element-portable/src/utils/arrays.ts

/*
Copyright 2024 New Vector Ltd.
Copyright 2020, 2021 The Matrix.org Foundation C.I.C.

SPDX-License-Identifier: AGPL-3.0-only OR GPL-3.0-only
Please see LICENSE files in the repository root for full details.
*/

import { percentageOf, percentageWithin } from "./numbers";

/**
 * Quickly resample an array to have less/more data points. If an input which is larger
 * than the desired size is provided, it will be downsampled. Similarly, if the input
 * is smaller than the desired size then it will be upsampled.
 * @param {number[]} input The input array to resample.
 * @param {number} points The number of samples to end up with.
 * @returns {number[]} The resampled array.
 */
export function arrayFastResample(input: number[], points: number): number[] {
    if (input.length === points) return input; // short-circuit a complicated call

    // Heavily inspired by matrix-media-repo (used with permission)
    // https://github.com/turt2live/matrix-media-repo/blob/abe72c87d2e29/util/util_audio/fastsample.go#L10
    const samples: number[] = [];
    if (input.length > points) {
        // Danger: this loop can cause out of memory conditions if the input is too small.
        const everyNth = Math.round(input.length / points);
        for (let i = 0; i < input.length; i += everyNth) {
            samples.push(input[i]);
        }
    } else {
        // Smaller inputs mean we have to spread the values over the desired length. We
        // end up overshooting the target length in doing this, but we're not looking to
        // be super accurate so we'll let the sanity trims do their job.
        const spreadFactor = Math.ceil(points / input.length);
        for (const val of input) {
            samples.push(...arraySeed(val, spreadFactor));
        }
    }

    // Trim to size & return
    return arrayTrimFill(samples, points, arraySeed(input[input.length - 1], points));
}

/**
 * Attempts a smooth resample of the given array. This is functionally similar to arrayFastResample
 * though can take longer due to the smoothing of data.
 * @param {number[]} input The input array to resample.
 * @param {number} points The number of samples to end up with.
 * @returns {number[]} The resampled array.
 */
// ts-prune-ignore-next
export function arraySmoothingResample(input: number[], points: number): number[] {
    if (input.length === points) return input; // short-circuit a complicated call

    let samples: number[] = [];
    if (input.length > points) {
        // We're downsampling. To preserve the curve we'll actually reduce our sample
        // selection and average some points between them.

        // All we're doing here is repeatedly averaging the waveform down to near our
        // target value. We don't average down to exactly our target as the loop might
        // never end, and we can over-average the data. Instead, we'll get as far as
        // we can and do a followup fast resample (the neighbouring points will be close
        // to the actual waveform, so we can get away with this safely).
        while (samples.length > points * 2 || samples.length === 0) {
            samples = [];
            for (let i = 1; i < input.length - 1; i += 2) {
                const prevPoint = input[i - 1];
                const nextPoint = input[i + 1];
                const currPoint = input[i];
                const average = (prevPoint + nextPoint + currPoint) / 3;
                samples.push(average);
            }
            input = samples;
        }

        return arrayFastResample(samples, points);
    } else {
        // In practice there's not much purpose in burning CPU for short arrays only to
        // end up with a result that can't possibly look much different than the fast
        // resample, so just skip ahead to the fast resample.
        return arrayFastResample(input, points);
    }
}

/**
 * Rescales the input array to have values that are inclusively within the provided
 * minimum and maximum.
 * @param {number[]} input The array to rescale.
 * @param {number} newMin The minimum value to scale to.
 * @param {number} newMax The maximum value to scale to.
 * @returns {number[]} The rescaled array.
 */
// ts-prune-ignore-next
export function arrayRescale(input: number[], newMin: number, newMax: number): number[] {
    const min: number = Math.min(...input);
    const max: number = Math.max(...input);
    return input.map((v) => percentageWithin(percentageOf(v, min, max), newMin, newMax));
}

/**
 * Creates an array of the given length, seeded with the given value.
 * @param {T} val The value to seed the array with.
 * @param {number} length The length of the array to create.
 * @returns {T[]} The array.
 */
export function arraySeed<T>(val: T, length: number): T[] {
    // Size the array up front for performance, and use `fill` to let the browser
    // optimize the operation better than we can with a `for` loop, if it wants.
    return new Array<T>(length).fill(val);
}

/**
 * Trims or fills the array to ensure it meets the desired length. The seed array
 * given is pulled from to fill any missing slots - it is recommended that this be
 * at least `len` long. The resulting array will be exactly `len` long, either
 * trimmed from the source or filled with the some/all of the seed array.
 * @param {T[]} a The array to trim/fill.
 * @param {number} len The length to trim or fill to, as needed.
 * @param {T[]} seed Values to pull from if the array needs filling.
 * @returns {T[]} The resulting array of `len` length.
 */
export function arrayTrimFill<T>(a: T[], len: number, seed: T[]): T[] {
    // Dev note: we do length checks because the spread operator can result in some
    // performance penalties in more critical code paths. As a utility, it should be
    // as fast as possible to not cause a problem for the call stack, no matter how
    // critical that stack is.
    if (a.length === len) return a;
    if (a.length > len) return a.slice(0, len);
    return a.concat(seed.slice(0, len - a.length));
}

/**
 * Clones an array as fast as possible, retaining references of the array's values.
 * @param a The array to clone. Must be defined.
 * @returns A copy of the array.
 */
export function arrayFastClone<T>(a: T[]): T[] {
    return a.slice(0, a.length);
}

