var assert = require('assert'); var error = require('../../../lib/error/index'); var _ = require('underscore'); var math = require('../../../index'); math.import(require('../../../lib/function/probability/distribution')); var Matrix = math.type.Matrix; var distribution = math.distribution; var assertApproxEqual = function(testVal, val, tolerance) { var diff = Math.abs(val - testVal); if (diff > tolerance) assert.equal(testVal, val); else assert.ok(diff <= tolerance) }; var assertUniformDistribution = function(values, min, max) { var interval = (max - min) / 10 , count, i; count = _.filter(values, function(val) { return val < min }).length; assert.equal(count, 0); count = _.filter(values, function(val) { return val > max }).length; assert.equal(count, 0); for (i = 0; i < 10; i++) { count = _.filter(values, function(val) { return val >= (min + i * interval) && val < (min + (i + 1) * interval) }).length; assertApproxEqual(count/values.length, 0.1, 0.02); } }; var assertUniformDistributionInt = function(values, min, max) { var range = _.range(Math.floor(min), Math.floor(max)), count; values.forEach(function(val) { assert.ok(_.contains(range, val)); }); range.forEach(function(val) { count = _.filter(values, function(testVal) { return testVal === val }).length; assertApproxEqual(count/values.length, 1/range.length, 0.03); }); }; describe('distribution', function () { var originalRandom, uniformDistrib; before(function () { // Seed Random Number Generator for Reproducibility math.config({randomSeed: 'test'}); }); after(function () { // Randomly seed random number generator math.config({randomSeed: null}); }); beforeEach(function() { uniformDistrib = distribution('uniform') }); describe('random', function() { var originalRandom; it('should pick uniformly distributed numbers in [0, 1]', function() { var picked = []; _.times(1000, function() { picked.push(uniformDistrib.random()) }); assertUniformDistribution(picked, 0, 1); }); it('should pick uniformly distributed numbers in [min, max]', function() { var picked = []; _.times(1000, function() { picked.push(uniformDistrib.random(-10, 10)); }); assertUniformDistribution(picked, -10, 10); }); it('should pick uniformly distributed random array, with elements in [0, 1]', function() { var picked = [], matrices = [], size = [2, 3, 4]; _.times(100, function() { matrices.push(uniformDistrib.random(size)); }); // Collect all values in one array matrices.forEach(function(matrix) { assert(Array.isArray(matrix)); assert.deepEqual(math.size(matrix), size); math.forEach(matrix, function(val) { picked.push(val); }) }); assert.equal(picked.length, 2 * 3 * 4 * 100); assertUniformDistribution(picked, 0, 1); }); it('should pick uniformly distributed random array, with elements in [0, max]', function() { var picked = [], matrices = [], size = [2, 3, 4]; _.times(100, function() { matrices.push(uniformDistrib.random(size, 8)); }); // Collect all values in one array matrices.forEach(function(matrix) { assert(Array.isArray(matrix)); assert.deepEqual(math.size(matrix), size); math.forEach(matrix, function(val) { picked.push(val); }) }); assert.equal(picked.length, 2 * 3 * 4 * 100); assertUniformDistribution(picked, 0, 8); }); it('should pick uniformly distributed random matrix, with elements in [0, 1]', function() { var picked = [], matrices = [], size = math.matrix([2, 3, 4]); _.times(100, function() { matrices.push(uniformDistrib.random(size)); }); // Collect all values in one array matrices.forEach(function(matrix) { assert(matrix instanceof Matrix); assert.deepEqual(matrix.size(), size.valueOf()); matrix.forEach(function(val) { picked.push(val); }) }); assert.equal(picked.length, 2 * 3 * 4 * 100); assertUniformDistribution(picked, 0, 1); }); it('should pick uniformly distributed random array, with elements in [min, max]', function() { var picked = [], matrices = [], size = [2, 3, 4]; _.times(100, function() { matrices.push(uniformDistrib.random(size, -103, 8)); }); // Collect all values in one array matrices.forEach(function(matrix) { assert.deepEqual(math.size(matrix), size); math.forEach(matrix, function(val) { picked.push(val); }) }); assert.equal(picked.length, 