def disaggregate_radiation(self, method='pot_rad'):
"""
Disaggregate solar radiation.
Parameters
----------
method : str, optional
Disaggregation method.
``pot_rad``
Calculates potential clear-sky hourly radiation and scales it according to the
mean daily radiation. (Default)
``pot_rad_via_ssd``
Calculates potential clear-sky hourly radiation and scales it according to the
observed daily sunshine duration.
``pot_rad_via_bc``
Calculates potential clear-sky hourly radiation and scales it according to daily
minimum and maximum temperature.
"""
if self.sun_times is None:
self.calc_sun_times()
self.data_disagg.glob = melodist.disaggregate_radiation(
self.data_daily,
self.sun_times,
melodist.potential_radiation(self.data_disagg.index, self.lon,
self.lat, self.timezone),
method=method,
angstr_a=self.statistics.glob.angstroem_a,
angstr_b=self.statistics.glob.angstroem_b,
bristcamp_a=self.statistics.glob.bristcamp_a,
bristcamp_c=self.statistics.glob.bristcamp_c)
def disaggregate_radiation(self, method='pot_rad'):
"""
Disaggregate solar radiation.
Parameters
----------
method : str, optional
Disaggregation method.
``pot_rad``
Calculates potential clear-sky hourly radiation and scales it according to the
mean daily radiation. (Default)
``pot_rad_via_ssd``
Calculates potential clear-sky hourly radiation and scales it according to the
observed daily sunshine duration.
``pot_rad_via_bc``
Calculates potential clear-sky hourly radiation and scales it according to daily
minimum and maximum temperature.
"""
if self.sun_times is None:
self.calc_sun_times()
self.data_disagg.glob = melodist.disaggregate_radiation(
self.data_daily,
self.sun_times,
melodist.potential_radiation(self.data_disagg.index, self.lon, self.lat, self.timezone),
method=method,
angstr_a=self.statistics.glob.angstroem_a,
angstr_b=self.statistics.glob.angstroem_b,
bristcamp_a=self.statistics.glob.bristcamp_a,
bristcamp_c=self.statistics.glob.bristcamp_c
)
def calc_radiation_stats(self, data_daily, day_length=None):
"""
Calculates statistics in order to derive solar radiation from sunshine duration or
minimum/maximum temperature.
Parameters
----------
data_daily : DataFrame
Daily data from the associated ``Station`` object.
day_length : Series, optional
Day lengths as calculated by ``calc_sun_times``.
"""
if 'ssd' in data_daily and day_length is not None:
df = pd.DataFrame(
data=dict(ssd=data_daily.ssd, day_length=day_length)).dropna(
how='any')
pot_rad = melodist.potential_radiation(
melodist.util.hourly_index(df.index), self._lon, self._lat,
self._timezone)
pot_rad_daily = pot_rad.resample('D', how='mean')
obs_rad_daily = self.data.glob.resample('D', how='mean')
a, b = melodist.fit_angstroem_params(data_daily.ssd, day_length,
pot_rad_daily, obs_rad_daily)
self.glob.angstroem_a = a
self.glob.angstroem_b = b
if 'tmin' in data_daily and 'tmax' in data_daily:
pot_rad = melodist.potential_radiation(
melodist.util.hourly_index(df.index), self._lon, self._lat,
self._timezone)
pot_rad_daily = pot_rad.resample('D', how='mean')
obs_rad_daily = self.data.glob.resample('D', how='mean')
df = pd.DataFrame(data=dict(
tmin=data_daily.tmin,
tmax=data_daily.tmax,
pot_rad=pot_rad_daily,
obs_rad=obs_rad_daily,
)).dropna(how='any')
a, c = melodist.fit_bristow_campbell_params(
df.tmin, df.tmax, df.pot_rad, df.obs_rad)
self.glob.bristcamp_a = a
self.glob.bristcamp_c = c
def disaggregate_radiation(self, method='pot_rad', pot_rad=None):
"""
Disaggregate solar radiation.
Parameters
----------
method : str, optional
Disaggregation method.
``pot_rad``
Calculates potential clear-sky hourly radiation and scales it according to the
mean daily radiation. (Default)
``pot_rad_via_ssd``
Calculates potential clear-sky hourly radiation and scales it according to the
observed daily sunshine duration.
``pot_rad_via_bc``
Calculates potential clear-sky hourly radiation and scales it according to daily
minimum and maximum temperature.
``mean_course``
Hourly radiation follows an observed average course (calculated for each month).
pot_rad : Series, optional
Hourly values of potential solar radiation. If ``None``, calculated internally.
"""
if self.sun_times is None:
self.calc_sun_times()
if pot_rad is None and method != 'mean_course':
pot_rad = melodist.potential_radiation(self.data_disagg.index,
self.lon, self.lat,
self.timezone)
self.data_disagg.glob = melodist.disaggregate_radiation(
self.data_daily,
sun_times=self.sun_times,
pot_rad=pot_rad,
method=method,
angstr_a=self.statistics.glob.angstroem.a,
angstr_b=self.statistics.glob.angstroem.b,
bristcamp_a=self.statistics.glob.bristcamp.a,
bristcamp_c=self.statistics.glob.bristcamp.c,
mean_course=self.statistics.glob.mean_course)
def disaggregate_radiation(self, method='pot_rad', pot_rad=None):
"""
Disaggregate solar radiation.
Parameters
----------
method : str, optional
Disaggregation method.
