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: Args:
      obs_dim: dimension of axis=1
docstr_tok: ["Args",":","obs_dim",":","dimension","of","axis=1"]
code: def __init__(self, obs_dim):
      """
      Args:
          obs_dim: dimension of axis=1
      """
      self.vars = np.zeros(obs_dim)
      self.means = np.zeros(obs_dim)
      self.cnt = 0
      self.first_pass = True
  
imports: import numpy
  import scipy.signal
label_desc: Use image node_id 1 to create a new Scaler object from inherited base classes: object with example: obj = Scaler(obs_dim)