package uk.ac.leeds.ccg.cluster;
/**Parameters class
 * Description: Parameter methods used by all clustering methods
 */
import java.io.*;
import java.awt.*;
import java.awt.event.*;

public class Parameters{
    // Version id
    private static final String version = "$id$";
    
    // Members
    /**@param animate control for visualising search
     * @param thresh significance threshold for the test
     * @param popMin minimum population size
     * @param canMin minimum incidence count
     * @param hH     rejection count for Monte Carlo test
     * @param meas   type of statistic
     * @param minPnt minimum point count
     * @param maxSam sample size for bootstrap
     * @param maxMC  integer Monte Carlo sample size
     * @param maxRep number of multiple testing re-runs
     */
    
    private boolean animate;
    private double thresh,popMin,canMin,hH;
    private int meas,minPnt,maxSam,maxMC,maxRep;
    private boolean excess;
    
    // Constructors
    public Parameters(){
        setDefaultParameters();
    }
    
    public Parameters( File file ) {
        try {
            StreamTokenizer st = new StreamTokenizer( new BufferedReader( new InputStreamReader( new FileInputStream( file ) ) ) );
            //System.out.println( "Setting parameters from " + file );
            st.nextToken();
            if ( st.sval.equalsIgnoreCase( "true" ) ) {
                setAnimate( true );
            } else {
                setAnimate( false );
            }
            st.nextToken();
            setSignificanceThreshold( st.nval );
            st.nextToken();
            setMinPopSize(st.nval);
            st.nextToken();
            setMinIncidenceCount( st.nval );
            st.nextToken();
            setMonteCarloRejectionCount( st.nval );
            st.nextToken();
            setStatType( ( int ) st.nval );
            st.nextToken();
            setMinPointCount( ( int ) st.nval );
            st.nextToken();
            setBootstrapSampleSize( ( int ) st.nval );
            st.nextToken();
            setMonteCarloSampleSize( ( int ) st.nval );
            st.nextToken();
            setMultipleTestReruns( ( int ) st.nval );
            if ( st.sval.equalsIgnoreCase( "true" ) ) {
                setExcess( true );
            } else {
                setExcess( false );
            }
        } catch ( java.io.IOException e) {
            System.out.println( e + " in Parameters( File( " + file.toString() + " ) )" );
            
        }
    }

    public Parameters( boolean animate, double thresh, double popMin,
    double canMin, double hH, int meas, int minPnt, int maxSam, int maxMC,
    int maxRep, boolean excess ){
        setAnimate( animate );
        setSignificanceThreshold( thresh );
        setMinPopSize( popMin );
        setMinIncidenceCount( canMin );
        setMonteCarloRejectionCount( hH );
        setStatType( meas );
        setMinPointCount( minPnt );
        setBootstrapSampleSize( maxSam );
        setMonteCarloSampleSize( maxMC );
        setMultipleTestReruns( maxRep );
        setExcess( excess );
    }
    
    // Methods
    public String tostring(){
        return
        "[excess " + getExcess() + "]\n"+
        "[animate " + getAnimate() + "]\n"+
        "[significance threshold " + getSignificanceThreshold() + "]\n"+
        "[minimum population size " + getMinPopSize() + "]\n"+
        "[minimum incidence count " + getMinIncidenceCount() + "]\n"+
        "[rejection count for Monte Carlo test " + getMonteCarloRejectionCount() + "]\n"+
        "[type of statistic " + getStatType() + "]\n"+
        "[minimum point count " + getMinPointCount() + "]\n"+
        "[sample size for bootstrap " + getBootstrapSampleSize() + "]\n"+
        "[integer Monte Carlo sample size " + getMonteCarloSampleSize() + "]\n"+
        "[number of multiple testing re-runs " + getMultipleTestReruns() + "]\n";
    }
    
    public Parameters getParameters() {
        return this;
    }
    
    public void setParameters( boolean animate, double thresh, double popMin,
    double canMin, double hH, int meas, int minPnt, int maxSam, int maxMC,
    int maxRep, boolean excess ) {
        setAnimate( animate );
        setSignificanceThreshold( thresh );
        setMinPopSize( popMin );
        setMinIncidenceCount( canMin );
        setMonteCarloRejectionCount( hH );
        setStatType( meas );
        setMinPointCount( minPnt );
        setBootstrapSampleSize( maxSam );
        setMonteCarloSampleSize( maxMC );
        setMultipleTestReruns( maxRep );
        setExcess( excess );
    }
    
    public void setDefaultParameters(){
        setParameters( false, 0.01d, 1.0d, 1.0d, 20.0d, 1, 1, 400, 200, 0, true );
    }
    
    public boolean getAnimate() { return this.animate; }
    public void setAnimate( boolean animate ) { this.animate = animate; }
    
    public double getSignificanceThreshold() { return this.thresh; }
    public void setSignificanceThreshold( double thresh ) { this.thresh = thresh; }
    
    public double getMinPopSize() { return this.popMin; }
    public void setMinPopSize( double popMin ) { this.popMin = popMin; }
    
    public double getMinIncidenceCount() { return this.canMin; }
    public void setMinIncidenceCount( double canMin ) { this.canMin = canMin; }
    
    public double getMonteCarloRejectionCount() { return this.hH; }
    public void setMonteCarloRejectionCount( double hH ) { this.hH = hH; }
    
    public int getStatType() { return this.meas; }
    public void setStatType( int meas ) { this.meas = meas; }
    
    public int getMinPointCount() { return this.minPnt; }
    public void setMinPointCount( int minPnt ) { this.minPnt = minPnt; }
    
    public int getBootstrapSampleSize() {return maxSam;}
    public void setBootstrapSampleSize(int i) {maxSam=i;}
    public int getMonteCarloSampleSize() {return maxMC;}
    public void setMonteCarloSampleSize(int i) {maxMC=i;}
    public int getMultipleTestReruns() {return maxRep;}
    public void setMultipleTestReruns(int i) {maxRep=i;}
    public boolean getExcess() { return excess; }
    public void setExcess(boolean excess) { this.excess = excess;}
    
    public void writeParameters(File file)
    throws IOException,FileNotFoundException{
        PrintWriter pw = new PrintWriter
        ( new BufferedWriter
        ( new OutputStreamWriter
        ( new FileOutputStream(file))));
        pw.println(getAnimate());
        pw.println(getSignificanceThreshold());
        pw.println(getMinPopSize());
        pw.println(getMinIncidenceCount());
        pw.println(getMonteCarloRejectionCount());
        pw.println(getStatType());
        pw.println(getMinPointCount());
        pw.println(getBootstrapSampleSize());
        pw.println(getMonteCarloSampleSize());
        pw.println(getMultipleTestReruns());
        if ( getExcess() ) {
            pw.println();
        } else {
            pw.println();
        }
        System.out.println("Parameters saved to "+file);
        pw.flush();
        pw.close();
    }
}