package stoppers;

import java.lang.*;
import java.io.*;
import main.BetterTokenizer;
import java.math.*;
import main.Cell;
import main.GeneralInput;
import main.Model;

public class StripeStop extends SimpleStop	{
	int 				stripeWidth, nonStripeWidth;
	String				node;
	int					fpos= -1, lpos= -1;	// left and right bounds of stripe, matches array index
	float 				threshold = (float) Math.exp(5.0);  // should be exp(sDif)
	boolean			done=false;
	float 				interval=1f;
	// stripe parameters
	float				sMin=0.2f;		// higher is better
	float				sDif=5f;		// ratio between instripe and exstripe
	float 	[]			stripeMeans;

	
	// No arg constructor for instantiating by name
	public StripeStop() { stopTime = 1; }
	
	public void init(Model model)  {
		super.init(model);
		stripeMeans = new float[model.arrayWidth];
	}
	
	public void loadParameters(BetterTokenizer tokenizer)  throws Exception {
		super.loadParameters(tokenizer);
		if((lpos < 0) || (fpos < 0) || (lpos >= model.arrayWidth) || (fpos >= model.arrayWidth) || (lpos - fpos < 0) || ((lpos - fpos) == (model.arrayWidth - 1)))
			throw new Exception("Error in StripeStop: Stripe not properly specified");
		stripeWidth = (lpos - fpos + 1);
		nonStripeWidth = model.arrayWidth - stripeWidth;
	}
	
	protected void loadParameter(String info, BetterTokenizer tokenizer) throws Exception {
		if(info.equals("Node")) { GeneralInput.nextToken(tokenizer); node = tokenizer.sval; }
		else if(info.equals("LeftStripeBorder")) { GeneralInput.nextToken(tokenizer); fpos = ((int)tokenizer.nval-1); }	// subtract 1 to make pos an array index
		else if(info.equals("RightStripeBorder")) { GeneralInput.nextToken(tokenizer); lpos = ((int)tokenizer.nval-1); }	// subtract 1 to make pos an array index
		else if(info.equals("Interval")) { GeneralInput.nextToken(tokenizer); interval = (float)tokenizer.nval; }
		else if(info.equals("StripeThreshold")) { GeneralInput.nextToken(tokenizer); sMin = (float)tokenizer.nval; }
		else if(info.equals("StripeDifference")) { GeneralInput.nextToken(tokenizer); sDif = (float)tokenizer.nval; 
																					   threshold = (float) Math.exp((double) sDif);
												  }
		else super.loadParameter(info,tokenizer);
	}
	
	public boolean stop(float time) {
		float instripe=0, exstripe=0;
		for(int i = 0; i < model.arrayWidth; i++)  stripeMeans[i] = 0;
		if(time > 0)  // time < 0 means MetaStopper's controlling things
			if(time < lastTime + interval)	{	return false;	}
		if(done) return true;  
		if(time > stopTime)	 return done=true;	
		for(int i = 0; i< model.arrayHeight; i++)  {
			int pos = i*model.arrayWidth;
			for(int j = 0; j < model.arrayWidth; j++)
				stripeMeans[j] += model.cells[pos + j].nodePeek(node);
		}
		for(int j = 0; j < fpos; j++)
			exstripe += stripeMeans[j];
		for(int j = fpos; j <= lpos; j++)
			instripe += stripeMeans[j] - sMin;
		for(int j = lpos + 1; j < model.arrayWidth; j++)
			exstripe += stripeMeans[j];

		instripe = instripe/stripeWidth;
		exstripe = exstripe/nonStripeWidth;
		score = (float) Math.exp((double) (instripe/exstripe));
		cumScore += score * (time - lastTime);
		lastTime = time;
		if(score < threshold)  {
			score = -cumScore;  // this is really (cumScore/totalTime) * totalTime
			return true;
		}
		else 
			return false;
	}
	
	public void initCells()  {
		for(int col = fpos; col <= lpos; col++)  {
			for(int row = 0; row < model.arrayHeight; row++)  {
				try {
					model.cells[row * model.arrayWidth + col].setValue(node, 1f);  // set each column full on
				} catch(Exception e) { System.out.println(e.toString()); }
			}
		}
	}

		
}