code: def _clearskypower(
      y, q, tod_i, doy_i, tod_vec, doy_vec, bw_tod, bw_doy
  ):
      """Estimate the clear sky power for a given day-of-year and hour-of-day.
  
      Parameters
      ----------
      y : Series of measurements
      q : Probability level used for the quantile
      tod_i : time-of-day of interest in hours
      doy_i : day-of-year of interest in days
      tod_vec : Series of time-of-day corresponding to the index of y
      doy_vec: Series of day-of-year corresponding to the index of y
      bw_tod : Kappa value used for defining weights for time-of-day
      bw_doy : Kappa value used for defining weights for day-of-year
  
      Returns
      -------
      csp : float
          The clear sky power at tod_i and doy_i
      """
      from scipy.stats import vonmises
      from statsmodels.stats.weightstats import DescrStatsW
  
      wts_tod = vonmises.pdf(
          x=tod_i * 2 * np.pi / 24,
          kappa=bw_tod,
          loc=tod_vec * 2 * np.pi / 24,
      )
      wts_doy = vonmises.pdf(
          x=doy_i * 2 * np.pi / 365.25,
          kappa=bw_doy,
          loc=doy_vec * 2 * np.pi / 365.25,
      )
  
      wts = wts_doy * wts_tod
      wts = wts / wts.sum()
  
      csp = DescrStatsW(y, weights=wts).quantile(probs=q).values[0]
  
      return csp
  
file_path: sktime/sktime/transformations/series/clear_sky.py
imports: import numpy
  import pandas
  from joblib import Parallel, delayed
  from sktime.transformations.base import BaseTransformer
label_desc: Use image node_id 1 for calling a global function with example usage: _clearskypower(y, q, tod_i, doy_i, tod_vec, doy_vec, bw_tod, bw_doy) and returns: csp