// load a volume for computation
void emotionRoiProcessing::loadVolume(studyParams &vdb, volume<float> &v, int index)
{
char processedFile[200], prefix[BUFF_SIZE], tempVolume[BUFF_SIZE];
if (0)
{
// gets the motion corrected and gaussian file
vdb.getMCGVolumeName(processedFile, index);
read_volume(v, string(processedFile));
}
else
{
// making the activation volume for viewing
vdb.getFinalVolumeFormat(prefix);
vdb.setActivationFile(index);
estimateActivation(index, index, vdb.slidingWindowSize, prefix, vdb.maskFile, vdb.activationFile);
// gets the motion corrected and gaussian file and calculates the mean with the last n volumes (n = sliding window size)
sprintf(tempVolume, "%s%s", vdb.outputDir, "temp.nii");
vdb.getMCGVolumeFormat(prefix);
estimateActivation(index, index, vdb.slidingWindowSize, prefix, tempVolume);
read_volume(v, string(tempVolume));
if (fileExists(tempVolume))
remove(tempVolume);
}
}
// plug in test function
DLLExport testSVM(studyParams &vdb, int index, float &classnum, float &projection, void * &userData)
{
char prefix[BUFF_SIZE];
SVMProcessing *svmProcessingVar = (SVMProcessing *) userData;
vdb.getFinalVolumeFormat(prefix);
fprintf(stderr, "Generating activation file.\n");
vdb.setActivationFile(index);
estimateActivation(index, index, vdb.slidingWindowSize, prefix, vdb.maskFile, vdb.activationFile);
fprintf(stderr, "Classifying.\n");
svmProcessingVar->test(index, vdb.activationFile, classnum, projection);
return 1;
}