pax_global_header00006660000000000000000000000064123431106700014507gustar00rootroot0000000000000052 comment=43d431bf757e62b3745cabe5db8520a57a416b6c python-neuroshare-0.9.2/000077500000000000000000000000001234311067000152115ustar00rootroot00000000000000python-neuroshare-0.9.2/.gitignore000066400000000000000000000001531234311067000172000ustar00rootroot00000000000000*~ *.lock *.DS_Store *.swp *.out *.pyc *.so build/ dist/ *.egg-info doc/build/* *.egg #data files *.mcdpython-neuroshare-0.9.2/.landscape.yaml000066400000000000000000000000641234311067000201050ustar00rootroot00000000000000ignore-paths: - doc - neuroshare/__init__.pypython-neuroshare-0.9.2/.travis.yml000066400000000000000000000003031234311067000173160ustar00rootroot00000000000000language: python virtualenv: system_site_packages: true install: - sudo apt-get install python-numpy python-dev script: - python setup.py install - cd $HOME - python -c "import neuroshare" python-neuroshare-0.9.2/COPYING000066400000000000000000000636201234311067000162530ustar00rootroot00000000000000 GNU LESSER GENERAL PUBLIC LICENSE Version 2.1, February 1999 Copyright (C) 1991, 1999 Free Software Foundation, Inc. 51 Franklin St, Fifth Floor, Boston, MA 02110-1301 USA Everyone is permitted to copy and distribute verbatim copies of this license document, but changing it is not allowed. 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Here is a sample; alter the names: Yoyodyne, Inc., hereby disclaims all copyright interest in the library `Frob' (a library for tweaking knobs) written by James Random Hacker. , 1 April 1990 Ty Coon, President of Vice That's all there is to it!python-neuroshare-0.9.2/README.md000066400000000000000000000015551234311067000164760ustar00rootroot00000000000000Python Bindings for Neuroshare ============================== The aim of this library is to provide a high level interface to the Neuroshare API, a standardized interface to access electrophysiology data stored in various different file formats. For information how to install and use it please refer to the [official documentation](http://pythonhosted.org/neuroshare/) ---- Support and discussion of python-neuroshare related questions happen in the official G-Node IRC channel #gnode on the freenode IRC network (cf. http://freenode.net). - - - [![Build Status](https://travis-ci.org/G-Node/python-neuroshare.png?branch=master)](https://travis-ci.org/G-Node/python-neuroshare) [![PyPI version](https://badge.fury.io/py/neuroshare.png)](http://badge.fury.io/py/neuroshare) [![Downloads](https://pypip.in/d/neuroshare/badge.png)](https://pypi.python.org/pypi/neuroshare) python-neuroshare-0.9.2/capi/000077500000000000000000000000001234311067000161255ustar00rootroot00000000000000python-neuroshare-0.9.2/capi/nsAPIdllimp.h000066400000000000000000000520321234311067000204540ustar00rootroot00000000000000/////////////////////////////////////////////////////////////////////////////////////////////////// // // Copyright (C) 2003 Neuroshare Project // // This library is free software; you can redistribute it and/or // modify it under the terms of the GNU Lesser General Public // License as published by the Free Software Foundation; either // version 2.1 of the License, or (at your option) any later version. // // This library 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 // Lesser General Public License for more details. // // A copy of the GNU Lesser General Public License can be obtained by writing to: // Free Software Foundation, Inc., // 59 Temple Place, Suite 330, // Boston, MA 02111-1307 // USA // // Contact information: // Angela Wang // CyberKinetics, Inc., // 391 G Chipeta Way // Salt Lake City, UT 84108 // USA // angela@bionictech.com // // Website: // www.neuroshare.org // // All other copyrights on this material are replaced by this license agreeement. // /////////////////////////////////////////////////////////////////////////////////////////////////// /* $Workfile: nsAPIdllimp.h $ */ // // File version : 1.0 // // Specification : based on Neuroshare API specification version 1.0 // // Description : This header file contains Neuroshare API function prototype delarations in // pointer form for importing Neuroshare function definitions from a DLL. // The file nsAPIdllimp.c contains C code to declare and load the functions. // // Authors : Shane Guillory, Angela Wang // /* $Date: 2/21/03 12:42p $ */ // /* $History: nsAPIdllimp.h $ // // ***************** Version 9 ***************** // User: Almut Date: 2/21/03 Time: 12:42p // Updated in $/Neuroshare/DLLTester // These headers now conform to Neuroshare API Spec 1.0 // // ***************** Version 1 ***************** // User: Angela Date: 2/21/03 Time: 11:45a // Created in $/Neuroshare/nsNEVLibrary // Version 1.0 Neuroshare Specifications // // ***************** Version 1 ***************** // User: Angela Date: 2/17/03 Time: 11:22a // Created in $/Neuroshare/nsNEVLibrary // Neuroshare API Ver 1.0 compliant header files // // ***************** Version 1 ***************** // User: Angela Date: 2/13/03 Time: 9:29a // Created in $/Neuroshare/nsNEVLibrary * * ***************** Version 8 ***************** * User: Angela Date: 1/14/03 Time: 9:44a * Updated in $/Neuroshare/nsNEVLibrary * * ***************** Version 7 ***************** * User: Angela Date: 1/10/03 Time: 12:15p * Updated in $/Neuroshare/nsNEVLibrary * Reword disclaimer * * ***************** Version 6 ***************** * User: Angela Date: 1/09/03 Time: 12:13p * Updated in $/Neuroshare/nsNEVLibrary * Changed some formatting of headers to look nicer * * ***************** Version 5 ***************** * User: Angela Date: 1/09/03 Time: 11:55a * Updated in $/Neuroshare/nsNEVLibrary * Added file headers, copyright, function headers v0.9b - Functions changed to use __stdcall calling convention for compatibility with Visual Basic. Function prototype declarations also changed to all-capital versions of the neuroshare function names. v0.9b - First public release.. */ /////////////////////////////////////////////////////////////////////////////////////////////////// // Standard include guards #ifndef NSAPIDLLIMP_H_INCLUDED #define NSAPIDLLIMP_H_INCLUDED #include "nsAPItypes.h" // Only need to specify "C" naming convention if using mixed C/C++ // It won't hurt if all C or all C++, so let's be safe #ifdef __cplusplus extern "C" { #endif #ifndef _WIN32 #define __stdcall #endif /////////////////////////////////////////////////////////////////////////////////////////////////// // // Definitions of function pointers // /////////////////////////////////////////////////////////////////////////////////////////////////// /////////////////////////////////////////////////////////////////////////////////////////////////// // Define pointer to ns_GetLibraryInfo // // Purpose: // Retrieves information about the loaded API library // // Parameters: // ns_LIBRARYINFO *pLibraryInfo pointer to ns_LIBRARYINFO structure to receive information // uint32 dwLibraryInfoSize size in bytes of ns_LIBRARYINFO structure // // Return Values: // ns_OK ns_LIBIRARYINFO successfully retrieved // ns_LIBEERROR library error // /////////////////////////////////////////////////////////////////////////////////////////////////// typedef ns_RESULT (__stdcall *NS_GETLIBRARYINFO) (ns_LIBRARYINFO *pLibraryInfo, uint32 dwLibraryInfoSize); /////////////////////////////////////////////////////////////////////////////////////////////////// // Define pointer to ns_OpenFile // // Purpose: // Opens the data file and assigns a file handle for internal use by the library. // // Parameters: // char *pszFilename name of file to open // uint32 *hFile pointer to a file handle // // Return Values: // ns_OK ns_LIBIRARYINFO successfully retrieved // ns_TYPEERROR library unable to open file type // ns_FILEERROR file access or read error // ns_LIBEERROR library error // /////////////////////////////////////////////////////////////////////////////////////////////////// typedef ns_RESULT (__stdcall *NS_OPENFILE) (const char *pszFilename, uint32 *hFile); /////////////////////////////////////////////////////////////////////////////////////////////////// // Define pointer to ns_GetFileInfo // // Purpose: // Retrieve general information about the data file // // Parameters: // uint32 hFile handle to NEV data file // ns_FILEINFO *pFileInfo pointer to ns_FILEINFO structure that receives data // uint32 dwFileInfoSize number of bytes returned in ns_FILEINFO // // Return Values: // ns_OK function succeeded // ns_BADFILE invalid file handle // ns_FILEERROR file access or read error // ns_LIBERROR library error, null pointer // /////////////////////////////////////////////////////////////////////////////////////////////////// typedef ns_RESULT (__stdcall *NS_GETFILEINFO) (uint32 hFile, ns_FILEINFO *pFileInfo, uint32 dwFileInfoSize); /////////////////////////////////////////////////////////////////////////////////////////////////// // Define pointer to ns_CloseFile // // Purpose: // Close the open data file // // Parameters: // uint32 hFile handle to NEV data file // // Return Values: // ns_OK function succeeded // ns_BADFILE invalid file handle // /////////////////////////////////////////////////////////////////////////////////////////////////// typedef ns_RESULT (__stdcall *NS_CLOSEFILE) (uint32 hFile); /////////////////////////////////////////////////////////////////////////////////////////////////// // Define pointer to ns_GetEntityInfo // // Purpose: // Retrieve Entity information // // Parameters: // uint32 hFile handle to NEV data file // uint32 dwEntityID entity ID // ns_ENTITYINFO *pEntityInfo pointer to ns_ENTITYINFO structure that receives information // uint32 dwEntityInfoSize number of bytes returned in ns_ENTITYINFO // // Return Values: // ns_OK function succeeded // ns_BADFILE invalid file handle // ns_LIBERROR library error, null pointer // /////////////////////////////////////////////////////////////////////////////////////////////////// typedef ns_RESULT (__stdcall *NS_GETENTITYINFO) (uint32 hFile, uint32 dwEntityID, ns_ENTITYINFO *pEntityInfo, uint32 dwEntityInfoSize); /////////////////////////////////////////////////////////////////////////////////////////////////// // Define pointer to ns_GetEventInfo // // Purpose: // Retrieve information for Event entities. // // Parameters: // uint32 hFile handle to NEV data file // uint32 dwEntityID Event entity ID // ns_EVENTINFO *pEventInfo pointer to ns_EVENTINFO structure to receive information // uint32 dwEventInfoSize number of bytes returned in ns_EVENTINFO // // Return Values: // ns_OK function succeeded // ns_BADFILE invalid file handle // ns_BADENTITY inappropriate or invalid entity identifier // ns_LIBERROR library error, null pointer // /////////////////////////////////////////////////////////////////////////////////////////////////// typedef ns_RESULT (__stdcall *NS_GETEVENTINFO) (uint32 hFile, uint32 dwEntityID, ns_EVENTINFO *pEventInfo, uint32 dwEventInfoSize); /////////////////////////////////////////////////////////////////////////////////////////////////// // Define pointer to ns_GetEventData // // Purpose: // Retrieve the timestamp and Evevy entity data items. // // Parameters: // uint32 hFile handle to NEV data file // uint32 dwEntityID Event entity ID // uint32 nIndex Event entity item number // double *pdTimeStamp pointer to double timestamp (in seconds) // void *pData pointer to data buffer to receive data // uint32 *pdwDataSize pointer to number of bytes of data retrieved into data buffer // // Return Values: // ns_OK function succeeded // ns_BADFILE invalid file handle // ns_BADENTITY inappropriate or invalie entity identifier // ns_LIBERROR library error, null pointer // /////////////////////////////////////////////////////////////////////////////////////////////////// typedef ns_RESULT (__stdcall *NS_GETEVENTDATA) (uint32 hFile, uint32 dwEntityID, uint32 nIndex, double *pdTimeStamp, void *pData, uint32 dwDataSize, uint32 *pdwDataRetSize); /////////////////////////////////////////////////////////////////////////////////////////////////// // Define pointer to ns_GetAnalogInfo // Purpose: // // Retrieve information for Analog entities // Parameters: // // uint32 hFile handle to NEV data file // uint32 dwEntityID Analog entity ID // ns_ANALOGINFO *pAnalogInfo pointer to ns_ANALOGINFO structure to receive data // uint32 dwAnalogInfoSize number of bytes returned in ns_ANALOGINFO // // Return Values: // ns_OK function succeeded // ns_BADFILE invalid file handle // ns_BADENTITY inappropriate or invalie entity identifier // ns_LIBERROR library error, null pointer // /////////////////////////////////////////////////////////////////////////////////////////////////// typedef ns_RESULT (__stdcall *NS_GETANALOGINFO) (uint32 hFile, uint32 dwEntityID, ns_ANALOGINFO *pAnalogInfo,uint32 dwAnalogInfoSize); /////////////////////////////////////////////////////////////////////////////////////////////////// // Define pointer to ns_GetAnalogData // // Purpose: // Retrieve analog data in the buffer at pData. If possible, dwIndexCount, analog data values are // returned in the buffer. As there may be time gaps in the sequential values, the number of // continuously sampled data items is returned in pdwContCount. // // Parameters: // uint32 hFile handle to NEV data file // uint32 dwEntityID Analog entity ID // uint32 dwStartIndex starting index to search for timestamp // uint32 dwIndexCount number of timestamps to retrieve // uint32 *pdwContCount pointer to count of the first non-sequential analog item // double *pData pointer of data buffer to receive data values // // Return Values: // ns_OK function succeeded // ns_BADFILE invalid file handle // ns_BADENTITY inappropriate or invalid entity identifier // ns_LIBERROR library error, null pointer // /////////////////////////////////////////////////////////////////////////////////////////////////// typedef ns_RESULT (__stdcall *NS_GETANALOGDATA) (uint32 hFile, uint32 dwEntityID, uint32 dwStartIndex, uint32 dwIndexCount, uint32 *pdwContCount, double *pData); /////////////////////////////////////////////////////////////////////////////////////////////////// // Define pointer to ns_GetSegmentInfo // // Purpose: // Retrieve information for Segment entities. // // Parameters: // uint32 hFile handle to NEV data file // uint32 dwEntityID Segment entity ID // ns_SEGMENTINFO *pSegmentInfo pointer to ns_SEGMENTINFO structure to receive information // uint32 dwSegmentInfoSize size in bytes retrieved in ns_SEGMENTINFO structure // // Return Values: // ns_OK function succeeded // ns_BADFILE invalid file handle // ns_BADENTITY invalid or inappropriate entity identifier specified // ns_FILEERROR file access or read error // ns_LIBERROR library error // /////////////////////////////////////////////////////////////////////////////////////////////////// typedef ns_RESULT (__stdcall *NS_GETSEGMENTINFO) (uint32 hFile, uint32 dwEntityID, ns_SEGMENTINFO *pSegmentInfo,uint32 dwSegmentInfoSize); /////////////////////////////////////////////////////////////////////////////////////////////////// // Define pointer to ns_GetSegmentSourceInfo // // Purpose: // Retrieve information on the source, dwSourceID, generating segment entity dwEntityID. // // Parameters: // uint32 hFile handle to NEV data file // uint32 dwEntityID Segment entity ID // uint32 dwSourceID entity ID of source /// ns_SEGSOURCEINFO *pSourceInfo pointer to ns_SEGSOURCEINFO structure to receive information // uint32 dwSourceInfoSize size in bytes retrieved in ns_SEGSOURCEINFO structure // // Return Values: // ns_OK function succeeded // ns_BADFILE invalid file handle // ns_BADENTITY invalid or inappropriate entity identifier specified // ns_FILEERROR file access or read error // ns_LIBERROR library error // /////////////////////////////////////////////////////////////////////////////////////////////////// typedef ns_RESULT (__stdcall *NS_GETSEGMENTSOURCEINFO) (uint32 hFile, uint32 dwEntityID, uint32 dwSourceID, ns_SEGSOURCEINFO *pSourceInfo, uint32 dwSourceInfoSize); /////////////////////////////////////////////////////////////////////////////////////////////////// // Define pointer to ns_GetSegmentData // // Purpose: // Retrieve segment data waveform and its timestamp. // The number of data points read is returned at pdwSampleCount. // // Parameters: // uint32 hFile handle to NEV data file // uint32 dwEntityID Segment entity ID // int32 nIndex Segment item index to retrieve // double *pdTimeStamp pointer to timestamp to retrieve // double *pData pointer to data buffer to receive data // uint32 *pdwSampleCount pointer to number of data items retrieved // uint32 *pdwUnitID pointer to unit ID of Segment data // // Return Values: // ns_OK function succeeded // ns_BADFILE invalid file handle // ns_BADENTITY invalid or inappropriate entity identifier specified // ns_FILEERROR file access or read error // ns_LIBERROR library error // /////////////////////////////////////////////////////////////////////////////////////////////////// typedef