2 * 3 * 4 * 100); assertUniformDistribution(picked, -103, 8); }); it ('should throw an error if called with invalid arguments', function() { assert.throws(function() { uniformDistrib.random(1, 2, [4, 8]); }); assert.throws(function() { uniformDistrib.random(1, 2, 3, 6); }); assert.throws( function () {uniformDistrib.random('str', 10)} ); assert.throws( function () {uniformDistrib.random(math.bignumber(-10), 10)} ); }); }); describe('randomInt', function() { it('should pick uniformly distributed integers in [min, max)', function() { var picked = []; _.times(10000, function() { picked.push(uniformDistrib.randomInt(-15, -5)); }); assertUniformDistributionInt(picked, -15, -5); }); it('should pick uniformly distributed random array, with elements in [min, max)', function() { var picked = [], matrices = [], size = [2, 3, 4]; _.times(1000, function() { matrices.push(uniformDistrib.randomInt(size, -14.9, -2)); }); // Collect all values in one array matrices.forEach(function(matrix) { assert.deepEqual(math.size(matrix), size); math.forEach(matrix, function(val) { picked.push(val) }); }); assert.equal(picked.length, 2 * 3 * 4 * 1000); assertUniformDistributionInt(picked, -14.9, -2); }); it('should throw an error if called with invalid arguments', function() { assert.throws(function() { uniformDistrib.randomInt(1, 2, [4, 8]); }); assert.throws(function() { uniformDistrib.randomInt(1, 2, 3, 6); }); }); }); describe('pickRandom', function() { it('should throw an error when providing a multi dimensional matrix', function() { assert.throws(function () { uniformDistrib.pickRandom(math.matrix([[1,2], [3,4]])); }, /Only one dimensional vectors supported/); }); it('should throw an error if the length of the weights does not match the length of the possibles', function() { var possibles = [11, 22, 33, 44, 55], weights = [1, 5, 2, 4], number = 2; assert.throws(function() { uniformDistrib.pickRandom(possibles, weights); }, /Weights must have the same length as possibles/); assert.throws(function() { uniformDistrib.pickRandom(possibles, number, weights); }, /Weights must have the same length as possibles/); assert.throws(function() { uniformDistrib.pickRandom(possibles, weights, number); }, /Weights must have the same length as possibles/); }); it('should throw an error if the weights array contains a non number or negative value', function() { var possibles = [11, 22, 33, 44, 55], weights = [1, 5, 2, -1, 6], number = 2; assert.throws(function() { uniformDistrib.pickRandom(possibles, weights); }, /Weights must be an array of positive numbers/); weights = [1, 5, 2, "stinky", 6]; assert.throws(function() { uniformDistrib.pickRandom(possibles, weights); }, /Weights must be an array of positive numbers/); }); it('should return a single value if no number argument was passed', function() { var possibles = [11, 22, 33, 44, 55], weights = [1, 5, 2, 4, 6]; assert.notEqual(possibles.indexOf(uniformDistrib.pickRandom(possibles)), -1); assert.notEqual(possibles.indexOf(uniformDistrib.pickRandom(possibles, weights)), -1); }); it('should return the given array if the given number is equal its length', function() { var possibles = [11, 22, 33, 44, 55], weights = [1, 5, 2, 4, 6], number = 5; assert.equal(uniformDistrib.pickRandom(possibles, number), possibles); assert.equal(uniformDistrib.pickRandom(possibles, number, weights), possibles); assert.equal(uniformDistrib.pickRandom(possibles, weights, number), possibles); }); it('should return the given array if the given number is greater than its length', function() { var possibles = [11, 22, 33, 44, 55], weights = [1, 5, 2, 4, 6], number = 6; assert.equal(uniformDistrib.pickRandom(possibles, number), possibles); assert.equal(uniformDistrib.pickRandom(possibles, number, weights), possibles); assert.equal(uniformDistrib.pickRandom(possibles, weights, number), possibles); }); it('should return an empty array if the given number is 0', function() { var possibles = [11, 22, 33, 44, 55], weights = [1, 5, 2, 4, 6], number = 