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feat: update stats/strided/distances TypeScript declarations #9936

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kgryte merged 1 commit into from
Jan 28, 2026
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feat: update stats/strided/distances TypeScript declarations #9936

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184 changes: 182 additions & 2 deletions lib/node_modules/@stdlib/stats/strided/distances/docs/types/index.d.ts
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Expand Up @@ -20,16 +20,196 @@

/* eslint-disable max-lines */

import dchebychev = require( '@stdlib/stats/strided/distances/dchebychev' );
import dcityblock = require( '@stdlib/stats/strided/distances/dcityblock' );
import dcosineDistance = require( '@stdlib/stats/strided/distances/dcosine-distance' );
import dcosineSimilarity = require( '@stdlib/stats/strided/distances/dcosine-similarity' );
import deuclidean = require( '@stdlib/stats/strided/distances/deuclidean' );
import dsquaredEuclidean = require( '@stdlib/stats/strided/distances/dsquared-euclidean' );

/**
* Interface describing a namespace.
* Interface describing the `distances` namespace.
*/
interface Namespace {
/**
* TODO
* Computes the Chebychev distance between two double-precision floating-point strided arrays.
*
* @param N - number of indexed elements
* @param x - first input array
* @param strideX - `x` stride length
* @param y - second input array
* @param strideY - `y` stride length
* @returns Chebychev distance
*
* @example
* var Float64Array = require( '@stdlib/array/float64' );
*
* var x = new Float64Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] );
* var y = new Float64Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] );
*
* var z = ns.dchebychev( x.length, x, 1, y, 1 );
* // returns 9.0
*
* @example
* var Float64Array = require( '@stdlib/array/float64' );
*
* var x = new Float64Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] );
* var y = new Float64Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] );
*
* var z = ns.dchebychev.ndarray( x.length, x, 1, 0, y, 1, 0 );
* // returns 9.0
*/
dchebychev: typeof dchebychev;

/**
* Computes the city block (Manhattan) distance between two double-precision floating-point strided arrays.
*
* @param N - number of indexed elements
* @param x - first input array
* @param strideX - `x` stride length
* @param y - second input array
* @param strideY - `y` stride length
* @returns city block (Manhattan) distance
*
* @example
* var Float64Array = require( '@stdlib/array/float64' );
*
* var x = new Float64Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] );
* var y = new Float64Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] );
*
* var z = ns.dcityblock( x.length, x, 1, y, 1 );
* // returns 26.0
*
* @example
* var Float64Array = require( '@stdlib/array/float64' );
*
* var x = new Float64Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] );
* var y = new Float64Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] );
*
* var z = ns.dcityblock.ndarray( x.length, x, 1, 0, y, 1, 0 );
* // returns 26.0
*/
dcityblock: typeof dcityblock;

/**
* Computes the cosine distance between two double-precision floating-point strided arrays.
*
* @param N - number of indexed elements
* @param x - first input array
* @param strideX - `x` stride length
* @param y - second input array
* @param strideY - `y` stride length
* @returns cosine distance
*
* @example
* var Float64Array = require( '@stdlib/array/float64' );
*
* var x = new Float64Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] );
* var y = new Float64Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] );
*
* var z = ns.dcosineDistance( x.length, x, 1, y, 1 );
* // returns ~1.061
*
* @example
* var Float64Array = require( '@stdlib/array/float64' );
*
* var x = new Float64Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] );
* var y = new Float64Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] );
*
* var z = ns.dcosineDistance.ndarray( x.length, x, 1, 0, y, 1, 0 );
* // returns ~1.061
*/
dcosineDistance: typeof dcosineDistance;

/**
* Computes the cosine similarity of two double-precision floating-point strided arrays.
*
* @param N - number of indexed elements
* @param x - first input array
* @param strideX - `x` stride length
* @param y - second input array
* @param strideY - `y` stride length
* @returns cosine similarity
*
* @example
* var Float64Array = require( '@stdlib/array/float64' );
*
* var x = new Float64Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] );
* var y = new Float64Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] );
*
* var z = ns.dcosineSimilarity( x.length, x, 1, y, 1 );
* // returns ~-0.061
*
* @example
* var Float64Array = require( '@stdlib/array/float64' );
*
* var x = new Float64Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] );
* var y = new Float64Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] );
*
* var z = ns.dcosineSimilarity.ndarray( x.length, x, 1, 0, y, 1, 0 );
* // returns ~-0.061
*/
dcosineSimilarity: typeof dcosineSimilarity;

/**
* Computes the Euclidean distance between two double-precision floating-point strided arrays.
*
* @param N - number of indexed elements
* @param x - first input array
* @param strideX - `x` stride length
* @param y - second input array
* @param strideY - `y` stride length
* @returns Euclidean distance
*
* @example
* var Float64Array = require( '@stdlib/array/float64' );
*
* var x = new Float64Array( [ 1.0, 2.0, 2.0, -7.0, -2.0, 3.0, 4.0, 2.0 ] );
* var y = new Float64Array( [ 2.0, 1.0, 2.0, 1.0, -2.0, 2.0, 3.0, 4.0 ] );
*
* var z = ns.deuclidean( x.length, x, 1, y, 1 );
* // returns ~8.485
*
* @example
* var Float64Array = require( '@stdlib/array/float64' );
*
* var x = new Float64Array( [ 1.0, 2.0, 2.0, -7.0, -2.0, 3.0, 4.0, 2.0 ] );
* var y = new Float64Array( [ 2.0, 1.0, 2.0, 1.0, -2.0, 2.0, 3.0, 4.0 ] );
*
* var z = ns.deuclidean.ndarray( x.length, x, 1, 0, y, 1, 0 );
* // returns ~8.485
*/
deuclidean: typeof deuclidean;

/**
* Computes the squared Euclidean distance between two double-precision floating-point strided arrays.
*
* @param N - number of indexed elements
* @param x - first input array
* @param strideX - `x` stride length
* @param y - second input array
* @param strideY - `y` stride length
* @returns squared Euclidean distance
*
* @example
* var Float64Array = require( '@stdlib/array/float64' );
*
* var x = new Float64Array( [ 1.0, 2.0, 2.0, -7.0, -2.0, 3.0, 4.0, 2.0 ] );
* var y = new Float64Array( [ 2.0, 1.0, 2.0, 1.0, -2.0, 2.0, 3.0, 4.0 ] );
*
* var z = ns.dsquaredEuclidean( x.length, x, 1, y, 1 );
* // returns 72.0
*
* @example
* var Float64Array = require( '@stdlib/array/float64' );
*
* var x = new Float64Array( [ 1.0, 2.0, 2.0, -7.0, -2.0, 3.0, 4.0, 2.0 ] );
* var y = new Float64Array( [ 2.0, 1.0, 2.0, 1.0, -2.0, 2.0, 3.0, 4.0 ] );
*
* var z = ns.dsquaredEuclidean.ndarray( x.length, x, 1, 0, y, 1, 0 );
* // returns 72.0
*/
dsquaredEuclidean: typeof dsquaredEuclidean;
}

/**
Expand Down