def test_distinct_xy_bounds_pole(self):
# is UserWarning issued for out-of-bounds? results will be unexpected!
cube = stock.simple_pp()
cube = cube[:4, :4]
lon = cube.coord('longitude')
lat = cube.coord('latitude')
lon.guess_bounds()
lat.guess_bounds()
from iris.util import regular_step
quarter = abs(regular_step(lon) * regular_step(lat) * 0.25)
half = abs(regular_step(lon) * regular_step(lat) * 0.5)
top_cell_half = abs(regular_step(lon) * (90 - lat.bounds[0, 1]) * 0.5)
minx = 3.7499990463256836
maxx = 7.499998092651367
miny = 84.99998474121094
maxy = 99.99998474121094
geometry = shapely.geometry.box(minx, miny, maxx, maxy)
# see http://stackoverflow.com/a/3892301 to assert warnings
with warnings.catch_warnings(record=True) as w:
warnings.simplefilter("always") # always trigger all warnings
weights = geometry_area_weights(cube, geometry)
self.assertEqual(
str(w[-1].message), "The geometry exceeds the "
"cube's y dimension at the upper end.")
self.assertTrue(issubclass(w[-1].category, UserWarning))
target = np.array([[0, top_cell_half, top_cell_half, 0],
[0, half, half, 0], [0, quarter, quarter, 0],
[0, 0, 0, 0]])
self.assertTrue(np.allclose(weights, target))
def test_distinct_xy_bounds(self):
# cases where geometry bnds are outside cube bnds correctly handled?
cube = stock.simple_pp()
cube = cube[:4, :4]
lon = cube.coord('longitude')
lat = cube.coord('latitude')
lon.guess_bounds()
lat.guess_bounds()
from iris.fileformats.rules import regular_step
quarter = abs(regular_step(lon) * regular_step(lat) * 0.25)
half = abs(regular_step(lon) * regular_step(lat) * 0.5)
full = abs(regular_step(lon) * regular_step(lat))
minx = 3.7499990463256836
maxx = 13.12499619
maxx_overshoot = 15.
miny = 84.99998474121094
maxy = 89.99998474121094
geometry = shapely.geometry.box(minx, miny, maxx, maxy)
geometry_overshoot = shapely.geometry.box(minx, miny, maxx_overshoot,
maxy)
weights = geometry_area_weights(cube, geometry)
weights_overshoot = geometry_area_weights(cube, geometry_overshoot)
target = np.array([
[0, quarter, half, half],
[0, half, full, full],
[0, quarter, half, half],
[0, 0, 0, 0]])
self.assertTrue(np.allclose(weights, target))
self.assertTrue(np.allclose(weights_overshoot, target))
def test_distinct_xy_bounds_pole(self):
# is UserWarning issued for out-of-bounds? results will be unexpected!
cube = stock.simple_pp()
cube = cube[:4, :4]
lon = cube.coord('longitude')
lat = cube.coord('latitude')
lon.guess_bounds()
lat.guess_bounds()
from iris.fileformats.rules import regular_step
quarter = abs(regular_step(lon) * regular_step(lat) * 0.25)
half = abs(regular_step(lon) * regular_step(lat) * 0.5)
minx = 3.7499990463256836
maxx = 7.499998092651367
miny = 84.99998474121094
maxy = 99.99998474121094
geometry = shapely.geometry.box(minx, miny, maxx, maxy)
# see http://stackoverflow.com/a/3892301 to assert warnings
with warnings.catch_warnings(record=True) as w:
warnings.simplefilter("always") # always trigger all warnings
weights = geometry_area_weights(cube, geometry)
self.assertEqual(str(w[-1].message), "The geometry exceeds the "
"cube's y dimension at the upper end.")
self.assertTrue(issubclass(w[-1].category, UserWarning))
target = np.array([
[0, half, half, 0],
[0, half, half, 0],
[0, quarter, quarter, 0],
[0, 0, 0, 0]])
self.assertTrue(np.allclose(weights, target))
def test_distinct_xy_bounds(self):
# cases where geometry bnds are outside cube bnds correctly handled?
cube = stock.simple_pp()
cube = cube[:4, :4]
lon = cube.coord('longitude')
lat = cube.coord('latitude')
lon.guess_bounds()
lat.guess_bounds()
from iris.util import regular_step
quarter = abs(regular_step(lon) * regular_step(lat) * 0.25)
half = abs(regular_step(lon) * regular_step(lat) * 0.5)
full = abs(regular_step(lon) * regular_step(lat))
minx = 3.7499990463256836
maxx = 13.12499619
maxx_overshoot = 15.
