def iddp_rid(eps, m, n, matvect): """ Compute ID of a real matrix to a specified relative precision using random matrix-vector multiplication. :param eps: Relative precision. :type eps: float :param m: Matrix row dimension. :type m: int :param n: Matrix column dimension. :type n: int :param matvect: Function to apply the matrix transpose to a vector, with call signature `y = matvect(x)`, where `x` and `y` are the input and output vectors, respectively. :type matvect: function :return: Rank of ID. :rtype: int :return: Column index array. :rtype: :class:`numpy.ndarray` :return: Interpolation coefficients. :rtype: :class:`numpy.ndarray` """ proj = np.empty(m + 1 + 2*n*(min(m, n) + 1), order='F') k, idx, proj, ier = _id.iddp_rid(eps, m, n, matvect, proj) if ier != 0: raise _RETCODE_ERROR proj = proj[:k*(n-k)].reshape((k, n-k), order='F') return k, idx, proj
def iddp_rid(eps, m, n, matvect): """ Compute ID of a real matrix to a specified relative precision using random matrix-vector multiplication. :param eps: Relative precision. :type eps: float :param m: Matrix row dimension. :type m: int :param n: Matrix column dimension. :type n: int :param matvect: Function to apply the matrix transpose to a vector, with call signature `y = matvect(x)`, where `x` and `y` are the input and output vectors, respectively. :type matvect: function :return: Rank of ID. :rtype: int :return: Column index array. :rtype: :class:`numpy.ndarray` :return: Interpolation coefficients. :rtype: :class:`numpy.ndarray` """ proj = np.empty(m + 1 + 2*n*(min(m, n) + 1), order='F') k, idx, proj, ier = _id.iddp_rid(eps, m, n, matvect, proj) if ier != 0: raise _RETCODE_ERROR proj = proj[:k*(n-k)].reshape((k, n-k), order='F') return k, idx, proj