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)