def test_perez_components(irrad_data, ephem_data, dni_et, relative_airmass):
dni = irrad_data['dni'].copy()
dni.iloc[2] = np.nan
out = irradiance.perez(40, 180, irrad_data['dhi'], dni,
dni_et, ephem_data['apparent_zenith'],
ephem_data['azimuth'], relative_airmass,
return_components=True)
expected = pd.DataFrame(np.array(
[[ 0. , 31.46046871, np.nan, 45.45539877],
[ 0. , 26.84138589, np.nan, 31.72696071],
[ 0. , 0. , np.nan, 4.47966439],
[ 0. , 4.62212181, np.nan, 9.25316454]]).T,
columns=['sky_diffuse', 'isotropic', 'circumsolar', 'horizon'],
index=irrad_data.index
)
if pandas_0_22():
expected_for_sum = expected['sky_diffuse'].copy()
expected_for_sum.iloc[2] = 0
else:
expected_for_sum = expected['sky_diffuse']
sum_components = out.iloc[:, 1:].sum(axis=1)
sum_components.name = 'sky_diffuse'
assert_frame_equal(out, expected, check_less_precise=2)
assert_series_equal(sum_components, expected_for_sum, check_less_precise=2)
def test_perez_components():
am = atmosphere.relativeairmass(ephem_data['apparent_zenith'])
dni = irrad_data['dni'].copy()
dni.iloc[2] = np.nan
out, df_components = irradiance.perez(40, 180, irrad_data['dhi'], dni,
dni_et, ephem_data['apparent_zenith'],
ephem_data['azimuth'], am, return_components=True)
expected = pd.Series(np.array(
[ 0. , 31.46046871, np.nan, 45.45539877]),
index=times)
expected_components = pd.DataFrame(
np.array([[ 0. , 26.84138589, np.nan, 31.72696071],
[ 0. , 0. , np.nan, 4.47966439],
[ 0. , 4.62212181, np.nan, 9.25316454]]).T,
columns=['isotropic', 'circumsolar', 'horizon'],
index=times
)
if pandas_0_22():
expected_for_sum = expected.copy()
expected_for_sum.iloc[2] = 0
else:
expected_for_sum = expected
sum_components = df_components.sum(axis=1)
assert_series_equal(out, expected, check_less_precise=2)
assert_frame_equal(df_components, expected_components)
assert_series_equal(sum_components, expected_for_sum, check_less_precise=2)
def test_perez_components(irrad_data, ephem_data, dni_et, relative_airmass):
dni = irrad_data['dni'].copy()
dni.iloc[2] = np.nan
out = irradiance.perez(40,
180,
irrad_data['dhi'],
dni,
dni_et,
ephem_data['apparent_zenith'],
ephem_data['azimuth'],
relative_airmass,
return_components=True)
expected = pd.DataFrame(
np.array([[0., 31.46046871, np.nan, 45.45539877],
[0., 26.84138589, np.nan, 31.72696071],
[0., 0., np.nan, 4.47966439],
[0., 4.62212181, np.nan, 9.25316454]]).T,
columns=['sky_diffuse', 'isotropic', 'circumsolar', 'horizon'],
index=irrad_data.index)
if pandas_0_22():
expected_for_sum = expected['sky_diffuse'].copy()
expected_for_sum.iloc[2] = 0
else:
expected_for_sum = expected['sky_diffuse']
sum_components = out.iloc[:, 1:].sum(axis=1)
sum_components.name = 'sky_diffuse'
assert_frame_equal(out, expected, check_less_precise=2)
assert_series_equal(sum_components, expected_for_sum, check_less_precise=2)
def test_perez_components():
am = atmosphere.relativeairmass(ephem_data['apparent_zenith'])
dni = irrad_data['dni'].copy()
dni.iloc[2] = np.nan
out, df_components = irradiance.perez(40,
180,
irrad_data['dhi'],
dni,
dni_et,
ephem_data['apparent_zenith'],
ephem_data['azimuth'],
am,
return_components=True)
expected = pd.Series(np.array([0., 31.46046871, np.nan, 45.45539877]),
index=times)
expected_components = pd.DataFrame(
np.array([[0., 26.84138589, np.nan, 31.72696071],
[0., 0., np.nan, 4.47966439],
[0., 4.62212181, np.nan, 9.25316454]]).T,
columns=['isotropic', 'circumsolar', 'horizon'],
index=times)
if pandas_0_22():
expected_for_sum = expected.copy()
expected_for_sum.iloc[2] = 0
else:
expected_for_sum = expected
sum_components = df_components.sum(axis=1)
assert_series_equal(out, expected, check_less_precise=2)
assert_frame_equal(df_components, expected_components)
assert_series_equal(sum_components, expected_for_sum, check_less_precise=2)