diff --git a/CMakeLists.txt b/CMakeLists.txt
index 1ace6aab70b38909185da8d3115f3d80f10de61e..1ea507921a4155151d0b757eaddd975562368767 100644
--- a/CMakeLists.txt
+++ b/CMakeLists.txt
@@ -21,7 +21,7 @@ if (NOT CMAKE_BUILD_TYPE)
set (CMAKE_BUILD_TYPE RELEASE CACHE STRING
"Choose the type of build, options are: None Debug Release."
FORCE)
-elseif("CMAKE_BUILD_TYPE" STREQUAL "Debug")
+elseif(CMAKE_BUILD_TYPE STREQUAL "Debug")
#TODO rewrite to use add_compile_definitions
endif (NOT CMAKE_BUILD_TYPE)
@@ -84,11 +84,12 @@ message("Boost_INCLUDE_DIRS: ${Boost_INCLUDE_DIRS}")
message("Boost_LIBRARY_DIRS: ${Boost_LIBRARY_DIRS}")
message("Boost_LIBRARIES: ${Boost_LIBRARIES}")
-message("lib4neuro LIB DIR: ${LIB4NEURO_DIR}")
-
find_package(exprtk)
+message("EXPRTK_INCLUDE_DIRS: ${EXPRTK_INCLUDE_DIRS}")
find_package(Turtle)
+message("TURTLE_INCLUDE_DIR: ${TURTLE_INCLUDE_DIR}")
+
#------------------------------------------#
# Detect maximum available number of cores #
diff --git a/external_dependencies/boost b/external_dependencies/boost
index 0792dde1c543aba10d66d634f923e6993f9699d3..35e0ef020057dce87e4ed65d3f34d28e12a0d411 160000
--- a/external_dependencies/boost
+++ b/external_dependencies/boost
@@ -1 +1 @@
-Subproject commit 0792dde1c543aba10d66d634f923e6993f9699d3
+Subproject commit 35e0ef020057dce87e4ed65d3f34d28e12a0d411
diff --git a/src/CSVReader/CSVReader.cpp b/src/CSVReader/CSVReader.cpp
new file mode 100644
index 0000000000000000000000000000000000000000..512ae5fb04fd6865ea97f65471e10b55a3ec2aa4
--- /dev/null
+++ b/src/CSVReader/CSVReader.cpp
@@ -0,0 +1,5 @@
+//
+// Created by martin on 14.11.18.
+//
+
+#include "CSVReader.h"
diff --git a/src/CSVReader/CSVReader.h b/src/CSVReader/CSVReader.h
new file mode 100644
index 0000000000000000000000000000000000000000..f2b8be5ad9984ce2d60e9bd4237f7e771aa83bb6
--- /dev/null
+++ b/src/CSVReader/CSVReader.h
@@ -0,0 +1,8 @@
+//
+// Created by martin on 14.11.18.
+//
+
+#ifndef LIB4NEURO_CSVREADER_H
+#define LIB4NEURO_CSVREADER_H
+
+#endif //LIB4NEURO_CSVREADER_H
diff --git a/src/tests/DESolver_test.cpp b/src/tests/DESolver_test.cpp
index 4f391d9e519a956a009f9b1de427cd7b42661cf9..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);
}
/**
@@ -112,31 +113,30 @@ BOOST_AUTO_TEST_SUITE(DESolver_test)
BOOST_AUTO_TEST_CASE(DESolver_get_solution_test) {
DESolver deSolver(1, 1, 1);
MultiIndex *alpha = new MultiIndex(1);
- NeuralNetwork *network = deSolver.get_solution(*alpha);
- BOOST_CHECK_EQUAL(1, network->get_n_inputs());
- BOOST_CHECK_EQUAL(1, network->get_n_outputs());
+ BOOST_CHECK_EQUAL(1, deSolver.get_solution(*alpha)->get_n_inputs());
+ BOOST_CHECK_EQUAL(1, deSolver.get_solution(*alpha)->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));
+ // 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()
diff --git a/src/tests/DataSet_test.cpp b/src/tests/DataSet_test.cpp
index f9d6746537f43f84b45cf2ca6e73781c4e630edb..ae6679caa26eabb090640ee11b42048970dde054 100644
--- a/src/tests/DataSet_test.cpp
+++ b/src/tests/DataSet_test.cpp
@@ -6,33 +6,34 @@
*/
#define BOOST_TEST_MODULE DataSet_test
-
-#include "boost_unit_tests_preamble.h"
-#include "../DataSet/DataSet.h"
-//#include <cstdio>
-//#include <iostream>
+#ifdef _WINDOWS
+ #include <boost/test/included/unit_test.hpp>
+#else
-//#include <boost/filesystem.hpp>
+ #ifndef BOOST_TEST_DYN_LINK
+ #define BOOST_TEST_DYN_LINK
+ #endif
+
+ #ifndef BOOST_TEST_NO_MAIN
+ #define BOOST_TEST_NO_MAIN
+ #endif
+
+ #include <boost/test/unit_test.hpp>
+ #include <boost/test/output_test_stream.hpp>
+#endif
+
+#include "../DataSet/DataSet.h"
+#include "stdio.h"
+#include <iostream>
