diff --git a/src/NetConnection/Connection.cpp b/src/NetConnection/Connection.cpp
deleted file mode 100644
index 25eb8c90e42d7e32acbb0ac0f7eeaf2c47135ca4..0000000000000000000000000000000000000000
--- a/src/NetConnection/Connection.cpp
+++ /dev/null
@@ -1,56 +0,0 @@
-/**
- * DESCRIPTION OF THE FILE
- *
- * @author Michal Kravčenko
- * @date 13.6.18 -
- */
-
-#include "Connection.h"
-
-Connection* Connection::get_copy(Neuron *n_in, Neuron *n_out){
- Connection *output = new Connection(n_in, n_out, this->con, false);
- return output;
-}
-
-Connection::Connection(Neuron *n_in, Neuron *n_out, ConnectionWeight* con, bool del_weight) {
- this->neuron_in = n_in;
- this->neuron_out = n_out;
-
- this->con = con;
- this->delete_connection = del_weight;
-}
-
-Connection::~Connection() {
- if(this->con && this->delete_connection ){
- delete this->con;
- this->con = nullptr;
- }
-}
-
-void Connection::adjust_weights(double* values) {
- this->con->adjust_weights(values);
-}
-
-
-Neuron* Connection::get_neuron_in() {
- return this->neuron_in;
-}
-
-Neuron* Connection::get_neuron_out() {
- return this->neuron_out;
-}
-
-//double Connection::get_weight() {
-// return this->weight;
-//}
-
-void Connection::pass_signal() {
-#ifdef VERBOSE_NN_EVAL
- printf(" passing signal between neurons %d -> %d, value: %f * %f\n", this->neuron_in, this->neuron_out, this->neuron_in->get_state(), this->con->eval());
-#endif
- this->neuron_out->adjust_potential(this->neuron_in->get_state() * this->con->eval());
-}
-
-void Connection::set_weights(double *values) {
- this->con->set_weights(values);
-}
diff --git a/src/NetConnection/Connection.h b/src/NetConnection/Connection.h
deleted file mode 100644
index b9895f32ff29223c804c07ab886b08d06df7b6f0..0000000000000000000000000000000000000000
--- a/src/NetConnection/Connection.h
+++ /dev/null
@@ -1,107 +0,0 @@
-/**
- * DESCRIPTION OF THE FILE
- *
- * @author Michal Kravčenko
- * @date 13.6.18 -
- */
-
-#ifndef INC_4NEURO_CONNECTION_H
-#define INC_4NEURO_CONNECTION_H
-
-#include "../Neuron/Neuron.h"
-#include "ConnectionWeight.h"
-#include "../settings.h"
-
-class Neuron;
-class ConnectionWeight;
-
-/**
- * Class representing directed connection between two neurons
- */
-class Connection {
-private:
-
- /**
- * Pointer to an object evaluating the weight function
- */
- ConnectionWeight *con = nullptr;
- /**
- * Pointer to the Neuron on the receiving end of this connection
- */
- Neuron *neuron_in = nullptr;
-
- /**
- * Pointer to the Neuron on the signaling end of this connection
- */
- Neuron *neuron_out = nullptr;
-
- /**
- *
- */
- bool delete_connection = true;
-
-
- //TODO pridat gradient pro ucely backpropagation
-
-public:
-
- /**
- * Returns a new object reprresenting an edge using the same weight function as this one
- * @param n_in
- * @param n_out
- * @return
- */
- virtual Connection* get_copy(Neuron *n_in, Neuron *n_out) final;
-
- /**
- *
- * @param n_in
- * @param n_out
- * @param con
- * @param delete_weight
- */
- Connection(Neuron *n_in, Neuron *n_out, ConnectionWeight* con, bool delete_weight = true);
-
- /**
- * Destructor, deletes the 'con' object
- */
- ~Connection();
-
- /**
- * Takes the array of double values and alters the corresponding weights associated
- * with the 'con' object
- * @param[in] values Values to be added to the associated weights
- */
- void adjust_weights(double *values);
-
- /**
- * Takes the array of double values and sets the corresponding weights associated
- * with the 'con' object
- * @param[in] values Values to be set to the associated weights
- */
- void set_weights(double *values);
-
- /**
- * Takes the output signal of Neuron 'neuron_out', multiplies it by the result of the
