MPI warmup auto metric

src/cmdstan/arguments/arg_auto_e.hpp

@@ -0,0 +1,17 @@
+#ifndef CMDSTAN_ARGUMENTS_ARG_AUTO_E_HPP
+#define CMDSTAN_ARGUMENTS_ARG_AUTO_E_HPP
+
+#include <cmdstan/arguments/unvalued_argument.hpp>
+
+namespace cmdstan {
+
+  class arg_auto_e: public unvalued_argument {
+  public:
+    arg_auto_e() {
+      _name = "auto_e";
+      _description = "Euclidean manifold that chooses between dense/diagonal metric at warmup";
+    }
+  };
+
+}
+#endif

src/cmdstan/arguments/arg_max_num_warmup.hpp

@@ -0,0 +1,26 @@
+#ifndef CMDSTAN_ARGUMENTS_ARG_MAX_NUM_WARMUP_HPP
+#define CMDSTAN_ARGUMENTS_ARG_MAX_NUM_WARMUP_HPP
+
+#include <cmdstan/arguments/singleton_argument.hpp>
+
+namespace cmdstan {
+
+  class arg_max_num_warmup: public int_argument {
+  public:
+    arg_max_num_warmup(): int_argument() {
+      _name = "max_num_warmup";
+      _description = "Maximum number of warmup iterations";
+      _validity = "0 <= warmup";
+      _default = "1000";
+      _default_value = 1000;
+      _constrained = true;
+      _good_value = 2.0;
+      _bad_value = -1.0;
+      _value = _default_value;
+    }
+
+    bool is_valid(int value) { return value >= 0; }
+  };
+
+}
+#endif

src/cmdstan/arguments/arg_metric.hpp

@@ -5,6 +5,7 @@
 #include <cmdstan/arguments/arg_unit_e.hpp>
 #include <cmdstan/arguments/arg_diag_e.hpp>
 #include <cmdstan/arguments/arg_dense_e.hpp>
+#include <cmdstan/arguments/arg_auto_e.hpp>
 
 namespace cmdstan {
 
@@ -17,6 +18,7 @@ namespace cmdstan {
       _values.push_back(new arg_unit_e());
       _values.push_back(new arg_diag_e());
       _values.push_back(new arg_dense_e());
+      _values.push_back(new arg_auto_e());
 
       _default_cursor = 1;
       _cursor = _default_cursor;

src/cmdstan/arguments/arg_sample.hpp

@@ -3,6 +3,7 @@
 
 #include <cmdstan/arguments/categorical_argument.hpp>
 #include <cmdstan/arguments/arg_num_samples.hpp>
+#include <cmdstan/arguments/arg_max_num_warmup.hpp>
 #include <cmdstan/arguments/arg_num_warmup.hpp>
 #include <cmdstan/arguments/arg_save_warmup.hpp>
 #include <cmdstan/arguments/arg_thin.hpp>
@@ -18,7 +19,11 @@ namespace cmdstan {
       _description = "Bayesian inference with Markov Chain Monte Carlo";
 
       _subarguments.push_back(new arg_num_samples());
+#ifdef MPI_ADAPTED_WARMUP
+      _subarguments.push_back(new arg_max_num_warmup());
+#else
       _subarguments.push_back(new arg_num_warmup());
+#endif
       _subarguments.push_back(new arg_save_warmup());
       _subarguments.push_back(new arg_thin());
       _subarguments.push_back(new arg_adapt());

src/cmdstan/command.hpp

@@ -27,6 +27,7 @@
 #include <stan/services/optimize/lbfgs.hpp>
 #include <stan/services/optimize/newton.hpp>
 #include <stan/services/sample/fixed_param.hpp>
+#include <stan/services/sample/hmc_nuts_auto_e_adapt.hpp>
 #include <stan/services/sample/hmc_nuts_dense_e.hpp>
 #include <stan/services/sample/hmc_nuts_dense_e_adapt.hpp>
 #include <stan/services/sample/hmc_nuts_diag_e.hpp>
@@ -143,6 +144,10 @@ namespace cmdstan {
     unsigned int cross_chain_window = 0;
     double cross_chain_rhat = 0.0;
     unsigned int cross_chain_ess = 0;
+
+    std::string output_file = dynamic_cast<string_argument*>(parser.arg("output")->arg("file"))->value();
+    std::string diagnostic_file = dynamic_cast<string_argument*>(parser.arg("output")->arg("diagnostic_file"))->value();
+
 #ifdef MPI_ADAPTED_WARMUP
     if (parser.arg("method")->arg("sample")) {
       categorical_argument* adapt = dynamic_cast<categorical_argument*>(parser.arg("method")->arg("sample")->arg("adapt"));
@@ -157,10 +162,8 @@ namespace cmdstan {
         stan::services::util::set_cross_chain_id(id, num_cross_chains);
         id_arg -> set_value(static_cast<int>(id));
 
-        string_argument* ptr_out = dynamic_cast<string_argument*>(parser.arg("output")->arg("file"));
-        std::string f_out = ptr_out -> value();
-        stan::services::util::set_cross_chain_file(f_out, num_cross_chains);
-        ptr_out -> set_value(f_out);
+	stan::services::util::set_cross_chain_file(output_file, num_cross_chains);  
+	stan::services::util::set_cross_chain_file(diagnostic_file, num_cross_chains);
 
         info.set_num_chains(num_cross_chains);
         err.set_num_chains(num_cross_chains);
@@ -176,17 +179,14 @@ namespace cmdstan {
     stan::callbacks::writer init_writer;
     stan::callbacks::interrupt interrupt;
 
