code: def entropy(X: npt.ArrayLike) -> float:
      """Shannons's entropy for time series.
  
      As defined by equations (3) and (4) from [1]_.
  
      Parameters
      ----------
      X: array_like
          Time series data as a 2D numpy array with sequence index along rows
          and value series in columns.
  
      Returns
      -------
      entropy: float
          Computed entropy.
      """
      p = np.sum(X, axis=0) / np.sum(X)
      p = p[p > 0.0]
      return -np.sum(p * np.log(p))
  
imports: from dataclasses import asdict, dataclass, field
  from typing import Dict, List
  import numpy
  import numpy.typing
  import pandas
  from sktime.base import BaseEstimator
  from sktime.utils.validation._dependencies import _check_estimator_deps
label_desc: Use image node_id 1 for calling a global function with example usage: entropy(X) and returns: unknown