- * weight function associated with this connection and adds the result to the potential
- * of the Neuron 'neuron_in'
- */
- void pass_signal();
-
-
- /**
- * Returns the pointer to the Neuron on the receiving end of this connection
- * @return
- */
- Neuron* get_neuron_in();
-
- /**
- * Returns the pointer to the Neuron on the signaling end of this connection
- * @return
- */
- Neuron* get_neuron_out();
-
-};
-
-
-#endif //INC_4NEURO_CONNECTION_H
diff --git a/src/NetConnection/ConnectionWeight.cpp b/src/NetConnection/ConnectionFunctionGeneral.cpp
similarity index 100%
rename from src/NetConnection/ConnectionWeight.cpp
rename to src/NetConnection/ConnectionFunctionGeneral.cpp
diff --git a/src/NetConnection/ConnectionWeight.h b/src/NetConnection/ConnectionFunctionGeneral.h
similarity index 100%
rename from src/NetConnection/ConnectionWeight.h
rename to src/NetConnection/ConnectionFunctionGeneral.h
diff --git a/src/NetConnection/ConnectionFunctionIdentity.cpp b/src/NetConnection/ConnectionFunctionIdentity.cpp
new file mode 100644
index 0000000000000000000000000000000000000000..b69160f489296576ca71e5cb99a6ada39c8a7eaf
--- /dev/null
+++ b/src/NetConnection/ConnectionFunctionIdentity.cpp
@@ -0,0 +1,16 @@
+/**
+ * DESCRIPTION OF THE FILE
+ *
+ * @author Michal Kravčenko
+ * @date 14.6.18 -
+ */
+
+#include "ConnectionWeightIdentity.h"
+
+ConnectionWeightIdentity::ConnectionWeightIdentity(double * val) {
+ this->value = val;
+}
+
+double ConnectionWeightIdentity::eval() {
+ return (*this->value);
+}
\ No newline at end of file
diff --git a/src/NetConnection/ConnectionWeightIdentity.h b/src/NetConnection/ConnectionFunctionIdentity.h
similarity index 61%
rename from src/NetConnection/ConnectionWeightIdentity.h
rename to src/NetConnection/ConnectionFunctionIdentity.h
index 2b214abaee05cad7cbe2de3a5210a599962ac3d7..d1d9c8d0f934c08812667f07addb884a1d4fad26 100644
--- a/src/NetConnection/ConnectionWeightIdentity.h
+++ b/src/NetConnection/ConnectionFunctionIdentity.h
@@ -8,21 +8,22 @@
#ifndef INC_4NEURO_CONNECTIONWEIGHTIDENTITY_H
#define INC_4NEURO_CONNECTIONWEIGHTIDENTITY_H
-#include "ConnectionWeight.h"
+#include "ConnectionFunctionGeneral.h"
-class ConnectionWeight;
+class ConnectionFunctionGeneral;
/**
*
*/
-class ConnectionWeightIdentity:public ConnectionWeight {
+class ConnectionWeightIdentity:public ConnectionFunctionGeneral {
private:
+ double * value = nullptr;
public:
/**
*
*/
- ConnectionWeightIdentity(std::vector<double>* w_array);
+ ConnectionWeightIdentity(double * value_ptr);
/**
*
diff --git a/src/NetConnection/ConnectionWeightIdentity.cpp b/src/NetConnection/ConnectionWeightIdentity.cpp
deleted file mode 100644
index ad3ffc0c8be7b7e06f9a71e9fb4718f7dc9d08dd..0000000000000000000000000000000000000000
--- a/src/NetConnection/ConnectionWeightIdentity.cpp
+++ /dev/null
@@ -1,22 +0,0 @@
-/**
- * DESCRIPTION OF THE FILE
- *
- * @author Michal Kravčenko
- * @date 14.6.18 -
- */
-
-#include "ConnectionWeightIdentity.h"
-
-ConnectionWeightIdentity::ConnectionWeightIdentity(std::vector<double>* w_array) {
- this->n_params = 1;
- this->weight_array = w_array;
-
- this->param_indices = new int[1];
-}
-
-double ConnectionWeightIdentity::eval() {
-
- double a = this->weight_array->at(this->param_indices[0]);
-
- return a;
-}
\ No newline at end of file
diff --git a/src/Neuron/NeuronNeuralNet.cpp b/src/Neuron/NeuronConstant.cpp
similarity index 58%
rename from src/Neuron/NeuronNeuralNet.cpp
rename to src/Neuron/NeuronConstant.cpp
index 70d1307df87a7535ba109c1f4309726c51116aa7..a656c3f628dd7e4d0716435f363f9f6c0688d5b6 100644
--- a/src/Neuron/NeuronNeuralNet.cpp
+++ b/src/Neuron/NeuronConstant.cpp
@@ -2,7 +2,7 @@
* DESCRIPTION OF THE FILE
*
* @author Michal Kravčenko
