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