-using namespace lib4neuro;
/**
* Boost testing suite for testing DataSet.h
*/
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 +41,9 @@ 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 +82,6 @@ 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 +171,6 @@ 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 +180,17 @@ 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 +213,6 @@ BOOST_AUTO_TEST_SUITE(DataSet_test)
dataSet.store_text(filename);
//Test of correct file creations
- //BOOST_CHECK(boost::filesystem::exists( "testDataSet" ));
DataSet newDataSet("testDataSet");
@@ -226,4 +223,4 @@ BOOST_AUTO_TEST_SUITE(DataSet_test)
remove("testDataSet");
}
-BOOST_AUTO_TEST_SUITE_END()
\ No newline at end of file
+BOOST_AUTO_TEST_SUITE_END()
diff --git a/src/tests/ErrorFunctions_test.cpp b/src/tests/ErrorFunctions_test.cpp
index d05b98d8e45f2b95c7d3e2cea647aaf33a6e194c..74502682d750b53c4a34648ed8d57cb2033c17d2 100644
--- a/src/tests/ErrorFunctions_test.cpp
+++ b/src/tests/ErrorFunctions_test.cpp
@@ -9,9 +9,61 @@
#include "boost_unit_tests_preamble.h"
#include "../ErrorFunction/ErrorFunctions.h"
+#include <turtle/mock.hpp>
using namespace lib4neuro;
+MOCK_BASE_CLASS(mock_network, lib4neuro::NeuralNetwork)
+{
+ MOCK_METHOD(get_subnet, 2)
+ MOCK_METHOD(add_neuron, 3)
+ MOCK_METHOD(add_connection_simple, 4)
+ MOCK_METHOD(add_existing_connection, 4)
+ MOCK_METHOD(copy_parameter_space, 1)
+ MOCK_METHOD(set_parameter_space_pointers, 1)
+ MOCK_METHOD(eval_single, 3)
+ MOCK_METHOD(add_to_gradient_single, 4)
+ MOCK_METHOD(randomize_weights, 0)
+ MOCK_METHOD(randomize_biases, 0)
+ MOCK_METHOD(randomize_parameters, 0)
+ MOCK_METHOD(get_n_inputs, 0)
+ MOCK_METHOD(get_n_outputs, 0)
+ MOCK_METHOD(get_n_weights, 0)
+ MOCK_METHOD(get_n_biases, 0)
+ MOCK_METHOD(get_neuron_bias_index, 1)
+ MOCK_METHOD(get_n_neurons, 0)
+ MOCK_METHOD(specify_input_neurons, 1)
+ MOCK_METHOD(specify_output_neurons, 1)
+ MOCK_METHOD(get_parameter_ptr_biases, 0)
+ MOCK_METHOD(get_parameter_ptr_weights, 0)
+ MOCK_METHOD(save_text, 1)
+ MOCK_METHOD(print_stats, 0)
+ MOCK_METHOD(print_weights, 0)
+};
+
+MOCK_BASE_CLASS(mock_error_fun, lib4neuro::ErrorFunction) {
+ MOCK_METHOD(eval, 1)
+ MOCK_METHOD(calculate_error_gradient, 3)
+ MOCK_METHOD(get_parameters, 0)
+ MOCK_METHOD(get_dataset, 0)
+ MOCK_METHOD(get_dimension,0)
+};
+
+MOCK_BASE_CLASS(mock_dataSet, lib4neuro::DataSet)
+{
+ // MOCK_CONSTRUCTOR( mock_dataSet, 4, (int, int, int, int), inde)
+ MOCK_CONSTRUCTOR_TPL( mock_dataSet, 1, (std::vector<std::pair<std::vector<double>, std::vector<double>>>), identifier2)
+ MOCK_METHOD(add_data_pair, 2)
+ MOCK_METHOD(get_n_elements, 0)
+ MOCK_METHOD(get_input_dim, 0)
+ MOCK_METHOD(get_output_dim, 0)
+ MOCK_METHOD(print_data, 0)
+ MOCK_METHOD(store_text, 1)
+
+};
+
+
+
/**
* Boost testing suite for testing ErrorFunction.h
* doesn't test inherited methods
@@ -19,22 +71,26 @@ using namespace lib4neuro;
BOOST_AUTO_TEST_SUITE(ErrorFunctions_test);
BOOST_AUTO_TEST_CASE(ErrorFunction_MSE_Construction_Test) {
- NeuralNetwork network;
- std::vector<std::pair<std::vector<double>, std::vector<double>>> data_vec;
- std::vector<double> inp, out;
- for (int i = 0; i < 3; i++) {
- inp.push_back(i);
- out.push_back(i + 4);
- }
- data_vec.emplace_back(std::make_pair(inp, out));
- DataSet dataSet(&data_vec);
- BOOST_CHECK_NO_THROW(MSE mse(&network, &dataSet));
+ mock_network network;
+ MOCK_EXPECT(network.get_n_biases).returns(1);
+ MOCK_EXPECT(network.get_n_weights).returns(1);
+ 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);
+
+ //mock_dataSet dataSet(data_vec_dy);
+ //MOCK_EXPECT(dataSet.identifier2);
