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These C/C++ source files consist of 150 classes, 300,000 lines of code, excluding a Qt-based user interface. Its functionality includes: GLM-statistics, hierarchical clustering, (non)-linear optimization, L1 and L2 norm minimization, Hungarian algorithm, EEG/MEG forward and inverse modelling, Boundary Element Method, spatio/temporal covariance m…

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DMS_Projects

The source files have been developed for MSVC version 2017, but they are all compatible with linux. There are two main applications: BIAP1D (for MEG and EEG) and BIAP4D (for MRI, fMRI, surfaces, etc). These applications need Qt 4.8.6 and are output in DMS_Projects\Exe\Biap64. Input file: DMS_Projects\Qt4Projects\Biap.sln

Qt binaries provided are: DMS_Projects\Exe\Biap64\QtGui4.dll DMS_Projects\Exe\Biap64\QtCore4.dll

DMS_Projects\Qt4Projects\Lib\qtmain4_64_R.lib (64 bits, release) DMS_Projects\Qt4Projects\Lib\qtmain4_64_D.lib (64 bits, debug) DMS_Projects\Qt4Projects\Lib\qtmain4_32_R.lib (32 bits, release) DMS_Projects\Qt4Projects\Lib\qtmain4_32_D.lib (32 bits, debug)

DMS_Projects\Qt4Projects\Lib\QtGui4_64_R (64 bits, release) DMS_Projects\Qt4Projects\Lib\QtGui4_64_D (64 bits, debug) DMS_Projects\Qt4Projects\Lib\QtGui4_32_R (32 bits, release) DMS_Projects\Qt4Projects\Lib\QtGui4_32_D (32 bits, debug)

DMS_Projects\Qt4Projects\Lib\QtCore4_64_R (64 bits, release) DMS_Projects\Qt4Projects\Lib\QtCore4_64_D (64 bits, debug) DMS_Projects\Qt4Projects\Lib\QtCore4_32_R (32 bits, release) DMS_Projects\Qt4Projects\Lib\QtCore4_32_D (32 bits, debug)

These binaries can be created by compiling source files from Qt 4.8.6 They are seperately stored in Qt4_MSVC2017_libs.zip

Mananuals for BIAP are stored in _BiapManual.zip

Help files to create Biap for linux can be found in: DMS_Projects\Qt4Projects\MakeBiap

Various smaller console applications can be found in: DMS_Projects\Console\Console.sln

Test applications showing how the objects work: DMS_Projects\Test\TestVarious.sln

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These C/C++ source files consist of 150 classes, 300,000 lines of code, excluding a Qt-based user interface. Its functionality includes: GLM-statistics, hierarchical clustering, (non)-linear optimization, L1 and L2 norm minimization, Hungarian algorithm, EEG/MEG forward and inverse modelling, Boundary Element Method, spatio/temporal covariance m…

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