Exemple #1
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    def test_basic(self):
        """Test that the __init__ method configures the plugin as expected."""

        plugin = PrecipPhaseProbability()
        self.assertTrue(
            plugin.percentile_plugin is GeneratePercentilesFromANeighbourhood)
        self.assertAlmostEqual(plugin.radius, 10000.0)
Exemple #2
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    def setUp(self):
        """Set up orography cube (as zeros) and falling_phase_level cube with
        multiple realizations designed to return snow, sleet and rain. The
        middle realization gives both not-snow and not-rain because both the
        20th percentile is <= zero and the 80th percentile is >= zero."""

        # cubes for testing have a grid-length of 2000m.
        self.plugin = PrecipPhaseProbability(radius=2100.0)
        self.mandatory_attributes = {
            "title": "mandatory title",
            "source": "mandatory_source",
            "institution": "mandatory_institution",
        }

        data = np.zeros((3, 3), dtype=np.float32)

        orog_cube = set_up_variable_cube(
            data,
            name="surface_altitude",
            units="m",
            spatial_grid="equalarea",
            attributes=self.mandatory_attributes,
        )

        falling_level_data = np.array(
            [
                [[-1, -1, -1], [-1, -1, -1], [-1, -1, -1]],
                [[0, -1, 0], [0, 1, 0], [0, -1, 0]],
                [[1, 1, 1], [1, 1, 1], [1, 1, 1]],
            ],
            dtype=np.float32,
        )

        falling_level_cube = set_up_variable_cube(
            falling_level_data,
            units="m",
            spatial_grid="equalarea",
            name="altitude_of_snow_falling_level",
            realizations=[0, 1, 2],
            attributes=self.mandatory_attributes,
        )

        self.cubes = iris.cube.CubeList([falling_level_cube, orog_cube])
        self.expected_template = np.zeros((3, 3, 3), dtype=np.int8)
Exemple #3
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    def setUp(self):
        """Set up orography cube (as zeros) and falling_phase_level cube with
        multiple realizations designed to return snow, sleet and rain. The
        middle realization gives both not-snow and not-rain because both the
        20th percentile is <= zero and the 80th percentile is >= zero."""

        # cubes for testing have a grid-length of 333333m.
        self.plugin = PrecipPhaseProbability(radius=350000.)
        self.mandatory_attributes = {
            'title': 'mandatory title',
            'source': 'mandatory_source',
            'institution': 'mandatory_institution'
        }

        data = np.zeros((3, 3), dtype=np.float32)

        orog_cube = set_up_variable_cube(data,
                                         name='surface_altitude',
                                         units='m',
                                         spatial_grid='equalarea',
                                         attributes=self.mandatory_attributes)

        falling_level_data = np.array(
            [[[-1, -1, -1], [-1, -1, -1], [-1, -1, -1]],
             [[0, -1, 0], [0, 1, 0], [0, -1, 0]],
             [[1, 1, 1], [1, 1, 1], [1, 1, 1]]],
            dtype=np.float32)

        falling_level_cube = set_up_variable_cube(
            falling_level_data,
            units='m',
            spatial_grid='equalarea',
            name='altitude_of_snow_falling_level',
            realizations=[0, 1, 2],
            attributes=self.mandatory_attributes)

        self.cubes = iris.cube.CubeList([falling_level_cube, orog_cube])
Exemple #4
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def process(*cubes: cli.inputcube, radius: float = 10000.):
    """
    Converts a phase-change-level cube into the
    probability of a specific precipitation phase being found at the surface.

    Args:
        cubes (iris.cube.CubeList or list):
            Contains cubes of the altitude of the phase-change level (this
            can be snow->sleet, or sleet->rain) and the altitude of the
            orography. The name of the phase-change level cube must be
            either "altitude_of_snow_falling_level" or
            "altitude_of_rain_falling_level". The name of the orography
            cube must be "surface_altitude".
        radius (float):
            Neighbourhood radius from which 80th percentile is found (m)

    """
    from improver.psychrometric_calculations.precip_phase_probability import (
        PrecipPhaseProbability)
    from iris.cube import CubeList
    return PrecipPhaseProbability(radius=radius).process(CubeList(cubes))
class Test_process(IrisTest):
    """Test the PhaseChangeLevel processing works"""
    def setUp(self):
        """Set up orography cube (as zeros) and falling_phase_level cube with
        multiple realizations designed to return snow, sleet and rain. The
        middle realization gives both not-snow and not-rain because both the
        20th percentile is <= zero and the 80th percentile is >= zero."""

