Apply the Cholesky square root of the covariance matrix to the input vector or matrix. Args: r (ndarray[nsamples

Compute and factorize the covariance matrix. Args: x (ndarray[nsamples, ndim]): The independent coordinates of the

Has the processes been computed since the last update of the kernel?

A flag indicating whether or not the covariance matrix was computed and factorized (using the :func:`compute` method).

r""" Compute the inner product of a vector with the inverse of the covariance matrix applied to itself: .. math::

The total number of parameters (including frozen parameters)

Get the dense inverse covariance matrix. This is used for computing gradients, but it is not recommended in general.