array to contain the Fourier transform
(default=None)
If one of the arrays is None, the fft is considered to be
an inplace transform.
direction -- direction of the Fourier transform, forward
or backward (default='forward')
flags -- list of fftw-flags to be used in planning
(default=['estimate'])
realtypes -- list of fft-types for real-to-real ffts, this
needs to be given if both input and output
arrays are real (default=None)
create_plan -- weather to actually create the plan (default=True)
nthreads -- number of threads to be used by the plan,
available only for threaded libraries (default=1)
"""
self.flags = flags
self.direction = direction
self.realtypes = realtypes
self.nthreads = nthreads
if create_plan:
if inarray is None and outarray is None:
raise 'Need at least one array to create the plan'
elif outarray is None:
self.create_plan(inarray,inarray)
elif inarray is None:
self.create_plan(outarray,outarray)
else:
self.create_plan(inarray,outarray)
def __set_shape(self,shape):
if len(shape)==1:
self.ndim = 1
self.N = tuple(shape)
elif len(shape) > 1:
self.ndim = len(shape)
self.N = tuple(shape)
else:
raise ValueError, 'shape must be at least one dimensional'
def __get_shape(self):
return self.N
shape = property(__get_shape, __set_shape)
def create_plan(self, inarray, outarray):
"""Create the actual fftw-plan from inarray and outarray"""
self.plan, self.type_plan = _create_plan(inarray,outarray,
direction=self.direction,
flags=self.flags,
realtypes=self.realtypes,
nthreads=self.nthreads)
self.shape = inarray.shape
self.inarray = inarray
self.outarray = outarray
def _get_parameter(self):
return self.plan
_as_parameter_ = property(_get_parameter)
def __call__(self):
"""Perform the Fourier transform outarray = fft(inarray) for
the arrays given at plan creation"""
self.execute()
def execute(self):
"""Execute the fftw plan, i.e. perform the FFT outarray = fft(inarray)
for the arrays given at plan creation"""
execute(self)
def __del__(self):
destroy_plan(self)
def guru_execute_dft(self,inarray,outarray):
"""Guru interface: perform Fourier transform on two given arrays,
outarray=fft(inarray). Important: This method does not perform any
checks on the array shape and alignment for performance reasons. It is
therefore crucial to only provide arrays with the same shape, dtype and
alignment as the arrays used for planning, failure to do so can lead to
unexpected behaviour and possibly python segfaulting
"""
guru_execute_dft(self,inarray,outarray)
def get_flops(self):
"""Return an exact count of the number of floating-point additions,
multiplications, and fused multiply-add operations involved in
the plan's execution. The total number of floating-point
operations (flops) is add + mul + 2*fma, or add + mul + fma if
the hardware supports fused multiply-add instructions
(although the number of FMA operations is only approximate
because of compiler voodoo).
"""
add = c_double(0)
mul = c_double(0)
fma = c_double(0)
lib.$libname$_flops(self, byref (add), byref (mul), byref (fma))
return add.value, mul.value, fma.value
python-fftw_0.2.2/src/templates/__init__.py 0000644 0001750 0001750 00000013527 11335634621 020320 0 ustar jerome jerome # This file is part of PyFFTW.
#
# Copyright (C) 2009 Jochen Schroeder
# Email: jschrod@berlios.de
#
# PyFFTW 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 3 of the License, or
# (at your option) any later version.
#
# PyFFTW 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 PyFFTW. If not, see .
"""
Python bindings to the FFTW library.
Usage:
In order to use PyFFTW you should have a basic understanding of the
FFTW3 interface. For documentation about FFTW3 go to http://www.fftw.org
In order to achieve maximum performance FFTW3 requires a planning stage
where the actual FFT is created from an input and output array.
To perform the FFT between the input and output array the plan is then
executed. This interface is therefore significantly different from the
traditional A = fft(B) interface.
In contrast to the C-library PyFFTW utilizes the Plan class for planning.
To create a fftw plan one creates a Plan object using an input and output
array, and possible parameters. PyFFTW determines from the input and output
arrays the correct plan to create. To perform the FFT one can either
call the Plan directly or call the method execute() or pass the plan
to the execute function.
Example:
--------
#create arrays
>>>inputa = numpy.zeros((1024,3), dtype=complex)
>>>outputa = numpy.zeros((1024,3), dtype=complex)
# create a forward and backward fft plan
>>>fft = fftw3.Plan(inputa,outputa, direction='forward', flags=['measure'])
>>>ifft = fftw3.Plan(outputa, inputa, direction='backward', flags=['measure'])
#initialize the input array
>>>inputa[:] = 0
>>>inputa += exp(-x**2/2)
#perform a forward transformation
>>>fft() # alternatively fft.execute() or fftw.execute(fft)
# do some calculations with the output array
>>>outputa *= D
#perform a backward transformation
>>>ifft()
The planning functions expect aligned, contiguous input arrays of
any shape.
Currently strides are not implemented. The dtype has to either be complex
or double. If you want to perform ffts on single or longdouble precision
arrays use the appropriate fftw3f or fftw3l module. FFTW overwrites the
arrays in the planning process, thus, if you use planning strategies
other than 'estimate' the arrays are going to be overwritten and have to
be reinitialized.
*IMPORTANT*
-----------
Because the plan uses pointers to the data of the arrays you cannot
perform operations on the arrays that change the data pointer. Therefore
>>>a = zeros(1024, dtype=complex)
>>>p = plan(a,b)
>>>a = a+10
>>>p()
does not work, i.e. the a object references different memory, however
the Fourier transform will be performed on the original memory (the
plan actually contains a reference to the orgininal data (p.inarray),
otherwise this operation could even result in a python segfault).
Aligned memory:
---------------
On many platforms using the SIMD units for part of the floating point
arithmetic significantly improves performance. FFTW can make use of the
SIMD operations, however the arrays have to be specifically aligned
in memory. PyFFTW provides a function which creates an numpy array
which is aligned to
a specified boundary. In most circumstances the default alignment to 16
byte boundary is what you want. Note that the same precautions as above
apply, i.e. creating an aligned array and then doing something like
a=a+1 will result in new memory allocated by python which might not
be aligned.
PyFFTW interface naming conventions:
------------------------------------
All exposed fftw-functions do have the same names as the C-functions with the
leading fftw_ striped from the name.
Direct access to the C-functions is available by importing lib.lib, the usual
precautions for using C-functions from Python apply.
Advanced and Guru interface:
----------------------------
Currently only the execute_dft function from the fftw guru and advanced
interface is exposed.
It is explicitly name guru_execute_dft. You should only use
these if you know what you're doing, as no checking is done on these functions.
Constants:
fftw_flags -- dictionary of possible flags for creating plans
fft_direction -- the direction of the fft (see the fftw documentation
for the mathematical meaning).
realfft_type -- a dictionary of possible types for real-to-real
transforms (see the fftw documentation for a
more detailed description).
"""
__all__ = ["export_wisdom_to_file", "export_wisdom_to_string",
"import_wisdom_from_string", "import_wisdom_from_file",
"import_system_wisdom", "forget_wisdom", "AlignedArray",
"create_aligned_array", "execute", "guru_execute_dft",
"destroy_plan", "Plan", "fftw_flags", "fft_direction",
"realfft_type"]
from wisdom import export_wisdom_to_file, export_wisdom_to_string,\
import_wisdom_from_string, import_wisdom_from_file, \
import_system_wisdom, forget_wisdom
from planning import create_aligned_array,\
execute, guru_execute_dft, destroy_plan,\
Plan, fftw_flags, fft_direction, realfft_type, \
print_plan, fprint_plan
python-fftw_0.2.2/src/templates/wisdom.tmpl.py 0000644 0001750 0001750 00000004103 11335634621 021024 0 ustar jerome jerome # This file is part of PyFFTW.
