def test_gueymard94_pw():
temp_air = np.array([0, 20, 40])
relative_humidity = np.array([0, 30, 100])
temps_humids = np.array(
list(itertools.product(temp_air, relative_humidity)))
pws = atmosphere.gueymard94_pw(temps_humids[:, 0], temps_humids[:, 1])
expected = np.array(
[ 0.1 , 0.33702061, 1.12340202, 0.1 ,
1.12040963, 3.73469877, 0.1 , 3.44859767, 11.49532557])
assert_allclose(pws, expected, atol=0.01)
def test_gueymard94_pw():
temp_air = np.array([0, 20, 40])
relative_humidity = np.array([0, 30, 100])
temps_humids = np.array(
list(itertools.product(temp_air, relative_humidity)))
pws = atmosphere.gueymard94_pw(temps_humids[:, 0], temps_humids[:, 1])
expected = np.array(
[ 0.1 , 0.33702061, 1.12340202, 0.1 ,
1.12040963, 3.73469877, 0.1 , 3.44859767, 11.49532557])
assert_allclose(pws, expected, atol=0.01)
def preprocess(self):
if self.timezone != 'Asia/Kolkata':
self.weather_data['Timestamp'] = pd.to_datetime(self.weather_data['Timestamp'].values, \
utc=True).tz_convert(self.timezone)
self.solar_data['Timestamp'] = pd.to_datetime(self.solar_data['Timestamp'].values, \
utc=True).tz_convert(self.timezone)
if 'Timestamp' in self.weather_data.columns:
self.weather_data.drop('Timestamp', inplace=True, axis=1)
if 'Timestamp' in self.solar_data.columns:
self.solar_data.drop('Timestamp', inplace=True, axis=1)
for col in self.weather_data.columns:
if self.weather_data[col].isnull().sum() > 0:
self.weather_data[col].interpolate(method='time',
axis=0,
inplace=True)
# if sum(self.weather_data.isnull().sum(axis=0)) == 0:
# print('All Null values removed')
self.weather_data['precipitable_water'] = gueymard94_pw(self.weather_data['temp_air'],\
self.weather_data['relative_humidity'])
# This row has relative humidity = 100, which is practically not possible
if len(self.weather_data.loc[
self.weather_data['precipitable_water'] > 8,
'relative_humidity']) > 0:
print(
'Invalid values in the relative humidity column \n Removing such values'
)
self.weather_data.loc['2018-08-19 13:03:00+05:30',
'relative_humidity'] = 70
self.weather_data['precipitable_water'] = gueymard94_pw(
self.weather_data['temp_air'],
self.weather_data['relative_humidity'])
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
