def test_pvfactors_timeseries(): """ Test that pvfactors is functional, using the TLDR section inputs of the package github repo README.md file: https://github.com/SunPower/pvfactors/blob/master/README.md#tldr---quick-start""" # Create some inputs timestamps = pd.DatetimeIndex([datetime(2017, 8, 31, 11), datetime(2017, 8, 31, 12)] ).set_names('timestamps') solar_zenith = [20., 10.] solar_azimuth = [110., 140.] surface_tilt = [10., 0.] surface_azimuth = [90., 90.] dni = [1000., 300.] dhi = [50., 500.] gcr = 0.4 pvrow_height = 1.75 pvrow_width = 2.44 albedo = 0.2 n_pvrows = 3 index_observed_pvrow = 1 rho_front_pvrow = 0.03 rho_back_pvrow = 0.05 horizon_band_angle = 15. # Expected values expected_ipoa_front = pd.Series([1034.96216923, 795.4423259], index=timestamps, name=(1, 'front', 'qinc')) expected_ipoa_back = pd.Series([92.11871485, 70.39404124], index=timestamps, name=(1, 'back', 'qinc')) # Test serial calculations ipoa_front, ipoa_back, df_registries = pvfactors_timeseries( solar_azimuth, solar_zenith, surface_azimuth, surface_tilt, timestamps, dni, dhi, gcr, pvrow_height, pvrow_width, albedo, n_pvrows=n_pvrows, index_observed_pvrow=index_observed_pvrow, rho_front_pvrow=rho_front_pvrow, rho_back_pvrow=rho_back_pvrow, horizon_band_angle=horizon_band_angle, run_parallel_calculations=False, n_workers_for_parallel_calcs=None) pd.testing.assert_series_equal(ipoa_front, expected_ipoa_front) pd.testing.assert_series_equal(ipoa_back, expected_ipoa_back) pd.testing.assert_index_equal(timestamps, df_registries.index.unique()) # Run calculations in parallel ipoa_front, ipoa_back, df_registries = pvfactors_timeseries( solar_azimuth, solar_zenith, surface_azimuth, surface_tilt, timestamps, dni, dhi, gcr, pvrow_height, pvrow_width, albedo, n_pvrows=n_pvrows, index_observed_pvrow=index_observed_pvrow, rho_front_pvrow=rho_front_pvrow, rho_back_pvrow=rho_back_pvrow, horizon_band_angle=horizon_band_angle, run_parallel_calculations=True, n_workers_for_parallel_calcs=None) pd.testing.assert_series_equal(ipoa_front, expected_ipoa_front) pd.testing.assert_series_equal(ipoa_back, expected_ipoa_back) pd.testing.assert_index_equal(timestamps, df_registries.index.unique())
def test_pvfactors_timeseries(run_parallel_calculations): """ Test that pvfactors is functional, using the TLDR section inputs of the package github repo README.md file: https://github.com/SunPower/pvfactors/blob/master/README.md#tldr---quick-start""" # Create some inputs timestamps = pd.DatetimeIndex( [datetime(2017, 8, 31, 11), datetime(2017, 8, 31, 12)]).set_names('timestamps') solar_zenith = [20., 10.] solar_azimuth = [110., 140.] surface_tilt = [10., 0.] surface_azimuth = [90., 90.] axis_azimuth = 0. dni = [1000., 300.] dhi = [50., 500.] gcr = 0.4 pvrow_height = 1.75 pvrow_width = 2.44 albedo = 0.2 n_pvrows = 3 index_observed_pvrow = 1 rho_front_pvrow = 0.03 rho_back_pvrow = 0.05 horizon_band_angle = 15. # Expected values expected_ipoa_front = pd.Series([1034.95474708997, 795.4423259036623], index=timestamps, name=('total_inc_front')) expected_ipoa_back = pd.Series([91.88707460262768, 78.05831585685215], index=timestamps, name=('total_inc_back')) # Run calculation ipoa_front, ipoa_back = pvfactors_timeseries( solar_azimuth, solar_zenith, surface_azimuth, surface_tilt, axis_azimuth, timestamps, dni, dhi, gcr, pvrow_height, pvrow_width, albedo, n_pvrows=n_pvrows, index_observed_pvrow=index_observed_pvrow, rho_front_pvrow=rho_front_pvrow, rho_back_pvrow=rho_back_pvrow, horizon_band_angle=horizon_band_angle, run_parallel_calculations=run_parallel_calculations, n_workers_for_parallel_calcs=-1) pd.testing.assert_series_equal(ipoa_front, expected_ipoa_front) pd.testing.assert_series_equal(ipoa_back, expected_ipoa_back)
def test_pvfactors_timeseries_pandas(example_values): """Test basic pvfactors functionality with Series inputs""" inputs, outputs = example_values for key in ['solar_zenith', 'solar_azimuth', 'surface_tilt', 'surface_azimuth', 'dni', 'dhi']: inputs[key] = pd.Series(inputs[key], index=inputs['timestamps']) ipoa_inc_front, ipoa_inc_back, _, _ = pvfactors_timeseries(**inputs) assert_series_equal(ipoa_inc_front, outputs['expected_ipoa_front']) assert_series_equal(ipoa_inc_back, outputs['expected_ipoa_back'])
