MultiTimeFieldAnalysis/pyBindMat.py at main · BhallaLab/MultiTimeFieldAnalysis · GitHub

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import numpy as np
import tc

r2bThresh = 3.0
r2bPercentile = 99.5

'''
### The data structures below are now obtained from the C++ code.

# These are the data structures. Params go into the function, and
# CellScore comes out. Default values are indicated here.
# These are initialized in C++, shown here for clarity.
class AnalysisParams():
    def __init__( self ):
		self.numCells = 100
		self.numTrials = 60
		self.numFrames = 202
        self.csOnsetFrame = 75
        self.usOnsetFrame = 190
        self.circPad = 20
        self.circShuffleFrames = 40 + 190 - 75
        self.binFrames = 3
        self.numShuffle = 1000
        self.epsilon = 1.0e-6

class TiAnalysisParams():
    def __init__( self ):
        self.transientThresh = 2.0
        self.tiPercentile = 99.0
        self.fracTRialsFiredThresh = 0.25
        self.frameDt = 1.0 / 12.5


'''

def convScoreToList( cs ):
    return {
        'meanScore':        cs.meanScore,
        'baseScore':        cs.baseScore,
        'percentileScore':  cs.percentileScore,
        'sigMean':          cs.sigMean,
        'sigBootstrap':     cs.sigBootstrap,
        'fracTrialsFired':  cs.fracTrialsFired,
        'meanPkIdx':        cs.meanPkIdx,
        'allPkIndices':     list( cs.allPkIndices ),
        'allPkScores':      list( cs.allPkScores ),
        'allPkPvalues':     list( cs.allPkPvalues ),
        'meanTrace':        list( cs.meanTrace ),
    }

def _setCommonParams( ap, DATA, csOnset, usOnset, circPad, circShuffleFrames, binFrames, numShuffle, frameDt, minPeakSep, dipFrames=2, dipSdev=1.0 ):
    ap.numCells, ap.numTrials, ap.numFrames = DATA.shape
    ap.csOnsetFrame     = int( csOnset )
    ap.usOnsetFrame     = int( usOnset )
    ap.circPad          = int( circPad )
    ap.circShuffleFrames = int( circShuffleFrames )
    ap.binFrames        = int( binFrames )
    ap.numShuffle       = int( numShuffle )
    ap.frameDt          = float( frameDt )
    ap.minPeakSep       = float( minPeakSep )
    ap.dipFrames        = int( dipFrames )
    ap.dipSdev          = float( dipSdev )

def runR2Banalysis( DATA, csOnset, usOnset, circPad, circShuffleFrames, binFrames, numShuffle, r2bThresh, r2bPercentile, frameDt=0.08, minPeakSep=0.4 ):
    ap = tc.AnalysisParams()
    _setCommonParams( ap, DATA, csOnset, usOnset, circPad, circShuffleFrames, binFrames, numShuffle, frameDt, minPeakSep )
    # Input DATA[cell, trial, frame] -> C++ expects [frame, trial, cell] flattened
    dat = np.array( np.swapaxes(DATA, 0, 2) ).reshape( -1 )
    cs = tc.r2bScore( dat, ap, r2bThresh, r2bPercentile )
    return [ convScoreToList( rr ) for rr in cs ]

def runTIanalysis( DATA, csOnset, usOnset, circPad, circShuffleFrames, binFrames, numShuffle, transientThresh, tiPercentile, fracTrialsFiredThresh, frameDt, minPeakSep=0.4 ):
    ap = tc.AnalysisParams()
    _setCommonParams( ap, DATA, csOnset, usOnset, circPad, circShuffleFrames, binFrames, numShuffle, frameDt, minPeakSep )

    tip = tc.TiAnalysisParams()
    tip.transientThresh       = transientThresh
    tip.tiPercentile          = tiPercentile
    tip.fracTrialsFiredThresh = fracTrialsFiredThresh
    tip.frameDt               = frameDt

    dat = np.array( np.swapaxes(DATA, 0, 2) ).reshape( -1 )
    cs = tc.tiScore( dat, ap, tip )
    return [ convScoreToList( rr ) for rr in cs ]

def runPEQanalysis( DATA, csOnset, usOnset, circPad, circShuffleFrames, binFrames, numShuffle, frameDt=0.08, minPeakSep=0.4 ):
    ap = tc.AnalysisParams()
    _setCommonParams( ap, DATA, csOnset, usOnset, circPad, circShuffleFrames, binFrames, numShuffle, frameDt, minPeakSep )
    pep = tc.PeqAnalysisParams()
    dat = np.array( np.swapaxes(DATA, 0, 2) ).reshape( -1 )
    cs = tc.peqScore( dat, ap, pep )
    return [ convScoreToList( rr ) for rr in cs ]

def main():
    parser = argparse.ArgumentParser( description = "Perform r2b time cell analysis on given matlab file" )
    parser.add_argument( "datafile",  type = str, help = "Required. File name to load, in matlab format" )
    args = parser.parse_args()

    dat = h5py.File( args.datafile, 'r' )
    printDatasetInfo( dat )

'''
if __name__ == '__main__':
    main()
'''