class_docstr: A utility class for PLDA class used for statistics calculations.
  
  This is also used to pack deep embeddings and meta-information in one object.
  
  Arguments
  ---------
  modelset : list
      List of model IDs for each session as an array of strings.
  segset : list
      List of session IDs as an array of strings.
  start : int
      Index of the first frame of the segment.
  stop : int
      Index of the last frame of the segment.
  stat0 : tensor
      An ndarray of float64. Each line contains 0-th order statistics
      from the corresponding session.
  stat1 : tensor
      An ndarray of float64. Each line contains 1-st order statistics
      from the corresponding session.
docstr: Center first order statistics.
  
  Arguments
  ---------
  mu : array
      Array to center on.
docstr_tok: ["Center","first","order","statistics",".","Arguments","--","--","--","--","-","mu",":","array","Array","to","center","on","."]
code: def center_stat1(self, mu):
      """Center first order statistics.
  
      Arguments
      ---------
      mu : array
          Array to center on.
      """
  
      dim = self.stat1.shape[1] / self.stat0.shape[1]
      index_map = numpy.repeat(numpy.arange(self.stat0.shape[1]), dim)
      self.stat1 = self.stat1 - (
          self.stat0[:, index_map] * mu.astype(STAT_TYPE)
      )
  
imports: import numpy
  import copy
  import pickle
  from scipy import linalg
label_desc: Use image node_id 12 for calling the StatObject_SB obj's underlying member method code with example usage: obj.center_stat1(mu) without return types