def test_resample_stat_map():
# Start with simple simulated data
bg_img, data = _simulate_img()
# Now double the voxel size and mess with the affine
affine = 2 * np.eye(4)
affine[3, 3] = 1
affine[0, 1] = 0.1
stat_map_img = Nifti1Image(data, affine)
# Make a mask for the stat image
mask_img = new_img_like(stat_map_img, data > 0, stat_map_img.affine)
# Now run the resampling
stat_map_img, mask_img = html_stat_map._resample_stat_map(
stat_map_img, bg_img, mask_img, resampling_interpolation='nearest')
# Check positive isotropic, near-diagonal affine
_check_affine(stat_map_img.affine)
_check_affine(mask_img.affine)
# Check voxel size matches bg_img
assert stat_map_img.affine[0, 0] == bg_img.affine[0, 0], (
"stat_map_img was not resampled at the resolution of background")
assert mask_img.affine[0, 0] == bg_img.affine[0, 0], (
"mask_img was not resampled at the resolution of background")
def test_resample_stat_map():
# Start with simple simulated data
bg_img, data = _simulate_img()
# Now double the voxel size and mess with the affine
affine = 2 * np.eye(4)
affine[3, 3] = 1
affine[0, 1] = 0.1
stat_map_img = Nifti1Image(data, affine)
# Make a mask for the stat image
mask_img = new_img_like(stat_map_img, data > 0, stat_map_img.affine)
# Now run the resampling
stat_map_img, mask_img = html_stat_map._resample_stat_map(
stat_map_img, bg_img, mask_img, resampling_interpolation='nearest')
# Check positive isotropic, near-diagonal affine
_check_affine(stat_map_img.affine)
_check_affine(mask_img.affine)
# Check voxel size matches bg_img
assert stat_map_img.affine[0, 0] == bg_img.affine[0, 0], (
"stat_map_img was not resampled at the resolution of background")
assert mask_img.affine[0, 0] == bg_img.affine[0, 0], (
"mask_img was not resampled at the resolution of background")
