class_docstr: Generate scale and offset based on running mean and stddev along axis=0
  
  offset = running mean
  scale = 1 / (stddev + 0.1) / 3 (i.e. 3x stddev = +/- 1.0)
docstr: returns 2-tuple: (scale, offset) 
docstr_tok: ["returns","2-tuple",":","(","scale",",","offset",")"]
code: def get(self):
      """returns 2-tuple: (scale, offset)"""
      return 1 / (np.sqrt(self.vars) + 0.1) / 3, self.means
  
imports: import numpy
  import scipy.signal
label_desc: Use image node_id 3 for calling the Scaler obj's underlying member method code with example usage: obj.get() and returns: unknown,  self