class Test__modify_first_guess(IrisTest):
"""Test the _modify_first_guess method."""
def setUp(self):
"""Create test cubes and plugin instance.
The cube coordinates look like this:
Dimension coordinates:
projection_y_coordinate: 3;
projection_x_coordinate: 3;
Scalar coordinates:
time: 2015-11-23 07:00:00
forecast_reference_time: 2015-11-23 07:00:00
forecast_period: 0 seconds
self.cube:
Metadata describes the nowcast lightning fields to be calculated.
forecast_period: 0 seconds (simulates nowcast data)
self.fg_cube:
Has 4 hour forecast period, to test impact at lr2
self.ltng_cube:
forecast_period: 0 seconds (simulates nowcast data)
self.precip_cube:
Has extra coordinate of length(3) "threshold" containing
points [0.5, 7., 35.] mm h-1.
self.vii_cube:
Has extra coordinate of length(3) "threshold" containing
points [0.5, 1., 2.] kg m-2.
"""
(
self.cube,
self.fg_cube,
self.ltng_cube,
self.precip_cube,
self.vii_cube,
) = set_up_lightning_test_cubes()
self.plugin = Plugin()
def test_basic(self):
"""Test that the method returns the expected cube type"""
result = self.plugin._modify_first_guess(self.cube, self.fg_cube,
self.ltng_cube,
self.precip_cube,
self.vii_cube)
self.assertIsInstance(result, Cube)
def test_input_with_vii(self):
"""Test that the method does not modify the input cubes."""
cube_a = self.cube.copy()
cube_b = self.fg_cube.copy()
cube_c = self.ltng_cube.copy()
cube_d = self.precip_cube.copy()
cube_e = self.vii_cube.copy()
self.plugin._modify_first_guess(cube_a, cube_b, cube_c, cube_d, cube_e)
self.assertArrayAlmostEqual(cube_a.data, self.cube.data)
self.assertArrayAlmostEqual(cube_b.data, self.fg_cube.data)
self.assertArrayAlmostEqual(cube_c.data, self.ltng_cube.data)
self.assertArrayAlmostEqual(cube_d.data, self.precip_cube.data)
self.assertArrayAlmostEqual(cube_e.data, self.vii_cube.data)
def test_missing_lightning(self):
"""Test that the method raises an error if the lightning cube doesn't
match the meta-data cube time coordinate."""
self.ltng_cube.coord("time").points = [1.0]
msg = "No matching lightning cube for"
with self.assertRaisesRegex(ConstraintMismatchError, msg):
self.plugin._modify_first_guess(self.cube, self.fg_cube,
self.ltng_cube, self.precip_cube,
None)
def test_missing_first_guess(self):
"""Test that the method raises an error if the first-guess cube doesn't
match the meta-data cube time coordinate."""
self.fg_cube.coord("time").points = [1.0]
msg = "is not available within the input cube within the " "allowed difference"
with self.assertRaisesRegex(ValueError, msg):
self.plugin._modify_first_guess(self.cube, self.fg_cube,
self.ltng_cube, self.precip_cube,
None)
def test_cube_has_no_time_coord(self):
"""Test that the method raises an error if the meta-data cube has no
time coordinate."""
self.cube.remove_coord("time")
msg = "Expected to find exactly 1 time coordinate, but found none."
