def test_index_img():
img_3d = nibabel.Nifti1Image(np.ones((3, 4, 5)), np.eye(4))
expected_error_msg = ("Input data has incompatible dimensionality: "
"Expected dimension is 4D and you provided "
"a 3D image.")
with pytest.raises(TypeError, match=expected_error_msg):
image.index_img(img_3d, 0)
affine = np.array([[1., 2., 3., 4.], [5., 6., 7., 8.], [9., 10., 11., 12.],
[0., 0., 0., 1.]])
img_4d, _ = data_gen.generate_fake_fmri(affine=affine)
fourth_dim_size = img_4d.shape[3]
tested_indices = (list(range(fourth_dim_size)) + [
slice(2, 8, 2), [1, 2, 3, 2], [], (np.arange(fourth_dim_size) % 3) == 1
])
for i in tested_indices:
this_img = image.index_img(img_4d, i)
expected_data_3d = get_data(img_4d)[..., i]
assert_array_equal(get_data(this_img), expected_data_3d)
assert_array_equal(this_img.affine, img_4d.affine)
for i in [
fourth_dim_size, -fourth_dim_size - 1, [0, fourth_dim_size],
np.repeat(True, fourth_dim_size + 1)
]:
with pytest.raises(IndexError,
match='out of bounds|invalid index|out of range|'
'boolean index'):
image.index_img(img_4d, i)
def test_index_img():
img_3d = nibabel.Nifti1Image(np.ones((3, 4, 5)), np.eye(4))
testing.assert_raises_regex(TypeError, '4D Niimg-like',
image.index_img, img_3d, 0)
affine = np.array([[1., 2., 3., 4.],
[5., 6., 7., 8.],
[9., 10., 11., 12.],
[0., 0., 0., 1.]])
img_4d, _ = testing.generate_fake_fmri(affine=affine)
fourth_dim_size = img_4d.shape[3]
tested_indices = (list(range(fourth_dim_size)) +
[slice(2, 8, 2), [1, 2, 3, 2], [],
(np.arange(fourth_dim_size) % 3) == 1])
for i in tested_indices:
this_img = image.index_img(img_4d, i)
expected_data_3d = img_4d.get_data()[..., i]
assert_array_equal(this_img.get_data(),
expected_data_3d)
assert_array_equal(this_img.get_affine(),
img_4d.get_affine())
for i in [fourth_dim_size, - fourth_dim_size - 1,
[0, fourth_dim_size],
np.repeat(True, fourth_dim_size + 1)]:
testing.assert_raises_regex(
IndexError,
'out of bounds|invalid index|out of range',
image.index_img, img_4d, i)
def test_index_img():
img_3d = nibabel.Nifti1Image(np.ones((3, 4, 5)), np.eye(4))
testing.assert_raises_regex(TypeError,
"Input data has incompatible dimensionality: "
"Expected dimension is 4D and you provided "
"a 3D image.",
image.index_img, img_3d, 0)
affine = np.array([[1., 2., 3., 4.],
[5., 6., 7., 8.],
[9., 10., 11., 12.],
[0., 0., 0., 1.]])
img_4d, _ = data_gen.generate_fake_fmri(affine=affine)
fourth_dim_size = img_4d.shape[3]
tested_indices = (list(range(fourth_dim_size)) +
[slice(2, 8, 2), [1, 2, 3, 2], [],
(np.arange(fourth_dim_size) % 3) == 1])
for i in tested_indices:
this_img = image.index_img(img_4d, i)
expected_data_3d = img_4d.get_data()[..., i]
assert_array_equal(this_img.get_data(),
expected_data_3d)
assert_array_equal(this_img.affine, img_4d.affine)
for i in [fourth_dim_size, - fourth_dim_size - 1,
[0, fourth_dim_size],
np.repeat(True, fourth_dim_size + 1)]:
testing.assert_raises_regex(
IndexError,
'out of bounds|invalid index|out of range|boolean index',
image.index_img, img_4d, i)
def test_pd_index_img():
# confirm indices from pandas dataframes are handled correctly
if 'pandas' not in sys.modules:
raise pytest.skip(msg='Pandas not available')
affine = np.array([[1., 2., 3., 4.], [5., 6., 7., 8.], [9., 10., 11., 12.],
[0., 0., 0., 1.]])
img_4d, _ = data_gen.generate_fake_fmri(affine=affine)
fourth_dim_size = img_4d.shape[3]
rng = np.random.RandomState(42)
arr = rng.uniform(size=fourth_dim_size) > 0.5
df = pd.DataFrame({"arr": arr})
np_index_img = image.index_img(img_4d, arr)
pd_index_img = image.index_img(img_4d, df)
assert_array_equal(get_data(np_index_img), get_data(pd_index_img))
def test_pd_index_img():
# confirm indices from pandas dataframes are handled correctly
if 'pandas' not in sys.modules:
raise SkipTest
affine = np.array([[1., 2., 3., 4.], [5., 6., 7., 8.], [9., 10., 11., 12.],
[0., 0., 0., 1.]])
img_4d, _ = testing.generate_fake_fmri(affine=affine)
fourth_dim_size = img_4d.shape[3]
rng = np.random.RandomState(0)
arr = rng.rand(fourth_dim_size) > 0.5
df = pd.DataFrame({"arr": arr})
np_index_img = image.index_img(img_4d, arr)
pd_index_img = image.index_img(img_4d, df)
assert_array_equal(np_index_img.get_data(), pd_index_img.get_data())
def test_pd_index_img():
# confirm indices from pandas dataframes are handled correctly
if 'pandas' not in sys.modules:
raise SkipTest
affine = np.array([[1., 2., 3., 4.],
[5., 6., 7., 8.],
[9., 10., 11., 12.],
[0., 0., 0., 1.]])
img_4d, _ = data_gen.generate_fake_fmri(affine=affine)
fourth_dim_size = img_4d.shape[3]
rng = np.random.RandomState(0)
arr = rng.rand(fourth_dim_size) > 0.5
df = pd.DataFrame({"arr": arr})
np_index_img = image.index_img(img_4d, arr)
pd_index_img = image.index_img(img_4d, df)
assert_array_equal(np_index_img.get_data(),
pd_index_img.get_data())
