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Clang tidy cleanup and using std algorithms #1373

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Clang tidy cleanup and using std algorithms #1373

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b9f545b
Clang tidy with modernize-use-equals-default,readability-braces-aroun…
SteveBronder Sep 30, 2019
4064902
Adds range based for loops via clang tidy, accumulates in log_sum_exp…
SteveBronder Sep 30, 2019
23706ed
[Jenkins] auto-formatting by clang-format version 6.0.0 (tags/google/…
stan-buildbot Sep 30, 2019
bade075
include <numeric> in dot_self header
SteveBronder Sep 30, 2019
8a2dff8
Merge branch 'clang-tidy/braces-defaults_constructor-range_for_loops'…
SteveBronder Sep 30, 2019
2407b7a
copy-pasted an accumulate without changing the variable names from on…
SteveBronder Sep 30, 2019
8bb5458
[Jenkins] auto-formatting by clang-format version 6.0.0 (tags/google/…
stan-buildbot Sep 30, 2019
0c31b37
fix headers
SteveBronder Sep 30, 2019
d68129f
forgot accumulate is in numeric and not algorithm
SteveBronder Sep 30, 2019
f9275d1
test in scal was using unitialized vector?
SteveBronder Sep 30, 2019
06c465a
merge to develop
SteveBronder Oct 8, 2019
bdadd8e
cleanups for promote_elements
SteveBronder Oct 8, 2019
8656836
[Jenkins] auto-formatting by clang-format version 5.0.0-3~16.04.1 (ta…
stan-buildbot Oct 8, 2019
d716461
remove tbb stuff that should be ignored
SteveBronder Oct 8, 2019
3266349
Use auto in gp_exp_quad_cov, add rule of 5 to accumulator, and pass b…
SteveBronder Nov 3, 2019
90be53e
[Jenkins] auto-formatting by clang-format version 6.0.0 (tags/google/…
stan-buildbot Nov 3, 2019
c9fef6c
merge to develop
SteveBronder Nov 5, 2019
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Use auto in gp_exp_quad_cov, add rule of 5 to accumulator, and pass b… 
…y value for log_sum_exp's accumulator with max_val
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@SteveBronder
SteveBronder committed Nov 3, 2019
commit 32663498befabd3272f13fd5e1b67af7e1cfa924
2 changes: 1 addition & 1 deletion stan/math/prim/arr/fun/log_sum_exp.hpp
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Expand Up @@ -32,7 +32,7 @@ inline double log_sum_exp(const std::vector<double>& x) {
double max_val = *std::max_element(x.begin(), x.end());
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This is very neat!

double sum = std::accumulate(
x.begin(), x.end(), 0.0,
[&max_val](auto& acc, auto&& x_i) { return acc + exp(x_i - max_val); });
[max_val](auto& acc, auto&& x_i) { return acc + exp(x_i - max_val); });
return max_val + log(sum);
}

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4 changes: 4 additions & 0 deletions stan/math/prim/mat/fun/accumulator.hpp
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Original file line number Diff line number Diff line change
Expand Up @@ -35,6 +35,10 @@ class accumulator {
* Destroy an accumulator.
*/
~accumulator() = default;
accumulator(const accumulator& other) = default;
accumulator(accumulator&& other) = default;
accumulator& operator=(const accumulator& other) = default;
accumulator& operator=(accumulator&& other) = default;

/**
* Add the specified arithmetic type value to the buffer after
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36 changes: 14 additions & 22 deletions stan/math/prim/mat/fun/gp_exp_quad_cov.hpp
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Original file line number Diff line number Diff line change
Expand Up @@ -38,8 +38,7 @@ namespace internal {
* @return squared distance
*/
template <typename T_x, typename T_sigma, typename T_l>
inline typename Eigen::Matrix<return_type_t<T_x, T_sigma, T_l>, Eigen::Dynamic,
Eigen::Dynamic>
inline auto
gp_exp_quad_cov(const std::vector<T_x> &x, const T_sigma &sigma_sq,
const T_l &neg_half_inv_l_sq) {
using std::exp;
Expand Down Expand Up @@ -70,8 +69,7 @@ gp_exp_quad_cov(const std::vector<T_x> &x, const T_sigma &sigma_sq,
* x is nan or infinite
*/
template <typename T_x, typename T_sigma>
inline typename Eigen::Matrix<return_type_t<T_x, T_sigma>, Eigen::Dynamic,
Eigen::Dynamic>
inline auto
gp_exp_quad_cov(const std::vector<Eigen::Matrix<T_x, -1, 1>> &x,
const T_sigma &sigma_sq) {
using std::exp;
Expand Down Expand Up @@ -107,8 +105,7 @@ gp_exp_quad_cov(const std::vector<Eigen::Matrix<T_x, -1, 1>> &x,
* @return squared distance
*/
template <typename T_x1, typename T_x2, typename T_sigma, typename T_l>
inline typename Eigen::Matrix<return_type_t<T_x1, T_x2, T_sigma, T_l>,
Eigen::Dynamic, Eigen::Dynamic>
inline auto
gp_exp_quad_cov(const std::vector<T_x1> &x1, const std::vector<T_x2> &x2,
const T_sigma &sigma_sq, const T_l &neg_half_inv_l_sq) {
using std::exp;
Expand Down Expand Up @@ -140,8 +137,7 @@ gp_exp_quad_cov(const std::vector<T_x1> &x1, const std::vector<T_x2> &x2,
* @return squared distance
*/
template <typename T_x1, typename T_x2, typename T_s>
inline typename Eigen::Matrix<return_type_t<T_x1, T_x2, T_s>, Eigen::Dynamic,
Eigen::Dynamic>
inline auto
gp_exp_quad_cov(const std::vector<Eigen::Matrix<T_x1, -1, 1>> &x1,
const std::vector<Eigen::Matrix<T_x2, -1, 1>> &x2,
const T_s &sigma_sq) {
Expand Down Expand Up @@ -173,8 +169,7 @@ gp_exp_quad_cov(const std::vector<Eigen::Matrix<T_x1, -1, 1>> &x1,
* x is nan or infinite
*/
template <typename T_x, typename T_sigma, typename T_l>
inline typename Eigen::Matrix<return_type_t<T_x, T_sigma, T_l>, Eigen::Dynamic,
Eigen::Dynamic>
inline auto
gp_exp_quad_cov(const std::vector<T_x> &x, const T_sigma &sigma,
const T_l &length_scale) {
check_positive("gp_exp_quad_cov", "magnitude", sigma);
Expand Down Expand Up @@ -213,8 +208,7 @@ gp_exp_quad_cov(const std::vector<T_x> &x, const T_sigma &sigma,
* x is nan or infinite
*/
template <typename T_x, typename T_sigma, typename T_l>
inline typename Eigen::Matrix<return_type_t<T_x, T_sigma, T_l>, Eigen::Dynamic,
Eigen::Dynamic>
inline auto
gp_exp_quad_cov(const std::vector<Eigen::Matrix<T_x, -1, 1>> &x,
const T_sigma &sigma, const std::vector<T_l> &length_scale) {
check_positive_finite("gp_exp_quad_cov", "magnitude", sigma);
Expand Down Expand Up @@ -256,8 +250,7 @@ gp_exp_quad_cov(const std::vector<Eigen::Matrix<T_x, -1, 1>> &x,
* x is nan or infinite
*/
template <typename T_x1, typename T_x2, typename T_sigma, typename T_l>
inline typename Eigen::Matrix<return_type_t<T_x1, T_x2, T_sigma, T_l>,
Eigen::Dynamic, Eigen::Dynamic>
inline auto
gp_exp_quad_cov(const std::vector<T_x1> &x1, const std::vector<T_x2> &x2,
const T_sigma &sigma, const T_l &length_scale) {
const char *function_name = "gp_exp_quad_cov";
Expand Down Expand Up @@ -305,8 +298,7 @@ gp_exp_quad_cov(const std::vector<T_x1> &x1, const std::vector<T_x2> &x2,
* x is nan or infinite
*/
