///////////////////////////////////////////////////////////////
//  neuron.h - define family of neurons
/*
    complete prologue

*/

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

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

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

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

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

void neuron::showInputs() { showCont("neuron inputs:  ", _inputs); }

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

void neuron::showWeights() { showCont("neuron weights: ", _weights); }


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

void neuron::input(int selectInput, double value) {
  
  if(selectInput < 0 || _inputs.size() <= selectInput)
    throw "index out of bounds in neuron::input()";
  _inputs[selectInput] = value;
}

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

void neuron::weight(int selectWeight, double value) {
  
  if(selectWeight < 0 || _weights.size() <= selectWeight)
    throw "index out of bounds in neuron::weight()";
  _weights[selectWeight] = value;
}

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

linearNeuron::linearNeuron(int numInputs) {

  int i;
  for(i=0; i<numInputs; i++) {
    _inputs.push_back(1.0);
    _weights.push_back(1.0);
  }
}

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

double linearNeuron::output() {

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

//----< computer neuron function slope >-----------------------

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

//----< make a new neuron >------------------------------------

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


#ifdef TEST_NEURON

void main() {

  linearNeuron ln(3);
  ln.input(1,2);
  ln.input(2,3);
  ln.showInputs();

  ln.weight(1,2);
  ln.weight(2,3);
  ln.showWeights();

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

  cout << "\n\n";

}

#endif