def get_subjects(study, subjType, listPrefix):
path = os.path.join('/cluster/kuperberg/SemPrMM/', 'MEG/')
subject_filename = path + 'scripts/function_inputs/' + listPrefix + '.txt'
subject_list = readInput.readList(subject_filename)
all_subs = []
for row in subject_list:
row = subjType + row
all_subs.append(row)
return [sub for sub in all_subs if len(find_eves(study, sub)) > 0]
def main(subjType, listPrefix, study):
rt_ax_avg= []
rt_ay_avg= []
rt_bx_avg = []
rt_by_avg = []
for mod in modalities:
##for study in studies:
##subjects = get_subjects(mod,study,subjType)
subjects = readInput.readList('/cluster/kuperberg/SemPrMM/MRI/scripts/input/' +listPrefix)
print(subjects)
print(study)
study_results, rt_ax_avg, rt_ay_avg, rt_bx_avg, rt_by_avg = parse_study(mod,study,subjects,listPrefix)
with open('/cluster/kuperberg/SemPrMM/MRI/results/behavioral_accuracy/'+mod+'_'+listPrefix+'_'+study+'_accuracy-short.log','w') as f:
f.write('sub:\t')#write out header
for code in code_names[study]:
f.write(code+'\t')
if study == 'AXCPT':
f.write('AllTasks\tAX_RT\tAY_RT\tBX_RT\tBY_RT\n')
else:
f.write('AllTasks\n')
for i, sub in enumerate(subjects):
#for i, sub in enumerate(sorted(study_results.keys(), reverse=True)):
num = den = 0
f.write(sub+':\t')
results = study_results[sub]
#sort codes numerically
codes = sorted([int(key) for key in results.keys()])
num = sum([item[0] for code,item in results.items() if int(code) in studies_tasks[study]])
den = sum([item[1] for code,item in results.items() if int(code) in studies_tasks[study]])
sorted_results = [float(results[str(code)][0])/float(results[str(code)][1]) for code in codes]
for result in sorted_results:
f.write(str(round(result,3))+'\t')
f.write(str(round(float(num)/den,3))+'\t')
if study == 'AXCPT':
f.write(str(rt_ay_avg[i])+'\t')
f.write(str(rt_by_avg[i])+'\t')
f.write(str(rt_bx_avg[i])+'\t')
f.write(str(rt_ax_avg[i])+'\n')
mriaccuracy2R(mod,study,subjType, listPrefix)
print("Completed. See results in /MRI/results/behavioral_accuracy/R/ folder")
def maxFilter(subjID):
##constants
corrThresh = .96
sampleTime = 30
expList = ['BaleenHP']
runDict = {'BaleenHP': ['Run1', 'Run2', 'Run3', 'Run4']}
dataPath = "/cluster/kuperberg/SemPrMM/MEG/data/" + subjID + "/"
badChanFileName = dataPath + subjID + "_bad_chan.txt"
badChanList = readInput.readList(badChanFileName)
print badChanList
badMEG = ''
for chan in badChanList:
if chan[0:3] == 'MEG':
print chan[-4:]
badMEG = badMEG + (chan[-4:]) + ' '
for exp in expList:
for run in runDict[exp]:
in_fif_fname = dataPath + subjID + '_' + exp + run + '_raw.fif'
out_fif_fname = dataPath + subjID + '_' + exp + run + '_MF_raw.fif'
command = (
'maxfilter -f %s -v -frame head -st %s -corr %s -origin 0 0 40 -bad %s -o %s -force'
%
(in_fif_fname, sampleTime, corrThresh, badMEG, out_fif_fname))
print command
st = os.system(command)
print 'Command executed: %s' % command
if st != 0:
raise ValueError('Pb while running : %s' % command)
else:
print(
'Done computing maxFilter. IMPORTANT : Please eye-ball the data !!'
)
def maxFilter(subjID):
##constants
corrThresh = .96
sampleTime = 30
expList = ['BaleenHP']
runDict = {'BaleenHP':['Run1','Run2','Run3','Run4']}
dataPath = "/cluster/kuperberg/SemPrMM/MEG/data/" + subjID + "/"
badChanFileName = dataPath + subjID + "_bad_chan.txt"
badChanList = readInput.readList(badChanFileName)
print badChanList
badMEG = ''
for chan in badChanList:
if chan[0:3] == 'MEG':
print chan[-4:]
badMEG = badMEG + (chan[-4:]) + ' '
for exp in expList:
for run in runDict[exp]:
in_fif_fname = dataPath + subjID + '_' + exp + run + '_raw.fif'
out_fif_fname = dataPath + subjID + '_' + exp + run + '_MF_raw.fif'
command = ('maxfilter -f %s -v -frame head -st %s -corr %s -origin 0 0 40 -bad %s -o %s -force'
% (in_fif_fname, sampleTime, corrThresh, badMEG, out_fif_fname))
print command
st = os.system(command)
print 'Command executed: %s' % command
if st != 0:
raise ValueError('Pb while running : %s' % command)
else:
print ('Done computing maxFilter. IMPORTANT : Please eye-ball the data !!')