- * @date 13.6.18 -
+ * @date 8.8.18 -
*/
-#include "NeuronNeuralNet.h"
+#include "NeuronConstant.h"
diff --git a/src/Neuron/NeuronConstant.h b/src/Neuron/NeuronConstant.h
new file mode 100644
index 0000000000000000000000000000000000000000..dff05a073c18122b477e414dd30585b39837c095
--- /dev/null
+++ b/src/Neuron/NeuronConstant.h
@@ -0,0 +1,17 @@
+/**
+ * DESCRIPTION OF THE FILE
+ *
+ * @author Michal Kravčenko
+ * @date 8.8.18 -
+ */
+
+#ifndef INC_4NEURO_NEURONCONSTANT_H
+#define INC_4NEURO_NEURONCONSTANT_H
+
+
+class NeuronConstant {
+
+};
+
+
+#endif //INC_4NEURO_NEURONCONSTANT_H
diff --git a/src/Neuron/NeuronNeuralNet.h b/src/Neuron/NeuronNeuralNet.h
deleted file mode 100644
index 35cb2a3ac180c2ca8a8201e4dbb66bcccb78568d..0000000000000000000000000000000000000000
--- a/src/Neuron/NeuronNeuralNet.h
+++ /dev/null
@@ -1,18 +0,0 @@
-/**
- * DESCRIPTION OF THE FILE
- *
- * @author Michal Kravčenko
- * @date 13.6.18 -
- */
-
-#ifndef INC_4NEURO_NEURONNEURALNET_H
-#define INC_4NEURO_NEURONNEURALNET_H
-
-#include "Neuron.h"
-
-class NeuronNeuralNet:public Neuron {
-
-};
-
-
-#endif //INC_4NEURO_NEURONNEURALNET_H
diff --git a/src/Neuron/NeuronTanh.cpp b/src/Neuron/NeuronTanh.cpp
deleted file mode 100644
index cef2a07faedf044e19f06c368b0729d5c1756bb0..0000000000000000000000000000000000000000
--- a/src/Neuron/NeuronTanh.cpp
+++ /dev/null
@@ -1,68 +0,0 @@
-//
-// Created by fluffymoo on 11.6.18.
-//
-
-#include "NeuronTanh.h"
-
-Neuron* NeuronTanh::get_copy( ){
- NeuronTanh* output = new NeuronTanh( this->activation_function_parameters[0]);
-
- return output;
-}
-
-NeuronTanh::NeuronTanh(double a) {
-
- this->n_activation_function_parameters = 1;
- this->activation_function_parameters = new double[1];
- this->activation_function_parameters[0] = a;
-
- this->edges_in = new std::vector<Connection*>(0);
- this->edges_out = new std::vector<Connection*>(0);
-
-}
-
-void NeuronTanh::activate( ) {
-
- double a = this->activation_function_parameters[0];
- double x = this->potential;
- double ex = std::pow(E, x - a);
- double exi = 1.0 / ex;
-
- this->state = (ex - exi) / (ex + exi);
-
-}
-
-double NeuronTanh::activation_function_eval_partial_derivative(int param_idx) {
-
- double a = this->activation_function_parameters[0];
- double x = this->potential;
-
-
- if(param_idx == 0){
- /**
- * TODO
- * Same as activation_function_get_derivative()
- */
- double ex = -4.0 * std::pow(E, 2.0 * (x + a));
- double exi = std::pow(E, 2.0 * a) + std::pow(E, 2.0 * x);
-
- return ex / (exi * exi);
- }
-
- return 0.0;
-
-}
-
-double NeuronTanh::activation_function_eval_derivative( ) {
-
- double a = this->activation_function_parameters[0];
- double x = this->potential;
- double ex = -4.0 * std::pow(E, 2.0 * (x + a));
- double exi = std::pow(E, 2.0 * a) + std::pow(E, 2.0 * x);
-
- return ex / (exi * exi);
-}
-
-Neuron* NeuronTanh::get_derivative() {
- return nullptr;
-}
\ No newline at end of file
diff --git a/src/Neuron/NeuronTanh.h b/src/Neuron/NeuronTanh.h
deleted file mode 100644
index 3d5ce6d8aabf4ad6bcabb55193612606dde7241d..0000000000000000000000000000000000000000
--- a/src/Neuron/NeuronTanh.h
+++ /dev/null
@@ -1,68 +0,0 @@
-/**
- * DESCRIPTION OF THE CLASS
- *
- * @author Martin Beseda
- * @author Martin Mrovec
- * @author Michal Kravčenko
- * @date 2017 - 2018
- */
-
-#ifndef INC_4NEURO_NEURONTANH_H
-#define INC_4NEURO_NEURONTANH_H
-
-#include <cmath>
-#include "Neuron.h"
-#include "../constants.h"
-
-class NeuronTanh:public Neuron, public IDifferentiable {
- friend class boost::serialization::access;
-
-protected:
- template<class Archive>
- void serialize(Archive & ar, const unsigned int version){
- //TODO separate implementation to NeuronLogistic.cpp!
