code: def _clip_2d(
      X, X_min, X_max, n_samples_X, n_samples_clip, n_timestamps
  ):
      X_clipped = np.empty((n_samples_X, n_samples_clip, n_timestamps))
      for i in prange(n_samples_X):
          X_clipped[i] = np.minimum(np.maximum(X[i], X_min), X_max)
      return X_clipped
  
file_path: pyts/pyts/metrics/lower_bounds.py
imports: import numpy
  from math import sqrt
  from numba import njit, prange
  from sklearn.utils import check_array
label_desc: Use image node_id 9 for calling a global function with example usage: _clip_2d(X, X_min, X_max, n_samples_X, n_samples_clip, n_timestamps) and returns: X_clipped