///////////////////////////////////////////////////////////////
//  neuron.cpp  - neuron family used in neural net           //
//  ver 1.0                                                  //
//                                                           //
//  Language:     Visual C++, ver 6.0                        //
//  Platform:     Dell XPS B1000r, Windows 2000              //
//  Application:  Prototype for Pr#1, ELE 591/791            //
//  Author:       Jim Fawcett, CST 2-187, Syracuse Univ      //
//                (315) 443-3948, jfawcett@twcny.rr.com      //
///////////////////////////////////////////////////////////////

#include "neuron.h"
#include <iostream>
using namespace std;

//----< generic function to display container contents >-------

template <class T>
void showCont(ostream &out, const char *msg, const T &cont) {

  out << msg;
  T::const_iterator it;
  for(it = cont.begin(); it != cont.end(); it++)
    out << " " << *it;
}

//----< set input value >--------------------------------------

void neuron::input (int select, double value) {

  if(_inputs.size() > select)
    _inputs[select] = value;
  else
    throw "index out of bounds in neuron::input()";
}

//----< set weight value >-------------------------------------

void neuron::weight(int select, double value) {

  if(_weights.size() > select)
    _weights[select] = value;
  else
    throw "index out of bounds in neuron::weight()";
}

//----< show inputs >------------------------------------------

void neuron::showInputs(ostream &out, const char *msg) { 
  
  showCont(out,msg, _inputs); 
}

//----< show weights >-----------------------------------------

void neuron::showWeights(ostream &out, const char *msg) { 
  
  showCont(out,msg, _weights); 
}

//
//----< constructor >------------------------------------------

linearNeuron::linearNeuron(int numInputs) {

  int i;
  for(i=0; i<numInputs; i++) {
    _inputs.push_back(1.0);     // zeroth input (bias) must be 1.0
    _weights.push_back(1.0);    // other inputs and weights just
  }                             // reserve space
}

//----< clone >------------------------------------------------

neuron* linearNeuron::clone( ) { 
  
  return new linearNeuron(_inputs.size()); 
}

//----< compute output >---------------------------------------

double linearNeuron::output( ) {

  int i;
  double s = 0;
  for(i=0; i<_inputs.size(); i++)
    s += _weights[i]*_inputs[i];
  return s;
}

//----< compute slope >----------------------------------------

double linearNeuron::slope( ) { return 1; }

//----< test stub >--------------------------------------------

#ifdef TEST_NEURON

void main() {

  linearNeuron ln(3);
  ln.input(1,2.0);
  ln.input(2,3.0);
  ln.showInputs(cout,"\n  neuron inputs:  ");
  
  ln.weight(1,2.0);
  ln.weight(2,3.0);
  ln.showWeights(cout,"\n  neuron weights: ");

  cout << "\n  linear neuron output is: " << ln.output() << endl;

  cout << "\n\n";
}

#endif