diff --git a/src/Solvers/DESolver.cpp b/src/Solvers/DESolver.cpp
index e674c0faffa6b40dd8a5a6dd03d9fab284942418..27d7bd85299d59163238594152116354d6996a7c 100644
--- a/src/Solvers/DESolver.cpp
+++ b/src/Solvers/DESolver.cpp
@@ -72,11 +72,11 @@ namespace lib4neuro {
throw std::invalid_argument(
"Parameters 'm', 'n_equations', 'n_inputs' and 'n_outputs' must be greater than zero!");
}
- printf("Differential Equation Solver with %d equations\n--------------------------------------------------------------------------\n",
- (int) n_equations);
+ std::cout <<"Differential Equation Solver with "<< (int)n_equations <<" equations"<<
+ std::endl <<"--------------------------------------------------------------------------"<<std::endl;
- printf("Constructing NN structure representing the solution [%d input neurons][%d inner neurons]...\n",
- (int) n_inputs, (int) m);
+ std::cout << "Constructing NN structure representing the solution [" << (int)n_inputs << " input neurons]["
+ << (int)m << " inner neurons]..." <<std::endl ;
this->dim_i = n_inputs;
this->dim_inn = m;
@@ -124,18 +124,19 @@ namespace lib4neuro {
for (size_t j = 0; j < this->dim_inn; ++j) {
weight_idx = this->solution->add_connection_simple(first_input_neuron + i, first_inner_neuron + j,
SIMPLE_CONNECTION_TYPE::NEXT_WEIGHT);
- printf(" adding a connection between input neuron %2d[%2d] and inner neuron %2d[%2d], weight index %3d\n",
- (int) i, (int) (first_input_neuron + i), (int) j, (int) (first_inner_neuron + j),
- (int) weight_idx);
- }
+ std::cout << " adding a connection between input neuron " << (int)i << "[" << (int)(first_input_neuron + i) <<
+ "] and inner neuron " << (int)j << "[" << (int)(first_inner_neuron + j) << "], weight index " << (int)weight_idx << std::endl;
+
+ }
}
/* connections between inner neurons and output neurons */
for (size_t i = 0; i < this->dim_inn; ++i) {
weight_idx = this->solution->add_connection_simple(first_inner_neuron + i, first_output_neuron,
SIMPLE_CONNECTION_TYPE::NEXT_WEIGHT);
- printf(" adding a connection between inner neuron %2d[%2d] and output neuron %2d[%2d], weight index %3d\n",
- (int) i, (int) (first_inner_neuron + i), 0, (int) (first_output_neuron), (int) weight_idx);
+ std::cout << " adding a connection between input neuron " << (int)i << "[" << (int)(first_input_neuron + i) <<
+ "] and output neuron 0[" << (int)(first_output_neuron) << "], weight index " << (int)weight_idx << std::endl;
+
}
MultiIndex initial_mi(this->dim_i);
@@ -153,7 +154,7 @@ namespace lib4neuro {
this->errors_functions_types = new std::vector<ErrorFunctionType>(this->n_equations);
this->errors_functions_data_sets = new std::vector<DataSet *>(this->n_equations);
- printf("done\n");
+ std::cout<<"done"<<std::endl;
}
diff --git a/src/tests/DESolver_test.cpp b/src/tests/DESolver_test.cpp
index 74acbac9d27bfe311fd00b3231425405d4161a99..de20352fd55f06b3b91621a4e55dcd45f8269967 100644
--- a/src/tests/DESolver_test.cpp
+++ b/src/tests/DESolver_test.cpp
@@ -97,13 +97,14 @@ BOOST_AUTO_TEST_SUITE(DESolver_test)
BOOST_CHECK_THROW(DESolver(1, 1, 0), std::invalid_argument);
BOOST_CHECK_NO_THROW(DESolver deSolver(1, 1, 1));
- /*boost::test_tools::output_test_stream output;
- {
- cout_redirect guard(output.rdbuf());
- DESolver deSolver(1,1,1,1);
- }
