[ENH] Added parameters to ACSF optimizer to make the parameters' fitting more flexible.

src/SymmetryFunction/ACSFParametersOptimizer.cpp

@@ -30,19 +30,30 @@ lib4neuro::ACSFParametersOptimizer::ACSFParametersOptimizer(lib4neuro::ErrorFunc
 
 void lib4neuro::ACSFParametersOptimizer::fit_ACSF_parameters(std::vector<SYMMETRY_FUNCTION_PARAMETER>& fitted_params,
                                                              bool random_init_params) {
+    fit_ACSF_parameters(fitted_params,
+                        random_init_params,
+                        30,
+                        10,
+                        1e-5,
+                        0.98,
+                        0.085,
+                        1e-6);
+}
 
+void lib4neuro::ACSFParametersOptimizer::fit_ACSF_parameters(std::vector<SYMMETRY_FUNCTION_PARAMETER>& fitted_params,
+                                                             bool random_init_params,
+                                                             unsigned int main_iterations_num,
+                                                             unsigned int steady_temperature_iters_num,
+                                                             double init_temperature,
+                                                             double temperature_change,
+                                                             double distribution_stddev,
+                                                             double termination_threshold) {
     COUT_INFO("Starting optimizing of ACSF parameters...");
 
     /* Seed the random numbers' generator */
     std::random_device rd{};
     std::mt19937 gen{rd()};
 
-//    GradientDescentBB gd(1e-6,
-//                         1000,
-//                         10000);
-//
-//    LevenbergMarquardt lm(1000);
-
     /* Construct and train a new linear neural network to evaluate the chosen symmetry functions' parameters */
     std::vector<unsigned int> neuron_numbers = {static_cast<unsigned int>(this->net->get_input_neurons_number()), 1};
     std::vector<NEURON_TYPE> type_hidden_neurons = {};
@@ -81,16 +92,16 @@ void lib4neuro::ACSFParametersOptimizer::fit_ACSF_parameters(std::vector<SYMMETR
     double current_error;
     double delta_error;
 
-    double temperature = 3e-4;  //TODO make flexible by adding function parameters
+    double temperature = init_temperature;  //TODO make flexible by adding function parameters
 
     MSE mse_init(&nn, this->data_set);
     previous_error = mse_init.eval();
 
     /* Iteratively improve the parameters */
     unsigned int iter_ind = 0;
-    for(unsigned int i = 0; i < 10; i++) {
+    for(unsigned int i = 0; i < main_iterations_num; i++) {
         /* Temperature iterations */
-        for(unsigned int j = 0; j < 10; j++) {
+        for(unsigned int j = 0; j < steady_temperature_iters_num; j++) {
             /* Change the selected parameters in ACSFs */
             for (auto& el : *this->net->get_elements()) {
                 for (auto& func : *el.second->getSymmetryFunctions()) {
@@ -103,7 +114,7 @@ void lib4neuro::ACSFParametersOptimizer::fit_ACSF_parameters(std::vector<SYMMETR
                                 func->set_parameter(param.first,
                                                     shift_max_vals.at((int) (d_uni(gen))));
                             } else {
-                                std::normal_distribution<> dd{param.second, 0.085};
+                                std::normal_distribution<> dd{param.second, distribution_stddev};
                                 func->set_parameter(param.first,
                                                     dd(gen));
                             }
@@ -124,18 +135,16 @@ void lib4neuro::ACSFParametersOptimizer::fit_ACSF_parameters(std::vector<SYMMETR
             MSE mse(&nn,
                     this->data_set);
 
-//            gd.optimize(mse);
-
             std::vector<double> new_weights = arma::conv_to<std::vector<double>>::from(
                 arma::solve(*this->data_set->get_inputs_matrix(),
-                    *this->data_set->get_outputs_matrix(),
-                    arma::solve_opts::fast));
+                            *this->data_set->get_outputs_matrix(),
+                            arma::solve_opts::fast));
             nn.copy_parameter_space(&new_weights);
 
             current_error = mse.eval();
 
             /* Termination condition */
-            if(current_error < 10e-6) {
+            if(current_error < termination_threshold) {
                 COUT_INFO("Error when optimizing ACSF parameters: " + std::to_string(current_error));
                 return;
             }
@@ -162,10 +171,9 @@ void lib4neuro::ACSFParametersOptimizer::fit_ACSF_parameters(std::vector<SYMMETR
 
             previous_error = current_error;
 
-            std::cout << "it: " << iter_ind << " Delta error: " << delta_error << std::endl;
             iter_ind++;
         }
 
-        temperature *= 0.98;
+        temperature *= temperature_change;
     }
 }

src/SymmetryFunction/ACSFParametersOptimizer.h

@@ -26,6 +26,15 @@ namespace lib4neuro {
 
         LIB4NEURO_API void fit_ACSF_parameters(std::vector<SYMMETRY_FUNCTION_PARAMETER>& fitted_params,
                                                bool random_init_params);
+
+        LIB4NEURO_API void fit_ACSF_parameters(std::vector<SYMMETRY_FUNCTION_PARAMETER>& fitted_params,
+                                               bool random_init_params,
+                                               unsigned int main_iterations_num,
+                                               unsigned int steady_temperature_iters_num,
+                                               double init_temperature,
+                                               double temperature_change,
+                                               double distribution_stddev,
+                                               double termination_threshold);
     };
 }