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* Adopt type=module follow changes in d3-format: * type=module * add exports * remove zip * license: ISC * update dependencies * update README * assert message * Update README * Update README * yarn upgrade * cleaner imports * cleaner imports * cleaner imports Co-authored-by: Mike Bostock <mbostock@gmail.com>
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| Original file line number | Diff line number | Diff line change |
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| @@ -1,27 +1,13 @@ | ||
| Copyright 2010-2016 Mike Bostock | ||
| All rights reserved. | ||
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| Redistribution and use in source and binary forms, with or without modification, | ||
| are permitted provided that the following conditions are met: | ||
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| * Redistributions of source code must retain the above copyright notice, this | ||
| list of conditions and the following disclaimer. | ||
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| * Redistributions in binary form must reproduce the above copyright notice, | ||
| this list of conditions and the following disclaimer in the documentation | ||
| and/or other materials provided with the distribution. | ||
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| * Neither the name of the author nor the names of contributors may be used to | ||
| endorse or promote products derived from this software without specific prior | ||
| written permission. | ||
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| THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND | ||
| ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED | ||
| WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE | ||
| DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE LIABLE FOR | ||
| ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES | ||
| (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; | ||
| LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON | ||
| ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT | ||
| (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS | ||
| SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. | ||
| Copyright 2010-2021 Mike Bostock | ||
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| Permission to use, copy, modify, and/or distribute this software for any purpose | ||
| with or without fee is hereby granted, provided that the above copyright notice | ||
| and this permission notice appear in all copies. | ||
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| THE SOFTWARE IS PROVIDED "AS IS" AND THE AUTHOR DISCLAIMS ALL WARRANTIES WITH | ||
| REGARD TO THIS SOFTWARE INCLUDING ALL IMPLIED WARRANTIES OF MERCHANTABILITY AND | ||
| FITNESS. IN NO EVENT SHALL THE AUTHOR BE LIABLE FOR ANY SPECIAL, DIRECT, | ||
| INDIRECT, OR CONSEQUENTIAL DAMAGES OR ANY DAMAGES WHATSOEVER RESULTING FROM LOSS | ||
| OF USE, DATA OR PROFITS, WHETHER IN AN ACTION OF CONTRACT, NEGLIGENCE OR OTHER | ||
| TORTIOUS ACTION, ARISING OUT OF OR IN CONNECTION WITH THE USE OR PERFORMANCE OF | ||
| THIS SOFTWARE. |
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| @@ -0,0 +1,11 @@ | ||
| { | ||
| "extends": "eslint:recommended", | ||
| "parserOptions": { | ||
| "sourceType": "module", | ||
| "ecmaVersion": 8 | ||
| }, | ||
| "env": { | ||
| "es6": true, | ||
| "mocha": true | ||
| } | ||
| } |
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| import assert from "assert"; | ||
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| export function assertInDelta(actual, expected, delta) { | ||
| assert(expected - delta <= actual && actual <= expected + delta, `${actual} should be within ${delta} of ${expected}`); | ||
