def test_add_srf(modes_all_single):
if eradiate.mode().has_flags(ModeFlags.ANY_MONO):
spectral_cfg = {"wavelengths": [550.0]}
elif eradiate.mode().has_flags(ModeFlags.ANY_CKD):
spectral_cfg = {"bins": ["550"]}
else:
pytest.skip(f"Please add test for '{eradiate.mode().id}' mode")
exp = OneDimExperiment(
atmosphere=None,
measures=MultiDistantMeasure.from_viewing_angles(
zeniths=[-60, -45, 0, 45, 60],
azimuths=0.0,
spp=1,
spectral_cfg=spectral_cfg,
),
)
exp.process()
measure = exp.measures[0]
# Apply basic post-processing
values = Pipeline([
Gather(var="radiance"),
AggregateCKDQuad(var="radiance", measure=measure)
]).transform(measure.results)
step = AddSpectralResponseFunction(measure=measure)
result = step.transform(values)
# The spectral response function is added to the dataset as a data variable
assert "srf" in result.data_vars
# Its only dimension is wavelength
assert set(result.srf.dims) == {"srf_w"}
def test_ckd_basic(modes_all_ckd):
"""
CKD correctness check
=====================
We check for correctness when using CKD modes with atmosphere-free scenes.
This test is designed to check that the CKD infrastructure
(preprocessing, spectral loop, postprocessing) works.
"""
# Configure experiment, run and postprocess results
exp = OneDimExperiment(
atmosphere=None,
surface=LambertianSurface(reflectance=1.0),
measures=[
MultiDistantMeasure.from_viewing_angles(
zeniths=np.arange(-60, 61, 5) * ureg.deg,
azimuths=0.0 * ureg.deg,
spectral_cfg={
"bin_set": "10nm",
"bins": [
"550",
"560",
"570",
"510",
], # We specify bins in arbitrary order on purpose
},
)
],
)
exp.run()
# Reflectance is uniform, equal to 1
assert np.allclose(exp.results["measure"].data_vars["brf"], 1.0)
def test_add_viewing_angles(mode_mono, measure_type, expected_zenith,
expected_azimuth):
# Initialise test data
if measure_type == "multi_distant-nohplane":
measure = MultiDistantMeasure.from_viewing_angles(
zeniths=[-60, -45, 0, 45, 60],
azimuths=0.0,
auto_hplane=False,
spp=1,
)
elif measure_type == "multi_distant-hplane":
measure = MultiDistantMeasure.from_viewing_angles(
zeniths=[-60, -45, 0, 45, 60],
azimuths=0.0,
auto_hplane=True,
spp=1,
)
elif measure_type == "hemispherical_distant":
measure = HemisphericalDistantMeasure(
film_resolution=(2, 2),
spp=1,
)
else:
assert False
exp = OneDimExperiment(atmosphere=None, measures=measure)
exp.process()
measure = exp.measures[0]
# Apply basic post-processing
values = Gather(var="radiance").transform(measure.results)
step = AddViewingAngles(measure=measure)
result = step.transform(values)
# Produced dataset has viewing angle coordinates
assert "vza" in result.coords
assert "vaa" in result.coords
# Viewing angles are set to appropriate values
assert np.allclose(expected_zenith, result.coords["vza"].values.squeeze())
assert np.allclose(expected_azimuth, result.coords["vaa"].values.squeeze())
def test_apply_spectral_response_function_transform(mode_id, spectral_cfg):
"""
Unit tests for ApplySpectralResponseFunction.transform().
"""
# Prepare basic data
eradiate.set_mode(mode_id)
exp = OneDimExperiment(
atmosphere=None,
measures=MultiDistantMeasure.from_viewing_angles(
id="measure",
zeniths=[-60, -45, 0, 45, 60],
azimuths=0.0,
spp=1,
spectral_cfg=spectral_cfg,
),
)
measure = exp.measures[0]
exp.process(measure)
# Apply first steps of post-processing
pipeline = exp.pipeline(measure)
values = pipeline.transform(measure.results, stop_after="add_viewing_angles")
# Apply tested pipeline step
step = ApplySpectralResponseFunction(measure=measure, vars=["radiance"])
if eradiate.mode().has_flags(ModeFlags.ANY_MONO):
# In mono modes, the dataset produced by previous steps is missing
# bin data required for the step to run successfully
with pytest.raises(ValueError):
step.transform(values)
return
# In binned modes, computation goes through
result = step.transform(values)
# The step adds a SRF-weighted variable
assert "radiance_srf" in result.data_vars
assert np.all(result.radiance_srf > 0.0)