ns_RESULT (__stdcall *NS_GETSEGMENTDATA) (uint32 hFile, uint32 dwEntityID, int32 nIndex, double *pdTimeStamp, double *pdData, uint32 dwDataBufferSize, uint32 *pdwSampleCount, uint32 *pdwUnitID ); /////////////////////////////////////////////////////////////////////////////////////////////////// // Define pointer to ns_GetNeuralInfo // // Purpose: // Retrieve information on Neural Events. // // Parameters: // uint32 hFile handle to NEV data file // uint32 dwEntityID Neural entity ID // ns_NEURALINFO *pNeuralInfo pointer to ns_NEURALINFO structure to receive information // uint32 dwNeuralInfoSize number of bytes returned in ns_NEURALINFO // // Return Values: // ns_OK function succeeded // ns_BADFILE invalid file handle // ns_BADENTITY inappropriate or invalid entity identifier // ns_LIBERROR library error, null pointer // /////////////////////////////////////////////////////////////////////////////////////////////////// typedef ns_RESULT (__stdcall *NS_GETNEURALINFO) (uint32 hFile, uint32 dwEntityID, ns_NEURALINFO *pNeuralInfo, uint32 dwNeuralInfoSize); /////////////////////////////////////////////////////////////////////////////////////////////////// // Define pointer to ns_GetNeuralData // // Purpose: // Retrieve requested number of Neural event timestamps (in sec) // // Parameters: // uint32 hFile handle to NEV data file // uint32 dwEntityID Neural event entity ID // uint32 dwStartIndex index of first Neural event item time to retrieve // uint32 dwIndexCount number of Neural event items to retrieve // double *pData pointer to buffer to receive times // // Return Values: // ns_OK function succeeded // ns_BADFILE invalid file handle // ns_BADENTITY inappropriate or invalie entity identifier // ns_LIBERROR library error, null pointer // /////////////////////////////////////////////////////////////////////////////////////////////////// typedef ns_RESULT (__stdcall *NS_GETNEURALDATA) (uint32 hFile, uint32 dwEntityID, uint32 dwStartIndex, uint32 dwIndexCount, double *pdData); /////////////////////////////////////////////////////////////////////////////////////////////////// // Define pointer to ns_GetIndexByTime // // Purpose: // // Given the time (sec), return the closest data item index, as specified by nFlag. // Finds the packet with the closest time to the requested time. // // Parameters: // // uint32 hFile handle to NEV data file // uint32 dwEntityID entity ID to search for // uint32 dwSearchTimeStamp timestamp of item to search for // int32 nFlag position of item relative to the requested timestamp // uint32 *pdwIndex pointer to index of item to retrieve // // Return Values: // // ns_OK function succeeded // ns_BADFILE invalid file handle // ns_LIBERROR library error, null pointer // /////////////////////////////////////////////////////////////////////////////////////////////////// typedef ns_RESULT (__stdcall *NS_GETINDEXBYTIME) (uint32 hFile, uint32 dwEntityID, double dTime, int32 nFlag, uint32 *pdwIndex); /////////////////////////////////////////////////////////////////////////////////////////////////// // Define pointer to ns_GetTimeByIndex // // Purpose: // // Given an index for an entity data item, return the time in seconds. // // Parameters: // // uint32 hFile handle to NEV data file // uint32 dwEntityID entity ID to search for // uint32 dwIndex index of entity item to search for // double *pdTime time of entity to retrieve // // Return Values: // // ns_OK function succeeded // ns_BADFILE invalid file handle // ns_LIBERROR library error, null pointer // /////////////////////////////////////////////////////////////////////////////////////////////////// typedef ns_RESULT (__stdcall *NS_GETTIMEBYINDEX) (uint32 hFile, uint32 dwEntityID, uint32 dwIndex, double *pdTime); /////////////////////////////////////////////////////////////////////////////////////////////////// // Define pointer to ns_GetLastErrorMsg // // Purpose: // Retrieve the most recent error text message // // Parameters: // char *pszMsgBuffer pointer to text buffer to receive error message // uint32 dwMsgBufferSize size in bytes of text buffer // // Return Values: // ns_OK function succeeded // ns_LIBERROR library error // // /////////////////////////////////////////////////////////////////////////////////////////////////// typedef ns_RESULT (__stdcall *NS_GETLASTERRORMSG) (char *pszMsgBuffer, uint32 dwMsgBufferSize); ////////////////////////////////////////////////////////////////////////////////////////////////// /////////////////////////////////////////////////////////////////////////////////////////////////// // The names of the function pointers are defined here to standardize its use // in the application. // // Function pointer variable names are defined in the host application. If these // names are to be defined differently, this section should be commented out. // #if 0 extern NS_GETLIBRARYINFO ns_GetLibraryInfo; extern NS_OPENFILE ns_OpenFile; extern NS_GETFILEINFO ns_GetFileInfo; extern NS_CLOSEFILE ns_CloseFile; extern NS_GETENTITYINFO ns_GetEntityInfo; extern NS_GETEVENTINFO ns_GetEventInfo; extern NS_GETEVENTDATA ns_GetEventData; extern NS_GETANALOGINFO ns_GetAnalogInfo; extern NS_GETANALOGDATA ns_GetAnalogData; extern NS_GETSEGMENTINFO ns_GetSegmentInfo; extern NS_GETSEGMENTSOURCEINFO ns_GetSegmentSourceInfo; extern NS_GETSEGMENTDATA ns_GetSegmentData; extern NS_GETNEURALINFO ns_GetNeuralInfo; extern NS_GETNEURALDATA ns_GetNeuralData; extern NS_GETINDEXBYTIME ns_GetIndexByTime; extern NS_GETTIMEBYINDEX ns_GetTimeByIndex; extern NS_GETLASTERRORMSG ns_GetLastErrorMsg; #endif #ifdef __cplusplus } #endif #endif // end of include guards python-neuroshare-0.9.2/capi/nsAPItypes.h000066400000000000000000000335231234311067000203430ustar00rootroot00000000000000/////////////////////////////////////////////////////////////////////////////////////////////////// // // Copyright (C) 2003 Neuroshare Project // // This library is free software; you can redistribute it and/or // modify it under the terms of the GNU Lesser General Public // License as published by the Free Software Foundation; either // version 2.1 of the License, or (at your option) any later version. // // This library 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 // Lesser General Public License for more details. // // A copy of the GNU Lesser General Public License can be obtained by writing to: // Free Software Foundation, Inc., // 59 Temple Place, Suite 330, // Boston, MA 02111-1307 // USA // // Contact information: // Angela Wang // CyberKinetics, Inc., // 391 G Chipeta Way // Salt Lake City, UT 84108 // USA // angela@bionictech.com // // Website: // www.neuroshare.org // // All other copyrights on this material are replaced by this license agreeement. // /////////////////////////////////////////////////////////////////////////////////////////////////// /* $Workfile: nsAPItypes.h $ */ // // File version : 1.0 // // Specification : based on Neuroshare API specification version 1.0 // // Description : This header file contains C declarations for constants, types, // and structures defined in the Neuroshare API specification document // // Authors : Shane Guillory, Angela Wang // /* $Date: 2/21/03 12:42p $ */ // /* $History: nsAPItypes.h $ // // ***************** Version 6 ***************** // User: Almut Date: 2/21/03 Time: 12:42p // Updated in $/Neuroshare/DLLTester // These headers now conform to Neuroshare API Spec 1.0 // // ***************** Version 1 ***************** // User: Angela Date: 2/21/03 Time: 11:45a // Created in $/Neuroshare/nsNEVLibrary // Version 1.0 Neuroshare Specifications // // ***************** Version 1 ***************** // User: Angela Date: 2/17/03 Time: 11:22a // Created in $/Neuroshare/nsNEVLibrary // Neuroshare API Ver 1.0 compliant header files // // ***************** Version 1 ***************** // User: Angela Date: 2/13/03 Time: 9:29a // Created in $/Neuroshare/nsNEVLibrary * * ***************** Version 5 ***************** * User: Angela Date: 1/14/03 Time: 9:42a * Updated in $/Neuroshare/nsNEVLibrary * Fixed location of brackets in structures * * ***************** Version 4 ***************** * User: Angela Date: 1/10/03 Time: 12:13p * Updated in $/Neuroshare/nsNEVLibrary * Reword disclaimer * * ***************** Version 3 ***************** * User: Angela Date: 1/09/03 Time: 12:14p * Updated in $/Neuroshare/nsNEVLibrary * Add copyright, disclaimer and file header v0.9b - Functions changed to use __stdcall calling convention for compatibility with Visual Basic. Function prototype declarations also changed to all-capital versions of the neuroshare function names. v0.9b - First public release.. */ /////////////////////////////////////////////////////////////////////////////////////////////////// /////////////////////////////////////////////////////////////////////////////////////////////////// // // Additional Remarks // // - The members of the Neuroshare API structures are defined on 4-byte boundaries. Make sure to // compile all with 4-byte or smaller alignement // /////////////////////////////////////////////////////////////////////////////////////////////////// // Standard Include guards #ifndef NSAPITYPES_H_INCLUDED #define NSAPITYPES_H_INCLUDED #define ns_LIBVERSION 0100 // version 01.00 /////////////////////////////////////////////////////////////////////////////////////////////////// // // Fixed storage size definitions for declared variables // (includes conditional testing so that there is no clash with win32 headers) // /////////////////////////////////////////////////////////////////////////////////////////////////// #if defined(_MSC_VER) typedef signed __int8 int8; typedef unsigned __int8 uint8; typedef signed __int16 int16; typedef unsigned __int16 uint16; typedef signed __int32 int32; typedef unsigned __int32 uint32; #pragma pack(push) #pragma pack(4) // specify 4-byte structure alignment #else #include typedef int8_t int8; typedef uint8_t uint8; typedef int16_t int16; typedef uint16_t uint16; typedef int32_t int32; typedef uint32_t uint32; #endif /////////////////////////////////////////////////////////////////////////////////////////////////// // // Library Return Code Definitions // /////////////////////////////////////////////////////////////////////////////////////////////////// typedef int32 ns_RESULT; #define ns_OK 0 //Function Successful #define ns_LIBERROR -1 //Linked Library Error #define ns_TYPEERROR -2 //Library unable to open file type #define ns_FILEERROR -3 //File access or read Error #define ns_BADFILE -4 //Invalid file handle passed to function #define ns_BADENTITY -5 //Invalid or inappropriate entity identifier specified #define ns_BADSOURCE -6 //Invalid source identifier specified #define ns_BADINDEX -7 //Invalid entity index or index range specified /////////////////////////////////////////////////////////////////////////////////////////////////// // // Definitions of constants and flags // /////////////////////////////////////////////////////////////////////////////////////////////////// // Library description flags #define ns_LIBRARY_DEBUG 0x01 // includes debug info linkage #define ns_LIBRARY_MODIFIED 0x02 // file was patched or modified #define ns_LIBRARY_PRERELEASE 0x04 // pre-release or beta version #define ns_LIBRARY_SPECIALBUILD 0x08 // different from release version #define ns_LIBRARY_MULTITHREADED 0x10 // library is multithread safe //Definitions of Event Entity types #define ns_EVENT_TEXT 0 // null-terminated ascii text string #define ns_EVENT_CSV 1 // comma separated ascii text values #define ns_EVENT_BYTE 2 // 8-bit value #define ns_EVENT_WORD 3 // 16-bit value #define ns_EVENT_DWORD 4 // 32-bit value //Definitions of entity types in the structure ns_ENTITYINFO #define ns_ENTITY_UNKNOWN 0 // unknown entity type #define ns_ENTITY_EVENT 1 // Event entity #define ns_ENTITY_ANALOG 2 // Analog entity #define ns_ENTITY_SEGMENT 3 // Segment entity #define ns_ENTITY_NEURALEVENT 4 // Sorted Neural entity //Flags used for locating data entries #define ns_BEFORE -1 // less than or equal to specified time #define ns_CLOSEST 0 // closest time #define ns_AFTER +1 // greater than or equal to specified time /////////////////////////////////////////////////////////////////////////////////////////////////// // // DLL library version information functions // /////////////////////////////////////////////////////////////////////////////////////////////////// //File descriptor structure typedef struct { char szDescription[32]; // Text description of the file type or file family char szExtension[8]; // Extension used on PC, Linux, and Unix Platforms char szMacCodes[8]; // Application and Type Codes used on Mac Platforms char szMagicCode[16]; // Null-terminated code used at the file beginning } ns_FILEDESC; // Library information structure typedef struct { uint32 dwLibVersionMaj; // Major version number of library uint32 dwLibVersionMin; // Minor version number of library uint32 dwAPIVersionMaj; // Major version number of API uint32 dwAPIVersionMin; // Minor version number of API char szDescription[64]; // Text description of the library char szCreator[64]; // Name of library creator uint32 dwTime_Year; // Year of last modification date uint32 dwTime_Month; // Month (0-11; January = 0) of last modification date uint32 dwTime_Day; // Day of the month (1-31) of last modification date uint32 dwFlags; // Additional library flags uint32 dwMaxFiles; // Maximum number of files library can simultaneously open uint32 dwFileDescCount; // Number of valid description entries in the following array ns_FILEDESC FileDesc[16]; // Text descriptor of files that the DLL can interpret } ns_LIBRARYINFO; // File information structure (the time of file creation should be reported in GMT) typedef struct { char szFileType[32]; // Manufacturer's file type descriptor uint32 dwEntityCount; // Number of entities in the data file. double dTimeStampResolution; // Minimum timestamp resolution double dTimeSpan; // Time span covered by the data file in seconds char szAppName[64]; // Name of the application that created the file uint32 dwTime_Year; // Year the file was created uint32 dwTime_Month; // Month (0-11; January = 0) uint32 dwTime_DayofWeek; // Day of the week (0-6; Sunday = 0) uint32 dwTime_Day; // Day of the month (1-31) uint32 dwTime_Hour; // Hour since midnight (0-23) uint32 dwTime_Min; // Minute after the hour (0-59) uint32 dwTime_Sec; // Seconds after the minute (0-59) uint32 dwTime_MilliSec; // Milliseconds after the second (0-1000) char szFileComment[256]; // Comments embedded in the source file } ns_FILEINFO; // General entity information structure typedef struct { char szEntityLabel[32]; // Specifies the label or name of the entity uint32 dwEntityType; // One of the ns_ENTITY_* types defined above uint32 dwItemCount; // Number of data items for the specified entity in the file } ns_ENTITYINFO; // Event entity information structure typedef struct { uint32 dwEventType; // One of the ns_EVENT_* types defined above uint32 dwMinDataLength; // Minimum number of bytes that can be returned for an Event uint32 dwMaxDataLength; // Maximum number of bytes that can be returned for an Event char szCSVDesc[128]; // Description of the data fields for CSV Event Entities } ns_EVENTINFO; // Analog information structure typedef struct { double dSampleRate; // The sampling rate in Hz used to digitize the analog values double dMinVal; // Minimum possible value of the input signal double dMaxVal; // Maximum possible value of the input signal char szUnits[16]; // Specifies the recording units of measurement double dResolution; // Minimum resolvable step (.0000305 for a +/-1V 16-bit ADC) double dLocationX; // X coordinate in meters double dLocationY; // Y coordinate in meters double dLocationZ; // Z coordinate in meters double dLocationUser; // Additional position information (e.g. tetrode number) double dHighFreqCorner; // High frequency cutoff in Hz of the source signal filtering uint32 dwHighFreqOrder; // Order of the filter used for high frequency cutoff char szHighFilterType[16]; // Type of filter used for high frequency cutoff (text format) double dLowFreqCorner; // Low frequency cutoff in Hz of the source signal filtering uint32 dwLowFreqOrder; // Order of the filter used for low frequency cutoff char szLowFilterType[16]; // Type of filter used for low frequency cutoff (text format) char szProbeInfo[128]; // Additional text information about the signal source } ns_ANALOGINFO; //Segment Information structure typedef struct { uint32 dwSourceCount; // Number of sources in the Segment Entity, e.g. 4 for a tetrode uint32 dwMinSampleCount; // Minimum number of samples in each Segment data item uint32 dwMaxSampleCount; // Maximum number of samples in each Segment data item double dSampleRate; // The sampling rate in Hz used to digitize source signals char szUnits[32]; // Specifies the recording units of measurement } ns_SEGMENTINFO; // Segment source information structure typedef struct { double dMinVal; // Minimum possible value of the input signal