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fix yaml to run on schedule, add more tests, & move file configuratio…
…n instructions from yaml file to python files update demo
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,96 @@ | ||
| import os, glob, shutil, pytest, numpy as np, pandas as pd | ||
| from neurocaps.extraction import TimeseriesExtractor | ||
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| dir = os.path.dirname(__file__) | ||
| bids_dir = os.path.join(dir, "ds000031_R1.0.4_ses001-022/ds000031_R1.0.4/") | ||
| pipeline_name = "fmriprep_1.0.0/fmriprep" | ||
| confounds=["Cosine*", "aComp*", "Rot*"] | ||
| parcel_approach = {"Custom": {"maps": os.path.join(dir, "HCPex.nii.gz")}} | ||
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| work_dir = os.path.join(bids_dir,"derivatives",pipeline_name) | ||
| # Duplicate data to create a subject 02 folder | ||
| cmd = f"mkdir -p {work_dir}/sub-02 && cp -r {work_dir}/sub-01/* {work_dir}/sub-02/" | ||
| os.system(cmd) | ||
| files = glob.glob(os.path.join(work_dir, "sub-02/ses-002/func", "*")) | ||
| [os.rename(x,x.replace("sub-01_","sub-02_" )) for x in files] | ||
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| # Add another session for sub 01 | ||
| cmd = f"mkdir -p {work_dir}/sub-01/ses-003 && cp -r {work_dir}/sub-01/ses-002/* {work_dir}/sub-01/ses-003" | ||
| os.system(cmd) | ||
| files = glob.glob(os.path.join(work_dir, "sub-01/ses-003/func", "*")) | ||
| [os.rename(x,x.replace("ses-002_","ses-003_" )) for x in files] | ||
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| # Add second run to sub_01 | ||
| files = glob.glob(os.path.join(work_dir, "sub-01/ses-002/func","*")) | ||
| [shutil.copyfile(x,x.replace("run-001","run-002")) for x in files] | ||
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| # Modify confound data for run 002 of subject 01 and subject 02 | ||
| confound_files = glob.glob(os.path.join(work_dir, "sub-01/ses-002/func","*run-002*confounds_timeseries.tsv")) + glob.glob(os.path.join(work_dir, "sub-02/ses-002/func","*run-001*confounds_timeseries.tsv")) | ||
| for file in confound_files: | ||
| confound_df = pd.read_csv(file, sep="\t") | ||
| confound_df["Cosine00"] = [x[0] for x in np.random.rand(40,1)] | ||
| confound_df.to_csv(file, sep="\t", index=None) | ||
|
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| # Should be able to retrieve and append data for each run and subject; Demonstrates it can retrieve subject specific file content | ||
| @pytest.mark.parametrize("n_cores", [None,1]) | ||
| def test_append(n_cores): | ||
| parcel_approach = {"Schaefer": {"yeo_networks": 7}} | ||
| extractor = TimeseriesExtractor(parcel_approach=parcel_approach, standardize="zscore_sample", | ||
| use_confounds=True, detrend=True, low_pass=0.15, high_pass=0.08, | ||
| confound_names=confounds) | ||
|
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| extractor.get_bold(bids_dir=bids_dir, task="rest", session="002",pipeline_name=pipeline_name, tr=1.2, n_cores=n_cores) | ||
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| assert extractor.subject_timeseries["01"]["run-001"].shape == (40,400) | ||
| assert extractor.subject_timeseries["01"]["run-002"].shape == (40,400) | ||
| assert extractor.subject_timeseries["02"]["run-001"].shape == (40,400) | ||
|
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||
| assert ["run-001", "run-002"] == list(extractor.subject_timeseries["01"]) | ||
| assert ["run-001"] == list(extractor.subject_timeseries["02"]) | ||
| assert not np.array_equal(extractor.subject_timeseries["01"]["run-001"], extractor.subject_timeseries["01"]["run-002"]) | ||
| assert not np.array_equal(extractor.subject_timeseries["02"]["run-001"], extractor.subject_timeseries["01"]["run-002"]) | ||
|
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||
| @pytest.mark.parametrize("runs",["001", ["002"]]) | ||
| def test_runs(runs): | ||
| parcel_approach = {"Schaefer": {"n_rois": 400}} | ||
| extractor = TimeseriesExtractor(parcel_approach=parcel_approach, standardize="zscore_sample", | ||
| use_confounds=True, detrend=True, low_pass=0.15, high_pass=0.08, | ||
| confound_names=confounds) | ||
|
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| extractor.get_bold(bids_dir=bids_dir, task="rest", session="002",runs=runs, pipeline_name=pipeline_name, tr=1.2) | ||
|
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| if runs == "001": | ||
| assert ["01", "02"] == list(extractor.subject_timeseries) | ||
| assert extractor.subject_timeseries["01"]["run-001"].shape == (40,400) | ||
| assert extractor.subject_timeseries["02"]["run-001"].shape == (40,400) | ||
|
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| assert ["run-001"] == list(extractor.subject_timeseries["01"]) | ||
| assert ["run-001"] == list(extractor.subject_timeseries["02"]) | ||
| assert not np.array_equal(extractor.subject_timeseries["02"]["run-001"], extractor.subject_timeseries["01"]["run-001"]) | ||
| else: | ||
| assert ["01"] == list(extractor.subject_timeseries) | ||
| assert ["run-002"] == list(extractor.subject_timeseries["01"]) | ||
|
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||
| def test_session(): | ||
| parcel_approach = {"Schaefer": {"yeo_networks": 7}} | ||
| extractor = TimeseriesExtractor(parcel_approach=parcel_approach, standardize="zscore_sample", | ||
| use_confounds=True, detrend=True, low_pass=0.15, high_pass=0.08, | ||
| confound_names=confounds) | ||
|
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| extractor.get_bold(bids_dir=bids_dir, task="rest", session="003",pipeline_name=pipeline_name, tr=1.2) | ||
|
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| # Only sub 01 and run-001 should be in subject_timeseries | ||
| assert extractor.subject_timeseries["01"]["run-001"].shape == (40,400) | ||
|
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| assert ["run-001"] == list(extractor.subject_timeseries["01"]) | ||
| assert ["02"] not in list(extractor.subject_timeseries) | ||
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| def test_session_error(): | ||
| parcel_approach = {"Schaefer": {"yeo_networks": 7}} | ||
| extractor = TimeseriesExtractor(parcel_approach=parcel_approach, standardize="zscore_sample", | ||
| use_confounds=True, detrend=True, low_pass=0.15, high_pass=0.08, | ||
| confound_names=confounds) | ||
|
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| # Should raise value error since sub-01 will have 2 sessions detected | ||
| with pytest.raises(ValueError): | ||
| extractor.get_bold(bids_dir=bids_dir, task="rest",pipeline_name=pipeline_name, tr=1.2) |
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