def test_linear_interpolator_3d():
random_data = np.random.random((64, 64, 64))
# evenly spaced bins
fv = {
ax: v
for ax, v in zip("xyz", np.mgrid[0.0:1.0:64j, 0.0:1.0:64j,
0.0:1.0:64j])
}
tfi = lin.TrilinearFieldInterpolator(random_data,
(0.0, 1.0, 0.0, 1.0, 0.0, 1.0), "xyz",
True)
assert_array_almost_equal(tfi(fv), random_data)
# randomly spaced bins
size = 64
bins = np.linspace(0.0, 1.0, size)
shifts = {
ax: (1.0 / size) * np.random.random(size) - (0.5 / size)
for ax in "xyz"
}
fv["x"] += shifts["x"][:, np.newaxis, np.newaxis]
fv["y"] += shifts["y"][:, np.newaxis]
fv["z"] += shifts["z"]
tfi = lin.TrilinearFieldInterpolator(
random_data,
(bins + shifts["x"], bins + shifts["y"], bins + shifts["z"]),
"xyz",
True,
)
assert_array_almost_equal(tfi(fv), random_data, 15)
def test_ghost_zone_extrapolation():
ds = fake_random_ds(16)
g = ds.index.grids[0]
vec = g.get_vertex_centered_data(['x', 'y', 'z'], no_ghost=True)
for i, ax in enumerate('xyz'):
xc = g[ax]
tf = lin.TrilinearFieldInterpolator(
xc,
(g.LeftEdge[0] + g.dds[0] / 2.0, g.RightEdge[0] - g.dds[0] / 2.0,
g.LeftEdge[1] + g.dds[1] / 2.0, g.RightEdge[1] - g.dds[1] / 2.0,
g.LeftEdge[2] + g.dds[2] / 2.0, g.RightEdge[2] - g.dds[2] / 2.0),
["x", "y", "z"],
truncate=True)
lx, ly, lz = np.mgrid[
g.LeftEdge[0]:g.RightEdge[0]:(g.ActiveDimensions[0] + 1) * 1j,
g.LeftEdge[1]:g.RightEdge[1]:(g.ActiveDimensions[1] + 1) * 1j,
g.LeftEdge[2]:g.RightEdge[2]:(g.ActiveDimensions[2] + 1) * 1j]
xi = tf({'x': lx, 'y': ly, 'z': lz})
xz = np.zeros(g.ActiveDimensions + 1)
ghost_zone_interpolate(1, xc, np.array([0.5, 0.5, 0.5], dtype="f8"),
xz, np.array([0.0, 0.0, 0.0], dtype="f8"))
ii = (lx, ly, lz)[i]
assert_array_equal(ii, vec[ax])
assert_array_equal(ii, xi)
assert_array_equal(ii, xz)