code: def zNormalize(ts):
      """
      Returns a z-normalized version of a time series.
  
      Parameters
      ----------
      ts: Time series to be normalized
      """
  
      ts -= np.mean(ts)
      std = np.std(ts)
  
      if std == 0:
          raise ValueError("The Standard Deviation cannot be zero")
      else:
          ts /= std
  
      return ts
  
file_path: matrixprofile-ts/matrixprofile/utils.py
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  from __future__ import unicode_literals
  import numpy
  import numpy.fft
label_desc: Use image node_id 1 for calling a global function with example usage: zNormalize(ts) and returns: ts