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feat: add stats/base/dists/halfnormal/entropy
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Jan 22, 2026
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3bcdeb9
feat: implementation of entropy halfnormal distribution
bhargava-d16 02b8c72
fix: added requested changes
bhargava-d16 08e96ee
fix: added requested changes
bhargava-d16 4decdce
fix: added requested changes
bhargava-d16 cbcafb8
fix: added python fixtures
bhargava-d16 d40d7fb
chore: minor clean-up
Planeshifter fa3f0ec
chore: minor clean-up
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231 changes: 231 additions & 0 deletions
231
lib/node_modules/@stdlib/stats/base/dists/halfnormal/entropy/README.md
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| <!-- | ||
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| @license Apache-2.0 | ||
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| Copyright (c) 2026 The Stdlib Authors. | ||
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| 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 | ||
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| http://www.apache.org/licenses/LICENSE-2.0 | ||
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| 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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| --> | ||
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| # Entropy | ||
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| > [Half-normal][half-normal-distribution] distribution [differential entropy][entropy]. | ||
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| <!-- Section to include introductory text. Make sure to keep an empty line after the intro `section` element and another before the `/section` close. --> | ||
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| <section class="intro"> | ||
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| The [differential entropy][entropy] (in [nats][nats]) for a [half-normal][half-normal-distribution] random variable is | ||
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| <!-- <equation class="equation" label="eq:halfnormal_entropy" align="center" raw="h\left( X \right) = \frac{1}{2}+\ln(\sigma)+\ln\left(\sqrt{\frac{\pi}{2}}\right)+\frac{\gamma}{2}" alt="Differential entropy for a half-normal distribution."> --> | ||
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| ```math | ||
| h\left( X \right) = \frac{1}{2}+\ln(\sigma)+\ln\left(\sqrt{\frac{\pi}{2}}\right)+\frac{\gamma}{2} | ||
| ``` | ||
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| <!-- </equation> --> | ||
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| where `σ > 0` is the scale parameter. | ||
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| </section> | ||
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| <!-- /.intro --> | ||
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| <!-- Package usage documentation. --> | ||
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| <section class="usage"> | ||
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| ## Usage | ||
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| ```javascript | ||
| var entropy = require( '@stdlib/stats/base/dists/halfnormal/entropy' ); | ||
| ``` | ||
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| #### entropy( sigma ) | ||
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| Returns the [differential entropy][entropy] of a [half-normal][half-normal-distribution] distribution with scale `sigma` (in [nats][nats]). | ||
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| ```javascript | ||
| var y = entropy( 1.0 ); | ||
| // returns ~1.014 | ||
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| y = entropy( 5.0 ); | ||
| // returns ~2.624 | ||
| ``` | ||
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| If provided `sigma ≤ 0`, the function returns `NaN`. | ||
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| ```javascript | ||
| var y = entropy( -1.0 ); | ||
| // returns NaN | ||
| ``` | ||
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| </section> | ||
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| <!-- /.usage --> | ||
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| <!-- Package usage notes. Make sure to keep an empty line after the `section` element and another before the `/section` close. --> | ||
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| <section class="notes"> | ||
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| </section> | ||
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| <!-- /.notes --> | ||
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| <!-- Package usage examples. --> | ||
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| <section class="examples"> | ||
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| ## Examples | ||
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| <!-- eslint no-undef: "error" --> | ||
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| ```javascript | ||
| var uniform = require( '@stdlib/random/array/uniform' ); | ||
| var logEachMap = require( '@stdlib/console/log-each-map' ); | ||
| var entropy = require( '@stdlib/stats/base/dists/halfnormal/entropy' ); | ||
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| var opts = { | ||
| 'dtype': 'float64' | ||
| }; | ||
| var sigma = uniform( 10, 0.1, 20.0, opts ); | ||
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| logEachMap( 'σ: %0.4f, h(X;σ): %0.4f', sigma, entropy ); | ||
| ``` | ||
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| </section> | ||
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| <!-- /.examples --> | ||
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| <!-- C interface documentation. --> | ||
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| * * * | ||
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| <section class="c"> | ||
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| ## C APIs | ||
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| <!-- Section to include introductory text. Make sure to keep an empty line after the intro `section` element and another before the `/section` close. --> | ||
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| <section class="intro"> | ||
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| </section> | ||
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| <!-- /.intro --> | ||
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| <!-- C usage documentation. --> | ||
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| <section class="usage"> | ||
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| ### Usage | ||
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| ```c | ||
| #include "stdlib/stats/base/dists/halfnormal/entropy.h" | ||
| ``` | ||
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| #### stdlib_base_dists_halfnormal_entropy( sigma ) | ||
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| Returns the differential entropy of a half-normal distribution. | ||
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| ```c | ||
