code: def compute_lcss_return_path(
      x: np.ndarray,
      y: np.ndarray,
      epsilon: float,
      bounding_matrix: np.ndarray,
      cost_matrix: np.ndarray,
  ) -> List[Tuple]:
      """Compute the path from lcss cost matrix.
  
      Parameters
      ----------
      x: np.ndarray (of shape (dimensions, timepoints)
          First time series.
      y: np.ndarray (of shape (dimensions, timepoints)
          Second time series.
      epsilon : float
          Matching threshold to determine if two subsequences are considered close
          enough to be considered 'common'.
      cost_matrix: np.ndarray (of size (n, m) where n is the length of the first time
                      series and m is the length of the second time series)
          The cost matrix used to compute the lcss distance.
      bounding_matrix: np.ndarray (of size (n, m) where n is the length of the first
                      time series and m is the length of the second time series)
          The bounding matrix that restricts the warping path.
  
      Returns
      -------
      list[tuple]
          List containing tuples that is the path through the cost matrix.
      """
      x_size = x.shape[1]
      y_size = y.shape[1]
      dimensions = x.shape[0]
  
      i, j = (x_size, y_size)
      path = []
  
      while i > 0 and j > 0:
          if np.isfinite(bounding_matrix[i - 1, j - 1]):
              curr_dist = 0
              for k in range(dimensions):
                  curr_dist += (x[k][i - 1] - y[k][j - 1]) ** 2
              curr_dist = np.sqrt(curr_dist)
              if curr_dist <= epsilon:
                  path.append((i - 1, j - 1))
                  i, j = (i - 1, j - 1)
              elif cost_matrix[i - 1][j] > cost_matrix[i][j - 1]:
                  i = i - 1
              else:
                  j = j - 1
      return path[::-1]
  
imports: from typing import List, Tuple
  import numpy
  from sktime.utils.numba.njit import njit
label_desc: Use image node_id 3 for calling a global function with example usage: compute_lcss_return_path(x, y, epsilon, bounding_matrix, cost_matrix) and returns: path