colorList = ['k', 'r']
lWidth = 4
ymin, ymax = [-.5, 24]
xmin, xmax = [-100, 600]
data_path = '/cluster/kuperberg/SemPrMM/MEG/data/'
results_path = '/cluster/kuperberg/SemPrMM/MEG/results/sensor_level/MEG_rms/'
channel_path = '/cluster/kuperberg/SemPrMM/MEG/scripts/function_inputs/MEG_Chan_Names/grad_'
channelGroups = ['frontal', 'temporal', 'parietal', 'occipital']
hemList = ['L', 'R']
###Get subject list
subjFile = '/cluster/kuperberg/SemPrMM/MEG/scripts/function_inputs/' + args.prefix + '.txt'
subjects = readInput.readList(subjFile)
print subjects
#subjects = ['1', '2','3']
for group in channelGroups:
pl.clf()
font = {'size': 30}
pl.rc('font', **font)
for hem in hemList:
channelFile = channel_path + hem + group + '.txt'
channelNames = readInput.readList(channelFile)
channelList = []
for item in channelNames:
channelList.append('MEG ' + item)
def spanData2R(subjType, listPrefix):
data_path = '/cluster/kuperberg/SemPrMM/assessment/'
inFile1 = data_path + 'scripts/function_input/' + str(listPrefix) + '.txt'
inFile2 = data_path + 'span/Input/' + 'WM-SpanLog_' + str(subjType)
outFile1 = data_path + 'results/span/R/' + str(listPrefix) + '_WM-Span_Long.txt'
## if (subjType == 'ac'):
## subject_filename = data_path + 'scripts/function_inputs/ac.meg.all.txt'
## if (subjType == 'sc'):
## subject_filename = data_path + 'scripts/function_inputs/sc.meg.all.txt'
## if (subjType == 'ya'):
## subject_filename = data_path + 'scripts/function_inputs/ya.meg.all.txt'
subject_list = readInput.readList(inFile1)
##print subject_list
##
for subject in subject_list:
print subject
#To Find the total number of rejected trials, and percentage inclusion
#subjID = str(subjType)+ str(subject)
totalTrials = 0 # Must be initialised within the loop to refresh for each subject :)
dataTable1=[]
dataTable2=[]
lineTemp = []
lineTemp1 = []
temp = 1
header = []
if os.path.exists(inFile1):
print("File exists")
else:
print("Check the input file name")
myFile1 = open(inFile2, "r")
while temp:
temp = myFile1.readline()
temp1 = temp.strip() # not ('')
if temp1:
temp2 = temp1.split()
dataTable1.append(temp2) # Save information as a list of items in a DataTable
runCount=len(dataTable1)
myFile1.close()
header = dataTable1[0]
span_len = len(header)
#print(runCount)
#print(span_len)
myFile2 = open(outFile1, "w")
myFile2.write("Sub:\t\tSpan\t\tNumCorrect\n")
for i in range(1, runCount):
lineTemp = (dataTable1[i])
##print(lineTemp)
#print(lineTemp[0])
for j in range(1,span_len):
if str(lineTemp[0]) in subject_list: # Compares the subject name to check if it exists in the listPrefix file.
