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306 lines
11 KiB
TypeScript
306 lines
11 KiB
TypeScript
/*
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Copyright 2020, 2021 The Matrix.org Foundation C.I.C.
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Licensed under the Apache License, Version 2.0 (the "License");
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you may not use this file except in compliance with the License.
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You may obtain a copy of the License at
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http://www.apache.org/licenses/LICENSE-2.0
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Unless required by applicable law or agreed to in writing, software
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distributed under the License is distributed on an "AS IS" BASIS,
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WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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See the License for the specific language governing permissions and
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limitations under the License.
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*/
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import { percentageOf, percentageWithin } from "./numbers";
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/**
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* Quickly resample an array to have less/more data points. If an input which is larger
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* than the desired size is provided, it will be downsampled. Similarly, if the input
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* is smaller than the desired size then it will be upsampled.
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* @param {number[]} input The input array to resample.
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* @param {number} points The number of samples to end up with.
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* @returns {number[]} The resampled array.
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*/
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export function arrayFastResample(input: number[], points: number): number[] {
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if (input.length === points) return input; // short-circuit a complicated call
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// Heavily inspired by matrix-media-repo (used with permission)
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// https://github.com/turt2live/matrix-media-repo/blob/abe72c87d2e29/util/util_audio/fastsample.go#L10
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const samples: number[] = [];
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if (input.length > points) {
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// Danger: this loop can cause out of memory conditions if the input is too small.
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const everyNth = Math.round(input.length / points);
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for (let i = 0; i < input.length; i += everyNth) {
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samples.push(input[i]);
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}
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} else {
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// Smaller inputs mean we have to spread the values over the desired length. We
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// end up overshooting the target length in doing this, but we're not looking to
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// be super accurate so we'll let the sanity trims do their job.
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const spreadFactor = Math.ceil(points / input.length);
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for (const val of input) {
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samples.push(...arraySeed(val, spreadFactor));
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}
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}
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// Trim to size & return
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return arrayTrimFill(samples, points, arraySeed(input[input.length - 1], points));
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}
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/**
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* Attempts a smooth resample of the given array. This is functionally similar to arrayFastResample
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* though can take longer due to the smoothing of data.
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* @param {number[]} input The input array to resample.
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* @param {number} points The number of samples to end up with.
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* @returns {number[]} The resampled array.
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*/
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export function arraySmoothingResample(input: number[], points: number): number[] {
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if (input.length === points) return input; // short-circuit a complicated call
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let samples: number[] = [];
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if (input.length > points) {
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// We're downsampling. To preserve the curve we'll actually reduce our sample
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// selection and average some points between them.
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// All we're doing here is repeatedly averaging the waveform down to near our
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// target value. We don't average down to exactly our target as the loop might
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// never end, and we can over-average the data. Instead, we'll get as far as
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// we can and do a followup fast resample (the neighbouring points will be close
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// to the actual waveform, so we can get away with this safely).
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while (samples.length > (points * 2) || samples.length === 0) {
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samples = [];
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for (let i = 1; i < input.length - 1; i += 2) {
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const prevPoint = input[i - 1];
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const nextPoint = input[i + 1];
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const currPoint = input[i];
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const average = (prevPoint + nextPoint + currPoint) / 3;
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samples.push(average);
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}
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input = samples;
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}
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return arrayFastResample(samples, points);
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} else {
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// In practice there's not much purpose in burning CPU for short arrays only to
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// end up with a result that can't possibly look much different than the fast
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// resample, so just skip ahead to the fast resample.
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return arrayFastResample(input, points);
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}
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}
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/**
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* Rescales the input array to have values that are inclusively within the provided
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* minimum and maximum.
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* @param {number[]} input The array to rescale.
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* @param {number} newMin The minimum value to scale to.
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* @param {number} newMax The maximum value to scale to.
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* @returns {number[]} The rescaled array.
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*/
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export function arrayRescale(input: number[], newMin: number, newMax: number): number[] {
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const min: number = Math.min(...input);
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const max: number = Math.max(...input);
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return input.map(v => percentageWithin(percentageOf(v, min, max), newMin, newMax));
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}
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/**
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* Creates an array of the given length, seeded with the given value.
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* @param {T} val The value to seed the array with.
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* @param {number} length The length of the array to create.
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* @returns {T[]} The array.
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*/
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export function arraySeed<T>(val: T, length: number): T[] {
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const a: T[] = [];
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for (let i = 0; i < length; i++) {
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a.push(val);
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}
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return a;
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}
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/**
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* Trims or fills the array to ensure it meets the desired length. The seed array
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* given is pulled from to fill any missing slots - it is recommended that this be
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* at least `len` long. The resulting array will be exactly `len` long, either
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* trimmed from the source or filled with the some/all of the seed array.
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* @param {T[]} a The array to trim/fill.
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* @param {number} len The length to trim or fill to, as needed.
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* @param {T[]} seed Values to pull from if the array needs filling.
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* @returns {T[]} The resulting array of `len` length.
