PercolationStats

/******************************************************************************

 *  Author:       Jules Martel (julesmartel@gmail.com)
 *  Date:         Tuesday 9th Feb. 2016
 *  Task: http://coursera.cs.princeton.edu/algs4/assignments/percolation.html
 *  This program estimates the means Standard deviation and percolation threshold
 *  value of a size N grid.
 *  It reads 2 parameters from command line times is the number of experiment
 *  and N the grid Size
 * ------------------------------TEST RESULTS----------------------------------------
                    //------- with Percolation.java ---------
 * input (n,T) =500 500
 * with WeightedQuickUnionUF through Percolation.java implementation elapsed time of MonteCarlo(n, T)=
 * (500,  * 500): 9.354
 * mean:                   = 0.5928887759999997
 * stddev                  = 0.005109796339884218
 * 95% confidence interval = [0.592440882602887, 0.5933366693971124 ]
 * Process finished with exit code 0

 * input (n,T) = 150 100
 * with QuickUnionUF through Percolation.java implementation elapsed time of MonteCarlo(n, T)= (150, 100):
 * 29.345
 * mean:                   = 0.5935008888888889
 * stddev                  = 0.011125106974212842
 * 95% confidence interval = [0.5913203679219431, 0.5956814098558346 ]
 * Process finished with exit code 0

                    //------- with PercoScala.scala ---------
 * input (n,T) = 150 100
 * with QuickUnionUF through PercoScala implementation elapsed time of MonteCarlo(n, T)= (150, 100): 11.305
 * mean:                   = 0.5932506666666664
 * stddev                  = 0.011555774874893586
 * 95% confidence interval = [0.5909857347911872, 0.5955155985421455 ]
 * Process finished with exit code 0

 * input (n,T) = 500 500
 * with WeightedQuickUnionUF through PercoScala implementation elapsed time of MonteCarlo(n, T)= (500,
 * 500): 9.917
 * mean:                   = 0.5927400480000005
 * stddev                  = 0.005282813982419002
 * 95% confidence interval = [0.5922769889378552, 0.5932031070621457 ]
 * Process finished with exit code 0
 ******************************************************************************/

import edu.princeton.cs.algs4.StdIn;
import edu.princeton.cs.algs4.StdRandom;
import edu.princeton.cs.algs4.StdStats;

public class PercolationStats {
    private static final double CONFIDENCE_95 = 1.96;
    private final int times;
    private final double[] thresholds;
    private final double stddev;
    private final double mean;

    public PercolationStats(int n, int times) {
        this.times = times;
        if (n <= 0 || times <= 0)
            throw new java.lang.IllegalArgumentException("not valid indices");

        thresholds = new double[times];
        // runs times times the monteCarlo simulation
        for (int i = 0; i < times; i++) {
            thresholds[i] = monteCarlo(n);
        }
        mean = StdStats.mean(thresholds);
        stddev = StdStats.stddev(thresholds);
    }

    public double mean() {
        return mean;
    }

    public double stddev() {
        return stddev;
    }

    public double confidenceLo() {
        return (mean - ((CONFIDENCE_95 * stddev) / Math.sqrt(times)));
    }

    public double confidenceHi() {
        return (mean + ((CONFIDENCE_95 * stddev) / Math.sqrt(times)));
    }

    private double monteCarlo(int n) {
        Percolation percolation = new Percolation(n);
        int p;
        int q;
        int opened = 0;
        // as long as the system does not percolate whe open a new random site
        while (!percolation.percolates()) {
            p = StdRandom.uniform(1, n + 1); // a random site index in a n size grid + 1 as last item is excluded
            q = StdRandom.uniform(1, n + 1); // an other random site
            if (!percolation.isOpen(p, q)) {
                percolation.open(p, q);
                opened++;
            }
        }
        return opened * 1.0 / (n * n);
    }

    public static void main(String[] args) {
        int n = StdIn.readInt();
        int t = StdIn.readInt();
        PercolationStats stats = new PercolationStats(n, t);
        System.out.println("mean:                   = " + stats.mean);
        System.out.println("stddev                  = " + stats.stddev);
        System.out.println("95% confidence interval = [" + stats.confidenceLo()
                + ", " + stats.confidenceHi() + " ]");
    }
}