def test_integration_four_echo(skip_integration):
""" Integration test of the full tedana workflow using four-echo test data
"""
if skip_integration:
pytest.skip('Skipping four-echo integration test')
out_dir = '/tmp/data/four-echo/TED.four-echo'
if os.path.exists(out_dir):
shutil.rmtree(out_dir)
# download data and run the test
download_test_data('https://osf.io/gnj73/download',
os.path.dirname(out_dir))
prepend = '/tmp/data/four-echo/'
prepend += 'sub-PILOT_ses-01_task-localizerDetection_run-01_echo-'
suffix = '_space-sbref_desc-preproc_bold+orig.HEAD'
datalist = [prepend + str(i + 1) + suffix for i in range(4)]
tedana_cli.tedana_workflow(data=datalist,
tes=[11.8, 28.04, 44.28, 60.52],
out_dir=out_dir,
tedpca='kundu-stabilize',
gscontrol=['gsr', 'mir'],
png_cmap='bone',
debug=True,
verbose=True)
# compare the generated output files
fn = resource_filename('tedana', 'tests/data/fiu_four_echo_outputs.txt')
check_integration_outputs(fn, out_dir)
def test_integration_three_echo(skip_integration):
""" Integration test of the full tedana workflow using three-echo test data
"""
if skip_integration:
pytest.skip('Skipping three-echo integration test')
out_dir = '/tmp/data/three-echo/TED.three-echo'
out_dir2 = '/tmp/data/three-echo/TED.three-echo-rerun'
if os.path.exists(out_dir):
shutil.rmtree(out_dir)
# download data and run the test
download_test_data('https://osf.io/rqhfc/download',
os.path.dirname(out_dir))
tedana_cli.tedana_workflow(
data='/tmp/data/three-echo/three_echo_Cornell_zcat.nii.gz',
tes=[14.5, 38.5, 62.5],
out_dir=out_dir,
low_mem=True,
tedpca='mdl')
# Test re-running, but use the CLI
args = ([
'-d', '/tmp/data/three-echo/three_echo_Cornell_zcat.nii.gz', '-e',
'14.5', '38.5', '62.5', '--out-dir', out_dir2, '--debug', '--verbose',
'--ctab',
os.path.join(out_dir, 'ica_decomposition.json'), '--mix',
os.path.join(out_dir, 'ica_mixing.tsv')
])
tedana_cli._main(args)
# compare the generated output files
fn = resource_filename('tedana',
'tests/data/cornell_three_echo_outputs.txt')
check_integration_outputs(fn, out_dir)
def test_integration_four_echo(skip_integration):
"""Integration test of the full tedana workflow using four-echo test data"""
if skip_integration:
pytest.skip("Skipping four-echo integration test")
out_dir = "/tmp/data/four-echo/TED.four-echo"
if os.path.exists(out_dir):
shutil.rmtree(out_dir)
# download data and run the test
download_test_data("https://osf.io/gnj73/download",
os.path.dirname(out_dir))
prepend = "/tmp/data/four-echo/"
prepend += "sub-PILOT_ses-01_task-localizerDetection_run-01_echo-"
suffix = "_space-sbref_desc-preproc_bold+orig.HEAD"
datalist = [prepend + str(i + 1) + suffix for i in range(4)]
tedana_cli.tedana_workflow(
data=datalist,
tes=[11.8, 28.04, 44.28, 60.52],
out_dir=out_dir,
tedpca="kundu-stabilize",
gscontrol=["gsr", "mir"],
png_cmap="bone",
debug=True,
verbose=True,
)
# compare the generated output files
fn = resource_filename("tedana", "tests/data/fiu_four_echo_outputs.txt")
check_integration_outputs(fn, out_dir)
def test_integration_four_echo(skip_integration):
"""Integration test of the full tedana workflow using four-echo test data"""
if skip_integration:
pytest.skip("Skipping four-echo integration test")
out_dir = "/tmp/data/four-echo/TED.four-echo"
out_dir_manual = "/tmp/data/four-echo/TED.four-echo-manual"
if os.path.exists(out_dir):
shutil.rmtree(out_dir)
if os.path.exists(out_dir_manual):
shutil.rmtree(out_dir_manual)
# download data and run the test
download_test_data("https://osf.io/gnj73/download",
os.path.dirname(out_dir))
prepend = "/tmp/data/four-echo/"
prepend += "sub-PILOT_ses-01_task-localizerDetection_run-01_echo-"
suffix = "_space-sbref_desc-preproc_bold+orig.HEAD"
datalist = [prepend + str(i + 1) + suffix for i in range(4)]
tedana_cli.tedana_workflow(
data=datalist,
tes=[11.8, 28.04, 44.28, 60.52],
out_dir=out_dir,
tedpca="kundu-stabilize",
gscontrol=["gsr", "mir"],
png_cmap="bone",
debug=True,
verbose=True,
)
# Test re-running with the component table
mixing_matrix = os.path.join(out_dir, "desc-ICA_mixing.tsv")
comptable = os.path.join(out_dir, "desc-tedana_metrics.tsv")
temporary_comptable = os.path.join(out_dir, "temporary_metrics.tsv")
comptable_df = pd.read_table(comptable)
comptable_df.loc[comptable_df["classification"] == "ignored",
"classification"] = "accepted"
comptable_df.to_csv(temporary_comptable, sep="\t", index=False)
tedana_cli.tedana_workflow(
data=datalist,
tes=[11.8, 28.04, 44.28, 60.52],
out_dir=out_dir_manual,
tedpca="kundu-stabilize",
gscontrol=["gsr", "mir"],
png_cmap="bone",
mixm=mixing_matrix,
ctab=temporary_comptable,
debug=True,
verbose=False,
