-added a new test showcasing the use of subnetworks sharing edge weights and...

-added a new test showcasing the use of subnetworks sharing edge weights and multiple error functions in swarm optimization

src/CMakeLists.txt

@@ -34,6 +34,9 @@ target_link_libraries(net_test_1 4neuro)
 add_executable(net_test_2 net_test_2.cpp)
 target_link_libraries(net_test_2 4neuro)
 
+add_executable(net_test_3 net_test_3.cpp)
+target_link_libraries(net_test_3 4neuro)
+
 ##############
 # UNIT TESTS #
 ##############

src/ErrorFunction/ErrorFunctions.h

@@ -72,7 +72,7 @@ public:
      * @param weights
      * @return
      */
-    virtual double eval(double* weights);
+    virtual double eval(double* weights = nullptr);
 
     /**
      *

src/net_test_3.cpp

 /**
  * Example of a set of neural networks sharing some edge weights
- */
+ * The system of equations associated with the net in this example is not regular
+ * minimizes the function: [(2y+0.5)^2 + (2x+y+0.25)^2] / 2 + [(4.5x + 0.37)^2] / 1
+ * minimum [0,010024714] at (x, y) = (-333/4370, -9593/43700) = (-0.076201373, -0.219519451)
+ * */
 
 //
 // Created by martin on 7/16/18.
@@ -17,15 +20,15 @@ int main() {
     std::vector<std::pair<std::vector<double>, std::vector<double>>> data_vec_01, data_vec_02;
     std::vector<double> inp, out;
 
-    inp = {0, 1, 0};
-    out = {0.5, 0};
+    inp = {0, 1};
+    out = {0.5};
     data_vec_01.emplace_back(std::make_pair(inp, out));
 
-    inp = {1, 0.5, 0};
-    out = {0.75, 0};
+    inp = {1, 0.5};
+    out = {0.75};
     data_vec_01.emplace_back(std::make_pair(inp, out));
 
-//    DataSet ds_01(&data_vec_01);
+    DataSet ds_01(&data_vec_01);
 
 
     inp = {1.25};
@@ -101,7 +104,7 @@ int main() {
 
     /* TRAINING METHOD SETUP */
     unsigned int n_edges = 2;
-    unsigned int dim = n_edges, max_iters = 5000;
+    unsigned int dim = n_edges, max_iters = 50;
 
 
     //must encapsulate each of the partial error functions
@@ -109,12 +112,13 @@ int main() {
 
     double c1 = 0.5, c2 = 1.5, w = 0.8;
 
-    unsigned int n_particles = 10;
+    unsigned int n_particles = 100;
 
     ParticleSwarm swarm_01(&mse_sum, domain_bounds, c1, c2, w, n_particles, max_iters);
 
-    swarm_01.optimize(0.5, 0.02);
+    swarm_01.optimize(0.5, 0.02, 0.9);
 
+    printf("evaluation of error: %f\n", mse_sum.eval());
 
     delete subnet_02;
     delete subnet_01;