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# emacs: -*- mode: python; py-indent-offset: 4; indent-tabs-mode: nil -*-
# vi: set ft=python sts=4 ts=4 sw=4 et:
import os
import nibabel as nb
import numpy as np
import pytest
from ...testing import utils
from ..confounds import CompCor, TCompCor, ACompCor
def close_up_to_column_sign(a, b, rtol=1e-05, atol=1e-08, equal_nan=False):
"""SVD can produce sign flips on a per-column basis."""
a = np.asanyarray(a)
b = np.asanyarray(b)
kwargs = dict(rtol=rtol, atol=atol, equal_nan=equal_nan)
a, b = np.array(a), np.array(b)
if np.allclose(a, b, **kwargs):
return True
ret = True
for acol, bcol in zip(a.T, b.T):
ret &= np.allclose(acol, bcol, **kwargs) or np.allclose(acol, -bcol, **kwargs)
if not ret:
break
return ret
@pytest.mark.parametrize(
"a, b, close",
[
([[0.1, 0.2], [0.3, 0.4]], [[-0.1, 0.2], [-0.3, 0.4]], True),
([[0.1, 0.2], [0.3, 0.4]], [[-0.1, 0.2], [0.3, -0.4]], False),
],
)
def test_close_up_to_column_sign(a, b, close):
a = np.asanyarray(a)
b = np.asanyarray(b)
assert close_up_to_column_sign(a, b) == close
# Sign flips of all columns never changes result
assert close_up_to_column_sign(a, -b) == close
assert close_up_to_column_sign(-a, b) == close
assert close_up_to_column_sign(-a, -b) == close
# Trivial case
assert close_up_to_column_sign(a, a)
assert close_up_to_column_sign(b, b)
class TestCompCor:
"""Note: Tests currently do a poor job of testing functionality"""
filenames = {
"functionalnii": "compcorfunc.nii",
"masknii": "compcormask.nii",
"masknii2": "compcormask2.nii",
"components_file": None,
}
@pytest.fixture(autouse=True)
def setup_class(self, tmpdir):
# setup
tmpdir.chdir()
noise = np.fromfunction(self.fake_noise_fun, self.fake_data.shape)
self.realigned_file = utils.save_toy_nii(
self.fake_data + noise, self.filenames["functionalnii"]
)
mask = np.ones(self.fake_data.shape[:3])
mask[0, 0, 0] = 0
mask[0, 0, 1] = 0
mask1 = utils.save_toy_nii(mask, self.filenames["masknii"])
other_mask = np.ones(self.fake_data.shape[:3])
other_mask[0, 1, 0] = 0
other_mask[1, 1, 0] = 0
mask2 = utils.save_toy_nii(other_mask, self.filenames["masknii2"])
self.mask_files = [mask1, mask2]
def test_compcor(self):
expected_components = [
[-0.1989607212, -0.5753813646],
[0.5692369697, 0.5674945949],
[-0.6662573243, 0.4675843432],
[0.4206466244, -0.3361270124],
[-0.1246655485, -0.1235705610],
]
self.run_cc(
CompCor(
num_components=6,
realigned_file=self.realigned_file,
mask_files=self.mask_files,
mask_index=0,
),
expected_components,
)
self.run_cc(
ACompCor(
num_components=6,
realigned_file=self.realigned_file,
mask_files=self.mask_files,
mask_index=0,
components_file="acc_components_file",
),
expected_components,
"aCompCor",
)
def test_compcor_variance_threshold_and_metadata(self):
expected_components = [
[-0.2027150345, -0.4954813834],
[0.2565929051, 0.7866217875],
[-0.3550986008, -0.0089784905],
[0.7512786244, -0.3599828482],
[-0.4500578942, 0.0778209345],
]
expected_metadata = {
"component": "CompCor00",
"mask": "mask",
"singular_value": "4.0720553036",
"variance_explained": "0.5527211465",
"cumulative_variance_explained": "0.5527211465",
"retained": "True",
}
ccinterface = CompCor(
variance_threshold=0.7,
realigned_file=self.realigned_file,
mask_files=self.mask_files,
mask_names=["mask"],
mask_index=1,
save_metadata=True,
)
self.run_cc(
ccinterface=ccinterface,
expected_components=expected_components,
expected_n_components=2,
expected_metadata=expected_metadata,
)
def test_tcompcor(self):
ccinterface = TCompCor(
num_components=6,
realigned_file=self.realigned_file,
percentile_threshold=0.75,
)
self.run_cc(
ccinterface,
[
[-0.1114536190, -0.4632908609],
[0.4566907310, 0.6983205193],
[-0.7132557407, 0.1340170559],
[0.5022537643, -0.5098322262],
[-0.1342351356, 0.1407855119],
],
"tCompCor",
)
def test_tcompcor_no_percentile(self):
ccinterface = TCompCor(num_components=6, realigned_file=self.realigned_file)
ccinterface.run()
mask = nb.load("mask_000.nii.gz").dataobj
