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feat: add stats/base/ndarray/meanpn
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Orthodox-64:feat-add-stats-base-ndarray-meanpn
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a45797c
feat: add stats/base/ndarray/meanpn
2cc3527
fixed-lint
8dd9b54
fix: resolve linting errors in meanpn (remove tabs and extra blank li…
281a5bc
fixing lint error
6e769f4
fix: lint-errors
d37ed25
Refactor meanpn function for fixing lint error
Orthodox-64 b3ec8ef
Fix formatting and ensure newline at end of file
Orthodox-64 0a21fc0
Fix missing newline at end of main.js
Orthodox-64 1555330
Update README to remove notes and add references
Orthodox-64 27b049b
docs: restore note
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130 changes: 130 additions & 0 deletions
130
lib/node_modules/@stdlib/stats/base/ndarray/meanpn/README.md
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| <!-- | ||
| @license Apache-2.0 | ||
| Copyright (c) 2025 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. | ||
| --> | ||
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| # meanpn | ||
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| > Compute the [arithmetic mean][arithmetic-mean] of a one-dimensional ndarray using a two-pass error correction algorithm. | ||
| <section class="intro"> | ||
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| The [arithmetic mean][arithmetic-mean] is defined as | ||
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| <!-- <equation class="equation" label="eq:arithmetic_mean" align="center" raw="\mu = \frac{1}{n} \sum_{i=0}^{n-1} x_i" alt="Equation for the arithmetic mean."> --> | ||
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| ```math | ||
| \mu = \frac{1}{n} \sum_{i=0}^{n-1} x_i | ||
| ``` | ||
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| <!-- <div class="equation" align="center" data-raw-text="\mu = \frac{1}{n} \sum_{i=0}^{n-1} x_i" data-equation="eq:arithmetic_mean"> | ||
| <img src="https://cdn.jsdelivr.net/gh/stdlib-js/stdlib@develop/lib/node_modules/%40stdlib/stats/base/ndarray/meanpn/docs/img/equation_arithmetic_mean.svg" alt="Equation for the arithmetic mean."> | ||
| <br> | ||
| </div> --> | ||
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| <!-- </equation> --> | ||
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| </section> | ||
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| <!-- /.intro --> | ||
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| <section class="usage"> | ||
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| ## Usage | ||
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| ```javascript | ||
| var meanpn = require( '@stdlib/stats/base/ndarray/meanpn' ); | ||
| ``` | ||
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| #### meanpn( arrays ) | ||
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| Computes the [arithmetic mean][arithmetic-mean] of a one-dimensional ndarray using a two-pass error correction algorithm. | ||
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| ```javascript | ||
| var ndarray = require( '@stdlib/ndarray/base/ctor' ); | ||
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| var xbuf = [ 1.0, 3.0, 4.0, 2.0 ]; | ||
| var x = new ndarray( 'generic', xbuf, [ 4 ], [ 1 ], 0, 'row-major' ); | ||
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| var v = meanpn( [ x ] ); | ||
| // returns 2.5 | ||
| ``` | ||
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| The function has the following parameters: | ||
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| - **arrays**: array-like object containing a one-dimensional input ndarray. | ||
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| </section> | ||
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| <!-- /.usage --> | ||
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| <section class="notes"> | ||
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| ## Notes | ||
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| - If provided an empty one-dimensional ndarray, the function returns `NaN`. | ||
| - This implementation uses a two-pass approach (Neely, 1966) to compute an error correction term for improved numerical accuracy. | ||
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| </section> | ||
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| <!-- /.notes --> | ||
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| <section class="examples"> | ||
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| ## Examples | ||
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| <!-- eslint-disable no-console --> | ||
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| ```javascript | ||
| var discreteUniform = require( '@stdlib/random/array/discrete-uniform' ); | ||
| var ndarray = require( '@stdlib/ndarray/base/ctor' ); | ||
| var ndarray2array = require( '@stdlib/ndarray/to-array' ); | ||
| var meanpn = require( '@stdlib/stats/base/ndarray/meanpn' ); | ||
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| var xbuf = discreteUniform( 10, -50, 50, { | ||
| 'dtype': 'generic' | ||
| }); | ||
| var x = new ndarray( 'generic', xbuf, [ xbuf.length ], [ 1 ], 0, 'row-major' ); | ||
| console.log( ndarray2array( x ) ); | ||
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| var v = meanpn( [ x ] ); | ||
| console.log( v ); | ||
| ``` | ||
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| </section> | ||
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| <!-- /.examples --> | ||
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| <!-- Section for related `stdlib` packages. Do not manually edit this section, as it is automatically populated. --> | ||
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| <section class="related"> | ||
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| </section> | ||
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| <!-- /.related --> | ||
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| <!-- Section for all links. Make sure to keep an empty line after the `section` element and another before the `/section` close. --> | ||