with self.assertRaisesRegex(CoordinateNotFoundError, msg):
self.plugin._modify_first_guess(self.cube, self.fg_cube,
self.ltng_cube, self.precip_cube,
None)
def test_precip_zero(self):
"""Test that apply_precip is being called"""
# Set lightning data to "no-data" so it has a Null impact
self.ltng_cube.data = np.full_like(self.ltng_cube.data, -1.0)
# No halo - we're only testing this method.
expected = self.fg_cube.copy()
# expected.data contains all ones except:
expected.data[1, 1] = 0.0067
result = self.plugin._modify_first_guess(self.cube, self.fg_cube,
self.ltng_cube,
self.precip_cube, None)
self.assertArrayAlmostEqual(result.data, expected.data)
def test_vii_large(self):
"""Test that ApplyIce is being called"""
# Set lightning data to zero so it has a Null impact
self.vii_cube.data[:, 1, 1] = 1.0
self.ltng_cube.data[1, 1] = -1.0
self.fg_cube.data[1, 1] = 0.0
# No halo - we're only testing this method.
expected = self.fg_cube.copy()
# expected.data contains all ones except:
expected.data[1, 1] = 0.9
result = self.plugin._modify_first_guess(self.cube, self.fg_cube,
self.ltng_cube,
self.precip_cube,
self.vii_cube)
self.assertArrayAlmostEqual(result.data, expected.data)
def test_null(self):
"""Test that large precip probs and -1 lrates have no impact"""
# Set prob(precip) data for lowest threshold to to 0.1, the highest
# value that has no impact.
self.precip_cube.data[0, 1, 1] = 0.1
# Set lightning data to -1 so it has a Null impact
self.ltng_cube.data = np.full_like(self.ltng_cube.data, -1.0)
# No halo - we're only testing this method.
expected = self.fg_cube.copy()
# expected.data should be an unchanged copy of fg_cube.
result = self.plugin._modify_first_guess(self.cube, self.fg_cube,
self.ltng_cube,
self.precip_cube, None)
self.assertArrayAlmostEqual(result.data, expected.data)
def test_lrate_large(self):
"""Test that large lightning rates increase zero lightning risk"""
expected = self.fg_cube.copy()
# expected.data contains all ones
# Set prob(precip) data for lowest threshold to to 1., so it has a Null
# impact when lightning is present.
self.precip_cube.data[0, 1, 1] = 1.0
# Set first-guess data zero point that will be increased
self.fg_cube.data[1, 1] = 0.0
# No halo - we're only testing this method.
result = self.plugin._modify_first_guess(self.cube, self.fg_cube,
self.ltng_cube,
self.precip_cube, None)
self.assertArrayAlmostEqual(result.data, expected.data)
def test_lrate_large_shortfc(self):
"""Test that nearly-large lightning rates increases zero lightning risk
when forecast_period is non-zero"""
expected = self.fg_cube.copy()
# expected.data contains all ones
# Set precip data to 1. so it has a Null impact
# Set prob(precip) data for lowest threshold to to 1., so it has a Null
# impact when lightning is present.
self.precip_cube.data[0, 1, 1] = 1.0
# Test the impact of the lightning-rate function.
# A highish lightning value at one-hour lead time isn't high enough to
# get to the high lightning category.
self.ltng_cube.data[1, 1] = 0.8
self.cube.coord("forecast_period").points = [3600.0] # seconds
# Set first-guess data zero point that will be increased
self.fg_cube.data[1, 1] = 0.0
# This time, lightning probability increases only to 0.25, not 1.
expected.data[1, 1] = 0.25
# No halo - we're only testing this method.
result = self.plugin._modify_first_guess(self.cube, self.fg_cube,
self.ltng_cube,
self.precip_cube, None)
self.assertArrayAlmostEqual(result.data, expected.data)
def test_lrate_large_null(self):
"""Test that large lightning rates do not increase high lightning
risk"""
expected = self.fg_cube.copy()
