def test_padding_fill(self, boundary_width, fill_value):
ds, coords, _ = datasets_grid_metric("C")
grid = Grid(ds, coords=coords)
data = ds.tracer
# iterate over all axes
expected = data.copy(deep=True)
for ax, widths in boundary_width.items():
dim = grid._get_dims_from_axis(
data, ax)[0] # ? not entirely sure why this is a list
expected = expected.pad({dim: widths},
"constant",
constant_values=fill_value)
# we intentionally strip all coords from padded arrays
expected = _strip_all_coords(expected)
result = pad(
data,
grid,
boundary="fill",
boundary_width=boundary_width,
fill_value=fill_value,
other_component=None,
)
xr.testing.assert_allclose(expected, result)
def test_padding_mixed(self, boundary_width):
ds, coords, _ = datasets_grid_metric("C")
grid = Grid(ds, coords=coords)
data = ds.tracer
axis_padding_mapping = {"X": "periodic", "Y": "extend"}
method_mapping = {
"periodic": "wrap",
"extend": "edge",
}
# iterate over all axes
expected = data.copy(deep=True)
for ax, widths in boundary_width.items():
dim = grid._get_dims_from_axis(
data, ax)[0] # ? not entirely sure why this is a list
expected = expected.pad({dim: widths},
method_mapping[axis_padding_mapping[ax]])
# we intentionally strip all coords from padded arrays
expected = _strip_all_coords(expected)
result = pad(
data,
grid,
boundary=axis_padding_mapping,
boundary_width=boundary_width,
fill_value=None,
other_component=None,
)
xr.testing.assert_allclose(expected, result)
