package yawning.mew;

import org.apache.commons.math.distribution.NormalDistributionImpl;

import ec.util.MersenneTwisterFast;

public class TestCDF {
    private static double ATTACKS = 3.0;
    private static double PCRIT = 0.6;
    private static int ITERATIONS = 1000000;

    public static void main(String args[]) {
        try {
            MersenneTwisterFast random = new MersenneTwisterFast();

            double meanCP = ATTACKS + ATTACKS * PCRIT;
            double sdCP = Math.sqrt(ATTACKS * PCRIT * (1 - PCRIT));
            double p5cp = 1 - new NormalDistributionImpl(meanCP, sdCP).cumulativeProbability(4.5);

            System.out.println("p(5 cp) using normal distribution modeling: " + p5cp);

            int lower = (int)ATTACKS;
            int upperIterations = (int)((ATTACKS - lower) * ITERATIONS + 0.5);
            int hit5cps = 0;
            for (int i = 0; i < ITERATIONS - upperIterations; i++) {
                int cp = lower;
                for (int j = 0; j < lower; j++) if (random.nextBoolean(PCRIT)) cp ++;
                if (cp >= 5) hit5cps++;
            }
            for (int i = 0; i < upperIterations; i++) {
                int cp = lower + 1;
                for (int j = 0; j < lower + 1; j++) if (random.nextBoolean(PCRIT)) cp ++;
                if (cp >= 5) hit5cps++;
            }
            System.out.println("p(5 cp) using monte carlo modeling: " + (double)hit5cps/ITERATIONS);

        }
        catch (Exception e) {
            e.printStackTrace();
        }
    }
}