def test_get_pvgis_tmy_kwargs(userhorizon_expected):
_, _, inputs, _ = get_pvgis_tmy(45, 8, usehorizon=False)
assert inputs['meteo_data']['use_horizon'] is False
data, _, _, _ = get_pvgis_tmy(45,
8,
userhorizon=[0, 10, 20, 30, 40, 15, 25, 5])
assert np.allclose(data['G(h)'], userhorizon_expected['G(h)'].values)
assert np.allclose(data['Gb(n)'], userhorizon_expected['Gb(n)'].values)
assert np.allclose(data['Gd(h)'], userhorizon_expected['Gd(h)'].values)
_, _, inputs, _ = get_pvgis_tmy(45, 8, startyear=2005)
assert inputs['meteo_data']['year_min'] == 2005
_, _, inputs, _ = get_pvgis_tmy(45, 8, endyear=2016)
assert inputs['meteo_data']['year_max'] == 2016
def test_get_pvgis_tmy_epw(expected, epw_meta):
data, _, _, meta = get_pvgis_tmy(45, 8, outputformat='epw')
assert np.allclose(data.ghi, expected['G(h)'])
assert np.allclose(data.dni, expected['Gb(n)'])
assert np.allclose(data.dhi, expected['Gd(h)'])
assert np.allclose(data.temp_air, expected['T2m'])
assert meta == epw_meta
def test_get_pvgis_tmy_csv(expected, month_year_expected, inputs_expected,
meta_expected, csv_meta):
data, months_selected, inputs, meta = get_pvgis_tmy(
45, 8, outputformat='csv')
# check each column of output separately
for outvar in meta_expected['outputs']['tmy_hourly']['variables'].keys():
assert np.allclose(data[outvar], expected[outvar])
assert np.allclose(
[_['month'] for _ in months_selected], np.arange(1, 13, 1))
assert np.allclose(
[_['year'] for _ in months_selected], month_year_expected)
assert inputs['latitude'] == inputs_expected['location']['latitude']
assert inputs['longitude'] == inputs_expected['location']['longitude']
assert inputs['elevation'] == inputs_expected['location']['elevation']
for meta_value in meta:
if not meta_value:
continue
if meta_value == 'PVGIS (c) European Communities, 2001-2020':
continue
assert meta_value in csv_meta
def get_from_pvgis(lat, lon, tz):
"""Return the pvgis data"""
# PVGIS information
info = get_pvgis_tmy(lat, lon)
# Altitude
alt = info[2]['location']['elevation']
# Get th principal information
df = info[0]
# Convert UTC to time zone
df.index = df.index.tz_convert(tz)
df.index.name = f'Time {tz}'
# Get the solar position
solpos = get_solarposition(time=df.index,
latitude=lat,
longitude=lon,
altitude=alt,
pressure=df.SP,
temperature=df.T2m)
# Create the schema
data = df
data = data.drop(df.columns, axis=1)
data['HourOfDay'] = df.index.hour
data['Zenith'] = solpos['zenith']
data['Temperature'] = df.T2m
data['Humidity'] = df.RH
data['WindSpeed'] = df.WS10m
data['WindDirection'] = df.WD10m
data['PrecipitableWater'] = gueymard94_pw(df.T2m, df.RH)
data['Pressure'] = df.SP
data['ExtraRadiation'] = get_extra_radiation(df.index)
data['GHI'] = df['G(h)']
return data
def test_get_pvgis_tmy(expected, month_year_expected, inputs_expected,
meta_expected):
data, months_selected, inputs, meta = get_pvgis_tmy(45, 8)
# check each column of output separately
for outvar in meta_expected['outputs']['tmy_hourly']['variables'].keys():
assert np.allclose(data[outvar], expected[outvar])
assert np.allclose(
[_['month'] for _ in months_selected], np.arange(1, 13, 1))
assert np.allclose(
[_['year'] for _ in months_selected], month_year_expected)
inputs_loc = inputs['location']
assert inputs_loc['latitude'] == inputs_expected['location']['latitude']
assert inputs_loc['longitude'] == inputs_expected['location']['longitude']
assert inputs_loc['elevation'] == inputs_expected['location']['elevation']
inputs_met_data = inputs['meteo_data']
expected_met_data = inputs_expected['meteo_data']
assert (
inputs_met_data['radiation_db'] == expected_met_data['radiation_db'])
assert inputs_met_data['year_min'] == expected_met_data['year_min']
assert inputs_met_data['year_max'] == expected_met_data['year_max']
assert inputs_met_data['use_horizon'] == expected_met_data['use_horizon']
assert inputs_met_data['horizon_db'] == expected_met_data['horizon_db']
assert meta == meta_expected
def test_get_pvgis_tmy(expected, month_year_expected, inputs_expected,
meta_expected):
pvgis_data = get_pvgis_tmy(45, 8)
_compare_pvgis_tmy_json(expected, month_year_expected, inputs_expected,
meta_expected, pvgis_data)
def test_get_pvgis_tmy_error():
err_msg = 'outputformat: Incorrect value.'
