def test_esmpy_normalisation():
"""
Integration test for :meth:`~esmf_regrid.esmf_regridder.Regridder`.
Checks against ESMF to ensure results are consistent.
"""
src_data = np.array(
[
[1.0, 1.0],
[1.0, 0.0],
[1.0, 0.0],
],
)
src_mask = np.array(
[
[True, False],
[False, False],
[False, False],
]
)
src_array = ma.array(src_data, mask=src_mask)
lon, lat, lon_bounds, lat_bounds = make_grid_args(2, 3)
src_grid = GridInfo(lon, lat, lon_bounds, lat_bounds)
src_esmpy_grid = src_grid._make_esmf_grid()
src_esmpy_grid.add_item(ESMF.GridItem.MASK, staggerloc=ESMF.StaggerLoc.CENTER)
src_esmpy_grid.mask[0][...] = src_mask
src_field = ESMF.Field(src_esmpy_grid)
src_field.data[...] = src_data
lon, lat, lon_bounds, lat_bounds = make_grid_args(3, 2)
tgt_grid = GridInfo(lon, lat, lon_bounds, lat_bounds)
tgt_field = tgt_grid.make_esmf_field()
regridder = Regridder(src_grid, tgt_grid)
regridding_kwargs = {
"ignore_degenerate": True,
"regrid_method": ESMF.RegridMethod.CONSERVE,
"unmapped_action": ESMF.UnmappedAction.IGNORE,
"factors": True,
"src_mask_values": [1],
}
esmpy_fracarea_regridder = ESMF.Regrid(
src_field, tgt_field, norm_type=ESMF.NormType.FRACAREA, **regridding_kwargs
)
esmpy_dstarea_regridder = ESMF.Regrid(
src_field, tgt_field, norm_type=ESMF.NormType.DSTAREA, **regridding_kwargs
)
tgt_field_dstarea = esmpy_dstarea_regridder(src_field, tgt_field)
result_esmpy_dstarea = tgt_field_dstarea.data
result_dstarea = regridder.regrid(src_array, norm_type="dstarea")
assert ma.allclose(result_esmpy_dstarea, result_dstarea)
tgt_field_fracarea = esmpy_fracarea_regridder(src_field, tgt_field)
result_esmpy_fracarea = tgt_field_fracarea.data
result_fracarea = regridder.regrid(src_array, norm_type="fracarea")
assert ma.allclose(result_esmpy_fracarea, result_fracarea)
def _regrid_rectilinear_to_rectilinear__prepare(src_grid_cube, tgt_grid_cube):
tgt_x = tgt_grid_cube.coord(axis="x")
tgt_y = tgt_grid_cube.coord(axis="y")
src_x = src_grid_cube.coord(axis="x")
src_y = src_grid_cube.coord(axis="y")
if len(src_x.shape) == 1:
grid_x_dim = src_grid_cube.coord_dims(src_x)[0]
grid_y_dim = src_grid_cube.coord_dims(src_y)[0]
else:
grid_y_dim, grid_x_dim = src_grid_cube.coord_dims(src_x)
srcinfo = _cube_to_GridInfo(src_grid_cube)
tgtinfo = _cube_to_GridInfo(tgt_grid_cube)
regridder = Regridder(srcinfo, tgtinfo)
regrid_info = RegridInfo(
x_dim=grid_x_dim,
y_dim=grid_y_dim,
x_coord=tgt_x,
y_coord=tgt_y,
regridder=regridder,
)
return regrid_info
def test_global_grid():
"""Test conversion of a global grid."""
