All files ndarray.js

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/**
* @license Apache-2.0
*
* Copyright (c) 2026 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 float64ToFloat32 = require( '@stdlib/number/float64/base/to-float32' );
var snansumkbn = require( '@stdlib/blas/ext/base/snansumkbn' ).ndarray;
 
 
// MAIN //
 
/**
* Computes the arithmetic mean of a single-precision floating-point strided array ignoring `NaN` values and using an improved Kahan-Babuska algorithm.
*
* ## Method
*
* -   This implementation uses an "improved Kahan–Babuška algorithm", as described by Neumaier (1974).
*
* ## References
*
* -   Neumaier, Arnold. 1974. "Rounding Error Analysis of Some Methods for Summing Finite Sums." _Zeitschrift Für Angewandte Mathematik Und Mechanik_ 54 (1): 39–51. doi:[10.1002/zamm.19740540106](https://doi.org/10.1002/zamm.19740540106).
*
* @param {PositiveInteger} N - number of indexed elements
* @param {Float32Array} x - input array
* @param {integer} strideX - stride length
* @param {NonNegativeInteger} offsetX - starting index
* @returns {number} arithmetic mean
*
* @example
* var Float32Array = require( '@stdlib/array/float32' );
* var snanmeankbn = require( '@stdlib/stats/strided/snanmeankbn' );
*
* var x = new Float32Array( [ 1.0, 10.0, NaN, 20.0, 3.0, 30.0 ] );
*
* var v = snanmeankbn.ndarray( 3, x, 2, 1 );
* // returns 20.0
*/
function snanmeankbn( N, x, strideX, offsetX ) {
	var count = 0;
	var sum;
	var ix;
	var i;
	var v;
 
	if ( N <= 0 ) {
		return NaN;
	}
	ix = offsetX;
	for ( i = 0; i < N; i++ ) {
		v = x[ ix ];
		if ( v === v ) {
			count += 1;
		}
		ix += strideX;
	}
	if ( count === 0 ) {
		return NaN;
	}
	sum = snansumkbn( N, x, strideX, offsetX );
	return float64ToFloat32( sum / count );
}
 
 
// EXPORTS //
 
module.exports = snanmeankbn;