json_file = "settings.json"
print("USING:", json_file)
# opening a json file
with open(json_file) as pipeline_file:
parameters = json.load(pipeline_file)
path = parameters["dataset_path"]
sfreq = parameters["downsample_dataset"]
sub_path = op.join(path, "data")
der_path = op.join(path, "derivatives")
files.make_folder(der_path)
proc_path = op.join(der_path, "processed")
files.make_folder(proc_path)
subjects = files.get_folders_files(sub_path)[0]
subjects.sort()
subject = subjects[index]
subject_id = subject.split("/")[-1]
meg_path = op.join(subject, "ses-01", "meg")
sub_path = op.join(proc_path, subject_id)
files.make_folder(sub_path)
dss = files.get_folders_files(meg_path)[0]
dss = [i for i in dss if "ds" in i]
dss.sort()
for ds in dss:
print("INPUT RAW FILE:", ds)
import pandas as pd
try:
subjects_path = str(sys.argv[1])
except:
subjects_path = "/home/mszul/datasets/explicit_implicit_beta/derivatives/processed"
try:
output_path = str(sys.argv[2])
except:
output_path = "/home/mszul/git/DANC_learning_beh/data"
print(subjects_path, op.exists(subjects_path))
print(output_path, op.exists(output_path))
subs = files.get_folders_files(subjects_path)[0]
subs.sort()
csv_files = []
for sub in subs:
print(sub)
csvs = files.get_files(sub, "sub", "-beh.csv")[2]
csvs.sort
csv_files.extend(csvs)
all_data = []
for i in csv_files:
sub_id = i.split(sep)[-2]
file_data = pd.read_csv(i)
file_data.subject_id = sub_id
all_data.append(file_data)
json_file = "settings.json"
print("USING:", json_file)
# opening a json file
with open(json_file) as pipeline_file:
parameters = json.load(pipeline_file)
path = parameters["dataset_path"]
sfreq = parameters["downsample_dataset"]
sub_path = op.join(path, "data")
der_path = op.join(path, "derivatives")
files.make_folder(der_path)
proc_path = op.join(der_path, "processed")
files.make_folder(proc_path)
subjects = files.get_folders_files(sub_path)[0]
subjects.sort()
for subject in subjects:
subject_id = subject.split("/")[-1]
meg_path = op.join(subject, "ses-01", "meg")
if len(files.get_folders_files(meg_path)[0]) > 0:
continue
else:
sub_path = op.join(proc_path, subject_id)
files.make_folder(sub_path)
zip_file = files.get_files(meg_path, "MEG", ".zip")[2][0]
print(files.get_files(meg_path, "MEG", ".zip")[1])
json_file = "settings.json"
print("USING:", json_file)
# opening a json file
with open(json_file) as pipeline_file:
parameters = json.load(pipeline_file)
path = parameters["dataset_path"]
sfreq = parameters["downsample_dataset"]
sub_path = op.join(path, "data")
der_path = op.join(path, "derivatives")
files.make_folder(der_path)
proc_path = op.join(der_path, "processed")
files.make_folder(proc_path)
subjects = files.get_folders_files(proc_path)[0]
subjects.sort()
subject = subjects[index]
subject_id = subject.split("/")[-1]
meg_path = op.join(subject, "ses-01", "meg")
sub_path = op.join(proc_path, subject_id)
files.make_folder(sub_path)
qc_folder = op.join(sub_path, "QC")
files.make_folder(qc_folder)
raw_paths = files.get_files(sub_path, subject_id, "-raw.fif")[2]
raw_paths.sort()
event_paths = files.get_files(sub_path, subject_id, "-eve.fif")[2]
# opening a json file
with open(json_file) as pipeline_file:
parameters = json.load(pipeline_file)
path = parameters["dataset_path"]
sfreq = parameters["downsample_dataset"]
hi_pass = parameters["hi_pass_filter"]
sub_path = op.join(path, "data")
der_path = op.join(path, "derivatives")
files.make_folder(der_path)
proc_path = op.join(der_path, "processed")
files.make_folder(proc_path)
subjects = files.get_folders_files(proc_path)[0]
subjects.sort()
subject = subjects[index]
subject_id = subject.split("/")[-1]
sub_path = op.join(proc_path, subject_id)
files.make_folder(sub_path)
#setting the paths and extracting files
slt_mot_paths = [i for i in files.get_folders_files(sub_path)[0] if "motor" in i]
slt_vis_paths = [i for i in files.get_folders_files(sub_path)[0] if "visual" in i]
epo_mot_paths = files.get_files(sub_path, "sub", "motor-epo.fif")[2]
epo_vis_paths = files.get_files(sub_path, "sub", "visual-epo.fif")[2]
beh_match_path = files.get_files(sub_path, "sub", "beh-match.json")[2][0]
with open(beh_match_path) as f:
beh_match = json.load(f)
parameters = json.load(pipeline_file)
def split_and_eval(x):
return [eval(i) for i in x.split(",")]
path = parameters["dataset_path"]
sfreq = parameters["downsample_dataset"]
der_path = op.join(path, "derivatives")
files.make_folder(der_path)
proc_path = op.join(der_path, "processed")
files.make_folder(proc_path)
subjects = files.get_folders_files(proc_path)[0]
subjects.sort()
subject = subjects[index]
subject_id = subject.split("/")[-1]
print(subject)
raw_meg_dir = op.join(path, "data")
raw_meg_path = op.join(raw_meg_dir, subject_id, "ses-01", "meg")
ds_paths = files.get_folders_files(raw_meg_path)[0]
ds_paths = [i for i in ds_paths if "misc" not in i]
ds_paths.sort()
res4_paths = [files.get_files(i, "", ".res4")[2][0] for i in ds_paths]
res4_paths.sort()
fs_folder = op.join(der_path, "freesurfer", subject_id)
surface_file = op.join(fs_folder, "pial.ds.gii")
