code: def _log_multivariate_normal_density_spherical(X, means, covars):
      """Compute Gaussian log-density at X for a spherical model."""
      cv = covars.copy()
      if covars.ndim == 1:
          cv = cv[:, np.newaxis]
      if cv.shape[1] == 1:
          cv = np.tile(cv, (1, X.shape[-1]))
      return _log_multivariate_normal_density_diag(X, means, cv)
  
imports: import numpy
  from scipy import linalg
  from time import time
  from ..base import BaseEstimator
  from ..utils import check_random_state, check_array, deprecated
  from ..utils.extmath import logsumexp
  from ..utils.validation import check_is_fitted
  from ..None import cluster
  from sklearn.externals.six.moves import zip
label_desc: Use image node_id 4 for calling a global function with example usage: _log_multivariate_normal_density_spherical(X, means, covars) and returns: _log_multivariate_normal_density_diag