double dMaxVal; // Maximum possible value of the input signal double dResolution; // Minimum input step size that can be resolved double dSubSampleShift; // Time diff btn timestamp and actual sampling time of source double dLocationX; // X coordinate of source in meters double dLocationY; // Y coordinate of source in meters double dLocationZ; // Z coordinate of source in meters double dLocationUser; // Additional position information (e.g tetrode number) double dHighFreqCorner; // High frequency cutoff in Hz of the source signal filtering uint32 dwHighFreqOrder; // Order of the filter used for high frequency cutoff char szHighFilterType[16]; // Type of filter used for high frequency cutoff (text format) double dLowFreqCorner; // Low frequency cutoff in Hz of the source signal filtering uint32 dwLowFreqOrder; // Order of the filter used for low frequency cutoff char szLowFilterType[16]; // Type of filter used for low frequency cutoff (text format) char szProbeInfo[128]; // Additional text information about the signal source } ns_SEGSOURCEINFO; // Neural Information structure typedef struct { uint32 dwSourceEntityID; // Optional ID number of a source entity uint32 dwSourceUnitID; // Optional sorted unit ID number used in the source entity char szProbeInfo[128]; // Additional probe text information or source entity label } ns_NEURALINFO; #if defined(_MSC_VER) # pragma pack(pop) #endif #endif python-neuroshare-0.9.2/capi/nspy_glue.c000066400000000000000000001033131234311067000202770ustar00rootroot00000000000000/* * Copyright © 2011 Christian Kellner * * This library is free software; you can redistribute it and/or * modify it under the terms of the GNU Lesser General Public * License as published by the Free Software Foundation; either * version 2 of the licence, or (at your option) any later version. * * This library 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 * Lesser General Public License for more details. * * You should have received a copy of the GNU Lesser General Public * License along with this library; if not, write to the * Free Software Foundation, Inc., 59 Temple Place - Suite 330, * Boston, MA 02111-1307, USA. * * Author: Christian Kellner */ #include //we want only fresh stuff #define NPY_NO_DEPRECATED_API NPY_1_7_API_VERSION #include #include #include #ifndef _WIN32 #include #include #else #define _WIN32_WINNT 0x0500 #define WINVER 0x0500 #define WIN32_LEAN_AND_MEAN #include #ifdef _MSC_VER # define _POSIX_ #endif #endif #include "nsAPItypes.h" #include "nsAPIdllimp.h" static PyObject *PgError; typedef struct { #ifdef _WIN32 HMODULE dl_handle; #else void *dl_handle; #endif NS_GETLIBRARYINFO GetLibraryInfo; NS_OPENFILE OpenFile; NS_CLOSEFILE CloseFile; NS_GETFILEINFO GetFileInfo; NS_GETENTITYINFO GetEntityInfo; NS_GETEVENTINFO GetEventInfo; NS_GETEVENTDATA GetEventData; NS_GETANALOGINFO GetAnalogInfo; NS_GETANALOGDATA GetAnalogData; NS_GETSEGMENTINFO GetSegmentInfo; NS_GETSEGMENTSOURCEINFO GetSegmentSourceInfo; NS_GETSEGMENTDATA GetSegmentData; NS_GETNEURALINFO GetNeuralInfo; NS_GETNEURALDATA GetNeuralData; NS_GETINDEXBYTIME GetIndexByTime; NS_GETTIMEBYINDEX GetTimeByIndex; NS_GETLASTERRORMSG GetLastErrorMsg; } NsLibrary; uint8 uint8_from_data (void *data, size_t data_len) { uint8 ret; if (data_len == 1) { uint8 *u8 = data; ret = *u8; } else if (data_len == 2) { ret = *(uint8 *) data; } else if (data_len == 4) { uint32 *u32; u32 = (uint32 *) data; ret = (uint8) *u32; } else { ret = 0; } return ret; } static uint16 uint16_from_data (void *data, size_t data_len) { uint16 ret; if (data_len == 1) { uint8 *u8 = data; ret = (uint16) *u8; } else if (data_len == 2) { ret = *(uint16 *) data; } else if (data_len == 4) { uint32 *u32; u32 = (uint32 *) data; ret = (uint16) *u32; } else { ret = 0; } return ret; } static uint32 uint32_from_data (void *data, size_t data_len) { uint16 ret; if (data_len == 1) { uint8 *u8 = data; ret = (uint32) *u8; } else if (data_len == 2) { uint16 *u16; u16 = (uint16 *) data; ret = (uint32) *u16; } else if (data_len == 4) { ret = *(uint32 *) data; } else { ret = 0; } return ret; } static int check_result_is_error (ns_RESULT res, NsLibrary *lib) { char buf[1024] = {0, }; ns_RESULT err_res; if (res == ns_OK) return 0; err_res = lib->GetLastErrorMsg (buf, sizeof (buf)); if (err_res == ns_OK) PyErr_Format (PgError, "Neuroshare-Error (%d): %s", res, buf); else PyErr_Format (PgError, "Internal Neuroshare-Error: %d", res); return 1; } static int dict_set_item_eat_ref (PyObject *dict, const char *string, PyObject *item) { int res; res = PyDict_SetItemString (dict, string, item); Py_DECREF (item); return res; } /* ************************************************************************** */ #ifndef _WIN32 #define GetProcAddress dlsym #endif #define PROC_ADDR(_struct, _function, _variable) \ _struct->_variable = (_function) GetProcAddress (_struct->dl_handle, "ns_" #_variable); \ if (_struct->_variable == NULL) \ { \ PyErr_Format (PgError, "Could not lookup function: %s", #_variable); \ return -1; \ } static int dl_assign_pointers (NsLibrary *lib) { PROC_ADDR (lib, NS_GETLIBRARYINFO, GetLibraryInfo); PROC_ADDR (lib, NS_OPENFILE, OpenFile); PROC_ADDR (lib, NS_CLOSEFILE, CloseFile); PROC_ADDR (lib, NS_GETFILEINFO, GetFileInfo); PROC_ADDR (lib, NS_GETENTITYINFO, GetEntityInfo); PROC_ADDR (lib, NS_GETEVENTINFO, GetEventInfo); PROC_ADDR (lib, NS_GETEVENTDATA, GetEventData); PROC_ADDR (lib, NS_GETANALOGINFO, GetAnalogInfo); PROC_ADDR (lib, NS_GETANALOGDATA, GetAnalogData); PROC_ADDR (lib, NS_GETSEGMENTINFO, GetSegmentInfo); PROC_ADDR (lib, NS_GETSEGMENTSOURCEINFO, GetSegmentSourceInfo); PROC_ADDR (lib, NS_GETSEGMENTDATA, GetSegmentData); PROC_ADDR (lib, NS_GETNEURALINFO, GetNeuralInfo); PROC_ADDR (lib, NS_GETNEURALDATA, GetNeuralData); PROC_ADDR (lib, NS_GETINDEXBYTIME, GetIndexByTime); PROC_ADDR (lib, NS_GETINDEXBYTIME, GetIndexByTime); PROC_ADDR (lib, NS_GETTIMEBYINDEX, GetTimeByIndex); PROC_ADDR (lib, NS_GETLASTERRORMSG, GetLastErrorMsg); return 0; } static void dl_set_error (const char *message) { #ifdef _WIN32 DWORD last_error; DWORD res; LPVOID buf_msg; char buf_str[1024] = {0,}; last_error = GetLastError (); res = FormatMessage (FORMAT_MESSAGE_ALLOCATE_BUFFER | FORMAT_MESSAGE_FROM_SYSTEM | FORMAT_MESSAGE_IGNORE_INSERTS, NULL, last_error, MAKELANGID (LANG_NEUTRAL, SUBLANG_DEFAULT), (LPTSTR) &buf_msg, 0, NULL); if (res > 0) res = WideCharToMultiByte (CP_ACP, 0, buf_msg, -1, buf_str, sizeof (buf_str), NULL, NULL); if (res == 0) _snprintf (buf_str, sizeof (buf_str), "%s", "Internal error"); PyErr_Format (PgError, "%s: %s", message, buf_str); LocalFree (buf_msg); #else PyErr_Format (PgError, "%s: %s", message, dlerror ()); #endif } #ifdef _WIN32 static int dl_load_library_win32 (const char *filename, NsLibrary *lib) { HMODULE handle; /* FIXME: set errors */ handle = LoadLibraryEx (filename, 0, 0); if (handle == NULL) return -1; lib->dl_handle = handle; return 0; } #else static int dl_load_library_unix (const char *filename, NsLibrary *lib) { int flags; void *dlh; flags = RTLD_NOW; dlh = dlopen (filename, flags); if (dlh == NULL) return -1; lib->dl_handle = dlh; return 0; } #endif static NsLibrary * dl_load_library (const char *filename) { int res; NsLibrary *lib; lib = malloc (sizeof (NsLibrary)); #ifdef _WIN32 res = dl_load_library_win32 (filename, lib); #else res = dl_load_library_unix (filename, lib); #endif if (res != 0) { dl_set_error ("Could not load library"); free (lib); lib = NULL; } return lib; } static int dl_unload_library (NsLibrary *lib) { int res; #ifdef _WIN32 res = ! FreeLibrary (lib->dl_handle); #else res = dlclose (lib->dl_handle); #endif if (res != 0) dl_set_error ("Could not unload library"); free (lib); return res; } static PyObject * library_open (PyObject *self, PyObject *args, PyObject *kwds) { NsLibrary *lib; PyObject *lib_handle; const char *filename; int res; if (!PyArg_ParseTuple (args, "s", &filename)) return NULL; lib = dl_load_library (filename); if (lib == NULL) return NULL; res = dl_assign_pointers (lib); if (res != 0) { dl_unload_library (lib); return NULL; } lib_handle = PyCObject_FromVoidPtr (lib, NULL); return lib_handle; } static PyObject * library_close (PyObject *self, PyObject *args, PyObject *kwds) { PyObject *cobj; NsLibrary *lib; int res; if (!PyArg_ParseTuple (args, "O", &cobj)) { PyErr_SetString (PyExc_StandardError, "Could not parse arguments"); return NULL; } if (!PyCObject_Check (cobj)) { PyErr_SetString (PyExc_TypeError, "Expected NsLibrary type"); return NULL; } lib = PyCObject_AsVoidPtr (cobj); res = dl_unload_library (lib); if (res != 0) return NULL; Py_RETURN_NONE; } static PyObject * do_get_library_info (PyObject *self, PyObject *args, PyObject *kwds) { PyObject *cobj; PyObject *dict; NsLibrary *lib; ns_LIBRARYINFO info; ns_RESULT res; if (!PyArg_ParseTuple (args, "O", &cobj)) { PyErr_SetString (PyExc_StandardError, "Could not parse arguments"); return NULL; } if (!PyCObject_Check (cobj)) { PyErr_SetString (PyExc_TypeError, "Expected NsLibrary type"); return NULL; } lib = PyCObject_AsVoidPtr (cobj); res = lib->GetLibraryInfo (&info, sizeof (info)); if (check_result_is_error (res, lib)) return NULL; dict = PyDict_New (); dict_set_item_eat_ref (dict, "Description", PyString_FromString (info.szDescription)); dict_set_item_eat_ref (dict, "Creator", PyString_FromString (info.szCreator)); dict_set_item_eat_ref (dict, "LibVersionMaj", PyInt_FromLong (info.dwLibVersionMaj)); dict_set_item_eat_ref (dict, "LibVersionMin", PyInt_FromLong (info.dwLibVersionMin)); dict_set_item_eat_ref (dict, "APIVersionMaj", PyInt_FromLong (info.dwAPIVersionMaj)); dict_set_item_eat_ref (dict, "APIVersionMin", PyInt_FromLong (info.dwAPIVersionMin)); dict_set_item_eat_ref (dict, "Time_Year", PyInt_FromLong (info.dwTime_Year)); dict_set_item_eat_ref (dict, "Time_Month", PyInt_FromLong (info.dwTime_Month)); dict_set_item_eat_ref (dict, "Time_Day", PyInt_FromLong (info.dwTime_Day)); dict_set_item_eat_ref (dict, "MaxFiles", PyInt_FromLong (info.dwMaxFiles)); return dict; } static ns_RESULT get_and_add_file_info (NsLibrary *lib, uint32 file_id, PyObject *dict) { ns_FILEINFO info; ns_RESULT res; res = lib->GetFileInfo (file_id, &info, sizeof (info)); if (res != ns_OK) return res; dict_set_item_eat_ref (dict, "FileType", PyString_FromString (info.szFileType)); dict_set_item_eat_ref (dict, "AppName", PyString_FromString (info.szAppName)); dict_set_item_eat_ref (dict, "FileComment", PyString_FromString (info.szFileComment)); dict_set_item_eat_ref (dict, "EntityCount", PyInt_FromLong (info.dwEntityCount)); dict_set_item_eat_ref (dict, "TimeStampResolution", PyFloat_FromDouble (info.dTimeStampResolution)); dict_set_item_eat_ref (dict, "TimeSpan", PyFloat_FromDouble (info.dTimeSpan)); dict_set_item_eat_ref (dict, "Time_Year", PyInt_FromLong (info.dwTime_Year)); dict_set_item_eat_ref (dict, "Time_Month", PyInt_FromLong (info.dwTime_Month)); dict_set_item_eat_ref (dict, "Time_Day", PyInt_FromLong (info.dwTime_Day)); dict_set_item_eat_ref (dict, "Time_Hour", PyInt_FromLong (info.dwTime_Hour)); dict_set_item_eat_ref (dict, "Time_Min", PyInt_FromLong (info.dwTime_Min)); dict_set_item_eat_ref (dict, "Time_Sec", PyInt_FromLong (info.dwTime_Sec)); dict_set_item_eat_ref (dict, "Time_MilliSec", PyInt_FromLong (info.dwTime_MilliSec)); return res; } static PyObject * do_open_file (PyObject *self, PyObject *args, PyObject *kwds) { const char *filename; PyObject *cobj; PyObject *tuple; PyObject *dict = NULL; NsLibrary *lib; ns_RESULT res; uint32 file_id; if (!PyArg_ParseTuple (args, "Os", &cobj, &filename)) { PyErr_SetString (PyExc_StandardError, "Could not parse arguments"); return NULL; } if (!PyCObject_Check (cobj)) { PyErr_SetString (PyExc_TypeError, "Expected NsLibrary type"); return NULL; } lib = PyCObject_AsVoidPtr (cobj); res = lib->OpenFile (filename, &file_id); if (res == ns_OK) { dict = PyDict_New (); res = get_and_add_file_info (lib, file_id, dict); } if (! check_result_is_error (res, lib)) { tuple = PyTuple_New (2); PyTuple_SetItem (tuple, 0, PyInt_FromLong (file_id)); PyTuple_SetItem (tuple, 1, dict); } else tuple = NULL; return tuple; } static PyObject * do_close_file (PyObject *self, PyObject *args, PyObject *kwds) { PyObject *cobj; PyObject *iobj; NsLibrary *lib; ns_RESULT res; uint32 file_id; if (!PyArg_ParseTuple (args, "OO", &cobj, &iobj)) { PyErr_SetString (PyExc_StandardError, "Could not parse arguments"); return NULL; } if (!PyCObject_Check (cobj) || !PyInt_Check (iobj)) { PyErr_SetString (PyExc_TypeError, "Wrong argument type(s)"); return NULL; } lib = PyCObject_AsVoidPtr (cobj); file_id = (uint32) PyInt_AsUnsignedLongMask (iobj); res = lib->CloseFile (file_id); if (check_result_is_error (res, lib)) return NULL; Py_RETURN_NONE; } /* *********************************** */ /* entity infos */ static int get_and_add_event_info (NsLibrary *lib, uint32 file_id, uint32 entity_id, PyObject *dict) { ns_EVENTINFO info; ns_RESULT res; res = lib->GetEventInfo (file_id, entity_id, &info, sizeof (info)); if (res != ns_OK) return res; dict_set_item_eat_ref (dict, "EventType", PyInt_FromLong (info.dwEventType)); dict_set_item_eat_ref (dict, "MinDataLength", PyInt_FromLong (info.dwMinDataLength)); dict_set_item_eat_ref (dict, "MaxDataLength", PyInt_FromLong (info.dwMaxDataLength)); dict_set_item_eat_ref (dict, "CSVDesc", PyString_FromString (info.szCSVDesc)); return ns_OK; } static int get_and_add_analog_info (NsLibrary *lib, uint32 file_id, uint32 entity_id, PyObject *dict) { ns_ANALOGINFO info; ns_RESULT res; res = lib->GetAnalogInfo (file_id, entity_id, &info, sizeof (info)); if (res != ns_OK) return res; dict_set_item_eat_ref (dict, "SampleRate", PyFloat_FromDouble (info.dSampleRate)); dict_set_item_eat_ref (dict, "MinVal", PyFloat_FromDouble (info.dMinVal)); dict_set_item_eat_ref (dict, "MaxVal", PyFloat_FromDouble (info.dMaxVal)); dict_set_item_eat_ref (dict, "Units", PyString_FromString (info.szUnits)); dict_set_item_eat_ref (dict, "Resolution", PyFloat_FromDouble (info.dResolution)); dict_set_item_eat_ref (dict, "LocationX", PyFloat_FromDouble (info.dLocationX)); dict_set_item_eat_ref (dict, "LocationY", PyFloat_FromDouble (info.dLocationY)); dict_set_item_eat_ref (dict, "LocationZ", PyFloat_FromDouble (info.dLocationZ)); dict_set_item_eat_ref (dict, "LocationUser", PyFloat_FromDouble (info.dLocationUser)); dict_set_item_eat_ref (dict, "HighFreqCorner", PyFloat_FromDouble (info.dHighFreqCorner)); dict_set_item_eat_ref (dict, "HighFreqOrder", PyInt_FromLong (info.dwHighFreqOrder)); dict_set_item_eat_ref (dict, "HighFilterType", PyString_FromString (info.szHighFilterType)); dict_set_item_eat_ref (dict, "LowFreqCorner", PyFloat_FromDouble (info.dLowFreqCorner)); dict_set_item_eat_ref (dict, "LowFreqOrder", PyInt_FromLong (info.dwLowFreqOrder)); dict_set_item_eat_ref (dict, "LowFilterType", PyString_FromString (info.szLowFilterType)); dict_set_item_eat_ref (dict, "ProbeInfo", PyString_FromString (info.szProbeInfo)); return ns_OK; } static int get_and_add_segment_source_info (NsLibrary *lib, uint32 file_id, uint32 entity_id, uint32 source_id, PyObject *list) { ns_SEGSOURCEINFO info; ns_RESULT res; PyObject *dict; dict = PyDict_New (); PyList_SetItem (list, source_id, dict); res = lib->GetSegmentSourceInfo (file_id, entity_id, source_id, &info, sizeof (info)); if (res != ns_OK) return res; dict_set_item_eat_ref (dict, "MinVal", PyFloat_FromDouble (info.dMinVal)); dict_set_item_eat_ref (dict, "MaxVal", PyFloat_FromDouble (info.dMaxVal)); dict_set_item_eat_ref (dict, "SubSampleShift", PyFloat_FromDouble (info.dSubSampleShift)); dict_set_item_eat_ref (dict, "Resolution", PyFloat_FromDouble (info.dResolution)); dict_set_item_eat_ref (dict, "LocationX", PyFloat_FromDouble (info.dLocationX)); dict_set_item_eat_ref (dict, "LocationY", PyFloat_FromDouble (info.dLocationY)); dict_set_item_eat_ref (dict, "LocationZ", PyFloat_FromDouble (info.dLocationZ)); dict_set_item_eat_ref (dict, "LocationUser", PyFloat_FromDouble (info.dLocationUser)); dict_set_item_eat_ref (dict, "HighFreqCorner", PyFloat_FromDouble (info.dHighFreqCorner)); dict_set_item_eat_ref (dict, "HighFreqOrder", PyInt_FromLong (info.dwHighFreqOrder)); dict_set_item_eat_ref (dict, "HighFilterType", PyString_FromString (info.szHighFilterType)); dict_set_item_eat_ref (dict, "LowFreqCorner", PyFloat_FromDouble (info.dLowFreqCorner)); dict_set_item_eat_ref (dict, "LowFreqOrder", PyInt_FromLong (info.dwLowFreqOrder)); dict_set_item_eat_ref (dict, "LowFilterType", PyString_FromString (info.szLowFilterType)); dict_set_item_eat_ref (dict, "ProbeInfo", PyString_FromString (info.szProbeInfo)); return ns_OK; } static int get_and_add_segment_info (NsLibrary *lib, uint32 file_id, uint32 entity_id, PyObject *dict) { ns_SEGMENTINFO info; ns_RESULT res; PyObject *list; unsigned int i; res = lib->GetSegmentInfo (file_id, entity_id, &info, sizeof (info)); if (res != ns_OK) return res; dict_set_item_eat_ref (dict, "SourceCount", PyInt_FromLong (info.dwSourceCount)); dict_set_item_eat_ref (dict, "MinSampleCount", PyInt_FromLong (info.dwMinSampleCount)); dict_set_item_eat_ref (dict, "MaxSampleCount", PyInt_FromLong (info.dwMaxSampleCount)); dict_set_item_eat_ref (dict, "SampleRate", PyFloat_FromDouble (info.dSampleRate)); dict_set_item_eat_ref (dict, "Units", PyString_FromString (info.szUnits)); list = PyList_New (info.dwSourceCount); for (i = 0; i < info.dwSourceCount; i++) get_and_add_segment_source_info (lib, file_id, entity_id, i, list); dict_set_item_eat_ref (dict, "SourceInfos", list); return res; } static int get_and_add_neural_info (NsLibrary *lib, uint32 file_id, uint32 entity_id, PyObject *dict) { ns_NEURALINFO info; ns_RESULT res; res = lib->GetNeuralInfo (file_id, entity_id, &info, sizeof (info)); if (res != ns_OK) return res; dict_set_item_eat_ref (dict, "SourceEntityID", PyInt_FromLong (info.dwSourceEntityID)); dict_set_item_eat_ref (dict, "SourceUnitID", PyInt_FromLong (info.dwSourceUnitID)); dict_set_item_eat_ref (dict, "ProbeInfo", PyString_FromString (info.szProbeInfo)); return ns_OK; } static PyObject * get_times_for_entity (NsLibrary *lib, uint32 file_id, uint32 entity_id, uint32 index, uint32 length) { PyObject *array; ns_RESULT res; npy_intp dims[1]; double *data; int i; res = ns_OK; dims[0] = length; array = PyArray_New (&PyArray_Type, 1, dims, NPY_DOUBLE, NULL, NULL /* data */, 0 /* itemsize */, NPY_ARRAY_CARRAY, NULL); data = (double *) PyArray_DATA ((PyArrayObject *) array); for (i = 0; i < length; i++) { res = lib->GetTimeByIndex (file_id, entity_id, index + i, (data + i)); if (res != ns_OK) break; } if (check_result_is_error (res, lib)) { Py_DECREF (array); return NULL; } return array; } /* ************************************************************************** */ /* "public" API */ static PyObject * do_get_entity_info (PyObject *self, PyObject *args, PyObject *kwds) { ns_ENTITYINFO info; PyObject *cobj; PyObject *iobj, *id_obj; PyObject *dict; NsLibrary *lib; ns_RESULT res; uint32 file_id; uint32 entity_id; if (!PyArg_ParseTuple (args, "OOO", &cobj, &iobj, &id_obj)) { PyErr_SetString (PyExc_StandardError, "Could not parse arguments"); return NULL; } if (!PyCObject_Check (cobj) || !PyInt_Check (iobj) || !PyInt_Check (id_obj)) { PyErr_SetString (PyExc_TypeError, "Wrong argument type(s)"); return NULL; } lib = PyCObject_AsVoidPtr (cobj); file_id = (uint32) PyInt_AsUnsignedLongMask (iobj); entity_id = (uint32) PyInt_AsUnsignedLongMask (id_obj); res = lib->GetEntityInfo (file_id, entity_id, &info, sizeof (info)); if (check_result_is_error (res, lib)) return NULL; dict = PyDict_New (); dict_set_item_eat_ref (dict, "EntityLabel", PyString_FromString (info.szEntityLabel)); dict_set_item_eat_ref (dict, "EntityType", PyInt_FromLong (info.dwEntityType)); dict_set_item_eat_ref (dict, "ItemCount", PyInt_FromLong (info.dwItemCount)); switch (info.dwEntityType) { case ns_ENTITY_EVENT: res = get_and_add_event_info (lib, file_id, entity_id, dict); break; case ns_ENTITY_ANALOG: res = get_and_add_analog_info (lib, file_id, entity_id, dict); break; case ns_ENTITY_SEGMENT: res = get_and_add_segment_info (lib, file_id, entity_id, dict); break; case ns_ENTITY_NEURALEVENT: res = get_and_add_neural_info (lib, file_id, entity_id, dict); break; } if (check_result_is_error (res, lib)) { Py_DECREF (dict); return NULL; } return dict; } /* ************************************ */ static PyObject * do_get_event_data (PyObject *self, PyObject *args, PyObject *kwds) { NsLibrary *lib; PyObject *cobj; PyObject *iobj, *id_obj, *idx_obj, *tp_obj, *sz_obj; PyObject *data_obj, *res_obj; uint32 file_id; uint32 entity_id; uint32 index; uint32 event_type; uint32 data_size; uint32 data_ret_size; double time_stamp; ns_RESULT res; void *buffer; if (!PyArg_ParseTuple (args, "OOOOOO", &cobj, &iobj, &id_obj, &idx_obj, &tp_obj, &sz_obj)) { PyErr_SetString (PyExc_StandardError, "Could not parse arguments"); return NULL; } if (!PyCObject_Check (cobj) || !PyInt_Check (iobj) || !PyInt_Check (id_obj) || !PyInt_Check (idx_obj) || !PyInt_Check (tp_obj) || !PyInt_Check (sz_obj)) { PyErr_SetString (PyExc_TypeError, "Wrong argument type(s)"); return NULL; } lib = PyCObject_AsVoidPtr (cobj); file_id = (uint32) PyInt_AsUnsignedLongMask (iobj); entity_id = (uint32) PyInt_AsUnsignedLongMask (id_obj); index = (uint32) PyInt_AsUnsignedLongMask (idx_obj); event_type = (uint32) PyInt_AsUnsignedLongMask (tp_obj); data_size = (uint32) PyInt_AsUnsignedLongMask (sz_obj); /* ** */ buffer = malloc (data_size); res = lib->GetEventData (file_id, entity_id, index, &time_stamp, buffer, data_size, &data_ret_size); if (check_result_is_error (res, lib)) { free (buffer); return NULL; } switch (event_type) { case ns_EVENT_TEXT: case ns_EVENT_CSV: data_obj = PyString_FromStringAndSize (buffer, data_ret_size); break; case ns_EVENT_BYTE: data_obj = PyInt_FromLong (uint8_from_data (buffer, data_ret_size)); break; case ns_EVENT_WORD: data_obj = PyInt_FromLong (uint16_from_data (buffer, data_ret_size)); break; case ns_EVENT_DWORD: data_obj = PyInt_FromLong (uint32_from_data (buffer, data_ret_size)); break; default: Py_INCREF (Py_None); data_obj = Py_None; } res_obj = Py_BuildValue ("(d,O)", time_stamp, data_obj); free (buffer); return res_obj; } static PyObject * do_get_analog_data (PyObject *self, PyObject *args, PyObject *kwds) { NsLibrary *lib; PyObject *cobj; PyObject *iobj, *id_obj, *idx_obj, *sz_obj; PyObject *res_obj; PyObject *array; PyObject *times; uint32 file_id; uint32 entity_id; uint32 index; uint32 count; uint32 cont_count; ns_RESULT res; void *buffer; npy_intp dims[1]; if (!PyArg_ParseTuple (args, "OOOOO", &cobj, &iobj, &id_obj, &idx_obj, &sz_obj)) { PyErr_SetString (PyExc_StandardError, "Could not parse arguments"); return NULL; } if (!PyCObject_Check (cobj) || !PyInt_Check (iobj) || !PyInt_Check (id_obj) || !PyInt_Check (idx_obj) || !PyInt_Check (sz_obj)) { PyErr_SetString (PyExc_TypeError, "Wrong argument type(s)"); return NULL; } lib = PyCObject_AsVoidPtr (cobj); file_id = (uint32) PyInt_AsUnsignedLongMask (iobj); entity_id = (uint32) PyInt_AsUnsignedLongMask (id_obj); index = (uint32) PyInt_AsUnsignedLongMask (idx_obj); count = (uint32) PyInt_AsUnsignedLongMask (sz_obj); /* ** */ dims[0] = count; //sample count array = PyArray_New (&PyArray_Type, 1, dims, NPY_DOUBLE, NULL, NULL /* data */, 0 /* itemsize */, NPY_ARRAY_CARRAY, NULL); buffer = PyArray_DATA ((PyArrayObject *) array); res = lib->GetAnalogData (file_id, entity_id, index, count, &cont_count, buffer); if (check_result_is_error (res, lib)) { Py_DECREF (array); return NULL; } times = get_times_for_entity (lib, file_id, entity_id, index, count); if (times == NULL) { Py_DECREF (array); return NULL; } res_obj = PyTuple_New (3); PyTuple_SetItem (res_obj, 0, array); PyTuple_SetItem (res_obj, 1, times); PyTuple_SetItem (res_obj, 2, PyInt_FromLong (cont_count)); return res_obj; } static PyObject * do_get_segment_data (PyObject *self, PyObject *args, PyObject *kwds) { NsLibrary *lib; PyObject *cobj; PyObject *iobj, *id_obj, *idx_obj, *sz_obj, *src_obj; PyObject *res_obj; PyObject *array; uint32 file_id; uint32 entity_id; uint32 index; uint32 count; uint32 sources; uint32 sample_count; uint32 uint_id; uint32 buffer_size; ns_RESULT res; double *buffer; npy_intp dims[2]; double time_stamp; if (!PyArg_ParseTuple (args, "OOOOOO", &cobj, &iobj, &id_obj, &idx_obj, &src_obj, &sz_obj)) { PyErr_SetString (PyExc_StandardError, "Could not parse arguments"); return NULL; } if (!PyCObject_Check (cobj) || !PyInt_Check (iobj) || !PyInt_Check (id_obj) || !PyInt_Check (idx_obj) || !PyInt_Check (sz_obj) || !PyInt_Check (src_obj)) { PyErr_SetString (PyExc_TypeError, "Wrong argument type(s)"); return NULL; } lib = PyCObject_AsVoidPtr (cobj); file_id = (uint32) PyInt_AsUnsignedLongMask (iobj); entity_id = (uint32) PyInt_AsUnsignedLongMask (id_obj); index = (uint32) PyInt_AsUnsignedLongMask (idx_obj); count = (uint32) PyInt_AsUnsignedLongMask (sz_obj); sources = (uint32) PyInt_AsUnsignedLongMask (src_obj); /* ** */ dims[0] = sources; //source count dims[1] = count; //sample count array = PyArray_New (&PyArray_Type, 2, dims, NPY_DOUBLE, NULL, NULL /* data */, 0 /* itemsize */, 0, NULL); buffer = (double *) PyArray_DATA ((PyArrayObject *) array); buffer_size = (uint32) PyArray_NBYTES ((PyArrayObject *) array); res = lib->GetSegmentData (file_id, entity_id, index, &time_stamp, buffer, buffer_size, &sample_count, &uint_id); if (check_result_is_error (res, lib)) { Py_DECREF (array); return NULL; } res_obj = PyTuple_New (4); PyTuple_SetItem (res_obj, 0, array); PyTuple_SetItem (res_obj, 1, PyFloat_FromDouble (time_stamp)); PyTuple_SetItem (res_obj, 2, PyInt_FromLong (sample_count)); PyTuple_SetItem (res_obj, 3, PyInt_FromLong (uint_id)); return res_obj; } static PyObject * do_get_neural_data (PyObject *self, PyObject *args, PyObject *kwds) { NsLibrary *lib; PyObject *cobj; PyObject *iobj, *id_obj, *idx_obj, *sz_obj; PyObject *array; uint32 file_id; uint32 entity_id; uint32 index; uint32 index_count; ns_RESULT res; void *buffer; npy_intp dims[1]; if (!PyArg_ParseTuple (args, "OOOOO", &cobj, &iobj, &id_obj, &idx_obj, &sz_obj)) { PyErr_SetString (PyExc_StandardError, "Could not parse arguments"); return NULL; } if (!PyCObject_Check (cobj) || !PyInt_Check (iobj) || !PyInt_Check (id_obj) || !PyInt_Check (idx_obj) || !PyInt_Check (sz_obj)) { PyErr_SetString (PyExc_TypeError, "Wrong argument type(s)"); return NULL; } lib = PyCObject_AsVoidPtr (cobj); file_id = (uint32) PyInt_AsUnsignedLongMask (iobj); entity_id = (uint32) PyInt_AsUnsignedLongMask (id_obj); index = (uint32) PyInt_AsUnsignedLongMask (idx_obj); index_count = (uint32) PyInt_AsUnsignedLongMask (sz_obj); /* ** */ dims[0] = index_count; array = PyArray_New (&PyArray_Type, 1, dims, NPY_DOUBLE, NULL, NULL /* data */, 0 /* itemsize */, NPY_ARRAY_CARRAY, NULL); buffer = PyArray_DATA ((PyArrayObject *) array); res = lib->GetNeuralData (file_id, entity_id, index, index_count, buffer); if (check_result_is_error (res, lib)) { Py_DECREF (array); return NULL; } return array; } static PyObject * do_get_index_by_time(PyObject *self, PyObject *args, PyObject *kwds) { NsLibrary *lib; PyObject *cobj; PyObject *iobj, *id_obj, *tp_obj, *fl_obj; double timepoint; uint32 file_id; uint32 entity_id; uint32 index; uint32 flags; ns_RESULT res; if (!PyArg_ParseTuple (args, "OOOOO", &cobj, &iobj, &id_obj, &tp_obj, &fl_obj)) { PyErr_SetString (PyExc_StandardError, "Could not parse arguments"); return NULL; } if (!PyCObject_Check (cobj) || !PyInt_Check (iobj) || !PyInt_Check (id_obj) || !PyFloat_Check (tp_obj) || !PyInt_Check (fl_obj)) { PyErr_SetString (PyExc_TypeError, "Wrong argument type(s)"); return NULL; } lib = PyCObject_AsVoidPtr (cobj); file_id = (uint32) PyInt_AsUnsignedLongMask (iobj); entity_id = (uint32) PyInt_AsUnsignedLongMask (id_obj); timepoint = PyFloat_AsDouble (tp_obj); flags = (uint32) PyInt_AsUnsignedLongMask (fl_obj); res = lib->GetIndexByTime (file_id, entity_id, timepoint, flags, &index); if (check_result_is_error (res, lib)) return NULL; return PyInt_FromLong (index); } static PyObject * do_get_time_by_index (PyObject *self, PyObject *args, PyObject *kwds) { NsLibrary *lib; PyObject *cobj; PyObject *iobj, *id_obj, *idx_obj; uint32 file_id; uint32 entity_id; uint32 index; double timepoint; ns_RESULT res; if (!PyArg_ParseTuple (args, "OOOO", &cobj, &iobj, &id_obj, &idx_obj)) { PyErr_SetString (PyExc_StandardError, "Could not parse arguments"); return NULL; } if (!PyCObject_Check (cobj) || !PyInt_Check (iobj) || !PyInt_Check (id_obj) || !PyInt_Check (idx_obj)) { PyErr_SetString (PyExc_TypeError, "Wrong argument type(s)"); return NULL; } lib = PyCObject_AsVoidPtr (cobj); file_id = (uint32) PyInt_AsUnsignedLongMask (iobj); entity_id = (uint32) PyInt_AsUnsignedLongMask (id_obj); index = (uint32) PyInt_AsUnsignedLongMask (idx_obj); res = lib->GetTimeByIndex (file_id, entity_id, index, &timepoint); if (check_result_is_error (res, lib)) return NULL; return Py_BuildValue ("d", timepoint); } static PyMethodDef NativeMethods[] = { {"library_open", (PyCFunction) library_open, METH_VARARGS | METH_KEYWORDS, "Open a Neuroshare Library"}, {"library_close", (PyCFunction) library_close, METH_VARARGS | METH_KEYWORDS, "Close an open Neuroshare Library"}, {"get_library_info", (PyCFunction) do_get_library_info, METH_VARARGS | METH_KEYWORDS, "Retrieves information about the loaded API library"}, {"open_file", (PyCFunction) do_open_file, METH_VARARGS | METH_KEYWORDS, "Opens the data file and returns its file info."}, {"close_file", (PyCFunction) do_close_file, METH_VARARGS | METH_KEYWORDS, "Close the open data file"}, {"get_entity_info", (PyCFunction) do_get_entity_info, METH_VARARGS | METH_KEYWORDS, "Retrieve Entity (general and specific) information"}, {"get_event_data", (PyCFunction) do_get_event_data, METH_VARARGS | METH_KEYWORDS, "Retrieve event data"}, {"get_analog_data", (PyCFunction) do_get_analog_data, METH_VARARGS | METH_KEYWORDS, "Retrieve analog data"}, {"get_segment_data", (PyCFunction) do_get_segment_data, METH_VARARGS | METH_KEYWORDS, "Retrieve segment data"}, {"get_neural_data", (PyCFunction) do_get_neural_data, METH_VARARGS | METH_KEYWORDS, "Retrieve analog data"}, {"get_time_by_index", (PyCFunction) do_get_time_by_index, METH_VARARGS | METH_KEYWORDS, "Timestamp of the index"}, {"get_index_by_time", (PyCFunction) do_get_index_by_time, METH_VARARGS | METH_KEYWORDS, "Index by timepoint"}, {NULL, NULL, 0, NULL} /* Sentinel */ }; PyMODINIT_FUNC init_capi(void) { PyObject *module; module = Py_InitModule ("neuroshare._capi", NativeMethods); if (module == NULL) return; PyModule_AddStringConstant (module, "__doc__", "neuroshare native (C) functions"); import_array (); PgError = PyErr_NewException ("_capi.error", NULL, NULL); Py_INCREF (PgError); PyModule_AddObject (module, "error", PgError); } python-neuroshare-0.9.2/doc/000077500000000000000000000000001234311067000157565ustar00rootroot00000000000000python-neuroshare-0.9.2/doc/Makefile000066400000000000000000000127611234311067000174250ustar00rootroot00000000000000# Makefile for Sphinx documentation # # You can set these variables from the command line. 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The HTML pages are in $(BUILDDIR)/html." dirhtml: $(SPHINXBUILD) -b dirhtml $(ALLSPHINXOPTS) $(BUILDDIR)/dirhtml @echo @echo "Build finished. The HTML pages are in $(BUILDDIR)/dirhtml." singlehtml: $(SPHINXBUILD) -b singlehtml $(ALLSPHINXOPTS) $(BUILDDIR)/singlehtml @echo @echo "Build finished. The HTML page is in $(BUILDDIR)/singlehtml." pickle: $(SPHINXBUILD) -b pickle $(ALLSPHINXOPTS) $(BUILDDIR)/pickle @echo @echo "Build finished; now you can process the pickle files." json: $(SPHINXBUILD) -b json $(ALLSPHINXOPTS) $(BUILDDIR)/json @echo @echo "Build finished; now you can process the JSON files." htmlhelp: $(SPHINXBUILD) -b htmlhelp $(ALLSPHINXOPTS) $(BUILDDIR)/htmlhelp @echo @echo "Build finished; now you can run HTML Help Workshop with the" \ ".hhp project file in $(BUILDDIR)/htmlhelp." qthelp: $(SPHINXBUILD) -b qthelp $(ALLSPHINXOPTS) $(BUILDDIR)/qthelp @echo @echo "Build finished; now you can run "qcollectiongenerator" with the" \ ".qhcp project file in $(BUILDDIR)/qthelp, like this:" @echo "# qcollectiongenerator $(BUILDDIR)/qthelp/Python-Neuroshare.qhcp" @echo "To view the help file:" @echo "# assistant -collectionFile $(BUILDDIR)/qthelp/Python-Neuroshare.qhc" devhelp: $(SPHINXBUILD) -b devhelp $(ALLSPHINXOPTS) $(BUILDDIR)/devhelp @echo @echo "Build finished." @echo "To view the help file:" @echo "# mkdir -p $$HOME/.local/share/devhelp/Python-Neuroshare" @echo "# ln -s $(BUILDDIR)/devhelp $$HOME/.local/share/devhelp/Python-Neuroshare" @echo "# devhelp" epub: $(SPHINXBUILD) -b epub $(ALLSPHINXOPTS) $(BUILDDIR)/epub @echo @echo "Build finished. The epub file is in $(BUILDDIR)/epub." latex: $(SPHINXBUILD) -b latex $(ALLSPHINXOPTS) $(BUILDDIR)/latex @echo @echo "Build finished; the LaTeX files are in $(BUILDDIR)/latex." @echo "Run \`make' in that directory to run these through (pdf)latex" \ "(use \`make latexpdf' here to do that automatically)." latexpdf: $(SPHINXBUILD) -b latex $(ALLSPHINXOPTS) $(BUILDDIR)/latex @echo "Running LaTeX files through pdflatex..." $(MAKE) -C $(BUILDDIR)/latex all-pdf @echo "pdflatex finished; the PDF files are in $(BUILDDIR)/latex." text: $(SPHINXBUILD) -b text $(ALLSPHINXOPTS) $(BUILDDIR)/text @echo @echo "Build finished. The text files are in $(BUILDDIR)/text." man: $(SPHINXBUILD) -b man $(ALLSPHINXOPTS) $(BUILDDIR)/man @echo @echo "Build finished. The manual pages are in $(BUILDDIR)/man." texinfo: $(SPHINXBUILD) -b texinfo $(ALLSPHINXOPTS) $(BUILDDIR)/texinfo @echo @echo "Build finished. The Texinfo files are in $(BUILDDIR)/texinfo." @echo "Run \`make' in that directory to run these through makeinfo" \ "(use \`make info' here to do that automatically)." info: $(SPHINXBUILD) -b texinfo $(ALLSPHINXOPTS) $(BUILDDIR)/texinfo @echo "Running Texinfo files through makeinfo..." make -C $(BUILDDIR)/texinfo info @echo "makeinfo finished; the Info files are in $(BUILDDIR)/texinfo." gettext: $(SPHINXBUILD) -b gettext $(I18NSPHINXOPTS) $(BUILDDIR)/locale @echo @echo "Build finished. The message catalogs are in $(BUILDDIR)/locale." changes: $(SPHINXBUILD) -b changes $(ALLSPHINXOPTS) $(BUILDDIR)/changes @echo @echo "The overview file is in $(BUILDDIR)/changes." linkcheck: $(SPHINXBUILD) -b linkcheck $(ALLSPHINXOPTS) $(BUILDDIR)/linkcheck @echo @echo "Link check complete; look for any errors in the above output " \ "or in $(BUILDDIR)/linkcheck/output.txt." doctest: $(SPHINXBUILD) -b doctest $(ALLSPHINXOPTS) $(BUILDDIR)/doctest @echo "Testing of doctests in the sources finished, look at the " \ "results in $(BUILDDIR)/doctest/output.txt." python-neuroshare-0.9.2/doc/make.bat000066400000000000000000000120071234311067000173630ustar00rootroot00000000000000@ECHO OFF REM Command file for Sphinx documentation if "%SPHINXBUILD%" == "" ( set SPHINXBUILD=sphinx-build ) set BUILDDIR=build set ALLSPHINXOPTS=-d %BUILDDIR%/doctrees %SPHINXOPTS% source set I18NSPHINXOPTS=%SPHINXOPTS% source if NOT "%PAPER%" == "" ( set ALLSPHINXOPTS=-D latex_paper_size=%PAPER% %ALLSPHINXOPTS% set I18NSPHINXOPTS=-D latex_paper_size=%PAPER% %I18NSPHINXOPTS% ) if "%1" == "" goto help if "%1" == "help" ( :help echo.Please use `make ^` where ^ is one of echo. html to make standalone HTML files echo. dirhtml to make HTML files named index.html in directories echo. singlehtml to make a single large HTML file echo. pickle to make pickle files echo. json to make JSON files echo. htmlhelp to make HTML files and a HTML help project echo. qthelp to make HTML files and a qthelp project echo. devhelp to make HTML files and a Devhelp project echo. epub to make an epub echo. latex to make LaTeX files, you can set PAPER=a4 or PAPER=letter echo. text to make text files echo. man to make manual pages echo. texinfo to make Texinfo files echo. gettext to make PO message catalogs echo. changes to make an overview over all changed/added/deprecated items echo. linkcheck to check all external links for integrity echo. doctest to run all doctests embedded in the documentation if enabled goto end ) if "%1" == "clean" ( for /d %%i in (%BUILDDIR%\*) do rmdir /q /s %%i del /q /s %BUILDDIR%\* goto end ) if "%1" == "html" ( %SPHINXBUILD% -b html %ALLSPHINXOPTS% %BUILDDIR%/html if errorlevel 1 exit /b 1 echo. echo.Build finished. The HTML pages are in %BUILDDIR%/html. goto end ) if "%1" == "dirhtml" ( %SPHINXBUILD% -b dirhtml %ALLSPHINXOPTS% %BUILDDIR%/dirhtml if errorlevel 1 exit /b 1 echo. echo.Build finished. The HTML pages are in %BUILDDIR%/dirhtml. goto end ) if "%1" == "singlehtml" ( %SPHINXBUILD% -b singlehtml %ALLSPHINXOPTS% %BUILDDIR%/singlehtml if errorlevel 1 exit /b 1 echo. echo.Build finished. The HTML pages are in %BUILDDIR%/singlehtml. goto end ) if "%1" == "pickle" ( %SPHINXBUILD% -b pickle %ALLSPHINXOPTS% %BUILDDIR%/pickle if errorlevel 1 exit /b 1 echo. echo.Build finished; now you can process the pickle files. goto end ) if "%1" == "json" ( %SPHINXBUILD% -b json %ALLSPHINXOPTS% %BUILDDIR%/json if errorlevel 1 exit /b 1 echo. echo.Build finished; now you can process the JSON files. goto end ) if "%1" == "htmlhelp" ( %SPHINXBUILD% -b htmlhelp %ALLSPHINXOPTS% %BUILDDIR%/htmlhelp if errorlevel 1 exit /b 1 echo. echo.Build finished; now you can run HTML Help Workshop with the ^ .hhp project file in %BUILDDIR%/htmlhelp. goto end ) if "%1" == "qthelp" ( %SPHINXBUILD% -b qthelp %ALLSPHINXOPTS% %BUILDDIR%/qthelp if errorlevel 1 exit /b 1 echo. echo.Build finished; now you can run "qcollectiongenerator" with the ^ .qhcp project file in %BUILDDIR%/qthelp, like this: echo.^> qcollectiongenerator %BUILDDIR%\qthelp\Python-Neuroshare.qhcp echo.To view the help file: echo.^> assistant -collectionFile %BUILDDIR%\qthelp\Python-Neuroshare.ghc goto end ) if "%1" == "devhelp" ( %SPHINXBUILD% -b devhelp %ALLSPHINXOPTS% %BUILDDIR%/devhelp if errorlevel 1 exit /b 1 echo. echo.Build finished. goto end ) if "%1" == "epub" ( %SPHINXBUILD% -b epub %ALLSPHINXOPTS% %BUILDDIR%/epub if errorlevel 1 exit /b 1 echo. echo.Build finished. The epub file is in %BUILDDIR%/epub. goto end ) if "%1" == "latex" ( %SPHINXBUILD% -b latex %ALLSPHINXOPTS% %BUILDDIR%/latex if errorlevel 1 exit /b 1 echo. echo.Build finished; the LaTeX files are in %BUILDDIR%/latex. goto end ) if "%1" == "text" ( %SPHINXBUILD% -b text %ALLSPHINXOPTS% %BUILDDIR%/text if errorlevel 1 exit /b 1 echo. echo.Build finished. The text files are in %BUILDDIR%/text. goto end ) if "%1" == "man" ( %SPHINXBUILD% -b man %ALLSPHINXOPTS% %BUILDDIR%/man if errorlevel 1 exit /b 1 echo. echo.Build finished. The manual pages are in %BUILDDIR%/man. goto end ) if "%1" == "texinfo" ( %SPHINXBUILD% -b texinfo %ALLSPHINXOPTS% %BUILDDIR%/texinfo if errorlevel 1 exit /b 1 echo. echo.Build finished. The Texinfo files are in %BUILDDIR%/texinfo. goto end ) if "%1" == "gettext" ( %SPHINXBUILD% -b gettext %I18NSPHINXOPTS% %BUILDDIR%/locale if errorlevel 1 exit /b 1 echo. echo.Build finished. The message catalogs are in %BUILDDIR%/locale. goto end ) if "%1" == "changes" ( %SPHINXBUILD% -b changes %ALLSPHINXOPTS% %BUILDDIR%/changes if errorlevel 1 exit /b 1 echo. echo.The overview file is in %BUILDDIR%/changes. goto end ) if "%1" == "linkcheck" ( %SPHINXBUILD% -b linkcheck %ALLSPHINXOPTS% %BUILDDIR%/linkcheck if errorlevel 1 exit /b 1 echo. echo.Link check complete; look for any errors in the above output ^ or in %BUILDDIR%/linkcheck/output.txt. goto end ) if "%1" == "doctest" ( %SPHINXBUILD% -b doctest %ALLSPHINXOPTS% %BUILDDIR%/doctest if errorlevel 1 exit /b 1 echo. echo.Testing of doctests in the sources finished, look at the ^ results in %BUILDDIR%/doctest/output.txt. goto end ) :end 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O“Á1Da=õ¶3eü-Ûü¤ªR‹0Àc¡¬¹¸TÑ^Ü …M¥ŠûMe·¯„c¸Ý±‹  ?!iSD#7“l/‚¸/H¥´,*x­ƒï£ >_“5aš,8§Áq‰!Ð¥6·á¿Ò°WÀ•έɲV¡ÔN'jiÒŽÞ8bœµA‹TZ48,Ç_Ý}éA¥GrPFÂД»ER¶Â8fy¾Îõ%Am8 mã`Aÿ€=^­•k;ýŽÖ-é×|ç¾oE"—¼ÇFC;¯rñˆ!s(Å-W³<"/BM¾”>JJku©¹N¨>hB¿‡‹XJ…jËÉ·|œt (`È—A/*†¦7Ê=«oóQÏ æ4‘‚ÎqŒl`쟗¡`TíGA€“Øi<è%‚W˸ú,¤»u‡&#Ô  0i){­iaÙ[ʱЖƒœw tú“/uò½›4Ù“°ÍçÒÇ…ß Ârâ¶”q7ÿU›7C ýä~Qþ~h¨OÉ)¸:×-PôbHA–«J*ŤÃBDÔp…Ž1†‘ò/Ö%êyõ»=AŸ£ˆâßàzc%Ǩ°ãµGóÅBž ¢=T!éq‚Àƒèl ¤=åâqòR­½1áå?ds7 o[&-¶ÅÜŒ9O-ê>ò7»»åhë U†ÍxM&IŸ‡’%{sF2ð§½5‘Lr4( ’—°WöðKÂdˆ¾0$¤ˆJõ›zé¼Ê½¯b,xô§‚&%=‡â$×÷}öPÿ ŸèèùÓÉkudÃÝVá7øC[ÐïFAú["E€öõ&=q¯ÀÒÈBW–zyõŒ¯q[ùéh|{…<eÁ‡š3 éâ-våá³60ô£÷+¦•r£îüJÝ‹×\t·WV:ÏïZ o_‰µ½w Óaé…þJ©Nž¼ÑP÷ ´wí6U¨«SƯü'UQ^ÝE¥ìýq*ëÃäÉ.˜]Èi­pX e”÷\ ŸV2¿ÇÃI×0BíÁ¬hê—R­ïO*ì'hèŒg¯7ßÖÖQWÁ qH‚¬fKJMÎÒÿêVóqõÜ ç•›, ³dh3Býí q«¦Û^æslw5¬ÖäLòûíÜÙ6L¥Q’ä‘ܺåÛÞœÅß?¤2í…~2MÞ:?áÇ—(y@°~ǪJ-:,(5ÝÚüYVBô¾›"k¬Üþ‹Ï‰ Ös—y‡»½bÙf?·Õp¶'%Z¿½æ#ÔFWª|U_t½_•2êV¨ã²A|>œc* É,C›Îü0çðÂýˆu=•>Kí ÔµWè‡r2mÚ#VUZI›:m4«EÃÒ$T¿U&[¨éÝk‹«ùÐyMÎPýpÒ5LpøÝßrÇÎjÒe!’‡˜2Î!„–ÈÀÀYóûÖt5Ÿ=äó8¼F9.EÛÖï› nÿÓ‡A¿ëˆÏÞ²&Õ{© DÛ4. ¹K ƒ@ÂBÛ?AYÀã*¸›°`§Ïr¾šýb§ N©kûø»þÜ$øìV´§‰`N€ÆÏWÄ)ÆÓ~²ú¦hYN)-@º˜Ü_\QžaPà³Ô»œ{+©ÆT+Ê:…!çvAcÂ$ÇK/߇0À¾êƒúîð;Új‚^ÛFŸ½y]÷ÑWN_©Îa¯þ`¯Bc²Q…ª[iȹHN• Ç}£A¹xàpŽZ¨Ï×Ü͇7Úk6×]úeWÓ~» ÒÒõ |ÿ>4ù’Í|pÑnæ÷œõYë1Ïë«îæCµî–£ éŸÝÇ^iH™pçk,à;*(Õ÷+S‹WÀõGÉóTÜ¢ý7«b½êÅÇ(µÂ¹:üö–ª ×þ‘ 6nnýø¹3±NÂI×U½¤eA KǃÁÀ)AP Ásv”€H¸pR;¿{×nnúû®Õß³º,í\ËÅï>.wTú—³|û-A“¶ „úPp+í]ÐFMzg?5.4²öêòÉK" n˜ Y(¼¶3¿ûƒÎý¿« ¸Ì>ÞXÃÊî Ï…Ä&ƒ…O4Œ2}Ô|}ò5lÌäüSxñ2\ÿóRÈr¹HbL ‡€˜Ð&ð$TîÀäΠ FuÚôG·êFÍ^I¨pQ¨§ÈdD׋Dræ`ò}3y{Ò/öU´}î&øöZë©uoñ8;ºˆåä›'ý®Î_š&®Ú ÷ö Qh¦@C¤Šc”RAÞù¥— H&?xhLºE  œe~ïF8ð‡î£/[¼Ýµ‘5w U%|o œúV¹^½0–a,à·7ý¥}çóG’ñü¶ÓëýPŽ)ù§²>ûgh´¯€¬ZL¨¢î Ѝ©WÈþÑÛ\þ/o—{äzqÀÔÛDr7|ø¶åä[GÝ-G,ñÞíåŒÀÚUmJ¦êºû¿÷™œ±3¿o@÷Ð…Õè‹\K<ŽªPŒbüFëÙCën|©¹«ñt×$Gkã™Î½/`À¶÷AÛÇœC/p-Nº®~¤LÈ)_òà⢩K1B2p Íj„&ä„©ZºZyÿ©O^ÛÑzöà1Cz~[õÞõ~^ƒý&g î4'h'c0•Ýž¦N‹ÆöiÐ׌(Ð0¥‘ÜëCbv1ù/!Ý®æÃ6GÝv|Å Òß_²úmÍ΀«“÷KŽ„ mÚ#‚«å0z|gÁbÔd,Y–ªÍ›Ž1é2¡ÿ¥Éù •²‚C$\ð] |f¶W½göšÏâö®•ù=]^s•eH?,Mæ¸4*¨²ôÅ ³t£feÃ3åÊ$S#jzàÑ¡ŠJÄ¢­ûØjsÀÙé }–ÕQ»-͙¬!‚:7}ÚÃöÚm]Ά=Íp®+^G*S¡JЦ‰ž©@@SÓ¦=œBjŒµ–N¤¸ZèµjsloGGÜ5C8‚^¾Û^P®†Oû´ä¤k˜!»tzθyw–O_ކÎcåA¥&:fUùŒTÙùƹšýê­mµ6^kƒ XIj”†œ¶ ärÝ;†W°× ‹Ëg©óz:¸¦•ã .²Ê•ªÔ"ì³!-m(T»TÓån9â´CWåsf–)Ti%!-dè9 éÑ@£¦Ëî¬ßã‚1 1i(^(x:N1¿sè™­JÕ]¯$‚ëBG. !·÷M¦nrÖï0¿{`IÊ9é~˜¸øA•)»Y{éQ“‡Œ’‘¡wv7ž VíYË·j888888’Nº88888888’HºxDzŽ$€“.Nº88888888†xpÔˆÒ9+ ™£ËM½u(Å>€ž*Žºƒ›»Ú«ñ$œtqô*QY|Í’lJ…â‰Ëî/Ì?3ŸP’N‰“=;u¦Ìó©¹%µ.kG}cÅn3¯5ŽÁ÷^È,.׳ F/{ê× …r´ù8‚é[(ÑS1¬F$fNÂH?ØQ{bã'zv»¥¹Æ øy %Ž€‡Œ!˜¹êi:ã®§f3Jþ“¶Œ0j²¥{”ñâ¶ÇˆáÇÜöî_¯ûÞ]ëæ'¯EŽ“.nH?üq¬o»ºèUá’˜ö¥„ {…þŒWLßòì?ÊrÆÏÐñ*äààààà88éƘzËce¥sW.‡—óZ¥ÄÑÞTü¥&APL5åŽ.Rªu^“7¤ÆÈ;½,mÔXÌ,ŸCú¶{¬ÀD°„‰D÷ŽA×t SN[D yÙð2ŠJN¶õ¢R ´åœ^›œtqDÀ¤å iùcDcù¸Ù–dÓ…ÅE ­†_ÕÃk¯MNº8"àÃ_~9ÐT± C@tË^T&TÑ—ü=Ö?yþŸAÆk“ƒƒƒƒƒƒ“.ލ û¡l#”Ö0)<B¸¨\h­ö:­ÿØøÓGíM'v3^7’Æh={ØÌ(Y_2û&¥ô8tL´iÎÕ v4ßñ^ÕŽµŸ u[ó©}<0*Ç G昱ê)…Zcú‰Kï›N¡g@«k(ah$oÒRµãíssË~ ;ôöoÚxÍqppppp xDú†ñ V E3–¥@;O†¦Î‡f×C7ðJÚáãšoüªÑÒ\Ãæ9888888éâààààààà¸zI7¤çàààààààH8éâàààààààऋƒƒƒƒƒƒƒƒ“.Nº88888888†xpTR2¾\p; x‰%äÆŠ®~sGkÀëqó¨ô1ÂQX2Žþbõ&ƒÞ`,„·YP´òGN(Íß{âÞæ#{?qóšâàààààèxœ.ò›7·fªTêy¥e“ EÊ#Œ±{@‡°ÁûúóÕgŽ8ìÖ+ì«xé'Ïøy­qppppppÒÅ'ûæ„ó™0mÖ x» zÃèiðZEE¤­Ew@ÏÀ”@{jϾõ…›glâµÇÁÁÁÁÁÑ?ÒÅ éG 2sò3˦Î\à W‹àÐ(DÚZD».´õÓÜn¤¤Êí…¥ãîúÍ›['òÚãàààààè8éa(¿fŽ™›7–R²ÊlàÞjYˉÔ>dÙPæÂ를988888úî½8Âðô~©?iú8x9Šø–L¬Â@Þs–µ¢™ðÍ2^ƒœtqÄŠÚMÆpëPÀSÅaÉÇdîåƒ/Ûy rpppppô|{qäÉS¡´µ‡‡‘Hq¸BZ° ”j(ÛyõqppppppÒÅþùûÿ V=p^îE"Å$¾E{ñ®Þ —¬8ôé»ÛÞ[s„× GÿÀ·Gv|°ži´úÆ` °eÒŒy: U7ÀáñPR{õÔlù œ‡rŠ0¶©¾æÌæ5ÿm¯ANº8âÄ–õ¯yü~ßaÞØ>f”ӌ’e„‘"B˜PŠÚO/- üß_}êøV»¥»â—ß}ÒÌkŽƒƒƒƒƒ£ÿàÁQG0æ,^AÿçkÐò*†q¹Ë„Ã**E£7Cßð}û‹wúíÞäµÅÁÁÁÁÁÑ?\‘žƒƒƒƒƒƒƒƒ#qøÿ š÷Á.«/ÚÜIEND®B`‚python-neuroshare-0.9.2/doc/source/_themes/000077500000000000000000000000001234311067000207025ustar00rootroot00000000000000python-neuroshare-0.9.2/doc/source/_themes/.gitignore000066400000000000000000000000311234311067000226640ustar00rootroot00000000000000*.pyc *.pyo .DS_Store *~ python-neuroshare-0.9.2/doc/source/_themes/LICENSE000066400000000000000000000033751234311067000217170ustar00rootroot00000000000000Copyright (c) 2010 by Armin Ronacher. Some rights reserved. Redistribution and use in source and binary forms of the theme, with or without modification, are permitted provided that the following conditions are met: * Redistributions of source code must retain the above copyright notice, this list of conditions and the following disclaimer. * Redistributions in binary form must reproduce the above copyright notice, this list of conditions and the following disclaimer in the documentation and/or other materials provided with the distribution. * The names of the contributors may not be used to endorse or promote products derived from this software without specific prior written permission. We kindly ask you to only use these themes in an unmodified manner just for Flask and Flask-related products, not for unrelated projects. If you like the visual style and want to use it for your own projects, please consider making some larger changes to the themes (such as changing font faces, sizes, colors or margins). THIS THEME IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS THEME, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. python-neuroshare-0.9.2/doc/source/_themes/README.md000066400000000000000000000024561234311067000221700ustar00rootroot00000000000000#G-Node Sphinx Styles This repo is home to in-house [Sphinx](http://sphinx.pocoo.org) themes used by the [German INCF Node](http://www.g-node.org). Their basic design is derived from [Flask](http://flask.pocoo.org)'s documentation. If you want to use it in your projects, follow these steps: 1. Set up a git submodule in your documentation folder under '_themes' that checks out the contents of this repository, or copy the files by hand. 2. Adjust your conf.py as follows: sys.path.append(os.path.abspath('_themes')) html_theme_path = ['_themes'] html_theme = 'gnode' The following themes currently exist: - _gnode_ - _gnode_small_ - Smaller version of the fully-fledged theme for one-page documentation. Following Flask's themes, a number of options exist for _gnode_ themes: [options] index_logo = '' filename of a picture in _static to be used as replacement for the h1 in the index.rst file. index_logo_height = 120px height of the index logo github_fork = '' repository name on github for the "fork me" badge __Acknowledgements__: Many thanks to Armin Ronacher for publishing and open-sourcing the templates.python-neuroshare-0.9.2/doc/source/_themes/gnode/000077500000000000000000000000001234311067000217765ustar00rootroot00000000000000python-neuroshare-0.9.2/doc/source/_themes/gnode/layout.html000066400000000000000000000013561234311067000242060ustar00rootroot00000000000000{%- extends "basic/layout.html" %} {%- block extrahead %} {{ super() }} {% if theme_touch_icon %} {% endif %} {% endblock %} {%- block relbar2 %}{% endblock %} {% block header %} {{ super() }} {% if pagename == 'index' %}
{% endif %} {% endblock %} {%- block footer %} {% if pagename == 'index' %}
{% endif %} {%- endblock %} python-neuroshare-0.9.2/doc/source/_themes/gnode/relations.html000066400000000000000000000011161234311067000246630ustar00rootroot00000000000000

Related Topics

python-neuroshare-0.9.2/doc/source/_themes/gnode/static/000077500000000000000000000000001234311067000232655ustar00rootroot00000000000000python-neuroshare-0.9.2/doc/source/_themes/gnode/static/flasky.css_t000066400000000000000000000144441234311067000256220ustar00rootroot00000000000000/* * flasky.css_t * ~~~~~~~~~~~~ * * :copyright: Copyright 2010 by Armin Ronacher. * :license: Flask Design License, see LICENSE for details. */ {% set page_width = '940px' %} {% set sidebar_width = '220px' %} @import url("basic.css"); /* -- page layout ----------------------------------------------------------- */ body { font-family: 'Georgia', serif; font-size: 17px; background-color: white; color: #000; margin: 0; padding: 0; } div.document { width: {{ page_width }}; margin: 30px auto 0 auto; } div.documentwrapper { float: left; width: 100%; } div.bodywrapper { margin: 0 0 0 {{ sidebar_width }}; } div.sphinxsidebar { width: {{ sidebar_width }}; } hr { border: 1px solid #B1B4B6; } div.body { background-color: #ffffff; color: #3E4349; padding: 0 30px 0 30px; } img.floatingflask { padding: 0 0 10px 10px; float: right; } div.footer { width: {{ page_width }}; margin: 20px auto 30px auto; font-size: 14px; color: #888; text-align: right; } div.footer a { color: #888; } div.related { display: none; } div.sphinxsidebar a { color: #444; text-decoration: none; border-bottom: 1px dotted #999; } div.sphinxsidebar a:hover { border-bottom: 1px solid #999; } div.sphinxsidebar { font-size: 14px; line-height: 1.5; } div.sphinxsidebarwrapper { padding: 18px 10px; } div.sphinxsidebarwrapper p.logo { padding: 0 0 20px 0; margin: 0; text-align: center; } div.sphinxsidebar h3, div.sphinxsidebar h4 { font-family: 'Garamond', 'Georgia', serif; color: #444; font-size: 24px; font-weight: normal; margin: 0 0 5px 0; padding: 0; } div.sphinxsidebar h4 { font-size: 20px; } div.sphinxsidebar h3 a { color: #444; } div.sphinxsidebar p.logo a, div.sphinxsidebar h3 a, div.sphinxsidebar p.logo a:hover, div.sphinxsidebar h3 a:hover { border: none; } div.sphinxsidebar p { color: #555; margin: 10px 0; } div.sphinxsidebar ul { margin: 10px 0; padding: 0; color: #000; } div.sphinxsidebar input { border: 1px solid #ccc; font-family: 'Georgia', serif; font-size: 1em; } /* -- body styles ----------------------------------------------------------- */ a { color: #004B6B; text-decoration: underline; } a:hover { color: #6D4100; text-decoration: underline; } div.body h1, div.body h2, div.body h3, div.body h4, div.body h5, div.body h6 { font-family: 'Garamond', 'Georgia', serif; font-weight: normal; margin: 30px 0px 10px 0px; padding: 0; } {% if theme_index_logo %} div.indexwrapper h1 { text-indent: -999999px; background: url({{ theme_index_logo }}) no-repeat center center; height: {{ theme_index_logo_height }}; } {% endif %} div.body h1 { margin-top: 0; padding-top: 0; font-size: 240%; } div.body h2 { font-size: 180%; } div.body h3 { font-size: 150%; } div.body h4 { font-size: 130%; } div.body h5 { font-size: 100%; } div.body h6 { font-size: 100%; } a.headerlink { color: #ddd; padding: 0 4px; text-decoration: none; } a.headerlink:hover { color: #444; background: #eaeaea; } div.body p, div.body dd, div.body li { line-height: 1.4em; } div.admonition { background: #fafafa; margin: 20px -30px; padding: 10px 30px; border-top: 1px solid #ccc; border-bottom: 1px solid #ccc; } div.admonition tt.xref, div.admonition a tt { border-bottom: 1px solid #fafafa; } dd div.admonition { margin-left: -60px; padding-left: 60px; } div.admonition p.admonition-title { font-family: 'Garamond', 'Georgia', serif; font-weight: normal; font-size: 24px; margin: 0 0 10px 0; padding: 0; line-height: 1; } div.admonition p.last { margin-bottom: 0; } div.highlight { background-color: white; } dt:target, .highlight { background: #FAF3E8; } div.note { background-color: #eee; border: 1px solid #ccc; } div.seealso { background-color: #ffc; border: 1px solid #ff6; } div.topic { background-color: #eee; } p.admonition-title { display: inline; } p.admonition-title:after { content: ":"; } pre, tt { font-family: 'Consolas', 'Menlo', 'Deja Vu Sans Mono', 'Bitstream Vera Sans Mono', monospace; font-size: 0.9em; } img.screenshot { } tt.descname, tt.descclassname { font-size: 0.95em; } tt.descname { padding-right: 0.08em; } img.screenshot { -moz-box-shadow: 2px 2px 4px #eee; -webkit-box-shadow: 2px 2px 4px #eee; box-shadow: 2px 2px 4px #eee; } table.docutils { border: 1px solid #888; -moz-box-shadow: 