miny = 84.99998474121094
maxy = 89.99998474121094
geometry = shapely.geometry.box(minx, miny, maxx, maxy)
geometry_overshoot = shapely.geometry.box(minx, miny, maxx_overshoot,
maxy)
weights = geometry_area_weights(cube, geometry)
weights_overshoot = geometry_area_weights(cube, geometry_overshoot)
target = np.array([[0, quarter, half, half], [0, half, full, full],
[0, quarter, half, half], [0, 0, 0, 0]])
self.assertTrue(np.allclose(weights, target))
self.assertTrue(np.allclose(weights_overshoot, target))
def test_no_realization(self):
cube = stock.simple_pp()
grib = mock.Mock()
mock_gribapi = mock.Mock(spec=gribapi)
with mock.patch(GRIB_API, mock_gribapi):
identification(cube, grib)
mock_gribapi.assert_has_calls([mock.call.grib_set_long(grib, "typeOfProcessedData", 2)])
def test_no_realization(self):
cube = stock.simple_pp()
grib = mock.Mock()
mock_gribapi = mock.Mock(spec=gribapi)
with mock.patch(GRIB_API, mock_gribapi):
identification(cube, grib)
mock_gribapi.assert_has_calls(
[mock.call.grib_set_long(grib, "typeOfProcessedData", 2)])
def test_365_calendar_export(self):
# test for 365 day calendar export
cube = stock.simple_pp()
new_unit = cf_units.Unit("hours since 1970-01-01 00:00:00", calendar=cf_units.CALENDAR_365_DAY)
cube.coord("time").units = new_unit
pp_field = mock.MagicMock(spec=PPField3)
iris.fileformats.pp._ensure_save_rules_loaded()
iris.fileformats.pp._save_rules.verify(cube, pp_field)
self.assertEqual(pp_field.lbtim.ic, 4)
def test_365_calendar_export(self):
# test for 365 day calendar export
cube = stock.simple_pp()
new_unit = iris.unit.Unit('hours since 1970-01-01 00:00:00',
calendar=iris.unit.CALENDAR_365_DAY)
cube.coord('time').units = new_unit
pp_field = mock.MagicMock(spec=PPField3)
iris.fileformats.pp._ensure_save_rules_loaded()
iris.fileformats.pp._save_rules.verify(cube, pp_field)
self.assertEqual(pp_field.lbtim.ic, 4)
def test_365_calendar_export(self):
# test for 365 day calendar export
cube = stock.simple_pp()
new_unit = cf_units.Unit('hours since 1970-01-01 00:00:00',
calendar=cf_units.CALENDAR_365_DAY)
cube.coord('time').units = new_unit
# Add an extra "fill_value" property, as used by the save rules.
cube.fill_value = None
pp_field = mock.MagicMock(spec=PPField3)
iris.fileformats.pp_save_rules.verify(cube, pp_field)
self.assertEqual(pp_field.lbtim.ic, 4)
def test_365_calendar_export(self):
# test for 365 day calendar export
cube = stock.simple_pp()
new_unit = cf_units.Unit('hours since 1970-01-01 00:00:00',
calendar=cf_units.CALENDAR_365_DAY)