+ BOOST_CHECK_NO_THROW(MSE mse(&network, &ds_02));
}
BOOST_AUTO_TEST_CASE(ErrorFunction_MSE_Eval_Test) {
- Neuron *n1 = new NeuronLinear();
- Neuron *n2 = new NeuronLinear();
- NeuralNetwork network;
+ mock_network network;
+ MOCK_EXPECT(network.get_n_biases).returns(1);
+ MOCK_EXPECT(network.get_n_weights).returns(1);
+ MOCK_EXPECT(network.eval_single);
std::vector<std::pair<std::vector<double>, std::vector<double>>> data_vec;
std::vector<double> inp, out;
for (int i = 0; i < 1; i++) {
@@ -42,16 +98,6 @@ BOOST_AUTO_TEST_SUITE(ErrorFunctions_test);
out.push_back(i + 4);
}
data_vec.emplace_back(std::make_pair(inp, out));
- network.add_neuron(n1);
- network.add_neuron(n2);
- network.add_connection_simple(0, 1, SIMPLE_CONNECTION_TYPE::UNITARY_WEIGHT, 2.5);
- network.randomize_weights();
- std::vector<size_t> net_input_neurons_indices(1);
- std::vector<size_t> net_output_neurons_indices(1);
- net_input_neurons_indices[0] = 0;
- net_output_neurons_indices[0] = 1;
- network.specify_input_neurons(net_input_neurons_indices);
- network.specify_output_neurons(net_output_neurons_indices);
DataSet dataSet(&data_vec);
@@ -60,13 +106,13 @@ BOOST_AUTO_TEST_SUITE(ErrorFunctions_test);
MSE mse(&network, &dataSet);
- BOOST_CHECK_EQUAL(9, mse.eval(&weights));
+ BOOST_CHECK_EQUAL(16, mse.eval(&weights));
}
-
+
BOOST_AUTO_TEST_CASE(ErrorFunction_MSE_Get_dimension_test) {
- Neuron *n1 = new NeuronLinear();
- Neuron *n2 = new NeuronLinear();
- NeuralNetwork network;
+ mock_network network;
+ MOCK_EXPECT(network.get_n_biases).returns(1);
+ MOCK_EXPECT(network.get_n_weights).returns(1);
std::vector<std::pair<std::vector<double>, std::vector<double>>> data_vec;
std::vector<double> inp, out;
for (int i = 0; i < 1; i++) {
@@ -74,17 +120,7 @@ BOOST_AUTO_TEST_SUITE(ErrorFunctions_test);
out.push_back(i + 4);
}
data_vec.emplace_back(std::make_pair(inp, out));
- network.add_neuron(n1);
- network.add_neuron(n2);
- network.add_connection_simple(0, 1, SIMPLE_CONNECTION_TYPE::UNITARY_WEIGHT, 2.5);
- network.randomize_weights();
- std::vector<size_t> net_input_neurons_indices(1);
- std::vector<size_t> net_output_neurons_indices(1);
- net_input_neurons_indices[0] = 0;
- net_output_neurons_indices[0] = 1;
- network.specify_input_neurons(net_input_neurons_indices);
- network.specify_output_neurons(net_output_neurons_indices);
-
+
DataSet dataSet(&data_vec);
MSE mse(&network, &dataSet);
@@ -95,94 +131,44 @@ BOOST_AUTO_TEST_SUITE(ErrorFunctions_test);
BOOST_AUTO_TEST_CASE(ErrorFunction_MSE_SUM_Construction_Test) {
BOOST_CHECK_NO_THROW(ErrorSum mse_sum);
}
-
+
BOOST_AUTO_TEST_CASE(ErrorFunction_MSE_SUM_Add_Error_Function_Test) {
- NeuralNetwork network;
- std::vector<std::pair<std::vector<double>, std::vector<double>>> data_vec;
- std::vector<double> inp, out;
- for (int i = 0; i < 3; i++) {
- inp.push_back(i);
- out.push_back(i + 4);
- }
- data_vec.emplace_back(std::make_pair(inp, out));
- DataSet dataSet(&data_vec);
-
- ErrorFunction *f = new MSE(&network, &dataSet);
-
+
+ mock_error_fun f;
+ MOCK_EXPECT(f.get_dimension).returns(1);
ErrorSum mse_sum;
- BOOST_CHECK_NO_THROW(mse_sum.add_error_function(f));
+ BOOST_CHECK_NO_THROW(mse_sum.add_error_function(&f, 1));
}
-
+
BOOST_AUTO_TEST_CASE(ErrorFunction_MSE_SUM_Eval_Test) {
- ErrorSum mse_sum;
-
- Neuron *n1 = new NeuronLinear();
- Neuron *n2 = new NeuronLinear();
- NeuralNetwork network;
- std::vector<std::pair<std::vector<double>, std::vector<double>>> data_vec;
- std::vector<double> inp, out;
- for (int i = 0; i < 1; i++) {
- inp.push_back(i);
- out.push_back(i + 4);
- }
- data_vec.emplace_back(std::make_pair(inp, out));
- network.add_neuron(n1);