2px 2px 4px #eee; -webkit-box-shadow: 2px 2px 4px #eee; box-shadow: 2px 2px 4px #eee; } table.docutils td, table.docutils th { border: 1px solid #888; padding: 0.25em 0.7em; } table.field-list, table.footnote { border: none; -moz-box-shadow: none; -webkit-box-shadow: none; box-shadow: none; } table.footnote { margin: 15px 0; width: 100%; border: 1px solid #eee; background: #fdfdfd; font-size: 0.9em; } table.footnote + table.footnote { margin-top: -15px; border-top: none; } table.field-list th { padding: 0 0.8em 0 0; } table.field-list td { padding: 0; } table.footnote td.label { width: 0px; padding: 0.3em 0 0.3em 0.5em; } table.footnote td { padding: 0.3em 0.5em; } dl { margin: 0; padding: 0; } dl dd { margin-left: 30px; } blockquote { margin: 0 0 0 30px; padding: 0; } ul, ol { margin: 10px 0 10px 30px; padding: 0; } pre { background: #eee; padding: 7px 30px; margin: 15px -30px; line-height: 1.3em; } dl pre, blockquote pre, li pre { margin-left: -60px; padding-left: 60px; } dl dl pre { margin-left: -90px; padding-left: 90px; } tt { background-color: #ecf0f3; color: #222; /* padding: 1px 2px; */ } tt.xref, a tt { background-color: #FBFBFB; border-bottom: 1px solid white; } a.reference { text-decoration: none; border-bottom: 1px dotted #004B6B; } a.reference:hover { border-bottom: 1px solid #6D4100; } a.footnote-reference { text-decoration: none; font-size: 0.7em; vertical-align: top; border-bottom: 1px dotted #004B6B; } a.footnote-reference:hover { border-bottom: 1px solid #6D4100; } a:hover tt { background: #EEE; } python-neuroshare-0.9.2/doc/source/_themes/gnode/static/small_flask.css000066400000000000000000000017201234311067000262670ustar00rootroot00000000000000/* * small_flask.css_t * ~~~~~~~~~~~~~~~~~ * * :copyright: Copyright 2010 by Armin Ronacher. * :license: Flask Design License, see LICENSE for details. */ body { margin: 0; padding: 20px 30px; } div.documentwrapper { float: none; background: white; } div.sphinxsidebar { display: block; float: none; width: 102.5%; margin: 50px -30px -20px -30px; padding: 10px 20px; background: #333; color: white; } div.sphinxsidebar h3, div.sphinxsidebar h4, div.sphinxsidebar p, div.sphinxsidebar h3 a { color: white; } div.sphinxsidebar a { color: #aaa; } div.sphinxsidebar p.logo { display: none; } div.document { width: 100%; margin: 0; } div.related { display: block; margin: 0; padding: 10px 0 20px 0; } div.related ul, div.related ul li { margin: 0; padding: 0; } div.footer { display: none; } div.bodywrapper { margin: 0; } div.body { min-height: 0; padding: 0; } python-neuroshare-0.9.2/doc/source/_themes/gnode/theme.conf000066400000000000000000000002401234311067000237430ustar00rootroot00000000000000[theme] inherit = basic stylesheet = flasky.css pygments_style = gnode_theme_support.FlaskyStyle [options] index_logo = index_logo_height = 120px touch_icon = python-neuroshare-0.9.2/doc/source/_themes/gnode_small/000077500000000000000000000000001234311067000231665ustar00rootroot00000000000000python-neuroshare-0.9.2/doc/source/_themes/gnode_small/layout.html000066400000000000000000000012531234311067000253720ustar00rootroot00000000000000{% extends "basic/layout.html" %} {% block header %} {{ super() }} {% if pagename == 'index' %}
{% endif %} {% endblock %} {% block footer %} {% if pagename == 'index' %}
{% endif %} {% endblock %} {# do not display relbars #} {% block relbar1 %}{% endblock %} {% block relbar2 %} {% if theme_github_fork %} Fork me on GitHub {% endif %} {% endblock %} {% block sidebar1 %}{% endblock %} {% block sidebar2 %}{% endblock %} python-neuroshare-0.9.2/doc/source/_themes/gnode_small/static/000077500000000000000000000000001234311067000244555ustar00rootroot00000000000000python-neuroshare-0.9.2/doc/source/_themes/gnode_small/static/flasky.css_t000066400000000000000000000107771234311067000270170ustar00rootroot00000000000000/* * flasky.css_t * ~~~~~~~~~~~~ * * Sphinx stylesheet -- flasky theme based on nature theme. * * :copyright: Copyright 2007-2010 by the Sphinx team, see AUTHORS. * :license: BSD, see LICENSE for details. * */ @import url("basic.css"); /* -- page layout ----------------------------------------------------------- */ body { font-family: 'Georgia', serif; font-size: 17px; color: #000; background: white; margin: 0; padding: 0; } div.documentwrapper { float: left; 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} table.field-list td { padding: 0; } table.footnote td { padding: 0.5em; } dl { margin: 0; padding: 0; } dl dd { margin-left: 30px; } pre { padding: 0; margin: 15px 0px; padding: 8px; line-height: 1.3em; padding: 7px 30px; background: #eee; border-radius: 2px; -moz-border-radius: 2px; -webkit-border-radius: 2px; } dl pre { margin-left: 0px; padding-left: 30px; } tt { background-color: #ecf0f3; color: #222; /* padding: 1px 2px; */ } tt.xref, a tt { background-color: #FBFBFB; } a:hover tt { background: #EEE; } python-neuroshare-0.9.2/doc/source/_themes/gnode_small/theme.conf000066400000000000000000000003131234311067000251340ustar00rootroot00000000000000[theme] inherit = basic stylesheet = flasky.css nosidebar = true pygments_style = gnode_theme_support.FlaskyStyle [options] index_logo = index_logo_height = 120px github_fork = G-Node/python-neuroshare python-neuroshare-0.9.2/doc/source/_themes/gnode_theme_support.py000066400000000000000000000113111234311067000253230ustar00rootroot00000000000000from pygments.style import Style from pygments.token import Keyword, Name, Comment, String, Error, \ Number, Operator, Generic, Whitespace, Punctuation, Other, Literal class FlaskyStyle(Style): background_color = "#f8f8f8" default_style = "" styles = { # No corresponding class for the following: #Text: "", # class: '' Whitespace: "underline #f8f8f8", # class: 'w' Error: "#a40000 border:#ef2929", # class: 'err' Other: "#000000", # class 'x' Comment: "italic #8f5902", # class: 'c' Comment.Preproc: "noitalic", # class: 'cp' Keyword: "bold #004461", # class: 'k' Keyword.Constant: "bold #004461", # class: 'kc' Keyword.Declaration: "bold #004461", # class: 'kd' Keyword.Namespace: "bold #004461", # class: 'kn' Keyword.Pseudo: "bold #004461", # class: 'kp' Keyword.Reserved: "bold #004461", # class: 'kr' Keyword.Type: "bold #004461", # class: 'kt' Operator: "#582800", # class: 'o' Operator.Word: "bold #004461", # class: 'ow' - like keywords Punctuation: "bold #000000", # class: 'p' # because special names such as Name.Class, Name.Function, etc. # are not recognized as such later in the parsing, we choose them # to look the same as ordinary variables. Name: "#000000", # class: 'n' Name.Attribute: "#c4a000", # class: 'na' - to be revised Name.Builtin: "#004461", # class: 'nb' Name.Builtin.Pseudo: "#3465a4", # class: 'bp' Name.Class: "#000000", # class: 'nc' - to be revised Name.Constant: "#000000", # class: 'no' - to be revised Name.Decorator: "#888", # class: 'nd' - to be revised Name.Entity: "#ce5c00", # class: 'ni' Name.Exception: "bold #cc0000", # class: 'ne' Name.Function: "#000000", # class: 'nf' Name.Property: "#000000", # class: 'py' Name.Label: "#f57900", # class: 'nl' Name.Namespace: "#000000", # class: 'nn' - to be revised Name.Other: "#000000", # class: 'nx' Name.Tag: "bold #004461", # class: 'nt' - like a keyword Name.Variable: "#000000", # class: 'nv' - to be revised Name.Variable.Class: "#000000", # class: 'vc' - to be revised Name.Variable.Global: "#000000", # class: 'vg' - to be revised Name.Variable.Instance: "#000000", # class: 'vi' - to be revised Number: "#990000", # class: 'm' Literal: "#000000", # class: 'l' Literal.Date: "#000000", # class: 'ld' String: "#4e9a06", # class: 's' String.Backtick: "#4e9a06", # class: 'sb' String.Char: "#4e9a06", # class: 'sc' String.Doc: "italic #8f5902", # class: 'sd' - like a comment String.Double: "#4e9a06", # class: 's2' String.Escape: "#4e9a06", # class: 'se' String.Heredoc: "#4e9a06", # class: 'sh' String.Interpol: "#4e9a06", # class: 'si' String.Other: "#4e9a06", # class: 'sx' String.Regex: "#4e9a06", # class: 'sr' String.Single: "#4e9a06", # class: 's1' String.Symbol: "#4e9a06", # class: 'ss' Generic: "#000000", # class: 'g' Generic.Deleted: "#a40000", # class: 'gd' Generic.Emph: "italic #000000", # class: 'ge' Generic.Error: "#ef2929", # class: 'gr' Generic.Heading: "bold #000080", # class: 'gh' Generic.Inserted: "#00A000", # class: 'gi' Generic.Output: "#888", # class: 'go' Generic.Prompt: "#745334", # class: 'gp' Generic.Strong: "bold #000000", # class: 'gs' Generic.Subheading: "bold #800080", # class: 'gu' Generic.Traceback: "bold #a40000", # class: 'gt' } python-neuroshare-0.9.2/doc/source/conf.py000066400000000000000000000176501234311067000205660ustar00rootroot00000000000000# -*- coding: utf-8 -*- # # Python-Neuroshare documentation build configuration file, created by # sphinx-quickstart on Wed Jul 31 15:22:11 2013. # # This file is execfile()d with the current directory set to its containing dir. # # Note that not all possible configuration values are present in this # autogenerated file. # # All configuration values have a default; values that are commented out # serve to show the default. import sys, os, pkg_resources # If extensions (or modules to document with autodoc) are in another directory, # add these directories to sys.path here. If the directory is relative to the # documentation root, use os.path.abspath to make it absolute, like shown here. #sys.path.insert(0, os.path.abspath('.')) # -- General configuration ----------------------------------------------------- # If your documentation needs a minimal Sphinx version, state it here. #needs_sphinx = '1.0' # Add any Sphinx extension module names here, as strings. They can be extensions # coming with Sphinx (named 'sphinx.ext.*') or your custom ones. extensions = ['sphinx.ext.autodoc', 'sphinx.ext.coverage', 'sphinx.ext.ifconfig', 'sphinx.ext.intersphinx'] # Add any paths that contain templates here, relative to this directory. templates_path = ['_templates'] # The suffix of source filenames. source_suffix = '.rst' # The encoding of source files. #source_encoding = 'utf-8-sig' # The master toctree document. master_doc = 'index' # General information about the project. project = u'Python-Neuroshare' copyright = u'2013, Christian Kellner' # The version info for the project you're documenting, acts as replacement for # |version| and |release|, also used in various other places throughout the # built documents. # # The short X.Y version. version = '1.0' # The full version, including alpha/beta/rc tags. release = '' # The language for content autogenerated by Sphinx. Refer to documentation # for a list of supported languages. #language = None # There are two options for replacing |today|: either, you set today to some # non-false value, then it is used: #today = '' # Else, today_fmt is used as the format for a strftime call. #today_fmt = '%B %d, %Y' # List of patterns, relative to source directory, that match files and # directories to ignore when looking for source files. exclude_patterns = [] # The reST default role (used for this markup: `text`) to use for all documents. #default_role = None # If true, '()' will be appended to :func: etc. cross-reference text. #add_function_parentheses = True # If true, the current module name will be prepended to all description # unit titles (such as .. function::). #add_module_names = True # If true, sectionauthor and moduleauthor directives will be shown in the # output. They are ignored by default. #show_authors = False # The name of the Pygments (syntax highlighting) style to use. pygments_style = 'sphinx' # A list of ignored prefixes for module index sorting. #modindex_common_prefix = [] # -- Options for HTML output --------------------------------------------------- # The theme to use for HTML and HTML Help pages. See the documentation for # a list of builtin themes. sys.path.append(os.path.abspath('_themes')) html_theme = 'gnode_small' # Theme options are theme-specific and customize the look and feel of a theme # further. For a list of options available for each theme, see the # documentation. #html_theme_options = {} # Add any paths that contain custom themes here, relative to this directory. html_theme_path = ['_themes'] # The name for this set of Sphinx documents. If None, it defaults to # " v documentation". #html_title = None # A shorter title for the navigation bar. Default is the same as html_title. #html_short_title = None # The name of an image file (relative to this directory) to place at the top # of the sidebar. #html_logo = None # The name of an image file (within the static path) to use as favicon of the # docs. This file should be a Windows icon file (.ico) being 16x16 or 32x32 # pixels large. #html_favicon = None # Add any paths that contain custom static files (such as style sheets) here, # relative to this directory. They are copied after the builtin static files, # so a file named "default.css" will overwrite the builtin "default.css". html_static_path = ['_static'] # If not '', a 'Last updated on:' timestamp is inserted at every page bottom, # using the given strftime format. #html_last_updated_fmt = '%b %d, %Y' # If true, SmartyPants will be used to convert quotes and dashes to # typographically correct entities. #html_use_smartypants = True # Custom sidebar templates, maps document names to template names. #html_sidebars = {} # Additional templates that should be rendered to pages, maps page names to # template names. #html_additional_pages = {} # If false, no module index is generated. #html_domain_indices = True # If false, no index is generated. #html_use_index = True # If true, the index is split into individual pages for each letter. #html_split_index = False # If true, links to the reST sources are added to the pages. #html_show_sourcelink = True # If true, "Created using Sphinx" is shown in the HTML footer. Default is True. html_show_sphinx = True # If true, "(C) Copyright ..." is shown in the HTML footer. Default is True. html_show_copyright = True # If true, an OpenSearch description file will be output, and all pages will # contain a tag referring to it. The value of this option must be the # base URL from which the finished HTML is served. #html_use_opensearch = '' # This is the file name suffix for HTML files (e.g. ".xhtml"). #html_file_suffix = None # Output file base name for HTML help builder. htmlhelp_basename = 'Python-Neurosharedoc' # -- Options for LaTeX output -------------------------------------------------- latex_elements = { # The paper size ('letterpaper' or 'a4paper'). #'papersize': 'letterpaper', # The font size ('10pt', '11pt' or '12pt'). #'pointsize': '10pt', # Additional stuff for the LaTeX preamble. #'preamble': '', } # Grouping the document tree into LaTeX files. List of tuples # (source start file, target name, title, author, documentclass [howto/manual]). latex_documents = [ ('index', 'Python-Neuroshare.tex', u'Python-Neuroshare Documentation', u'Christian Kellner', 'manual'), ] # The name of an image file (relative to this directory) to place at the top of # the title page. #latex_logo = None # For "manual" documents, if this is true, then toplevel headings are parts, # not chapters. #latex_use_parts = False # If true, show page references after internal links. #latex_show_pagerefs = False # If true, show URL addresses after external links. #latex_show_urls = False # Documents to append as an appendix to all manuals. #latex_appendices = [] # If false, no module index is generated. #latex_domain_indices = True # -- Options for manual page output -------------------------------------------- # One entry per manual page. List of tuples # (source start file, name, description, authors, manual section). man_pages = [ ('index', 'python-neuroshare', u'Python-Neuroshare Documentation', [u'Christian Kellner'], 1) ] # If true, show URL addresses after external links. #man_show_urls = False # -- Options for Texinfo output ------------------------------------------------ # Grouping the document tree into Texinfo files. List of tuples # (source start file, target name, title, author, # dir menu entry, description, category) texinfo_documents = [ ('index', 'Python-Neuroshare', u'Python-Neuroshare Documentation', u'Christian Kellner', 'Python-Neuroshare', 'One line description of project.', 'Miscellaneous'), ] # Documents to append as an appendix to all manuals. #texinfo_appendices = [] # If false, no module index is generated. #texinfo_domain_indices = True # How to display URL addresses: 'footnote', 'no', or 'inline'. #texinfo_show_urls = 'footnote' intersphinx_mapping = { 'http://docs.python.org/2.7' : None, 'http://docs.scipy.org/doc/numpy': None } python-neuroshare-0.9.2/doc/source/index.rst000066400000000000000000000171551234311067000211300ustar00rootroot00000000000000.. Python-Neuroshare documentation master file .. currentmodule:: neuroshare Python Bindings for Neuroshare ============================== The Neuroshare API is a standardized interface to access electrophysiology data stored in various different file formats. To do so, it