#
# Copyright (C) 2009 Jochen Schroeder
# Email: jschrod@berlios.de
#
# PyFFTW 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 3 of the License, or
# (at your option) any later version.
#
# PyFFTW 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 PyFFTW. If not, see .
from lib import lib, PyFile_AsFile
def export_wisdom_to_file(filename):
"""Export accumulated wisdom to file given by the filename"""
fp = open(filename, 'a')
c_fp = PyFile_AsFile(fp)
lib.$libname$_export_wisdom_to_file(c_fp)
fp.close()
def export_wisdom_to_string():
"""Returns a string with the accumulated wisdom"""
return lib.$libname$_export_wisdom_to_string()
def import_wisdom_from_file(filename):
"""Imports wisdom from the file given by the filename"""
fp = open(filename,'r')
c_fp = PyFile_AsFile(fp)
if lib.$libname$_import_wisdom_from_file(c_fp):
pass
else:
raise IOError, "Could not read wisdom from file %s" % filename
def import_wisdom_from_string(wisdom):
"""Import wisdom from the given string"""
if lib.$libname$_import_wisdom_from_string(wisdom):
pass
else:
raise Exception, "Could not read wisdom from string: %s" % wisdom
def import_system_wisdom():
"""Import the system wisdom, this lives under /etc/fftw/wisdom on
Unix/Linux systems"""
if lib.$libname$_import_system_wisdom():
pass
else:
raise IOError, "Could not read system wisdom. On GNU/Linux and Unix "\
"system wisdom is located in /etc/fftw/wisdom"
def forget_wisdom():
"""Clear all wisdom"""
lib.$libname$_forget_wisdom()
python-fftw_0.2.2/src/templates/lib.tmpl.py 0000644 0001750 0001750 00000040274 11547507650 020307 0 ustar jerome jerome # This file is part of PyFFTW.
#
# Copyright (C) 2009 Jochen Schroeder
# Email: jschrod@berlios.de
#
# PyFFTW 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 3 of the License, or
# (at your option) any later version.
#
# PyFFTW 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 PyFFTW. If not, see .
import ctypes
from ctypes import pythonapi, util, py_object
from numpy import ctypeslib, typeDict
from platform import system as psystem
from os.path import splitext, join, isfile, dirname, abspath, basename
from os.path import join as joinpath
from os import name as osname
from os import environ
from warnings import warn
try:
fftw_path = environ['FFTW_PATH']
libfullpath = joinpath(abspath(fftw_path),r'$library$')
if not isfile(libfullpath):
raise IOError
except KeyError:
libfullpath = r'$libraryfullpath$'
except IOError:
warn('could not find %s in FFTW_PATH using installtime path'
%'$library$')
libfullpath = r'$libraryfullpath$'
if not isfile(libfullpath) and (osname=='nt' or psystem=='Windows'):
if isfile(joinpath(dirname(__file__), libfullpath)):
libfullpath = joinpath(dirname(__file__), libfullpath)
# must use ctypes.RTLD_GLOBAL for threading support
ctypes._dlopen(libfullpath, ctypes.RTLD_GLOBAL)
lib = ctypes.cdll.LoadLibrary(libfullpath)
#check if library is actually loaded there doesn't seem to be a better way to
#do this in ctypes
if not hasattr(lib, '$libname$_plan_dft_1d'):
raise OSError('Could not load $library$')
if osname == 'nt' or psystem() == 'Windows':
lib_threads = lib
else:
libbase, dot, ext = basename(libfullpath).partition('.')
