def pmodelenv(values):
"""Fixture to create PModelEnvironments with scalar and array inputs
"""
sc = pmodel.PModelEnvironment(tc=values['tc_sc'],
vpd=values['vpd_sc'],
co2=values['co2_sc'],
patm=values['patm_sc'])
ar = pmodel.PModelEnvironment(tc=values['tc_ar'],
vpd=values['vpd_ar'],
co2=values['co2_ar'],
patm=values['patm_ar'])
return {'sc': sc, 'ar': ar}
def dataset():
"""Fixture to load test inputs from file from data folder in package root
"""
test_dir = os.path.dirname(os.path.abspath(__file__))
data_file_path = os.path.normpath(
os.path.join(test_dir, os.pardir, os.pardir, 'data',
'pmodel_inputs.nc'))
dataset = netCDF4.Dataset(data_file_path)
# TODO - masked arrays should be handled (it is basically the same as
# NA values in the R implementation) but for current validation
# this is just going to convert them to filled arrays
dataset.set_auto_mask(False)
# Extract the six variables for all months
temp = dataset['temp'][:]
co2 = dataset['CO2'][:] # Note - spatially constant but mapped.
elev = dataset['elevation'][:] # Note - temporally constant but repeated
vpd = dataset['VPD'][:]
fapar = dataset['fAPAR'][:]
ppfd = dataset['ppfd'][:]
dataset.close()
# Convert elevation to atmospheric pressure
patm = pmodel.calc_patm(elev)
# Calculate p model environment
env = pmodel.PModelEnvironment(tc=temp, vpd=vpd, co2=co2, patm=patm)
return env, fapar, ppfd
def test_pmodelenvironment_dewpoint():
with pytest.raises(ValueError):
ret = pmodel.PModelEnvironment(tc=np.array([-15, 5, 10, 15, 20]),
vpd=-1,
co2=400,
patm=101325)
def test_pmodelenvironment_toocold():
with pytest.raises(ValueError):
ret = pmodel.PModelEnvironment(tc=np.array([-35, 5, 10, 15, 20]),
vpd=1000,
co2=400,
patm=101325)
def test_pmodelenvironment_constraint():
with pytest.warns(UserWarning):
ret = pmodel.PModelEnvironment(tc=np.array([-15, 5, 10, 15, 20]),
vpd=100000,
co2=400,
patm=101325)
def test_pmodelenvironment(values, variables):
ret = pmodel.PModelEnvironment(tc=values[variables['tc']],
patm=values[variables['patm']],
vpd=values[variables['vpd']],
co2=values[variables['co2']])
assert np.allclose(ret.gammastar, values[variables['gammastar']])
assert np.allclose(ret.ns_star, values[variables['ns_star']])
assert np.allclose(ret.kmm, values[variables['kmm']])
assert np.allclose(ret.ca, values[variables['ca']])