- network.add_neuron(n2);
- network.add_connection_simple(0, 1, SIMPLE_CONNECTION_TYPE::UNITARY_WEIGHT, 2.5);
- network.randomize_weights();
- std::vector<size_t> net_input_neurons_indices(1);
- std::vector<size_t> net_output_neurons_indices(1);
- net_input_neurons_indices[0] = 0;
- net_output_neurons_indices[0] = 1;
- network.specify_input_neurons(net_input_neurons_indices);
- network.specify_output_neurons(net_output_neurons_indices);
-
- DataSet dataSet(&data_vec);
-
- ErrorFunction *f = new MSE(&network, &dataSet);
-
- mse_sum.add_error_function(f);
+ mock_error_fun f;
+ MOCK_EXPECT(f.get_dimension).returns(1);
+ MOCK_EXPECT(f.eval).returns(1.75);
+ ErrorSum mse_sum;
std::vector<double> weights;
weights.push_back(1);
- BOOST_CHECK_EQUAL(9, mse_sum.eval(&weights));
+ mse_sum.add_error_function(&f);
+ BOOST_CHECK_EQUAL(1.75, mse_sum.eval(&weights));
}
-
+
BOOST_AUTO_TEST_CASE(ErrorFunction_MSE_SUM_Get_Dimension_test) {
ErrorSum mse_sum;
BOOST_CHECK_EQUAL(0, mse_sum.get_dimension());
+ mock_error_fun f;
+ MOCK_EXPECT(f.get_dimension).returns(2);
+ MOCK_EXPECT(f.eval).returns(1.75);
+
- Neuron *n1 = new NeuronLinear();
- Neuron *n2 = new NeuronLinear();
- NeuralNetwork network;
- std::vector<std::pair<std::vector<double>, std::vector<double>>> data_vec;
- std::vector<double> inp, out;
- for (int i = 0; i < 1; i++) {
- inp.push_back(i);
- out.push_back(i + 4);
- }
- data_vec.emplace_back(std::make_pair(inp, out));
- network.add_neuron(n1);
- network.add_neuron(n2);
- network.add_connection_simple(0, 1, SIMPLE_CONNECTION_TYPE::UNITARY_WEIGHT, 2.5);
- network.randomize_weights();
- std::vector<size_t> net_input_neurons_indices(1);
- std::vector<size_t> net_output_neurons_indices(1);
- net_input_neurons_indices[0] = 0;
- net_output_neurons_indices[0] = 1;
- network.specify_input_neurons(net_input_neurons_indices);
- network.specify_output_neurons(net_output_neurons_indices);
-
- DataSet dataSet(&data_vec);
-
- ErrorFunction *f = new MSE(&network, &dataSet);
+ std::vector<double> weights;
+ weights.push_back(1);
- mse_sum.add_error_function(f);
+ mse_sum.add_error_function(&f);
BOOST_CHECK_EQUAL(2, mse_sum.get_dimension());
}
-BOOST_AUTO_TEST_SUITE_END()
\ No newline at end of file
+BOOST_AUTO_TEST_SUITE_END()
diff --git a/src/tests/NeuralNetworkSum_test.cpp b/src/tests/NeuralNetworkSum_test.cpp
index ce538b830299406a7352d0ea48b8afd2d5c44898..d757730a469cc2d9d7456d96577b668d1fe5f73b 100644
--- a/src/tests/NeuralNetworkSum_test.cpp
+++ b/src/tests/NeuralNetworkSum_test.cpp
@@ -7,17 +7,45 @@
#define BOOST_TEST_MODULE NeuralNetworkSum_test
+
#include "boost_unit_tests_preamble.h"
#include "../Network/NeuralNetworkSum.h"
-
+#include <turtle/mock.hpp>
using namespace lib4neuro;
+MOCK_BASE_CLASS(mock_network, lib4neuro::NeuralNetwork)
+{
+ MOCK_METHOD(get_subnet, 2)
+ MOCK_METHOD(add_neuron, 3)
+ MOCK_METHOD(add_connection_simple, 4)
+ MOCK_METHOD(add_existing_connection, 4)
+ MOCK_METHOD(copy_parameter_space, 1)
+ MOCK_METHOD(set_parameter_space_pointers, 1)
+ MOCK_METHOD(eval_single, 3)
+ MOCK_METHOD(add_to_gradient_single, 4)
+ MOCK_METHOD(randomize_weights, 0)
+ MOCK_METHOD(randomize_biases, 0)
+ MOCK_METHOD(randomize_parameters, 0)
+ MOCK_METHOD(get_n_inputs, 0)
+ MOCK_METHOD(get_n_outputs, 0)
+ MOCK_METHOD(get_n_weights, 0)
+ MOCK_METHOD(get_n_biases, 0)
+ MOCK_METHOD(get_neuron_bias_index, 1)
+ MOCK_METHOD(get_n_neurons, 0)
+ MOCK_METHOD(specify_input_neurons, 1)
+ MOCK_METHOD(specify_output_neurons, 1)
+ MOCK_METHOD(get_parameter_ptr_biases, 0)
+ MOCK_METHOD(get_parameter_ptr_weights, 0)
+ MOCK_METHOD(save_text, 1)
+ MOCK_METHOD(print_stats, 0)
+ MOCK_METHOD(print_weights, 0)
+};
+
/**
* Boost testing suite for testing NeuralNetworkSum.h
*/
BOOST_AUTO_TEST_SUITE(NeuralNetworkSum_test)
-
/**
* Test of creating new instance of NeuralNetworkSum
*/
@@ -27,28 +55,17 @@ BOOST_AUTO_TEST_SUITE(NeuralNetworkSum_test)
}
BOOST_AUTO_TEST_CASE(NeuralNetworkSum_add_network_test) {
- NeuralNetwork network;
+ mock_network network;
+ //NeuralNetwork network;
NeuralNetworkSum networkSum;
-
- BOOST_CHECK_NO_THROW(networkSum.add_network(&network, "5"));
+ 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);
@@ -57,28 +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
+BOOST_AUTO_TEST_SUITE_END()
diff --git a/src/tests/NeuralNetwork_test.cpp b/src/tests/NeuralNetwork_test.cpp
index e81fd5ab953f1b9eabc0687f523e0491d2619e8e..7fefcf72394aeed0131bb6400c20ac2b6c5c4a60 100644
--- a/src/tests/NeuralNetwork_test.cpp
+++ b/src/tests/NeuralNetwork_test.cpp
@@ -8,22 +8,18 @@
#define BOOST_TEST_MODULE NeuralNetwork_test
#include "boost_unit_tests_preamble.h"
-
+#include <turtle/mock.hpp>
#include "../Network/NeuralNetwork.h"
using namespace lib4neuro;
-struct cerr_redirect {
- cerr_redirect(std::streambuf *new_buffer)
- : old(std::cerr.rdbuf(new_buffer)
- ) {}
-
- ~cerr_redirect() {
- std::cout.rdbuf(old);
- }
-private:
- std::streambuf *old;
+MOCK_BASE_CLASS(mock_NeuronLinear, lib4neuro::NeuronLinear)
+{
+ MOCK_METHOD(activate, 2)
+ MOCK_METHOD(activation_function_eval_derivative_bias, 2)
+ MOCK_METHOD(activation_function_eval_derivative, 2)
+ MOCK_METHOD(get_derivative, 0)
};
/**
@@ -44,9 +40,10 @@ BOOST_AUTO_TEST_SUITE(NeuralNetwork_test)
* Existing bias out of range cancelation
*/
BOOST_AUTO_TEST_CASE(NeuralNetwork_add_neuron_test) {
- Neuron *n1 = new NeuronLinear();
- Neuron *n2 = new NeuronLinear();
- Neuron *n3 = new NeuronLinear();
+ mock_NeuronLinear *n1 = new mock_NeuronLinear;
+ mock_NeuronLinear *n2 = new mock_NeuronLinear;
+ mock_NeuronLinear *n3 = new mock_NeuronLinear;
+ mock_NeuronLinear *n4 = new mock_NeuronLinear;
NeuralNetwork network;
@@ -61,22 +58,15 @@ BOOST_AUTO_TEST_SUITE(NeuralNetwork_test)
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"));
- }
+ }
/**
* Test of add_connection_simple method
*/
BOOST_AUTO_TEST_CASE(NeuralNetwork_add_connection_simple_test) {
- Neuron *n1 = new NeuronLinear();
- Neuron *n2 = new NeuronLinear();
- NeuralNetwork network;
+ mock_NeuronLinear *n1 = new mock_NeuronLinear;
+ mock_NeuronLinear *n2 = new mock_NeuronLinear;
+ NeuralNetwork network;
network.add_neuron(n1, BIAS_TYPE::NO_BIAS);
network.add_neuron(n2, BIAS_TYPE::NO_BIAS);
@@ -87,13 +77,6 @@ BOOST_AUTO_TEST_SUITE(NeuralNetwork_test)
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;
-// {
-// cerr_redirect guard(output.rdbuf());
-// 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"));
}
/**
@@ -101,8 +84,10 @@ BOOST_AUTO_TEST_SUITE(NeuralNetwork_test)
*/
BOOST_AUTO_TEST_CASE(NeuralNetwork_specify_inputs_neurons_test) {
NeuralNetwork network;
- Neuron *n1 = new NeuronLinear();
- network.add_neuron(n1, BIAS_TYPE::NO_BIAS);
+ mock_NeuronLinear po;
+ mock_NeuronLinear *n1 = new mock_NeuronLinear();
+
+ network.add_neuron(n1, BIAS_TYPE::NO_BIAS);
std::vector<size_t> inputs;
inputs.push_back(0);
@@ -114,8 +99,8 @@ BOOST_AUTO_TEST_SUITE(NeuralNetwork_test)
BOOST_AUTO_TEST_CASE(NeuralNetwork_specify_outputs_neurons_test) {
NeuralNetwork network;
- Neuron *n1 = new NeuronLinear();
- network.add_neuron(n1, BIAS_TYPE::NO_BIAS);
+ mock_NeuronLinear *n1 = new mock_NeuronLinear;
+ network.add_neuron(n1, BIAS_TYPE::NO_BIAS);
std::vector<size_t> outputs;
outputs.push_back(0);
@@ -126,8 +111,14 @@ BOOST_AUTO_TEST_SUITE(NeuralNetwork_test)
