def test_sprog(
n_cascade_levels,
ar_order,
probmatching_method,
domain,
min_csi):
"""Tests SPROG nowcast."""
# inputs
precip_input, metadata = get_precipitation_fields(num_prev_files=2,
num_next_files=0,
return_raw=False,
metadata=True,
upscale=2000)
precip_input = precip_input.filled()
precip_obs = get_precipitation_fields(num_prev_files=0,
num_next_files=3,
return_raw=False,
upscale=2000)[1:, :, :]
precip_obs = precip_obs.filled()
# Retrieve motion field
pytest.importorskip("cv2")
oflow_method = motion.get_method("LK")
retrieved_motion = oflow_method(precip_input)
# Run nowcast
nowcast_method = nowcasts.get_method("sprog")
precip_forecast = nowcast_method(
precip_input,
retrieved_motion,
n_timesteps=3,
R_thr=metadata["threshold"],
n_cascade_levels=n_cascade_levels,
ar_order=ar_order,
probmatching_method=probmatching_method,
domain=domain,
)
# result
result = verification.det_cat_fct(
precip_forecast[-1],
precip_obs[-1],
thr=0.1,
scores="CSI")["CSI"]
print(f"got CSI={result:.1f}, required > {min_csi:.1f}")
assert result > min_csi
def test_sprog(
n_cascade_levels, ar_order, probmatching_method, domain, timesteps, min_csi
):
"""Tests SPROG nowcast."""
# inputs
precip_input, metadata = get_precipitation_fields(
num_prev_files=2,
num_next_files=0,
return_raw=False,
metadata=True,
upscale=2000,
)
precip_input = precip_input.filled()
precip_obs = get_precipitation_fields(
num_prev_files=0, num_next_files=3, return_raw=False, upscale=2000
)[1:, :, :]
precip_obs = precip_obs.filled()
pytest.importorskip("cv2")
oflow_method = motion.get_method("LK")
retrieved_motion = oflow_method(precip_input)
nowcast_method = nowcasts.get_method("sprog")
precip_forecast = nowcast_method(
precip_input,
retrieved_motion,
timesteps=timesteps,
R_thr=metadata["threshold"],
n_cascade_levels=n_cascade_levels,
ar_order=ar_order,
probmatching_method=probmatching_method,
domain=domain,
)
assert precip_forecast.ndim == 3
assert precip_forecast.shape[0] == (
timesteps if isinstance(timesteps, int) else len(timesteps)
)
result = verification.det_cat_fct(
precip_forecast[-1], precip_obs[-1], thr=0.1, scores="CSI"
)["CSI"]
assert result > min_csi, f"CSI={result:.1f}, required > {min_csi:.1f}"
def test_anvil_rainrate(n_cascade_levels, ar_order, ar_window_radius,
timesteps, min_csi):
"""Tests ANVIL nowcast using rain rate precipitation fields."""
# inputs
precip_input, metadata = get_precipitation_fields(
num_prev_files=4,
num_next_files=0,
return_raw=False,
metadata=True,
upscale=2000,
)
precip_input = precip_input.filled()
precip_obs = get_precipitation_fields(num_prev_files=0,
num_next_files=3,
return_raw=False,
upscale=2000)[1:, :, :]
precip_obs = precip_obs.filled()
pytest.importorskip("cv2")
oflow_method = motion.get_method("LK")
retrieved_motion = oflow_method(precip_input)
nowcast_method = nowcasts.get_method("anvil")
precip_forecast = nowcast_method(
precip_input[-(ar_order + 2):],
retrieved_motion,
timesteps=timesteps,
rainrate=None, # no R(VIL) conversion is done
n_cascade_levels=n_cascade_levels,
ar_order=ar_order,
ar_window_radius=ar_window_radius,
)
assert precip_forecast.ndim == 3
assert precip_forecast.shape[0] == (timesteps if isinstance(
timesteps, int) else len(timesteps))
result = verification.det_cat_fct(precip_forecast[-1],
precip_obs[-1],
thr=0.1,
scores="CSI")["CSI"]
assert result > min_csi, f"CSI={result:.2f}, required > {min_csi:.2f}"
def test_det_cat_fct(pred, obs, thr, scores, expected):
"""Test the det_cat_fct."""
assert_array_almost_equal(
list(det_cat_fct(pred, obs, thr, scores).values()), expected)