# expected.data contains all ones
# Set precip data to 1. so it has a Null impact
# Set prob(precip) data for lowest threshold to to 1., so it has a Null
# impact when lightning is present.
self.precip_cube.data[0, 1, 1] = 1.0
# Set first-guess data zero point that will be increased
self.fg_cube.data[1, 1] = 1.0
# No halo - we're only testing this method.
result = self.plugin._modify_first_guess(self.cube, self.fg_cube,
self.ltng_cube,
self.precip_cube, None)
self.assertArrayAlmostEqual(result.data, expected.data)
def test_lrate_small(self):
"""Test that lightning nearby (encoded as lightning rate zero)
increases lightning risk at point"""
# Set prob(precip) data for lowest threshold to to 1., so it has a Null
# impact when lightning is present.
self.precip_cube.data[0, 1, 1] = 1.0
# Set lightning data to zero to represent the data halo
self.ltng_cube.data[1, 1] = 0.0
# Set first-guess data zero point that will be increased
self.fg_cube.data[1, 1] = 0.0
# No halo - we're only testing this method.
expected = self.fg_cube.copy()
# expected.data contains all ones except:
expected.data[1, 1] = 0.25
result = self.plugin._modify_first_guess(self.cube, self.fg_cube,
self.ltng_cube,
self.precip_cube, None)
self.assertArrayAlmostEqual(result.data, expected.data)
class Test__modify_first_guess(IrisTest):
"""Test the _modify_first_guess method."""
def setUp(self):
"""Create cubes with a single zero prob(precip) point.
The cubes look like this:
precipitation_amount / (kg m^-2)
Dimension coordinates:
time: 1;
projection_y_coordinate: 3;
projection_x_coordinate: 3;
Auxiliary coordinates:
forecast_period (on time coord): 4.0 hours (simulates UM data)
Scalar coordinates:
forecast_reference_time: 2015-11-23 03:00:00
Data:
self.cube:
Describes the nowcast fields to be calculated.
forecast_period (on time coord): 0.0 hours (simulates nowcast data)
All points contain float(1.) except the
zero point [0, 1, 1] which is float(0.)
self.fg_cube:
All points contain float(1.)
self.ltng_cube:
forecast_period (on time coord): 0.0 hours (simulates nowcast data)
All points contain float(1.)
self.precip_cube:
With extra coordinate of length(3) "threshold" containing
points [0.5, 7., 35.] mm hr-1.
All points contain float(1.) except the
zero point [0, 0, 1, 1] which is float(0.)
and [1:, 0, ...] which are float(0.)
self.vii_cube:
With extra coordinate of length(3) "threshold" containing
points [0.5, 1., 2.] kg m^-2.
forecast_period (on time coord): 0.0 hours (simulates nowcast data)
Time and forecast_period dimensions "sqeezed" to be Scalar coords.
All points contain float(0.)
"""
self.cube = add_forecast_reference_time_and_forecast_period(
set_up_cube_with_no_realizations(zero_point_indices=((0, 1, 1), ),
num_grid_points=3),
fp_point=0.0)
self.fg_cube = add_forecast_reference_time_and_forecast_period(
set_up_cube_with_no_realizations(zero_point_indices=[],
num_grid_points=3))
self.ltng_cube = add_forecast_reference_time_and_forecast_period(
set_up_cube_with_no_realizations(zero_point_indices=[],
num_grid_points=3),
fp_point=0.0)
self.precip_cube = (add_forecast_reference_time_and_forecast_period(
set_up_cube(num_realization_points=3,
zero_point_indices=((0, 1, 1), ),
num_grid_points=3),
fp_point=0.0))
threshold_coord = self.precip_cube.coord('realization')
threshold_coord.points = [0.5, 7.0, 35.0]
threshold_coord.rename('threshold')
threshold_coord.units = cf_units.Unit('mm hr-1')
self.precip_cube.data[1:, 0, ...] = 0.
