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Ben Cipollini
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Test 2D - 5D; remove some tests to increase speed.
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‎nibabel/tests/test_funcs.py

Lines changed: 84 additions & 80 deletions
Original file line numberDiff line numberDiff line change
@@ -34,88 +34,92 @@ def test_concat():
3434
assert_raises(ValueError, concat_images, [])
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3636
# Build combinations of 3D, 4D w/size[3] == 1, and 4D w/size[3] == 3
37-
all_shapes_3D = ((1, 2, 5), (7, 3, 1), (13, 11, 11), (0, 1, 1))
38-
all_shapes_4D_unary = tuple((shape + (1,) for shape in all_shapes_3D))
39-
all_shapes_4D_multi = tuple((shape + (3,) for shape in all_shapes_3D))
40-
all_shapes = all_shapes_3D + all_shapes_4D_unary + all_shapes_4D_multi
37+
all_shapes_5D = ((1, 4, 5, 3, 3),
38+
(7, 3, 1, 4, 5),
39+
(0, 2, 1, 4, 5))
4140

4241
affine = np.eye(4)
43-
# Loop over all possible combinations of images, in first and
44-
# second position.
45-
for data0_shape in all_shapes:
46-
data0_numel = np.asarray(data0_shape).prod()
47-
data0 = np.arange(data0_numel).reshape(data0_shape)
48-
img0_mem = Nifti1Image(data0, affine)
49-
50-
for data1_shape in all_shapes:
51-
data1_numel = np.asarray(data1_shape).prod()
52-
data1 = np.arange(data1_numel).reshape(data1_shape)
53-
img1_mem = Nifti1Image(data1, affine)
54-
img2_mem = Nifti1Image(data1, affine+1) # bad affine
55-
img3_mem = Nifti1Image(data1.T, affine) # bad data shape
56-
57-
# Loop over every possible axis, including None (explicit and implied)
58-
for axis in (list(range(-2, 3)) + [None, '__default__']):
59-
60-
# Allow testing default vs. passing explicit param
61-
if axis == '__default__':
62-
np_concat_kwargs = dict(axis=-1)
63-
concat_imgs_kwargs = dict()
64-
axis = None # Convert downstream
65-
elif axis is None:
66-
np_concat_kwargs = dict(axis=-1)
67-
concat_imgs_kwargs = dict(axis=axis)
68-
else:
69-
np_concat_kwargs = dict(axis=axis)
70-
concat_imgs_kwargs = dict(axis=axis)
71-
72-
# Create expected output
73-
try:
74-
# Error will be thrown if the np.concatenate fails.
75-
# However, when axis=None, the concatenate is possible
76-
# but our efficient logic (where all images are
77-
# 3D and the same size) fails, so we also
78-
# have to expect errors for those.
79-
expect_error = data0.ndim != data1.ndim
80-
if axis is None: # 3D from here and below
81-
all_data = np.concatenate([data0[..., np.newaxis], data1[..., np.newaxis]],**np_concat_kwargs)
82-
else: # both 3D, appending on final axis
83-
all_data = np.concatenate([data0, data1],
84-
**np_concat_kwargs)
85-
except ValueError:
86-
# Shapes are not combinable
87-
expect_error = True
88-
89-
# Check filenames and in-memory images work
90-
with InTemporaryDirectory():
91-
# Try mem-based, file-based, and mixed
92-
imgs = [img0_mem, img1_mem, img2_mem, img3_mem]
93-
img_files = [_as_fname(img) for img in imgs]
94-
imgs_mixed = [imgs[0], img_files[1], imgs[2], img_files[3]]
95-
for img0, img1, img2, img3 in (imgs, img_files, imgs_mixed):
96-
try:
97-
all_imgs = concat_images([img0, img1],
98-
**concat_imgs_kwargs)
99-
except ValueError as ve:
100-
assert_true(expect_error, ve.message)
101-
else:
102-
assert_false(expect_error, "Expected a concatenation error, but got none.")
103-
assert_array_equal(all_imgs.get_data(), all_data)
104-
assert_array_equal(all_imgs.affine, affine)
105-
106-
# check that not-matching affines raise error
107-
assert_raises(ValueError, concat_images, [img0, img2], **concat_imgs_kwargs)
108-
assert_raises(ValueError, concat_images, [img0, img3], **concat_imgs_kwargs)