myFile2.write(lineTemp[0] + '\t\t')
myFile2.write(header[j] + '\t\t')
myFile2.write(lineTemp[j])
myFile2.write('\n')
print("Completed. See result in /assessment/results/span/R/ folder")
##Define data file names data_path = '/Volumes/CUTTLEFISH/MEG_Experiments/'+args.exp+'/data/'+args.subjID + '/' raw_fname = data_path + args.subjID + '_' + args.par + '-Filtered_raw.fif' outfile_fname = data_path + 'rej/' + args.subjID + '_' + args.par + '-Filtered_raw_blink.txt' badChan_fname = data_path + args.subjID + '_bad_chan.txt' ##Define default parameters thresh = 3e-13 blinkChanList = [0, 1, 2, 21, 22, 23, 24, 41, 42, 43, 44, 59, 60, 61, 62, 63, 82, 83, 84, 100] # starts at 0 for python winSize = 100 #ms on each side of test sample ##Read in a subject-specific threshold, if it exists if os.path.isfile(data_path + 'rej/rej_thr.txt'): thrString = readInput.readList(data_path + 'rej/rej_thr.txt') thrList = thrString[0].split() thresh = float(thrList[1]) print print 'Threshold used is:',thresh print ##Read in raw data (158 channels x time samples) raw = fiff.Raw(raw_fname) ch_names = raw.info['ch_names'] ##Read in a subject-specific blink-channel list, if it exists if os.path.isfile(data_path + 'rej/' + args.subjID + '_rej_chan.txt'):
ymin = -1e-13
ymax = 1e-13
##Filenames
filename = '/Volumes/CUTTLEFISH/MEG_Experiments/'+args.exp+'/results/Quadrants/'+args.par+'_'+args.subjList+'_'+'quadTest.txt'
myFile = open(filename, "w")
myFile.close()
quadList = ['LA','LP','RA','RP']
subjList = readInput.readList('/Volumes/CUTTLEFISH/MEG_Experiments/'+args.exp + '/subjLists/'+ args.subjList + '.txt')
print subjList[0]
for subj in subjList:
#initialize structure to hold data for each condition
quadData = {}
for cond in args.condList:
quadData[cond] = []
data_path = '/Volumes/CUTTLEFISH/MEG_Experiments/'+args.exp+'/data/'+subj + '/'
data_file = data_path + subj + '_' + args.par
print data_file
quadCount = 0
for quad in quadList:
##Set the factors to examine protocolList = ['MaskedMM_All', 'MaskedMM_All', 'MaskedMM_All'] condList = ['1', '2', '3'] hemList = ['lh','rh'] #labelList = ['G_front_inf-Opercular', 'G_front_inf-Triangul','G_front_inf-Orbital', 'Pole_temporal', 'G_temp_ant-sup-Lateral','G_temp_post-sup-Lateral','S_temporal_ant-sup','S_temporal_post-sup','G_temporal_ant-middle','G_temporal_post-middle','G_temporal_inf','S_temporal_inf','G_pariet_inf-Angular','G_temp_sup-Plan_polar','aparc2009-aMTGSTS','aparc2009-pMTGSTS','aparc2009-IFG','aparc2009-aMTGSTSTP','ya.n24.bal.BaleenHP_300-500_cluster'] labelList = ['aparc-IFG','aparc-pMTGSTS'] ##Convert input times from ms to samples baseline=100 #ms sample1 = int( round( (args.t1+baseline)/1.6667 ) ) sample2 = int( round( (args.t2+baseline)/1.6667 ) ) ###Get subject list subjFile = '/cluster/kuperberg/SemPrMM/MEG/scripts/function_inputs/' + args.prefix + '.txt' subjects = readInput.readList(subjFile) print subjects ################################### ########MAKE DATA TABLE############ ################################### dataTable = [] for x in range(3): print protocolList[x] for label in labelList:
channelGroups = ['ant','post']
hemList = ['left','right']
pl.clf()
for group in channelGroups:
font = {
'weight' : 'bold',
'size' : 16}
pl.rc('font', **font)
#figure(num=None, figsize=(16, 6), dpi=80, facecolor='w', edgecolor='k') # you could use this to change the size of the figure
for hem in hemList:
channelFile = channel_path + hem + '_' + group+ '.txt'
channelList = readInput.readList(channelFile)
if hem == 'left':
if group == 'ant':
pl.subplot(2,2,1)
pl.title("Left Anterior")
else:
pl.subplot(2,2,3)
pl.title("Left Posterior")
else:
if group == 'ant':
pl.subplot(2,2,2)
pl.title("Right Anterior")
else:
pl.subplot(2,2,4)
pl.title("Right Posterior")
args = parser.parse_args()
if args.baseline:
if args.baseline not in args.condList:
sys.exit("Error: Baseline condition does not exist. It must be from condList")
##Filenames
data_path = "/Volumes/CUTTLEFISH/MEG_Experiments/" + args.exp + "/data/" + args.subjID + "/"