# iris.util.queeze is applied here to demote the singular coord "time"
# to a scalar coord.
self.vii_cube = squeeze(
add_forecast_reference_time_and_forecast_period(set_up_cube(
num_realization_points=3,
zero_point_indices=[],
num_grid_points=3),
fp_point=0.0))
threshold_coord = self.vii_cube.coord('realization')
threshold_coord.points = [0.5, 1.0, 2.0]
threshold_coord.rename('threshold')
threshold_coord.units = cf_units.Unit('kg m^-2')
self.vii_cube.data = np.zeros_like(self.vii_cube.data)
self.plugin = Plugin()
def test_basic(self):
"""Test that the method returns the expected cube type"""
result = self.plugin._modify_first_guess(self.cube, self.fg_cube,
self.ltng_cube,
self.precip_cube,
self.vii_cube)
self.assertIsInstance(result, Cube)
def test_input_with_vii(self):
"""Test that the method does not modify the input cubes."""
cube_a = self.cube.copy()
cube_b = self.fg_cube.copy()
cube_c = self.ltng_cube.copy()
cube_d = self.precip_cube.copy()
cube_e = self.vii_cube.copy()
self.plugin._modify_first_guess(cube_a, cube_b, cube_c, cube_d, cube_e)
self.assertArrayAlmostEqual(cube_a.data, self.cube.data)
self.assertArrayAlmostEqual(cube_b.data, self.fg_cube.data)
self.assertArrayAlmostEqual(cube_c.data, self.ltng_cube.data)
self.assertArrayAlmostEqual(cube_d.data, self.precip_cube.data)
self.assertArrayAlmostEqual(cube_e.data, self.vii_cube.data)
def test_missing_lightning(self):
"""Test that the method raises an error if the lightning cube doesn't
match the meta-data cube time coordinate."""
self.ltng_cube.coord('time').points = [1.0]
msg = ("No matching lightning cube for")
with self.assertRaisesRegex(ConstraintMismatchError, msg):
self.plugin._modify_first_guess(self.cube, self.fg_cube,
self.ltng_cube, self.precip_cube,
None)
def test_missing_first_guess(self):
"""Test that the method raises an error if the first-guess cube doesn't
match the meta-data cube time coordinate."""
self.fg_cube.coord('time').points = [1.0]
msg = ("is not available within the input cube within the "
"allowed difference")
with self.assertRaisesRegex(ValueError, msg):
self.plugin._modify_first_guess(self.cube, self.fg_cube,
self.ltng_cube, self.precip_cube,
None)
def test_cube_has_no_time_coord(self):
"""Test that the method raises an error if the meta-data cube has no
time coordinate."""
self.cube.remove_coord('time')
msg = ("Expected to find exactly 1 time coordinate, but found none.")
with self.assertRaisesRegex(CoordinateNotFoundError, msg):
self.plugin._modify_first_guess(self.cube, self.fg_cube,
self.ltng_cube, self.precip_cube,
None)
def test_precip_zero(self):
"""Test that apply_precip is being called"""
# Set lightning data to "no-data" so it has a Null impact
self.ltng_cube.data = np.full_like(self.ltng_cube.data, -1.)
# No halo - we're only testing this method.
expected = self.fg_cube.copy()
# expected.data contains all ones except:
expected.data[0, 1, 1] = 0.0067
result = self.plugin._modify_first_guess(self.cube, self.fg_cube,
self.ltng_cube,
self.precip_cube, None)
self.assertArrayAlmostEqual(result.data, expected.data)
def test_vii_large(self):
"""Test that ApplyIce is being called"""
# Set lightning data to zero so it has a Null impact
self.vii_cube.data[:, 1, 1] = 1.
self.ltng_cube.data[0, 1, 1] = -1.
self.fg_cube.data[0, 1, 1] = 0.
# No halo - we're only testing this method.
expected = self.fg_cube.copy()
# expected.data contains all ones except:
expected.data[0, 1, 1] = 0.9
result = self.plugin._modify_first_guess(self.cube, self.fg_cube,
self.ltng_cube,
self.precip_cube,
self.vii_cube)
self.assertArrayAlmostEqual(result.data, expected.data)
def test_null(self):
"""Test that large precip probs and -1 lrates have no impact"""
# Set prob(precip) data for lowest threshold to to 0.1, the highest
# value that has no impact.
self.precip_cube.data[0, 0, 1, 1] = 0.1
# Set lightning data to -1 so it has a Null impact
self.ltng_cube.data = np.full_like(self.ltng_cube.data, -1.)