n_lons = 6
n_lats = 5
lon_bounds = (-180, 180)
lat_bounds = (-90, 90)
cube = _grid_cube(
n_lons,
n_lats,
lon_bounds,
lat_bounds,
circular=True,
coord_system=GeogCS(EARTH_RADIUS),
)
gridinfo = _cube_to_GridInfo(cube)
# Ensure conversion to ESMF works without error
_ = gridinfo.make_esmf_field()
# The following test ensures there are no overlapping cells.
# This catches geometric/topological abnormalities that would arise from,
# for example: switching lat/lon values, using euclidean coords vs spherical.
rg = Regridder(gridinfo, gridinfo)
expected_weights = scipy.sparse.identity(n_lats * n_lons)
assert np.array_equal(expected_weights.todense(),
rg.weight_matrix.todense())
assert gridinfo.crs == GeogCS(EARTH_RADIUS).as_cartopy_crs()
def _regrid_rectilinear_to_unstructured__prepare(
src_grid_cube,
target_mesh_cube,
method,
precomputed_weights=None,
resolution=None,
):
"""
First (setup) part of 'regrid_rectilinear_to_unstructured'.
Check inputs and calculate the sparse regrid matrix and related info.
The 'regrid info' returned can be re-used over many 2d slices.
"""
grid_x = src_grid_cube.coord(axis="x")
grid_y = src_grid_cube.coord(axis="y")
mesh = target_mesh_cube.mesh
location = target_mesh_cube.location
if mesh is None:
raise ValueError("The given cube is not defined on a mesh.")
if method == "conservative":
if location != "face":
raise ValueError(
f"Conservative regridding requires a target cube located on "
f"the face of a cube, target cube had the {location} location."
)
center = False
elif method == "bilinear":
if location not in ["face", "node"]:
raise ValueError(
f"Bilinear regridding requires a target cube with a node "
f"or face location, target cube had the {location} location."
)
if location == "face" and None in mesh.face_coords:
raise ValueError(
"Bilinear regridding requires a target cube on a face location to have "
"a face center."
)
center = True
else:
raise ValueError(
f"method must be either 'bilinear' or 'conservative', got '{method}'."
)
assert mesh is not None
if grid_x.ndim == 1:
(grid_x_dim,) = src_grid_cube.coord_dims(grid_x)
(grid_y_dim,) = src_grid_cube.coord_dims(grid_y)
else:
grid_y_dim, grid_x_dim = src_grid_cube.coord_dims(grid_x)
meshinfo = _mesh_to_MeshInfo(mesh, location)
gridinfo = _cube_to_GridInfo(src_grid_cube, center=center, resolution=resolution)
regridder = Regridder(
gridinfo, meshinfo, method=method, precomputed_weights=precomputed_weights
)
regrid_info = (grid_x_dim, grid_y_dim, grid_x, grid_y, mesh, location, regridder)
return regrid_info
def test_Regridder_init_fail():
"""Basic test for :meth:`~esmf_regrid.esmf_regridder.Regridder.__init__`."""
lon, lat, lon_bounds, lat_bounds = make_grid_args(2, 3)
src_grid = GridInfo(lon, lat, lon_bounds, lat_bounds)
lon, lat, lon_bounds, lat_bounds = make_grid_args(3, 2)
tgt_grid = GridInfo(lon, lat, lon_bounds, lat_bounds)
with pytest.raises(ValueError):
_ = Regridder(src_grid, tgt_grid, method="other")
def test_large_mesh_validity():
"""Test validity of objects derived from a large gridlike Mesh."""
mesh = _gridlike_mesh(40, 20)
meshinfo = _mesh_to_MeshInfo(mesh, location="face")
# Ensure conversion to ESMF works without error.
_ = meshinfo.make_esmf_field()
# The following test ensures there are no overlapping cells.
# This catches geometric/topological abnormalities that would arise from,
# for example: switching lat/lon values, using euclidean coords vs spherical.
rg = Regridder(meshinfo, meshinfo)
expected_weights = scipy.sparse.identity(meshinfo.size)
assert np.allclose(expected_weights.todense(), rg.weight_matrix.todense())
def test_Regridder_init():
"""Basic test for :meth:`~esmf_regrid.esmf_regridder.Regridder.__init__`."""
