/**************************************************************************************************
 * LibNeural++ v.0.2 - All-purpose library for managing neural networks                           *
 * Copyright (C) 2009, BlackLight                                                                 *
 *                                                                                                *
 * This program is free software: you can redistribute it and/or modify it under the terms of the *
 * GNU General Public License as published by the Free Software Foundation, either version 3 of   *
 * the License, or (at your option) any later version. This program is distributed in the hope    *
 * that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of         *
 * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for    *
 * more details. You should have received a copy of the GNU General Public License along with     *
 * this program. If not, see <http://www.gnu.org/licenses/>.                                      *
 **************************************************************************************************/

#include "neural++.hpp"

namespace neuralpp  {

Neuron::Neuron (double (*a)(double), double (*d)(double))  {
	actv_f=a;
	deriv=d;
}

Neuron::Neuron (vector< Synapsis > i, vector< Synapsis > o, double (*a)(double), double(*d)(double))  {
	in=i;
	out=o;

	actv_f=a;
	deriv=d;
}

Synapsis& Neuron::synIn (size_t i)  { return in[i]; }

Synapsis& Neuron::synOut (size_t i)  { return out[i]; }

void Neuron::push_in (Synapsis& s)  { in.push_back(s); }

void Neuron::push_out (Synapsis& s)  { out.push_back(s); }

void Neuron::setProp (double val)  { prop_val=val; }

void Neuron::setActv (double val)  { actv_val=actv_f(val); }

size_t Neuron::nIn()  { return in.size(); }

size_t Neuron::nOut()  { return out.size(); }

double Neuron::getProp()  { return prop_val; }

double Neuron::getActv()  { return actv_val; }

double Neuron::propagate()  {
	double aux=0;

	for (size_t i=0; i<nIn(); i++)
		aux += (in[i].getWeight() * in[i].getIn()->actv_val);
	return aux;
}
}