def test__assign_total_irrad(sapm_dc_snl_ac_system, location, weather,
total_irrad):
weather[['poa_global', 'poa_diffuse', 'poa_direct']] = total_irrad
mc = ModelChain(sapm_dc_snl_ac_system, location)
mc._assign_total_irrad(weather)
for k in modelchain.POA_DATA_KEYS:
assert_series_equal(mc.total_irrad[k], total_irrad[k])
def test__prepare_temperature(sapm_dc_snl_ac_system, location, weather,
total_irrad):
data = weather.copy()
data[['poa_global', 'poa_diffuse', 'poa_direct']] = total_irrad
mc = ModelChain(sapm_dc_snl_ac_system, location, aoi_model='no_loss',
spectral_model='no_loss')
# prepare_temperature expects mc.total_irrad and mc.weather to be set
mc._assign_weather(data)
mc._assign_total_irrad(data)
mc._prepare_temperature(data)
expected = pd.Series([48.928025, 38.080016], index=data.index)
assert_series_equal(mc.cell_temperature, expected)
data['module_temperature'] = [40., 30.]
mc._prepare_temperature(data)
expected = pd.Series([42.4, 31.5], index=data.index)
assert_series_equal(mc.cell_temperature, expected)
data['cell_temperature'] = [50., 35.]
mc._prepare_temperature(data)
assert_series_equal(mc.cell_temperature, data['cell_temperature'])
def test__assign_total_irrad(sapm_dc_snl_ac_system, location, weather,
total_irrad):
data = pd.concat([weather, total_irrad], axis=1)
mc = ModelChain(sapm_dc_snl_ac_system, location)
mc._assign_total_irrad(data)
assert_frame_equal(mc.total_irrad, total_irrad)