template <typename T_x1, typename T_x2, typename T_s, typename T_l>
inline typename Eigen::Matrix<return_type_t<T_x1, T_x2, T_s, T_l>,
Eigen::Dynamic, Eigen::Dynamic>
inline auto
gp_exp_quad_cov(const std::vector<Eigen::Matrix<T_x1, -1, 1>> &x1,
const std::vector<Eigen::Matrix<T_x2, -1, 1>> &x2,
const T_s &sigma, const std::vector<T_l> &length_scale) {
Expand Down Expand Up @@ -353,7 +345,7 @@ gp_exp_quad_cov(const std::vector<Eigen::Matrix<T_x1, -1, 1>> &x1,
* x is nan or infinite
*/
template <>
inline Eigen::MatrixXd gp_exp_quad_cov(const std::vector<double> &x,
inline auto gp_exp_quad_cov(const std::vector<double> &x,
const double &sigma,
const double &length_scale) {
const char *function_name = "gp_exp_quad_cov";
Expand Down Expand Up @@ -396,7 +388,7 @@ inline Eigen::MatrixXd gp_exp_quad_cov(const std::vector<double> &x,
* x is nan or infinite
*/
template <>
inline Eigen::MatrixXd gp_exp_quad_cov(const std::vector<Eigen::VectorXd> &x,
inline auto gp_exp_quad_cov(const std::vector<Eigen::VectorXd> &x,
const double &sigma,
const double &length_scale) {
const char *function_name = "gp_exp_quad_cov";
Expand Down Expand Up @@ -440,7 +432,7 @@ inline Eigen::MatrixXd gp_exp_quad_cov(const std::vector<Eigen::VectorXd> &x,
* x is nan or infinite
*/
template <>
inline Eigen::MatrixXd gp_exp_quad_cov(
inline auto gp_exp_quad_cov(
const std::vector<Eigen::VectorXd> &x, const double &sigma,
const std::vector<double> &length_scale) {
const char *function_name = "gp_exp_quad_cov";
Expand Down Expand Up @@ -487,7 +479,7 @@ inline Eigen::MatrixXd gp_exp_quad_cov(
* x is nan or infinite
*/
template <>
inline typename Eigen::MatrixXd gp_exp_quad_cov(const std::vector<double> &x1,
inline auto gp_exp_quad_cov(const std::vector<double> &x1,
const std::vector<double> &x2,
const double &sigma,
const double &length_scale) {
Expand Down Expand Up @@ -538,7 +530,7 @@ inline typename Eigen::MatrixXd gp_exp_quad_cov(const std::vector<double> &x1,
* x is nan or infinite
*/
template <>
inline typename Eigen::MatrixXd gp_exp_quad_cov(
inline auto gp_exp_quad_cov(
const std::vector<Eigen::VectorXd> &x1,
const std::vector<Eigen::VectorXd> &x2, const double &sigma,
const double &length_scale) {
Expand Down Expand Up @@ -594,7 +586,7 @@ inline typename Eigen::MatrixXd gp_exp_quad_cov(
* x is nan or infinite
*/
template <>
inline typename Eigen::MatrixXd gp_exp_quad_cov(
inline auto gp_exp_quad_cov(
const std::vector<Eigen::VectorXd> &x1,
const std::vector<Eigen::VectorXd> &x2, const double &sigma,
const std::vector<double> &length_scale) {
Expand Down
1 change: 1 addition & 0 deletions stan/math/rev/arr/fun/log_sum_exp.hpp
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Expand Up @@ -13,6 +13,7 @@ namespace stan {
namespace math {

namespace internal {
// If we make a vectorized value_of we can just use the prim version here
inline double log_sum_exp_as_double(const std::vector<var>& x) {
using std::exp;
using std::log;
Expand Down
2 changes: 1 addition & 1 deletion stan/math/rev/mat/fun/gp_exp_quad_cov.hpp
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Expand Up @@ -208,7 +208,7 @@ class gp_exp_quad_cov_vari<T_x, double, T_l> : public vari {
* @throw std::domain_error if sigma <= 0, l <= 0, or
* x is nan or infinite
*/
template <typename T_x, typename = enable_if_arithmetic<scalar_type_t<T_x>>>
template <typename T_x, typename = require_arithmetic_t<scalar_type_t<T_x>>>
inline Eigen::Matrix<var, -1, -1> gp_exp_quad_cov(const std::vector<T_x> &x,
const var &sigma,
const var &length_scale) {
Expand Down
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