code: def mv_normal_chol_like(x, mu, sig):
      R
      # TODO: Vectorize in Fortran
      if len(np.shape(x)) > 1:
          return np.sum([flib.chol_mvnorm(r, mu, sig) for r in x])
      else:
          return flib.chol_mvnorm(x, mu, sig)
docs: R"""
      Multivariate normal log-likelihood.
  
      .. math::
          f(x \mid \pi, \sigma) = \frac{1}{(2\pi)^{1/2}|\sigma|)} \exp\left\{ -\frac{1}{2} (x-\mu)^{\prime}(\sigma \sigma^{\prime})^{-1}(x-\mu) \right\}
  
      :Parameters:
        - `x` : (n,k)
        - `mu` : (k) Location parameter.
        - `sigma` : (k,k) Lower triangular matrix.
  
      .. seealso:: :func:`mv_normal_like`, :func:`mv_normal_cov_like`