def test_interpolation_singular():
""" test interpolation on singular dimensions """
grid = UnitGrid([1])
field = ScalarField(grid, data=3)
# test constant boundary conditions
bc = [{"type": "value", "value": 1}, {"type": "value", "value": 5}]
x = np.linspace(0, 1, 7).reshape((7, 1))
y = field.interpolate(x, method="numba", bc=bc)
np.testing.assert_allclose(y, 1 + 4 * x.ravel())
# test derivative boundary conditions
bc = [{
"type": "derivative",
"value": -2
}, {
"type": "derivative",
"value": 2
}]
x = np.linspace(0, 1, 7).reshape((7, 1))
y = field.interpolate(x, method="numba", bc=bc)
np.testing.assert_allclose(y, 2 + 2 * x.ravel())
# test boundary interpolation
for upper in [True, False]:
val = field.get_boundary_values(axis=0, upper=upper, bc=[{"value": 1}])
assert val == pytest.approx(1)
def test_corner_interpolation():
"""test whether the field can also be interpolated up to the corner of the grid"""
grid = UnitGrid([1, 1], periodic=False)
field = ScalarField(grid)
field.set_ghost_cells({"value": 1})
assert field.interpolate(np.array([0.5, 0.5])) == pytest.approx(0.0)
assert field.interpolate(np.array([0.0, 0.5])) == pytest.approx(0.0)
assert field.interpolate(np.array([0.5, 0.0])) == pytest.approx(0.0)
assert field.interpolate(np.array([0.0, 0.0])) == pytest.approx(0.0)
def test_interpolation_mutable():
"""test interpolation on mutable fields"""
grid = UnitGrid([2], periodic=True)
field = ScalarField(grid)
for backend in ["numba", "scipy"]:
field.data = 1
np.testing.assert_allclose(field.interpolate([0.5], backend=backend), 1)
field.data = 2
np.testing.assert_allclose(field.interpolate([0.5], backend=backend), 2)
# test overwriting field values
data = np.full_like(field.data, 3)
intp = field.make_interpolator(backend="numba")
np.testing.assert_allclose(intp(np.array([0.5]), data), 3)
def test_interpolation_inhomogeneous_bc():
"""test field interpolation with inhomogeneous boundary condition"""
sf = ScalarField(UnitGrid([3, 3], periodic=False))
x = 1 + np.random.random()
bc = ["natural", {"type": "value", "value": "x"}]
v = sf.interpolate([x, 0], backend="numba", bc=bc)
assert x == pytest.approx(v)
def test_interpolation_singular():
"""test interpolation on singular dimensions"""
grid = UnitGrid([1])
field = ScalarField(grid, data=3)
# test constant boundary conditions
x = np.linspace(0, 1, 7).reshape((7, 1))
y = field.interpolate(x, backend="numba")
np.testing.assert_allclose(y, 3)
def test_complex_methods():
"""test special methods for complex data type"""
grid = UnitGrid([2, 2])
f = ScalarField(grid, 1j)
for backend in ["scipy", "numba"]:
val = f.interpolate([1, 1], backend=backend)
np.testing.assert_allclose(val, np.array([1j, 1j]))
f = ScalarField(grid, 1 + 2j)
np.testing.assert_allclose(f.project("x").data, np.full((2,), 2 + 4j))
np.testing.assert_allclose(f.slice({"x": 1}).data, np.full((2,), 1 + 2j))
def test_interpolation_singular():
"""test interpolation on singular dimensions"""
grid = UnitGrid([1])
field = ScalarField(grid, data=3)
# test constant boundary conditions
x = np.linspace(0, 1, 7).reshape((7, 1))
y = field.interpolate(x, backend="numba")
np.testing.assert_allclose(y, 3)
# # test boundary interpolation
for upper in [True, False]:
val = field.get_boundary_values(axis=0, upper=upper, bc=[{"value": 1}])
assert val == pytest.approx(1)