package uk.ac.leeds.ccg.cluster;
import java.awt.*;
import java.awt.event.*;
import java.util.*;
//import com.sun.java.util.collections.*; //change for 1.2!
import uk.ac.leeds.ccg.geotools.*;
// import uk.ac.leeds.ccg.geotools.classification.*;

/** A class that implements Besag and Newell Cluster Hunt
 * The main class BandN creates the main frame and proivides 3 buttons
 * modified to use the new results object - 31/01/01
 */
public class Grimson extends SimpleMethod implements Method, Runnable
{
    // Members
    GrimsonTimeParameters parameters;
    GrimsonTimeParametersViewer parametersViewer;
    Database database;
    Results results;
    Viewer viewer;                        // Geotools viewer
    GeoRectangle geoRectangle = null;     // Geotools geoRectangle
    Shader shader;                        // Geotools shader
    EqualInterval2 equalinterval2;
    
    // Methods
    public static void main(String args[]){
        Grimson grimson = new Grimson();
        grimson.run();
    }
    
	public Grimson(){
		parameters = new GrimsonTimeParameters();
		parametersViewer = new GrimsonTimeParametersViewer(parameters);

	}
    public String toString() {return "Grimson";}
    public Parameters getParameters() {return parameters;}
    public ParametersViewer getParametersViewer() {return parametersViewer;}
    public void setShader(Shader s) {shader=s;}
    public void setViewer(Viewer v) {viewer=v;}
    public void setData(Database d) {database=d;}

    public SignificanceTest getSignificanceTest(){return significanceTest;}
    
    public void setSearch(GeoRectangle r) {geoRectangle=r;}
    public Results getResults(){return results;}
    
    public void run(){
	int n = 0, K = 0;
	double EA;
	int A = 0, x;
	double Vary, VarA, RC, VC, prob, pois, y, Z;
        double bL, bU, to, from;

	results = new Results();
        double highrisk = parameters.getHR();
	int numbin = parameters.getNumBin();
	double bin[] = new double[numbin];
	double mintime = parameters.getStartTime();
	double maxtime = parameters.getEndTime();
        double thresh = parameters.getSignificanceThreshold();
        double norm[] = {0.0, 1.645, 1.75, 1.88, 2.05, 2.32, 2.37, 2.41, 2.46,
            2.51,  2.57,  2.65,  2.75,  2.88,  3.09,  3.29};
        double thre[] = {0.5, 0.05, 0.04, 0.03, 0.02, 0.01, 0.009, 0.008, 0.007,
            0.006, 0.005, 0.004, 0.003, 0.002, 0.001, 0.0005};

        // MyPoint p;
        double stat = (double) 0.0;
	// System.out.println("Grimson "+significanceTest);
        // if (significanceTest == null) {
	    // System.out.println("Grimson started with a null sig test using Poisson");
            // significanceTest = new PoissonTest();
            // significanceTest.setParameters(parameters);
        // }
        System.out.println(""+this+" "+significanceTest);
        GeoData gcases = database.getCaseVals();
        Vector tcases = database.getCases();
        Vector points = database.getPoints();

	equalinterval2 = new EqualInterval2(gcases, numbin, mintime, maxtime);
        for (int j=0; j<numbin; j++){
            bL = equalinterval2.getBin(j).getLowerInclusion();
            bU = equalinterval2.getBin(j).getUpperExclusion();
// System.out.println(bL +" "+ bU);
           for (int i=0; i<gcases.getSize(); i++){
                from = ((MyPoint)points.elementAt(i)).cases;
                to = ((MyPoint)points.elementAt(i)).pop;
// System.out.println(from +" "+ to);
                if (from >= bU || to < bL) continue;
        if (from < mintime) from=mintime;
        if (to > maxtime) to = maxtime;
                if (to == from){
                    bin[j]++;
                    continue;
                }
                double length = to - from;
                if (from <= bL){
                    if (to < bU) bin[j] += (to - bL)/length;
                    else bin[j] += (bU - bL)/length;
                }
                else{
                    if (to < bU) bin[j] += 1.;
                    else bin[j] += (bU - from)/length;
                }
            }
// System.out.println(bin[j]);
        }

	// for (int i=1; i<=gcases.getSize(); i++){
	    // if (gcases.getValue(i) < mintime || gcases.getValue(i) > maxtime) continue;
	    // bin[ equalinterval2.classify((double) gcases.getValue(i)) ]++;
	// }

	x = numbin;
	
	for (int i=0; i<numbin; i++)
	    if (bin[i] >= highrisk) n +=1;
	// System.out.println(n +" "+ x);
        for (int i=1; i<numbin; i++){
	    if(bin[i] >= highrisk && bin[i-1] >= highrisk) A += 1;
	}
        System.out.println("Value for Grimson's method "+ A);
	
	// Calculate the expectation, variance & probability
	y = (double) (2. * x - 2.) / x; 
	EA = (double) y * n * (n-1) / (2. * (x - 1.));
System.out.println("E[A] = " + EA);

        if (A <= EA  || A==0)
            System.out.println("No evidence of a single cluster");
            else{
	        Vary = (double) 2. * (x - 2.) / (x * (x - 1.));
	        RC = (double) 2. * (y-1.) *(n-2) / (x-2.);
	        RC += (x*y-4.*y+2.)*(n-2.)*(n-3.)/(2.*(x-2.)*(x-3));
	        RC += 1. - EA;
	        RC *= EA;
	        VC = (double) n*(n-1.)*(n-2.)/((x-1.)*(x-2.));
	        VC -= n*(n-1.)*(n-2.)*(n-3.)/((x-1.)*(x-2.)*(x-3.));
	        VC *= Vary;
	        VarA = RC + VC;
// System.out.println(Vary +" "+ RC +" "+ VC +" "+ VarA);
	        if (VC/VarA < 0.2  && EA/VarA < 2 && EA/VarA > 0.5){ // use Poisson
		    prob = Math.exp(-EA);
		    pois = prob;
		    for (int i=1; i<A; i++){
			prob *= (double) EA / i;
		        pois += prob;
		    }
		    pois = 1. - pois;
		    System.out.println("Poisson prob. " + pois);
		    if (pois < thresh)
			System.out.println("Significant at the "+ 100.*thresh +"% level - cluster!");
		    else
			System.out.println("This is not significant at the "+ 100.*thresh +"% level - no cluster!");	
		}
	        else{  //  use Normal
                    // calculate Z score
                    Z = (double) (A - EA) / Math.sqrt(VarA);
    		    System.out.println("Normal value " +Z);
                    int ind = 0;
                    for (int i=0; i<16; i++) if (thresh <= thre[i]) ind = i;
                    double zthre = norm[ind];
                    // System.out.println("Thres " +" "+ ind +" "+ thre[ind] +" "+ norm[ind] +" "+ Z);

                    if (Z > zthre)
                        System.out.println("Significant at the "+ 100.*thresh +"% level - cluster!");
                    else
		        System.out.println("This is not significant at the "+ 100.*thresh +"% level - no cluster!");
	            }
            }

	// System.out.println("prob " + prob);

            // If significant pass details to the results object
            // if(significanceTest.isSignificant(points))
            // {
                // stat = significanceTest.getStatistic();
                // results.addResult(cc,stat);
            // }
        notifyProgressEventListener(0.0);
    }
}