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* @license Apache-2.0
*
* Copyright (c) 2020 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 isPositiveZero = require( '@stdlib/math/base/assert/is-positive-zero' );
var arraylike2object = require( '@stdlib/array/base/arraylike2object' );
var accessors = require( './accessors.js' );
// MAIN //
/**
* Computes the maximum value of a strided array according to a mask, ignoring `NaN` values.
*
* @param {PositiveInteger} N - number of indexed elements
* @param {NumericArray} x - input array
* @param {integer} strideX - stride length for `x`
* @param {NonNegativeInteger} offsetX - starting index for `x`
* @param {NumericArray} mask - mask array
* @param {integer} strideMask - stride length for `mask`
* @param {NonNegativeInteger} offsetMask - starting index for `mask`
* @returns {number} maximum value
*
* @example
* var x = [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];
* var mask = [ 0, 0, 0, 0, 0, 0, 0, 0, 1, 1 ];
*
* var v = nanmskmax( 5, x, 2, 1, mask, 2, 1 );
* // returns 4.0
*/
function nanmskmax( N, x, strideX, offsetX, mask, strideMask, offsetMask ) {
var max;
var ix;
var im;
var ox;
var om;
var v;
var i;
if ( N <= 0 ) {
return NaN;
}
ox = arraylike2object( x );
om = arraylike2object( mask );
if ( ox.accessorProtocol || om.accessorProtocol ) {
return accessors( N, ox, strideX, offsetX, om, strideMask, offsetMask );
}
ix = offsetX;
im = offsetMask;
for ( i = 0; i < N; i++ ) {
v = x[ ix ];
if ( v === v && mask[ im ] === 0 ) {
break;
}
ix += strideX;
im += strideMask;
}
if ( i === N ) {
return NaN;
}
max = v;
i += 1;
for ( i; i < N; i++ ) {
ix += strideX;
im += strideMask;
if ( mask[ im ] ) {
continue;
}
v = x[ ix ];
if ( isnan( v ) ) {
continue;
}
if ( v > max || ( v === max && isPositiveZero( v ) ) ) {
max = v;
}
}
return max;
}
// EXPORTS //
module.exports = nanmskmax;
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