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)