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*/
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export function arrayTrimFill<T>(a: T[], len: number, seed: T[]): T[] {
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// Dev note: we do length checks because the spread operator can result in some
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// performance penalties in more critical code paths. As a utility, it should be
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// as fast as possible to not cause a problem for the call stack, no matter how
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// critical that stack is.
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if (a.length === len) return a;
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if (a.length > len) return a.slice(0, len);
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return a.concat(seed.slice(0, len - a.length));
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}
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/**
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* Clones an array as fast as possible, retaining references of the array's values.
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* @param a The array to clone. Must be defined.
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* @returns A copy of the array.
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*/
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export function arrayFastClone<T>(a: T[]): T[] {
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return a.slice(0, a.length);
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}
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/**
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* Determines if the two arrays are different either in length, contents,
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* or order of those contents.
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* @param a The first array. Must be defined.
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* @param b The second array. Must be defined.
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* @returns True if they are different, false otherwise.
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*/
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export function arrayHasOrderChange(a: any[], b: any[]): boolean {
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if (a.length === b.length) {
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for (let i = 0; i < a.length; i++) {
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if (a[i] !== b[i]) return true;
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}
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return false;
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} else {
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return true; // like arrayHasDiff, a difference in length is a natural change
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}
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}
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/**
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* Determines if two arrays are different through a shallow comparison.
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* @param a The first array. Must be defined.
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* @param b The second array. Must be defined.
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* @returns True if they are different, false otherwise.
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*/
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export function arrayHasDiff(a: any[], b: any[]): boolean {
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if (a.length === b.length) {
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// When the lengths are equal, check to see if either array is missing
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// an element from the other.
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if (b.some(i => !a.includes(i))) return true;
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if (a.some(i => !b.includes(i))) return true;
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// if all the keys are common, say so
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return false;
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} else {
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return true; // different lengths means they are naturally diverged
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}
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}
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/**
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* Performs a diff on two arrays. The result is what is different with the
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* first array (`added` in the returned object means objects in B that aren't
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* in A). Shallow comparisons are used to perform the diff.
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* @param a The first array. Must be defined.
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* @param b The second array. Must be defined.
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* @returns The diff between the arrays.
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*/
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export function arrayDiff<T>(a: T[], b: T[]): { added: T[], removed: T[] } {
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return {
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added: b.filter(i => !a.includes(i)),
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removed: a.filter(i => !b.includes(i)),
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};
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}
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/**
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* Returns the union of two arrays.
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* @param a The first array. Must be defined.
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* @param b The second array. Must be defined.
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* @returns The union of the arrays.
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*/
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export function arrayUnion<T>(a: T[], b: T[]): T[] {
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return a.filter(i => b.includes(i));
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}
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/**
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* Merges arrays, deduping contents using a Set.
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* @param a The arrays to merge.
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* @returns The merged array.
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*/
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export function arrayMerge<T>(...a: T[][]): T[] {
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return Array.from(a.reduce((c, v) => {
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v.forEach(i => c.add(i));
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return c;
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}, new Set<T>()));
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}
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/**
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* Moves a single element from fromIndex to toIndex.
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* @param {array} list the list from which to construct the new list.
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* @param {number} fromIndex the index of the element to move.
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* @param {number} toIndex the index of where to put the element.
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* @returns {array} A new array with the requested value moved.
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*/
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export function moveElement<T>(list: T[], fromIndex: number, toIndex: number): T[] {
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const result = Array.from(list);
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const [removed] = result.splice(fromIndex, 1);
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result.splice(toIndex, 0, removed);
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return result;
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}
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/**
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* Helper functions to perform LINQ-like queries on arrays.
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*/
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export class ArrayUtil<T> {
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/**
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* Create a new array helper.
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* @param a The array to help. Can be modified in-place.
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*/
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constructor(private a: T[]) {
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}
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/**
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* The value of this array, after all appropriate alterations.
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*/
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public get value(): T[] {
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return this.a;
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}
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/**
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* Groups an array by keys.
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* @param fn The key-finding function.
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* @returns This.
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*/
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public groupBy<K>(fn: (a: T) => K): GroupedArray<K, T> {
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const obj = this.a.reduce((rv: Map<K, T[]>, val: T) => {
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const k = fn(val);
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if (!rv.has(k)) rv.set(k, []);
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rv.get(k).push(val);
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return rv;
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}, new Map<K, T[]>());
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return new GroupedArray(obj);
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}
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}
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/**
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* Helper functions to perform LINQ-like queries on groups (maps).
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*/
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export class GroupedArray<K, T> {
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/**
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* Creates a new group helper.
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* @param val The group to help. Can be modified in-place.
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*/
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constructor(private val: Map<K, T[]>) {
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}
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/**
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* The value of this group, after all applicable alterations.
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*/
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public get value(): Map<K, T[]> {
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return this.val;
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}
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/**
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* Orders the grouping into an array using the provided key order.
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* @param keyOrder The key order.
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* @returns An array helper of the result.
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*/
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public orderBy(keyOrder: K[]): ArrayUtil<T> {
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const a: T[] = [];
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for (const k of keyOrder) {
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if (!this.val.has(k)) continue;
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a.push(...this.val.get(k));
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}
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return new ArrayUtil(a);
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}
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}
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