Add tests for new functions

src/tests/DESolver_test.cpp

@@ -10,7 +10,6 @@
 #include <boost/test/unit_test.hpp>
 #include <iostream>
 #include <boost/test/output_test_stream.hpp>
-
 #include "../Solvers/DESolver.h"
 
 /**
@@ -116,6 +115,26 @@ BOOST_AUTO_TEST_SUITE(DESolver_test)
         BOOST_CHECK_EQUAL(1, network->get_n_outputs());
     }
 
+    BOOST_AUTO_TEST_CASE(DESolver_add_eq_test){
+        DESolver *deSolver = new DESolver(1,1,1);
+        MultiIndex *multiIndex = new MultiIndex(2);
+        multiIndex->set_partial_derivative(0,1);
+        multiIndex->set_partial_derivative(1,0.5);
+
+        deSolver->add_to_differential_equation(0, *multiIndex, 0.5);
+
+        std::vector<double> inp, out;
+        std::vector<std::pair<std::vector<double>, std::vector<double>>> data_vec_dy;
+        inp = {0.0};
+        out = {8.0};
+        data_vec_dy.emplace_back(std::make_pair(inp, out));
+        DataSet ds_02(&data_vec_dy);
 
+        deSolver->set_error_function( 0, ErrorFunctionType::ErrorFuncMSE, &ds_02 );
+
+        std::vector<double> weights;
+        weights.push_back(1.0);
+        BOOST_CHECK_EQUAL(64,deSolver->eval_total_error(weights));
+    }
 
 BOOST_AUTO_TEST_SUITE_END()

src/tests/NeuralNetwork_test.cpp

@@ -13,14 +13,15 @@
 
 struct cerr_redirect {
     cerr_redirect(std::streambuf *new_buffer)
-    : old(std::cerr.rdbuf(new_buffer)
+            : old(std::cerr.rdbuf(new_buffer)
     ) {}
 
     ~cerr_redirect() {
         std::cout.rdbuf(old);
     }
-    private:
-        std::streambuf *old;
+
+private:
+    std::streambuf *old;
 };
 
 /**
@@ -38,7 +39,6 @@ BOOST_AUTO_TEST_SUITE(NeuralNetwork_test)
 
     /**
      * Test of add_neuron method
-     * TODO
      * Existing bias out of range cancelation
      */
     BOOST_AUTO_TEST_CASE(NeuralNetwork_add_neuron_test) {
@@ -47,7 +47,6 @@ BOOST_AUTO_TEST_SUITE(NeuralNetwork_test)
         Neuron *n3 = new NeuronLinear();
         Neuron *n4 = new NeuronLinear();
 
-
         NeuralNetwork network;
 
         //Tests of correct neuron indexs when add_neuron
@@ -56,16 +55,18 @@ BOOST_AUTO_TEST_SUITE(NeuralNetwork_test)
         BOOST_CHECK_EQUAL(1, network.add_neuron(n2, BIAS_TYPE::NEXT_BIAS));
 
         BOOST_CHECK_EQUAL(2, network.add_neuron(n4, BIAS_TYPE::NO_BIAS));
-//TODO fix dumping stack error
-//        boost::test_tools::output_test_stream output;
-//        {
-//            cerr_redirect guard(output.rdbuf());
-//          network.add_neuron(n3, BIAS_TYPE::EXISTING_BIAS, 3);
-//        }
-//        BOOST_CHECK(output.is_equal("The supplied bias index is too large!\n\n"));
 
+        BOOST_CHECK_EQUAL(3, network.get_n_neurons());
 
+        BOOST_CHECK_EQUAL(2, network.get_n_biases());
 
+////TODO fix dumping stack error
+        boost::test_tools::output_test_stream output;
+        {
+            cerr_redirect guard(output.rdbuf());
+          network.add_neuron(n3, BIAS_TYPE::EXISTING_BIAS, 3);
+        }
+        BOOST_CHECK(output.is_equal("The supplied bias index is too large!\n\n"));
     }
 
     /**
@@ -78,12 +79,13 @@ BOOST_AUTO_TEST_SUITE(NeuralNetwork_test)
         network.add_neuron(n1, BIAS_TYPE::NO_BIAS);
         network.add_neuron(n2, BIAS_TYPE::NO_BIAS);
 
