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Updated main.py #11

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Updated main.py #11

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54cd91b
Updated main.py
hfxcarl Dec 21, 2023
3371c30
[pre-commit.ci] auto fixes from pre-commit.com hooks
pre-commit-ci[bot] Dec 21, 2023
2582870
Update main.py
hfxcarl Dec 21, 2023
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22 changes: 12 additions & 10 deletions main.py
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Original file line number Diff line number Diff line change
Expand Up @@ -7,7 +7,8 @@
import numpy as np
from sklearn import covariance

from nilearn import input_data, datasets
from nilearn.input_data import NiftiLabelsMasker
from nilearn.datasets import fetch_atlas_basc_multiscale_2015

###############################################################################
# Functions used to build the container
Expand All @@ -18,7 +19,7 @@
def copy_atlas():
if not os.path.exists(ATLAS_DIR):
os.makedirs(ATLAS_DIR)
atlas_filename = datasets.fetch_atlas_basc_multiscale_2015().scale122
atlas_filename = fetch_atlas_basc_multiscale_2015().scale122
shutil.copy(atlas_filename, os.path.join(ATLAS_DIR, ATLAS_FILENAME))


Expand Down Expand Up @@ -50,19 +51,20 @@ def participant_level(args, subjects_to_analyze):
# Retrieve the atlas
atlas_filename = os.path.join(os.path.dirname(__file__),
ATLAS_DIR, ATLAS_FILENAME)
# build masker
masker = NiftiLabelsMasker(
labels_img=atlas_filename,
standardize=True,
detrend=True,
verbose=3)

# find all RS scans and extract time-series on them
for subject_label in subjects_to_analyze:
for fmri_file in glob(os.path.join(args.bids_dir,
func_files = glob(os.path.join(args.bids_dir,
"derivatives",
"sub-%s" % subject_label,
"func", "*_hmc_mni.nii.gz")
):
masker = input_data.NiftiLabelsMasker(
labels_img=atlas_filename,
standardize=True,
detrend=True,
verbose=3)
"func", "*_hmc_mni.nii.gz"))
for fmri_file in func_files:
time_series = masker.fit_transform(fmri_file)
out_file = os.path.split(fmri_file)[-1].replace("_hmc_mni.nii.gz",
"_time_series.tsv")
Expand Down