lon, lat, lon_bounds, lat_bounds = make_grid_args(2, 3)
src_grid = GridInfo(lon, lat, lon_bounds, lat_bounds)
lon, lat, lon_bounds, lat_bounds = make_grid_args(3, 2)
tgt_grid = GridInfo(lon, lat, lon_bounds, lat_bounds)
rg = Regridder(src_grid, tgt_grid)
result = rg.weight_matrix
expected = _expected_weights()
assert np.allclose(result.toarray(), expected.toarray())
def test_curvilinear_grid():
"""Test conversion of a curvilinear global grid."""
n_lons = 6
n_lats = 5
lon_bounds = (-180, 180)
lat_bounds = (-90, 90)
cube = _curvilinear_cube(
n_lons,
n_lats,
lon_bounds,
lat_bounds,
coord_system=GeogCS(EARTH_RADIUS),
)
gridinfo = _cube_to_GridInfo(cube)
# Ensure conversion to ESMF works without error
_ = gridinfo.make_esmf_field()
# The following test ensures there are no overlapping cells.
# This catches geometric/topological abnormalities that would arise from,
# for example: switching lat/lon values, using euclidean coords vs spherical.
rg = Regridder(gridinfo, gridinfo)
expected_weights = scipy.sparse.identity(n_lats * n_lons)
assert np.array_equal(expected_weights.todense(),
rg.weight_matrix.todense())
assert gridinfo.crs == GeogCS(EARTH_RADIUS).as_cartopy_crs()
# While curvilinear coords do not have the "circular" attribute, the code
# allows "circular" to be True when setting the core regridder directly.
# This describes an ESMF object which is topologically different, but ought
# to be geometrically equivalent to the non-circular case.
circular_gridinfo = _cube_to_GridInfo(cube)
circular_gridinfo.circular = True
rg_circular = Regridder(circular_gridinfo, gridinfo)
assert np.allclose(expected_weights.todense(),
rg_circular.weight_matrix.todense())
def test_local_grid():
"""Test conversion of a local grid."""
n_lons = 6
n_lats = 5
lon_bounds = (-20, 20)
lat_bounds = (20, 60)
cube = _grid_cube(n_lons, n_lats, lon_bounds, lat_bounds)
gridinfo = _cube_to_GridInfo(cube)
# Ensure conversion to ESMF works without error
_ = gridinfo.make_esmf_field()
# The following test ensures there are no overlapping cells.
# Note that this test fails when longitude is circular.
rg = Regridder(gridinfo, gridinfo)
expected_weights = scipy.sparse.identity(n_lats * n_lons)
assert np.array_equal(expected_weights.todense(), rg.weight_matrix.todense())
def test_expanded_lons_with_mesh():
"""
Basic test for regridding with :meth:`~esmf_regrid.esmf_regridder.RefinedGridInfo.make_esmf_field`.
Mirrors the tests in :func:`~esmf_regrid.tests.unit.experimental.unstructured_regrid.test_MeshInfo.test_regrid_with_mesh`
but with slightly different expected values due to increased accuracy.
"""
mesh_args = _make_small_mesh_args()
mesh = MeshInfo(*mesh_args)
grid_args = make_grid_args(2, 3)
grid = RefinedGridInfo(*grid_args[2:4], resolution=4)
mesh_to_grid_regridder = Regridder(mesh, grid)
mesh_input = np.array([3, 2])
grid_output = mesh_to_grid_regridder.regrid(mesh_input)
expected_grid_output = np.array([
[2.671534474734418, 3.0],
[2.088765949748455, 2.922517356506756],
[2.0, 2.340882413622917],
])
assert ma.allclose(expected_grid_output, grid_output)
grid_to_mesh_regridder = Regridder(grid, mesh)
grid_input = np.array([[0, 0], [1, 0], [2, 1]])
mesh_output = grid_to_mesh_regridder.regrid(grid_input)
expected_mesh_output = np.array([0.14117205318254747, 1.1976140197893996])
assert ma.allclose(expected_mesh_output, mesh_output)
def _give_extra_dims(array):
result = np.stack([array, array + 1])
result = np.stack([result, result + 10, result + 100])
return result
extra_dim_mesh_input = _give_extra_dims(mesh_input)
extra_dim_grid_output = mesh_to_grid_regridder.regrid(extra_dim_mesh_input)
extra_dim_expected_grid_output = _give_extra_dims(expected_grid_output)
assert ma.allclose(extra_dim_expected_grid_output, extra_dim_grid_output)
extra_dim_grid_input = _give_extra_dims(grid_input)
extra_dim_mesh_output = grid_to_mesh_regridder.regrid(extra_dim_grid_input)
extra_dim_expected_mesh_output = _give_extra_dims(expected_mesh_output)
assert ma.allclose(extra_dim_expected_mesh_output, extra_dim_mesh_output)
def test_grid_with_scalars():
"""Test conversion of a grid with scalar coords."""
