Seperate out model printout from n_residuals

n_models_store now sets how many models to store (default still n_residual)

src/descriptor_identifier/SISSORegressor.cpp

@@ -9,6 +9,7 @@ SISSORegressor::SISSORegressor(
     std::vector<int> leave_out_inds,
     int n_dim,
     int n_residual,
+    int n_models_store,
     bool fix_intercept
 ):
     _prop(prop),
@@ -24,6 +25,7 @@ SISSORegressor::SISSORegressor(
     _n_samp(prop.size()),
     _n_dim(n_dim),
     _n_residual(n_residual),
+    _n_models_store(n_models_store),
     _lwork(-1),
     _fix_intercept(fix_intercept)
 {
@@ -106,13 +108,15 @@ void SISSORegressor::fit()
     start = std::clock();
 
     std::vector<Model> models;
-    for(int rr = 0; rr < _n_residual; ++rr)
+    for(int rr = 0; rr < std::max(_n_residual, _n_models_store); ++rr)
     {
         node_value_arrs::clear_temp_test_reg();
         model_node_ptr model_feat = std::make_shared<ModelNode>(_feat_space->phi_selected()[rr]->arr_ind(), _feat_space->phi_selected()[rr]->rung(), _feat_space->phi_selected()[rr]->expr(), _feat_space->phi_selected()[rr]->postfix_expr(), _feat_space->phi_selected()[rr]->value(), _feat_space->phi_selected()[rr]->test_value(), _feat_space->phi_selected()[rr]->unit());
         models.push_back(Model(_prop, _prop_test, {model_feat}, _task_sizes_train, _task_sizes_test, _fix_intercept));
+        if(rr < _n_residual)
             models.back().copy_error(&residual[rr * _n_samp]);
-        if(_mpi_comm->rank() == 0)
+
+        if((_mpi_comm->rank() == 0) && (rr < _n_models_store))
         {
             models.back().to_file("models/train_dim_1_model_" + std::to_string(rr) + ".dat");
             if(_leave_out_inds.size() > 0)
@@ -145,7 +149,7 @@ void SISSORegressor::fit()
         {
             std::cout << "Time for l0-norm: " << duration << std::endl;
 
-            for(int rr = 0; rr < _n_residual; ++rr)
+            for(int rr = 0; rr < _n_models_store; ++rr)
             {
                 _models.back()[rr].to_file("models/train_dim_" + std::to_string(dd) + "_model_" + std::to_string(rr) + ".dat");
                 if(_leave_out_inds.size() > 0)
@@ -159,12 +163,13 @@ void SISSORegressor::fit()
 
 void SISSORegressor::l0_norm(std::vector<double>& prop, int n_dim)
 {
+    int  n_get_models = std::max(_n_residual, _n_models_store);
     std::vector<double> coefs(n_dim + 1, 0.0);
 
     std::vector<int> inds(n_dim, 0);
-    std::vector<int> inds_min(_n_residual * _n_dim, -1);
+    std::vector<int> inds_min(n_get_models * _n_dim, -1);
 
-    std::vector<double> min_errors(_n_residual, util_funcs::norm(_prop.data(), _n_samp));
+    std::vector<double> min_errors(n_get_models, util_funcs::norm(_prop.data(), _n_samp));
 
     for(int rr = 0; rr < n_dim; ++rr)
         inds[rr] = _feat_space->phi_selected().size() - 1 - rr;
@@ -192,18 +197,18 @@ void SISSORegressor::l0_norm(std::vector<double>& prop, int n_dim)
         }
     } while(util_funcs::iterate(inds, inds.size(), _mpi_comm->size()));
 
-    std::vector<double> all_min_error(_mpi_comm->size() * _n_residual);
-    std::vector<int> all_inds_min(_mpi_comm->size() *_n_residual * n_dim);
+    std::vector<double> all_min_error(_mpi_comm->size() * n_get_models);
+    std::vector<int> all_inds_min(_mpi_comm->size() * n_get_models * n_dim);
 
-    mpi::all_gather(*_mpi_comm, min_errors.data(), _n_residual, all_min_error);
-    mpi::all_gather(*_mpi_comm, inds_min.data(), _n_residual * n_dim, all_inds_min);
+    mpi::all_gather(*_mpi_comm, min_errors.data(), n_get_models, all_min_error);
+    mpi::all_gather(*_mpi_comm, inds_min.data(), n_get_models * n_dim, all_inds_min);
 
     inds = util_funcs::argsort(all_min_error);
 
     std::vector<model_node_ptr> min_nodes(n_dim);
     std::vector<Model> models;
 