}
BOOST_AUTO_TEST_CASE(NeuralNetwork_eval_single_test) {
- Neuron *n1 = new NeuronLinear();
- Neuron *n2 = new NeuronLinear();
+ mock_NeuronLinear *n1 = new mock_NeuronLinear();
+ mock_NeuronLinear *n2 = new mock_NeuronLinear();
+
+ mock_NeuronLinear n3 = *n1;
+ mock_NeuronLinear n4 = *n2;
+ MOCK_EXPECT(n3.activate).returns(5);
+ MOCK_EXPECT(n4.activate).returns(5);
+
NeuralNetwork network;
network.add_neuron(n1);
@@ -153,9 +144,10 @@ BOOST_AUTO_TEST_SUITE(NeuralNetwork_test)
}
BOOST_AUTO_TEST_CASE(NeuralNetwork_randomize_weights_test) {
- Neuron *n1 = new NeuronLinear();
- Neuron *n2 = new NeuronLinear();
- NeuralNetwork network;
+ mock_NeuronLinear *n1 = new mock_NeuronLinear();
+ mock_NeuronLinear *n2 = new mock_NeuronLinear();
+
+ NeuralNetwork network;
network.add_neuron(n1, BIAS_TYPE::NO_BIAS);
network.add_neuron(n2, BIAS_TYPE::NO_BIAS);
@@ -174,4 +166,4 @@ BOOST_AUTO_TEST_SUITE(NeuralNetwork_test)
BOOST_CHECK(sum<0.15 && sum>-0.15);
}
-BOOST_AUTO_TEST_SUITE_END()
\ No newline at end of file
+BOOST_AUTO_TEST_SUITE_END()
diff --git a/src/tests/ParticleSwarm_test.cpp b/src/tests/ParticleSwarm_test.cpp
index 3d4850b7510d794e7c06e15ca648c2bda6c6b338..8e017c641a656a9bfbf73da6bcc935ca8a5988eb 100644
--- a/src/tests/ParticleSwarm_test.cpp
+++ b/src/tests/ParticleSwarm_test.cpp
@@ -10,7 +10,18 @@
#include "boost_unit_tests_preamble.h"
#include "../LearningMethods/ParticleSwarm.h"
-
+#include <turtle/mock.hpp>
+
+MOCK_BASE_CLASS(mock_Error, lib4neuro::ErrorFunction)
+{
+ MOCK_METHOD(eval, 1)
+ MOCK_METHOD(calculate_error_gradient, 3)
+ MOCK_METHOD(get_parameters, 0)
+ MOCK_METHOD(get_dataset, 0)
+ MOCK_METHOD(get_dimension, 0)
+
+
+};
using namespace lib4neuro;
/**
@@ -28,49 +39,39 @@ BOOST_AUTO_TEST_SUITE(ParticleSwarm_test)
BOOST_AUTO_TEST_CASE(ParticleSwarm_construction_test){
std::vector<double> domain_bound;
domain_bound.push_back(5);
- NeuralNetwork network;
-// std::vector<std::pair<std::vector<double>, std::vector<double>>> data_vec;
-// std::vector<double> inp, out;
-//
-// for (int i = 0; i < 3; i++) {
-// inp.push_back(i);
-// out.push_back(i + 4);
-// }
-//
-// data_vec.emplace_back(std::make_pair(inp, out));
-//
-// DataSet dataSet(&data_vec);
-// ErrorFunction *error = new MSE(&network, &dataSet);
-
+
BOOST_CHECK_NO_THROW(ParticleSwarm swarm(&domain_bound, 0, 1, 1, 0.5, 0.05, 0.5, 0, 20));
}
- BOOST_AUTO_TEST_CASE(ParticleSwarm_optimalize_test){
+ BOOST_AUTO_TEST_CASE(ParticleSwarm_optimalize_and_get_parameters_test){
std::vector<double> domain_bound;
- domain_bound.push_back(5);
- NeuralNetwork network;
- std::vector<std::pair<std::vector<double>, std::vector<double>>> data_vec;
- std::vector<double> inp, out;
-
- for (int i = 0; i < 3; i++) {
- inp.push_back(i);
- out.push_back(i + 4);
- }
-
- data_vec.emplace_back(std::make_pair(inp, out));
-
- DataSet dataSet(&data_vec);
- ErrorFunction *error = new MSE(&network, &dataSet);
-
- ParticleSwarm swarm(&domain_bound, 0, 1, 1, -1,1,1, 0, 20);
- BOOST_CHECK_THROW(swarm.optimize( *error ), std::invalid_argument) ;
-
- ParticleSwarm swarm2(&domain_bound, 0, 1, 1, 1,-1,1, 0, 20);
- BOOST_CHECK_THROW(swarm2.optimize( *error ), std::invalid_argument) ;
-
- ParticleSwarm swarm3(&domain_bound, 0, 1, 1, 1,1,-1, 0, 20);
- BOOST_CHECK_THROW(swarm3.optimize( *error ), std::invalid_argument) ;
+ domain_bound.push_back(-5);
+ domain_bound.push_back(5);
+ domain_bound.push_back(-5);
+ domain_bound.push_back(5);
+ domain_bound.push_back(-5);
+ domain_bound.push_back(5);
+ domain_bound.push_back(-5);
+ domain_bound.push_back(5);
+ domain_bound.push_back(-5);
+ domain_bound.push_back(5);
+
+
+ mock_Error error;