n_lons = 1
n_lats = 5
lon_bounds = (-20, 20)
lat_bounds = (20, 60)
cube = _grid_cube(n_lons, n_lats, lon_bounds, lat_bounds)
# Convert longitude to a scalar
cube = cube[:, 0]
assert len(cube.shape) == 1
gridinfo = _cube_to_GridInfo(cube)
# Ensure conversion to ESMF works without error
_ = gridinfo.make_esmf_field()
# The following test ensures there are no overlapping cells.
rg = Regridder(gridinfo, gridinfo)
expected_weights = scipy.sparse.identity(n_lats * n_lons)
assert np.array_equal(expected_weights.todense(), rg.weight_matrix.todense())
def test_regrid_with_mesh():
"""Basic test for regridding with :meth:`~esmf_regrid.esmf_regridder.GridInfo.make_esmf_field`."""
mesh_args = _make_small_mesh_args()
mesh = MeshInfo(*mesh_args)
grid_args = make_grid_args(2, 3)
grid = GridInfo(*grid_args)
mesh_to_grid_regridder = Regridder(mesh, grid)
mesh_input = np.array([3, 2])
grid_output = mesh_to_grid_regridder.regrid(mesh_input)
expected_grid_output = np.array([
[2.671294712940605, 3.0],
[2.0885553467353097, 2.9222786250561574],
[2.0, 2.3397940801753307],
])
assert ma.allclose(expected_grid_output, grid_output)
grid_to_mesh_regridder = Regridder(grid, mesh)
grid_input = np.array([[0, 0], [1, 0], [2, 1]])
mesh_output = grid_to_mesh_regridder.regrid(grid_input)
expected_mesh_output = np.array([0.1408245341331448, 1.19732762534643])
assert ma.allclose(expected_mesh_output, mesh_output)
def _give_extra_dims(array):
result = np.stack([array, array + 1])
result = np.stack([result, result + 10, result + 100])
return result
extra_dim_mesh_input = _give_extra_dims(mesh_input)
extra_dim_grid_output = mesh_to_grid_regridder.regrid(extra_dim_mesh_input)
extra_dim_expected_grid_output = _give_extra_dims(expected_grid_output)
assert ma.allclose(extra_dim_expected_grid_output, extra_dim_grid_output)
extra_dim_grid_input = _give_extra_dims(grid_input)
extra_dim_mesh_output = grid_to_mesh_regridder.regrid(extra_dim_grid_input)
extra_dim_expected_mesh_output = _give_extra_dims(expected_mesh_output)
assert ma.allclose(extra_dim_expected_mesh_output, extra_dim_mesh_output)
def _regrid_rectilinear_to_rectilinear__prepare(src_grid_cube, tgt_grid_cube):
tgt_x, tgt_y = get_xy_dim_coords(tgt_grid_cube)
src_x, src_y = get_xy_dim_coords(src_grid_cube)
grid_x_dim = src_grid_cube.coord_dims(src_x)[0]
grid_y_dim = src_grid_cube.coord_dims(src_y)[0]
srcinfo = _cube_to_GridInfo(src_grid_cube)
tgtinfo = _cube_to_GridInfo(tgt_grid_cube)
regridder = Regridder(srcinfo, tgtinfo)
regrid_info = RegridInfo(
x_dim=grid_x_dim,
y_dim=grid_y_dim,
x_coord=tgt_x,
y_coord=tgt_y,
regridder=regridder,
)
return regrid_info
def test_expanded_lats_with_mesh():
"""Basic test for regridding with :meth:`~esmf_regrid.esmf_regridder.RefinedGridInfo.make_esmf_field`."""
