Copy new tests from #1290

Also fix CSV precision bug in matrix outputs

Author: WardBrian

src/cmdstan/stansummary_helper.hpp

@@ -557,10 +557,7 @@ void write_all_model_params(const stan::mcmc::chainset &chains,
         if (as_csv) {
           *out << "\"" << chains.param_name(row_maj_index_chains) << "\"";
           for (int j = 0; j < params.cols(); j++) {
-            *out << "," << std::fixed
-                 << std::setprecision(compute_precision(
-                        params(row_maj_index, j), sig_figs, false))
-                 << params(row_maj_index, j);
+            *out << "," << params(row_maj_index, j);
           }
         } else {
           *out << std::setw(max_name_length + 1) << std::left

src/test/interface/example_output/matrix_summary.csv

@@ -0,0 +1,23 @@
+name,Mean,MCSE,StdDev,MAD,5%,50%,95%,ESS_bulk,ESS_tail,R_hat
+"lp__",-15.3787,1.17576,3.71807,0.779848,-20.9245,-14.8305,-12.6946,5,5,1.31109
+"accept_stat__",0.68789,0.0961912,0.304183,0.252626,0.208269,0.779947,0.989055,5,5,1.05408
+"stepsize__",0.894277,nan,1.17028e-16,0,0.894277,0.894277,0.894277,nan,nan,nan
+"treedepth__",0.9,0.1,0.316228,0,0.45,1,1,nan,nan,nan
+"x[1]",0.608916,0.0690549,0.218371,0.108465,0.284524,0.666485,0.866975,5,5,0.905216
+"x[2]",0.479369,0.051013,0.161317,0.164219,0.263389,0.451793,0.686842,5,5,1.00156
+"y[1,1]",0.425556,0.124575,0.393941,0.150819,0.0588995,0.164637,0.926039,5,5,1.431
+"y[1,2]",0.595682,0.0758338,0.239808,0.178212,0.249647,0.663856,0.850511,5,5,1.11989
+"y[1,3]",0.473713,0.104663,0.330973,0.39317,0.0677836,0.483405,0.863312,5,5,0.986085
+"y[2,1]",0.511464,0.0868387,0.274608,0.383569,0.167417,0.487338,0.895304,5,5,1.43105
+"y[2,2]",0.559192,0.0872593,0.275938,0.307409,0.230475,0.525767,0.932888,5,5,0.915761
+"y[2,3]",0.51956,0.0997935,0.315575,0.212694,0.0361943,0.536618,0.930452,5,5,1.32719
+# Inference for Stan model: issue_342_model
+# 1 chains: each with iter=10; warmup=1000; thin=1; 10 iterations saved.
+# 
+# Warmup took 0.23 seconds
+# Sampling took 0.0018 seconds
+# Samples were drawn using hmc with nuts.
+# For each parameter, ESS_bulk and ESS_tail measure the effective sample size 
+for the entire sample (bulk) and for the the .05 and .95 tails (tail), 
+# and R_hat measures the potential scale reduction on split chains.
+At convergence R_hat will be very close to 1.00.