# No halo - we're only testing this method.
expected = self.fg_cube.copy()
# expected.data should be an unchanged copy of fg_cube.
result = self.plugin._modify_first_guess(self.cube, self.fg_cube,
self.ltng_cube,
self.precip_cube, None)
self.assertArrayAlmostEqual(result.data, expected.data)
def test_lrate_large(self):
"""Test that large lightning rates increase zero lightning risk"""
expected = self.fg_cube.copy()
# expected.data contains all ones
# Set precip data to 1. so it has a Null impact
# Set prob(precip) data for lowest threshold to to 1., so it has a Null
# impact when lightning is present.
self.precip_cube.data[0, 0, 1, 1] = 1.
# Set first-guess data zero point that will be increased
self.fg_cube.data[0, 1, 1] = 0.
# No halo - we're only testing this method.
result = self.plugin._modify_first_guess(self.cube, self.fg_cube,
self.ltng_cube,
self.precip_cube, None)
self.assertArrayAlmostEqual(result.data, expected.data)
def test_lrate_large_shortfc(self):
"""Test that nearly-large lightning rates increases zero lightning risk
when forecast_period is non-zero"""
expected = self.fg_cube.copy()
# expected.data contains all ones
# Set precip data to 1. so it has a Null impact
# Set prob(precip) data for lowest threshold to to 1., so it has a Null
# impact when lightning is present.
self.precip_cube.data[0, 0, 1, 1] = 1.
# Test the impact of the lightning-rate function.
# A highish lightning value at one-hour lead time isn't high enough to
# get to the high lightning category.
self.ltng_cube.data[0, 1, 1] = 0.8
self.cube.coord('forecast_period').points = [1.] # hours
# Set first-guess data zero point that will be increased
self.fg_cube.data[0, 1, 1] = 0.
# This time, lightning probability increases only to 0.25, not 1.
expected.data[0, 1, 1] = 0.25
# No halo - we're only testing this method.
result = self.plugin._modify_first_guess(self.cube, self.fg_cube,
self.ltng_cube,
self.precip_cube, None)
self.assertArrayAlmostEqual(result.data, expected.data)
def test_lrate_large_null(self):
"""Test that large lightning rates do not increase high lightning
risk"""
expected = self.fg_cube.copy()
# expected.data contains all ones
# Set precip data to 1. so it has a Null impact
# Set prob(precip) data for lowest threshold to to 1., so it has a Null
# impact when lightning is present.
self.precip_cube.data[0, 0, 1, 1] = 1.
# Set first-guess data zero point that will be increased
self.fg_cube.data[0, 1, 1] = 1.
# No halo - we're only testing this method.
result = self.plugin._modify_first_guess(self.cube, self.fg_cube,
self.ltng_cube,
self.precip_cube, None)
self.assertArrayAlmostEqual(result.data, expected.data)
def test_lrate_small(self):
"""Test that lightning nearby (encoded as lightning rate zero)
increases lightning risk at point"""
# Set prob(precip) data for lowest threshold to to 1., so it has a Null
# impact when lightning is present.
self.precip_cube.data[0, 0, 1, 1] = 1.
# Set lightning data to zero to represent the data halo
self.ltng_cube.data[0, 1, 1] = 0.
# Set first-guess data zero point that will be increased
self.fg_cube.data[0, 1, 1] = 0.
# No halo - we're only testing this method.
expected = self.fg_cube.copy()
# expected.data contains all ones except:
expected.data[0, 1, 1] = 0.25
result = self.plugin._modify_first_guess(self.cube, self.fg_cube,
self.ltng_cube,
self.precip_cube, None)
self.assertArrayAlmostEqual(result.data, expected.data)