-
         BOOST_CHECK_EQUAL(0, network.add_connection_simple(0, 1, SIMPLE_CONNECTION_TYPE::NEXT_WEIGHT));
         BOOST_CHECK_EQUAL(1, network.add_connection_simple(0, 1, SIMPLE_CONNECTION_TYPE::NEXT_WEIGHT, 5));
         BOOST_CHECK_EQUAL(2, network.add_connection_simple(0, 1, SIMPLE_CONNECTION_TYPE::UNITARY_WEIGHT));
-        BOOST_CHECK_EQUAL(3, network.add_connection_simple(0, 1, SIMPLE_CONNECTION_TYPE::UNITARY_WEIGHT,5));
-        BOOST_CHECK_EQUAL(4, network.add_connection_simple(0, 1, SIMPLE_CONNECTION_TYPE::EXISTING_WEIGHT,1));
+        BOOST_CHECK_EQUAL(3, network.add_connection_simple(0, 1, SIMPLE_CONNECTION_TYPE::UNITARY_WEIGHT, 5));
+        BOOST_CHECK_EQUAL(4, network.add_connection_simple(0, 1, SIMPLE_CONNECTION_TYPE::EXISTING_WEIGHT, 1));
+
+        BOOST_CHECK_EQUAL(2, network.get_n_weights());
 //TODO fix dumping stack error
 //        boost::test_tools::output_test_stream output;
 //        {
@@ -91,7 +93,6 @@ BOOST_AUTO_TEST_SUITE(NeuralNetwork_test)
 //            network.add_connection_simple(0, 1, SIMPLE_CONNECTION_TYPE::EXISTING_WEIGHT,10);
 //        }
 //        BOOST_CHECK(output.is_equal("The supplied connection weight index is too large!\n\n"));
-
     }
 
     /**
@@ -108,8 +109,8 @@ BOOST_AUTO_TEST_SUITE(NeuralNetwork_test)
         BOOST_CHECK_EQUAL(0, network.get_n_inputs());
         network.specify_input_neurons(inputs);
         BOOST_CHECK_EQUAL(1, network.get_n_inputs());
-
     }
+
     BOOST_AUTO_TEST_CASE(NeuralNetwork_specify_outputs_neurons_test) {
         NeuralNetwork network;
         Neuron *n1 = new NeuronLinear();
@@ -121,7 +122,6 @@ BOOST_AUTO_TEST_SUITE(NeuralNetwork_test)
         BOOST_CHECK_EQUAL(0, network.get_n_outputs());
         network.specify_output_neurons(outputs);
         BOOST_CHECK_EQUAL(1, network.get_n_outputs());
-
     }
 
     BOOST_AUTO_TEST_CASE(NeuralNetwork_eval_single_test) {
@@ -132,8 +132,7 @@ BOOST_AUTO_TEST_SUITE(NeuralNetwork_test)
         network.add_neuron(n1);
         network.add_neuron(n2);
 
-
-        network.add_connection_simple(0, 1, SIMPLE_CONNECTION_TYPE::UNITARY_WEIGHT , 2.5);
+        network.add_connection_simple(0, 1, SIMPLE_CONNECTION_TYPE::UNITARY_WEIGHT, 2.5);
 
         std::vector<size_t> output_neuron_indices;
         output_neuron_indices.push_back(1);
@@ -150,7 +149,28 @@ BOOST_AUTO_TEST_SUITE(NeuralNetwork_test)
 
         network.eval_single(input, output);
         BOOST_CHECK_EQUAL(5, output.at(0));
+    }
+
+    BOOST_AUTO_TEST_CASE(NeuralNetwork_randomize_weights_test) {
+        Neuron *n1 = new NeuronLinear();
+        Neuron *n2 = new NeuronLinear();
+        NeuralNetwork network;
+        network.add_neuron(n1, BIAS_TYPE::NO_BIAS);
+        network.add_neuron(n2, BIAS_TYPE::NO_BIAS);
+
+        for (int i = 0; i < 100; i++) {
+            network.add_connection_simple(0, 1, SIMPLE_CONNECTION_TYPE::NEXT_WEIGHT);
+        }
+        network.randomize_weights();
+        std::vector<double> *weights = network.get_parameter_ptr_weights();
+
+        double sum=0;
 
+        for (int i = 0; i < 100; i++) {
+            sum += weights->at(i);
+        }
+        sum=sum/100;
+        BOOST_CHECK(sum<0.15 && sum>-0.15);
     }
 
 BOOST_AUTO_TEST_SUITE_END()
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