def test_smooth_img():
# This function only checks added functionalities compared
# to _smooth_array()
shapes = ((10, 11, 12), (13, 14, 15))
lengths = (17, 18)
fwhm = (1., 2., 3.)
img1, mask1 = testing.generate_fake_fmri(shape=shapes[0],
length=lengths[0])
img2, mask2 = testing.generate_fake_fmri(shape=shapes[1],
length=lengths[1])
for create_files in (False, True):
with testing.write_tmp_imgs(img1, img2,
create_files=create_files) as imgs:
# List of images as input
out = image.smooth_img(imgs, fwhm)
assert_true(isinstance(out, list))
assert_true(len(out) == 2)
for o, s, l in zip(out, shapes, lengths):
assert_true(o.shape == (s + (l,)))
# Single image as input
out = image.smooth_img(imgs[0], fwhm)
assert_true(isinstance(out, nibabel.Nifti1Image))
assert_true(out.shape == (shapes[0] + (lengths[0],)))
def test_smooth_img():
# This function only checks added functionalities compared
# to _smooth_array()
shapes = ((10, 11, 12), (13, 14, 15))
lengths = (17, 18)
fwhm = (1., 2., 3.)
img1, mask1 = testing.generate_fake_fmri(shape=shapes[0],
length=lengths[0])
img2, mask2 = testing.generate_fake_fmri(shape=shapes[1],
length=lengths[1])
for create_files in (False, True):
with testing.write_tmp_imgs(img1, img2,
create_files=create_files) as imgs:
# List of images as input
out = image.smooth_img(imgs, fwhm)
assert_true(isinstance(out, list))
assert_true(len(out) == 2)
for o, s, l in zip(out, shapes, lengths):
assert_true(o.shape == (s + (l, )))
# Single image as input
out = image.smooth_img(imgs[0], fwhm)
assert_true(isinstance(out, nibabel.Nifti1Image))
assert_true(out.shape == (shapes[0] + (lengths[0], )))
# Check corner case situations when fwhm=0, See issue #1537
# Test whether function smooth_img raises a warning when fwhm=0.
assert_warns(UserWarning, image.smooth_img, img1, fwhm=0.)
# Test output equal when fwhm=None and fwhm=0
out_fwhm_none = image.smooth_img(img1, fwhm=None)
out_fwhm_zero = image.smooth_img(img1, fwhm=0.)
assert_array_equal(out_fwhm_none.get_data(), out_fwhm_zero.get_data())
def test_smooth_img():
# This function only checks added functionalities compared
# to _smooth_array()
shapes = ((10, 11, 12), (13, 14, 15))
lengths = (17, 18)
fwhm = (1., 2., 3.)
img1, mask1 = data_gen.generate_fake_fmri(shape=shapes[0],
length=lengths[0])
img2, mask2 = data_gen.generate_fake_fmri(shape=shapes[1],
length=lengths[1])
for create_files in (False, True):
with testing.write_tmp_imgs(img1, img2,
create_files=create_files) as imgs:
# List of images as input
out = image.smooth_img(imgs, fwhm)
assert_true(isinstance(out, list))
assert_true(len(out) == 2)
for o, s, l in zip(out, shapes, lengths):
assert_true(o.shape == (s + (l,)))
# Single image as input
out = image.smooth_img(imgs[0], fwhm)
assert_true(isinstance(out, nibabel.Nifti1Image))
assert_true(out.shape == (shapes[0] + (lengths[0],)))
# Check corner case situations when fwhm=0, See issue #1537
# Test whether function smooth_img raises a warning when fwhm=0.
assert_warns(UserWarning, image.smooth_img, img1, fwhm=0.)
# Test output equal when fwhm=None and fwhm=0
out_fwhm_none = image.smooth_img(img1, fwhm=None)
out_fwhm_zero = image.smooth_img(img1, fwhm=0.)
assert_array_equal(out_fwhm_none.get_data(), out_fwhm_zero.get_data())
data1 = np.zeros((10, 11, 12))
data1[2:4, 1:5, 3:6] = 1
data2 = np.zeros((13, 14, 15))
data2[2:4, 1:5, 3:6] = 9
img1_nifti2 = nibabel.Nifti2Image(data1, affine=np.eye(4))
img2_nifti2 = nibabel.Nifti2Image(data2, affine=np.eye(4))
out = image.smooth_img([img1_nifti2, img2_nifti2], fwhm=1.)
def test_smooth_img():
# This function only checks added functionalities compared
# to _smooth_array()
shapes = ((10, 11, 12), (13, 14, 15))
lengths = (17, 18)
fwhm = (1., 2., 3.)
img1, mask1 = data_gen.generate_fake_fmri(shape=shapes[0],
length=lengths[0])
img2, mask2 = data_gen.generate_fake_fmri(shape=shapes[1],
length=lengths[1])
for create_files in (False, True):
with testing.write_tmp_imgs(img1, img2,
create_files=create_files) as imgs:
# List of images as input
out = image.smooth_img(imgs, fwhm)
assert isinstance(out, list)
assert len(out) == 2
for o, s, l in zip(out, shapes, lengths):
assert o.shape == (s + (l, ))
# Single image as input
out = image.smooth_img(imgs[0], fwhm)
assert isinstance(out, nibabel.Nifti1Image)
assert out.shape == (shapes[0] + (lengths[0], ))
# Check corner case situations when fwhm=0, See issue #1537
# Test whether function smooth_img raises a warning when fwhm=0.
with pytest.warns(UserWarning):
image.smooth_img(img1, fwhm=0.)
# Test output equal when fwhm=None and fwhm=0
out_fwhm_none = image.smooth_img(img1, fwhm=None)
out_fwhm_zero = image.smooth_img(img1, fwhm=0.)
assert_array_equal(get_data(out_fwhm_none), get_data(out_fwhm_zero))
data1 = np.zeros((10, 11, 12))
data1[2:4, 1:5, 3:6] = 1
data2 = np.zeros((13, 14, 15))
data2[2:4, 1:5, 3:6] = 9
img1_nifti2 = nibabel.Nifti2Image(data1, affine=np.eye(4))
img2_nifti2 = nibabel.Nifti2Image(data2, affine=np.eye(4))
out = image.smooth_img([img1_nifti2, img2_nifti2], fwhm=1.)
