def test_time(self):
"""Test output time coordinates are as expected"""
current_time = self.cubes[1].coord("time").points[0]
result = generate_advection_velocities_from_winds(
self.cubes, self.steering_flow, self.orogenh)
for cube in result:
self.assertIsInstance(cube, iris.cube.Cube)
self.assertEqual(cube.coord("time").points[0], current_time)
def test_basic(self):
"""Test function returns a cubelist with the expected components"""
result = generate_advection_velocities_from_winds(
self.cubes, self.steering_flow, self.orogenh
)
self.assertIsInstance(result, iris.cube.CubeList)
self.assertEqual(result[0].name(), "precipitation_advection_x_velocity")
self.assertEqual(result[1].name(), "precipitation_advection_y_velocity")
def test_input_sort(self):
"""Test output time coordinates are correct if the inputs are in the wrong
order"""
current_time = self.cubes[1].coord("time").points[0]
reversed_cubelist = iris.cube.CubeList([self.cubes[1], self.cubes[0]])
result = generate_advection_velocities_from_winds(
reversed_cubelist, self.steering_flow, self.orogenh)
for cube in result:
self.assertIsInstance(cube, iris.cube.Cube)
self.assertEqual(cube.coord("time").points[0], current_time)
def process(
steering_flow: inputflow,
orographic_enhancement: cli.inputcube,
*cubes: cli.inputcube,
):
"""Calculate optical flow components as perturbations from the model
steering flow. Advects the older of the two input radar observations to
the validity time of the newer observation, then calculates the velocity
required to adjust this forecast to match the observation. Sums the
steering flow and perturbation values to give advection components for
extrapolation nowcasting.
Args:
steering_flow (iris.cube.CubeList):
Model steering flow as u- and v- wind components. These must
have names: "grid_eastward_wind" and "grid_northward_wind".
orographic_enhancement (iris.cube.Cube):
Cube containing the orographic enhancement fields.
cubes (tuple of iris.cube.Cube):
Two radar precipitation observation cubes.
Returns:
iris.cube.CubeList:
List of u- and v- advection velocities
"""
from iris.cube import CubeList
from improver.nowcasting.optical_flow import (
generate_advection_velocities_from_winds,
)
if len(cubes) != 2:
raise ValueError("Expected 2 radar cubes - got {}".format(len(cubes)))
advection_velocities = generate_advection_velocities_from_winds(
CubeList(cubes), steering_flow, orographic_enhancement
)
return advection_velocities