data_file = data_path + args.subjID + "_" + args.par
print data_path
print data_file
chans = readInput.readList(data_path + "/sensor_list/" + args.chan_filename + ".txt")
chans = [int(chan) for chan in chans]
print "actual chans as shown in MNE: {}".format(chans)
chans = [chan - 1 for chan in chans] # this accounts for python indexing at 0
print "chans as interpreted by iPython: {}".format(chans)
##Plot condition(s)
cm = plt.get_cmap("cool") # this chooses the colors to use for data lines
fig = plt.figure()
ax = fig.add_subplot(111)
ax.set_color_cycle([cm(1.0 * i / len(args.condList)) for i in range(len(args.condList))])
for cond in args.condList:
condName = cond
all_data[k][sub] = v
except IOError:
pass
return all_data
if __name__ == '__main__':
data_path = '/cluster/kuperberg/SemPrMM/MEG/'
subjType = sys.argv[1]
if (subjType == 'ac'):
subject_filename = data_path + 'scripts/function_inputs/ac.meg.all.txt'
if (subjType == 'sc'):
subject_filename = data_path + 'scripts/function_inputs/sc.n16.meeg.b.txt'
if (subjType == 'ya'):
subject_filename = data_path + 'scripts/function_inputs/ya.meg.all.possible.txt'
subject_list = readInput.readList(subject_filename)
subjects = []
for row in subject_list:
row = subjType + row
subjects.append(row)
print subjects
all_data = get_data(subjects)
for k, v in all_data.items():
#print k, v
##Note:
fname = '/%s/kuperberg/SemPrMM/MEG/results/artifact_rejection/heogveog_rejection/%s_%s_rejTable.txt' % (
pre, subjType, k)
codes = sorted(v[subjType + '12'].keys(),
cmp=lambda x, y: cmp(int(x), int(y))
) ##using subject ID 12 to retrieve item codes
args=parser.parse_args() ##Get the condCode information sys.path.insert(0,'/Volumes/CUTTLEFISH/MEG_Experiments/'+args.exp + '/') fileName =args.exp+'_condCodes' print fileName cc = __import__(fileName) ##importing condCodes ##Initialize path variables and read subject list expPath = '/Volumes/CUTTLEFISH/MEG_Experiments/'+args.exp+'/' data_path = expPath + 'data/' results_path = expPath +'results/' subjList = readInput.readList(expPath + 'subjLists/' + args.subjList+'.txt') ##create structure for mne python to call all the conditions up labelList = cc.condLabels[args.par] # dictionary from trigger to condition sorted by trigger number event_id = collections.OrderedDict(sorted(labelList, key=lambda item : item[0])) print event_id numCond = len(event_id) #initialize structures needed to create grand average allData = [ [] for item in range(numCond) ] ##channel x time MEG data allNave = [ [] for item in range(numCond) ] ##number of trials per condition in ave ###################################################################################
def computeEvents(subjType, par):
data_path = '/cluster/kuperberg/SemPrMM/MEG/'
outFile = data_path + 'results/artifact_rejection/megeeg_rejection/' + str(
subjType) + '_MEEGArtRejSummary_' + str(par)
myFile2 = open(outFile, "w")
if (subjType == 'ac'):
subject_filename = data_path + 'scripts/function_inputs/ac.meg.all.txt'
if (subjType == 'sc'):
subject_filename = data_path + 'scripts/function_inputs/sc.meg.all.txt'
if (subjType == 'ya'):
subject_filename = data_path + 'scripts/function_inputs/ya.meg.all.txt'
subject_list = readInput.readList(subject_filename)
# subject_list = ['9', '14', '12', '3', '1', '6']
print subject_list
for subject in subject_list:
#To Find the total number of rejected trials, and percentage inclusion
subjID = str(subjType) + str(subject)
# subjID = 'sc14'
totalTrials = 0 # Must be initialised within the loop to refresh for each subject :)
totalRejects = 0
trialCount = 0
rtrialCount = 0
pReject = 0
dataTable1 = []
dataTable2 = []
lineTemp = []
lineTemp1 = []
temp = 1
inFile1 = data_path + 'data/' + str(
subjID) + '/ave_projon/logs/' + str(
subjID) + '_MEEGArtReject_' + str(par)
if os.path.exists(inFile1):
myFile1 = open(inFile1, "r")
while temp:
temp = myFile1.readline()
temp1 = temp.strip(
) # when I included (' ') it did not return the items as a list, but when I just wrote () it did the trick!