0; assert.equal(uniformDistrib.pickRandom(possibles, number).length, 0); assert.equal(uniformDistrib.pickRandom(possibles, number, weights).length, 0); assert.equal(uniformDistrib.pickRandom(possibles, weights, number).length, 0); }); it('should return an array of length 1 if the number passed is 1', function() { var possibles = [11, 22, 33, 44, 55], weights = [1, 5, 2, 4, 6], number = 1; assert(Array.isArray(uniformDistrib.pickRandom(possibles, number))); assert(Array.isArray(uniformDistrib.pickRandom(possibles, number, weights))); assert(Array.isArray(uniformDistrib.pickRandom(possibles, weights, number))); assert.equal(uniformDistrib.pickRandom(possibles, number).length, 1); assert.equal(uniformDistrib.pickRandom(possibles, number, weights).length, 1); assert.equal(uniformDistrib.pickRandom(possibles, weights, number).length, 1); }); it('should pick the given number of values from the given array', function() { var possibles = [11, 22, 33, 44, 55], weights = [1, 5, 2, 4, 6], number = 3; assert.equal(uniformDistrib.pickRandom(possibles, number).length, number); assert.equal(uniformDistrib.pickRandom(possibles, number, weights).length, number); assert.equal(uniformDistrib.pickRandom(possibles, weights, number).length, number); }); it('should pick a value from the given array following an uniform distribution if only possibles are passed', function() { var possibles = [11, 22, 33, 44, 55], picked = [], count; _.times(1000, function() { picked.push(uniformDistrib.pickRandom(possibles)); }); count = _.filter(picked, function(val) { return val === 11 }).length; assert.equal(math.round(count/picked.length, 1), 0.2); count = _.filter(picked, function(val) { return val === 22 }).length; assert.equal(math.round(count/picked.length, 1), 0.2); count = _.filter(picked, function(val) { return val === 33 }).length; assert.equal(math.round(count/picked.length, 1), 0.2); count = _.filter(picked, function(val) { return val === 44 }).length; assert.equal(math.round(count/picked.length, 1), 0.2); count = _.filter(picked, function(val) { return val === 55 }).length; assert.equal(math.round(count/picked.length, 1), 0.2); }); it('should pick a value from the given matrix following an uniform distribution', function() { var possibles = math.matrix([11, 22, 33, 44, 55]), picked = [], count; _.times(1000, function() { picked.push(uniformDistrib.pickRandom(possibles)); }); count = _.filter(picked, function(val) { return val === 11 }).length; assert.equal(math.round(count/picked.length, 1), 0.2); count = _.filter(picked, function(val) { return val === 22 }).length; assert.equal(math.round(count/picked.length, 1), 0.2); count = _.filter(picked, function(val) { return val === 33 }).length; assert.equal(math.round(count/picked.length, 1), 0.2); count = _.filter(picked, function(val) { return val === 44 }).length; assert.equal(math.round(count/picked.length, 1), 0.2); count = _.filter(picked, function(val) { return val === 55 }).length; assert.equal(math.round(count/picked.length, 1), 0.2); }); it('should pick a given number of values from the given array following an uniform distribution if no weights were passed', function() { var possibles = [11, 22, 33, 44, 55], number = 2, picked = [], count; _.times(1000, function() { picked.push.apply(picked, uniformDistrib.pickRandom(possibles, number)); }); assert.equal(picked.length, 2000); count = _.filter(picked, function(val) { return val === 11 }).length; assert.equal(math.round(count/picked.length, 1), 0.2); count = _.filter(picked, function(val) { return val === 22 }).length; assert.equal(math.round(count/picked.length, 1), 0.2); count = _.filter(picked, function(val) { return val === 33 }).length; assert.equal(math.round(count/picked.length, 1), 0.2); count = _.filter(picked, function(val) { return val === 44 }).length; assert.equal(math.round(count/picked.length, 1), 0.2); count = _.filter(picked, function(val) { return val === 55 }).length; assert.equal(math.round(count/picked.length, 1), 0.2); }); it('should pick numbers from the given matrix following an uniform distribution', function() { var