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())