- BOOST_CHECK(output.is_equal("Differential Equation Solver with 1 equations\n--------------------------------------------------------------------------\nConstructing NN structure representing the solution [1 input neurons][1 inner neurons][1 output neurons]...\n adding a connection between input neuron 0 and inner neuron 0, weight index 0\n adding a connection between inner neuron 0 and output neuron 0, weight index 1\ndone\n\n"));
- */
+ //TODO fix it
+ //std::stringstream buffer1;
+ //std::streambuf * old1 = std::cout.rdbuf(buffer1.rdbuf());
+ //DESolver deSolver(1, 1, 1);
+ //std::string text = buffer1.str();
+ //
+ // // BOOST_CHECK(text._Equal("Differential Equation Solver with 1 equations\n--------------------------------------------------------------------------\nConstructing NN structure representing the solution [1 input neurons][1 inner neurons][1 output neurons]...\n adding a connection between input neuron 0 and inner neuron 0, weight index 0\n adding a connection between inner neuron 0 and output neuron 0, weight index 1\ndone\n\n"));
+ //std::cout.rdbuf(old1);
}
/**
@@ -117,26 +118,25 @@ BOOST_AUTO_TEST_SUITE(DESolver_test)
}
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 *deSolver = new DESolver(1,1,1);
+ // MultiIndex *multiIndex = new MultiIndex(2);
+ // multiIndex->set_partial_derivative(0,1);
+ // multiIndex->set_partial_derivative(1,0.5);
- //TODO BUG in NeuralNetworkSUM add_network Exprtwrapper
//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));
+ //
+ // 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()
diff --git a/src/tests/DataSet_test.cpp b/src/tests/DataSet_test.cpp
index f9d6746537f43f84b45cf2ca6e73781c4e630edb..be0f1e4dbbbb38b13855817fa8648dd988566efc 100644
--- a/src/tests/DataSet_test.cpp
+++ b/src/tests/DataSet_test.cpp
@@ -10,11 +10,9 @@
#include "boost_unit_tests_preamble.h"
#include "../DataSet/DataSet.h"
-//#include <cstdio>
-//#include <iostream>
-
-//#include <boost/filesystem.hpp>
+#include <iostream>
+//#include <boost/archive/archive_exception.hpp>
using namespace lib4neuro;
/**
@@ -22,17 +20,7 @@ using namespace lib4neuro;
*/
BOOST_AUTO_TEST_SUITE(DataSet_test)
- struct cout_redirect {
- cout_redirect(std::streambuf *new_buffer)
- : old(std::cout.rdbuf(new_buffer)) {}
-
- ~cout_redirect() {
- std::cout.rdbuf(old);
- }
-
- private:
- std::streambuf *old;
- };
+
/**
* Test of DataSet constructor with filepath parameter
@@ -40,8 +28,9 @@ BOOST_AUTO_TEST_SUITE(DataSet_test)
BOOST_AUTO_TEST_CASE(DataSet_construction_from_file_test) {
//test of exception with non-existing file path
//TODO resolve exception throw
- // DataSet dataSet("file/unknown");
- //BOOST_CHECK_THROW(DataSet dataSet("file unknown"), boost::archive::archive_exception::input_stream_error);
+ //DataSet dataSet("file/unknown");
+
+ //BOOST_CHECK_THROW(DataSet dataSet("file unknown"), std::out_of_range);// boost::archive::archive_exception::input_stream_error);
}
/**
@@ -80,7 +69,6 @@ BOOST_AUTO_TEST_SUITE(DataSet_test)
DataSet dataSet(&data_vec);
//test of equal data
- //TODO out of range, ==
BOOST_CHECK_EQUAL(0, dataSet.get_data()->at(0).first.at(0));
BOOST_CHECK_EQUAL(4, dataSet.get_data()->at(0).second.at(0));
@@ -170,8 +158,7 @@ BOOST_AUTO_TEST_SUITE(DataSet_test)
* Test of print_data method
*/
BOOST_AUTO_TEST_CASE(DataSet_print_data_test) {
- //TODO this test causes problems on windows machines
- /*
+
std::vector<std::pair<std::vector<double>, std::vector<double>>> data_vec;
std::vector<double> inp, out;
@@ -181,18 +168,17 @@ BOOST_AUTO_TEST_SUITE(DataSet_test)
}
data_vec.emplace_back(std::make_pair(inp, out));
-
DataSet dataSet(&data_vec);
-
- boost::test_tools::output_test_stream output;