cube.coord('time').units = new_unit
# Add an extra "fill_value" property, as used by the save rules.
cube.fill_value = None
pp_field = mock.MagicMock(spec=PPField3)
iris.fileformats.pp_save_rules.verify(cube, pp_field)
self.assertEqual(pp_field.lbtim.ic, 4)
def test_realization_n(self):
cube = stock.simple_pp()
realisation = iris.coords.AuxCoord((2,), standard_name="realization", units="1")
cube.add_aux_coord(realisation)
grib = mock.Mock()
mock_gribapi = mock.Mock(spec=gribapi)
with mock.patch(GRIB_API, mock_gribapi):
identification(cube, grib)
mock_gribapi.assert_has_calls([mock.call.grib_set_long(grib, "typeOfProcessedData", 4)])
def test_realization_n(self):
cube = stock.simple_pp()
realisation = iris.coords.AuxCoord((2,), standard_name='realization',
units='1')
cube.add_aux_coord(realisation)
grib = mock.Mock()
mock_gribapi = mock.Mock(spec=gribapi)
with mock.patch(GRIB_API, mock_gribapi):
identification(cube, grib)
mock_gribapi.assert_has_calls(
[mock.call.grib_set_long(grib, "typeOfProcessedData", 4)])
def test_pp_append_singles(self):
# Test pp append saving - single cubes.
# load 2 arrays of >2D cubes
cube = stock.simple_pp()
reference_txt_path = tests.get_result_path(('cube_to_pp', 'append_single.txt'))
with self.cube_save_test(reference_txt_path, reference_cubes=[cube, cube]) as temp_pp_path:
iris.save(cube, temp_pp_path) # Create file
iris.save(cube, temp_pp_path, append=True) # Append to file
reference_txt_path = tests.get_result_path(('cube_to_pp', 'replace_single.txt'))
with self.cube_save_test(reference_txt_path, reference_cubes=cube) as temp_pp_path:
iris.save(cube, temp_pp_path) # Create file
iris.save(cube, temp_pp_path) # Replace file
def test_pp_append_singles(self):
# Test pp append saving - single cubes.
# load 2 arrays of >2D cubes
cube = stock.simple_pp()
reference_txt_path = tests.get_result_path(('cube_to_pp', 'append_single.txt'))
with self.cube_save_test(reference_txt_path, reference_cubes=[cube, cube]) as temp_pp_path:
iris.save(cube, temp_pp_path) # Create file
iris.save(cube, temp_pp_path, append=True) # Append to file
reference_txt_path = tests.get_result_path(('cube_to_pp', 'replace_single.txt'))
with self.cube_save_test(reference_txt_path, reference_cubes=cube) as temp_pp_path:
iris.save(cube, temp_pp_path) # Create file
iris.save(cube, temp_pp_path) # Replace file
def test_distinct_xy(self):
cube = stock.simple_pp()
cube = cube[:4, :4]
lon = cube.coord('longitude')
lat = cube.coord('latitude')
lon.guess_bounds()
lat.guess_bounds()
from iris.util import regular_step
quarter = abs(regular_step(lon) * regular_step(lat) * 0.25)
half = abs(regular_step(lon) * regular_step(lat) * 0.5)
minx = 3.7499990463256836
maxx = 7.499998092651367
miny = 84.99998474121094
maxy = 89.99998474121094
geometry = shapely.geometry.box(minx, miny, maxx, maxy)
weights = geometry_area_weights(cube, geometry)
target = np.array([[0, quarter, quarter, 0], [0, half, half, 0],
[0, quarter, quarter, 0], [0, 0, 0, 0]])
self.assertTrue(np.allclose(weights, target))
def test_distinct_xy(self):
cube = stock.simple_pp()
cube = cube[:4, :4]
lon = cube.coord('longitude')
lat = cube.coord('latitude')
lon.guess_bounds()
lat.guess_bounds()
from iris.fileformats.rules import regular_step
quarter = abs(regular_step(lon) * regular_step(lat) * 0.25)
half = abs(regular_step(lon) * regular_step(lat) * 0.5)
minx = 3.7499990463256836
maxx = 7.499998092651367
miny = 84.99998474121094
maxy = 89.99998474121094
geometry = shapely.geometry.box(minx, miny, maxx, maxy)
weights = geometry_area_weights(cube, geometry)
target = np.array([
[0, quarter, quarter, 0],
[0, half, half, 0],
[0, quarter, quarter, 0],
[0, 0, 0, 0]])
self.assertTrue(np.allclose(weights, target))
def setUp(self):
# Load some data from a file so that we have some deferred data.
self.cube = stock.simple_pp()
def setUp(self):
# Load some data from a file so that we have some deferred data.
self.cube = stock.simple_pp()