possibles = math.matrix([11, 22, 33, 44, 55]), number = 3, picked = [], count; _.times(1000, function() { picked.push.apply(picked, uniformDistrib.pickRandom(possibles, number)); }); assert.equal(picked.length, 3000); count = _.filter(picked, function(val) { return val === 11 }).length; assert.equal(math.round(count/picked.length, 1), 0.2); count = _.filter(picked, function(val) { return val === 22 }).length; assert.equal(math.round(count/picked.length, 1), 0.2); count = _.filter(picked, function(val) { return val === 33 }).length; assert.equal(math.round(count/picked.length, 1), 0.2); count = _.filter(picked, function(val) { return val === 44 }).length; assert.equal(math.round(count/picked.length, 1), 0.2); count = _.filter(picked, function(val) { return val === 55 }).length; assert.equal(math.round(count/picked.length, 1), 0.2); }); it('should pick a value from the given array following a weighted distribution', function() { var possibles = [11, 22, 33, 44, 55], weights = [1, 4, 0, 2, 3], picked = [], count; _.times(1000, function() { picked.push(uniformDistrib.pickRandom(possibles, weights)); }); count = _.filter(picked, function(val) { return val === 11 }).length; assert.equal(math.round(count/picked.length, 1), 0.1); count = _.filter(picked, function(val) { return val === 22 }).length; assert.equal(math.round((count)/picked.length, 1), 0.4); count = _.filter(picked, function(val) { return val === 33 }).length; assert.equal(math.round(count/picked.length, 1), 0); count = _.filter(picked, function(val) { return val === 44 }).length; assert.equal(math.round(count/picked.length, 1), 0.2); count = _.filter(picked, function(val) { return val === 55 }).length; assert.equal(math.round(count/picked.length, 1), 0.3); }); it('should pick a value from the given matrix following a weighted distribution', function() { var possibles = math.matrix([11, 22, 33, 44, 55]), weights = [1, 4, 0, 2, 3], picked = [], count; _.times(1000, function() { picked.push(uniformDistrib.pickRandom(possibles, weights)); }); count = _.filter(picked, function(val) { return val === 11 }).length; assert.equal(math.round(count/picked.length, 1), 0.1); count = _.filter(picked, function(val) { return val === 22 }).length; assert.equal(math.round((count)/picked.length, 1), 0.4); count = _.filter(picked, function(val) { return val === 33 }).length; assert.equal(math.round(count/picked.length, 1), 0); count = _.filter(picked, function(val) { return val === 44 }).length; assert.equal(math.round(count/picked.length, 1), 0.2); count = _.filter(picked, function(val) { return val === 55 }).length; assert.equal(math.round(count/picked.length, 1), 0.3); }); it('should return an array of values from the given array following a weighted distribution', function() { var possibles = [11, 22, 33, 44, 55], weights = [1, 4, 0, 2, 3], number = 2, picked = [], count; _.times(1000, function() { picked.push.apply(picked, uniformDistrib.pickRandom(possibles, number, weights)); }); count = _.filter(picked, function(val) { return val === 11 }).length; assert.equal(math.round(count/picked.length, 1), 0.1); count = _.filter(picked, function(val) { return val === 22 }).length; assert.equal(math.round((count)/picked.length, 1), 0.4); count = _.filter(picked, function(val) { return val === 33 }).length; assert.equal(math.round(count/picked.length, 1), 0); count = _.filter(picked, function(val) { return val === 44 }).length; assert.equal(math.round(count/picked.length, 1), 0.2); count = _.filter(picked, function(val) { return val === 55 }).length; assert.equal(math.round(count/picked.length, 1), 0.3); _.times(1000, function() { picked.push.apply(picked, uniformDistrib.pickRandom(possibles, weights, number)); }); count = _.filter(picked, function(val) { return val === 11 }).length; assert.equal(math.round(count/picked.length, 1), 0.1); count = _.filter(picked, function(val) { return val === 22 }).length; assert.equal(math.round((count)/picked.length, 1), 0.4); count = _.filter(picked, function(val) { return val === 33 }).length; assert.equal(math.round(count/picked.length, 