def main():
configFile = 'greenEyes.toml'
cfg = initializeGreenEyes(configFile)
runData = StructDict()
runData.cheating_probability = np.zeros((cfg.nStations, ))
runData.correct_prob = np.zeros((cfg.nStations, ))
runData.interpretation = getSubjectInterpretation(cfg)
runData.badVoxels = {}
runData.dataForClassification = {}
story_TRs = cfg.story_TR_2 - cfg.story_TR_1
SKIP = 10
all_data = np.zeros((cfg.nVox, cfg.nTR_run - SKIP)) # don't need to save
runData.story_data = np.zeros((cfg.nVox, story_TRs))
#### MAIN PROCESSING ###
## FUNCTION TO OPERATE OVER ALL SCANNING RUNS
scanNum = 9
for TRindex in np.arange(cfg.nTR_run - SKIP):
print('TRindex')
#for TRindex in np.arange(44):
TRnum = TRindex + 1 + SKIP # actual file number to look for
TRindex_story = TRindex - cfg.story_TR_1
full_nifti_name = convertToNifti(TRnum, scanNum, cfg)
registeredFileName = registerNewNiftiToMNI(cfg, full_nifti_name)
maskedData = apply_mask(registeredFileName, cfg.MASK)
all_data[:, TRindex] = maskedData
if TRindex_story >= 0: # we're at a story TR now
runData.story_data[:, TRindex_story] = maskedData
if np.any(TRindex_story == cfg.last_tr_in_station.astype(int)):
# NOW PREPROCESS AND CLASSIFY
runData = preprocessAndPredict(cfg, runData, TRindex_story)
else:
pass
def main():
# MAKES STRUCT WITH ALL PARAMETERS IN IT
argParser = argparse.ArgumentParser()
argParser.add_argument('--config', '-c', default='greenEyes_organized.toml', type=str,
help='experiment config file (.json or .toml)')
argParser.add_argument('--runs', '-r', default=None, type=str,
help='Comma separated list of run numbers')
argParser.add_argument('--scans', '-s', default=None, type=str,
help='Comma separated list of scan number')
# creates web pipe communication link to send/request responses through web pipe
argParser.add_argument('--webpipe', '-w', default=None, type=str,
help='Named pipe to communicate with webServer')
argParser.add_argument('--webfilesremote', '-x', default=False, action='store_true',
help='dicom files retrieved from remote server')
args = argParser.parse_args()
params = StructDict({'config': args.config,'runs': args.runs, 'scans': args.scans,
'webpipe': args.webpipe, 'webfilesremote': args.webfilesremote})
cfg = initializeGreenEyes(params.config,params)
# initialize file interface class -- for now only local
fileInterface = FileInterface()
# intialize watching in particular directory
fileWatcher.initWatch(cfg.intelrt.imgDir, cfg.intelrt.dicomNamePattern, cfg.minExpectedDicomSize)
runData = StructDict()
runData.cheating_probability = np.zeros((cfg.nStations,))
runData.correct_prob = np.zeros((cfg.nStations,))
runData.interpretation = getSubjectInterpretation(cfg)
runData.badVoxels = {}
runData.dataForClassification = {}
story_TRs = cfg.story_TR_2 - cfg.story_TR_1
SKIP = 10
all_data = np.zeros((cfg.nVox,cfg.nTR_run)) # don't need to save
runData.story_data = np.zeros((cfg.nVox,story_TRs))
#### MAIN PROCESSING ###
## FUNCTION TO OPERATE OVER ALL SCANNING RUNS
# LOOP OVER ALL CFG.SCANNUMS
nRuns = len(cfg.runs)
for runIndex in np.arange(nRuns):
header = makeRunHeader(cfg,runIndex)
print(header)
run = cfg.runs[runIndex]
scanNum = cfg.scanNums[runIndex]
storyTRCount = 0
for TRFilenum in np.arange(SKIP+1,cfg.nTR_run+1):
##### GET DATA BUFFER FROM LOCAL MACHINE ###
dicomData = fileInterface.watchfile(getDicomFileName(cfg, scanNum, TRFilenum), timeout=5) # if starts with slash it's full path, if not, it assumes it's the watch directory and builds
full_nifti_name = convertToNifti(TRFilenum,scanNum,cfg)
registeredFileName = registerNewNiftiToMNI(cfg,full_nifti_name)
maskedData = apply_mask(registeredFileName,cfg.mask_filename)
all_data[:,TRFilenum] = maskedData
if TRFilenum >= cfg.fileNum_story_TR_1 and TRFilenum <= cfg.fileNum_story_TR_2: # we're at a story TR now
runData.story_data[:,storyTRCount] = maskedData
if np.any(storyTRCount == cfg.last_tr_in_station.astype(int)):
# NOW PREPROCESS AND CLASSIFY
runData = preprocessAndPredict(cfg,runData,storyTRCount)
text_to_save = '{0:05d}'.format(runData.correct_prob[stationInd])
file_name_to_save = getStationClassoutputFilename(cfg.sessionId, cfg.run, stationInd)
full_filename_to_save = cfg.intelrt.subject_full_day_path + file_name_to_save
fileInterface.putTextFile(full_filename_to_save,text_to_save)
storyTRCount += 1
else: