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[WIP] initial implementation of sqrt_spd and inv_sqrt_spd #1145

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[WIP] initial implementation of sqrt_spd and inv_sqrt_spd #1145

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73bf8b3
initial implementation of sqrt_spd and inv_sqrt_spd
bgoodri Mar 7, 2019
f85bae9
Updated the input and output types of the sqrt_spd adj_jac_apply (Iss…
bbbales2 Mar 8, 2019
3f5807a
Merge commit '9d0acc533a2c8656e14bc5db4f4da72ee99cf699' into HEAD
yashikno Mar 8, 2019
5480a40
[Jenkins] auto-formatting by clang-format version 6.0.0 (tags/google/…
stan-buildbot Mar 8, 2019
f89b6a5
fix order of headers
bgoodri Mar 8, 2019
ca80605
bump size of test up
bgoodri Mar 8, 2019
2fa0a27
[Jenkins] auto-formatting by clang-format version 6.0.0 (tags/google/…
stan-buildbot Mar 8, 2019
2b1f2fe
add check for NaNs
bgoodri Mar 8, 2019
1751a76
more usage of adj_jac_apply()
bgoodri Mar 10, 2019
a6daa9e
Merge branch 'feature/matrix_sqrt' of https://github.com/stan-dev/mat…
bgoodri Mar 10, 2019
1adbee1
[Jenkins] auto-formatting by clang-format version 5.0.0-3~16.04.1 (ta…
stan-buildbot Mar 10, 2019
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[Jenkins] auto-formatting by clang-format version 5.0.0-3~16.04.1 (ta… 
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stan-buildbot committed Mar 10, 2019
commit 1adbee1b20401a3908a1ba81ded824873d169cb3
2 changes: 1 addition & 1 deletion stan/math/rev/mat/fun/inv_sqrt_spd.hpp
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Expand Up @@ -24,9 +24,9 @@ class inv_sqrt_spd_op {
template <std::size_t size>
Eigen::MatrixXd operator()(const std::array<bool, size> &needs_adj,
const Eigen::MatrixXd &m) {
using Eigen::kroneckerProduct;
using Eigen::MatrixXd;
using Eigen::VectorXd;
using Eigen::kroneckerProduct;
K_ = m.rows();
Eigen::SelfAdjointEigenSolver<MatrixXd> solver(m);
MatrixXd V = solver.eigenvectors();
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2 changes: 1 addition & 1 deletion stan/math/rev/mat/fun/sqrt_spd.hpp
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Original file line number Diff line number Diff line change
Expand Up @@ -24,9 +24,9 @@ class sqrt_spd_op {
template <std::size_t size>
Eigen::MatrixXd operator()(const std::array<bool, size> &needs_adj,
const Eigen::MatrixXd &m) {
using Eigen::kroneckerProduct;
using Eigen::MatrixXd;
using Eigen::VectorXd;
using Eigen::kroneckerProduct;
K_ = m.rows();
Eigen::SelfAdjointEigenSolver<MatrixXd> solver(m);
MatrixXd V = solver.eigenvectors();
Expand Down