All files native.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 contains = require( '@stdlib/array/base/assert/contains' ).factory;
var serialize = require( '@stdlib/ndarray/base/serialize-meta-data' );
var getData = require( '@stdlib/ndarray/base/data-buffer' );
var getDType = require( '@stdlib/ndarray/base/dtype' );
var addon = require( './../src/addon.node' );
var fallback = require( './main.js' );
 
 
// VARIABLES //
 
// List of data types supported by the native add-on:
var DTYPES = [
	'float64',
	'float32',
	'int32',
	'uint32',
	'int16',
	'uint16',
	'int8',
	'uint8',
	'uint8c'
];
var isSupportedDataType = contains( DTYPES );
 
 
// MAIN //
 
/**
* Computes the variance of a one-dimensional ndarray, ignoring `NaN` values and using a two-pass algorithm.
*
* ## Notes
*
* -   The function expects the following ndarrays:
*
*     -   a one-dimensional input ndarray.
*     -   a zero-dimensional ndarray specifying the degrees of freedom adjustment.
*
* -   If either the input ndarray or the ndarray specifying the degrees of freedom adjustment has a data type which is not supported by the native add-on (e.g., `generic`), the function falls back to the JavaScript implementation.
*
* @private
* @param {ArrayLikeObject<Object>} arrays - array-like object containing ndarrays
* @returns {number} variance
*
* @example
* var vector = require( '@stdlib/ndarray/vector/ctor' );
* var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' );
*
* var x = vector( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0, NaN, NaN ], 'generic' );
*
* var correction = scalar2ndarray( 1.0, {
*     'dtype': 'generic'
* });
*
* var v = nanvariancepn( [ x, correction ] );
* // returns ~4.79
*/
function nanvariancepn( arrays ) {
	var correction = arrays[ 1 ];
	var x = arrays[ 0 ];
	if ( !isSupportedDataType( getDType( x ) ) || !isSupportedDataType( getDType( correction ) ) ) { // eslint-disable-line max-len
		return fallback( arrays );
	}
	return addon( getData( x ), serialize( x ), getData( correction ), serialize( correction ) ); // eslint-disable-line max-len
}
 
 
// EXPORTS //
 
module.exports = nanvariancepn;