        # cubes for testing have a grid-length of 333333m.
        self.plugin = PrecipPhaseProbability(radius=350000.0)
        self.mandatory_attributes = {
            "title": "mandatory title",
            "source": "mandatory_source",
            "institution": "mandatory_institution",
        }

        data = np.zeros((3, 3), dtype=np.float32)

        orog_cube = set_up_variable_cube(
            data,
            name="surface_altitude",
            units="m",
            spatial_grid="equalarea",
            attributes=self.mandatory_attributes,
        )

        falling_level_data = np.array(
            [
                [[-1, -1, -1], [-1, -1, -1], [-1, -1, -1]],
                [[0, -1, 0], [0, 1, 0], [0, -1, 0]],
                [[1, 1, 1], [1, 1, 1], [1, 1, 1]],
            ],
            dtype=np.float32,
        )

        falling_level_cube = set_up_variable_cube(
            falling_level_data,
            units="m",
            spatial_grid="equalarea",
            name="altitude_of_snow_falling_level",
            realizations=[0, 1, 2],
            attributes=self.mandatory_attributes,
        )

        self.cubes = iris.cube.CubeList([falling_level_cube, orog_cube])

    def test_prob_snow(self):
        """Test that process returns a cube with the right name, units and
        values. In this instance the phase change is from snow to sleet."""
        result = self.plugin.process(self.cubes)
        expected = np.zeros((3, 3, 3), dtype=np.float32)
        expected[0] = 1.0
        self.assertIsInstance(result, iris.cube.Cube)
        self.assertEqual(result.name(), "probability_of_snow_at_surface")
        self.assertEqual(result.units, Unit("1"))
        self.assertDictEqual(result.attributes, self.mandatory_attributes)
        self.assertArrayAlmostEqual(result.data, expected)

    def test_prob_rain(self):
        """Test that process returns a cube with the right name, units and
        values. In this instance the phase change is from sleet to rain."""
        self.cubes[0].rename("altitude_of_rain_falling_level")
        result = self.plugin.process(self.cubes)
        expected = np.zeros((3, 3, 3), dtype=np.float32)
        expected[2] = 1.0
        self.assertIsInstance(result, iris.cube.Cube)
        self.assertEqual(result.name(), "probability_of_rain_at_surface")
        self.assertEqual(result.units, Unit("1"))
        self.assertArrayAlmostEqual(result.data, expected)

    def test_unit_conversion(self):
        """Test that process returns the same as test_prob_rain when the
        orography cube units are in feet."""
        self.cubes[1].units = Unit("feet")
        self.cubes[0].rename("altitude_of_rain_falling_level")
        result = self.plugin.process(self.cubes)
        expected = np.zeros((3, 3, 3), dtype=np.float32)
        expected[2] = 1.0
        self.assertIsInstance(result, iris.cube.Cube)
        self.assertEqual(result.name(), "probability_of_rain_at_surface")
        self.assertEqual(result.units, Unit("1"))
        self.assertArrayAlmostEqual(result.data, expected)

    def test_unit_synonyms(self):
        """Test that process returns the same as test_prob_rain when the
        orography cube units are "metres" (a synonym of "m")."""
        self.cubes[1].units = Unit("metres")
        self.cubes[0].rename("altitude_of_rain_falling_level")
        result = self.plugin.process(self.cubes)
        expected = np.zeros((3, 3, 3), dtype=np.float32)
        expected[2] = 1.0
        self.assertIsInstance(result, iris.cube.Cube)
        self.assertEqual(result.name(), "probability_of_rain_at_surface")
        self.assertEqual(result.units, Unit("1"))
        self.assertArrayAlmostEqual(result.data, expected)

    def test_bad_phase_cube(self):
        """Test that process raises an exception when the input phase cube is
        incorrectly named."""
        self.cubes[0].rename("altitude_of_kittens")
        msg = "Could not extract a rain or snow falling-level cube from"
        with self.assertRaisesRegex(ValueError, msg):
            self.plugin.process(self.cubes)

    def test_bad_orography_cube(self):
        """Test that process raises an exception when the input orography
        cube is incorrectly named."""
        self.cubes[1].rename("altitude_of_kittens")
        msg = "Could not extract surface_altitude cube from"
        with self.assertRaisesRegex(ValueError, msg):
            self.plugin.process(self.cubes)

    def test_bad_units(self):
        """Test that process raises an exception when the input cubes cannot
        be coerced into the same units."""
        self.cubes[1].units = Unit("seconds")
        msg = "Unable to convert from "
        with self.assertRaisesRegex(ValueError, msg):
            self.plugin.process(self.cubes)

    def test_spatial_mismatch(self):
        """Test that process raises an exception when the input cubes have
        different spatial coordinates."""
        self.cubes[1] = set_up_variable_cube(
            self.cubes[1].data,
            name="surface_altitude",
            units="m",
            spatial_grid="latlon",
            attributes=self.mandatory_attributes,
        )
        msg = "Spatial coords mismatch between"
        with self.assertRaisesRegex(ValueError, msg):
            self.plugin.process(self.cubes)