code: def jensens_alpha(
      returns: Series, benchmark_returns: Series
  ) -> float:
      """Jensen's 'Alpha' of a series and a benchmark.
  
      Args:
          returns (pd.Series): Series of 'returns's
          benchmark_returns (pd.Series): Series of 'benchmark_returns's
  
      >>> result = ta.jensens_alpha(returns, benchmark_returns)
      """
      returns = verify_series(returns)
      benchmark_returns = verify_series(benchmark_returns)
  
      benchmark_returns.interpolate(inplace=True)
      return linear_regression(benchmark_returns, returns)["a"]
  
imports: from typing import Tuple
  from numpy import log
  from numpy import nan
  from numpy import sqrt
  from pandas import Series, Timedelta
  from ._core import verify_series
  from ._time import total_time
  from ._math import linear_regression, log_geometric_mean
  from pandas_ta import RATE
  from pandas_ta.performance import drawdown, log_return, percent_return
label_desc: Use image node_id 4 for calling a global function with example usage: jensens_alpha(returns, benchmark_returns) and returns: linear_regression