def writeSummaryBehavioralDataToFile(dataFrame, workSheet, Tag, col): # Write the row names LoadLevels = numpy.unique(dataFrame.data.LoadLevels) WriteToGoogleSpreadSheet.writeData(workSheet, LoadLevels, 1, 2, 'Load') data1 = dataFrame.data.RT.groupby(dataFrame.data.LoadLevels).mean() title1 = '%s_meanRT' % (Tag) col1 = col + 1 rowStart = 2 WriteToGoogleSpreadSheet.writeData(workSheet, data1, col1, rowStart, title1) data2 = dataFrame.data.Acc.groupby(dataFrame.data.LoadLevels).mean() title2 = '%s_meanAcc' % (Tag) col2 = col + 2 rowStart = 2 WriteToGoogleSpreadSheet.writeData(workSheet, data2, col2, rowStart, title2) data3 = dataFrame.data.Acc.groupby(dataFrame.data.LoadLevels).sum() title3 = '%s_numCorr' % (Tag) col3 = col + 3 rowStart = 2 WriteToGoogleSpreadSheet.writeData(workSheet, data3, col3, rowStart, title3)
def ProcessAFile(inputFile,subid,Tag,col): print inputFile print subid df1 = ProcessData.loadBehDataFile(inputFile) df1 = ProcessData.processBehavioralFile(df1) wkB = WriteToGoogleSpreadSheet.openWorkBook() # Check to see if a worksheet exists worksheetName = 'behData_%s'%(subid) try: wkS = wkB.worksheet(worksheetName) except: wkS = WriteToGoogleSpreadSheet.createWorksheet(wkB, subid) ProcessData.writeSummaryBehavioralDataToFile(df1, wkS, Tag, col) return df1
def writeSummaryBehavioralDataToFile(dataFrame, workSheet, Tag, col): # Write the row names LoadLevels = numpy.unique(dataFrame.data.LoadLevels) WriteToGoogleSpreadSheet.writeData(workSheet, LoadLevels, 1, 2,'Load') data1 = dataFrame.data.RT.groupby(dataFrame.data.LoadLevels).mean() title1 = '%s_meanRT'%(Tag) col1 = col + 1 rowStart = 2 WriteToGoogleSpreadSheet.writeData(workSheet, data1, col1, rowStart,title1) data2 = dataFrame.data.Acc.groupby(dataFrame.data.LoadLevels).mean() title2 = '%s_meanAcc'%(Tag) col2 = col + 2 rowStart = 2 WriteToGoogleSpreadSheet.writeData(workSheet, data2, col2, rowStart,title2) data3 = dataFrame.data.Acc.groupby(dataFrame.data.LoadLevels).sum() title3 = '%s_numCorr'%(Tag) col3 = col + 3 rowStart = 2 WriteToGoogleSpreadSheet.writeData(workSheet, data3, col3, rowStart,title3)
def ProcessAFile(inputFile,subid,Tag): df1 = ProcessData.loadBehDataFile(inputFile) df1 = ProcessData.processBehavioralFile(df1) wkB = WriteToGoogleSpreadSheet.openWorkBook() wkS = WriteToGoogleSpreadSheet.createWorksheet(wkB, subid) writeSummaryBehavioralDataToFile(df1, wkS, Tag)
wkB = WriteToGoogleSpreadSheet.openWorkBook() wkS = WriteToGoogleSpreadSheet.createWorksheet(wkB, subid) writeSummaryBehavioralDataToFile(df1, wkS, Tag) ex = Example() # This will ask you to select on or more files ex.showDialog() df1 = ProcessData.loadBehDataFile(ex.fileName[0][0]) df1 = ProcessData.processBehavioralFile(df1) ProcessData.createSPMDesignMatrix(df1, 'P00002001_S0001_Run1_DM') df2 = ProcessData.loadBehDataFile(ex.fileName[0][1]) df2 = ProcessData.processBehavioralFile(df2) ProcessData.createSPMDesignMatrix(df1, 'P00002001_S0001_Run2_DM') wkB = WriteToGoogleSpreadSheet.openWorkBook() wkS = WriteToGoogleSpreadSheet.createWorksheet(wkB, '2001') writeSummaryBehavioralDataToFile(df1, wkS, 'Run1') ########################################################################### # Can I extract the trial start times and group them the same way? # Stim On Times LoadLevels = numpy.unique(dataFrame.data.LoadLevels) # Load level 1 TrialsToKeep = (dataFrame.data.LoadLevels==1) & (df1.data.Acc != -1) S1on = numpy.array(df1.data.TrialStart[TrialsToKeep]) S1dur = numpy.array(df1.data.StimDur[TrialsToKeep]) TrialsToKeep = (df1.data.LoadLevels==1) & (df1.data.RetDur > 0) & (df1.data.Acc != -1)