num_nonmasked_voxels = np.count_nonzero(mask)
assert num_nonmasked_voxels == 1
def test_compcor_no_regress_poly(self):
self.run_cc(
CompCor(
num_components=6,
realigned_file=self.realigned_file,
mask_files=self.mask_files,
mask_index=0,
pre_filter=False,
),
[
[0.4451946442, -0.7683311482],
[-0.4285129505, -0.0926034137],
[0.5721540256, 0.5608764842],
[-0.5367548139, 0.0059943226],
[-0.0520809054, 0.2940637551],
],
)
def test_tcompcor_asymmetric_dim(self):
asymmetric_shape = (2, 3, 4, 5)
asymmetric_data = utils.save_toy_nii(
np.zeros(asymmetric_shape), "asymmetric.nii"
)
TCompCor(realigned_file=asymmetric_data).run()
assert nb.load("mask_000.nii.gz").shape == asymmetric_shape[:3]
def test_compcor_bad_input_shapes(self):
# dim 0 is < dim 0 of self.mask_files (2)
shape_less_than = (1, 2, 2, 5)
# dim 0 is > dim 0 of self.mask_files (2)
shape_more_than = (3, 3, 3, 5)
for data_shape in (shape_less_than, shape_more_than):
data_file = utils.save_toy_nii(np.zeros(data_shape), "temp.nii")
interface = CompCor(realigned_file=data_file, mask_files=self.mask_files[0])
with pytest.raises(ValueError):
interface.run() # Dimension mismatch
def test_tcompcor_bad_input_dim(self):
bad_dims = (2, 2, 2)
data_file = utils.save_toy_nii(np.zeros(bad_dims), "temp.nii")
interface = TCompCor(realigned_file=data_file)
with pytest.raises(ValueError):
interface.run() # Not a 4D file
def test_tcompcor_merge_intersect_masks(self):
for method in ["union", "intersect"]:
TCompCor(
realigned_file=self.realigned_file,
mask_files=self.mask_files,
merge_method=method,
).run()
if method == "union":
assert np.array_equal(
nb.load("mask_000.nii.gz").dataobj,
([[[0, 0], [0, 0]], [[0, 0], [1, 0]]]),
)
if method == "intersect":
assert np.array_equal(
nb.load("mask_000.nii.gz").dataobj,
([[[0, 0], [0, 0]], [[0, 1], [0, 0]]]),
)
def test_tcompcor_index_mask(self):
TCompCor(
realigned_file=self.realigned_file, mask_files=self.mask_files, mask_index=1
).run()
assert np.array_equal(
nb.load("mask_000.nii.gz").dataobj, ([[[0, 0], [0, 0]], [[0, 1], [0, 0]]])
)
def test_tcompcor_multi_mask_no_index(self):
interface = TCompCor(
realigned_file=self.realigned_file, mask_files=self.mask_files
)
with pytest.raises(ValueError):
interface.run() # more than one mask file
def run_cc(
self,
ccinterface,
expected_components,
expected_header="CompCor",
expected_n_components=None,
expected_metadata=None,
):
# run
ccresult = ccinterface.run()
# assert
expected_file = ccinterface._list_outputs()["components_file"]
assert ccresult.outputs.components_file == expected_file
assert os.path.exists(expected_file)
assert os.path.getsize(expected_file) > 0
with open(ccresult.outputs.components_file) as components_file:
header = components_file.readline().rstrip().split("\t")
components_data = np.loadtxt(components_file, delimiter="\t")
if expected_n_components is None:
expected_n_components = min(
ccinterface.inputs.num_components, self.fake_data.shape[3]
)
assert header == [
f"{expected_header}{i:02d}" for i in range(expected_n_components)
]
assert components_data.shape == (self.fake_data.shape[3], expected_n_components)
assert close_up_to_column_sign(components_data[:, :2], expected_components)
if ccinterface.inputs.save_metadata:
expected_metadata_file = ccinterface._list_outputs()["metadata_file"]
assert ccresult.outputs.metadata_file == expected_metadata_file
assert os.path.exists(expected_metadata_file)
assert os.path.getsize(expected_metadata_file) > 0
with open(ccresult.outputs.metadata_file) as metadata_file:
components_metadata = [
line.rstrip().split("\t") for line in metadata_file
]
components_metadata = dict(
zip(components_metadata[0], components_metadata[1])
)
assert components_metadata == expected_metadata
return ccresult
@staticmethod
def fake_noise_fun(i, j, l, m):
return m * i + l - j
fake_data = np.array(
[
[[[8, 5, 3, 8, 0], [6, 7, 4, 7, 1]], [[7, 9, 1, 6, 5], [0, 7, 4, 7, 7]]],
[[[2, 4, 5, 7, 0], [1, 7, 0, 5, 4]], [[7, 3, 9, 0, 4], [9, 4, 1, 5, 0]]],
]
)
|