libdir = dirname(libfullpath)
lib_threads = joinpath(libdir, libbase + '_threads.'+ ext)
try:
lib_threads = ctypes.cdll.LoadLibrary(lib_threads)
except OSError, e:
warn("Could not load threading library %s, threading support is disabled"
%lib_threads)
lib_threads = None
_typelist = [('$libname$_plan_dft_1d', (typeDict['$complex$'], typeDict['$complex$'], 1)),
('$libname$_plan_dft_2d', (typeDict['$complex$'], typeDict['$complex$'], 2)),
('$libname$_plan_dft_3d', (typeDict['$complex$'], typeDict['$complex$'], 3)),
('$libname$_plan_dft', (typeDict['$complex$'], typeDict['$complex$'])),
('$libname$_plan_dft_c2r_1d', (typeDict['$complex$'], typeDict['$float$'], 1)),
('$libname$_plan_dft_c2r_2d', (typeDict['$complex$'], typeDict['$float$'], 2)),
('$libname$_plan_dft_c2r_3d', (typeDict['$complex$'], typeDict['$float$'], 3)),
('$libname$_plan_dft_c2r', (typeDict['$complex$'], typeDict['$float$'])),
('$libname$_plan_dft_r2c_1d', (typeDict['$float$'], typeDict['$complex$'], 1)),
('$libname$_plan_dft_r2c_2d', (typeDict['$float$'], typeDict['$complex$'], 2)),
('$libname$_plan_dft_r2c_3d', (typeDict['$float$'], typeDict['$complex$'], 3)),
('$libname$_plan_dft_r2c', (typeDict['$float$'], typeDict['$complex$'])),
('$libname$_plan_r2r_1d', (typeDict['$float$'], typeDict['$float$'], 1)),
('$libname$_plan_r2r_2d', (typeDict['$float$'], typeDict['$float$'], 2)),
('$libname$_plan_r2r_3d', (typeDict['$float$'], typeDict['$float$'], 3)),
('$libname$_plan_r2r', (typeDict['$float$'], typeDict['$float$']))]
_adv_typelist = [('$libname$_plan_many_dft', (typeDict['$complex$'],
typeDict['$complex$'])),
('$libname$_plan_many_dft_c2r', (typeDict['$complex$'],
typeDict['$float$'])),
('$libname$_plan_many_dft_r2c', (typeDict['$float$'],
typeDict['$complex$'])),
('$libname$_plan_many_r2r', (typeDict['$float$'],
typeDict['$float$']))]
def set_argtypes(val, types):
if types[0] == typeDict['$complex$'] and types[1] == typeDict['$complex$']:
set_argtypes_c2c(val,types)
elif types[0] == typeDict['$complex$'] or types[1] == typeDict['$complex$']:
set_argtypes_c2r(val,types)
else:
set_argtypes_r2r(val,types)
def set_argtypes_c2c(val,types):
if len(types) >2:
val.argtypes = [ctypes.c_int for i in range(types[2])] +\
[ctypeslib.ndpointer(dtype=types[0],ndim=types[2], \
flags='contiguous, writeable, '\
'aligned'),
ctypeslib.ndpointer(dtype=types[1], ndim=types[2],\
flags='contiguous, writeable, '\
'aligned'),
ctypes.c_int, ctypes.c_uint]
else:
val.argtypes = [ctypes.c_int, ctypeslib.ndpointer(dtype=ctypes.c_int,
ndim=1,\
flags='contiguous, '\
'aligned'),
ctypeslib.ndpointer(dtype=types[0], flags='contiguous,'\
' writeable, '\
'aligned'),
ctypeslib.ndpointer(dtype=types[1],flags='contiguous, '\
'writeable,'\
'aligned'),
ctypes.c_int, ctypes.c_uint]
def set_argtypes_c2r(val,types):
if len(types) >2:
val.argtypes = [ctypes.c_int for i in range(types[2])] +\
[ctypeslib.ndpointer(dtype=types[0],ndim=types[2], \
flags='contiguous, writeable, '\
'aligned'),
ctypeslib.ndpointer(dtype=types[1], ndim=types[2],\
