parameters: (resp, X, nk, means, reg_covar)
return_statement: return _estimate_gaussian_covariances_diag(resp, X, nk,
                                                 means, reg_covar).mean(1)
docstring: Estimate the spherical variance values.
  
      Parameters
      ----------
      responsibilities : array-like, shape (n_samples, n_components)
  
      X : array-like, shape (n_samples, n_features)
  
      nk : array-like, shape (n_components,)
  
      means : array-like, shape (n_components, n_features)
  
      reg_covar : float
  
      Returns
      -------
      variances : array, shape (n_components,)
          The variance values of each components.
docstring_summary: Estimate the spherical variance values.
docstring_tokens: Estimate the spherical variance values .
function: def _estimate_gaussian_covariances_spherical(resp, X, nk, means, reg_covar):
      """Estimate the spherical variance values.
  
      Parameters
      ----------
      responsibilities : array-like, shape (n_samples, n_components)
  
      X : array-like, shape (n_samples, n_features)
  
      nk : array-like, shape (n_components,)
  
      means : array-like, shape (n_components, n_features)
  
      reg_covar : float
  
      Returns
      -------
      variances : array, shape (n_components,)
          The variance values of each components.
      """
      return _estimate_gaussian_covariances_diag(resp, X, nk,
                                                 means, reg_covar).mean(1)
function_tokens: def _estimate_gaussian_covariances_spherical ( resp , X , nk , means , reg_covar ) : return _estimate_gaussian_covariances_diag ( resp , X , nk , means , reg_covar ) . mean ( 1 )