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fix modelchain poa tests #1052

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Merged
merged 2 commits into from
Sep 8, 2020
Merged

fix modelchain poa tests #1052

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6a828c9
fix modelchain poa tests
wholmgren Sep 7, 2020
6079b96
poa_data_keys to poa_keys
wholmgren Sep 8, 2020
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12 changes: 6 additions & 6 deletions pvlib/modelchain.py
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Original file line number Diff line number Diff line change
Expand Up @@ -21,20 +21,20 @@
# keys that are used to detect input data and assign data to appropriate
# ModelChain attribute
# for ModelChain.weather
WEATHER_KEYS = {'ghi', 'dhi', 'dni', 'wind_speed', 'temp_air',
'precipitable_water'}
WEATHER_KEYS = ('ghi', 'dhi', 'dni', 'wind_speed', 'temp_air',
'precipitable_water')

# for ModelChain.total_irrad
POA_DATA_KEYS = {'poa_global', 'poa_direct', 'poa_diffuse'}
POA_KEYS = ('poa_global', 'poa_direct', 'poa_diffuse')

# Optional keys to communicate temperature data. If provided,
# 'cell_temperature' overrides ModelChain.temperature_model and sets
# ModelChain.cell_temperature to the data. If 'module_temperature' is provdied,
# overrides ModelChain.temperature_model with
# pvlib.temperature.sapm_celL_from_module
TEMPERATURE_KEYS = {'module_temperature', 'cell_temperature'}
TEMPERATURE_KEYS = ('module_temperature', 'cell_temperature')

DATA_KEYS = WEATHER_KEYS | POA_DATA_KEYS | TEMPERATURE_KEYS
DATA_KEYS = WEATHER_KEYS + POA_KEYS + TEMPERATURE_KEYS

# these dictionaries contain the default configuration for following
# established modeling sequences. They can be used in combination with
Expand Down Expand Up @@ -1090,7 +1090,7 @@ def _assign_weather(self, data):
return self

def _assign_total_irrad(self, data):
key_list = [k for k in POA_DATA_KEYS if k in data]
key_list = [k for k in POA_KEYS if k in data]
self.total_irrad = data[key_list].copy()
return self

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22 changes: 13 additions & 9 deletions pvlib/tests/test_modelchain.py
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Original file line number Diff line number Diff line change
Expand Up @@ -181,8 +181,8 @@ def weather():
@pytest.fixture
def total_irrad(weather):
return pd.DataFrame({'poa_global': [800., 500.],
'poa_diffuse': [300., 200.],
'poa_direct': [500., 300.]}, index=weather.index)
'poa_direct': [500., 300.],
'poa_diffuse': [300., 200.]}, index=weather.index)


def test_ModelChain_creation(sapm_dc_snl_ac_system, location):
Expand Down Expand Up @@ -336,21 +336,25 @@ def test_run_model_tracker(sapm_dc_snl_ac_system, location, weather, mocker):

def test__assign_total_irrad(sapm_dc_snl_ac_system, location, weather,
total_irrad):
weather[['poa_global', 'poa_diffuse', 'poa_direct']] = total_irrad
data = pd.concat([weather, total_irrad], axis=1)
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])
mc._assign_total_irrad(data)
assert_frame_equal(mc.total_irrad, total_irrad)


def test_prepare_inputs_from_poa(sapm_dc_snl_ac_system, location,
weather, total_irrad):
data = weather.copy()
data[['poa_global', 'poa_diffuse', 'poa_direct']] = total_irrad
data = pd.concat([weather, total_irrad], axis=1)
mc = ModelChain(sapm_dc_snl_ac_system, location)
mc.prepare_inputs_from_poa(data)
weather_expected = weather.copy()
weather_expected['temp_air'] = 20
weather_expected['wind_speed'] = 0
# order as expected
weather_expected = weather_expected[
['ghi', 'dhi', 'dni', 'wind_speed', 'temp_air']]
# weather attribute
assert_frame_equal(mc.weather, weather)
assert_frame_equal(mc.weather, weather_expected)
# total_irrad attribute
assert_frame_equal(mc.total_irrad, total_irrad)

Expand Down