uses format- specific shared libraries. Refer to the official website http://neuroshare.org for more information. The aim of this library is to provide a high level interface to the Neuroshare API, i.e. it focuses on API usability more then being a mere python version of the C API. Thus none of the original Neuroshare API calls are directly exposed but the interface consists of python objects that resemble (more or less) the Neuroshare Entities. Installation ------------ The compile-time requirements for python-neuroshare are the 'setuptools' and the Python development files and a working C compiler (clang or gcc) and NumPy. For Debian based distributions, e.g. Ubuntu, this can easily be done with:: $ sudo apt-get install clang python-setuptools \ python-dev python-numpy After that, python-neuroshare is installed with the following command:: $ sudo python setup.py install Additional runtime dependencies: * The Neuroshare vendor DLLs for the specific data file(s)! Please refer to the following section for more information. Installation of vendor DLLs *************************** Python-neuroshare relies on the vendor specific DLLs to access data files. Therefore the specific DLLs for each type of file must be downloaded and installed into one of the following locations:: /usr/local/lib/neuroshare /usr/lib/neuroshare ~/.neuroshare A (possibly incomplete) list of the vendor specific DLLs can be obtained be obtained from the neuroshare website: http://neuroshare.sourceforge.net/DLLLinks.shtml Please note that you need the corresponding DLLs for your platform (e.g. Linux, 64-bit). If you find yourself in the situation that there is no DLL for your specific platform and you are either on a UNIX-like system you can use G-Node's very one nswineproxy component to use the Windows 32 bit DLLs. Please refer to the nswineproxy homepage for more information: https://github.com/G-Node/nswineproxy Quickstart ---------- Opening a file:: import neuroshare as ns fd = ns.File ("NeuroshareExample.mcd") Iterate over the entities in the file:: for entity in fd.list_entities(): print entity.label, entity.entity_type ... do something else with entity ... Access analog signal data:: analog1 = fd.entities[1] #open analog signal entity data, times, count = analog1.get_data() #load data data will contain the raw data, times the timepoints of each datapoint and count how many datapoints in data are actually continous. Reporting Bugs & Submitting Patches ----------------------------------- Any bugs can and should be filed to the project's issue tracker at github: https://github.com/G-Node/python-neuroshare/issues Contact & Support ----------------- Support and discussion of python-neuroshare related questions happen in the official G-Node IRC channel #gnode on the freenode IRC network (cf. http://freenode.net). User's Guide ============ File structure and Entities --------------------------- Neuroshare provides access to raw data and metadata (such as the sampling rate and creation date) via so called Entities, which groups data of the same type together. The standard defines 4 different entities: Events, Analog signals, Segments and Neural entities (i.e. spiketrains): .. image:: _static/entities.png :width: 580px :align: center Event entities represent specific timepoints with associated data, e.g. trigger events. Analog signal entities represents continuously sampled, i.e. digitized, analog data. Examples are waveforms recorded via an electrode (microelectrodes, EKG, EEG). Segment entities contain cutouts of continuously sampled analog signals from one or more sources that are usually short in time. Most prominent example are waveforms of action potentials from one ore more electrodes. Neural entities are arrays of timestamps when action potentials happened, i.e. arrays of spike times. Data access ----------- All entities in the file are accessed by their entity index. Each individual entity can have one or more data entries attached to it; these are indetified by a sequential index. .. image:: _static/data_schema.png :width: 580px :align: center API --- The basic desgin of the API closely follows the Neuroshare entity model. For all 4 entities there is a class that represents that entity: * :class:`EventEntity` for Events * :class:`AnalogEntity` for Analog signal entities * :class:`SegmentEntity` for Segements * :class:`NeuralEntity` for Neural entities All entity classes derive from a common :class:`Entity` class that provides metadata common to all entites such as the label (:func:`Entity.label`) and how many data entries are contained in the entity (:func:`Entity.item_count` or just ``len(entity)``). Opening a file is simply done by creating a :class:`neuroshare.File` object with the path to the datafile as constructor argument: ``fd = neuroshare.File('data.mcd')``. Individual enitities can be accessed via the :func:`File.get_entity` function or via indexing through the :func:`File.entities` property (e.g. ``File.entities[idx]``). Data is accessed via the ``get_data()`` function that all 4 entities provide. Consult the documentation of the individual functions for details. Code Examples ------------- List entities in a file *********************** How to list all entities in a file called `data.mcd`:: import neuroshare as ns fd = ns.File('data.mcd') for i, entity in enumerate(fd.entities): print('%04d: "%s" type: %d' % (i, entity.label, entity.entity_type)) This will produces the following output:: 0000: "trig0001 0000 0000 trig0001" type: 1 0001: "elec0001 0000 0000 01" type: 2 0002: "elec0001 0001 0001 02" type: 2 0003: "elec0001 0002 0002 03" type: 2 [...] Access the raw data inside an analog signal entity ************************************************** To access the data and timestamps of an analog entity the :func:`AnalogEntity.get_data` is used:: analog1 = fd.entities[1] #access the entity 1 #now load all the raw data data, timestamps, cont_count = analog1.get_data() The ``data`` value is a ``3-tuple`` which contains the raw data and the timestamps for each datapoint. It is also possible to retrieve a subset of the available data:: data = analog1.get_data(20, 10) #fetch 10 elements starting at index 20 print("%d" % data[0].shape) # -> 10 print (data[0]) # -> # [ 8.50000000e-05 7.00000000e-05 2.16666667e-05 3.16666667e-05 # 3.66666667e-05 0.00000000e+00 -5.50000000e-05 -9.33333333e-05 # -6.66666667e-05 3.33333333e-06] Metadata ******** Metadata is exposed as python properties of the individual entities:: print(analog1.units) # -> 'V' print(analog1.sample_rate) # -> 25000.0 API Reference ============= File ---- .. autoclass:: File :members: Entity ------ .. autoclass:: Entity :members: Event Entity ------------ .. autoclass:: EventEntity :members: Analog Entity ------------- .. autoclass:: AnalogEntity :members: Neural Entity ------------- .. autoclass:: NeuralEntity :members: Segment Entity -------------- .. autoclass:: SegmentEntity :members: Indices and tables ================== * :ref:`genindex` * :ref:`modindex` * :ref:`search` *(c) 2013 Christian Kellner and the German Neuroinformatics Node* .. image:: _static/gnode_logo.png :width: 200px :align: center :target: http://www.g-node.org python-neuroshare-0.9.2/neuroshare/000077500000000000000000000000001234311067000173645ustar00rootroot00000000000000python-neuroshare-0.9.2/neuroshare/AnalogEntity.py000066400000000000000000000063271234311067000223440ustar00rootroot00000000000000 from Entity import Entity class AnalogEntity(Entity): """:class:`Entity` that represents continuously sampled, i.e. digitized, analog data. Examples are waveforms recorded via an electrode (microelectrodes, EKG, EEG). Actual data can be accessed via the :func:`get_data` function. .. note:: data may contain gaps (e.g. when no data is recorded between trails) """ def __init__(self, nsfile, eid, info): super(AnalogEntity, self).__init__(eid, nsfile, info) @property def sample_rate(self): """Sampling rate (in Hz).""" return self._info['SampleRate'] @property def min_value(self): """Minimum value of the data""" return self._info['MinVal'] @property def max_value(self): """Maximum value of the data""" return self._info['MaxVal'] @property def resolution(self): """Minimal resolvable step size""" return self._info['Resolution'] @property def units(self): """Physical units of measured data""" return self._info['Units'] @property def location_x(self): """x coordinate of the source [in meters]""" return self._info['LocationX'] @property def location_y(self): """y coordinate of the source [in meters]""" return self._info['LocationY'] @property def location_z(self): """z coordinate of the source [in meters]""" return self._info['LocationZ'] @property def location_user(self): """Hardware specific additional location information""" return self._info['LocationUser'] @property def high_freq_corner(self): """High frequency cutoff [in Hz] of the filter""" return self._info['HighFreqCorner'] @property def high_freq_order(self): """Order of the high frequency filter""" return self._info['HighFreqOrder'] @property def high_filter_type(self): """Type of the filter used [text]""" return self._info['HighFilterType'] @property def low_freq_corner(self): """Low frequency cutoff [in Hz] of the filter""" return self._info['LowFreqCorner'] @property def low_freq_order(self): """Order of the high frequency filter""" return self._info['LowFreqOrder'] @property def low_filter_type(self): """Type of the filter used [text]""" return self._info['LowFilterType'] @property def probe_info(self): """Additional information""" return self._info['ProbeInfo'] def get_data(self, index=0, count=-1): """Retrieve raw data from file starting at ``index`` up to ``count`` elements. If no parameters are given retrieves all available data. Returns a tuple with three elements containing the raw data ``[0]``, the timestamp of each data point ``[1]`` and how many of the data values are continuous ``[2]``. Example use: ``data, times, count = analog1.get_data()`` Raw data and timestamp data are return as :class:`numpy.ndarray`. """ if count < 0: count = self.item_count lib = self.file.library data = lib._get_analog_data(self, index, count) return data python-neuroshare-0.9.2/neuroshare/Entity.py000066400000000000000000000036011234311067000212120ustar00rootroot00000000000000 class EntityTime(object): Closest = 0 Before = -1 After = 1 class Entity(object): """Base class of all entities that are contained in a neuroshare file """ def __init__(self, entity_id, nsfile, entity_info): self._info = entity_info self._id = entity_id self._file = nsfile @property def id(self): """The entity id of this entity""" return self._id @property def file(self): """The underlying data file of this entity""" return self._file @property def metadata_raw(self): return self._info @property def label(self): """The label or name of the entity""" return self._info['EntityLabel'] @property def entity_type(self): """The type of the entity (of EntityType)""" return self._info['EntityType'] @property def item_count(self): """ Number of data items for the specified entity in the file""" return self._info['ItemCount'] def get_time_by_index(self, index): """Convert from a given index to the corresponding timestamp""" return self._file.library._get_time_by_index(self, index) def get_index_by_time(self, timepoint, position=EntityTime.Closest): """Convert from a given timestamp to the corresponding index. The position argument controls how the timestamp is matched to the index. Options are: * before and inclusive of the timepoint (``EntityTime.Before``) * after and inclusive of the timepoint (``EntityTime.After``) * closest to timepoint (``EntityTime.Closest``) [default] """ return self._file.library._get_index_by_time(self, timepoint, position) def __len__(self): return self.item_count class EntityType(object): Unknown = 0 Unkown = 0 Event = 1 Analog = 2 Segment = 3 Neural = 4 python-neuroshare-0.9.2/neuroshare/EventEntity.py000066400000000000000000000030551234311067000222170ustar00rootroot00000000000000 from Entity import Entity class EventEntity(Entity): """Event entities represent specific timepoints with associated data, e.g. trigger events. Data can be binary (8, 16 or 32 bit) values, text or comma separated values (cvs). """ EVENT_TEXT = 1 EVENT_CSV = 2 EVENT_BYTE = 3 EVENT_WORD = 4 EVENT_DWORD = 5 def __init__(self, nsfile, eid, info): super(EventEntity, self).__init__(eid, nsfile, info) @property def event_type(self): """The type of the event: * binary (8, 16, 32 bit) [``EVENT_BYTE, EVENT_WORD, EVENT_DWORD``] * text [``EVENT_TEXT``] * comma separated values (csv) [``EVENT_CSV``] """ return self._info['EventType'] @property def csv_desc(self): """Description of the csv fields""" return self._info['CSVDesc'] @property def max_data_length(self): """Maximum length of the data for the event [in bytes]""" return self._info['MaxDataLength'] @property def min_data_length(self): """Minimum length of the data for the event [in bytes]""" return self._info['MinDataLength'] def get_data(self, index): """Retrieve the data at ``index``. Returns a 2-tuple with the timestamp of the data at the first position (``[0]``) and the actual data a the second position (``[1]``)). Example use: ``timestamp, data = event.get_data(0)``""" lib = self.file.library data = lib._get_event_data(self, index) return datapython-neuroshare-0.9.2/neuroshare/File.py000066400000000000000000000106061234311067000206200ustar00rootroot00000000000000 from Library import Library from Entity import EntityType from EventEntity import EventEntity from AnalogEntity import AnalogEntity from SegmentEntity import SegmentEntity from NeuralEntity import NeuralEntity class EntityProxy(object): def __init__(self, nsfile): self._nsfile = nsfile def __getitem__(self, key): return self._nsfile.get_entity(key) def __iter__(self): for x in xrange(0, self._nsfile.entity_count): yield self[x] def __len__(self): return self._nsfile.entity_count class File(object): """Object that represents a datafile that can be open via neuroshare at the location given by ``filename``. The file will be opened upon object construction. Individual entities can be opened via the :func:`get_entity` function or the :func:`entities` property. NB: The first entity index is **0** """ def __init__(self, filename, library=None): self._handle = None self._filename = filename if not library: library = Library.for_file(filename) self._lib = library (handle, info) = self._lib._open_file(filename) self._handle = handle self._info = info self._eproxy = EntityProxy(self) def __del__(self): self.close() def close(self): """Close the file.""" if self._handle: self._lib._close_file(self) self._handle = None @property def library(self): return self._lib @property def file_type(self): """Text description of the file type""" return self._info['FileType'] @property def metadata_raw(self): return self._info @property def app_name(self): """The name of the application that created the file""" return self._info['AppName'] @property def comment(self): """Additional comments""" return self._info['FileComment'] @property def entity_count(self): """The number of entities in this file""" return self._info['EntityCount'] @property def time_span(self): """Timespan of the data in the file [in seconds]""" return self._info['TimeSpan'] @property def time_stamp_resolution(self): """Minimum resolution of timestamps [in seconds]""" return self._info['TimeStampResolution'] @property def ctime(self): """The time when this file was created, i.e. the data recorded. Returns a :py:class:`datetime.datetime` object. """ from datetime import datetime year = self._info['Time_Year'] month = self._info['Time_Month'] day = self._info['Time_Day'] hour = self._info['Time_Hour'] minute = self._info['Time_Min'] sec = self._info['Time_Sec'] millisec = self._info['Time_MilliSec'] msec = millisec * 1000 ct = datetime(year, month, day, hour, minute, sec, msec) return ct def get_entity(self, entity_id): """Open the entity at the given index.""" info = self._lib._get_entity_info(self, entity_id) entity_type = info['EntityType'] if entity_type == EntityType.Event: entity = EventEntity(self, entity_id, info) elif entity_type == EntityType.Analog: entity = AnalogEntity(self, entity_id, info) elif entity_type == EntityType.Segment: entity = SegmentEntity(self, entity_id, info) elif entity_type == EntityType.Neural: entity = NeuralEntity(self, entity_id, info) else: return None # should not happen, throw exception? return entity def list_entities(self, start=0, end=-1): """List all entities. The range can be limited via the ``start`` and ``end`` parameters.""" if end == -1: end = self.entity_count for x in xrange(start, end): yield self.get_entity(x) @property def entities(self): """Property that returns a proxy object to allow the opening of entities in a via indexing, ie:: entity = datafile.entities[10] #retrieve the entity with at 10 """ return self._eproxy @property def _get_handle(self): return self._handle @property def handle(self): return self._handle def __repr__(self): return 'neuroshare.File(%r)' % self._filename python-neuroshare-0.9.2/neuroshare/Library.py000066400000000000000000000132301234311067000213410ustar00rootroot00000000000000import os import sys import _capi class ArgumentError(Exception): def __init__(self, arg, msg): self.arg = arg self.msg = msg def __str__(self): return "\"%s\": %s" % (self.arg, self.msg) class DLLException(Exception): def __init__(self, name, ext, lib=None): self.name = name self.ext = ext self.lib = lib class DLLTypeUnknown(DLLException): def __str__(self): return '"%s": Unknown library type.' % self.ext class DLLNotFound(DLLException): def __str__(self): return 'Vendor DLL "%s" could not be found' % self.lib def _find_dll(library_name): known_paths = ["~/.neuroshare", "/usr/lib/neuroshare", "/usr/local/lib/neuroshare"] platform = sys.platform if platform.startswith('linux'): dll_suffix = "so" elif platform.startswith('darwin'): dll_suffix = "dylib" elif platform.startswith('win'): dll_suffix = "dll" else: dll_suffix = "error" dll_name = "%s.