/*
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* @author Hong-Phuc Bui
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* @filename dfhi-random-test
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* Initial Date 16.12.19
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*/
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import {expect, test} from "@jest/globals";
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import * as Rand from "./dfhi-random.js";
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const LONGEST_TIMEOUT = 2*5000; // secs
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test( "uniform distribution with default min = 0", () => {
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let min = 0,
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max = 10;
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let uniformSetupFn = (a,b) => () => Rand.uniform(b);
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testUniformDistribution(min, max, uniformSetupFn);
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});
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test("uniform distribution in a rang [min,max)", () => {
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let max = 10,
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min = 5;
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let uniformSetupFn = (a, b) => () => Rand.uniform(a, b);
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testUniformDistribution(min, max, uniformSetupFn);
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});
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function testUniformDistribution(min, max, uniformSetupFn) {
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let randomCount = 1000,
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dist = {};
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let uniformFn = uniformSetupFn(min, max);
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for (let i = 0; i < randomCount; ++i) {
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let r = uniformFn();
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expect(r < max).toBeTruthy();
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expect(min <= r).toBeTruthy();
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if (dist[r]) {
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dist[r] += 1;
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} else {
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dist[r] = 1;
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}
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}
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let exemplars = max - min; // how many distinct int numbers in [min, max);
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let means = randomCount/exemplars; // Erwartungswert
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let epsilon = 0.5;
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for (let [key, value] of Object.entries(dist) ) {
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let diff = Math.abs((value-means)/value );
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expect(diff < epsilon ).toBeTruthy();
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}
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}
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test ("bad range of uniform", () => {
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let max = 10,
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min = max + 1;
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try{
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Rand.uniform(min, max);
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}catch (error) {
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expect(error.message).toBe('bad range [11, 10)');
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}
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});
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test( "discrete distribution", () => {
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let p = [0.1, 0.3, 0.6];
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testDiscreteDist(p);
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}, LONGEST_TIMEOUT);
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test("discrete random 2", () => {
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let p = [0.1, 0.5]; // same as [0.1, 0.5, 0.5]
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testDiscreteDist(p);
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}, LONGEST_TIMEOUT);
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function testDiscreteDist(p) {
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let countRandom = {};
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let iteration = 10000;
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for(let count = 0; count < iteration; ++count) {
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let i = Rand.discrete(p);
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if (countRandom[i]) {
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countRandom[i] += 1;
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} else {
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countRandom[i] = 1;
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}
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}
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console.log(p);
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let lastP = 1 - p.reduce( (acc, c) => acc + c );
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let epsilon = 0.1;
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for( let [key,count] of Object.entries(countRandom) ) {
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let testP = p[key] ? p[key] : lastP;
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let cP = count / iteration,
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percentDiff = Math.abs(cP - testP) / testP;
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let msg = `probability of ${key} is ${count} / ${iteration} = ${cP},` +
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`near by ${testP} with relative error less than ${percentDiff*100}%`
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expect(percentDiff < epsilon).toBeTruthy();
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}
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}
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test("discrete bad distribution", () => {
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let p = [0.5, 0.5, 0.5]; // same as [0.1, 0.5, 0.5]
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try {
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Rand.discrete(p);
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} catch (error) {
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expect(error.message).toBe('bad distribution [0.5,0.5,0.5]');
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}
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});
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