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Handle rank more carefully in sparse GP solves #332

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Handle rank more carefully in sparse GP solves #332

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4 changes: 3 additions & 1 deletion include/albatross/src/models/sparse_gp.hpp
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Original file line number Diff line number Diff line change
Expand Up @@ -315,6 +315,7 @@ class SparseGaussianProcessRegression
}
B.bottomRows(n_new) = A_ldlt.sqrt_solve(K_fu);
const auto B_qr = B.colPivHouseholderQr();
ALBATROSS_ASSERT(B_qr.rank() == B_qr.cols());

// Form:
// y_aug = |R_old P_old^T v_old|
Expand Down Expand Up @@ -379,8 +380,9 @@ class SparseGaussianProcessRegression
compute_internal_components(u, features, targets, &A_ldlt, &K_uu_ldlt,
&K_fu, &y);
const auto B_qr = compute_sigma_qr(K_uu_ldlt, A_ldlt, K_fu);
ALBATROSS_ASSERT(B_qr.rank() == B_qr.cols());

Eigen::VectorXd y_augmented = Eigen::VectorXd::Zero(B_qr.matrixR().rows());
Eigen::VectorXd y_augmented = Eigen::VectorXd::Zero(B_qr.rows());
if (Base::use_async_) {
y_augmented.topRows(y.size()) = A_ldlt.async_sqrt_solve(y);
} else {
Expand Down
8 changes: 6 additions & 2 deletions include/albatross/src/utils/linalg_utils.hpp
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Expand Up @@ -20,8 +20,10 @@ get_R(const Eigen::ColPivHouseholderQR<Eigen::MatrixXd> &qr) {
// Unfortunately the matrixR() method in Eigen's QR decomposition isn't
// actually the R matrix, it's tall skinny matrix whose lower trapezoid
// contains internal data, only the upper triangular portion is useful
//
// https://eigen.tuxfamily.org/dox/classEigen_1_1ColPivHouseholderQR.html#abe18678c6af88786f2902eeaf2483251
return qr.matrixR()
.topRows(qr.matrixR().cols())
.topLeftCorner(qr.rank(), qr.rank())
.template triangularView<Eigen::Upper>();
}

Expand All @@ -32,7 +34,9 @@ template <typename MatrixType>
inline Eigen::MatrixXd sqrt_solve(const Eigen::MatrixXd &R,
const Eigen::VectorXi &permutation_indices,
const MatrixType &rhs) {

// If `R` is not full-rank, the solve operation below isn't
// well-defined.
ALBATROSS_ASSERT(R.rows() == rhs.rows());
Eigen::MatrixXd sqrt(rhs.rows(), rhs.cols());
for (Eigen::Index i = 0; i < permutation_indices.size(); ++i) {
sqrt.row(i) = rhs.row(permutation_indices.coeff(i));
Expand Down