package com.intuit.tank.harness.functions;
/*
* #%L
* Intuit Tank Agent (apiharness)
* %%
* Copyright (C) 2011 - 2015 Intuit Inc.
* %%
* All rights reserved. This program and the accompanying materials
* are made available under the terms of the Eclipse Public License v1.0
* which accompanies this distribution, and is available at
* http://www.eclipse.org/legal/epl-v10.html
* #L%
*/
/*************************************************************************
* Compilation: javac StdRandom.java
* Execution: java StdRandom
*
* A library of static methods to generate random numbers from
* different distributions (bernoulli, uniform, gaussian,
* discrete, and exponential). Also includes a method for
* shuffling an array.
*
* % java StdRandom 5
* 90 26.36076 false 8.79269 0
* 13 18.02210 false 9.03992 1
* 58 56.41176 true 8.80501 0
* 29 16.68454 false 8.90827 0
* 85 86.24712 true 8.95228 0
*
*
* Remark
* ------
* - Relies on randomness of nextDouble() method in java.util.Random
* to generate pseudorandom numbers in [0, 1).
*
* - This library allows you to set the pseudorandom number seed.
*
* - See http://www.honeylocust.com/RngPack/ for an industrial
* strength random number generator in Java.
*
*************************************************************************/
import java.util.Random;
/**
* <i>Standard random</i>. This class provides methods for generating random number from various distributions.
* <p>
* For additional documentation, see <a href="http://introcs.cs.princeton.edu/22library">Section 2.2</a> of
* <i>Introduction to Programming in Java: An Interdisciplinary Approach</i> by Robert Sedgewick and Kevin Wayne.
*/
public final class StdRandom {
private static Random random = new Random();
private StdRandom() {
}
/**
* Set the seed of the psedurandom number generator.
*/
public static void setSeed(long seed) {
random = new Random(seed);
}
/**
* Return real number uniformly in [0, 1).
*/
public static double uniform() {
return random.nextDouble();
}
/**
* Return real number uniformly in [0, 1).
*/
public static double random() {
return random.nextDouble();
}
/**
* Return an integer uniformly between 0 and N-1.
*/
public static int uniform(int N) {
return random.nextInt(N);
}
// /////////////////////////////////////////////////////////////////////////
// STATIC METHODS BELOW RELY ON JAVA.UTIL.RANDOM ONLY INDIRECTLY VIA
// THE STATIC METHODS ABOVE.
// /////////////////////////////////////////////////////////////////////////
/**
* Return int uniformly in [a, b).
*/
public static int uniform(int a, int b) {
return a + uniform(b - a);
}
/**
* Return real number uniformly in [a, b).
*/
public static double uniform(double a, double b) {
return a + uniform() * (b - a);
}
/**
* Return a boolean, which is true with probability p, and false otherwise.
*/
public static boolean bernoulli(double p) {
return uniform() < p;
}
/**
* Return a boolean, which is true with probability .5, and false otherwise.
*/
public static boolean bernoulli() {
return bernoulli(0.5);
}
/**
* Return a real number with a standard Gaussian distribution.
*/
public static double gaussian() {
// use the polar form of the Box-Muller transform
double r, x, y;
do {
x = uniform(-1.0, 1.0);
y = uniform(-1.0, 1.0);
r = x * x + y * y;
} while (r >= 1 || r == 0);
return x * Math.sqrt(-2 * Math.log(r) / r);
// Remark: y * Math.sqrt(-2 * Math.log(r) / r)
// is an independent random gaussian
}
/**
* Return a real number from a gaussian distribution with given mean and stddev
*/
public static double gaussian(double mean, double stddev) {
return mean + stddev * gaussian();
}
/**
* Return an integer with a geometric distribution with mean 1/p.
*/
public static int geometric(double p) {
// using algorithm given by Knuth
return (int) Math.ceil(Math.log(uniform()) / Math.log(1.0 - p));
}
/**
* Return an integer with a Poisson distribution with mean lambda.
*/
public static int poisson(double lambda) {
// using algorithm given by Knuth
// see http://en.wikipedia.org/wiki/Poisson_distribution
int k = 0;
double p = 1.0;
double L = Math.exp(-lambda);
do {
k++;
p *= uniform();
} while (p >= L);
return k - 1;
}
/**
* Return a real number with a Pareto distribution with parameter alpha.
*/
public static double pareto(double alpha) {
return Math.pow(1 - uniform(), -1.0 / alpha) - 1.0;
}
/**
* Return a real number with a Cauchy distribution.
*/
public static double cauchy() {
return Math.tan(Math.PI * (uniform() - 0.5));
}
/**
* Return a number from a discrete distribution: i with probability a[i].
*/
public static int discrete(double[] a) {
// precondition: sum of array entries equals 1
double r = uniform();
double sum = 0.0;
for (int i = 0; i < a.length; i++) {
sum = sum + a[i];
if (sum >= r)
return i;
}
assert false;
return -1;
}
/**
* Return a real number from an exponential distribution with rate lambda.
*/
public static double exp(double lambda) {
return -Math.log(1 - Math.random()) / lambda;
}
/**
* Rearrange the elements of an array in random order.
*/
public static void shuffle(Object[] a) {
int N = a.length;
for (int i = 0; i < N; i++) {
int r = i + uniform(N - i); // between i and N-1
Object temp = a[i];
a[i] = a[r];
a[r] = temp;
}
}
/**
* Rearrange the elements of a double array in random order.
*/
public static void shuffle(double[] a) {
int N = a.length;
for (int i = 0; i < N; i++) {
int r = i + uniform(N - i); // between i and N-1
double temp = a[i];
a[i] = a[r];
a[r] = temp;
}
}
/**
* Rearrange the elements of an int array in random order.
*/
public static void shuffle(int[] a) {
int N = a.length;
for (int i = 0; i < N; i++) {
int r = i + uniform(N - i); // between i and N-1
int temp = a[i];
a[i] = a[r];
a[r] = temp;
}
}
/**
* Rearrange the elements of the subarray a[lo..hi] in random order.
*/
public static void shuffle(Object[] a, int lo, int hi) {
if (lo < 0 || lo > hi || hi >= a.length)
throw new RuntimeException("Illegal subarray range");
for (int i = lo; i <= hi; i++) {
int r = i + uniform(hi - i + 1); // between i and hi
Object temp = a[i];
a[i] = a[r];
a[r] = temp;
}
}
/**
* Rearrange the elements of the subarray a[lo..hi] in random order.
*/
public static void shuffle(double[] a, int lo, int hi) {
if (lo < 0 || lo > hi || hi >= a.length)
throw new RuntimeException("Illegal subarray range");
for (int i = lo; i <= hi; i++) {
int r = i + uniform(hi - i + 1); // between i and hi
double temp = a[i];
a[i] = a[r];
a[r] = temp;
}
}
/**
* Rearrange the elements of the subarray a[lo..hi] in random order.
*/
public static void shuffle(int[] a, int lo, int hi) {
if (lo < 0 || lo > hi || hi >= a.length)
throw new RuntimeException("Illegal subarray range");
for (int i = lo; i <= hi; i++) {
int r = i + uniform(hi - i + 1); // between i and hi
int temp = a[i];
a[i] = a[r];
a[r] = temp;
}
}
//
// /**
// * Unit test.
// */
// public static void main(String[] args) {
// int N = Integer.parseInt(args[0]);
// if (args.length == 2) StdRandom.setSeed(Long.parseLong(args[1]));
//
// double[] t = { .5, .3, .1, .1 };
//
// for (int i = 0; i < N; i++) {
// StdOut.printf("%2d " , uniform(100));
// StdOut.printf("%8.5f ", uniform(10.0, 99.0));
// StdOut.printf("%5b " , bernoulli(.5));
// StdOut.printf("%7.5f ", gaussian(9.0, .2));
// StdOut.printf("%2d " , discrete(t));
// StdOut.println();
// }
// }
}