Merge branch 'feature/3299-chainset' of https://github.com/stan-dev/stan

into feature/3299-chainset
stan-dev · Oct 21, 2024 · 32b7fec · 32b7fec
2 parents c38b15f + 199155d
commit 32b7fec
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Showing 4 changed files with 30 additions and 25 deletions.
diff --git a/src/stan/analyze/mcmc/compute_effective_sample_size.hpp b/src/stan/analyze/mcmc/compute_effective_sample_size.hpp
@@ -36,8 +36,9 @@ __attribute__((deprecated))
 #elif defined(_MSC_VER)
 __declspec(deprecated)
 #endif
-inline double compute_effective_sample_size(std::vector<const double*> draws,
-                                            std::vector<size_t> sizes) {
+inline double
+compute_effective_sample_size(std::vector<const double*> draws,
+                              std::vector<size_t> sizes) {
   int num_chains = sizes.size();
   size_t num_draws = sizes[0];
   for (int chain = 1; chain < num_chains; ++chain) {
@@ -170,8 +171,8 @@ __attribute__((deprecated))
 #elif defined(_MSC_VER)
 __declspec(deprecated)
 #endif
-inline double compute_effective_sample_size(std::vector<const double*> draws,
-                                            size_t size) {
+inline double
+compute_effective_sample_size(std::vector<const double*> draws, size_t size) {
   int num_chains = draws.size();
   std::vector<size_t> sizes(num_chains, size);
   return compute_effective_sample_size(draws, sizes);
@@ -203,8 +204,9 @@ __attribute__((deprecated))
 #elif defined(_MSC_VER)
 __declspec(deprecated)
 #endif
-inline double compute_split_effective_sample_size(
-    std::vector<const double*> draws, std::vector<size_t> sizes) {
+inline double
+compute_split_effective_sample_size(std::vector<const double*> draws,
+                                    std::vector<size_t> sizes) {
   int num_chains = sizes.size();
   size_t num_draws = sizes[0];
   for (int chain = 1; chain < num_chains; ++chain) {
@@ -246,8 +248,9 @@ __attribute__((deprecated))
 #elif defined(_MSC_VER)
 __declspec(deprecated)
 #endif
-inline double compute_split_effective_sample_size(
-    std::vector<const double*> draws, size_t size) {
+inline double
+compute_split_effective_sample_size(std::vector<const double*> draws,
+                                    size_t size) {
   int num_chains = draws.size();
   std::vector<size_t> sizes(num_chains, size);
   return compute_split_effective_sample_size(draws, sizes);

diff --git a/src/stan/analyze/mcmc/compute_potential_scale_reduction.hpp b/src/stan/analyze/mcmc/compute_potential_scale_reduction.hpp
@@ -39,8 +39,9 @@ __attribute__((deprecated))
 #elif defined(_MSC_VER)
 __declspec(deprecated)
 #endif
-inline double compute_potential_scale_reduction(
-    std::vector<const double*> draws, std::vector<size_t> sizes) {
+inline double
+compute_potential_scale_reduction(std::vector<const double*> draws,
+                                  std::vector<size_t> sizes) {
   int num_chains = sizes.size();
   size_t num_draws = sizes[0];
   if (num_draws == 0) {
@@ -131,8 +132,9 @@ __attribute__((deprecated))
 #elif defined(_MSC_VER)
 __declspec(deprecated)
 #endif
-inline double compute_potential_scale_reduction(
-    std::vector<const double*> draws, size_t size) {
+inline double
+compute_potential_scale_reduction(std::vector<const double*> draws,
+                                  size_t size) {
   int num_chains = draws.size();
   std::vector<size_t> sizes(num_chains, size);
   return compute_potential_scale_reduction(draws, sizes);
@@ -161,8 +163,9 @@ __attribute__((deprecated))
 #elif defined(_MSC_VER)
 __declspec(deprecated)
 #endif
-inline double compute_split_potential_scale_reduction(
-    std::vector<const double*> draws, std::vector<size_t> sizes) {
+inline double
+compute_split_potential_scale_reduction(std::vector<const double*> draws,
+                                        std::vector<size_t> sizes) {
   int num_chains = sizes.size();
   size_t num_draws = sizes[0];
   for (int chain = 1; chain < num_chains; ++chain) {
@@ -201,8 +204,9 @@ __attribute__((deprecated))
 #elif defined(_MSC_VER)
 __declspec(deprecated)
 #endif
-inline double compute_split_potential_scale_reduction(
-    std::vector<const double*> draws, size_t size) {
+inline double
+compute_split_potential_scale_reduction(std::vector<const double*> draws,
+                                        size_t size) {
   int num_chains = draws.size();
   std::vector<size_t> sizes(num_chains, size);
   return compute_split_potential_scale_reduction(draws, sizes);

