def test_instantiate_StatisticsSurface():
from os.path import dirname, join, abspath
from clinica.pipelines.statistics_surface.statistics_surface_pipeline import StatisticsSurface
root = dirname(abspath(join(abspath(__file__), pardir)))
root = join(root, 'data', 'StatisticsSurface')
parameters = {
'design_matrix': '1 + group + age + sex',
'contrast': 'group',
'str_format': '%s %s %s %f %s',
'group_label': 'UnitTest',
'glm_type': 'group_comparison',
'custom_file':
'@subject/@session/t1/freesurfer_cross_sectional/@subject_@session/surf/@[email protected]',
'feature_label': 'cortical_thickness',
'full_width_at_half_maximum': 20,
'threshold_uncorrected_pvalue': 0.001,
'threshold_corrected_pvalue': 0.05,
'cluster_threshold': 0.001
}
pipeline = StatisticsSurface(caps_directory=join(root, 'in', 'caps'),
tsv_file=join(root, 'in', 'subjects.tsv'),
parameters=parameters)
pipeline.build()
def test_instantiate_StatisticsSurface():
from os.path import abspath, dirname, join
from clinica.pipelines.statistics_surface.statistics_surface_pipeline import (
StatisticsSurface, )
root = dirname(abspath(join(abspath(__file__), pardir)))
root = join(root, "data", "StatisticsSurface")
parameters = {
# Clinica compulsory parameters
"group_label": "UnitTest",
"orig_input_data": "t1-freesurfer",
"glm_type": "group_comparison",
"contrast": "group",
# Optional parameters
"covariates": "age sex",
}
pipeline = StatisticsSurface(
caps_directory=join(root, "in", "caps"),
tsv_file=join(root, "in", "subjects.tsv"),
parameters=parameters,
)
pipeline.build()
def test_run_StatisticsSurface(cmdopt):
import shutil
from os.path import abspath, dirname, join
import numpy as np
from scipy.io import loadmat
from clinica.pipelines.statistics_surface.statistics_surface_pipeline import (
StatisticsSurface,
)
working_dir = cmdopt
root = dirname(abspath(join(abspath(__file__), pardir, pardir)))
root = join(root, "data", "StatisticsSurface")
clean_folder(join(root, "out", "caps"), recreate=False)
clean_folder(join(working_dir, "StatisticsSurface"))
shutil.copytree(join(root, "in", "caps"), join(root, "out", "caps"))
parameters = {
# Clinica compulsory parameters
"group_label": "UnitTest",
"orig_input_data": "t1-freesurfer",
"glm_type": "group_comparison",
"contrast": "group",
# Optional parameters
"covariates": "age sex",
}
pipeline = StatisticsSurface(
caps_directory=join(root, "out", "caps"),
tsv_file=join(root, "in", "subjects.tsv"),
base_dir=join(working_dir, "StatisticsSurface"),
parameters=parameters,
)
pipeline.build()
pipeline.run(plugin="MultiProc", plugin_args={"n_procs": 1}, bypass_check=True)
# Check files
filename = "group-UnitTest_AD-lt-CN_measure-ct_fwhm-20_correctedPValue.mat"
out_file = join(
root,
"out",
"caps",
"groups",
"group-UnitTest",
"statistics",
"surfstat_group_comparison",
filename,
)
ref_file = join(root, "ref", filename)
out_file_mat = loadmat(out_file)["correctedpvaluesstruct"]
ref_file_mat = loadmat(ref_file)["correctedpvaluesstruct"]
for i in range(4):
assert np.allclose(
out_file_mat[0][0][i], ref_file_mat[0][0][i], rtol=1e-8, equal_nan=True
)
clean_folder(join(root, "out", "caps"), recreate=False)
clean_folder(join(working_dir, "StatisticsSurface"), recreate=False)
def test_run_StatisticsSurface(cmdopt):
from clinica.pipelines.statistics_surface.statistics_surface_pipeline import StatisticsSurface
from os.path import dirname, join, abspath
import shutil
import numpy as np
from scipy.io import loadmat
working_dir = cmdopt
root = dirname(abspath(join(abspath(__file__), pardir)))
root = join(root, 'data', 'StatisticsSurface')
clean_folder(join(root, 'out', 'caps'), recreate=False)
clean_folder(join(working_dir, 'StatisticsSurface'))
shutil.copytree(join(root, 'in', 'caps'), join(root, 'out', 'caps'))
parameters = {
'design_matrix': '1 + group + age + sex',
'contrast': 'group',
'str_format': '%s %s %s %f %s',
'group_label': 'UnitTest',
'glm_type': 'group_comparison',
'custom_file':
'@subject/@session/t1/freesurfer_cross_sectional/@subject_@session/surf/@[email protected]',
'feature_label': 'cortical_thickness',
'full_width_at_half_maximum': 20,
'threshold_uncorrected_pvalue': 0.001,
'threshold_corrected_pvalue': 0.05,
'cluster_threshold': 0.001
}
pipeline = StatisticsSurface(caps_directory=join(root, 'out', 'caps'),
tsv_file=join(root, 'in', 'subjects.tsv'),
base_dir=join(working_dir,
'StatisticsSurface'),
parameters=parameters)
pipeline.build()
pipeline.run(plugin='MultiProc',
plugin_args={'n_procs': 8},
bypass_check=True)
# Check files
out_file = join(
root,
'out/caps/groups/group-UnitTest/statistics/surfstat_group_comparison/group-UnitTest_AD-lt-CN_measure-cortical_thickness_fwhm-20_correctedPValue.mat'
)
ref_file = join(
root,
