def test_get_sky_diffuse_missing_dni_extra():
msg = 'dni_extra is required'
with pytest.raises(ValueError, match=msg):
irradiance.get_sky_diffuse(30,
180,
0,
180,
1000,
1100,
100,
airmass=1,
model='haydavies')
def test_get_sky_diffuse_model_invalid():
with pytest.raises(ValueError):
irradiance.get_sky_diffuse(30,
180,
0,
180,
1000,
1100,
100,
dni_extra=1360,
airmass=1,
model='invalid')
def test_sky_diffuse_zenith_close_to_90(model):
# GH 432
sky_diffuse = irradiance.get_sky_diffuse(30,
180,
89.999,
230,
dni=10,
ghi=51,
dhi=50,
dni_extra=1360,
airmass=12,
model=model)
assert sky_diffuse < 100
def test_get_sky_diffuse_missing_airmass(irrad_data, ephem_data, dni_et):
# test assumes location is Tucson, AZ
# calculated airmass should be the equivalent to fixture airmass
dni = irrad_data['dni'].copy()
dni.iloc[2] = np.nan
out = irradiance.get_sky_diffuse(40,
180,
ephem_data['apparent_zenith'],
ephem_data['azimuth'],
dni,
irrad_data['ghi'],
irrad_data['dhi'],
dni_et,
model='perez')
expected = pd.Series(np.array([0., 31.46046871, np.nan, 45.45539877]),
index=irrad_data.index)
assert_series_equal(out, expected, check_less_precise=2)
def test_sky_diffuse_zenith_close_to_90(model):
# GH 432
sky_diffuse = irradiance.get_sky_diffuse(
30, 180, 89.999, 230,
dni=10, ghi=51, dhi=50, dni_extra=1360, airmass=12, model=model)
assert sky_diffuse < 100
