示例#1
0
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]])
示例#2
0
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())