'ref/group-UnitTest_AD-lt-CN_measure-cortical_thickness_fwhm-20_correctedPValue.mat'
)
out_file_mat = loadmat(out_file)['correctedpvaluesstruct']
ref_file_mat = loadmat(ref_file)['correctedpvaluesstruct']
for i in range(4):
assert np.allclose(out_file_mat[0][0][i],
ref_file_mat[0][0][i],
rtol=1e-8,
equal_nan=True)
clean_folder(join(root, 'out', 'caps'), recreate=False)
clean_folder(join(working_dir, 'StatisticsSurface'), recreate=False)
def run_StatisticsSurface(input_dir: Path, output_dir: Path, ref_dir: Path,
working_dir: Path) -> None:
import shutil
import numpy as np
from scipy.io import loadmat
from clinica.pipelines.statistics_surface.statistics_surface_pipeline import (
StatisticsSurface, )
caps_dir = output_dir / "caps"
tsv = input_dir / "subjects.tsv"
# Copy necessary data from in to out
shutil.copytree(input_dir / "caps", caps_dir, copy_function=shutil.copy)
parameters = {
# Clinica compulsory parameters
"group_label": "UnitTest",
"orig_input_data": "t1-freesurfer",
"glm_type": "group_comparison",
"contrast": "group",
# Optional parameters
"covariates": ["age", "sex"],
}
pipeline = StatisticsSurface(
caps_directory=fspath(caps_dir),
tsv_file=fspath(tsv),
base_dir=fspath(working_dir),
parameters=parameters,
)
pipeline.build()
pipeline.run(plugin="MultiProc",
plugin_args={"n_procs": 1},
bypass_check=True)
# Check files
filename = "group-UnitTest_AD-lt-CN_measure-ct_fwhm-20_correctedPValue.mat"
out_file = (caps_dir / "groups" / "group-UnitTest" / "statistics" /
"surfstat_group_comparison" / filename)
ref_file = ref_dir / filename
out_file_mat = loadmat(fspath(out_file))["correctedpvaluesstruct"]
ref_file_mat = loadmat(fspath(ref_file))["correctedpvaluesstruct"]
for i in range(4):
assert np.allclose(
out_file_mat[0][0][i],
ref_file_mat[0][0][i],
rtol=1e-8,
equal_nan=True,
)
def test_run_StatisticsSurface(cmdopt):
from clinica.pipelines.statistics_surface.statistics_surface_pipeline import StatisticsSurface
from os.path import dirname, join, abspath
import shutil
import numpy as np
from scipy.io import loadmat
working_dir = cmdopt
root = dirname(abspath(join(abspath(__file__), pardir)))
root = join(root, 'data', 'StatisticsSurface')
clean_folder(join(root, 'out', 'caps'), recreate=False)
clean_folder(join(working_dir, 'StatisticsSurface'))
shutil.copytree(join(root, 'in', 'caps'), join(root, 'out', 'caps'))
parameters = {
# Clinica compulsory parameters
'group_label': 'UnitTest',
'orig_input_data': 't1-freesurfer',
'glm_type': 'group_comparison',
'contrast': 'group',
# Optional parameters
'covariates': 'age sex',
}
pipeline = StatisticsSurface(caps_directory=join(root, 'out', 'caps'),
tsv_file=join(root, 'in', 'subjects.tsv'),
base_dir=join(working_dir,
'StatisticsSurface'),
parameters=parameters)
pipeline.build()
pipeline.run(plugin='MultiProc',
plugin_args={'n_procs': 1},
bypass_check=True)
# Check files
filename = 'group-UnitTest_AD-lt-CN_measure-ct_fwhm-20_correctedPValue.mat'
out_file = join(root, 'out', 'caps', 'groups', 'group-UnitTest',
'statistics', 'surfstat_group_comparison', filename)
ref_file = join(root, 'ref', filename)
out_file_mat = loadmat(out_file)['correctedpvaluesstruct']
ref_file_mat = loadmat(ref_file)['correctedpvaluesstruct']
for i in range(4):
assert np.allclose(out_file_mat[0][0][i],
ref_file_mat[0][0][i],
rtol=1e-8,
equal_nan=True)
clean_folder(join(root, 'out', 'caps'), recreate=False)
clean_folder(join(working_dir, 'StatisticsSurface'), recreate=False)
def test_instantiate_StatisticsSurface():
from os.path import dirname, join, abspath
from clinica.pipelines.statistics_surface.statistics_surface_pipeline import StatisticsSurface
root = dirname(abspath(join(abspath(__file__), pardir)))
root = join(root, 'data', 'StatisticsSurface')
parameters = {
# Clinica compulsory parameters
'group_label': 'UnitTest',
'orig_input_data': 't1-freesurfer',
'glm_type': 'group_comparison',
'contrast': 'group',
# Optional parameters
'covariates': 'age sex',
}
pipeline = StatisticsSurface(caps_directory=join(root, 'in', 'caps'),
tsv_file=join(root, 'in', 'subjects.tsv'),
parameters=parameters)
pipeline.build()
def test_instantiate_StatisticsSurface(cmdopt):
from clinica.pipelines.statistics_surface.statistics_surface_pipeline import (
StatisticsSurface, )
input_dir = Path(cmdopt["input"])
root = input_dir / "StatisticsSurface"
parameters = {
# Clinica compulsory parameters
"group_label": "UnitTest",
"orig_input_data": "t1-freesurfer",
"glm_type": "group_comparison",
"contrast": "group",
# Optional parameters
"covariates": "age sex",
}
pipeline = StatisticsSurface(
caps_directory=fspath(root / "in" / "caps"),
tsv_file=fspath(root / "in" / "subjects.tsv"),
parameters=parameters,
)
pipeline.build()