1), 0); count = _.filter(picked, function(val) { return val === 44 }).length; assert.equal(math.round(count/picked.length, 1), 0.2); count = _.filter(picked, function(val) { return val === 55 }).length; assert.equal(math.round(count/picked.length, 1), 0.3); }); it('should return an array of values from the given matrix following a weighted distribution', function() { var possibles = math.matrix([11, 22, 33, 44, 55]), weights = [1, 4, 0, 2, 3], number = 2, picked = [], count; _.times(1000, function() { picked.push.apply(picked, uniformDistrib.pickRandom(possibles, number, weights)); }); count = _.filter(picked, function(val) { return val === 11 }).length; assert.equal(math.round(count/picked.length, 1), 0.1); count = _.filter(picked, function(val) { return val === 22 }).length; assert.equal(math.round((count)/picked.length, 1), 0.4); count = _.filter(picked, function(val) { return val === 33 }).length; assert.equal(math.round(count/picked.length, 1), 0); count = _.filter(picked, function(val) { return val === 44 }).length; assert.equal(math.round(count/picked.length, 1), 0.2); count = _.filter(picked, function(val) { return val === 55 }).length; assert.equal(math.round(count/picked.length, 1), 0.3); _.times(1000, function() { picked.push.apply(picked, uniformDistrib.pickRandom(possibles, weights, number)); }); count = _.filter(picked, function(val) { return val === 11 }).length; assert.equal(math.round(count/picked.length, 1), 0.1); count = _.filter(picked, function(val) { return val === 22 }).length; assert.equal(math.round((count)/picked.length, 1), 0.4); count = _.filter(picked, function(val) { return val === 33 }).length; assert.equal(math.round(count/picked.length, 1), 0); count = _.filter(picked, function(val) { return val === 44 }).length; assert.equal(math.round(count/picked.length, 1), 0.2); count = _.filter(picked, function(val) { return val === 55 }).length; assert.equal(math.round(count/picked.length, 1), 0.3); }); }); describe('distribution.normal', function() { it('should pick numbers in [0, 1] following a normal distribution', function() { var picked = [], count, dist = distribution('normal'); _.times(100000, function() { picked.push(dist.random()) }); count = _.filter(picked, function(val) { return val < 0 }).length; assert.equal(count, 0); count = _.filter(picked, function(val) { return val > 1 }).length; assert.equal(count, 0); count = _.filter(picked, function(val) { return val < 0.25 }).length; assertApproxEqual(count/picked.length, 0.07, 0.01); count = _.filter(picked, function(val) { return val < 0.4 }).length; assertApproxEqual(count/picked.length, 0.27, 0.01); count = _.filter(picked, function(val) { return val < 0.5 }).length; assertApproxEqual(count/picked.length, 0.5, 0.01); count = _.filter(picked, function(val) { return val < 0.6 }).length; assertApproxEqual(count/picked.length, 0.73, 0.01); count = _.filter(picked, function(val) { return val < 0.75 }).length; assertApproxEqual(count/picked.length, 0.93, 0.01); }); }); it('should throw an error in case of unknown distribution name', function() { assert.throws(function () { distribution('non-existing'); }, /Unknown distribution/) }); it('created random functions should throw an error in case of wrong number of arguments', function() { var dist = distribution('uniform'); assert.throws(function () {dist.random([2,3], 10, 100, 12); }, error.ArgumentsError); assert.throws(function () {dist.randomInt([2,3], 10, 100, 12); }, error.ArgumentsError); assert.throws(function () {dist.pickRandom(); }, error.ArgumentsError); assert.throws(function () {dist.pickRandom([], 23, [], 9); }, error.ArgumentsError); }); it('created random functions should throw an error in case of wrong type of arguments', function() { var dist = distribution('uniform'); assert.throws(function () {dist.pickRandom(23); }, error.TypeError); // TODO: more type testing... }); it('should LaTeX distribution', function () { var expression = math.parse('distribution("normal")'); assert.equal(expression.toTex(), '\\mathrm{distribution}\\left(\\mathtt{"normal"}\\right)'); }); });