mesh_args = _make_small_mesh_args()
mesh = MeshInfo(*mesh_args)
grid = RefinedGridInfo(np.array([0, 5, 10]),
np.array([-90, 90]),
resolution=4)
mesh_to_grid_regridder = Regridder(mesh, grid)
mesh_input = np.array([3, 2])
grid_output = mesh_to_grid_regridder.regrid(mesh_input)
expected_grid_output = np.array([
[2.2024695514629724, 2.4336888097502642],
])
assert ma.allclose(expected_grid_output, grid_output)
grid_to_mesh_regridder = Regridder(grid, mesh)
grid_input = np.array([[1, 2]])
mesh_output = grid_to_mesh_regridder.regrid(grid_input)
expected_mesh_output = np.array([1.7480791292591336, 1.496070008348207])
assert ma.allclose(expected_mesh_output, mesh_output)
def _give_extra_dims(array):
result = np.stack([array, array + 1])
result = np.stack([result, result + 10, result + 100])
return result
extra_dim_mesh_input = _give_extra_dims(mesh_input)
extra_dim_grid_output = mesh_to_grid_regridder.regrid(extra_dim_mesh_input)
extra_dim_expected_grid_output = _give_extra_dims(expected_grid_output)
assert ma.allclose(extra_dim_expected_grid_output, extra_dim_grid_output)
extra_dim_grid_input = _give_extra_dims(grid_input)
extra_dim_mesh_output = grid_to_mesh_regridder.regrid(extra_dim_grid_input)
extra_dim_expected_mesh_output = _give_extra_dims(expected_mesh_output)
assert ma.allclose(extra_dim_expected_mesh_output, extra_dim_mesh_output)
def test_regrid_bilinear_with_mesh():
"""Basic test for regridding with :meth:`~esmf_regrid.esmf_regridder.GridInfo.make_esmf_field`."""
# We create a mesh with the following shape:
# 20 ,+ ,+ 4
# / | with nodes: / |
# 10 +' ,+ 1 +' ,+ 3
# | / | | / |
# 0 +---+ 0 +---+ 2
# 0 10
mesh_args = _make_small_mesh_args()
elem_coords = np.array([[5, 0], [5, 10]])
node_mesh = MeshInfo(*mesh_args, location="node")
face_mesh = MeshInfo(*mesh_args, elem_coords=elem_coords, location="face")
# We create a grid with the following shape:
# 20/3 +---+
# | |
# 10/3 +---+
# | |
# 0 +---+
# 0 10
grid_args = [ar * 2 for ar in make_grid_args(2, 3)]
grid = GridInfo(*grid_args, center=True)
mesh_to_grid_regridder = Regridder(node_mesh, grid, method="bilinear")
mesh_input = np.arange(5)
grid_output = mesh_to_grid_regridder.regrid(mesh_input)