``pot_rad``
Calculates potential clear-sky hourly radiation and scales it according to the
mean daily radiation. (Default)
``pot_rad_via_ssd``
Calculates potential clear-sky hourly radiation and scales it according to the
observed daily sunshine duration.
``pot_rad_via_bc``
Calculates potential clear-sky hourly radiation and scales it according to daily
minimum and maximum temperature.
``mean_course``
Hourly radiation follows an observed average course (calculated for each month).
pot_rad : Series, optional
Hourly values of potential solar radiation. If ``None``, calculated internally.
"""
if self.sun_times is None:
self.calc_sun_times()
if pot_rad is None and method != 'mean_course':
pot_rad = melodist.potential_radiation(self.data_disagg.index, self.lon, self.lat, self.timezone)
self.data_disagg.glob = melodist.disaggregate_radiation(
self.data_daily,
sun_times=self.sun_times,
pot_rad=pot_rad,
method=method,
angstr_a=self.statistics.glob.angstroem.a,
angstr_b=self.statistics.glob.angstroem.b,
bristcamp_a=self.statistics.glob.bristcamp.a,
bristcamp_c=self.statistics.glob.bristcamp.c,
mean_course=self.statistics.glob.mean_course
)
def calc_radiation_stats(self,
data_daily=None,
day_length=None,
how='all'):
"""
Calculates statistics in order to derive solar radiation from sunshine duration or
minimum/maximum temperature.
Parameters
----------
data_daily : DataFrame, optional
Daily data from the associated ``Station`` object.
day_length : Series, optional
Day lengths as calculated by ``calc_sun_times``.
"""
assert how in ('all', 'seasonal', 'monthly')
self.glob.mean_course = melodist.util.calculate_mean_daily_course_by_month(
self.data.glob)
if data_daily is not None:
pot_rad = melodist.potential_radiation(
melodist.util.hourly_index(data_daily.index), self._lon,
self._lat, self._timezone)
pot_rad_daily = pot_rad.resample('D').mean()
obs_rad_daily = self.data.glob.resample('D').mean()
if how == 'all':
month_ranges = [np.arange(12) + 1]
elif how == 'seasonal':
month_ranges = [[3, 4, 5], [6, 7, 8], [9, 10, 11], [12, 1, 2]]
elif how == 'monthly':
month_ranges = zip(np.arange(12) + 1)
def myisin(s, v):
return pd.Series(s).isin(v).values
def extract_months(s, months):
return s[myisin(s.index.month, months)]
if 'ssd' in data_daily and day_length is not None:
for months in month_ranges:
a, b = melodist.fit_angstroem_params(
extract_months(data_daily.ssd, months),
extract_months(day_length, months),
extract_months(pot_rad_daily, months),
extract_months(obs_rad_daily, months),
)
for month in months:
self.glob.angstroem.loc[month] = a, b
if 'tmin' in data_daily and 'tmax' in data_daily:
df = pd.DataFrame(data=dict(
tmin=data_daily.tmin,
tmax=data_daily.tmax,
pot_rad=pot_rad_daily,
obs_rad=obs_rad_daily,
)).dropna(how='any')
for months in month_ranges:
a, c = melodist.fit_bristow_campbell_params(
extract_months(df.tmin, months),
extract_months(df.tmax, months),
extract_months(df.pot_rad, months),
extract_months(df.obs_rad, months),
)
for month in months:
self.glob.bristcamp.loc[month] = a, c
def calc_radiation_stats(self, data_daily=None, day_length=None, how='all'):
"""
Calculates statistics in order to derive solar radiation from sunshine duration or
minimum/maximum temperature.
Parameters
----------
data_daily : DataFrame, optional
Daily data from the associated ``Station`` object.
day_length : Series, optional
Day lengths as calculated by ``calc_sun_times``.
"""
assert how in ('all', 'seasonal', 'monthly')
self.glob.mean_course = melodist.util.calculate_mean_daily_course_by_month(self.data.glob)
if data_daily is not None:
pot_rad = melodist.potential_radiation(
melodist.util.hourly_index(data_daily.index),
self._lon, self._lat, self._timezone)
pot_rad_daily = pot_rad.resample('D').mean()
obs_rad_daily = self.data.glob.resample('D').mean()
if how == 'all':
month_ranges = [np.arange(12) + 1]
elif how == 'seasonal':
month_ranges = [[3, 4, 5], [6, 7, 8], [9, 10, 11], [12, 1, 2]]
elif how == 'monthly':
month_ranges = zip(np.arange(12) + 1)
def myisin(s, v):
return pd.Series(s).isin(v).values
def extract_months(s, months):
return s[myisin(s.index.month, months)]
if 'ssd' in data_daily and day_length is not None:
for months in month_ranges:
a, b = melodist.fit_angstroem_params(
extract_months(data_daily.ssd, months),
extract_months(day_length, months),
extract_months(pot_rad_daily, months),
extract_months(obs_rad_daily, months),
)
for month in months:
self.glob.angstroem.loc[month] = a, b
if 'tmin' in data_daily and 'tmax' in data_daily:
df = pd.DataFrame(
data=dict(
tmin=data_daily.tmin,
tmax=data_daily.tmax,
pot_rad=pot_rad_daily,
obs_rad=obs_rad_daily,
)
).dropna(how='any')
for months in month_ranges:
a, c = melodist.fit_bristow_campbell_params(
extract_months(df.tmin, months),
extract_months(df.tmax, months),
extract_months(df.pot_rad, months),
extract_months(df.obs_rad, months),
)
for month in months:
self.glob.bristcamp.loc[month] = a, c