+
+ MOCK_EXPECT(error.get_dimension).returns(5);
+ MOCK_EXPECT(error.eval).returns(0.8);
+
+ ParticleSwarm swarm(&domain_bound, 0, 1, 1, 1, 1, 1, 5, 20);
+
+ BOOST_CHECK_NO_THROW(swarm.optimize(error));
+
+
+
+ for (int i = 0; i < swarm.get_parameters()->size(); i++) {
+ BOOST_CHECK_NO_THROW(swarm.get_parameters()->at(i));
+ }
}
-BOOST_AUTO_TEST_SUITE_END()
\ No newline at end of file
+BOOST_AUTO_TEST_SUITE_END()
diff --git a/src/tests/Particle_test.cpp b/src/tests/Particle_test.cpp
index 4fe8c88225b7d530481a116f47564d667441acb0..dd963141278f4794f27c944a5346501b24c52d14 100644
--- a/src/tests/Particle_test.cpp
+++ b/src/tests/Particle_test.cpp
@@ -7,165 +7,72 @@
#define BOOST_TEST_MODULE Particle_test
-#include "boost_unit_tests_preamble.h"
+#ifdef _WINDOWS
+#include <boost/test/included/unit_test.hpp>
+#include <turtle/mock.hpp>
+#else
+
+#ifndef BOOST_TEST_DYN_LINK
+#define BOOST_TEST_DYN_LINK
+#endif
+
+#ifndef BOOST_TEST_NO_MAIN
+#define BOOST_TEST_NO_MAIN
+#endif
+#include <turtle/mock.hpp>
+#include <boost/test/unit_test.hpp>
+#include <boost/test/output_test_stream.hpp>
+
+#endif
#include "../LearningMethods/ParticleSwarm.h"
-using namespace lib4neuro;
+MOCK_BASE_CLASS(mock_Error, lib4neuro::ErrorFunction)
+{
+ MOCK_METHOD(eval, 1)
+ MOCK_METHOD(calculate_error_gradient, 3)
+ MOCK_METHOD(get_parameters, 0)
+ MOCK_METHOD(get_dataset, 0)
+ MOCK_METHOD(get_dimension, 0)
+};
/**
* Boost testing suite for testing ParticleSwarm.h
* TODO
*/
- BOOST_AUTO_TEST_SUITE(Particle_test)
-
- BOOST_AUTO_TEST_CASE(Particle_construction_test) {
- std::vector<double> domain_bound = {1, 2, 3, 4, 5};
- Neuron *n1 = new NeuronLinear();
- Neuron *n2 = new NeuronLinear();
- NeuralNetwork network;
- std::vector<std::pair<std::vector<double>, std::vector<double>>> data_vec;
- std::vector<double> inp, out;
-
- for (int i = 0; i < 1; i++) {
- inp.push_back(i);
- out.push_back(i + 4);
- }
-
- data_vec.emplace_back(std::make_pair(inp, out));
- network.add_neuron(n1);
- network.add_neuron(n2);
- network.add_connection_simple(0, 1, SIMPLE_CONNECTION_TYPE::UNITARY_WEIGHT, 2.5);
- network.randomize_weights();
-
- std::vector<size_t> net_input_neurons_indices(1);
- std::vector<size_t> net_output_neurons_indices(1);
- net_input_neurons_indices[0] = 0;
-
- net_output_neurons_indices[0] = 1;
-
- network.specify_input_neurons(net_input_neurons_indices);
- network.specify_output_neurons(net_output_neurons_indices);
-
- DataSet dataSet(&data_vec);
- ErrorFunction *error = new MSE(&network, &dataSet);
- Particle particle(error, &domain_bound);
- BOOST_CHECK_NO_THROW(Particle particle(error, &domain_bound));
- // particle.get_coordinate();
- }
-
- BOOST_AUTO_TEST_CASE(Particle_get_coordinate_test) {
- std::vector<double> domain_bound = {1, 2, 3, 4, 5};
- Neuron *n1 = new NeuronLinear();
- Neuron *n2 = new NeuronLinear();
- NeuralNetwork network;
- std::vector<std::pair<std::vector<double>, std::vector<double>>> data_vec;
- std::vector<double> inp, out;
-
- for (int i = 0; i < 1; i++) {
- inp.push_back(i);
- out.push_back(i + 4);
- }
-
- data_vec.emplace_back(std::make_pair(inp, out));
- network.add_neuron(n1);
- network.add_neuron(n2);
- network.add_connection_simple(0, 1, SIMPLE_CONNECTION_TYPE::UNITARY_WEIGHT, 2.5);
- network.randomize_weights();
-
- std::vector<size_t> net_input_neurons_indices(1);
- std::vector<size_t> net_output_neurons_indices(1);
- net_input_neurons_indices[0] = 0;
-
- net_output_neurons_indices[0] = 1;
-
- network.specify_input_neurons(net_input_neurons_indices);
- network.specify_output_neurons(net_output_neurons_indices);
-
- DataSet dataSet(&data_vec);