/**
 * Determines if the two arrays are different either in length, contents,
 * or order of those contents.
 * @param a The first array. Must be defined.
 * @param b The second array. Must be defined.
 * @returns True if they are different, false otherwise.
 */
export function arrayHasOrderChange(a: any[], b: any[]): boolean {
    if (a.length === b.length) {
        for (let i = 0; i < a.length; i++) {
            if (a[i] !== b[i]) return true;
        }
        return false;
    } else {
        return true; // like arrayHasDiff, a difference in length is a natural change
    }
}

/**
 * Determines if two arrays are different through a shallow comparison.
 * @param a The first array. Must be defined.
 * @param b The second array. Must be defined.
 * @returns True if they are different, false otherwise.
 */
export function arrayHasDiff(a: any[], b: any[]): boolean {
    if (a.length === b.length) {
        // When the lengths are equal, check to see if either array is missing
        // an element from the other.
        if (b.some((i) => !a.includes(i))) return true;
        if (a.some((i) => !b.includes(i))) return true;

        // if all the keys are common, say so
        return false;
    } else {
        return true; // different lengths means they are naturally diverged
    }
}

export type Diff<T> = { added: T[]; removed: T[] };

/**
 * Performs a diff on two arrays. The result is what is different with the
 * first array (`added` in the returned object means objects in B that aren't
 * in A). Shallow comparisons are used to perform the diff.
 * @param a The first array. Must be defined.
 * @param b The second array. Must be defined.
 * @returns The diff between the arrays.
 */
export function arrayDiff<T>(a: T[], b: T[]): Diff<T> {
    return {
        added: b.filter((i) => !a.includes(i)),
        removed: a.filter((i) => !b.includes(i)),
    };
}

/**
 * Returns the intersection of two arrays.
 * @param a The first array. Must be defined.
 * @param b The second array. Must be defined.
 * @returns The intersection of the arrays.
 */
export function arrayIntersection<T>(a: T[], b: T[]): T[] {
    return a.filter((i) => b.includes(i));
}

/**
 * Unions arrays, deduping contents using a Set.
 * @param a The arrays to merge.
 * @returns The union of all given arrays.
 */
export function arrayUnion<T>(...a: T[][]): T[] {
    return Array.from(
        a.reduce((c, v) => {
            v.forEach((i) => c.add(i));
            return c;
        }, new Set<T>()),
    );
}

/**
 * Moves a single element from fromIndex to toIndex.
 * @param {array} list the list from which to construct the new list.
 * @param {number} fromIndex the index of the element to move.
 * @param {number} toIndex the index of where to put the element.
 * @returns {array} A new array with the requested value moved.
 */
export function moveElement<T>(list: T[], fromIndex: number, toIndex: number): T[] {
    const result = Array.from(list);
    const [removed] = result.splice(fromIndex, 1);
    result.splice(toIndex, 0, removed);

    return result;
}

/**
 * Helper functions to perform LINQ-like queries on arrays.
 */
export class ArrayUtil<T> {
    /**
     * Create a new array helper.
     * @param a The array to help. Can be modified in-place.
     */
    public constructor(private a: T[]) {}

    /**
     * The value of this array, after all appropriate alterations.
     */
    public get value(): T[] {
        return this.a;
    }

    /**
     * Groups an array by keys.
     * @param fn The key-finding function.
     * @returns This.
     */
    public groupBy<K>(fn: (a: T) => K): GroupedArray<K, T> {
        const obj = this.a.reduce((rv: Map<K, T[]>, val: T) => {
            const k = fn(val);
            if (!rv.has(k)) rv.set(k, []);
            rv.get(k)!.push(val);
            return rv;
        }, new Map<K, T[]>());
        return new GroupedArray(obj);
    }
}

/**
 * Helper functions to perform LINQ-like queries on groups (maps).
 */
export class GroupedArray<K, T> {
    /**
     * Creates a new group helper.
     * @param val The group to help. Can be modified in-place.
     */
    public constructor(private val: Map<K, T[]>) {}

    /**
     * The value of this group, after all applicable alterations.
     */
    public get value(): Map<K, T[]> {
        return this.val;
    }

    /**
     * Orders the grouping into an array using the provided key order.
     * @param keyOrder The key order.
     * @returns An array helper of the result.
     */
    public orderBy(keyOrder: K[]): ArrayUtil<T> {
        const a: T[] = [];
        for (const k of keyOrder) {
            if (!this.val.has(k)) continue;
            a.push(...this.val.get(k)!);
        }
        return new ArrayUtil(a);
    }
}

export const concat = (...arrays: Uint8Array[]): Uint8Array => {
    return arrays.reduce((concatenatedSoFar: Uint8Array, toBeConcatenated: Uint8Array) => {
        const concatenated = new Uint8Array(concatenatedSoFar.length + toBeConcatenated.length);
        concatenated.set(concatenatedSoFar, 0);
        concatenated.set(toBeConcatenated, concatenatedSoFar.length);
        return concatenated;
    }, new Uint8Array(0));
};

/**
 * Async version of Array.every.
 */
export async function asyncEvery<T>(values: Iterable<T>, predicate: (value: T) => Promise<boolean>): Promise<boolean> {
    for (const value of values) {
        if (!(await predicate(value))) return false;
    }
    return true;
}

/**
 * Async version of Array.some.
 */
export async function asyncSome<T>(values: Iterable<T>, predicate: (value: T) => Promise<boolean>): Promise<boolean> {
    for (const value of values) {
        if (await predicate(value)) return true;
    }
    return false;
}

export function filterBoolean<T>(values: Array<T | null | undefined>): T[] {
    return values.filter(Boolean) as T[];
}