flags='contiguous, writeable, '\
'aligned'),
ctypes.c_uint]
else:
val.argtypes = [ctypes.c_int, ctypeslib.ndpointer(dtype=ctypes.c_int,
ndim=1,\
flags='contiguous, '\
'aligned'),
ctypeslib.ndpointer(dtype=types[0], flags='contiguous,'\
' writeable, '\
'aligned'),
ctypeslib.ndpointer(dtype=types[1],flags='contiguous, '\
'writeable,'\
'aligned'),
ctypes.c_uint]
def set_argtypes_r2r(val, types):
if len(types) > 2:
val.argtypes = [ctypes.c_int for i in range(types[2])] +\
[ctypeslib.ndpointer(dtype=types[0], ndim=types[2],
flags='contiguous, writeable, '\
'aligned'),
ctypeslib.ndpointer(dtype=types[1], ndim=types[2],
flags='contiguous, writeable, '\
'aligned')] +\
[ctypes.c_int for i in range(types[2])] +\
[ctypes.c_uint]
else:
val.argtypes = [ctypes.c_int, ctypeslib.ndpointer(dtype=ctypes.c_int,
ndim=1,
flags='contiguous, '\
'aligned'),
ctypeslib.ndpointer(dtype=types[0], flags='contiguous,'\
'writeable, '\
'aligned'),
ctypeslib.ndpointer(dtype=types[1], flags='contiguous,'\
'writeable, '\
'aligned'),
ctypeslib.ndpointer(dtype=ctypes.c_int, ndim=1,
flags='contiguous, aligned'),
ctypes.c_uint]
def set_argtypes_adv(val, types):
if types[0] == typeDict['$complex$'] and types[1] == typeDict['$complex$']:
val.argtypes = [ctypes.c_int, ctypeslib.ndpointer(dtype=ctypes.c_int,
ndim=1,
flags='contiguous, '\
'aligned'),
ctypes.c_int,
ctypeslib.ndpointer(dtype=types[0], flags='contiguous,'\
'aligned,'\
'writeable'),
ctypeslib.ndpointer(dtype=ctypes.c_int, ndim=1,
flags='contiguous,aligned'),
ctypes.c_int, ctypes.c_int,
ctypeslib.ndpointer(dtype=types[1], flags='contiguous,'\
'aligned,'\
'writeable'),
ctypeslib.ndpointer(dtype=ctypes.c_int, ndim=1,
flags='contiguous,aligned'),
ctypes.c_int, ctypes.c_int,
ctypes.c_int, ctypes.c_uint]
elif types[0] == typeDict['$complex$'] or types[1]==typeDict['$complex$']:
val.argtypes = [ctypes.c_int, ctypeslib.ndpointer(dtype=ctypes.c_int,
ndim=1,
flags='contiguous, '\
'aligned'),
ctypes.c_int,
ctypeslib.ndpointer(dtype=types[0], flags='contiguous,'\
'aligned,'\
'writeable'),
ctypeslib.ndpointer(dtype=ctypes.c_int, ndim=1,
flags='contiguous,aligned'),
ctypes.c_int, ctypes.c_int,
ctypeslib.ndpointer(dtype=types[1], flags='contiguous,'\
'aligned,'\
'writeable'),
ctypeslib.ndpointer(dtype=ctypes.c_int, ndim=1,
flags='contiguous,aligned'),
ctypes.c_int, ctypes.c_int,
ctypes.c_uint]
elif types[0] == typeDict['$float$'] and types[1]==typeDict['$float$']:
val.argtypes = [ctypes.c_int, ctypeslib.ndpointer(dtype=ctypes.c_int,
ndim=1,
flags='contiguous, '\
'aligned'),
ctypes.c_int,
ctypeslib.ndpointer(dtype=types[0], flags='contiguous,'\
'aligned,'\
'writeable'),
ctypeslib.ndpointer(dtype=ctypes.c_int, ndim=1,
flags='contiguous,aligned'),
ctypes.c_int, ctypes.c_int,
ctypeslib.ndpointer(dtype=types[1], flags='contiguous,'\
'aligned,'\
'writeable'),
ctypeslib.ndpointer(dtype=ctypes.c_int, ndim=1,
flags='contiguous, aligned'),
ctypes.c_int, ctypes.c_int,
ctypeslib.ndpointer(dtype=ctypes.c_int, ndim=1,
flags='contiguous, aligned'),
ctypes.c_uint]