| } |
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -1,46 +1,44 @@ | ||
| var tape = require("tape-await"), | ||
| d3 = Object.assign({}, require("../"), require("d3-array")), | ||
| skewness = require("./skewness"), | ||
| kurtosis = require("./kurtosis"); | ||
| import {mean, range, variance} from "d3-array"; | ||
| import {randomBates, randomLcg} from "../src/index.js"; | ||
| import {skewness, kurtosis} from "./statistics.js"; | ||
| import {assertInDelta} from "./asserts.js"; | ||
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| require("./inDelta"); | ||
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| tape("d3.randomBates(n) returns random numbers with a mean of one-half", test => { | ||
| var randomBates = d3.randomBates.source(d3.randomLcg(0.6351090615932817)); | ||
| test.inDelta(d3.mean(d3.range(10000).map(randomBates(1))), 0.5, 0.05); | ||
| test.inDelta(d3.mean(d3.range(10000).map(randomBates(10))), 0.5, 0.05); | ||
| test.inDelta(d3.mean(d3.range(10000).map(randomBates(1.5))), 0.5, 0.05); | ||
| test.inDelta(d3.mean(d3.range(10000).map(randomBates(4.2))), 0.5, 0.05); | ||
| it("randomBates(n) returns random numbers with a mean of one-half", () => { | ||
| const r = randomBates.source(randomLcg(0.6351090615932817)); | ||
| assertInDelta(mean(range(10000).map(r(1))), 0.5, 0.05); | ||
| assertInDelta(mean(range(10000).map(r(10))), 0.5, 0.05); | ||
| assertInDelta(mean(range(10000).map(r(1.5))), 0.5, 0.05); | ||
| assertInDelta(mean(range(10000).map(r(4.2))), 0.5, 0.05); | ||
| }); | ||
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| tape("d3.randomBates(n) returns random numbers with a variance of 1 / (12 * n)", test => { | ||
| var randomBates = d3.randomBates.source(d3.randomLcg(0.1284832084868286)); | ||
| test.inDelta(d3.variance(d3.range(10000).map(randomBates(1))), 1 / 12, 0.05); | ||
| test.inDelta(d3.variance(d3.range(10000).map(randomBates(10))), 1 / 120, 0.05); | ||
| test.inDelta(d3.variance(d3.range(10000).map(randomBates(1.5))), 1 / 18, 0.05); | ||
| test.inDelta(d3.variance(d3.range(10000).map(randomBates(4.2))), 1 / 50.4, 0.05); | ||
| it("randomBates(n) returns random numbers with a variance of 1 / (12 * n)", () => { | ||
| const r = randomBates.source(randomLcg(0.1284832084868286)); | ||
| assertInDelta(variance(range(10000).map(r(1))), 1 / 12, 0.05); | ||
| assertInDelta(variance(range(10000).map(r(10))), 1 / 120, 0.05); | ||
| assertInDelta(variance(range(10000).map(r(1.5))), 1 / 18, 0.05); | ||
| assertInDelta(variance(range(10000).map(r(4.2))), 1 / 50.4, 0.05); | ||
| }); | ||
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| tape("d3.randomBates(n) returns random numbers with a skewness of 0", test => { | ||
| var randomBates = d3.randomBates.source(d3.randomLcg(0.051567609139606674)); | ||
| test.inDelta(skewness(d3.range(10000).map(randomBates(1))), 0, 0.05); | ||
| test.inDelta(skewness(d3.range(10000).map(randomBates(10))), 0, 0.05); | ||
| test.inDelta(skewness(d3.range(10000).map(randomBates(1.5))), 0, 0.05); | ||
| test.inDelta(skewness(d3.range(10000).map(randomBates(4.2))), 0, 0.05); | ||
| it("randomBates(n) returns random numbers with a skewness of 0", () => { | ||
| const r = randomBates.source(randomLcg(0.051567609139606674)); | ||
| assertInDelta(skewness(range(10000).map(r(1))), 0, 0.05); | ||
| assertInDelta(skewness(range(10000).map(r(10))), 0, 0.05); | ||
| assertInDelta(skewness(range(10000).map(r(1.5))), 0, 0.05); | ||
| assertInDelta(skewness(range(10000).map(r(4.2))), 0, 0.05); | ||
| }); | ||
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| tape("d3.randomBates(n) returns random numbers with a kurtosis of -6 / (5 * n)", test => { | ||
| var randomBates = d3.randomBates.source(d3.randomLcg(0.696913354780724)); | ||
| test.inDelta(kurtosis(d3.range(10000).map(randomBates(1))), -6 / 5, 0.05); | ||
| test.inDelta(kurtosis(d3.range(10000).map(randomBates(10))), -6 / 50, 0.1); | ||
| test.inDelta(kurtosis(d3.range(10000).map(randomBates(1.5))), -6 / 7.5, 0.05); | ||
| test.inDelta(kurtosis(d3.range(10000).map(randomBates(4.2))), -6 / 21, 0.05); | ||
| it("randomBates(n) returns random numbers with a kurtosis of -6 / (5 * n)", () => { | ||
| const r = randomBates.source(randomLcg(0.696913354780724)); | ||
| assertInDelta(kurtosis(range(10000).map(r(1))), -6 / 5, 0.05); | ||
| assertInDelta(kurtosis(range(10000).map(r(10))), -6 / 50, 0.1); | ||
| assertInDelta(kurtosis(range(10000).map(r(1.5))), -6 / 7.5, 0.05); | ||
| assertInDelta(kurtosis(range(10000).map(r(4.2))), -6 / 21, 0.05); | ||
| }); | ||
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| tape("d3.randomBates(0) is equivalent to d3.randomUniform()", test => { | ||
| var randomBates = d3.randomBates.source(d3.randomLcg(0.7717596603725383)); | ||
| test.inDelta(d3.mean(d3.range(10000).map(randomBates(0))), 0.5, 0.05); | ||
| test.inDelta(d3.variance(d3.range(10000).map(randomBates(0))), 1 / 12, 0.05); | ||
| test.inDelta(skewness(d3.range(10000).map(randomBates(0))), 0, 0.05); | ||
| test.inDelta(kurtosis(d3.range(10000).map(randomBates(0))), -6 / 5, 0.05); | ||
| it("randomBates(0) is equivalent to randomUniform()", () => { | ||
| const r = randomBates.source(randomLcg(0.7717596603725383)); | ||
| assertInDelta(mean(range(10000).map(r(0))), 0.5, 0.05); | ||
| assertInDelta(variance(range(10000).map(r(0))), 1 / 12, 0.05); | ||
| assertInDelta(skewness(range(10000).map(r(0))), 0, 0.05); | ||
| assertInDelta(kurtosis(range(10000).map(r(0))), -6 / 5, 0.05); | ||
| }); |
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -1,52 +1,50 @@ | ||
| var tape = require("tape-await"), | ||
| skewness = require("./skewness"), | ||
| kurtosis = require("./kurtosis"), | ||
| d3 = Object.assign({}, require("../"), require("d3-array")); | ||
| import {mean, range, variance} from "d3-array"; | ||
| import {randomBernoulli, randomLcg} from "../src/index.js"; | ||
| import {skewness, kurtosis} from "./statistics.js"; | ||
| import {assertInDelta} from "./asserts.js"; | ||
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| require("./inDelta"); | ||
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| function mean(p) { | ||
| function dmean(p) { | ||
| return p; | ||
| } | ||
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| function variance(p) { | ||
| function dvariance(p) { | ||
| return p * (1 - p); | ||
| } | ||
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| function skew(p) { | ||
| return (1 - 2 * p) / Math.sqrt(variance(p)); | ||
| return (1 - 2 * p) / Math.sqrt(dvariance(p)); | ||
| } | ||
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| function kurt(p) { | ||
| return (6 * Math.pow(p, 2) - 6 * p + 1) / (variance(p)); | ||
| return (6 * Math.pow(p, 2) - 6 * p + 1) / (dvariance(p)); | ||
| } | ||
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| tape("randomBernoulli(p) returns random bernoulli distributed numbers with a mean of p", test => { | ||
| var randomBernoulli = d3.randomBernoulli.source(d3.randomLcg(0.48444190806583465)); | ||
| test.inDelta(d3.mean(d3.range(10000).map(randomBernoulli(1))), mean(1), variance(1)); | ||
| test.inDelta(d3.mean(d3.range(10000).map(randomBernoulli(.5))), mean(.5), variance(.5)); | ||
| test.inDelta(d3.mean(d3.range(10000).map(randomBernoulli(.25))), mean(.25), variance(.25)); | ||
| test.inDelta(d3.mean(d3.range(10000).map(randomBernoulli(0))), mean(0), variance(0)); | ||
| it("randomBernoulli(p) returns random bernoulli distributed numbers with a mean of p", () => { | ||
