Replace Boost circular_buffer with minimal implementation

src/stan/optimization/lbfgs_update.hpp

@@ -2,7 +2,7 @@
 #define STAN_OPTIMIZATION_LBFGS_UPDATE_HPP
 
 #include <stan/math/prim/fun/Eigen.hpp>
-#include <boost/circular_buffer.hpp>
+#include <stan/util/ring_buffer.hpp>
 #include <tuple>
 #include <vector>
 
@@ -28,7 +28,7 @@ class LBFGSUpdate {
    *
    * @param L New size of buffer.
    **/
-  void set_history_size(size_t L) { _buf.rset_capacity(L); }
+  void set_history_size(size_t L) { _buf.reset_capacity(L); }
 
   /**
    * Add a new set of update vectors to the history.
@@ -72,8 +72,8 @@ class LBFGSUpdate {
    **/
   inline void search_direction(VectorT &pk, const VectorT &gk) const {
     std::vector<Scalar> alphas(_buf.size());
-    typename boost::circular_buffer<UpdateT>::const_reverse_iterator buf_rit;
-    typename boost::circular_buffer<UpdateT>::const_iterator buf_it;
+    typename stan::util::ring_buffer<UpdateT>::const_reverse_iterator buf_rit;
+    typename stan::util::ring_buffer<UpdateT>::const_iterator buf_it;
     typename std::vector<Scalar>::const_iterator alpha_it;
     typename std::vector<Scalar>::reverse_iterator alpha_rit;
 
@@ -103,7 +103,7 @@ class LBFGSUpdate {
   }
 
  protected:
-  boost::circular_buffer<UpdateT> _buf;
+  stan::util::ring_buffer<UpdateT> _buf;
   Scalar _gammak;
 };
 }  // namespace optimization

src/stan/services/pathfinder/single.hpp

@@ -12,7 +12,7 @@
 #include <stan/services/util/initialize.hpp>
 #include <stan/services/util/create_rng.hpp>
 #include <stan/services/util/duration_diff.hpp>
-#include <boost/circular_buffer.hpp>
+#include <stan/util/ring_buffer.hpp>
 #include <tbb/parallel_for.h>
 #include <tbb/concurrent_queue.h>
 #include <tbb/task_group.h>
@@ -659,8 +659,8 @@ inline auto pathfinder_lbfgs_single(
                 + std::to_string(lbfgs.logp()));
   }
   int ret = 0;
-  boost::circular_buffer<Eigen::VectorXd> param_buff(max_history_size);
-  boost::circular_buffer<Eigen::VectorXd> grad_buff(max_history_size);
+  stan::util::ring_buffer<Eigen::VectorXd> param_buff(max_history_size);
+  stan::util::ring_buffer<Eigen::VectorXd> grad_buff(max_history_size);
   Eigen::VectorXd prev_params
       = Eigen::Map<Eigen::VectorXd>(cont_vector.data(), cont_vector.size());
   std::size_t history_size = 0;