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34e62e3
feat(number): add exponentialDistribution function
ST-DDT d3236f4
chore: simplify tables
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feat(number): introduce distributor functions
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Merge branch 'next' into feat/number/exponentional-distribution
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docs: fix missing param tags
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docs: add distributors api docs
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Merge branch 'next' into feat/number/exponentional-distribution
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Merge branch 'next' into feat/number/exponentional-distribution
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docs: minor rephrasing for more natural language
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docs: update @since tags to 10.3.0
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Merge branch 'next' into feat/number/exponentional-distribution
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docs: refreshable distributor examples
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chore: simplify
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Merge branch 'next' into feat/number/exponentional-distribution
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Merge branch 'next' into feat/number/exponentional-distribution
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| Original file line number | Diff line number | Diff line change |
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| import type { Randomizer } from '../randomizer'; | ||
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| /** | ||
| * A function that determines the distribution of generated values. | ||
| * Values generated by a randomizer are considered uniformly distributed, distributor functions can be used to change this. | ||
| * If many results are collected the results form a limited distribution between `0` and `1`. | ||
| * So an exponential distributor's values will resemble a limited exponential distribution. | ||
| * | ||
| * Common examples of distributor functions are: | ||
| * | ||
| * - Uniform distributor: All values have the same likelihood. | ||
| * - Normal distributor: Values are more likely to be close to a specific value. | ||
| * - Exponential distributor: Values are more likely to be close to 0. | ||
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| * | ||
| * Distributor functions can be used by some faker functions such as `faker.number.int()` and `faker.number.float()`. | ||
| * | ||
| * Please note that the result from the distributor function is processed further by the function accepting it. | ||
| * E.g. a distributor result of `0.5` within a call to `faker.number.int({ min: 10, max: 20 })` will result in `15`. | ||
| * | ||
| * @param randomizer The randomizer to use for generating values. | ||
| * | ||
| * @returns Generates a random float between 0 (inclusive) and 1 (exclusive). | ||
| * | ||
| * @example | ||
| * import { Distributor, Randomizer, faker } from '@faker-js/faker'; | ||
| * | ||
| * const alwaysMin: Distributor = () => 0; | ||
| * faker.number.int({ min: 2, max: 10, distributor: alwaysMin }); // 2 | ||
| * faker.number.int({ min: 2, max: 10, distributor: alwaysMin }); // 2 | ||
| * faker.number.int({ min: 2, max: 10, distributor: alwaysMin }); // 2 | ||
| * | ||
| * const uniform: Distributor = (randomizer: Randomizer) => randomizer.next(); | ||
| * faker.number.int({ min: 0, max: 10, distributor: uniform }); // 5 | ||
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| * faker.number.int({ min: 0, max: 10, distributor: uniform }); // 2 | ||
| * faker.number.int({ min: 0, max: 10, distributor: uniform }); // 9 | ||
| * | ||
| * @since 10.4.0 | ||
| */ | ||
| export type Distributor = (randomizer: Randomizer) => number; | ||
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| Original file line number | Diff line number | Diff line change |
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| @@ -0,0 +1,122 @@ | ||
| import { FakerError } from '../errors/faker-error'; | ||
