All files / stats/base/stdevpn/lib accessors.js

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/**
* @license Apache-2.0
*
* Copyright (c) 2025 The Stdlib Authors.
*
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
*    http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*/
 
'use strict';
 
// MODULES //
 
var isnan = require( '@stdlib/math/base/assert/is-nan' );
var sqrt = require( '@stdlib/math/base/special/sqrt' );
 
// MAIN //
/**
 * Computes the standard deviation of a strided array using a two-pass algorithm.
 *
 * @private
 * @param {PositiveInteger} N - number of indexed elements
 * @param {number} correction - degrees of freedom adjustment
 * @param {Object} x - input array object
 * @param {Collection} x.data - input array data
 * @param {Array<Function>} x.accessors - array element accessors
 * @param {integer} strideX - strideX length
 * @param {NonNegativeInteger} offsetX - starting index
 * @returns {number} standard deviation
 * @example
 * var toAccessorArray = require( '@stdlib/array/base/to-accessor-array' );
 * var arraylike2object = require( '@stdlib/array/base/arraylike2object' );
 *
 * var x = toAccessorArray( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] );
 *
 * var v = stdevpn( 4, 1, arraylike2object( x ), 2, 1 );
 * // returns 2.5
 */
function stdevpn( N, correction, x, strideX, offsetX) {
	var xbuf;
	var xget;
	var ix;
	var mean;
	var M2;
	var delta;
	var v;
	var i;
 
	// Cache reference to array data:
	xbuf = x.data;
 
	// Cache a reference to the element accessor:
	xget = x.accessors[ 0 ];
 
	if ( N <= 0 || (N - correction) <= 0) {
		return NaN;
	}
 
	mean = 0.0;
	M2 = 0.0;
 
	ix = offsetX;
	for ( i = 0; i < N; i++ ) {
		v = xget( xbuf, ix );
 
		delta = v - mean;
		mean += delta / (i + 1);
		M2 += delta * (v - mean);
 
		ix += strideX;
	}
 
	var variance = M2 / (N - correction);
 
	return sqrt( variance );
}
// EXPORTS //
 
module.exports = stdevpn;