# For a flat surface, we would expect the fractional part of these values
# to be either 1/3 or 2/3. Since the actual surface lies on a sphere, and
# due to the way ESMF calculates these values, the expected output is
# slightly different. It's worth noting that the finer the resolution, the
# closer these numbers are. Since the grids/meshes lie on coarse steps of
# about 10 degrees, we can expect most cases to behave more similarly to
# bilinear regridders on flat surfaces.
expected_grid_output = np.array([
[0.0, 2.0],
[0.6662902773937054, 2.6662902773105808],
[-1, 3.333709722689418],
])
expected_grid_mask = np.array([[0, 0], [0, 0], [1, 0]])
expected_grid_output = ma.array(expected_grid_output,
mask=expected_grid_mask)
assert ma.allclose(expected_grid_output, grid_output)
grid_to_mesh_regridder = Regridder(grid, node_mesh, method="bilinear")
grid_input = np.array([[0, 0], [1, 0], [2, 1]])
mesh_output = grid_to_mesh_regridder.regrid(grid_input)
expected_mesh_output = ma.array([0.0, 1.5, 0.0, 0.5, -1],
mask=[0, 0, 0, 0, 1])
assert ma.allclose(expected_mesh_output, mesh_output)
grid_to_face_mesh_regridder = Regridder(grid, face_mesh, method="bilinear")
grid_input_2 = np.array([[0, 0], [1, 0], [4, 1]])
face_mesh_output = grid_to_face_mesh_regridder.regrid(grid_input_2)
expected_face_mesh_output = np.array([0.0, 1.4888258584989558])
assert ma.allclose(expected_face_mesh_output, face_mesh_output)
def _give_extra_dims(array):
result = np.stack([array, array + 1])
result = np.stack([result, result + 10, result + 100])
return result
extra_dim_mesh_input = _give_extra_dims(mesh_input)
extra_dim_grid_output = mesh_to_grid_regridder.regrid(extra_dim_mesh_input)
extra_dim_expected_grid_output = _give_extra_dims(expected_grid_output)
assert ma.allclose(extra_dim_expected_grid_output, extra_dim_grid_output)
extra_dim_grid_input = _give_extra_dims(grid_input)
extra_dim_mesh_output = grid_to_mesh_regridder.regrid(extra_dim_grid_input)
extra_dim_expected_mesh_output = _give_extra_dims(expected_mesh_output)
assert ma.allclose(extra_dim_expected_mesh_output, extra_dim_mesh_output)
def test_Regridder_regrid():
"""Basic test for :meth:`~esmf_regrid.esmf_regridder.Regridder.regrid`."""
lon, lat, lon_bounds, lat_bounds = make_grid_args(2, 3)
src_grid = GridInfo(lon, lat, lon_bounds, lat_bounds)
lon, lat, lon_bounds, lat_bounds = make_grid_args(3, 2)
tgt_grid = GridInfo(lon, lat, lon_bounds, lat_bounds)
# Set up the regridder with precomputed weights.
rg = Regridder(src_grid, tgt_grid, precomputed_weights=_expected_weights())
src_array = np.array([[1.0, 1.0], [1.0, 0.0], [1.0, 0.0]])
src_masked = ma.array(src_array, mask=np.array([[1, 0], [0, 0], [0, 0]]))
# Regrid with unmasked data.
result_nomask = rg.regrid(src_array)
expected_nomask = ma.array([
[1.0, 0.8336393373988409, 0.6674194025656824],
[1.0, 0.4999999999999997, 0.0],
])
assert ma.allclose(result_nomask, expected_nomask)
# Regrid with an masked array with no masked points.
result_ma_nomask = rg.regrid(ma.array(src_array))
assert ma.allclose(result_ma_nomask, expected_nomask)
# Regrid with a fully masked array.
result_fullmask = rg.regrid(ma.array(src_array, mask=True))
expected_fulmask = ma.array(np.zeros([2, 3]), mask=True)
assert ma.allclose(result_fullmask, expected_fulmask)
# Regrid with a masked array containing a masked point.
result_withmask = rg.regrid(src_masked)
expected_withmask = ma.array([
[0.9999999999999999, 0.7503444126612077, 0.6674194025656824],
[1.0, 0.4999999999999997, 0.0],
])
assert ma.allclose(result_withmask, expected_withmask)
# Regrid while setting mdtol.
result_half_mdtol = rg.regrid(src_masked, mdtol=0.5)
expected_half_mdtol = ma.array(expected_withmask,
mask=np.array([[1, 0, 1], [0, 0, 0]]))
assert ma.allclose(result_half_mdtol, expected_half_mdtol)