| import type { Distributor } from './distributor'; | ||
| import { uniformDistributor } from './uniform'; | ||
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| /** | ||
| * Creates a new function that generates power-law/exponentially distributed values. | ||
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| * This function uses `(base ** next() - 1) / (base - 1)` to spread the values. | ||
| * | ||
| * The following table shows the rough distribution of values generated using `exponentialDistributor({ base: x })`: | ||
| * | ||
| * | Result | Base 0.1 | Base 0.5 | Base 1 | Base 2 | Base 10 | | ||
| * | :-------: | -------: | -------: | -----: | -----: | ------: | | ||
| * | 0.0 - 0.1 | 4.1% | 7.4% | 10.0% | 13.8% | 27.8% | | ||
| * | 0.1 - 0.2 | 4.5% | 7.8% | 10.0% | 12.5% | 16.9% | | ||
| * | 0.2 - 0.3 | 5.0% | 8.2% | 10.0% | 11.5% | 12.1% | | ||
| * | 0.3 - 0.4 | 5.7% | 8.7% | 10.0% | 10.7% | 9.4% | | ||
| * | 0.4 - 0.5 | 6.6% | 9.3% | 10.0% | 10.0% | 7.8% | | ||
| * | 0.5 - 0.6 | 7.8% | 9.9% | 10.0% | 9.3% | 6.6% | | ||
| * | 0.6 - 0.7 | 9.4% | 10.7% | 10.0% | 8.8% | 5.7% | | ||
| * | 0.7 - 0.8 | 12.1% | 11.5% | 10.0% | 8.2% | 5.0% | | ||
| * | 0.8 - 0.9 | 16.9% | 12.6% | 10.0% | 7.8% | 4.5% | | ||
| * | 0.9 - 1.0 | 27.9% | 13.8% | 10.0% | 7.5% | 4.1% | | ||
| * | ||
| * The following table shows the rough distribution of values generated using `exponentialDistributor({ bias: x })`: | ||
| * | ||
| * | Result | Bias -9 | Bias -1 | Bias 0 | Bias 1 | Bias 9 | | ||
| * | :-------: | ------: | ------: | -----: | -----: | -----: | | ||
| * | 0.0 - 0.1 | 27.9% | 13.7% | 10.0% | 7.4% | 4.1% | | ||
| * | 0.1 - 0.2 | 16.9% | 12.5% | 10.0% | 7.8% | 4.5% | | ||
| * | 0.2 - 0.3 | 12.1% | 11.6% | 10.0% | 8.3% | 5.1% | | ||
| * | 0.3 - 0.4 | 9.5% | 10.7% | 10.0% | 8.8% | 5.7% | | ||
| * | 0.4 - 0.5 | 7.8% | 10.0% | 10.0% | 9.3% | 6.6% | | ||
| * | 0.5 - 0.6 | 6.6% | 9.3% | 10.0% | 9.9% | 7.7% | | ||
| * | 0.6 - 0.7 | 5.7% | 8.8% | 10.0% | 10.7% | 9.5% | | ||
| * | 0.7 - 0.8 | 5.0% | 8.2% | 10.0% | 11.5% | 12.1% | | ||
| * | 0.8 - 0.9 | 4.5% | 7.8% | 10.0% | 12.6% | 16.8% | | ||
| * | 0.9 - 1.0 | 4.1% | 7.4% | 10.0% | 13.7% | 27.9% | | ||
| * | ||
| * @param options The options for generating the distributor. | ||
| * @param options.base The base of the exponential distribution. Should be greater than 0. Defaults to `2`. | ||
| * The higher/more above `1` the `base`, the more likely the number will be closer to the minimum value. | ||
| * The lower/closer to zero the `base`, the more likely the number will be closer to the maximum value. | ||
| * Values of `1` will generate a uniform distributor. | ||
| * Can alternatively be configured using the `bias` option. | ||
| * @param options.bias An alternative way to specify the `base`. Also accepts values below zero. Defaults to `-1`. | ||
| * The higher/more positive the `bias`, the more likely the number will be closer to the maximum value. | ||
| * The lower/more negative the `bias`, the more likely the number will be closer to the minimum value. | ||
| * Values of `0` will generate a uniform distributor. | ||
| * Can alternatively be configured using the `base` option. | ||
| * | ||
| * @example | ||
| * import { exponentialDistributor, generateMersenne53Randomizer } from '@faker-js/faker'; | ||
| * | ||
| * const randomizer = generateMersenne53Randomizer(); | ||
| * const distributor = exponentialDistributor(); | ||
| * distributor(randomizer) // 0.04643770898904198 | ||
| * distributor(randomizer) // 0.13436127925491848 | ||
| * distributor(randomizer) // 0.4202905589842396 | ||
| * distributor(randomizer) // 0.5164955927828387 | ||
| * distributor(randomizer) // 0.3476359433171099 | ||
| * | ||
| * @since 10.4.0 | ||
| */ | ||
| export function exponentialDistributor( | ||
| options?: | ||
| | { | ||
| /** | ||
| * The base of the exponential distribution. Should be greater than 0. | ||
| * The higher/more above `1` the `base`, the more likely the number will be closer to the minimum value. | ||
| * The lower/closer to zero the `base`, the more likely the number will be closer to the maximum value. | ||
| * Values of `1` will generate a uniform distribution. | ||