- ErrorFunction *error = new MSE(&network, &dataSet);
- Particle particle1( error, &domain_bound );
- Particle particle2( error, &domain_bound );
-
- BOOST_CHECK(*particle1.get_coordinate() != *particle2.get_coordinate());
- }
-
- //Random
- //TODO
- /*
- BOOST_AUTO_TEST_CASE(particle_change_coordiante_test) {
- double domain_bound[5] = {1,2,3,4,5};
- Neuron *n1 = new NeuronLinear(1, 1);
- Neuron *n2 = new NeuronLinear(2, 2);
- NeuralNetwork network;
- std::vector<std::pair<std::vector<double>, std::vector<double>>> data_vec;
- std::vector<double> inp, out;
-
- for (int i = 0; i < 1; i++) {
- inp.push_back(i);
- out.push_back(i + 4);
- }
-
- data_vec.emplace_back(std::make_pair(inp, out));
- network.add_neuron(n1);
- network.add_neuron(n2);
- network.add_connection_simple(0, 1, 0, 2.5);
- network.randomize_weights();
-
- std::vector<size_t> net_input_neurons_indices(1);
- std::vector<size_t> net_output_neurons_indices(1);
- net_input_neurons_indices[0] = 0;
-
- net_output_neurons_indices[0] = 1;
-
- network.specify_input_neurons(net_input_neurons_indices);
- network.specify_output_neurons(net_output_neurons_indices);
-
-
-
- DataSet dataSet(&data_vec);
- ErrorFunction *error = new MSE(&network, &dataSet);
- Particle particle(error, &domain_bound[0]);
- particle.change_coordinate(1.0, 2.0, 2.0, &domain_bound[1], 1);
-
-
- BOOST_CHECK_EQUAL(1.32664, *particle.get_coordinate());
- }
-
- BOOST_AUTO_TEST_CASE(particle_optimal_value_test){
- double domain_bound[5] = {1,2,3,4,5};
- Neuron *n1 = new NeuronLinear(1, 1);
- Neuron *n2 = new NeuronLinear(2, 2);
- NeuralNetwork network;
- std::vector<std::pair<std::vector<double>, std::vector<double>>> data_vec;
- std::vector<double> inp, out;
-
- for (int i = 0; i < 1; i++) {
- inp.push_back(i);
- out.push_back(i + 4);
- }
-
- data_vec.emplace_back(std::make_pair(inp, out));
- network.add_neuron(n1);
- network.add_neuron(n2);
- network.add_connection_simple(0, 1, 0, 2.5);
- network.randomize_weights();
-
- std::vector<size_t> net_input_neurons_indices(1);
- std::vector<size_t> net_output_neurons_indices(1);
- net_input_neurons_indices[0] = 0;
-
- net_output_neurons_indices[0] = 1;
-
- network.specify_input_neurons(net_input_neurons_indices);
- network.specify_output_neurons(net_output_neurons_indices);
+BOOST_AUTO_TEST_SUITE(Particle_test)
+
+BOOST_AUTO_TEST_CASE(Particle_construction_test) {
+ std::vector<double> domain_bound{ 1, 2, 3, 4, 5 };
+ mock_Error error;
+ MOCK_EXPECT(error.get_dimension).once().returns(5);
+ MOCK_EXPECT(error.eval).once().returns(0.8);
+ BOOST_CHECK_NO_THROW(Particle(&error, &domain_bound));
+}
+
+BOOST_AUTO_TEST_CASE(Particle_get_coordinate_test) {
+ std::vector<double> domain_bound{ 1, 2, 3, 4, 5 };
+ mock_Error error;
+
+ MOCK_EXPECT(error.get_dimension).returns(5);
+ MOCK_EXPECT(error.eval).returns(0.8);
+
+ Particle particle1(&error, &domain_bound);
+ Particle particle2(&error, &domain_bound);
+
+ BOOST_CHECK(*particle1.get_coordinate() != *particle2.get_coordinate());
+}
+BOOST_AUTO_TEST_CASE(Particle_get_optimal_value_test) {
+ std::vector<double> domain_bound{ 1, 2, 3, 4, 5 };
+ mock_Error error;
+
+ MOCK_EXPECT(error.get_dimension).returns(5);
+ MOCK_EXPECT(error.eval).returns(0.8);
+
- DataSet dataSet(&data_vec);
- ErrorFunction *error = new MSE(&network, &dataSet);
- Particle particle(error, &domain_bound[0]);
- BOOST_CHECK_CLOSE(1.789708839, particle.get_optimal_value(), 0.00001 );
- }
- */
+ Particle particle1(&error, &domain_bound);
+ BOOST_CHECK_EQUAL(0.8, particle1.get_optimal_value());
+}
-BOOST_AUTO_TEST_SUITE_END()
\ No newline at end of file
+BOOST_AUTO_TEST_SUITE_END()