All files / strided/nanmeanors/lib ndarray.js

58.53% Statements 48/82
100% Branches 1/1
0% Functions 0/1
58.53% Lines 48/82

Press n or j to go to the next uncovered block, b, p or k for the previous block.

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 831x 1x 1x 1x 1x 1x 1x 1x 1x 1x 1x 1x 1x 1x 1x 1x 1x 1x 1x 1x 1x 1x 1x 1x 1x 1x 1x 1x 1x 1x 1x 1x 1x 1x 1x 1x 1x 1x 1x 1x 1x 1x 1x                                                                     1x 1x 1x 1x 1x  
/**
* @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 arraylike2object = require( '@stdlib/array/base/arraylike2object' );
var accessors = require( './accessors.js' );
 
 
// MAIN //
 
/**
* Computes the arithmetic mean of a strided array, ignoring `NaN` values and using ordinary recursive summation.
*
* @param {PositiveInteger} N - number of indexed elements
* @param {NumericArray} x - input array
* @param {integer} strideX - stride length
* @param {NonNegativeInteger} offsetX - starting index
* @returns {number} arithmetic mean
*
* @example
* var x = [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0, NaN ];
*
* var v = nanmeanors( 4, x, 2, 1 );
* // returns 1.25
*/
function nanmeanors( N, x, strideX, offsetX ) {
	var sum;
	var ix;
	var v;
	var n;
	var i;
	var o;

	if ( N <= 0 ) {
		return NaN;
	}
	o = arraylike2object( x );
	if ( o.accessorProtocol ) {
		return accessors( N, o, strideX, offsetX );
	}
	if ( N === 1 || strideX === 0 ) {
		return x[ offsetX ];
	}
	ix = offsetX;
	sum = 0.0;
	n = 0;
	for ( i = 0; i < N; i++ ) {
		v = x[ ix ];
		if ( v === v ) {
			sum += v;
			n += 1;
		}
		ix += strideX;
	}
	if ( n === 0 ) {
		return NaN;
	}
	return sum / n;
}
 
 
// EXPORTS //
 
module.exports = nanmeanors;