src/test/interface/example_output/matrix_summary.nom

@@ -0,0 +1,27 @@
+Inference for Stan model: issue_342_model
+1 chains: each with iter=10; warmup=1000; thin=1; 10 iterations saved.
+
+Warmup took 0.23 seconds
+Sampling took 0.0018 seconds
+
+                Mean   MCSE   StdDev   MAD     5%   50%   95%  ESS_bulk  ESS_tail  R_hat
+
+lp__             -15    1.2      3.7  0.78    -21   -15   -13       5.0       5.0    1.3
+accept_stat__   0.69  0.096  3.0e-01  0.25   0.21  0.78  0.99       5.0       5.0    1.1
+stepsize__      0.89    nan  1.2e-16  0.00   0.89  0.89  0.89       nan       nan    nan
+treedepth__     0.90   0.10  3.2e-01  0.00   0.45   1.0   1.0       nan       nan    nan
+
+x[1]            0.61  0.069     0.22  0.11   0.28  0.67  0.87       5.0       5.0   0.91
+x[2]            0.48  0.051     0.16  0.16   0.26  0.45  0.69       5.0       5.0    1.0
+y[1,1]          0.43   0.12     0.39  0.15  0.059  0.16  0.93       5.0       5.0    1.4
+y[1,2]          0.60  0.076     0.24  0.18   0.25  0.66  0.85       5.0       5.0    1.1
+y[1,3]          0.47   0.10     0.33  0.39  0.068  0.48  0.86       5.0       5.0   0.99
+y[2,1]          0.51  0.087     0.27  0.38   0.17  0.49  0.90       5.0       5.0    1.4
+y[2,2]          0.56  0.087     0.28  0.31   0.23  0.53  0.93       5.0       5.0   0.92
+y[2,3]          0.52  0.100     0.32  0.21  0.036  0.54  0.93       5.0       5.0    1.3
+
+Samples were drawn using hmc with nuts.
+For each parameter, ESS_bulk and ESS_tail measure the effective sample size 
+for the entire sample (bulk) and for the the .05 and .95 tails (tail), 
+and R_hat measures the potential scale reduction on split chains.
+At convergence R_hat will be very close to 1.00.

src/test/interface/stansummary_test.cpp

@@ -685,3 +685,65 @@ TEST(CommandStansummary, check_csv_output_include_param) {
   if (return_code != 0)
     FAIL();
 }
+
+TEST(CommandStansummary, check_reorder_stats) {
+  std::string path_separator;
+  path_separator.push_back(get_path_separator());
+  std::string csv_file = "src" + path_separator + "test" + path_separator
+                         + "interface" + path_separator + "matrix_output.csv";
+  std::stringstream ss_command;
+  ss_command << "bin" << path_separator << "stansummary " << csv_file;
+  run_command_output out = run_command(ss_command.str());
+  ASSERT_FALSE(out.hasError);
+
+  std::string expected_file = "src" + path_separator + "test" + path_separator
+                              + "interface" + path_separator + "example_output"
+                              + path_separator + "matrix_summary.nom";
+  std::ifstream expected_output(expected_file.c_str());
+  EXPECT_FALSE(expected_output.bad());
+  std::stringstream ss;
+  ss << expected_output.rdbuf();
+  EXPECT_EQ(ss.str(), out.output);
+}
+
+TEST(CommandStansummary, check_reorder_stats_csv) {
+  std::string path_separator;
+  path_separator.push_back(get_path_separator());
+  std::string target_csv_file = "test" + path_separator + "interface"
+                                + path_separator
+                                + "tmp_test_target_csv_file_e.csv";
+  std::string csv_file = "src" + path_separator + "test" + path_separator
+                         + "interface" + path_separator + "matrix_output.csv";
+  std::stringstream ss_command;
+  ss_command << "bin" << path_separator << "stansummary "
+             << "-c " << target_csv_file << " " << csv_file;
+  run_command_output out = run_command(ss_command.str());
+  ASSERT_FALSE(out.hasError);
+
+  std::string expected_file = "src" + path_separator + "test" + path_separator
+                              + "interface" + path_separator + "example_output"
+                              + path_separator + "matrix_summary.csv";
+  std::ifstream expected_output(expected_file.c_str());
+  EXPECT_FALSE(expected_output.bad());
+  std::stringstream ss_expected;
+  ss_expected << expected_output.rdbuf();
+
+  std::ifstream target_stream(target_csv_file.c_str());
+  if (!target_stream.is_open()) {
+    std::cerr << "Failed to open file: " << target_csv_file << "\n";
+    std::cerr << "Error: " << std::strerror(errno) << std::endl;
+    FAIL();
+  }
+  std::stringstream ss_actual;
+  ss_actual << target_stream.rdbuf();
+  target_stream.close();
+
+  EXPECT_EQ(ss_expected.str(), ss_actual.str());
+
+  int return_code = std::remove(target_csv_file.c_str());
+  if (return_code != 0) {
+    std::cerr << "Failed to remove file: " << target_csv_file << "\n";
+    std::cerr << "Error: " << std::strerror(errno) << std::endl;
+    FAIL();
+  }
+}