| double out = stdlib_base_dists_halfnormal_entropy( 1.0 ); | ||
| // returns ~1.014 | ||
| ``` | ||
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| The function accepts the following arguments: | ||
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| - **sigma**: `[in] double` scale parameter. | ||
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| ```c | ||
| double stdlib_base_dists_halfnormal_entropy( const double sigma ); | ||
| ``` | ||
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| </section> | ||
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| <!-- /.usage --> | ||
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| <!-- C API usage notes. Make sure to keep an empty line after the `section` element and another before the `/section` close. --> | ||
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| <section class="notes"> | ||
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| </section> | ||
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| <!-- /.notes --> | ||
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| <!-- C API usage examples. --> | ||
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| <section class="examples"> | ||
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| ### Examples | ||
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| ```c | ||
| #include "stdlib/stats/base/dists/halfnormal/entropy.h" | ||
| #include <stdlib.h> | ||
| #include <stdio.h> | ||
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| static double random_uniform( const double min, const double max ) { | ||
| double v = (double)rand() / ( (double)RAND_MAX + 1.0 ); | ||
| return min + ( v*(max-min) ); | ||
| } | ||
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| int main( void ) { | ||
| double sigma; | ||
| double y; | ||
| int i; | ||
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| for ( i = 0; i < 25; i++ ) { | ||
| sigma = random_uniform( 0.1, 20.0 ); | ||
| y = stdlib_base_dists_halfnormal_entropy( sigma ); | ||
| printf( "σ: %lf, h(σ): %lf\n", sigma, y ); | ||
| } | ||
| } | ||
| ``` | ||
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| </section> | ||
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| <!-- /.examples --> | ||
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| </section> | ||
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| <!-- /.c --> | ||
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| <!-- Section to include cited references. If references are included, add a horizontal rule *before* the section. Make sure to keep an empty line after the `section` element and another before the `/section` close. --> | ||
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| <section class="references"> | ||
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| </section> | ||
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| <!-- /.references --> | ||
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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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| [half-normal-distribution]: https://en.wikipedia.org/wiki/Half-normal_distribution | ||
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| [entropy]: https://en.wikipedia.org/wiki/Entropy_%28information_theory%29 | ||
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| [nats]: https://en.wikipedia.org/wiki/Nat_%28unit%29 | ||
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| </section> | ||
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| <!-- /.links --> |
60 changes: 60 additions & 0 deletions
60
lib/node_modules/@stdlib/stats/base/dists/halfnormal/entropy/benchmark/benchmark.js
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| /** | ||
| * @license Apache-2.0 | ||
| * | ||
| * Copyright (c) 2026 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 Float64Array = require( '@stdlib/array/float64' ); | ||
| var randu = require( '@stdlib/random/base/randu' ); | ||
| var isnan = require( '@stdlib/math/base/assert/is-nan' ); | ||
| var EPS = require( '@stdlib/constants/float64/eps' ); | ||
| var pkg = require( './../package.json' ).name; | ||
| var entropy = require( './../lib' ); | ||
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| // MAIN // | ||
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| bench( pkg, function benchmark( b ) { | ||
| var sigma; | ||
| var len; | ||
| var y; | ||
| var i; | ||
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| len = 100; | ||
| sigma = new Float64Array( len ); | ||
| for ( i = 0; i < len; i++ ) { | ||
| sigma[ i ] = ( randu()*20.0 ) + EPS; | ||
| } | ||
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| b.tic(); | ||
| for ( i = 0; i < b.iterations; i++ ) { | ||
| y = entropy( sigma[ i % len ] ); | ||
| if ( isnan( y ) ) { | ||
| b.fail( 'should not return NaN' ); | ||
| } | ||
| } | ||
| b.toc(); | ||
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| if ( isnan( y ) ) { | ||
| b.fail( 'should not return NaN' ); | ||
| } | ||
| b.pass( 'benchmark finished' ); | ||
| b.end(); | ||
| }); | ||
70 changes: 70 additions & 0 deletions
70
lib/node_modules/@stdlib/stats/base/dists/halfnormal/entropy/benchmark/benchmark.native.js
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| /** | ||
| * @license Apache-2.0 | ||
| * | ||
| * Copyright (c) 2026 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 resolve = require( 'path' ).resolve; | ||
| var bench = require( '@stdlib/bench' ); | ||
| var Float64Array = require( '@stdlib/array/float64' ); | ||
| var randu = require( '@stdlib/random/base/randu' ); | ||
| var isnan = require( '@stdlib/math/base/assert/is-nan' ); | ||
| var EPS = require( '@stdlib/constants/float64/eps' ); | ||
| var tryRequire = require( '@stdlib/utils/try-require' ); | ||
| var format = require( '@stdlib/string/format' ); | ||
| var pkg = require( './../package.json' ).name; | ||
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| // VARIABLES // | ||
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| var entropy = tryRequire( resolve( __dirname, './../lib/native.js' ) ); | ||
| var opts = { | ||
| 'skip': ( entropy instanceof Error ) | ||
| }; | ||
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| // MAIN // | ||
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| bench( format( '%s::native', pkg ), opts, function benchmark( b ) { | ||
| var sigma; | ||
| var len; | ||
| var y; | ||
| var i; | ||
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| len = 100; | ||
| sigma = new Float64Array( len ); | ||
| for ( i = 0; i < len; i++ ) { | ||
| sigma[ i ] = ( randu() * 20.0 ) + EPS; | ||
| } | ||
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| b.tic(); | ||
| for ( i = 0; i < b.iterations; i++ ) { | ||
| y = entropy( sigma[ i % len ] ); | ||
| if ( isnan( y ) ) { | ||
| b.fail( 'should not return NaN' ); | ||
| } | ||
| } | ||
| b.toc(); | ||
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| if ( isnan( y ) ) { | ||
|
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| b.fail( 'should not return NaN' ); | ||
| } | ||
| b.pass( 'benchmark finished' ); | ||
| b.end(); | ||
| }); | ||
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