if temp1:
temp2 = temp1.split()
dataTable1.append(
temp2
) # Save information as a list of items in a DataTable
runCount = len(dataTable1)
myFile1.close()
for i in range(0, len(dataTable1)):
lineTemp = (dataTable1[i])
trialCount = float(lineTemp[0])
rtrialCount = float(lineTemp[1])
totalTrials = totalTrials + trialCount
totalRejects = totalRejects + rtrialCount
pReject = (1 - round(((totalRejects) / float(totalTrials)), 4))
#print(pReject)
# To Display the total number of rejected trials, and percentage
myFile2 = open(outFile, "a")
myFile2.write("\n")
myFile2.write(subjID)
myFile2.write("\n")
myFile2.write("Number of events found:\t")
myFile2.write(str(totalTrials))
myFile2.write("\n")
myFile2.write("Number of events rejected:\t")
myFile2.write(str(totalRejects))
myFile2.write("\n")
myFile2.write("MEG/EEG Inclusion Rate:\t")
myFile2.write(str(pReject))
myFile2.write("\n")
# To Find the name of the bad channels rejected
items = []
chans = []
chantot = []
temp3 = 1
dataTable3 = []
dataTable4 = []
linetemp1 = []
inFile2 = data_path + 'data/' + str(
subjID) + '/ave_projon/logs/' + str(
subjID) + '_MEEGArtReject-BadChan_' + str(par)
myFile3 = open(inFile2, "r")
while temp3:
temp3 = myFile3.readline()
temp4 = temp3.strip()
if temp4:
temp5 = temp4.split()
dataTable3.append(
temp5
) # Save information as a list of items in a DataTable
for i in range(0, len(dataTable3)):
lineTemp1 = dataTable3[i]
#print(lineTemp1[0])
chans.append(lineTemp1[0])
chantot.append(lineTemp1[1])
items = list(set(chans))
#print(items)
items = sorted(
items, key=itemgetter(0)
) # To print Gradiometer, magnetometers and the the EEG channels in oreder.
# To Display the name of the bad channels rejected
myFile2.write("Number of Times MEG/EEG Channels Rejected")
myFile2.write("\n")
for i in range(0, len(items)):
x = 0
myFile2.write(str(items[i]))
for j in range(0, len(chans)):
if items[i] == chans[j]:
x = x + int(chantot[j])
#print(items[i])
#print(x)
myFile2.write("\t")
myFile2.write(str(x))
myFile2.write("\n")
myFile2.close()
myFile3.close()
data_file = data_path + args.filename + '_' + 'ga'
print data_path
print data_file
quadList = ['LA','LP','RA','RP']
for quad in quadList: ##########
args.chan_filename = '/Volumes/CUTTLEFISH/MNE_scripts/function_inputs/quad-'+quad+'.txt'
plot_out= data_path+'Quadrants/'+args.filename+'_'+quad+'.png' #individual plots
chans = readInput.readList(args.chan_filename)
chans = [int(chan) for chan in chans]
#print "actual chans as shown in MNE: {}".format(chans)
#chans = [chan-1 for chan in chans] # this accounts for python indexing at 0
print "chans as interpreted by iPython: {}".format(chans)
##Plot condition(s)
cm = plt.get_cmap('cool') # this chooses the colors to use for data lines
fig = plt.figure()
ax = fig.add_subplot(111)
ax.set_color_cycle([cm(1.*i/len(args.condList)) for i in range(len(args.condList))])
for cond in args.condList:
condName = cond
results_path = '/cluster/kuperberg/SemPrMM/MEG/results/sensor_level/MEG_rms/rms_ga/'
channel_path = '/cluster/kuperberg/SemPrMM/MEG/scripts/function_inputs/MEG_Chan_Names/grad_'
channelGroups = ['frontal','temporal','parietal','occipital']
hemList = ['L', 'R']
for group in channelGroups:
pl.clf()
font = {
'size' : 30}
pl.rc('font', **font)
for hem in hemList:
channelFile = channel_path + hem + group+ '.txt'
channelNames = readInput.readList(channelFile)
channelList = []
for item in channelNames:
channelList.append('MEG ' + item)
print group
print channelList
if hem == 'L':
pl.subplot(121)
else:
pl.subplot(122)
for c in range(2):
file = data_path + args.prefix +'-ave.fif'
print file
print 'set ',condList[c]
ymin,ymax = [-.5,26]
xmin,xmax = [-100,660]
data_path = '/cluster/kuperberg/SemPrMM/MEG/data/'
results_path = '/cluster/kuperberg/SemPrMM/MEG/results/sensor_level/MEG_rms/'
channel_path = '/cluster/kuperberg/SemPrMM/MEG/scripts/function_inputs/MEG_Chan_Names/grad_'
channelGroups = ['frontal','temporal','parietal','occipital']
##channelGroups = ['occipital']
hemList = ['L', 'R']
###Get subject list
subjFile = '/cluster/kuperberg/SemPrMM/MEG/scripts/function_inputs/' + args.prefix + '.txt'
subjects = readInput.readList(subjFile)
print subjects
#subjects = ['1', '2','3']
for group in channelGroups:
pl.clf()
font = {
'size' : 16}
pl.rc('font', **font)
for hem in hemList:
channelFile = channel_path + hem + group+ '.txt'
channelNames = readInput.readList(channelFile)
channelList = []
for item in channelNames:
data_path = '/cluster/kuperberg/SemPrMM/MEG/results/sensor_level/ga_fif/'
results_path = '/cluster/kuperberg/SemPrMM/MEG/results/sensor_level/MEG_rms/rms_ga/'
