def test_apply():
# most tests are in ``same_transform`` above, via the
# test_io_orientations.
a = np.arange(24).reshape((2,3,4))
# Test 4D
t_arr = apply_orientation(a[:,:,:,None], ornt)
yield assert_equal(t_arr.ndim, 4)
# Orientation errors
yield assert_raises(OrientationError,
apply_orientation,
a[:,:,1], ornt)
yield assert_raises(OrientationError,
apply_orientation,
a,
[[0,1],[np.nan,np.nan],[2,1]])
def same_transform(taff, ornt, shape):
# Applying transformations implied by `ornt` to a made-up array
# ``arr`` of shape `shape`, results in ``t_arr``. When the point
# indices from ``arr`` are transformed by (the inverse of) `taff`,
# and we index into ``t_arr`` with these transformed points, then we
# should get the same values as we would from indexing into arr with
# the untransformed points.
shape = np.array(shape)
size = np.prod(shape)
arr = np.arange(size).reshape(shape)
# apply ornt transformations
t_arr = apply_orientation(arr, ornt)
# get all point indices in arr
i,j,k = shape
arr_pts = np.mgrid[:i,:j,:k].reshape((3,-1))
# inverse of taff takes us from point index in arr to point index in
# t_arr
itaff = np.linalg.inv(taff)
# apply itaff so that points indexed in t_arr should correspond
o2t_pts = np.dot(itaff[:3,:3], arr_pts) + itaff[:3,3][:,None]
assert np.allclose(np.round(o2t_pts), o2t_pts)
# fancy index out the t_arr values
vals = t_arr[list(o2t_pts.astype('i'))]
return np.all(vals == arr.ravel())
