parameters: (self, points_to_sample)
docstring: r"""Compute the cholesky factorization of the variance (matrix) of this GP at each point of ``Xs`` (``points_to_sample``).
  
          ``points_to_sample`` may not contain duplicate points. Violating this results in singular covariance matrices.
  
          :param points_to_sample: num_to_sample points (in dim dimensions) being sampled from the GP
          :type points_to_sample: array of float64 with shape (num_to_sample, dim)
          :return: cholesky factorization of the variance matrix of this GP, lower triangular
          :rtype: array of float64 with shape (num_to_sample, num_to_sample), lower triangle filled in
docstring_summary: r"""Compute the cholesky factorization of the variance (matrix) of this GP at each point of ``Xs`` (``points_to_sample``).
docstring_tokens: r Compute the cholesky factorization of the variance ( matrix ) of this GP at each point of Xs ( points_to_sample ) .
function: def compute_cholesky_variance_of_points(self, points_to_sample):
          r"""Compute the cholesky factorization of the variance (matrix) of this GP at each point of ``Xs`` (``points_to_sample``).
  
          ``points_to_sample`` may not contain duplicate points. Violating this results in singular covariance matrices.
  
          :param points_to_sample: num_to_sample points (in dim dimensions) being sampled from the GP
          :type points_to_sample: array of float64 with shape (num_to_sample, dim)
          :return: cholesky factorization of the variance matrix of this GP, lower triangular
          :rtype: array of float64 with shape (num_to_sample, num_to_sample), lower triangle filled in
  
          """
          pass
function_tokens: def compute_cholesky_variance_of_points ( self , points_to_sample ) : pass