def test_slice_time_image():
# Test slice timing on image in memory
n_slices = 4
n_vols = 5
TR = 3.5
vol_times = np.arange(n_vols) * TR
# Add some random jitter per slice
slice_times = np.arange(n_slices) * TR / n_slices
slice_times = slice_times + np.random.normal(0, 0.05, size=(n_slices,))
# TEST AXIAL
data = np.random.normal(size=(2, 3, n_slices, n_vols))
img = nib.Nifti1Image(data, np.eye(4))
# Test against interpolation with interp_slice
for order in ('linear', 'cubic', 1, 4):
interped = np.zeros_like(data)
for slice_no in range(n_slices):
orig_times = vol_times + slice_times[slice_no]
interped[:, :, slice_no, :] = interp_slice(
orig_times, data[:, :, slice_no, :], vol_times, order)
interped_img = slice_time_image(img, slice_times, TR, order)
assert_almost_equal(interped_img.get_data(), interped)
# TEST SAGITTAL
data = np.random.normal(size=(n_slices, 2, 3, n_vols))
img = nib.Nifti1Image(data, np.eye(4))
for order in ('linear', 'cubic', 1, 4):
interped = np.zeros_like(data)
for slice_no in range(n_slices):
orig_times = vol_times + slice_times[slice_no]
interped[slice_no, ...] = interp_slice(
orig_times, data[slice_no, ...], vol_times, order)
interped_img = slice_time_image(img, slice_times, TR, order,
slice_axis=0)
assert_almost_equal(interped_img.get_data(), interped)
def test_slice_time_image():
# Test slice timing on image in memory
n_slices = 4
n_vols = 5
TR = 3.5
vol_times = np.arange(n_vols) * TR
# Add some random jitter per slice
slice_times = np.arange(n_slices) * TR / n_slices
slice_times = slice_times + np.random.normal(0, 0.05, size=(n_slices, ))
# TEST AXIAL
data = np.random.normal(size=(2, 3, n_slices, n_vols))
img = nib.Nifti1Image(data, np.eye(4))
# Test against interpolation with interp_slice
for order in ('linear', 'cubic', 1, 4):
interped = np.zeros_like(data)
for slice_no in range(n_slices):
orig_times = vol_times + slice_times[slice_no]
interped[:, :, slice_no, :] = interp_slice(orig_times,
data[:, :, slice_no, :],
vol_times, order)
interped_img = slice_time_image(img, slice_times, TR, order)
assert_almost_equal(interped_img.get_data(), interped)
# TEST SAGITTAL
data = np.random.normal(size=(n_slices, 2, 3, n_vols))
img = nib.Nifti1Image(data, np.eye(4))
for order in ('linear', 'cubic', 1, 4):
interped = np.zeros_like(data)
for slice_no in range(n_slices):
orig_times = vol_times + slice_times[slice_no]
interped[slice_no, ...] = interp_slice(orig_times, data[slice_no,
...],
vol_times, order)
interped_img = slice_time_image(img,
slice_times,
TR,
order,
slice_axis=0)
assert_almost_equal(interped_img.get_data(), interped)
def test_slice_time_file():
# Test slice_time_file from slice_time_image
n_slices = 5
n_vols = 4
TR = 2.0
data = np.random.normal(size=(2, 3, n_slices, n_vols))
img = nib.Nifti1Image(data, np.eye(4))
slice_times = np.arange(n_slices) * TR / n_slices + 0.1
tmpdir = tempfile.mkdtemp()
try:
fname = os.path.join(tmpdir, 'myfile.nii')
a_fname = os.path.join(tmpdir, 'amyfile.nii')
nib.save(img, fname)
for order in ('linear', 'cubic', 1, 4):
interped_img = slice_time_image(img, slice_times, TR, order)
slice_time_file(fname, slice_times, TR, order)
a_img = nib.load(a_fname)
assert_almost_equal(interped_img.get_data(), a_img.get_data())
del a_img
finally:
shutil.rmtree(tmpdir)
def test_slice_time_file():
# Test slice_time_file from slice_time_image
n_slices = 5
n_vols = 4
TR = 2.0
data = np.random.normal(size=(2, 3, n_slices, n_vols))
img = nib.Nifti1Image(data, np.eye(4))
slice_times = np.arange(n_slices) * TR / n_slices + 0.1
tmpdir = tempfile.mkdtemp()
try:
fname = os.path.join(tmpdir, 'myfile.nii')
a_fname = os.path.join(tmpdir, 'amyfile.nii')
nib.save(img, fname)
for order in ('linear', 'cubic', 1, 4):
interped_img = slice_time_image(img, slice_times, TR, order)
slice_time_file(fname, slice_times, TR, order)
a_img = nib.load(a_fname)
assert_almost_equal(interped_img.get_data(), a_img.get_data())
del a_img
finally:
shutil.rmtree(tmpdir)