-    for(int rr = 0; rr < _n_residual; ++rr)
+    for(int rr = 0; rr < n_get_models; ++rr)
     {
         node_value_arrs::clear_temp_test_reg();
         for(int ii = 0; ii < n_dim; ++ii)

src/descriptor_identifier/SISSORegressor.hpp

@@ -46,6 +46,7 @@ protected:
     int _n_dim; //!< Number of dimensions to calculate
     int _n_residual; //!< Number of residuals to pass to the next sis model
     int _lwork; //!< size of the work array (for dgels_)
+    int _n_models_store; //!< The number of models to store in files
 
     bool _fix_intercept; //!< If true fix intercept to 0
 public:
@@ -60,9 +61,10 @@ public:
      * @param leave_out_inds  List of indexes from the initial data file in the test set
      * @param n_dim Maximum dimensionality of the generated models
      * @param n_residual Number of residuals to pass to the next SIS operation
+     * @param n_models_store Number of features to store in files
      * @param fix_intrecept If true fix intercept to 0
      */
-    SISSORegressor(std::shared_ptr<FeatureSpace> feat_space, std::vector<double> prop, std::vector<double> prop_test, std::vector<int> task_sizes_train, std::vector<int> task_sizes_test, std::vector<int> leave_out_inds, int n_dim, int n_residual, bool fix_intercept=false);
+    SISSORegressor(std::shared_ptr<FeatureSpace> feat_space, std::vector<double> prop, std::vector<double> prop_test, std::vector<int> task_sizes_train, std::vector<int> task_sizes_test, std::vector<int> leave_out_inds, int n_dim, int n_residual, int n_models_store, bool fix_intercept=false);
 
     /**
      * @brief Get the optimal size of the working array
@@ -159,6 +161,12 @@ public:
      */
     inline int n_residual(){return _n_residual;}
 
+    // DocString: sisso_reg_n_modles_store
+    /**
+     * @brief The number of models to store in output files
+     */
+    inline int n_models_store(){return _n_models_store;}
+
     // Python interface functions
     #ifdef PY_BINDINGS
         /**
@@ -172,6 +180,7 @@ public:
          * @param leave_out_inds  List of indexes from the initial data file in the test set
          * @param n_dim Maximum dimensionality of the generated models
          * @param n_residual Number of residuals to pass to the next SIS operation
+         * @param n_models_store Number of features to store in files
          * @param fix_intrecept If true fix intercept to 0
          */
         SISSORegressor(
@@ -183,6 +192,7 @@ public:
             py::list leave_out_inds,
             int n_dim,
             int n_residual,
+            int n_models_store,
             bool fix_intercept=false
         );
 
@@ -198,6 +208,7 @@ public:
          * @param leave_out_inds  List of indexes from the initial data file in the test set
          * @param n_dim Maximum dimensionality of the generated models
          * @param n_residual Number of residuals to pass to the next SIS operation
+         * @param n_models_store Number of features to store in files
          * @param fix_intrecept If true fix intercept to 0
          */
         SISSORegressor(
@@ -209,6 +220,7 @@ public:
             py::list leave_out_inds,
             int n_dim,
             int n_residual,
+            int n_models_store,
             bool fix_intercept=false
         );
 

src/inputs/InputParser.cpp

@@ -17,6 +17,7 @@ InputParser::InputParser(boost::property_tree::ptree IP, std::string fn, std::sh
     _n_rung_generate(IP.get<int>("n_rung_generate", 0)),
     _n_samp(0),
     _n_residuals(IP.get<int>("n_residual", 1)),
+    _n_models_store(IP.get<int>("n_models_store", _n_residuals)),
     _fix_intercept(IP.get<bool>("fix_intercept", false))
 {
     std::ifstream data_stream;

src/inputs/InputParser.hpp

@@ -60,6 +60,7 @@ public:
     int _n_sis_select; //!< //!< Number of features to select for each dimensions
     int _n_samp; //!< //!< Number of samples (training data)
     int _n_residuals; //!< Number of residuals to pass to the next sis model
+    int _n_models_store; //!< Number of models to store
 
     bool _fix_intercept; //!< If true force intercept to be 0.0
     /**

src/main.cpp

@@ -36,7 +36,7 @@ int main(int argc, char const *argv[])
         std::cout<< "time input_parsing/Feature space generation: "<< duration << std::endl;
 
     node_value_arrs::initialize_d_matrix_arr();
-    SISSORegressor sisso(IP._feat_space, IP._prop_train, IP._prop_test, IP._task_sizes_train, IP._task_sizes_test, IP._leave_out_inds, IP._n_dim, IP._n_residuals, IP._fix_intercept);
+    SISSORegressor sisso(IP._feat_space, IP._prop_train, IP._prop_test, IP._task_sizes_train, IP._task_sizes_test, IP._leave_out_inds, IP._n_dim, IP._n_residuals, IP._n_models_store, IP._fix_intercept);
     sisso.fit();
 
