def loss(delta): x = np.arange(100.0) border = 10 indices = np.arange(x.size) + delta # linear interpolation of the linear function y=x should be exact shifted = lsp_ndimage.map_coordinates(x, [indices], order=1) return ((x - shifted) ** 2)[border:-border].mean()
def testMapCoordinates(self, shape, dtype, coords_shape, coords_dtype,
order, mode, cval, impl, round_, rng_factory):
def args_maker():
x = np.arange(prod(shape), dtype=dtype).reshape(shape)
coords = [(size - 1) * rng(coords_shape, coords_dtype)
for size in shape]
if round_:
coords = [c.round().astype(int) for c in coords]
return x, coords
rng = rng_factory(self.rng())
lsp_op = lambda x, c: lsp_ndimage.map_coordinates(
x, c, order=order, mode=mode, cval=cval)
impl_fun = (osp_ndimage.map_coordinates
if impl == "original" else _fixed_ref_map_coordinates)
osp_op = lambda x, c: impl_fun(x, c, order=order, mode=mode, cval=cval)
if dtype in float_dtypes:
epsilon = max([
dtypes.finfo(dtypes.canonicalize_dtype(d)).eps
for d in [dtype, coords_dtype]
])
self._CheckAgainstNumpy(osp_op,
lsp_op,
args_maker,
tol=100 * epsilon)
else:
self._CheckAgainstNumpy(osp_op, lsp_op, args_maker, tol=0)
def testMapCoordinatesRoundHalf(self, dtype, order):
x = np.arange(-3, 3, dtype=dtype)
c = np.array([[.5, 1.5, 2.5, 3.5]])
def args_maker():
return x, c
lsp_op = lambda x, c: lsp_ndimage.map_coordinates(x, c, order=order)
osp_op = lambda x, c: osp_ndimage.map_coordinates(x, c, order=order)
self._CheckAgainstNumpy(osp_op, lsp_op, args_maker)
def testMapCoordinatesRoundHalf(self, dtype, order):
x = np.arange(-3, 3, dtype=dtype)
c = np.array([[.5, 1.5, 2.5, 3.5]])
def args_maker():
return x, c
lsp_op = lambda x, c: lsp_ndimage.map_coordinates(x, c, order=order)
osp_op = lambda x, c: osp_ndimage.map_coordinates(x, c, order=order)
with jtu.strict_promotion_if_dtypes_match([dtype, c.dtype]):
self._CheckAgainstNumpy(osp_op, lsp_op, args_maker)
def testMapCoordinatesErrors(self):
x = np.arange(5.0)
c = [np.linspace(0, 5, num=3)]
with self.assertRaisesRegex(NotImplementedError, 'requires order<=1'):
lsp_ndimage.map_coordinates(x, c, order=2)
with self.assertRaisesRegex(
NotImplementedError, 'does not yet support mode'):
lsp_ndimage.map_coordinates(x, c, order=1, mode='reflect')
with self.assertRaisesRegex(ValueError, 'sequence of length'):
lsp_ndimage.map_coordinates(x, [c, c], order=1)
def _resample_1d(inputs, new_size):
if inputs.ndim != 1:
raise ValueError(f'inputs must be 1d but has shape {inputs.shape}')
x = jnp.linspace(0, inputs.size - 1, num=new_size)
return ndimage.map_coordinates(inputs, [x], order=1, mode='nearest')
def interp(x):
xu = interval_to_unit(x, y0, y1)
xun = np.clip(xu * n, 0, n)
return map_coordinates(pvals, np.atleast_1d(xun), order=1, mode='nearest')