# Regrid with norm_type="dstarea".
result_dstarea = rg.regrid(src_masked, norm_type="dstarea")
expected_dstarea = ma.array([
[0.3325805974343169, 0.4999999999999999, 0.6674194025656823],
[0.9999999999999998, 0.499931367542066, 0.0],
])
assert ma.allclose(result_dstarea, expected_dstarea)
def _give_extra_dims(array):
result = np.stack([array, array + 1])
result = np.stack([result, result + 10, result + 100])
return result
# Regrid with multiple extra dimensions.
extra_dim_src = _give_extra_dims(src_array)
extra_dim_expected = _give_extra_dims(expected_nomask)
extra_dim_result = rg.regrid(extra_dim_src)
assert ma.allclose(extra_dim_result, extra_dim_expected)
# Regrid extra dimensions with different masks.
mixed_mask_src = ma.stack([src_array, src_masked])
mixed_mask_expected = np.stack([expected_nomask, expected_withmask])
mixed_mask_result = rg.regrid(mixed_mask_src)
assert ma.allclose(mixed_mask_result, mixed_mask_expected)
assert src_array.T.shape != src_array.shape
with pytest.raises(ValueError):
_ = rg.regrid(src_array.T)
with pytest.raises(ValueError):
_ = rg.regrid(src_masked, norm_type="INVALID")
def test_Regridder_init_small():
"""
Simplified test for :meth:`~esmf_regrid.esmf_regridder.Regridder.regrid`.
This test is designed to be simple enough to generate predictable weights.
With predictable weights it is easier to check that the weights are
associated with the correct indices.
"""
# The following ASCII visualisation describes the source and target grids
# and the indices which ESMF assigns to their cells.
# Analysis of the weights dict returned by ESMF confirms that this is
# indeed the indexing which ESMF assigns these grids.
#
# 30 +---+---+ +-------+
# | 3 | 6 | | |
# 20 +---+---+ | 2 |
# | 2 | 5 | | |
# 10 +---+---+ +-------+
# | 1 | 4 | | 1 |
# 0 +---+---+ +-------+
# 0 10 20 0 20
def _get_points(bounds):
points = (bounds[:-1] + bounds[1:]) / 2
return points
lon_bounds = np.array([0, 10, 20])
lat_bounds = np.array([0, 10, 20, 30])
lon, lat = _get_points(lon_bounds), _get_points(lat_bounds)
src_grid = GridInfo(lon, lat, lon_bounds, lat_bounds)
assert src_grid.shape == (3, 2)
assert src_grid._index_offset() == 1
lon_bounds = np.array([0, 20])
lat_bounds = np.array([0, 10, 30])
lon, lat = _get_points(lon_bounds), _get_points(lat_bounds)
tgt_grid = GridInfo(lon, lat, lon_bounds, lat_bounds)
assert tgt_grid.shape == (2, 1)
assert tgt_grid._index_offset() == 1
rg = Regridder(src_grid, tgt_grid)
result = rg.weight_matrix
weights_dict = {}
weights_dict["row_dst"] = (
np.array([1, 1, 1, 1, 2, 2, 2, 2], dtype=np.int32) -
src_grid._index_offset())
weights_dict["col_src"] = (
np.array([1, 2, 4, 5, 2, 3, 5, 6], dtype=np.int32) -
tgt_grid._index_offset())
# The following weights are calculated from grids on a sphere with great circles
# defining the lines. Because of this, weights are not exactly the same as they
# would be in euclidean geometry and there are some small additional weights
# where the cells would not ordinarily overlap in a euclidean grid.
weights_dict["weights"] = np.array([
0.4962897,
0.0037103, # Small weight due to using great circle lines
0.4962897,
0.0037103, # Small weight due to using great circle lines
0.25484249,
0.24076863,
0.25484249,
0.24076863,
])
expected_weights = scipy.sparse.csr_matrix(
(weights_dict["weights"], (weights_dict["row_dst"],
weights_dict["col_src"])))
assert np.allclose(result.toarray(), expected_weights.toarray())