# set the return and argument types on the plan functions
for name, types in _typelist:
val = getattr(lib, name)
val.restype = ctypes.c_void_p
set_argtypes(val,types)
##do the same for advanced plans
for name, types in _adv_typelist:
val = getattr(lib, name)
val.restype = ctypes.c_void_p
set_argtypes_adv(val,types)
#malloc and free
lib.$libname$_malloc.restype = ctypes.c_void_p
lib.$libname$_malloc.argtypes = [ctypes.c_int]
lib.$libname$_free.restype = None
lib.$libname$_free.argtypes = [ctypes.c_void_p]
#create a buffer from memory (necessary for array allocation)
PyBuffer_FromReadWriteMemory = pythonapi.PyBuffer_FromReadWriteMemory
PyBuffer_FromReadWriteMemory.restype = py_object
PyBuffer_FromReadWriteMemory.argtypes = [ctypes.c_void_p, ctypes.c_int]
#executing arrays
lib.$libname$_execute.restype = None
lib.$libname$_execute.argtypes = [ctypes.c_void_p]
#guru execution
lib.$libname$_execute_dft.restype = None
lib.$libname$_execute_dft.argtypes = [ctypes.c_void_p,
ctypeslib.ndpointer(flags='aligned, contiguous, '\
'writeable'),\
ctypeslib.ndpointer(flags='aligned, contiguous, '\
'writeable')]
#destroy plans
lib.$libname$_destroy_plan.restype = None
lib.$libname$_destroy_plan.argtypes = [ctypes.c_void_p]
#enable threading for plans
if lib_threads is not None:
lib_threads.$libname$_init_threads.restype = ctypes.c_int
lib_threads.$libname$_init_threads.argtypes = []
lib_threads.$libname$_plan_with_nthreads.restype = None
lib_threads.$libname$_plan_with_nthreads.argtypes = [ctypes.c_int]
lib_threads.$libname$_cleanup_threads.restype = None
lib_threads.$libname$_cleanup_threads.argtypes = []
s = lib_threads.$libname$_init_threads()
if not s:
sys.stderr.write('$libname$_init_threads call failed, disabling threads support\n')
lib_threads = None
#wisdom
# create c-file object from python
PyFile_AsFile = pythonapi.PyFile_AsFile
PyFile_AsFile.argtypes = [ctypes.py_object]
PyFile_AsFile.restype = ctypes.c_void_p
#export to file
lib.$libname$_export_wisdom_to_file.argtypes = [ctypes.c_void_p]
lib.$libname$_export_wisdom_to_file.restype = None
#export to string
lib.$libname$_export_wisdom_to_string.argtypes = None
lib.$libname$_export_wisdom_to_string.restype = ctypes.c_char_p
#import from file
lib.$libname$_import_wisdom_from_file.argtypes = [ctypes.c_void_p]
lib.$libname$_import_wisdom_from_file.restype = ctypes.c_int
#import from string
lib.$libname$_import_wisdom_from_string.argtypes = [ctypes.c_char_p]
lib.$libname$_import_wisdom_from_string.restype = ctypes.c_int
#import system wisdom
lib.$libname$_import_system_wisdom.restype = ctypes.c_int
lib.$libname$_import_system_wisdom.argtypes = None
#forget wisdom
lib.$libname$_forget_wisdom.restype = None
lib.$libname$_forget_wisdom.argtype = None
python-fftw_0.2.2/AUTHORS 0000644 0001750 0001750 00000000353 11335634621 014463 0 ustar jerome jerome PyFFTW:
Copyright (C) 2009-2010
Jochen Schroeder
Email: cycomanic@gmail.com
Pearu Peterson
Email: pearu.peterson@gmail.com
--
The image of Fourier in the test subdirectory is Public Domain
(as of information from www.wikipedia.org)