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 isnan = require( '@stdlib/math/base/assert/is-nan' );
var isNegativeZero = require( '@stdlib/math/base/assert/is-negative-zero' );
 
 
// MAIN //
 
/**
* Computes the cumulative minimum of double-precision floating-point strided array elements ignoring `NaN` values.
*
* @param {PositiveInteger} N - number of indexed elements
* @param {Float64Array} x - input array
* @param {integer} strideX - `x` stride length
* @param {NonNegativeInteger} offsetX - starting index for `x`
* @param {Float64Array} y - output array
* @param {integer} strideY - `y` stride length
* @param {NonNegativeInteger} offsetY - starting index for `y`
* @returns {Float64Array} output array
*
* @example
* var Float64Array = require( '@stdlib/array/float64' );
*
* var x = new Float64Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] );
* var y = new Float64Array( x.length );
*
* var v = dnancumin( 4, x, 2, 1, y, 1, 0 );
* // returns <Float64Array>[ 1.0, -2.0, -2.0, -2.0, 0.0, 0.0, 0.0, 0.0 ]
*/
function dnancumin( N, x, strideX, offsetX, y, strideY, offsetY ) {
	var min;
	var ix;
	var iy;
	var v;
	var i;
 
	if ( N <= 0 ) {
		return y;
	}
	ix = offsetX;
	iy = offsetY;
	i = 0;
 
	for ( i; i < N; i++ ) {
		v = x[ ix ];
		if ( isnan( v ) === false ) {
			break;
		}
		y[ iy ] = v;
		ix += strideX;
		iy += strideY;
	}
 
	if ( i === N ) {
		return y;
	}
 
	min = v;
	y[ iy ] = min;
	ix += strideX;
	iy += strideY;
	i += 1;
	for ( i; i < N; i++ ) {
		v = x[ ix ];
		if ( isnan( v ) === false ) {
			if ( v < min || ( v === min && isNegativeZero( v ) ) ) {
				min = v;
			}
		}
		y[ iy ] = min;
		ix += strideX;
		iy += strideY;
	}
 
	return y;
}
 
 
// EXPORTS //
 
module.exports = dnancumin;