diff --git a/src/stan/analyze/mcmc/ess.hpp b/src/stan/analyze/mcmc/ess.hpp
@@ -21,7 +21,7 @@ namespace analyze {
  * which normalizes lag-k autocorrelation estimators by N instead of (N - k),
  * yielding biased but more stable estimators as discussed in Geyer (1992); see
  * https://projecteuclid.org/euclid.ss/1177011137.
- * 
+ *
  * @param chains matrix of draws across all chains
  * @return effective sample size for the specified parameter
  */

diff --git a/src/test/unit/mcmc/chainset_test.cpp b/src/test/unit/mcmc/chainset_test.cpp
@@ -170,8 +170,7 @@ TEST_F(McmcChains, summary_stats) {
   EXPECT_NEAR(theta_sd_expect, bern_chains.sd("theta"), 1e-5);
 
   double theta_mad_expect = 0.12309;
-  EXPECT_NEAR(theta_mad_expect, bern_chains.max_abs_deviation("theta"),
-              1e-5);
+  EXPECT_NEAR(theta_mad_expect, bern_chains.max_abs_deviation("theta"), 1e-5);
 
   double theta_mcse_mean_expect = 0.003234;
   EXPECT_NEAR(theta_mcse_mean_expect, bern_chains.mcse_mean("theta"), 1e-4);
@@ -182,8 +181,8 @@ TEST_F(McmcChains, summary_stats) {
   Eigen::VectorXd probs(6);
   probs << 0.0, 0.01, 0.05, 0.95, 0.99, 1.0;
   Eigen::VectorXd quantiles_expect(6);
-  quantiles_expect << 0.004072, 0.046281, 0.077169, 0.473885,
-      0.574524, 0.698401;
+  quantiles_expect << 0.004072, 0.046281, 0.077169, 0.473885, 0.574524,
+      0.698401;
   Eigen::VectorXd theta_quantiles = bern_chains.quantiles("theta", probs);
   for (size_t i = 0; i < probs.size(); ++i) {
     EXPECT_NEAR(quantiles_expect(i), theta_quantiles(i), 1e-5);
@@ -196,14 +195,13 @@ TEST_F(McmcChains, summary_stats) {
   double theta_ess_bulk_expect = 1407.5124;
   double theta_ess_tail_expect = 1291.7131;
   auto ess = bern_chains.split_rank_normalized_ess("theta");
-  EXPECT_NEAR(theta_ess_bulk_expect, ess.first,  1e-4);
+  EXPECT_NEAR(theta_ess_bulk_expect, ess.first, 1e-4);
   EXPECT_NEAR(theta_ess_tail_expect, ess.second, 1e-4);
 
   // autocorrelation - first 10 lags
   Eigen::VectorXd theta_ac_expect(10);
-  theta_ac_expect << 1.00000, 0.42204, 0.20683,
-      0.08383, 0.037326, 0.02507, 0.02003,
-      0.01347, 0.00476, 0.029495;
+  theta_ac_expect << 1.00000, 0.42204, 0.20683, 0.08383, 0.037326, 0.02507,
+      0.02003, 0.01347, 0.00476, 0.029495;
   auto theta_ac = bern_chains.autocorrelation(0, "theta");
   for (size_t i = 0; i < 10; ++i) {
     EXPECT_NEAR(theta_ac(i), theta_ac_expect(i), 0.0005);