with pytest.raises(requests.HTTPError, match=err_msg):
get_pvgis_tmy(45, 8, outputformat='bad')
with pytest.raises(requests.HTTPError, match='404 Client Error'):
get_pvgis_tmy(45, 8, url='https://re.jrc.ec.europa.eu/')
def test_get_pvgis_tmy_epw(expected, epw_meta):
pvgis_data = get_pvgis_tmy(45, 8, outputformat='epw')
_compare_pvgis_tmy_epw(expected, epw_meta, pvgis_data)
def test_get_pvgis_tmy_csv(expected, month_year_expected, inputs_expected,
meta_expected, csv_meta):
pvgis_data = get_pvgis_tmy(45, 8, outputformat='csv')
_compare_pvgis_tmy_csv(expected, month_year_expected, inputs_expected,
meta_expected, csv_meta, pvgis_data)
def test_get_pvgis_tmy_basic(expected, meta_expected):
pvgis_data = get_pvgis_tmy(45, 8, outputformat='basic')
_compare_pvgis_tmy_basic(expected, meta_expected, pvgis_data)
def test_get_pvgis_tmy_basic(expected, meta_expected):
data, _, _, _ = get_pvgis_tmy(45, 8, outputformat='basic')
# check each column of output separately
for outvar in meta_expected['outputs']['tmy_hourly']['variables'].keys():
assert np.allclose(data[outvar], expected[outvar])
def test_get_pvgis_map_variables(pvgis_tmy_mapped_columns):
actual, _, _, _ = get_pvgis_tmy(45, 8, map_variables=True)
assert all([c in pvgis_tmy_mapped_columns for c in actual.columns])
def test_get_pvgis_tmy_epw(expected, epw_meta):
pvgis_data = get_pvgis_tmy(45, 8, outputformat='epw', map_variables=False)
_compare_pvgis_tmy_epw(expected, epw_meta, pvgis_data)
def test_get_pvgis_tmy_basic(expected, meta_expected):
pvgis_data = get_pvgis_tmy(45, 8, outputformat='basic',
map_variables=False)
_compare_pvgis_tmy_basic(expected, meta_expected, pvgis_data)
def test_get_pvgis_tmy(expected, month_year_expected, inputs_expected,
meta_expected):
pvgis_data = get_pvgis_tmy(45, 8, map_variables=False)
_compare_pvgis_tmy_json(expected, month_year_expected, inputs_expected,
meta_expected, pvgis_data)
def test_pvgis_tmy_variable_map_deprecating_warning_0_10():
with pytest.warns(pvlibDeprecationWarning, match='names will be renamed'):
_ = get_pvgis_tmy(45, 8)
with pytest.warns(pvlibDeprecationWarning, match='names will be renamed'):
fn = DATA_DIR / 'tmy_45.000_8.000_2005_2016.epw'
_ = read_pvgis_tmy(fn)