channel_path = '/cluster/kuperberg/SemPrMM/MEG/scripts/function_inputs/MEG_Chan_Names/grad_'
channelGroups = ['frontal', 'temporal', 'parietal', 'occipital']
hemList = ['L', 'R']
for group in channelGroups:
pl.clf()
font = {'size': 30}
pl.rc('font', **font)
for hem in hemList:
channelFile = channel_path + hem + group + '.txt'
channelNames = readInput.readList(channelFile)
channelList = []
for item in channelNames:
channelList.append('MEG ' + item)
print group
print channelList
if hem == 'L':
pl.subplot(121)
else:
pl.subplot(122)
for c in range(2):
file = data_path + args.prefix + '-ave.fif'
print file
print 'set ', condList[c]
evoked = mne.fiff.read_evoked(file,
myFile2.write(lineTemp[j] + '\n')
myFile2.write('\n')
if __name__ == "__main__":
modalities = ['MRI']
studies = ['MaskedMM']
#subjType = ['ac', 'sc', 'ya']
all_lines = 0
for mod in modalities:
subjects = readInput.readList('/cluster/kuperberg/SemPrMM/MRI/scripts/input/' +listPrefix)
print(subjects)
with open('/cluster/kuperberg/SemPrMM/MRI/results/behavioral_accuracy/'+mod+'_'+listPrefix+'_'+study+'_accuracy-short_new.log','w') as d:
#print(study)
d.write('sub' + '\t' + 'Acc_AniPrime' + 'Acc_AniTarg' +'\n')
for sub in subjects:
acc_anipri_avg = 0.0
acc_anitar_avg = 0.0
acc_ani_avg = 0.0
rt_anipri_avg = 0.0
rt_anitar_avg = 0.0
rt_ani_avg = 0.0
acc_AniPrime = 0.0
acc_AniTar = 0.0
acc_Ani = 0.0
channelGroups = ['ant','post']
hemList = ['left','right']
for group in channelGroups:
pl.clf()
font = {
'weight' : 'bold',
'size' : 16}
pl.rc('font', **font)
#figure(num=None, figsize=(16, 6), dpi=80, facecolor='w', edgecolor='k') # you could use this to change the size of the figure
for hem in hemList:
channelFile = channel_path + hem + '_' + group+ '.txt'
channelList = readInput.readList(channelFile)
if hem == 'left':
pl.subplot(121)
else:
pl.subplot(122)
for c in range(2):
##get the data
file = data_path + prefixList[c] +'-ave.fif'
##file = data_path + args.prefix1 +'-ave.fif'
print file
print 'set ',condList[c]
evoked = fiff.Evoked(file,setno=condList[c],baseline=(-100,0),proj=False)
times=evoked.times*1000
sel = fiff.pick_types(evoked.info,meg=False,eeg=False,include=channelList)
args = parser.parse_args()
exp = args.exp ## msabri
subjID = args.subjID
par = args.par ##Left Right etc.,
set1 = args.set1
condName = [args.set1] ##If set1 and set2 are condition names
####Setup Subject Speciifc Information
data_path = '/home/custine/MEG/data/' +exp+'/'+subjID + '/ave_projon/'
results_path = data_path +'plots/'
fname = data_path + subjID +'_' +par+'-ave.fif'
out_fname = results_path + subjID + '_' + par +'_'+set1+'_meg_evoked_color.png'
print out_fname
#chan_path = '/home/custine/MEG/scripts/function_inputs/MEG_Chan_Names/'
chan_fname = '/home/custine/MEG/scripts/function_inputs/MEG_Chan_Number/MEG_chan_number_list-m.txt'
chan_names = readInput.readList(chan_fname)
#chan_list = []
#for item in chan_names:
# chan_list.append('MEG'+item)
chan_names = [int(chan) for chan in chan_names]
####Reading the Evoked data structure
for c in condName:
print c
evoked = mne.fiff.Evoked(fname, setno='epochs_'+c , baseline = (None, 0))
#evoked = mne.fiff.Evoked(fname, setno = c , baseline = (None, 0)) ##Use this if you are using condition numbers
#badChanSet = set(evoked.info['bads'])
sel = chan_names
#sel = list(set(chan_names) - set(badChanSet))
print sel
data = evoked.data[sel]
all_data[k] = {}
all_data[k][sub] = v
except IOError:
pass
return all_data
if __name__ == '__main__':
data_path = '/cluster/kuperberg/SemPrMM/MEG/'
subjType = sys.argv[1]
if (subjType == 'ac'):
subject_filename = data_path + 'scripts/function_inputs/ac.meg.all.txt'
if (subjType == 'sc'):
subject_filename = data_path + 'scripts/function_inputs/sc.n16.meeg.b.txt'
if (subjType == 'ya'):
subject_filename = data_path + 'scripts/function_inputs/ya.meg.all.possible.txt'
subject_list = readInput.readList(subject_filename)
subjects = []
for row in subject_list:
row = subjType+row
subjects.append(row)
print subjects
all_data = get_data(subjects)
for k,v in all_data.items():
#print k, v
##Note:
fname = '/%s/kuperberg/SemPrMM/MEG/results/artifact_rejection/heogveog_rejection/%s_%s_rejTable.txt' % (pre, subjType, k)
codes = sorted(v[subjType+'12'].keys(), cmp=lambda x,y: cmp(int(x), int(y))) ##using subject ID 12 to retrieve item codes
print codes
code_line = '\t\t%s' % '\t\t\t'.join(codes)
#print code_line
###############################################################
### Get User Input
parser = argparse.ArgumentParser(description = 'Get user input..')
