[Jenkins] auto-formatting by clang-format version 6.0.0-1ubuntu2~16.04.1 (tags/RELEASE_600/final)

Author: stan-buildbot

stan/math/rev/functor/cvodes_integrator.hpp

@@ -238,8 +238,8 @@ class cvodes_integrator {
     LS_ = SUNLinSol_Dense(nv_state_, A_, sundials_context_);
 
     if (num_y0_vars_ + num_args_vars_ > 0) {
-      nv_state_sens_ = N_VCloneEmptyVectorArray(
-          num_y0_vars_ + num_args_vars_, nv_state_);
+      nv_state_sens_
+          = N_VCloneEmptyVectorArray(num_y0_vars_ + num_args_vars_, nv_state_);
       for (std::size_t i = 0; i < num_y0_vars_ + num_args_vars_; i++) {
         NV_DATA_S(nv_state_sens_[i]) = &coupled_state_[N_] + i * N_;
       }
@@ -251,8 +251,7 @@ class cvodes_integrator {
     SUNMatDestroy(A_);
     N_VDestroy_Serial(nv_state_);
     if (num_y0_vars_ + num_args_vars_ > 0) {
-      N_VDestroyVectorArray(nv_state_sens_,
-                            num_y0_vars_ + num_args_vars_);
+      N_VDestroyVectorArray(nv_state_sens_, num_y0_vars_ + num_args_vars_);
     }
   }
 

stan/math/rev/functor/cvodes_integrator_adjoint.hpp

@@ -122,21 +122,24 @@ class cvodes_integrator_adjoint_vari : public vari_base {
           state_backward_(Eigen::VectorXd::Zero(N)),
           quad_(Eigen::VectorXd::Zero(num_args_vars)),
           t0_(t0),
-          nv_state_forward_(N_VMake_Serial(N, state_forward_.data(), sundials_context_)),
-          nv_state_backward_(N_VMake_Serial(N, state_backward_.data(), sundials_context_)),
-          nv_quad_(N_VMake_Serial(num_args_vars, quad_.data(), sundials_context_)),
-          nv_absolute_tolerance_forward_(
-              N_VMake_Serial(N, absolute_tolerance_forward_.data(), sundials_context_)),
-          nv_absolute_tolerance_backward_(
-              N_VMake_Serial(N, absolute_tolerance_backward_.data(), sundials_context_)),
+          nv_state_forward_(
+              N_VMake_Serial(N, state_forward_.data(), sundials_context_)),
+          nv_state_backward_(
+              N_VMake_Serial(N, state_backward_.data(), sundials_context_)),
+          nv_quad_(
+              N_VMake_Serial(num_args_vars, quad_.data(), sundials_context_)),
+          nv_absolute_tolerance_forward_(N_VMake_Serial(
+              N, absolute_tolerance_forward_.data(), sundials_context_)),
+          nv_absolute_tolerance_backward_(N_VMake_Serial(
+              N, absolute_tolerance_backward_.data(), sundials_context_)),
           A_forward_(SUNDenseMatrix(N, N, sundials_context_)),
           A_backward_(SUNDenseMatrix(N, N, sundials_context_)),
-          LS_forward_(
-              N == 0 ? nullptr
-                     : SUNLinSol_Dense(nv_state_forward_, A_forward_, sundials_context_)),
-          LS_backward_(
-              N == 0 ? nullptr
-                     : SUNLinSol_Dense(nv_state_backward_, A_backward_, sundials_context_)),
+          LS_forward_(N == 0 ? nullptr
+                             : SUNLinSol_Dense(nv_state_forward_, A_forward_,
+                                               sundials_context_)),
+          LS_backward_(N == 0 ? nullptr
+                              : SUNLinSol_Dense(nv_state_backward_, A_backward_,
+                                                sundials_context_)),
           cvodes_mem_(CVodeCreate(solver_forward, sundials_context_)),
           local_args_tuple_(deep_copy_vars(args)...),
           value_of_args_tuple_(value_of(args)...) {

stan/math/rev/functor/idas_integrator.hpp

@@ -82,7 +82,10 @@ class idas_integrator {
    */
   idas_integrator(const double rtol, const double atol,
                   const int64_t max_num_steps = IDAS_MAX_STEPS)
-      : sundials_context_(), rtol_(rtol), atol_(atol), max_num_steps_(max_num_steps) {
+      : sundials_context_(),
+        rtol_(rtol),
+        atol_(atol),
+        max_num_steps_(max_num_steps) {
     if (rtol_ <= 0) {
       invalid_argument("idas_integrator", "relative tolerance,", rtol_, "",
                        ", must be greater than 0");

stan/math/rev/functor/kinsol_solve.hpp

@@ -72,7 +72,8 @@ Eigen::VectorXd kinsol_solve(const F1& f, const Eigen::VectorXd& x,
   CHECK_KINSOL_CALL(KINInit(kinsol_data.kinsol_memory_,
                             &system_data::kinsol_f_system, kinsol_data.nv_x_));
 
-  N_Vector scaling = N_VNew_Serial(N, kinsol_data.sundials_context_.SUNContext());
+  N_Vector scaling
+      = N_VNew_Serial(N, kinsol_data.sundials_context_.SUNContext());
   N_Vector nv_x = N_VNew_Serial(N, kinsol_data.sundials_context_.SUNContext());
   Eigen::VectorXd x_solution(N);