def test_parameter_get_unit_works(name, product, unit, expect):
assert datamodel.Parameter(
description=name,
unit=unit,
dtype="f4",
dimension=["time"],
).get_unit(datamodel.is_temperature(product)) == expect
def test_parameter_l2type_works(para, expect):
assert datamodel.Parameter(
description=para,
unit=datamodel.Unit.product,
dtype=datamodel.DType.f4,
dimension=datamodel.Dimension.d2,
).l2type == expect
def test_parameter_get_description_works(para, product, expect):
assert datamodel.Parameter(
description=para,
unit="mm",
dtype="f4",
dimension=["time"],
).get_description(datamodel.is_temperature(product)) == expect
(1, 1.5, np.inf),
(1, 1.5, np.NINF),
(1, 1.5, np.NAN),
))
def test_l2i_is_not_valid_works(freqmode, residual, lmfactor):
assert not datamodel.L2i(GenerationTime=dt.datetime(2000, 1, 2, 3, 4, 5),
Residual=residual,
MinLmFactor=lmfactor,
FreqMode=freqmode).isvalid()
@pytest.mark.parametrize("para,expect", (
(
datamodel.Parameter(
datamodel.L2ancDesc.LST,
"-",
"-",
"-",
),
0.,
),
(
datamodel.Parameter(
datamodel.L2iDesc.Residual,
"-",
"-",
"-",
),
7.,
),
(
datamodel.Parameter(