def test_pvfactors_scalar_orientation(example_values): """test that surface_tilt and surface_azimuth inputs can be scalars""" # GH 1127, GH 1332 inputs, outputs = example_values inputs['surface_tilt'] = 10. inputs['surface_azimuth'] = 90. # the second tilt is supposed to be zero, so we need to # update the expected irradiances too: outputs['expected_ipoa_front'].iloc[1] = 800.6524022701132 outputs['expected_ipoa_back'].iloc[1] = 81.72135884745822 ipoa_inc_front, ipoa_inc_back, _, _ = pvfactors_timeseries(**inputs) assert_series_equal(ipoa_inc_front, outputs['expected_ipoa_front']) assert_series_equal(ipoa_inc_back, outputs['expected_ipoa_back'])
def test_pvfactors_timeseries_pandas_inputs(): """ Test that pvfactors is functional, using the TLDR section inputs of the package github repo README.md file, but converted to pandas Series: https://github.com/SunPower/pvfactors/blob/master/README.md#tldr---quick-start""" # Create some inputs timestamps = pd.DatetimeIndex([datetime(2017, 8, 31, 11), datetime(2017, 8, 31, 12)] ).set_names('timestamps') solar_zenith = pd.Series([20., 10.]) solar_azimuth = pd.Series([110., 140.]) surface_tilt = pd.Series([10., 0.]) surface_azimuth = pd.Series([90., 90.]) axis_azimuth = 0. dni = pd.Series([1000., 300.]) dhi = pd.Series([50., 500.]) gcr = 0.4 pvrow_height = 1.75 pvrow_width = 2.44 albedo = 0.2 n_pvrows = 3 index_observed_pvrow = 1 rho_front_pvrow = 0.03 rho_back_pvrow = 0.05 horizon_band_angle = 15. # Expected values expected_ipoa_front = pd.Series([1034.95474708997, 795.4423259036623], index=timestamps, name=('total_inc_front')) expected_ipoa_back = pd.Series([92.12563846416197, 78.05831585685098], index=timestamps, name=('total_inc_back')) # Run calculation ipoa_inc_front, ipoa_inc_back, _, _ = pvfactors_timeseries( solar_azimuth, solar_zenith, surface_azimuth, surface_tilt, axis_azimuth, timestamps, dni, dhi, gcr, pvrow_height, pvrow_width, albedo, n_pvrows=n_pvrows, index_observed_pvrow=index_observed_pvrow, rho_front_pvrow=rho_front_pvrow, rho_back_pvrow=rho_back_pvrow, horizon_band_angle=horizon_band_angle) assert_series_equal(ipoa_inc_front, expected_ipoa_front) assert_series_equal(ipoa_inc_back, expected_ipoa_back)
def test_pvfactors_timeseries_list(example_values): """Test basic pvfactors functionality with list inputs""" inputs, outputs = example_values ipoa_inc_front, ipoa_inc_back, _, _ = pvfactors_timeseries(**inputs) assert_series_equal(ipoa_inc_front, outputs['expected_ipoa_front']) assert_series_equal(ipoa_inc_back, outputs['expected_ipoa_back'])
def test_pvfactors_timeseries_pandas_inputs(): """ Test that pvfactors is functional, using the TLDR section inputs of the package github repo README.md file, but converted to pandas Series: https://github.com/SunPower/pvfactors/blob/master/README.md#tldr---quick-start""" # Create some inputs timestamps = pd.DatetimeIndex( [datetime(2017, 8, 31, 11), datetime(2017, 8, 31, 12)]).set_names('timestamps') solar_zenith = pd.Series([20., 10.]) solar_azimuth = pd.Series([110., 140.]) surface_tilt = pd.Series([10., 0.]) surface_azimuth = pd.Series([90., 90.]) dni = pd.Series([1000., 300.]) dhi = pd.Series([50., 500.]) gcr = 0.4 pvrow_height = 1.75 pvrow_width = 2.44 albedo = 0.2 n_pvrows = 3 index_observed_pvrow = 1 rho_front_pvrow = 0.03 rho_back_pvrow = 0.05 horizon_band_angle = 15. # Expected values expected_ipoa_front = pd.Series([1034.96216923, 795.4423259], index=timestamps, name=(1, 'front', 'qinc')) expected_ipoa_back = pd.Series([92.11871485, 70.39404124], index=timestamps, name=(1, 'back', 'qinc')) # Test serial calculations ipoa_front, ipoa_back, df_registries = pvfactors_timeseries( solar_azimuth, solar_zenith, surface_azimuth, surface_tilt, timestamps, dni, dhi, gcr, pvrow_height, pvrow_width, albedo, n_pvrows=n_pvrows, index_observed_pvrow=index_observed_pvrow, rho_front_pvrow=rho_front_pvrow, rho_back_pvrow=rho_back_pvrow, horizon_band_angle=horizon_band_angle, run_parallel_calculations=False, n_workers_for_parallel_calcs=None) pd.testing.assert_series_equal(ipoa_front, expected_ipoa_front) pd.testing.assert_series_equal(ipoa_back, expected_ipoa_back) pd.testing.assert_index_equal(timestamps, df_registries.index.unique()) # Run calculations in parallel ipoa_front, ipoa_back, df_registries = pvfactors_timeseries( solar_azimuth, solar_zenith, surface_azimuth, surface_tilt, timestamps, dni, dhi, gcr, pvrow_height, pvrow_width, albedo, n_pvrows=n_pvrows, index_observed_pvrow=index_observed_pvrow, rho_front_pvrow=rho_front_pvrow, rho_back_pvrow=rho_back_pvrow, horizon_band_angle=horizon_band_angle, run_parallel_calculations=True, n_workers_for_parallel_calcs=None) pd.testing.assert_series_equal(ipoa_front, expected_ipoa_front) pd.testing.assert_series_equal(ipoa_back, expected_ipoa_back) pd.testing.assert_index_equal(timestamps, df_registries.index.unique())