109-
110-
# except if check_affines is False
111-
try:
112-
all_imgs = concat_images([img0, img1], **concat_imgs_kwargs)
113-
except ValueError as ve:
114-
assert_true(expect_error, ve.message)
115-
else:
116-
assert_false(expect_error, "Expected a concatenation error, but got none.")
117-
assert_array_equal(all_imgs.get_data(), all_data)
118-
assert_array_equal(all_imgs.affine, affine)
42+
for dim in range(2, 6):
43+
all_shapes_ND = tuple((shape[:dim] for shape in all_shapes_5D))
44+
all_shapes_N1D_unary = tuple((shape + (1,) for shape in all_shapes_ND))
45+
all_shapes = all_shapes_ND + all_shapes_N1D_unary
46+
47+
# Loop over all possible combinations of images, in first and
48+
# second position.
49+
for data0_shape in all_shapes:
50+
data0_numel = np.asarray(data0_shape).prod()
51+
data0 = np.arange(data0_numel).reshape(data0_shape)
52+
img0_mem = Nifti1Image(data0, affine)
53+
54+
for data1_shape in all_shapes:
55+
data1_numel = np.asarray(data1_shape).prod()
56+
data1 = np.arange(data1_numel).reshape(data1_shape)
57+
img1_mem = Nifti1Image(data1, affine)
58+
img2_mem = Nifti1Image(data1, affine+1) # bad affine
59+
60+
# Loop over every possible axis, including None (explicit and implied)
61+
for axis in (list(range(-(dim-2), (dim-1))) + [None, '__default__']):
62+
63+
# Allow testing default vs. passing explicit param
64+
if axis == '__default__':
65+
np_concat_kwargs = dict(axis=-1)
66+
concat_imgs_kwargs = dict()
67+
axis = None # Convert downstream
68+
elif axis is None:
69+
np_concat_kwargs = dict(axis=-1)
70+
concat_imgs_kwargs = dict(axis=axis)
71+
else:
72+
np_concat_kwargs = dict(axis=axis)
73+
concat_imgs_kwargs = dict(axis=axis)
74+
75+
# Create expected output
76+
try:
77+
# Error will be thrown if the np.concatenate fails.
78+
# However, when axis=None, the concatenate is possible
79+
# but our efficient logic (where all images are
80+
# 3D and the same size) fails, so we also
81+
# have to expect errors for those.
82+
expect_error = data0.ndim != data1.ndim
83+
if axis is None: # 3D from here and below
84+
all_data = np.concatenate([data0[..., np.newaxis],
85+
data1[..., np.newaxis]],
86+
**np_concat_kwargs)
87+
else: # both 3D, appending on final axis
88+
all_data = np.concatenate([data0, data1],
89+
**np_concat_kwargs)
90+
except ValueError:
91+
# Shapes are not combinable
92+
expect_error = True
93+
94+
# Check filenames and in-memory images work
95+
with InTemporaryDirectory():
96+
# Try mem-based, file-based, and mixed
97+
imgs = [img0_mem, img1_mem, img2_mem]
98+
img_files = [_as_fname(img) for img in imgs]
99+
imgs_mixed = [imgs[0], img_files[1], imgs[2]]
100+
for img0, img1, img2 in (imgs, img_files, imgs_mixed):
101+
try:
102+
all_imgs = concat_images([img0, img1],
103+
**concat_imgs_kwargs)
104+
except ValueError as ve:
105+
assert_true(expect_error, ve.message)
106+
else:
107+
assert_false(expect_error, "Expected a concatenation error, but got none.")
108+
assert_array_equal(all_imgs.get_data(), all_data)
109+
assert_array_equal(all_imgs.affine, affine)
110+
111+
# check that not-matching affines raise error
112+
assert_raises(ValueError, concat_images, [img0, img2], **concat_imgs_kwargs)
113+
114+
# except if check_affines is False
115+
try:
116+
all_imgs = concat_images([img0, img1], **concat_imgs_kwargs)
117+
except ValueError as ve:
118+
assert_true(expect_error, ve.message)
119+
else:
120+
assert_false(expect_error, "Expected a concatenation error, but got none.")
121+
assert_array_equal(all_imgs.get_data(), all_data)
122+
assert_array_equal(all_imgs.affine, affine)
119123

120124

121125
def test_closest_canonical():

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