- ar & boost::serialization::base_object<Neuron>(*this);
- };
-
-public:
-
- Neuron* get_copy( );
-
- /**
- * Constructs the object of the Hyperbolic Tangent >neuron with activation function
- * f(x) = (e^(x-a) - e^(a-x))/(e^(x-a) + e^(a-x))
- * @param[in] a First coefficient, stored in activation_function_parameters[0]
- */
- explicit NeuronTanh(double a = 0.0);
-
- /**
- * Evaluates '(e^(x-a) - e^(a-x))/(e^(x-a) + e^(a-x))' and stores the result into the 'state' property
- */
- void activate( ) override;
-
- /**
- * Calculates the partial derivative of the activation function
- * f(x) = (e^(x-a) - e^(a-x))/(e^(x-a) + e^(a-x))
- * @param[in] param_idx Index of the parameter to calculate derivative of
- * @return Partial derivative of the activation function according to the
- * 'param_idx'-th parameter.
- */
- double activation_function_eval_partial_derivative(int param_idx) override;
-
- /**
- * TODO
- * Wrong return statement, there is no b
- * Calculates d/dx of (e^(x-a) - e^(a-x))/(e^(x-a) + e^(a-x))
- * @return a * e^(b - x) * [e^(b - x) + 1]^(-a)
- */
- double activation_function_eval_derivative( ) override;
-
- /**
- * Returns a pointer to a Neuron with derivative as its activation function
- * @return
- */
- Neuron* get_derivative() override;
-};
-
-
-#endif //INC_4NEURO_NEURONTANH_H
diff --git a/src/examples/net_test_ode_1.cpp b/src/examples/net_test_ode_1.cpp
index 525174bdab9d86b9e4e8af2fd094aa63bf0b7838..7cc320be3d373dfde557496406b27ba49e0b8ebf 100644
--- a/src/examples/net_test_ode_1.cpp
+++ b/src/examples/net_test_ode_1.cpp
@@ -5,18 +5,103 @@
* y(0) = 1
* (d/dt)y(0) = 1
*
+ * -------------------------------------------
+ * Analytical solution: e^(-2x) * (3x + 1)
+ *
* @author Michal Kravčenko
* @date 17.7.18 -
*/
-
+#include <random>
#include <vector>
#include <utility>
+#include <iostream>
#include "../include/4neuro.h"
#include "Solvers/DESolver.h"
-int main() {
+void test_analytical_gradient_y(unsigned int n_inner_neurons) {
+ unsigned int n_inputs = 1;
+}
+
+void test_analytical_y(unsigned int n_inner_neurons){
+ unsigned int n_inputs = 1;
+ unsigned int n_outputs = 1;
+ unsigned int n_equations = 1;
+
+ /* SETUP OF THE TRAINING DATA */
+ std::vector<double> inp, out;
+
+ double d1_s = 0.0, d1_e = 1.0, frac, alpha, x;
+
+ /* TRAIN DATA FOR THE GOVERNING DE */
+ std::vector<std::pair<std::vector<double>, std::vector<double>>> data_vec_g;
+ unsigned int train_size = 150;
+
+ /* ISOTROPIC TRAIN SET */
+ frac = (d1_e - d1_s) / (train_size - 1);
+// for(unsigned int i = 0; i < train_size; ++i){
+// x = frac * i;
+// inp = {x};
+// out = {std::pow(E, -2 * x) * (3 * x + 1)};
+// data_vec_g.emplace_back(std::make_pair(inp, out));
+//
+// std::cout << i + 1 << " " << x << " " << out[0] << std::endl;
+// }
+
+ /* CHEBYSCHEV TRAIN SET */
+ alpha = PI / (train_size - 1);
+ frac = 0.5 * (d1_e - d1_s);
+ for(unsigned int i = 0; i < train_size; ++i){
+ x = (std::cos(PI - alpha * i) + 1.0) * frac + d1_s;
+ inp = {x};
+ out = {std::pow(E, -2 * x) * (3 * x + 1)};
+ data_vec_g.emplace_back(std::make_pair(inp, out));
+
+ std::cout << i + 1 << " " << x << " " << out[0] << std::endl;
+ }
