code: def se_cov(cov):
      """
      get standard deviation from covariance matrix
  
      just a shorthand function np.sqrt(np.diag(cov))
  
      Parameters
      ----------
      cov : array_like, square
          covariance matrix
  
      Returns
      -------
      std : ndarray
          standard deviation from diagonal of cov
      """
      return np.sqrt(np.diag(cov))
  
file_path: statsmodels/statsmodels/stats/moment_helpers.py
imports: import numpy
  from scipy.special import comb
label_desc: Use image node_id 14 for calling a global function with example usage: se_cov(cov) and returns: np