Fixed order of updated inverse metric with stepsize (Issue #2881)

Author: bbbales2

src/stan/mcmc/hmc/nuts/adapt_dense_e_nuts.hpp

@@ -35,10 +35,10 @@ class adapt_dense_e_nuts : public dense_e_nuts<Model, BaseRNG>,
           = this->covar_adaptation_.learn_covariance(inv_metric, this->z_.q);
 
       if (update) {
-        this->init_stepsize(logger);
-
         this->z_.set_inv_metric(inv_metric);
 
+        this->init_stepsize(logger);
+
         this->stepsize_adaptation_.set_mu(log(10 * this->nom_epsilon_));
         this->stepsize_adaptation_.restart();
       }

src/stan/mcmc/hmc/nuts/adapt_diag_e_nuts.hpp

@@ -35,10 +35,10 @@ class adapt_diag_e_nuts : public diag_e_nuts<Model, BaseRNG>,
           = this->var_adaptation_.learn_variance(inv_metric, this->z_.q);
 
       if (update) {
-        this->init_stepsize(logger);
-
         this->z_.set_inv_metric(inv_metric);
 
+        this->init_stepsize(logger);
+
         this->stepsize_adaptation_.set_mu(log(10 * this->nom_epsilon_));
         this->stepsize_adaptation_.restart();
       }

src/stan/mcmc/hmc/nuts_classic/adapt_dense_e_nuts_classic.hpp

@@ -35,10 +35,10 @@ class adapt_dense_e_nuts_classic : public dense_e_nuts_classic<Model, BaseRNG>,
           = this->covar_adaptation_.learn_covariance(inv_metric, this->z_.q);
 
       if (update) {
-        this->init_stepsize(logger);
-
         this->z_.set_inv_metric(inv_metric);
 
+        this->init_stepsize(logger);
+
         this->stepsize_adaptation_.set_mu(log(10 * this->nom_epsilon_));
         this->stepsize_adaptation_.restart();
       }

src/stan/mcmc/hmc/nuts_classic/adapt_diag_e_nuts_classic.hpp

@@ -36,10 +36,10 @@ class adapt_diag_e_nuts_classic : public diag_e_nuts_classic<Model, BaseRNG>,
           = this->var_adaptation_.learn_variance(inv_metric, this->z_.q);
 
       if (update) {
-        this->init_stepsize(logger);
-
         this->z_.set_inv_metric(inv_metric);
 
+        this->init_stepsize(logger);
+
         this->stepsize_adaptation_.set_mu(log(10 * this->nom_epsilon_));
         this->stepsize_adaptation_.restart();
       }

src/stan/mcmc/hmc/static/adapt_dense_e_static_hmc.hpp

@@ -38,10 +38,10 @@ class adapt_dense_e_static_hmc : public dense_e_static_hmc<Model, BaseRNG>,
           = this->covar_adaptation_.learn_covariance(inv_metric, this->z_.q);
 
       if (update) {
-        this->init_stepsize(logger);
-        this->update_L_();
         this->z_.set_inv_metric(inv_metric);
 
+        this->init_stepsize(logger);
+        this->update_L_();
         this->stepsize_adaptation_.set_mu(log(10 * this->nom_epsilon_));
         this->stepsize_adaptation_.restart();
       }

src/stan/mcmc/hmc/static/adapt_diag_e_static_hmc.hpp

@@ -38,10 +38,10 @@ class adapt_diag_e_static_hmc : public diag_e_static_hmc<Model, BaseRNG>,
           = this->var_adaptation_.learn_variance(inv_metric, this->z_.q);
 
       if (update) {
-        this->init_stepsize(logger);
-        this->update_L_();
         this->z_.set_inv_metric(inv_metric);
 
+        this->init_stepsize(logger);
+        this->update_L_();
         this->stepsize_adaptation_.set_mu(log(10 * this->nom_epsilon_));
         this->stepsize_adaptation_.restart();
       }

src/stan/mcmc/hmc/static_uniform/adapt_dense_e_static_uniform.hpp

@@ -37,10 +37,10 @@ class adapt_dense_e_static_uniform
           = this->covar_adaptation_.learn_covariance(inv_metric, this->z_.q);
 
       if (update) {
-        this->init_stepsize(logger);
-
         this->z_.set_inv_metric(inv_metric);
 
+        this->init_stepsize(logger);
+
         this->stepsize_adaptation_.set_mu(log(10 * this->nom_epsilon_));
         this->stepsize_adaptation_.restart();
       }

src/stan/mcmc/hmc/static_uniform/adapt_diag_e_static_uniform.hpp

@@ -36,10 +36,10 @@ class adapt_diag_e_static_uniform
       bool update
           = this->var_adaptation_.learn_variance(inv_metric, this->z_.q);
       if (update) {
-        this->init_stepsize(logger);
-
         this->z_.set_inv_metric(inv_metric);
 
+        this->init_stepsize(logger);
+
         this->stepsize_adaptation_.set_mu(log(10 * this->nom_epsilon_));
         this->stepsize_adaptation_.restart();
       }

src/stan/mcmc/hmc/xhmc/adapt_dense_e_xhmc.hpp

@@ -35,10 +35,10 @@ class adapt_dense_e_xhmc : public dense_e_xhmc<Model, BaseRNG>,
           = this->covar_adaptation_.learn_covariance(inv_metric, this->z_.q);
 
       if (update) {
-        this->init_stepsize(logger);
-
         this->z_.set_inv_metric(inv_metric);
 
+        this->init_stepsize(logger);
+
         this->stepsize_adaptation_.set_mu(log(10 * this->nom_epsilon_));
         this->stepsize_adaptation_.restart();
       }

src/stan/mcmc/hmc/xhmc/adapt_diag_e_xhmc.hpp

@@ -35,10 +35,10 @@ class adapt_diag_e_xhmc : public diag_e_xhmc<Model, BaseRNG>,
           = this->var_adaptation_.learn_variance(inv_metric, this->z_.q);
 
       if (update) {
-        this->init_stepsize(logger);
-
         this->z_.set_inv_metric(inv_metric);
 
+        this->init_stepsize(logger);
+
         this->stepsize_adaptation_.set_mu(log(10 * this->nom_epsilon_));
         this->stepsize_adaptation_.restart();
       }