[MERGE] Merge with kra568/tmp

src/LearningMethods/LearningMethods.cpp

-/**
- * DESCRIPTION OF THE FILE
- *
- * @author Michal Kravčenko
- * @date 10.9.18 -
- */
 
 #include "LearningMethod.h"
 
 namespace lib4neuro {
+    //TODO NOT SAFE!!!!
     std::vector<double>* LearningMethod::get_parameters() {
         return &this->optimal_parameters;
     }
@@ -17,4 +12,4 @@ namespace lib4neuro {
         this->optimize(ef,
                        ofs);
     }
-}
+}
\ No newline at end of file

src/LearningMethods/ParticleSwarm.cpp

@@ -299,7 +299,7 @@ namespace lib4neuro {
 
 
         /* initialize the particles */
-        for (size_t pi = 0; pi < this->n_particles; ++pi) {
+        for (size_t pi = 0; pi < this->particle_swarm.size(); ++pi) {
             if (this->particle_swarm.at(pi)) {
                 delete this->particle_swarm.at(pi);
             }
@@ -548,9 +548,10 @@ namespace lib4neuro {
         this->w = w;
         this->n_particles = n_particles;
         this->iter_max = iter_max;
+        this->particle_swarm.resize(this->n_particles);
         std::fill(this->particle_swarm.begin(),
                   this->particle_swarm.end(),
                   nullptr);
     }
 
-}
+}
\ No newline at end of file

src/Neuron/NeuronBiased.cpp

-/**
- * DESCRIPTION OF THE FILE
- *
- * @author Michal Kravčenko
- * @date 15.3.19 -
- */
 
 #include <boost/serialization/export.hpp>
 
@@ -40,4 +34,4 @@ namespace lib4neuro {
         return output;
     }
 
-}//end of namespace lib4neuro
+}//end of namespace lib4neuro
\ No newline at end of file

src/Solvers/DESolver.cpp

@@ -91,6 +91,8 @@ namespace lib4neuro {
         this->dim_i = n_inputs;
         this->dim_inn = m;
         this->n_equations = n_equations;
+        this->errors_functions_types.resize(n_equations);
+        this->errors_functions_data_sets.resize(n_equations);
 
 
 

src/examples/net_test_1.cpp

@@ -159,7 +159,6 @@ int main() {
                                   mse);
 
     /* Normalize data to prevent 'nan' results */
-    ds.normalize();
     net.randomize_parameters();
     optimize_via_gradient_descent(net,
                                   mse);

src/examples/net_test_ode_1.cpp

@@ -67,12 +67,17 @@ void optimize_via_particle_swarm(l4n::DESolver& solver,
 void optimize_via_gradient_descent(l4n::DESolver& solver,
                                    double accuracy) {
     printf("Solution via a gradient descent method!\n");
+    solver.randomize_parameters();
+// TODO does not work (poor design of netsum)
+//    l4n::LevenbergMarquardt leven(10000, 0, 1e-6, 1e-6, 1e-6);
+//    solver.solve(leven);
+
+
     l4n::GradientDescent gd(accuracy,
                             1000,
                             500000);
-
-    solver.randomize_parameters();
     solver.solve(gd);
+
 }
 
 void export_solution(size_t n_test_points,

src/examples/net_test_pde_1.cpp

@@ -310,7 +310,7 @@ void test_pde(double accuracy,
     }
     l4n::DataSet ds_t(&data_vec_t);
     l4n::DataSet ds_x(&data_vec_x);
-
+    std::cout << "Train data setup finished" << std::endl;
 
 
 
@@ -324,6 +324,7 @@ void test_pde(double accuracy,
     solver_01.set_error_function(2,
                                  l4n::ErrorFunctionType::ErrorFuncMSE,
                                  &ds_x);
+    std::cout << "Error function defined" << std::endl;
 
     /* Solving the equation */
     optimize_via_particle_swarm(solver_01,
@@ -373,18 +374,18 @@ int main() {
             << "********************************************************************************************************************************************"
             << std::endl;
 
-    unsigned int n_inner_neurons = 4;
-    unsigned int train_size = 50;
+    unsigned int n_inner_neurons = 2;
+    unsigned int train_size = 5;
     double accuracy = 1e-3;
     double ds = 0.0;
     double de = 1.0;
 
-    unsigned int test_size = 100;
+    unsigned int test_size = 10;
     double ts = ds;
     double te = de + 0;
 
-    size_t particle_swarm_max_iters = 1000;
-    size_t n_particles = 50;
+    size_t particle_swarm_max_iters = 10;
+    size_t n_particles = 5;
     test_pde(accuracy,
              n_inner_neurons,
              train_size,

src/examples/x2_fitting.cpp

-
 #include <iostream>
 
 #include "4neuro.h"
@@ -33,4 +32,4 @@ int main() {
     mse.eval_on_data_set(ds.get());
 
     return 0;
-}
+}
\ No newline at end of file