code: def _sample_mvn(n_samples, cov, prng):
      """Draw a multivariate normal sample from the graph defined by cov.
  
      Parameters
      -----------
      n_samples : int
  
      cov : matrix of shape (n_features, n_features)
          Covariance matrix of the graph.
  
      prng : np.random.RandomState instance.
      """
      n_features, _ = cov.shape
      return prng.multivariate_normal(
          np.zeros(n_features), cov, size=n_samples
      )
  
file_path: skggm/inverse_covariance/profiling/monte_carlo_profile.py
imports: from __future__ import absolute_import
  import numpy
  from functools import partial
  from sklearn.base import clone
  from joblib import Parallel, delayed
  from .metrics import error_fro
  from .erdos_renyi_graph import ErdosRenyiGraph
  from ..None import QuicGraphicalLasso, QuicGraphicalLassoCV
label_desc: Use image node_id 1 for calling a global function with example usage: _sample_mvn(n_samples, cov, prng) and returns: prng