-
Notifications
You must be signed in to change notification settings - Fork 4
/
3_run_audio.py
110 lines (94 loc) · 3.85 KB
/
3_run_audio.py
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
import os, sys, datetime, pickle
import subprocess, logging, time
import pp
import scipy as sp
import numpy as np
import matplotlib.pylab as pl
import pandas as pd
from IPython import embed as shell
import glob
project_directory = '/home/degee/research/2016_pupil_yesno_audio/data2/'
raw_data = '/home/raw_data/UvA/Donner_lab/2017_eLife/3_pupil_yesno_audio/'
sjs_all = []
subjects = [
'sub-01',
# 'sub-02',
# 'sub-03',
# 'sub-04',
# 'sub-05',
# 'sub-06',
# 'sub-07',
# 'sub-08',
# 'sub-09',
# 'sub-10',
# 'sub-11',
# 'sub-12',
# 'sub-13',
# 'sub-14',
# 'sub-15',
# 'sub-16',
# 'sub-17',
# 'sub-18',
# 'sub-19',
# 'sub-20',
# 'sub-21',
# 'sub-22',
# 'sub-23',
# 'sub-24',
]
for s in subjects:
runs = np.sort([r.split('/')[-1] for r in glob.glob(os.path.join(raw_data, s, 'sub-*'))])
sjs_all.append([s, runs])
def run_subject(sj, raw_data, project_directory, exp_name = 'detection_pupil'):
import defs_pupil_audio
import numpy as np
session_nrs = [int(f.split('ses-')[-1][:1]) for f in sj[1]]
aliases = []
for i in range(len(sj[1])):
aliases.append('detection_{}_{}'.format(i+1, session_nrs[i]))
raw_data = [os.path.join(raw_data, sj[0], f) for f in sj[1]]
experiment = 2
if sj[0] in ['sub-01', 'sub-02', 'sub-03', 'sub-04', 'sub-05', 'sub-06', 'sub-09', 'sub-10', 'sub-11', 'sub-14', 'sub-18', 'sub-19', 'sub-20', 'sub-23', 'sub-24',]:
version = 1
else:
version = 2
# ------------------
# PREPROCESSING: -
# ------------------
# pupilPreprocessSession = defs_pupil_audio.pupilPreprocessSession(subject = sj[0], experiment_name = exp_name, experiment_nr = experiment, version = version, sample_rate_new=50, project_directory = project_directory,)
# pupilPreprocessSession.import_raw_data(raw_data, aliases)
# pupilPreprocessSession.delete_hdf5()
# pupilPreprocessSession.import_all_data(aliases)
# for alias in aliases:
# pupilPreprocessSession.process_runs(alias, artifact_rejection='strict', create_pupil_BOLD_regressor=False)
# pass
# pupilPreprocessSession.process_across_runs(aliases)
return True
def analyze_group(project_directory, exp_name = 'detection_pupil'):
import defs_pupil_audio
# ------------------
# ACROSS SUBJECTS: -
# ------------------
subjects = ['sub-01', 'sub-02', 'sub-03', 'sub-04', 'sub-05', 'sub-06', 'sub-07', 'sub-08', 'sub-09', 'sub-10', 'sub-11', 'sub-12', 'sub-13', 'sub-14', 'sub-15', 'sub-16', 'sub-17', 'sub-18', 'sub-19', 'sub-20', 'sub-21', 'sub-22', 'sub-23', 'sub-24',]
# pupilAnalysisSessionAcross = defs_pupil_audio.pupilAnalysesAcross(subjects=subjects, experiment_name=exp_name, project_directory=project_directory)
# pupilAnalysisSessionAcross.behavior_choice()
# pupilAnalysisSessionAcross.behavior_normalized(prepare=False)
# pupilAnalysisSessionAcross.SDT_correlation(bins=5)
return True
def analyze_subjects(sjs_all):
if len(sjs_all) > 1:
job_server = pp.Server(ppservers=())
start_time = time.time()
jobs = [(sj, job_server.submit(run_subject,(sj, raw_data, project_directory), (), ('PupilYesNoDetection',))) for sj in sjs_all]
results = []
for s, job in jobs:
job()
print "Time elapsed: ", time.time() - start_time, "s"
job_server.print_stats()
else:
run_subject(sjs_all[0], raw_data=raw_data, project_directory=project_directory)
def main():
analyze_subjects(sjs_all)
analyze_group(project_directory=project_directory, exp_name='detection_pupil')
if __name__ == '__main__':
main()