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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';
/**
* Computes the standard deviation of a single-precision floating-point strided array using an accessor function and a one-pass algorithm proposed by Youngs and Cramer.
*
* @param {PositiveInteger} N - number of indexed elements
* @param {Function} accessor - accessor function for accessing array elements
* @param {Object} x - input array-like object supporting the accessor protocol
* @param {integer} stride - stride length
* @param {number} correction - degrees of freedom adjustment (e.g., 0 for population, 1 for sample)
* @returns {number} standard deviation
*
* @example
* var Float32Array = require( '@stdlib/array/float32' );
*
* function accessor( idx ) {
* return this.values[ idx ];
* }
*
* var x = {
* 'values': new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] ),
* 'get': accessor
* };
*
* var v = accessor( 5, x.get, x, 1, 1 );
* // returns ~1.4142
*/
function accessor( N, accessor, x, stride, correction ) {
if (typeof accessor !== 'function') {
throw new TypeError( 'invalid argument. Second argument must be a function.' );
}
if (!x || typeof x !== 'object') {
return NaN;
}
if (!Number.isInteger(N) || N <= 0) {
return NaN;
}
if (!Number.isFinite(correction) || correction < 0 || correction >= N) {
return NaN;
}
if (!Number.isInteger(stride)) {
return NaN;
}
if (N === 1) {
return 0.0;
}
var mean = 0.0;
var M2 = 0.0;
var ix = stride < 0 ? (1 - N) * stride : 0;
for (var i = 0; i < N; i++, ix += stride) {
var v = accessor.call( x, ix );
if (typeof v !== 'number' || isNaN(v)) {
return NaN;
}
var delta = v - mean;
mean += delta / (i + 1);
M2 += delta * (v - mean);
}
return Math.sqrt( M2 / (N - correction) );
}
module.exports = accessor; |