parser.add_argument('exp', type = str)
parser.add_argument('par', type = str)
args = parser.parse_args()
exp = args.exp ## msabri
par = args.par ##Left Right etc.,
####Setup Subject Speciifc Information
data_path = '/home/custine/MEG/data/' + exp
subjList = readInput.readList('/home/custine/MEG/scripts/function_inputs/'+exp+'_subjList.txt')
result_path = '/home/custine/MEG/results/sensor_level/ga_fif/'
print subjList
event_id ={}
condName = {}
labels = cc.condLabels[par]
for row in labels:
event_id[row[1]] = int(row[0])
print event_id
print 'Number of Conditions...'
lenCond = len(event_id)
print lenCond
allData = [ [] for item in range(lenCond)]
def spanData2R(subjType, listPrefix):
data_path = '/cluster/kuperberg/SemPrMM/assessment/'
inFile1 = data_path + 'scripts/function_input/' + str(listPrefix) + '.txt'
inFile2 = data_path + 'span/Input/' + 'WM-SpanLog_' + str(subjType)
outFile1 = data_path + 'results/span/R/' + str(
listPrefix) + '_WM-Span_Long.txt'
## if (subjType == 'ac'):
## subject_filename = data_path + 'scripts/function_inputs/ac.meg.all.txt'
## if (subjType == 'sc'):
## subject_filename = data_path + 'scripts/function_inputs/sc.meg.all.txt'
## if (subjType == 'ya'):
## subject_filename = data_path + 'scripts/function_inputs/ya.meg.all.txt'
subject_list = readInput.readList(inFile1)
##print subject_list
##
for subject in subject_list:
print subject
#To Find the total number of rejected trials, and percentage inclusion
#subjID = str(subjType)+ str(subject)
totalTrials = 0 # Must be initialised within the loop to refresh for each subject :)
dataTable1 = []
dataTable2 = []
lineTemp = []
lineTemp1 = []
temp = 1
header = []
if os.path.exists(inFile1):
print("File exists")
else:
print("Check the input file name")
myFile1 = open(inFile2, "r")
while temp:
temp = myFile1.readline()
temp1 = temp.strip() # not ('')
if temp1:
temp2 = temp1.split()
dataTable1.append(
temp2) # Save information as a list of items in a DataTable
runCount = len(dataTable1)
myFile1.close()
header = dataTable1[0]
span_len = len(header)
#print(runCount)
#print(span_len)
myFile2 = open(outFile1, "w")
myFile2.write("Sub:\t\tSpan\t\tNumCorrect\n")
for i in range(1, runCount):
lineTemp = (dataTable1[i])
##print(lineTemp)
#print(lineTemp[0])
for j in range(1, span_len):
if str(
lineTemp[0]
) in subject_list: # Compares the subject name to check if it exists in the listPrefix file.