     if(mpi_setup::comm->rank() == 0)
@@ -49,12 +49,6 @@ int main(int argc, char const *argv[])
             else
                 std::cout << std::endl;
             std::cout << sisso.models()[ii][0] << "\n" << std::endl;
-            // for(int jj = 0; jj < sisso.models()[ii].size(); ++jj)
-            // {
-            //     sisso.models()[ii][jj].to_file("models/train_dim_" + std::to_string(ii) + "_model_" + std::to_string(jj) + ".dat");
-            //     if(IP._prop_test.size() > 0)
-            //         sisso.models()[ii][jj].to_file("models/test_dim_" + std::to_string(ii) + "_model_" + std::to_string(jj) + ".dat", false, IP._leave_out_inds);
-            // }
         }
     }
 

src/python/__init__.py

@@ -187,6 +187,7 @@ def generate_fs_sr_from_csv(
     n_sis_select,
     max_dim,
     n_residuals=1,
+    n_model_store=1,
     task_key=None,
     leave_out_frac=0.0,
 ):
@@ -223,5 +224,6 @@ def generate_fs_sr_from_csv(
         leave_out_inds,
         max_dim,
         n_residuals,
+        n_model_store,
     )
     return fs, sr

src/python/bindings_docstring_keyed.cpp

@@ -374,8 +374,8 @@ void sisso::descriptor_identifier::registerModel()
 
 void sisso::descriptor_identifier::registerSISSORegressor()
 {
-    class_<SISSORegressor>("SISSORegressor", init<std::shared_ptr<FeatureSpace>, np::ndarray, np::ndarray, py::list, py::list, py::list, int, int, optional<bool>>())
-        .def(init<std::shared_ptr<FeatureSpace>, py::list, py::list, py::list, py::list, py::list, int, int, optional<bool>>())
+    class_<SISSORegressor>("SISSORegressor", init<std::shared_ptr<FeatureSpace>, np::ndarray, np::ndarray, py::list, py::list, py::list, int, int, int, optional<bool>>())
+        .def(init<std::shared_ptr<FeatureSpace>, py::list, py::list, py::list, py::list, py::list, int, int, int, optional<bool>>())
         .def("fit", &SISSORegressor::fit, "@DocString_sisso_reg_fit@")
         .add_property("prop", &SISSORegressor::prop_py, "@DocString_sisso_reg_prop_py@")
         .add_property("prop_test", &SISSORegressor::prop_test_py, "@DocString_sisso_reg_prop_test_py@")
@@ -383,6 +383,7 @@ void sisso::descriptor_identifier::registerSISSORegressor()
         .add_property("n_samp", &SISSORegressor::n_samp, "@DocString_sisso_reg_n_samp@")
         .add_property("n_dim", &SISSORegressor::n_dim, "@DocString_sisso_reg_n_dim@")
         .add_property("n_residual", &SISSORegressor::n_residual, "@DocString_sisso_reg_n_residual@")
+        .add_property("n_models_store", &SISSORegressor::n_models_store, "@DocString_sisso_reg_n_models_store@")
         .add_property("feat_space", &SISSORegressor::feat_space, "@DocString_sisso_reg_feat_space@")
         .add_property("task_sizes_train", &SISSORegressor::task_sizes_train, "@DocString_sisso_reg_task_sizes_train@")
         .add_property("task_sizes_test", &SISSORegressor::task_sizes_test, "@DocString_sisso_reg_task_sizes_test@")

src/python/descriptor_identifier/SISSORegressor.cpp

@@ -9,6 +9,7 @@ SISSORegressor::SISSORegressor(
     py::list leave_out_inds,
     int n_dim,
     int n_residual,
+    int n_models_store,
     bool fix_intercept
 ) :
     _prop(python_conv_utils::from_ndarray<double>(prop)),
@@ -24,6 +25,7 @@ SISSORegressor::SISSORegressor(
     _n_samp(prop.shape(0)),
     _n_dim(n_dim),
     _n_residual(n_residual),
+    _n_models_store(n_models_store),
     _lwork(-1),
     _fix_intercept(fix_intercept)
 {
@@ -46,6 +48,7 @@ SISSORegressor::SISSORegressor(
     py::list leave_out_inds,
     int n_dim,
     int n_residual,
+    int n_models_store,
     bool fix_intercept
 ) :
     _prop(python_conv_utils::from_list<double>(prop)),
@@ -61,6 +64,7 @@ SISSORegressor::SISSORegressor(
     _n_samp(py::len(prop)),
     _n_dim(n_dim),
     _n_residual(n_residual),
+    _n_models_store(n_models_store),
     _lwork(-1),
     _fix_intercept(fix_intercept)
 {

tests/sisso.json

@@ -2,12 +2,13 @@
     "desc_dim": 2,
     "n_sis_select": 10,
     "max_rung": 2,
-    "n_residual": 10,
+    "n_residual": 1,
     "data_file": "data.csv",
     "property_key": "Prop",
     "task_key": "Task",
     "leave_out_frac": 0.2,
     "n_rung_generate": 0,
+    "n_models_store": 10,
     "leave_out_inds": [],
     "fix_intercept": false,
     "opset": ["add", "sub", "mult", "div", "exp", "inv", "sq", "cb", "sqrt", "cbrt", "abs_diff"]