%s" % (library_name, dll_suffix) dt = os.path.join(os.getcwd(), dll_name) if os.path.lexists(dt): return dt for cur_path in known_paths+sys.path: dt = os.path.join(os.path.expanduser(cur_path), dll_name) if os.path.lexists(dt): return dt return None def find_library_for_file(filename): dll_map = {"mcd": "nsMCDLibrary", "plx": "nsPlxLibrary", "map": "nsAOLibrary", "nev": "nsNEVLibrary", "nex": "NeuroExplorerNeuroShareLibrary"} (root, ext) = os.path.splitext(filename) if not ext or not ext.startswith('.'): raise ArgumentError(filename, "Could find file extension") ext = ext[1:] if ext not in dll_map: raise DLLTypeUnknown(root, ext) library_name = dll_map[ext] path = _find_dll(library_name) if not path: path = _find_dll("nsWineLibrary") if not path: raise DLLNotFound(root, ext, library_name) return library_name, path def load_library_for_file(filename): return Library.for_file(filename) # ## Library Implementation class Library(object): _loaded_libs = {} @classmethod def for_file(cls, filename): (name, path) = find_library_for_file(filename) if name not in cls._loaded_libs: lib = Library(name, path) cls._loaded_libs[name] = lib return cls._loaded_libs[name] def __init__(self, name, path): self._name = name self._path = path self._handle = _capi.library_open(path) self._open_files = [] self._info = _capi.get_library_info(self._handle) def _open_file(self, filename): (fh, file_info) = _capi.open_file(self._handle, filename) self._open_files.append(fh) return fh, file_info def _close_file(self, nsfile): fh = nsfile.handle _capi.close_file(self._handle, fh) self._open_files.remove(fh) def _get_entity_info(self, nsfile, entity_id): fh = nsfile.handle info = _capi.get_entity_info(self._handle, fh, entity_id) return info def _get_event_data(self, event, index): fh = event.file.handle entity_id = event.id event_type = event.event_type max_data_len = event.max_data_length data = _capi.get_event_data(self._handle, fh, entity_id, index, event_type, max_data_len) return data def _get_analog_data(self, analog, index, count): fh = analog.file.handle entity_id = analog.id data = _capi.get_analog_data(self._handle, fh, entity_id, index, count) return data def _get_segment_data(self, segment, index): fh = segment.file.handle entity_id = segment.id source_count = segment.source_count max_sample_count = segment.max_sample_count data = _capi.get_segment_data(self._handle, fh, entity_id, index, source_count, max_sample_count) return data def _get_neural_data(self, neural, index, count): fh = neural.file.handle entity_id = neural.id data = _capi.get_neural_data(self._handle, fh, entity_id, index, count) return data def _get_time_by_index(self, entity, index): fh = entity.file.handle entity_id = entity.id t = _capi.get_time_by_index(self._handle, fh, entity_id, index) return t def _get_index_by_time(self, entity, time, position): fh = entity.file.handle entity_id = entity.id idx = _capi.get_index_by_time(self._handle, fh, entity_id, time, position) return idx def __del__(self): _capi.library_close(self._handle) @property def metadata_raw(self): return self._info @property def creator(self): return self._info['Creator'] @property def description(self): return self._info['Description'] @property def api_version(self): major = self._info['APIVersionMaj'] minor = self._info['APIVersionMin'] return major, minor @property def library_version(self): major = self._info['LibVersionMaj'] minor = self._info['LibVersionMin'] return major, minor @property def max_files(self): return self._info['MaxFiles'] @property def mtime(self): from datetime import date year = self._info['Time_Year'] month = self._info['Time_Month'] day = self._info['Time_Day'] return date(year, month, day) @property def name(self): return self._name @property def path(self): return self._pathpython-neuroshare-0.9.2/neuroshare/NeuralEntity.py000066400000000000000000000026231234311067000223640ustar00rootroot00000000000000from Entity import Entity class NeuralEntity(Entity): """Entity the represents timestamps of action potentials, i.e. spike times. Cutouts of the waveforms corresponding to spike data in a neural entity might be found in a separate :class:`SegmentEntity` (cf. :func:`source_entity_id`). """ def __init__(self, nsfile, eid, info): super(NeuralEntity, self).__init__(eid, nsfile, info) @property def probe_info(self): """Additional information about the signal source""" return self._info['ProbeInfo'] @property def source_entity_id(self): """[*Optional*] Id of the source entity of this spike, if any. For example the spike waveform of the action potential corresponding to this spike might have been recorded in a segment entity.""" return self._info['SourceEntityID'] @property def source_unit_id(self): """[*Optional*] unit id used in the source entity (cf. :func:`source_entity_id`)""" return self._info['SourceUnitID'] def get_data(self, index=0, count=-1): """Retrieve the spike times associated with this entity. A subset of the data can be requested via the ``index`` and ``count`` parameters.""" lib = self.file.library if count < 0: count = self.item_count data = lib._get_neural_data(self, index, count) return data python-neuroshare-0.9.2/neuroshare/SegmentEntity.py000066400000000000000000000072551234311067000225460ustar00rootroot00000000000000from Entity import Entity class SegmentSource(object): """Segment sources provide access to the metadata of individual sources of a :class:`SegmentEntity`""" def __init__(self, segment, source_id, info): self._segment = segment self._source_id = source_id self._info = info @property def segment(self): return self._segment @property def id(self): return self._source_id @property def metadata_raw(self): return self._info @property def min_value(self): return self._info['MinVal'] @property def max_value(self): return self._info['MaxVal'] @property def resolution(self): return self._info['Resolution'] @property def sub_sample_shift(self): return self._info['SubSampleShift'] @property def location_x(self): """x coordinate [in meters]""" return self._info['LocationX'] @property def location_y(self): """y coordinate [in meters]""" return self._info['LocationY'] @property def location_z(self): """z coordinate [in meters]""" return self._info['LocationZ'] @property def location_user(self): """Additional hardware specific location information""" return self._info['LocationUser'] @property def high_freq_corner(self): return self._info['HighFreqCorner'] @property def high_freq_order(self): return self._info['HighFreqOrder'] @property def high_filter_type(self): return self._info['HighFilterType'] @property def low_freq_corner(self): return self._info['LowFreqCorner'] @property def low_freq_order(self): return self._info['LowFreqOrder'] @property def low_filter_type(self): return self._info['LowFilterType'] @property def probe_info(self): """Additional information""" return self._info['ProbeInfo'] class SourcesBag(object): def __init__(self, segment, infos): self._infos = infos self._segment = segment def __getitem__(self, key): source_id = int(key) source_info = self._infos[source_id] return SegmentSource(self._segment, source_id, source_info) def __iter__(self): for x in range(0, len(self._infos)): yield self[x] class SegmentEntity(Entity): """Segment entities contain cutouts of continuously sampled analog signals from one or more sources that are usually short in time. Most prominent example are waveforms of action potentials from one ore more electrodes.""" def __init__(self, nsfile, eid, info): from copy import copy self._source_infos = info['SourceInfos'] pure_info = copy(info) del pure_info['SourceInfos'] super(SegmentEntity, self).__init__(eid, nsfile, pure_info) @property def max_sample_count(self): """Maximum number of samples in each data item""" return self._info['MaxSampleCount'] @property def source_count(self): """Number of sources for this segment entity.""" return self._info['SourceCount'] @property def sources(self): """Property that provides access to the metadata of the individual sources of this entity. Returns a sequence of objects of type :class:`SegmentSource`. Metadata properties of a SegmentSource are analogous to the :class:`AnalogEntity`.""" return SourcesBag(self, self._source_infos) def get_data(self, index): """Retrieve the data at ``index``""" lib = self.file.library data = lib._get_segment_data(self, index) return datapython-neuroshare-0.9.2/neuroshare/__init__.py000066400000000000000000000006011234311067000214720ustar00rootroot00000000000000 __author__ = 'Christian Kellner' __version__ = '0.9.2' __contact__ = 'kellner@biologie.uni-muenchen.de' __license__ = 'LGPL' from Library import Library from File import File from Entity import EntityType from Entity import Entity from EventEntity import EventEntity from AnalogEntity import AnalogEntity from SegmentEntity import SegmentEntity from NeuralEntity import NeuralEntity python-neuroshare-0.9.2/ns-convert000077500000000000000000000132531234311067000172410ustar00rootroot00000000000000#!/usr/bin/env python import os import sys import h5py import neuroshare as ns import numpy as np import getopt class ProgressIndicator(object): def __init__(self, offset=0): self._cur_value = offset self._max_value = 0 def setup(self, max_value): self._max_value = max_value self.progress(self._max_value, 0) def __add__(self, other): self._cur_value += other self.progress(self._max_value, self._cur_value) return self def progress(self, max_value, cur_value): pass class Converter(object): def __init__(self, filepath, output=None, progress=None): if not output: (basefile, ext) = os.path.splitext(filepath) output = "%s.hdf5" % basefile nf = ns.File(filepath) h5 = h5py.File(output, 'w') self._nf = nf self._h5 = h5 self._groups = {} self.convert_map = {1: self.convert_event, 2: self.convert_analog, 3: self.convert_segment, 4: self.convert_neural} if not progress: progress = ProgressIndicator() self._progress = progress def get_group_for_type(self, entity_type): name_map = {1: 'Event', 2: 'Analog', 3: 'Segment', 4: 'Neural'} if entity_type not in self._groups: name = name_map[entity_type] group = self._h5.create_group(name) self._groups[entity_type] = group return self._groups[entity_type] def convert(self): progress = self._progress progress.setup(len(self._nf.entities)) self.copy_metadata(self._h5, self._nf.metadata_raw) for entity in self._nf.entities: conv = self.convert_map[entity.entity_type] conv(entity) progress + 1 self._h5.close() def convert_event(self, event): dtype = self.dtype_by_event(event) nitems = event.item_count data = np.empty([nitems], dtype) for n in xrange(0, event.item_count): data[n] = event.get_data(n) group = self.get_group_for_type(event.entity_type) dset = group.create_dataset(event.label, data=data) self.copy_metadata(dset, event.metadata_raw) def convert_analog(self, analog): (data, times, ic) = analog.get_data() group = self.get_group_for_type(analog.entity_type) d_t = np.vstack((times, data)).T dset = group.create_dataset(analog.label, data=d_t) self.copy_metadata(dset, analog.metadata_raw) def convert_segment(self, segment): if not segment.item_count: return group = self.get_group_for_type(segment.entity_type) seg_group = group.create_group(segment.label) self.copy_metadata(seg_group, segment.metadata_raw) for index in xrange(0, segment.source_count): source = segment.sources[index] name = 'SourceInfo.%d.' % index self.copy_metadata(seg_group, source.metadata_raw, prefix=name) for index in xrange(0, segment.item_count): (data, timestamp, samples, unit) = segment.get_data(index) name = '%d - %f' % (index, timestamp) dset = seg_group.create_dataset(name, data=data.T) dset.attrs['Timestamp'] = timestamp dset.attrs['Unit'] = unit dset.attrs['Index'] = index def convert_neural(self, neural): data = neural.get_data() group = self._groups[neural.entity_type] name = "%d - %s" % (neural.id, neural.label) dset = group.create_dataset(name, data=data) self.copy_metadata(dset, neural.metadata_raw) @classmethod def copy_metadata(cls, target, metadata, prefix=None): for (key, value) in metadata.iteritems(): if prefix is not None: key = prefix + key target.attrs[key] = value @classmethod def dtype_by_event(cls, event): type_map = {ns.EventEntity.EVENT_TEXT : 'a', ns.EventEntity.EVENT_CSV : 'a', ns.EventEntity.EVENT_BYTE : 'b', ns.EventEntity.EVENT_WORD : 'h', ns.EventEntity.EVENT_DWORD : 'i'} val_type = type_map[event.event_type] if val_type == 'a': val_type += str(event.max_data_length) return np.dtype([('timestamp', 'd'), ('value', val_type)]) class ConsoleIndicator(ProgressIndicator): def __init__(self): super(ConsoleIndicator, self).__init__() self._size = 60 self._last_msg = "" def progress(self, max_value, cur_value): size = self._size prefix = "Converting" x = int(size*cur_value/max_value) msg = "%s [%s%s] %i/%i\r" % (prefix, "#"*x, "." * (size-x), cur_value, max_value) self._last_msg = msg sys.stdout.write(msg) sys.stdout.flush() def cleanup(self): sys.stdout.write('%s\r' % (' '*len(self._last_msg))) sys.stdout.flush() def main(): opts, rem = getopt.getopt(sys.argv[1:], 'o:', ['output=', 'version=', ]) output = None for opt, arg in opts: if opt in ("-o", "--output"): output = arg if len(rem) != 1: print "Wrong number of arguments" return -1 filename = rem[0] ci = ConsoleIndicator() converter = Converter(filename, output, progress=ci) converter.convert() ci.cleanup() return 0 if __name__ == "__main__": res = main() sys.exit(res) python-neuroshare-0.9.2/setup.cfg000066400000000000000000000002251234311067000170310ustar00rootroot00000000000000[build_sphinx] source-dir = doc/source build-dir = build/docs all_files = 1 [upload_sphinx] upload-dir = build/docs/html [build_ext] inplace = 1 python-neuroshare-0.9.2/setup.py000077500000000000000000000047311234311067000167330ustar00rootroot00000000000000#!/usr/bin/env python """Python Bindings for Neuroshare --------------------------------- The Neuroshare API is a standardized interface to access electrophysiology data stored in various different file formats. To do so, it uses format- specific shared libraries. Refer to the official website http://neuroshare.org for more information. The aim of this library is to provide a high level interface to the Neuroshare API, i.e. it focuses on API usability more then being a mere python version of the C API. Thus none of the original Neuroshare API calls are directly exposed but the interface is through python objects that resemble (more or less) the Neuroshare Entities. """ try: from setuptools import setup, Extension except ImportError: from distutils.core import setup, Extension from distutils.extension import Extension import numpy as np import os #parse metadata from neuroshare/__init__.py import re srcdir = os.path.dirname(__file__) path = os.path.join(srcdir, 'neuroshare', '__init__.py') txt_data = open(path).read() metadata = dict(re.findall("__([a-z]+)__ = [\"']([^\"']+)[\"']", txt_data)) classifiers = [ 'Development Status :: 5 - Production/Stable', 'Programming Language :: Python', 'Programming Language :: C', 'License :: OSI Approved :: GNU Library or Lesser General Public License (LGPL)', 'Operating System :: OS Independent', 'Intended Audience :: Developers', 'Topic :: Scientific/Engineering', 'Topic :: Software Development :: Libraries :: Python Modules'] native_ext = Extension('neuroshare._capi', include_dirs=[np.get_include()], sources=['capi/nspy_glue.c']) setup (name = 'neuroshare', version = metadata['version'], author = metadata['author'], author_email = metadata['contact'], url = 'http://www.g-node.org/neuroshare-tools', keywords = ['neuroshare', 'neuroscience', 'science'], description = __doc__.split("\n")[0], long_description = "\n".join(__doc__.split("\n")[2:]), license = 'LGPL', platforms = ["Windows", "Linux", "Solaris", "Mac OS-X", "Unix"], classifiers = classifiers, ext_modules = [native_ext], packages = ['neuroshare'], scripts = ['ns-convert'], setup_requires = ['Sphinx-PyPI-upload', 'numpy >= 1.7'] )