-    std::fstream output_stream(dynamic_cast<string_argument*>(parser.arg("output")->arg("file"))->value().c_str(),
-                               std::fstream::out);
+    std::fstream output_stream(output_file.c_str(), std::fstream::out);
 #ifdef MPI_ADAPTED_WARMUP
     stan::callbacks::mpi_stream_writer sample_writer(num_cross_chains, output_stream, "# ");
 #else
     stan::callbacks::stream_writer sample_writer(output_stream, "# ");
 #endif    
 
-
-    std::fstream diagnostic_stream(dynamic_cast<string_argument*>(parser.arg("output")->arg("diagnostic_file"))->value().c_str(),
-                                   std::fstream::out);
+    std::fstream diagnostic_stream(diagnostic_file.c_str(), std::fstream::out);
 #ifdef MPI_ADAPTED_WARMUP
     stan::callbacks::mpi_stream_writer diagnostic_writer(num_cross_chains, diagnostic_stream, "# ");
 #else
@@ -416,7 +416,7 @@ namespace cmdstan {
         if (adapt_engaged == true && num_warmup == 0) {
           info("The number of warmup samples (num_warmup) must be greater than zero if adaptation is enabled.");
           return_code = stan::services::error_codes::CONFIG;
-        } else if (engine->value() == "nuts" && metric->value() == "dense_e" && adapt_engaged == false && metric_supplied == false) {
+        } else if (engine->value() == "nuts" && (metric->value() == "dense_e" || metric->value() == "auto_e") && adapt_engaged == false && metric_supplied == false) {
           int max_depth = dynamic_cast<int_argument*>(dynamic_cast<categorical_argument*>(algo->arg("hmc")->arg("engine")->arg("nuts"))->arg("max_depth"))->value();
           return_code = stan::services::sample::hmc_nuts_dense_e(model,
                                                                  *init_context,
@@ -436,7 +436,7 @@ namespace cmdstan {
                                                                  init_writer,
                                                                  sample_writer,
                                                                  diagnostic_writer);
-        } else if (engine->value() == "nuts" && metric->value() == "dense_e" && adapt_engaged == false && metric_supplied == true) {
+        } else if (engine->value() == "nuts" && (metric->value() == "dense_e" || metric->value() == "auto_e") && adapt_engaged == false && metric_supplied == true) {
           int max_depth = dynamic_cast<int_argument*>(dynamic_cast<categorical_argument*>(algo->arg("hmc")->arg("engine")->arg("nuts"))->arg("max_depth"))->value();
           return_code = stan::services::sample::hmc_nuts_dense_e(model,
                                                                  *init_context,
@@ -495,6 +495,44 @@ namespace cmdstan {
                                                                        init_writer,
                                                                        sample_writer,
                                                                        diagnostic_writer);
+        } else if (engine->value() == "nuts" && metric->value() == "auto_e" && adapt_engaged == true && metric_supplied == false) {
+          int max_depth = dynamic_cast<int_argument*>(dynamic_cast<categorical_argument*>(algo->arg("hmc")->arg("engine")->arg("nuts"))->arg("max_depth"))->value();
+          double delta = dynamic_cast<real_argument*>(adapt->arg("delta"))->value();
+          double gamma = dynamic_cast<real_argument*>(adapt->arg("gamma"))->value();
+          double kappa = dynamic_cast<real_argument*>(adapt->arg("kappa"))->value();
+          double t0 = dynamic_cast<real_argument*>(adapt->arg("t0"))->value();
+          unsigned int init_buffer = dynamic_cast<u_int_argument*>(adapt->arg("init_buffer"))->value();
+          unsigned int term_buffer = dynamic_cast<u_int_argument*>(adapt->arg("term_buffer"))->value();
+          unsigned int window = dynamic_cast<u_int_argument*>(adapt->arg("window"))->value();
+          return_code = stan::services::sample::hmc_nuts_auto_e_adapt(model,
+								      *init_context,
+								      random_seed,
+								      id,
+								      init_radius,
+                                                                      num_cross_chains,
+								      cross_chain_window,
+								      cross_chain_rhat,
+								      cross_chain_ess,
+ 								      num_warmup,
+								      num_samples,
+								      num_thin,
+								      save_warmup,
+								      refresh,
+								      stepsize,
+								      stepsize_jitter,
+								      max_depth,
+								      delta,
+								      gamma,
+								      kappa,
+								      t0,
+								      init_buffer,
+								      term_buffer,
+								      window,
+								      interrupt,
+								      logger,
+								      init_writer,
+								      sample_writer,
+								      diagnostic_writer);
         } else if (engine->value() == "nuts" && metric->value() == "dense_e" && adapt_engaged == true && metric_supplied == true) {
           int max_depth = dynamic_cast<int_argument*>(dynamic_cast<categorical_argument*>(algo->arg("hmc")->arg("engine")->arg("nuts"))->arg("max_depth"))->value();
           double delta = dynamic_cast<real_argument*>(adapt->arg("delta"))->value();