+ DataSet ds_00(&data_vec_g);
+
+// return;
+
+ DESolver solver_01( n_equations, n_inputs, n_inner_neurons, n_outputs );
+
+ NeuralNetwork * solution = solver_01.get_solution();
+
+
+ /* PARTICLE SWARM TRAINING METHOD SETUP */
+ unsigned int max_iters = 150;
+
+ //must encapsulate each of the partial error functions
+ double *domain_bounds = new double[ 2 * n_inner_neurons * (n_inputs + n_outputs) ];
+ for(unsigned int i = 0; i < n_inner_neurons * (n_inputs + n_outputs); ++i){
+ domain_bounds[2 * i] = -800.0;
+ domain_bounds[2 * i + 1] = 800.0;
+ }
+
+ double c1 = 0.5, c2 = 0.8, w = 0.8;
+
+ unsigned int n_particles = 100;
+
+ double gamma = 0.5, epsilon = 0.001, delta = 0.9;
+
+ MSE mse(solution, &ds_00);
+ ParticleSwarm swarm_01(&mse, domain_bounds, c1, c2, w, n_particles, max_iters);
+ swarm_01.optimize( gamma, epsilon, delta );
+
+ unsigned int n_test_points = 100;
+ std::vector<double> input(1), output(1);
+ double error = 0.0;
+ for(unsigned int i = 0; i < n_test_points; ++i){
+ input[0] = i * ((d1_e - d1_s) / (n_test_points - 1)) + d1_s;
+ solution->eval_single(input, output);
+ std::cout << i + 1 << " " << std::abs(output[0] - std::pow(E, -2 * input[0]) * (3 * input[0] + 1))<< " " << output[0] << std::endl;
+ }
+
+ delete [] domain_bounds;
+}
+
+void test_odr(unsigned int n_inner_neurons){
unsigned int n_inputs = 1;
unsigned int n_inner_neurons = 5;
unsigned int n_outputs = 1;
@@ -107,18 +192,41 @@ int main() {
domain_bounds[2 * i + 1] = 800.0;
}
- double c1 = 0.5, c2 = 0.7, w = 0.3;
+ double c1 = 0.5, c2 = 1.5, w = 0.8;
- unsigned int n_particles = 25;
+ unsigned int n_particles = 100;
- double gamma = 0.8, epsilon = 1e-6, delta = 0.9;
+ double gamma = 0.5, epsilon = 0.02, delta = 0.9;
solver_01.solve_via_particle_swarm( domain_bounds, c1, c2, w, n_particles, max_iters, gamma, epsilon, delta );
NeuralNetwork *solution = solver_01.get_solution();
+ unsigned int n_test_points = 100;
+ std::vector<double> input(1), output(1);
+ for(unsigned int i = 0; i < n_test_points; ++i){
+
+ input[0] = i * ((d1_e - d1_s) / (n_test_points - 1)) + d1_s;
+
+ solution->eval_single(input, output);
+
+ std::cout << i + 1 << " " << output[0] << std::endl;
+ }
+
delete [] domain_bounds;
+}
+
+int main() {
+
+ unsigned int n_inner_neurons = 20;
+
+// test_odr(n_inner_neurons);
+
+ test_analytical_y(n_inner_neurons);
+ test_analytical_gradient_y(n_inner_neurons);
+
+
return 0;
-}
\ No newline at end of file
+}
diff --git a/src/tests/Connection_test.cpp b/src/tests/Connection_test.cpp
deleted file mode 100644
index 027c696c88e37e52175937f74bf15fd80dcc55a3..0000000000000000000000000000000000000000
--- a/src/tests/Connection_test.cpp
+++ /dev/null
@@ -1,71 +0,0 @@
-/**
- * DESCRIPTION OF THE CLASS
- *
- * @author David Vojtek
- * @date 2018
- */
-
-#define BOOST_TEST_NO_MAIN
-
-#include <boost/test/unit_test.hpp>
-
-
-#include "../NetConnection/Connection.h"
-#include "../NetConnection/ConnectionWeight.h"
-#include "../Neuron/NeuronLinear.h"
-#include <iostream>
-/**
- * Boost testing suite for testing Connection.h
- */
-
-BOOST_AUTO_TEST_SUITE(Connection_test)
-
- /**
- * Test of constructor of Connection
- */
