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: Rotate first-order statistics by a right-product.
  
  Arguments
  ---------
  R : ndarray
      Matrix to use for right product on the first order statistics.
docstr_tok: ["Rotate","first-order","statistics","by","a","right-product",".","Arguments","--","--","--","--","-","R",":","ndarray","Matrix","to","use","for","right","product","on","the","first","order","statistics","."]
code: def rotate_stat1(self, R):
      """Rotate first-order statistics by a right-product.
  
      Arguments
      ---------
      R : ndarray
          Matrix to use for right product on the first order statistics.
      """
      self.stat1 = numpy.dot(self.stat1, R)
  
imports: import numpy
  import copy
  import pickle
  from scipy import linalg
label_desc: Use image node_id 14 for calling the StatObject_SB obj's underlying member method code with example usage: obj.rotate_stat1(R) without return types