)
os.remove(temporary_comptable)
# compare the generated output files
fn = resource_filename("tedana", "tests/data/fiu_four_echo_outputs.txt")
check_integration_outputs(fn, out_dir)
def test_integration_five_echo(skip_integration):
"""Integration test of the full tedana workflow using five-echo test data"""
if skip_integration:
pytest.skip("Skipping five-echo integration test")
out_dir = "/tmp/data/five-echo/TED.five-echo"
if os.path.exists(out_dir):
shutil.rmtree(out_dir)
# download data and run the test
download_test_data("https://osf.io/9c42e/download",
os.path.dirname(out_dir))
prepend = "/tmp/data/five-echo/p06.SBJ01_S09_Task11_e"
suffix = ".sm.nii.gz"
datalist = [prepend + str(i + 1) + suffix for i in range(5)]
echo_times = [15.4, 29.7, 44.0, 58.3, 72.6]
tedana_cli.tedana_workflow(
data=datalist,
tes=echo_times,
out_dir=out_dir,
tedpca=0.95,
fittype="curvefit",
fixed_seed=49,
tedort=True,
verbose=True,
)
# Just a check on the component table pending a unit test of load_comptable
comptable = os.path.join(out_dir, "desc-tedana_metrics.tsv")
df = pd.read_table(comptable)
assert isinstance(df, pd.DataFrame)
# Test re-running, but use the CLI
out_dir2 = "/tmp/data/five-echo/TED.five-echo-manual"
acc_comps = df.loc[df["classification"] == "accepted"].index.values
acc_comps = [str(c) for c in acc_comps]
mixing = os.path.join(out_dir, "desc-ICA_mixing.tsv")
t2smap = os.path.join(out_dir, "T2starmap.nii.gz")
args = (["-d"] + datalist + ["-e"] + [str(te) for te in echo_times] + [
"--out-dir",
out_dir2,
"--debug",
"--verbose",
"--manacc",
*acc_comps,
"--ctab",
comptable,
"--mix",
mixing,
"--t2smap",
t2smap,
])
tedana_cli._main(args)
# compare the generated output files
fn = resource_filename("tedana",
"tests/data/nih_five_echo_outputs_verbose.txt")
check_integration_outputs(fn, out_dir)
def test_integration_three_echo(skip_integration):
"""Integration test of the full tedana workflow using three-echo test data"""
if skip_integration:
pytest.skip("Skipping three-echo integration test")
out_dir = "/tmp/data/three-echo/TED.three-echo"
out_dir_manual = "/tmp/data/three-echo/TED.three-echo-rerun"
if os.path.exists(out_dir):
shutil.rmtree(out_dir)
if os.path.exists(out_dir_manual):
shutil.rmtree(out_dir_manual)
# download data and run the test
download_test_data("https://osf.io/rqhfc/download",
os.path.dirname(out_dir))
tedana_cli.tedana_workflow(
data="/tmp/data/three-echo/three_echo_Cornell_zcat.nii.gz",
tes=[14.5, 38.5, 62.5],
out_dir=out_dir,
low_mem=True,
tedpca="aic",
)
# Test re-running, but use the CLI
args = [
"-d",
"/tmp/data/three-echo/three_echo_Cornell_zcat.nii.gz",
"-e",
"14.5",
"38.5",
"62.5",
"--out-dir",
out_dir_manual,
"--debug",
"--verbose",
"--ctab",
os.path.join(out_dir, "desc-tedana_metrics.tsv"),
"--mix",
os.path.join(out_dir, "desc-ICA_mixing.tsv"),
]
tedana_cli._main(args)
# compare the generated output files
fn = resource_filename("tedana",
"tests/data/cornell_three_echo_outputs.txt")
check_integration_outputs(fn, out_dir)
def test_integration_five_echo(skip_integration):
""" Integration test of the full tedana workflow using five-echo test data
"""
if skip_integration:
pytest.skip('Skipping five-echo integration test')
out_dir = '/tmp/data/five-echo/TED.five-echo'
if os.path.exists(out_dir):
shutil.rmtree(out_dir)
# download data and run the test
download_test_data('https://osf.io/9c42e/download',
os.path.dirname(out_dir))
prepend = '/tmp/data/five-echo/p06.SBJ01_S09_Task11_e'
suffix = '.sm.nii.gz'
datalist = [prepend + str(i + 1) + suffix for i in range(5)]
echo_times = [15.4, 29.7, 44.0, 58.3, 72.6]
tedana_cli.tedana_workflow(data=datalist,
tes=echo_times,
out_dir=out_dir,
tedpca=0.95,
fittype='curvefit',
fixed_seed=49,
tedort=True,
verbose=True)
# Just a check on the component table pending a unit test of load_comptable
comptable = os.path.join(out_dir, 'desc-tedana_metrics.tsv')
df = pd.read_table(comptable)
assert isinstance(df, pd.DataFrame)
# Test re-running, but use the CLI
out_dir2 = '/tmp/data/five-echo/TED.five-echo-manual'
acc_comps = df.loc[df['classification'] == 'accepted'].index.values
acc_comps = [str(c) for c in acc_comps]
mixing = os.path.join(out_dir, 'desc-ICA_mixing.tsv')
t2smap = os.path.join(out_dir, 'T2starmap.nii.gz')
args = (['-d'] + datalist + ['-e'] + [str(te) for te in echo_times] + [
'--out-dir', out_dir2, '--debug', '--verbose', '--manacc', *acc_comps,
'--ctab', comptable, '--mix', mixing, '--t2smap', t2smap
])
tedana_cli._main(args)
# compare the generated output files
fn = resource_filename('tedana',
'tests/data/nih_five_echo_outputs_verbose.txt')
check_integration_outputs(fn, out_dir)