time-to-botec

Benchmark sampling in different programming languages
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ndarray.js (1918B)


      1 /**
      2 * @license Apache-2.0
      3 *
      4 * Copyright (c) 2020 The Stdlib Authors.
      5 *
      6 * Licensed under the Apache License, Version 2.0 (the "License");
      7 * you may not use this file except in compliance with the License.
      8 * You may obtain a copy of the License at
      9 *
     10 *    http://www.apache.org/licenses/LICENSE-2.0
     11 *
     12 * Unless required by applicable law or agreed to in writing, software
     13 * distributed under the License is distributed on an "AS IS" BASIS,
     14 * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
     15 * See the License for the specific language governing permissions and
     16 * limitations under the License.
     17 */
     18 
     19 'use strict';
     20 
     21 // MODULES //
     22 
     23 var isnan = require( '@stdlib/math/base/assert/is-nan' );
     24 var abs = require( '@stdlib/math/base/special/abs' );
     25 
     26 
     27 // MAIN //
     28 
     29 /**
     30 * Computes the sum of absolute values (L1 norm) of double-precision floating-point strided array elements, ignoring `NaN` values and using ordinary recursive summation.
     31 *
     32 * @param {PositiveInteger} N - number of indexed elements
     33 * @param {Float64Array} x - input array
     34 * @param {integer} stride - stride length
     35 * @param {NonNegativeInteger} offset - starting index
     36 * @returns {number} sum
     37 *
     38 * @example
     39 * var Float64Array = require( '@stdlib/array/float64' );
     40 * var floor = require( '@stdlib/math/base/special/floor' );
     41 *
     42 * var x = new Float64Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0, NaN, NaN ] );
     43 * var N = floor( x.length / 2 );
     44 *
     45 * var v = dnanasumors( N, x, 2, 1 );
     46 * // returns 9.0
     47 */
     48 function dnanasumors( N, x, stride, offset ) {
     49 	var sum;
     50 	var ix;
     51 	var v;
     52 	var i;
     53 
     54 	if ( N <= 0 ) {
     55 		return 0.0;
     56 	}
     57 	if ( N === 1 || stride === 0 ) {
     58 		if ( isnan( x[ offset ] ) ) {
     59 			return 0.0;
     60 		}
     61 		return abs( x[ offset ] );
     62 	}
     63 	ix = offset;
     64 	sum = 0.0;
     65 	for ( i = 0; i < N; i++ ) {
     66 		v = x[ ix ];
     67 		if ( isnan( v ) === false ) {
     68 			sum += abs( v );
     69 		}
     70 		ix += stride;
     71 	}
     72 	return sum;
     73 }
     74 
     75 
     76 // EXPORTS //
     77 
     78 module.exports = dnanasumors;