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| <section class="links"> | ||
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| [arithmetic-mean]: https://en.wikipedia.org/wiki/Arithmetic_mean | ||
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| </section> | ||
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| <!-- /.links --> | ||
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102
lib/node_modules/@stdlib/stats/base/ndarray/meanpn/benchmark/benchmark.js
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| /** | ||
| * @license Apache-2.0 | ||
| * | ||
| * Copyright (c) 2025 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. | ||
| */ | ||
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| 'use strict'; | ||
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| // MODULES // | ||
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| var bench = require( '@stdlib/bench' ); | ||
| var uniform = require( '@stdlib/random/array/uniform' ); | ||
| var isnan = require( '@stdlib/math/base/assert/is-nan' ); | ||
| var pow = require( '@stdlib/math/base/special/pow' ); | ||
| var ndarray = require( '@stdlib/ndarray/base/ctor' ); | ||
| var pkg = require( './../package.json' ).name; | ||
| var meanpn = require( './../lib' ); | ||
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| // VARIABLES // | ||
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| var options = { | ||
| 'dtype': 'generic' | ||
| }; | ||
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| // FUNCTIONS // | ||
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| /** | ||
| * Creates a benchmark function. | ||
| * | ||
| * @private | ||
| * @param {PositiveInteger} len - array length | ||
| * @returns {Function} benchmark function | ||
| */ | ||
| function createBenchmark( len ) { | ||
| var xbuf; | ||
| var x; | ||
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| xbuf = uniform( len, -10.0, 10.0, options ); | ||
| x = new ndarray( options.dtype, xbuf, [ len ], [ 1 ], 0, 'row-major' ); | ||
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| return benchmark; | ||
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| function benchmark( b ) { | ||
| var v; | ||
| var i; | ||
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| b.tic(); | ||
| for ( i = 0; i < b.iterations; i++ ) { | ||
| v = meanpn( [ x ] ); | ||
| if ( isnan( v ) ) { | ||
| b.fail( 'should not return NaN' ); | ||
| } | ||
| } | ||
| b.toc(); | ||
| if ( isnan( v ) ) { | ||
| b.fail( 'should not return NaN' ); | ||
| } | ||
| b.pass( 'benchmark finished' ); | ||
| b.end(); | ||
| } | ||
| } | ||
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| // MAIN // | ||
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| /** | ||
| * Main execution sequence. | ||
| * | ||
| * @private | ||
| */ | ||
| function main() { | ||
| var len; | ||
| var min; | ||
| var max; | ||
| var f; | ||
| var i; | ||
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| min = 1; // 10^min | ||
| max = 6; // 10^max | ||
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| for ( i = min; i <= max; i++ ) { | ||
| len = pow( 10, i ); | ||
| f = createBenchmark( len ); | ||
| bench( pkg+':len='+len, f ); | ||
| } | ||
| } | ||
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| main(); |
42 changes: 42 additions & 0 deletions
42
...modules/@stdlib/stats/base/ndarray/meanpn/docs/img/equation_arithmetic_mean.svg
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32 changes: 32 additions & 0 deletions
32
lib/node_modules/@stdlib/stats/base/ndarray/meanpn/docs/repl.txt
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| {{alias}}( arrays ) | ||
| Computes the arithmetic mean of a one-dimensional ndarray using a two-pass | ||
| error correction algorithm. | ||
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| If provided an empty ndarray, the function returns `NaN`. | ||
|
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| Parameters | ||
| ---------- | ||
| arrays: ArrayLikeObject<ndarray> | ||
| Array-like object containing a one-dimensional input ndarray. | ||
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| Returns | ||
| ------- | ||
| out: number | ||
| Arithmetic mean. | ||
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| Examples | ||
| -------- | ||
| > var xbuf = [ 1.0, -2.0, 2.0 ]; | ||
| > var dt = 'generic'; | ||
| > var sh = [ xbuf.length ]; | ||
| > var sx = [ 1 ]; | ||
| > var ox = 0; | ||
| > var ord = 'row-major'; | ||
| > var x = new {{alias:@stdlib/ndarray/ctor}}( dt, xbuf, sh, sx, ox, ord ); | ||
| > {{alias}}( [ x ] ) | ||
| ~0.3333 | ||
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| See Also | ||
| -------- | ||
|
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45
lib/node_modules/@stdlib/stats/base/ndarray/meanpn/docs/types/index.d.ts
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| /* | ||
| * @license Apache-2.0 | ||
| * | ||
| * Copyright (c) 2025 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. | ||
| */ | ||
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| // TypeScript Version: 4.1 | ||
|
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| /// <reference types="@stdlib/types"/> | ||
|
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| import { ndarray } from '@stdlib/types/ndarray'; | ||
|
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| /** | ||
| * Computes the arithmetic mean of a one-dimensional ndarray using a two-pass error correction algorithm. | ||
| * | ||
| * @param arrays - array-like object containing an input ndarray | ||
| * @returns arithmetic mean | ||
| * | ||
| * @example | ||
| * var ndarray = require( '@stdlib/ndarray/base/ctor' ); | ||
| * | ||
| * var xbuf = [ 1.0, 3.0, 4.0, 2.0 ]; | ||
| * var x = new ndarray( 'generic', xbuf, [ 4 ], [ 1 ], 0, 'row-major' ); | ||
| * | ||
| * var v = meanpn( [ x ] ); | ||
| * // returns 2.5 | ||
| */ | ||
| declare function meanpn<T extends ndarray = ndarray>( arrays: [ T ] ): number; | ||
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| // EXPORTS // | ||
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| export = meanpn; |
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