| const r = randomBernoulli.source(randomLcg(0.48444190806583465)); | ||
| assertInDelta(mean(range(10000).map(r(1))), dmean(1), dvariance(1)); | ||
| assertInDelta(mean(range(10000).map(r(0.5))), dmean(0.5), dvariance(0.5)); | ||
| assertInDelta(mean(range(10000).map(r(0.25))), dmean(0.25), dvariance(0.25)); | ||
| assertInDelta(mean(range(10000).map(r(0))), dmean(0), dvariance(0)); | ||
| }); | ||
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| tape("randomBernoulli(p) returns random bernoulli distributed numbers with a variance of p * (1 - p)", test => { | ||
| var randomBernoulli = d3.randomBernoulli.source(d3.randomLcg(0.9781605192898934)); | ||
| test.inDelta(d3.variance(d3.range(10000).map(randomBernoulli(1))), variance(1), 0); | ||
| test.inDelta(d3.variance(d3.range(10000).map(randomBernoulli(.5))), variance(.5), 0.05); | ||
| test.inDelta(d3.variance(d3.range(10000).map(randomBernoulli(.25))), variance(.25), 0.05); | ||
| test.inDelta(d3.variance(d3.range(10000).map(randomBernoulli(0))), variance(0), 0); | ||
| it("randomBernoulli(p) returns random bernoulli distributed numbers with a variance of p * (1 - p)", () => { | ||
| const r = randomBernoulli.source(randomLcg(0.9781605192898934)); | ||
| assertInDelta(variance(range(10000).map(r(1))), dvariance(1), 0); | ||
| assertInDelta(variance(range(10000).map(r(0.5))), dvariance(0.5), 0.05); | ||
| assertInDelta(variance(range(10000).map(r(0.25))), dvariance(0.25), 0.05); | ||
| assertInDelta(variance(range(10000).map(r(0))), dvariance(0), 0); | ||
| }); | ||
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| tape("randomBernoulli(p) returns random bernoulli distributed numbers with a skewness of (1 - 2 * p) / sqrt(p * (1 - p)).", test => { | ||
| var randomBernoulli = d3.randomBernoulli.source(d3.randomLcg(0.9776249148208429)); | ||
| test.inDelta(skewness(d3.range(10000).map(randomBernoulli(.5))), skew(.5), 0.08); | ||
| test.inDelta(skewness(d3.range(10000).map(randomBernoulli(.25))), skew(.25), 0.05); | ||
| it("randomBernoulli(p) returns random bernoulli distributed numbers with a skewness of (1 - 2 * p) / sqrt(p * (1 - p)).", () => { | ||
| const r = randomBernoulli.source(randomLcg(0.9776249148208429)); | ||
| assertInDelta(skewness(range(10000).map(r(0.5))), skew(0.5), 0.08); | ||
| assertInDelta(skewness(range(10000).map(r(0.25))), skew(0.25), 0.05); | ||
| }); | ||
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| tape("randomBernoulli(p) returns random bernoulli distributed numbers with a kurtosis excess of (6 * p^2 - 6 * p - 1) / (p * (1 - p)).", test => { | ||
| var randomBernoulli = d3.randomBernoulli.source(d3.randomLcg(0.8260973119979638)); | ||
| test.inDelta(kurtosis(d3.range(10000).map(randomBernoulli(.05))), kurt(.05), kurt(.05) * 0.2); | ||
| test.inDelta(kurtosis(d3.range(10000).map(randomBernoulli(.10))), kurt(.10), kurt(.10) * 0.2); | ||
| test.inDelta(kurtosis(d3.range(10000).map(randomBernoulli(.15))), kurt(.15), kurt(.15) * 0.2); | ||
| test.inDelta(kurtosis(d3.range(50000).map(randomBernoulli(.20))), kurt(.20), kurt(.20) * 0.4); | ||
| it("randomBernoulli(p) returns random bernoulli distributed numbers with a kurtosis excess of (6 * p^2 - 6 * p - 1) / (p * (1 - p)).", () => { | ||
| const r = randomBernoulli.source(randomLcg(0.8260973119979638)); | ||
| assertInDelta(kurtosis(range(10000).map(r(0.05))), kurt(0.05), kurt(0.05) * 0.2); | ||
| assertInDelta(kurtosis(range(10000).map(r(0.10))), kurt(0.10), kurt(0.10) * 0.2); | ||
| assertInDelta(kurtosis(range(10000).map(r(0.15))), kurt(0.15), kurt(0.15) * 0.2); | ||
| assertInDelta(kurtosis(range(50000).map(r(0.20))), kurt(0.20), kurt(0.20) * 0.4); | ||
| }); |
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