102 lines
2.3 KiB
JavaScript
102 lines
2.3 KiB
JavaScript
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/**
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* @license Apache-2.0
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*
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* Copyright (c) 2020 The Stdlib Authors.
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*
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* Licensed under the Apache License, Version 2.0 (the "License");
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* you may not use this file except in compliance with the License.
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* You may obtain a copy of the License at
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*
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* http://www.apache.org/licenses/LICENSE-2.0
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*
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* Unless required by applicable law or agreed to in writing, software
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* distributed under the License is distributed on an "AS IS" BASIS,
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* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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* See the License for the specific language governing permissions and
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* limitations under the License.
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*/
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'use strict';
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// MODULES //
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var isnan = require( '@stdlib/math/base/assert/is-nan' );
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// MAIN //
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/**
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* Computes the range of a double-precision floating-point strided array according to a mask, ignoring `NaN` values.
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*
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* @param {PositiveInteger} N - number of indexed elements
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* @param {Float64Array} x - input array
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* @param {integer} strideX - `x` stride length
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* @param {NonNegativeInteger} offsetX - `x` starting index
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* @param {Uint8Array} mask - mask array
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* @param {integer} strideMask - `mask` stride length
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* @param {NonNegativeInteger} offsetMask - `mask` starting index
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* @returns {number} range
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*
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* @example
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* var Float64Array = require( '@stdlib/array/float64' );
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* var Uint8Array = require( '@stdlib/array/uint8' );
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* var floor = require( '@stdlib/math/base/special/floor' );
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*
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* var x = new Float64Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );
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* var mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 0, 0, 1, 1 ] );
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* var N = floor( x.length / 2 );
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*
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* var v = dnanmskrange( N, x, 2, 1, mask, 2, 1 );
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* // returns 6.0
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*/
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function dnanmskrange( N, x, strideX, offsetX, mask, strideMask, offsetMask ) {
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var max;
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var min;
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var ix;
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var im;
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var v;
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var i;
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if ( N <= 0 ) {
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return NaN;
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}
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ix = offsetX;
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im = offsetMask;
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for ( i = 0; i < N; i++ ) {
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v = x[ ix ];
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if ( v === v && mask[ im ] === 0 ) {
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break;
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}
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ix += strideX;
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im += strideMask;
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}
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if ( i === N ) {
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return NaN;
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}
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min = v;
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max = min;
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i += 1;
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for ( i; i < N; i++ ) {
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ix += strideX;
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im += strideMask;
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if ( mask[ im ] ) {
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continue;
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}
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v = x[ ix ];
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if ( isnan( v ) ) {
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continue;
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}
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if ( v < min ) {
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min = v;
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} else if ( v > max ) {
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max = v;
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}
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}
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return max - min;
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}
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// EXPORTS //
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module.exports = dnanmskrange;
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