class_docstr: QMC sampling from a multivariate Normal :math:`N(\mu, \Sigma)`.
  
  Parameters
  ----------
  mean : array_like (d,)
      The mean vector. Where ``d`` is the dimension.
  cov : array_like (d, d), optional
      The covariance matrix. If omitted, use `cov_root` instead.
      If both `cov` and `cov_root` are omitted, use the identity matrix.
  cov_root : array_like (d, d'), optional
      A root decomposition of the covariance matrix, where ``d'`` may be less
      than ``d`` if the covariance is not full rank. If omitted, use `cov`.
  inv_transform : bool, optional
      If True, use inverse transform instead of Box-Muller. Default is True.
  engine : QMCEngine, optional
      Quasi-Monte Carlo engine sampler. If None, `Sobol` is used.
  seed : {None, int, `numpy.random.Generator`}, optional
      If `seed` is None the `numpy.random.Generator` singleton is used.
      If `seed` is an int, a new ``Generator`` instance is used,
      seeded with `seed`.
      If `seed` is already a ``Generator`` instance then that instance is
      used.
  
  Examples
  --------
  >>> import matplotlib.pyplot as plt
  >>> from scipy.stats import qmc
  >>> engine = qmc.MultivariateNormalQMC(mean=[0, 5], cov=[[1, 0], [0, 1]])
  >>> sample = engine.random(512)
  >>> _ = plt.scatter(sample[:, 0], sample[:, 1])
  >>> plt.show()
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docstr: Reset the engine to base state.
  
  Returns
  -------
  engine : MultivariateNormalQMC
      Engine reset to its base state.
code: def reset(self) -> MultivariateNormalQMC:
      """Reset the engine to base state.
  
      Returns
      -------
      engine : MultivariateNormalQMC
          Engine reset to its base state.
  
      """
      super().reset()
      self.engine.reset()
      return self
  
imports: from __future__ import annotations
  import os
  import copy
  import numbers
  from abc import ABC, abstractmethod
  import math
  from typing import ClassVar, List, Optional, overload, TYPE_CHECKING
  import warnings
  import numpy
  import scipy.stats
  from scipy._lib._util import rng_integers
  from scipy.stats._sobol import initialize_v, _cscramble, _fill_p_cumulative, _draw, _fast_forward, _categorize, initialize_direction_numbers, _MAXDIM, _MAXBIT
  from scipy.stats._qmc_cy import _cy_wrapper_centered_discrepancy, _cy_wrapper_wrap_around_discrepancy, _cy_wrapper_mixture_discrepancy, _cy_wrapper_l2_star_discrepancy, _cy_wrapper_update_discrepancy
label_desc: Use image node_id 3 for calling the MultivariateNormalQMC obj's underlying member method code with example usage: obj.reset() and returns: self