def test_basic(self):
"""Test that the __repr__ returns the expected string."""
result = str(OrographicAlphas())
msg = ('<OrographicAlphas: min_alpha: {}; max_alpha: {}; '
'coefficient: {}; power: {}; '
'invert_alphas: {}>'.format(0.0, 1.0, 1, 1, True))
self.assertEqual(result, msg)
def setUp(self):
"""Set up cube & plugin"""
self.plugin = OrographicAlphas(min_alpha=0.3, max_alpha=0.5)
self.cube = set_up_cube()
self.gradient_x, self.gradient_y = \
DifferenceBetweenAdjacentGridSquares(gradient=True).process(
self.cube)
def process(orography: cli.inputcube,
*,
min_alpha: float = 0.0,
max_alpha: float = 1.0,
coefficient: float = 1.0,
power: float = 1.0,
invert_alphas=True):
"""Generate alpha smoothing parameters for recursive filtering based on
orography gradients.
Args:
orography (iris.cube.Cube):
A 2D field of orography for the grid to generate alphas for.
min_alpha (float):
The minimum value of alpha.
max_alpha (float):
The maximum value of alpha.
coefficient (float):
The coefficient for the alpha calculation.
power (float):
The power for the alpha equation.
invert_alphas (bool):
If True then the max and min alpha values will be swapped.
Returns:
iris.cube.CubeList:
Processed CubeList containing alpha_x and alpha_y cubes.
"""
from improver.utilities.ancillary_creation import OrographicAlphas
return OrographicAlphas(min_alpha, max_alpha, coefficient, power,
invert_alphas).process(orography)
def test_basic(self):
"""Test default attribute initialisation"""
result = OrographicAlphas()
self.assertTrue(result.invert_alphas)
self.assertEqual(result.min_alpha, 0.)
self.assertEqual(result.max_alpha, 1.)
self.assertEqual(result.coefficient, 1.)
self.assertEqual(result.power, 1.)
def setUp(self):
"""Set up cube & plugin"""
self.plugin = OrographicAlphas()
cube = set_up_cube()
self.cubelist = [cube, cube]
def setUp(self):
"""Set up cube & plugin"""
self.plugin = OrographicAlphas(coefficient=0.5, power=2.)
self.cube = set_up_cube()