code: def positive_turning(signal):
      """Computes number of positive turning points of the signal.
  
      Feature computational cost: 1
  
      Parameters
      ----------
      signal : nd-array
          Input from which  positive turning points are counted
  
      Returns
      -------
      float
          Number of positive turning points
  
      """
      diff_sig = np.diff(signal)
  
      array_signal = np.arange(len(diff_sig[:-1]))
  
      positive_turning_pts = np.where(
          (diff_sig[array_signal + 1] < 0)
          & (diff_sig[array_signal] > 0)
      )[0]
  
      return len(positive_turning_pts)
  
imports: import scipy.signal
  from tsfel.feature_extraction.features_utils import *
label_desc: Use image node_id 4 for calling a global function with example usage: positive_turning(signal) and returns: len