def check_call(self, mdtol=None):
# Check that `iris.analysis.AreaWeighted` correctly calls an
# `iris.analysis._area_weighted.AreaWeightedRegridder` object.
if mdtol is None:
area_weighted = AreaWeighted()
mdtol = 1
else:
area_weighted = AreaWeighted(mdtol=mdtol)
self.assertEqual(area_weighted.mdtol, mdtol)
with mock.patch("iris.analysis.AreaWeightedRegridder", return_value=mock.sentinel.regridder) as awr:
regridder = area_weighted.regridder(mock.sentinel.src, mock.sentinel.target)
awr.assert_called_once_with(mock.sentinel.src, mock.sentinel.target, mdtol=mdtol)
self.assertIs(regridder, mock.sentinel.regridder)
def test_regrid_area_w_real_start(self):
real_cube = self.cube.copy()
real_cube.data
# Regrid the cube onto the template.
out = real_cube.regrid(self.template_cube, AreaWeighted())
# Save the data
with self.temp_filename(suffix=".nc") as fname:
iris.save(out, fname)
def test_regrid_area_w_lazy(self):
# Regrid the cube onto the template.
out = self.cube.regrid(self.template_cube, AreaWeighted())
# Check data is still lazy
self.assertTrue(self.cube.has_lazy_data())
self.assertTrue(out.has_lazy_data())
# Save the data
with self.temp_filename(suffix=".nc") as fname:
iris.save(out, fname)
def check_call(self, mdtol=None):
# Check that `iris.analysis.AreaWeighted` correctly calls an
# `iris.analysis._area_weighted.AreaWeightedRegridder` object.
if mdtol is None:
area_weighted = AreaWeighted()
mdtol = 1
else:
area_weighted = AreaWeighted(mdtol=mdtol)
self.assertEqual(area_weighted.mdtol, mdtol)
with mock.patch('iris.analysis.AreaWeightedRegridder',
return_value=mock.sentinel.regridder) as awr:
regridder = area_weighted.regridder(mock.sentinel.src,
mock.sentinel.target)
awr.assert_called_once_with(mock.sentinel.src,
mock.sentinel.target,
mdtol=mdtol)
self.assertIs(regridder, mock.sentinel.regridder)
def test_regrid_area_w_lazy_chunked(self):
# Chunked data makes the regridder run repeatedly
self.cube.data = self.cube.lazy_data().rechunk((1, -1, -1))
# Regrid the cube onto the template.
out = self.cube.regrid(self.template_cube, AreaWeighted())
# Check data is still lazy
self.assertTrue(self.cube.has_lazy_data())
self.assertTrue(out.has_lazy_data())
# Save the data
with self.temp_filename(suffix=".nc") as fname:
iris.save(out, fname)
def setup(self) -> None:
# Prepare a cube and a template
cube_file_path = tests.get_data_path(
["NetCDF", "regrid", "regrid_xyt.nc"])
self.cube = iris.load_cube(cube_file_path)
# Prepare a tougher cube and chunk it
chunked_cube_file_path = tests.get_data_path(
["NetCDF", "regrid", "regrid_xyt.nc"])
self.chunked_cube = iris.load_cube(chunked_cube_file_path)
# Chunked data makes the regridder run repeatedly
self.cube.data = self.cube.lazy_data().rechunk((1, -1, -1))
template_file_path = tests.get_data_path(
["NetCDF", "regrid", "regrid_template_global_latlon.nc"])
self.template_cube = iris.load_cube(template_file_path)
# Prepare a regridding scheme
self.scheme_area_w = AreaWeighted()
# A cached stock of standard horizontal target grids.
_CACHE = dict()
# Supported point interpolation schemes.
POINT_INTERPOLATION_SCHEMES = {
'linear': Linear(extrapolation_mode='mask'),
'nearest': Nearest(extrapolation_mode='mask'),
}
# Supported horizontal regridding schemes.
HORIZONTAL_SCHEMES = {
'linear': Linear(extrapolation_mode='mask'),
'linear_extrapolate': Linear(extrapolation_mode='extrapolate'),
'nearest': Nearest(extrapolation_mode='mask'),
'area_weighted': AreaWeighted(),
'unstructured_nearest': UnstructuredNearest(),
}
# Supported vertical interpolation schemes.
VERTICAL_SCHEMES = ('linear', 'nearest',
'linear_horizontal_extrapolate_vertical',
'nearest_horizontal_extrapolate_vertical')
def parse_cell_spec(spec):
"""
Parse an MxN cell specification string.
Parameters
----------
def test_invalid_low_mdtol(self):
msg = "mdtol must be in range 0 - 1"
with self.assertRaisesRegex(ValueError, msg):
AreaWeighted(mdtol=-0.2)
def test_invalid_high_mdtol(self):
msg = 'mdtol must be in range 0 - 1'
with self.assertRaisesRegexp(ValueError, msg):
AreaWeighted(mdtol=1.2)
def setup(self):
# Prepare a cube and a regridding scheme.
file_path = tests.get_data_path(
["NetCDF", "global", "xyt", "SMALL_hires_wind_u_for_ipcc4.nc"])
self.cube = iris.load_cube(file_path)
self.scheme_area_w = AreaWeighted()
def time_regrid_area_w(self) -> None:
# Regrid the cube onto the template.
out = self.cube.regrid(self.template_cube, AreaWeighted())
# Realise the data
out.data