- BOOST_AUTO_TEST_CASE(Connection_construction__test) {
-
- Neuron *neuron1 = new NeuronLinear(2, 3);
- Neuron *neuron2 = new NeuronLinear(4, 5);
- std::vector<double> w_array = {2, 3, 4, 5, 6};
-
- ConnectionWeight *conn = new ConnectionWeight(2, &w_array);
- Connection connection(neuron1, neuron2, conn);
- //Test of correct input neuron
- BOOST_CHECK_EQUAL(neuron1, connection.get_neuron_in());
- //Test of correct output neuron
- BOOST_CHECK_EQUAL(neuron2, connection.get_neuron_out());
- }
-
- /**
- * Test of pass_signal method
- */
- BOOST_AUTO_TEST_CASE(Connection_pass_signal_test) {
-
- Neuron *neuron1 = new NeuronLinear(2, 3);
- Neuron *neuron2 = new NeuronLinear(4, 5);
- std::vector<double> w_array = {2, 3, 4, 5, 6};
- std::function<double(double *, int *, int)> f = [](double *weight_array, int *index_array, int n_params) {
- double a = weight_array[0];
- double b = weight_array[1];
- return (a + 1.5 * b);
- };
-
-
- ConnectionWeight *conn = new ConnectionWeight(2, &w_array);
-
- Connection connection(neuron1, neuron2, conn);
-
- neuron1->activate();
- neuron2->activate();
- // test of neuron state before passing signal
- BOOST_CHECK_EQUAL(4, neuron2->get_state());
- connection.pass_signal();
- neuron2->activate();
- // test of neuron state after passing signal
- BOOST_CHECK_EQUAL(7204, neuron2->get_state());
-
- }
-
-
-BOOST_AUTO_TEST_SUITE_END()
\ No newline at end of file
diff --git a/src/tests/NeuronTanh.cpp b/src/tests/NeuronTanh.cpp
deleted file mode 100644
index cac6e0982d00011a03c6917ca6f5b439e7527d96..0000000000000000000000000000000000000000
--- a/src/tests/NeuronTanh.cpp
+++ /dev/null
@@ -1,51 +0,0 @@
-/**
- * DESCRIPTION OF THE CLASS
- *
- * @author David Vojtek
- * @date 2018
- */
-
-#define BOOST_TEST_NO_MAIN
-
-#include <boost/test/unit_test.hpp>
-
-#include "../Neuron/NeuronTanh.h"
-/**
- * Boost testing suite for testing NeuronTanh.h
- * doesn't test inherited methods
- */
-BOOST_AUTO_TEST_SUITE(neuronTanh_test)
-
- /**
- * Test of creating new instance of NeuronTanh
- */
- BOOST_AUTO_TEST_CASE(neuronTanh_construction__test) {
- NeuronTanh neuron(1.745);
- //Test of correct value of activation function parameter
- BOOST_CHECK_EQUAL(neuron.activation_function_get_parameter(0), 1.745);
- }
-
- /**
- * Test of activate method
- */
- BOOST_AUTO_TEST_CASE(neuronTanh_activate__test) {
- NeuronTanh neuron(2.0);
- neuron.activate();
- //Test of correct state after activate neuron
- BOOST_CHECK_CLOSE(-0.96402758007581, neuron.get_state(), 0.00001);
- }
-
- /**
- * Test of derivative methods
- */
- BOOST_AUTO_TEST_CASE(neuronTanh_derivative_test) {
- NeuronTanh neuron(2.0);
-
- //Test of correct output of activation_function_get_derivative method
- BOOST_CHECK_CLOSE(-0.0706508248531644, neuron.activation_function_eval_derivative(), 0.00001);
- //Tests of correct outputs of activation_function_get_partial_derivative method
- BOOST_CHECK_CLOSE(-0.0706508248531644, neuron.activation_function_eval_partial_derivative(0), 0.00001);
- BOOST_CHECK_EQUAL(0.0, neuron.activation_function_eval_partial_derivative(10000));
- }
-
-BOOST_AUTO_TEST_SUITE_END()
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