package model;

/**
 * <p>Title:DOG_Cell.java</p>
 * <p>Description: The DOG Model of a Center-Surround Receptive Field</p>
 * <p>Copyright: Copyright (c) 2009</p>
 * <p>Company: Hanover College</p>
 * @author John H. Krantz, Ph.D.
 * @version 0.5
 */

//import java.awt.*;
//import javax.swing.*;
// Model Imports
import model.compute.NormalEq;

public class DOG_Cell {

  // cell parameters
  private double sdE = 2;  // Std. deviation of Excitatory area
  private double sdI = 6;  // Std. Deviation of Inhibitory area
  private double eFactor = 1;  // factor to change the 
  // balance of excitation to inhibition in a center-surround
  // cell.  if 1, e=i in a full field stimulation so no output
  // if > 1 there there will be some excitation in a full
  // field stimulation.
  
  // a column of cells
  private int cellDim = (int)(sdI*3);
  private double [][] cell = new double[cellDim][cellDim];
  
  // computational objects
  private NormalEq excit = new NormalEq();
  private NormalEq inhib = new NormalEq();
  
  public DOG_Cell() {
	  setupCell();
  }
  public DOG_Cell(double sd_E, double sd_I){
	  sdE = (sd_E > 0 ? sd_E : sdE);
	  sdI = (sd_I > 0 & sd_I != sdE ? sd_E : sdI);
	  setupCell();
  }

  // set methods
  /**
   * Set the width of the bar of the simple cell
   * @param double w width of  bar in standard deviation
   */
  public void setCellParameters(double sd_E, double sd_I){
	  sdE = (sd_E > 0 ? sd_E : sdE);
	  sdI = (sd_I > 0 & sd_I != sd_E ? sd_I : sdI);
	  setupCell();
  }
  /**
   * Set the relative balance of excitation to inhibition.
   * If eVal = 1, then excitation and inhibition are balanced
   * in fill-field stimulation, 0 output.  If eVal > 1,
   * there there will be excitation in the full-field
   * stimulation.
   * @param double eVal the relative weight of excitation.
   */
  public void setExcitFactor(double eVal){
	  eFactor = (eVal >= 1.0 ? eVal : eFactor);
  }

  public void setupCell(){
	  cellDim = (int)sdI;
	  if (sdE > sdI) cellDim = (int)sdE;
	  cell = new double[3*cellDim+1][3*cellDim+1];
	  double ctr = cellDim+cellDim/2+1.0;
	  excit.setCtr(ctr,ctr);
	  inhib.setCtr(ctr,ctr);
	  excit.setStdDev(sdE);
	  inhib.setStdDev(sdI);
	  for (double x = 0; x < cell.length; x ++){
		  for (double y = 0; y < cell[0].length; y ++){
			  // the sdI/sdE weighting takes care of the 
			  // different sizes of the two distributions
			  cell[(int)x][(int)y] = eFactor*(sdI/sdE)* 
				  excit.getNormal2D(x,y)-inhib.getNormal2D(x,y);
		  }
	  }
  }

  // get methods
  public double [][] getCell()  { return cell; }
  public double getExcitWidth() { return sdE; }
  public double getInhibWidth() { return sdI; }
  public double getExcitFactor()   { return eFactor; }
}