| * Can alternatively be configured using the `bias` option. | ||
| * | ||
| * @default 2 | ||
| */ | ||
| base?: number; | ||
| } | ||
| | { | ||
| /** | ||
| * An alternative way to specify the `base`. Also accepts values below zero. | ||
| * The higher/more positive the `bias`, the more likely the number will be closer to the maximum value. | ||
| * The lower/more negative the `bias`, the more likely the number will be closer to the minimum value. | ||
| * Values of `0` will generate a uniform distribution. | ||
| * Can alternatively be configured using the `base` option. | ||
| * | ||
| * @default -1 | ||
| */ | ||
| bias?: number; | ||
| } | ||
| ): Distributor; | ||
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| /** | ||
| * Creates a new function that generates exponentially distributed values. | ||
| * This function uses `(base ** next() - 1) / (base - 1)` to spread the values. | ||
| * | ||
| * @param options The options for generating the distributor. | ||
| * @param options.base The base of the exponential distribution. Should be greater than 0. Defaults to `2`. | ||
| * The higher/more above `1` the `base`, the more likely the number will be closer to the minimum value. | ||
| * The lower/closer to zero the `base`, the more likely the number will be closer to the maximum value. | ||
| * Values of `1` will generate a uniform distributor. | ||
| * Can alternatively be configured using the `bias` option. | ||
| * @param options.bias An alternative way to specify the `base`. Also accepts values below zero. Defaults to `-1`. | ||
| * The higher/more positive the `bias`, the more likely the number will be closer to the maximum value. | ||
| * The lower/more negative the `bias`, the more likely the number will be closer to the minimum value. | ||
| * Values of `0` will generate a uniform distributor. | ||
| * Can alternatively be configured using the `base` option. | ||
| */ | ||
| export function exponentialDistributor( | ||
| options: { | ||
| base?: number; | ||
| bias?: number; | ||
| } = {} | ||
| ): Distributor { | ||
| const { bias = -1, base = bias <= 0 ? -bias + 1 : 1 / (bias + 1) } = options; | ||
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| if (base === 1) { | ||
| return uniformDistributor(); | ||
| } else if (base <= 0) { | ||
| throw new FakerError('Base should be greater than 0.'); | ||
| } | ||
|
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| return ({ next }) => (base ** next() - 1) / (base - 1); | ||
| } | ||
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,41 @@ | ||
| import type { Distributor } from './distributor'; | ||
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| /** | ||
| * Creates a new function that generates uniformly distributed values. | ||
| * The likelihood of each value is the same. | ||
| * | ||
| * The following table shows the rough distribution of values generated using `uniformDistributor()`: | ||
| * | ||
| * | Result | Uniform | | ||
| * | :-------: | ------: | | ||
| * | 0.0 - 0.1 | 10.0% | | ||
| * | 0.1 - 0.2 | 10.0% | | ||
| * | 0.2 - 0.3 | 10.0% | | ||
| * | 0.3 - 0.4 | 10.0% | | ||
| * | 0.4 - 0.5 | 10.0% | | ||
| * | 0.5 - 0.6 | 10.0% | | ||
| * | 0.6 - 0.7 | 10.0% | | ||
| * | 0.7 - 0.8 | 10.0% | | ||
| * | 0.8 - 0.9 | 10.0% | | ||
| * | 0.9 - 1.0 | 10.0% | | ||
| * | ||
| * @returns A new uniform distributor function. | ||
| * | ||
| * @example | ||
| * import { generateMersenne53Randomizer, uniformDistributor } from '@faker-js/faker'; | ||
| * | ||
| * const randomizer = generateMersenne53Randomizer(); | ||
| * const distributor = uniformDistributor(); | ||
| * distributor(randomizer) // 0.9100215692561207 | ||
| * distributor(randomizer) // 0.791632947887336 | ||
| * distributor(randomizer) // 0.14770035310214324 | ||
| * distributor(randomizer) // 0.28282249581185814 | ||
| * distributor(randomizer) // 0.017890944117802343 | ||
| * | ||
| * @since 10.4.0 | ||
| */ | ||
| export function uniformDistributor(): Distributor { | ||
| return UNIFORM_DISTRIBUTOR; | ||
| } | ||
|
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| const UNIFORM_DISTRIBUTOR: Distributor = ({ next }) => next(); | ||
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