70 lines
1.8 KiB
JavaScript
70 lines
1.8 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 dapxsum = require( '@stdlib/blas/ext/base/dapxsum' ).ndarray;
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// MAIN //
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/**
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* Computes the arithmetic mean of a double-precision floating-point strided array using a one-pass trial mean algorithm.
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*
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* ## References
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*
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* - Ling, Robert F. 1974. "Comparison of Several Algorithms for Computing Sample Means and Variances." _Journal of the American Statistical Association_ 69 (348). American Statistical Association, Taylor & Francis, Ltd.: 859–66. doi:[10.2307/2286154](https://doi.org/10.2307/2286154).
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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} stride - stride length
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* @returns {number} arithmetic mean
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*
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* @example
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* var Float64Array = require( '@stdlib/array/float64' );
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*
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* var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );
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* var N = x.length;
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*
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* var v = dmeanli( N, x, 1 );
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* // returns ~0.3333
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*/
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function dmeanli( N, x, stride ) {
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var ix;
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if ( N <= 0 ) {
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return NaN;
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}
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if ( N === 1 || stride === 0 ) {
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return x[ 0 ];
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}
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if ( stride < 0 ) {
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ix = (1-N) * stride;
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} else {
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ix = 0;
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}
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return x[ ix ] + ( dapxsum( N-1, -x[ ix ], x, stride, ix+stride ) / N );
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}
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// EXPORTS //
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module.exports = dmeanli;
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