myFile2.write(lineTemp[0] + '\t\t')
myFile2.write(header[j] + '\t\t')
myFile2.write(lineTemp[j])
myFile2.write('\n')
print("Completed. See result in /assessment/results/span/R/ folder")
###############################################################################
# Parameters
parser = argparse.ArgumentParser(description='Get input')
parser.add_argument('prefix', type=str)
parser.add_argument('protocol', type=str)
parser.add_argument('cond1', type=int)
parser.add_argument('cond2', type=int)
parser.add_argument('t1', type=float)
parser.add_argument('t2', type=float)
parser.add_argument('model', type=str)
parser.add_argument('threshold', type=float)
args = parser.parse_args()
subjFile = '/cluster/kuperberg/SemPrMM/MEG/scripts/function_inputs/' + args.prefix + '.txt'
subjects = readInput.readList(subjFile)
print subjects
time_interval = (
args.t1, args.t2
) #If you set a real time_interval, you will average across this and do spatial clusters
dec = None
#time_interval = None #If you set time_interval to None, it will do spatiotemporal clusters
#dec = 10 # this sets the temporal decimation factor. e.g. if you sampled 600Hz and set this to 3, you will downsample the test to every 5 ms
thresholds = [
args.threshold
] #This sets the threshold for the first stage of the test. You have the option of including more than one threshold to see what happens when it changes
#def stat_fun(X):
def computeEvents(subjType, par):
data_path = '/cluster/kuperberg/SemPrMM/MEG/'
outFile = data_path + 'results/artifact_rejection/megeeg_rejection/' + str(subjType) + '_MEEGArtRejSummary_' + str(par)
myFile2 = open(outFile, "w")
if (subjType == 'ac'):
subject_filename = data_path + 'scripts/function_inputs/ac.meg.all.txt'
if (subjType == 'sc'):
subject_filename = data_path + 'scripts/function_inputs/sc.meg.all.txt'
if (subjType == 'ya'):
subject_filename = data_path + 'scripts/function_inputs/ya.meg.all.txt'
subject_list = readInput.readList(subject_filename)
# subject_list = ['9', '14', '12', '3', '1', '6']
print subject_list
for subject in subject_list:
#To Find the total number of rejected trials, and percentage inclusion
subjID = str(subjType)+ str(subject)
# subjID = 'sc14'
totalTrials = 0 # Must be initialised within the loop to refresh for each subject :)
totalRejects = 0
trialCount=0
rtrialCount=0
pReject=0
dataTable1=[]
dataTable2=[]
lineTemp = []
lineTemp1 = []
temp = 1
inFile1 = data_path + 'data/' + str(subjID) + '/ave_projon/logs/' + str(subjID) + '_MEEGArtReject_' + str(par)
if os.path.exists(inFile1):
myFile1 = open(inFile1, "r")
while temp:
temp = myFile1.readline()
temp1 = temp.strip() # when I included (' ') it did not return the items as a list, but when I just wrote () it did the trick!
if temp1:
temp2 = temp1.split()
dataTable1.append(temp2) # Save information as a list of items in a DataTable
runCount=len(dataTable1)
myFile1.close()
for i in range(0, len(dataTable1)):
lineTemp = (dataTable1[i])
trialCount=float(lineTemp[0])
rtrialCount=float(lineTemp[1])
totalTrials = totalTrials + trialCount
totalRejects = totalRejects + rtrialCount
pReject=(1-round(((totalRejects)/float(totalTrials)),4))
#print(pReject)
# To Display the total number of rejected trials, and percentage
myFile2 = open(outFile, "a")
myFile2.write("\n")
myFile2.write(subjID)
myFile2.write("\n")
myFile2.write("Number of events found:\t")
myFile2.write(str(totalTrials))
myFile2.write("\n")
myFile2.write("Number of events rejected:\t")
myFile2.write(str(totalRejects))
myFile2.write("\n")
myFile2.write("MEG/EEG Inclusion Rate:\t")
myFile2.write(str(pReject))
myFile2.write("\n")
# To Find the name of the bad channels rejected
items=[]
chans=[]
chantot=[]
temp3 = 1
dataTable3=[]
dataTable4=[]
linetemp1=[]
inFile2 = data_path + 'data/' + str(subjID) + '/ave_projon/logs/' + str(subjID) + '_MEEGArtReject-BadChan_' + str(par)
myFile3 = open(inFile2, "r")
while temp3:
temp3 = myFile3.readline()
temp4 = temp3.strip()
if temp4:
temp5 = temp4.split()
dataTable3.append(temp5) # Save information as a list of items in a DataTable
for i in range(0, len(dataTable3)):
lineTemp1 = dataTable3[i]
#print(lineTemp1[0])
chans.append(lineTemp1[0])
chantot.append(lineTemp1[1])
items=list(set(chans))
#print(items)
items = sorted(items, key=itemgetter(0)) # To print Gradiometer, magnetometers and the the EEG channels in oreder.
# To Display the name of the bad channels rejected
myFile2.write("Number of Times MEG/EEG Channels Rejected")
myFile2.write("\n")
for i in range(0, len(items)):
x=0
myFile2.write(str(items[i]))
for j in range(0, len(chans)):
if items[i] == chans[j]:
x = x + int(chantot[j])
#print(items[i])
#print(x)
myFile2.write("\t")
myFile2.write(str(x))
myFile2.write("\n")
myFile2.close()
myFile3.close()