- {
- cout_redirect guard(output.rdbuf());
- dataSet.print_data();
- }
+ std::stringstream buffer;
+ std::streambuf * old = std::cout.rdbuf(buffer.rdbuf());
+ dataSet.print_data();
+
//Test of correct print of DataSet
- BOOST_CHECK(output.is_equal("0 -> 4 \n"));
- */
+ std::string text = buffer.str();
+ BOOST_CHECK(text._Equal("0 -> 4 \n"));
+ std::cout.rdbuf(old);
+
}
/**
@@ -215,7 +201,6 @@ BOOST_AUTO_TEST_SUITE(DataSet_test)
dataSet.store_text(filename);
//Test of correct file creations
- //BOOST_CHECK(boost::filesystem::exists( "testDataSet" ));
DataSet newDataSet("testDataSet");
diff --git a/src/tests/NeuralNetworkSum_test.cpp b/src/tests/NeuralNetworkSum_test.cpp
index f449a4193c6334320ecd65e561193746446ab5c4..b51aea9721e1d7e090389d95f3b0db6a12fa0de7 100644
--- a/src/tests/NeuralNetworkSum_test.cpp
+++ b/src/tests/NeuralNetworkSum_test.cpp
@@ -58,26 +58,14 @@ BOOST_AUTO_TEST_SUITE(NeuralNetworkSum_test)
mock_network network;
//NeuralNetwork network;
NeuralNetworkSum networkSum;
- std::string po = "x";
- // BOOST_CHECK_NO_THROW(networkSum.add_network(&network, po));
+ std::string po = "f(x,y,z,t) =x+y+z+t";
+ BOOST_CHECK_NO_THROW(networkSum.add_network(&network, po));
}
- BOOST_AUTO_TEST_CASE(NeuralNetworkSum_eval_single_weights_test) {
- Neuron *n1 = new NeuronLinear();
- Neuron *n2 = new NeuronLinear();
- NeuralNetwork network;
- network.add_neuron(n1);
- network.add_neuron(n2);
-
- network.add_connection_simple(0, 1, SIMPLE_CONNECTION_TYPE::UNITARY_WEIGHT, 2.5);
-
- std::vector<size_t> output_neuron_indices(1);
- output_neuron_indices[0] = (size_t) 1;
- network.specify_output_neurons(output_neuron_indices);
-
- std::vector<size_t> input_neuron_indices(1);
- input_neuron_indices[0] = (size_t) 0;
- network.specify_input_neurons(input_neuron_indices);
+ BOOST_AUTO_TEST_CASE(NeuralNetworkSum_eval_single_weights_test) {
+
+ mock_network network;
+ MOCK_EXPECT(network.eval_single);
std::vector<double> input;
input.push_back(1);
@@ -86,28 +74,22 @@ BOOST_AUTO_TEST_SUITE(NeuralNetworkSum_test)
double weights = 5;
NeuralNetworkSum networkSum;
- networkSum.add_network(&network, "2");
+ networkSum.add_network(&network, "f(x) =x");
networkSum.eval_single(input, output);
- BOOST_CHECK_EQUAL(2, output.at(0));
+ BOOST_CHECK_EQUAL(0, output.at(0));
}
-/*
+
BOOST_AUTO_TEST_CASE(NeuralNetworkSum_get_weights_test) {
NeuralNetworkSum networkSum;
BOOST_CHECK_EQUAL(0, networkSum.get_n_weights());
- Neuron *n1 = new NeuronLinear();
- Neuron *n2 = new NeuronLinear();
- NeuralNetwork network;
- network.add_neuron(n1);
- network.add_neuron(n2);
-
- network.add_connection_simple(0, 1, SIMPLE_CONNECTION_TYPE::NEXT_WEIGHT, 2.5);
-
- networkSum.add_network(&network, "2");
+ mock_network network;
+ MOCK_EXPECT(network.get_n_weights).returns(1);
+ networkSum.add_network(&network, "f(x) =x");
BOOST_CHECK_EQUAL(1, networkSum.get_n_weights());
}
-*/
+
BOOST_AUTO_TEST_SUITE_END()
\ No newline at end of file
diff --git a/src/tests/ParticleSwarm_test.cpp b/src/tests/ParticleSwarm_test.cpp
index 5bdd215d22f989078e57299e52834d5c751a985e..4358bdb52d1a90ed200e70a775d27241e7d929c0 100644
--- a/src/tests/ParticleSwarm_test.cpp
+++ b/src/tests/ParticleSwarm_test.cpp
@@ -61,8 +61,6 @@ BOOST_AUTO_TEST_SUITE(ParticleSwarm_test)
MOCK_EXPECT(error.get_dimension).returns(5);
MOCK_EXPECT(error.eval).returns(0.8);
- //MOCK_EXPECT(error.change_coordinate).once.returns(0.2);
- //
ParticleSwarm swarm(&domain_bound, 0, 1, 1, 1, 1, 1, 5, 20);