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feat: add C implementation for @stdlib/stats/base/dists/lognormal/logcdf #4716

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46 changes: 10 additions & 36 deletions lib/node_modules/@stdlib/math/base/special/ln/manifest.json
Original file line number Diff line number Diff line change
Expand Up @@ -38,12 +38,9 @@
"libraries": [],
"libpath": [],
"dependencies": [
"@stdlib/math/base/napi/unary",
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There is no need to make these changes in the manifest.json of math/base/special/ln,

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there is nothing show like this in manifest.json of math/base/special/ln in repo

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What I meant was that there was no need to change the block of code in math/base/special/ln so it will be good to revert it back.

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It is depends on base/dists/normal/logcdf , which is not implement at that moment.

"@stdlib/number/float64/base/get-high-word",
"@stdlib/number/float64/base/set-high-word",
"@stdlib/math/base/assert/is-nan",
"@stdlib/constants/float64/ninf",
"@stdlib/constants/float64/exponent-bias"
"@stdlib/stats/base/dists/normal/logcdf",
"@stdlib/math/base/special/ln",
"@stdlib/constants/float64/ninf"
]
},
{
Expand All @@ -58,11 +55,10 @@
"libraries": [],
"libpath": [],
"dependencies": [
"@stdlib/number/float64/base/get-high-word",
"@stdlib/number/float64/base/set-high-word",
"@stdlib/math/base/assert/is-nan",
"@stdlib/constants/float64/ninf",
"@stdlib/constants/float64/exponent-bias"
"@stdlib/math/base/napi/binary",
"@stdlib/math/base/special/ln",
"@stdlib/constants/float64/eps",
"@stdlib/constants/float64/ninf"
]
},
{
Expand All @@ -77,32 +73,10 @@
"libraries": [],
"libpath": [],
"dependencies": [
"@stdlib/number/float64/base/get-high-word",
"@stdlib/number/float64/base/set-high-word",
"@stdlib/math/base/assert/is-nan",
"@stdlib/constants/float64/ninf",
"@stdlib/constants/float64/exponent-bias"
]
},
{
"task": "build",
"wasm": true,
"src": [
"./src/main.c"
],
"include": [
"./include"
],
"libraries": [],
"libpath": [],
"dependencies": [
"@stdlib/number/float64/base/get-high-word",
"@stdlib/number/float64/base/set-high-word",
"@stdlib/math/base/assert/is-nan",
"@stdlib/constants/float64/ninf",
"@stdlib/constants/float64/exponent-bias"
"@stdlib/stats/base/dists/normal/logcdf",
"@stdlib/math/base/special/ln",
"@stdlib/constants/float64/ninf"
]
}
]
}

Original file line number Diff line number Diff line change
Expand Up @@ -128,6 +128,95 @@ for ( i = 0; i < 10; i++ ) {

<!-- /.examples -->

<!-- C interface documentation. -->

* * *

<section class="c">

## C APIs

<!-- Section to include introductory text. Make sure to keep an empty line after the intro `section` element and another before the `/section` close. -->

<section class="intro">

</section>

<!-- /.intro -->

<!-- C usage documentation. -->

<section class="usage">

### Usage

```c
#include "stdlib/stats/base/dists/lognormal/logcdf.h"
```

#### stdlib_base_dists_lognormal_logcdf( x, mu, sigma )

Returns the logcdf for a lognormal distribution with mean `mu` and standard deviation `sigma`.

```c
double out = stdlib_base_dists_lognormal_logcdf( 2.0, 0.0, 1.0 );
// returns ~-0.2799
```

The function accepts the following arguments:

- **x**: `[in] double` input value
- **mu**: `[in] double` mean.
- **sigma**: `[in] double` standard deviation.

```c
double stdlib_base_dists_lognormal_logcdf( const double x, const double mu, const double sigma );
```

</section>

<!-- /.usage -->

<!-- C API usage notes. Make sure to keep an empty line after the `section` element and another before the `/section` close. -->

<section class="notes">

</section>

<!-- /.notes -->

<!-- C API usage examples. -->

<section class="examples">

### Examples

```c
#include "stdlib/stats/base/dists/lognormal/logcdf.h"
#include <stdlib.h>
#include <stdio.h>

static double random_uniform( const double min, const double max ) {
double v = (double)rand() / ( (double)RAND_MAX + 1.0 );
return min + ( v*(max-min) );
}

int main( void ) {
double x;
double sigma;
double mu;
double y;
int i;
for ( i = 0; i < 25; i++ ) {
x = random_uniform ( 0.0, 20.0 ) - 10.0;
mu = random_uniform( 0.0, 10.0 ) - 5.0;
sigma = random_uniform( 0.0, 20.0 );
y = stdlib_base_dists_lognormal_logcdf( x, mu, sigma );
printf( "x: %lf µ: %lf, σ: %lf, Var(X;µ,σ): %lf\n", x, mu, sigma, y );
}
}
```

<!-- Section for related `stdlib` packages. Do not manually edit this section, as it is automatically populated. -->

<section class="related">
Expand Down
Original file line number Diff line number Diff line change
Expand Up @@ -21,6 +21,8 @@
// MODULES //

var bench = require( '@stdlib/bench' );
var Float64Array = require( '@stdlib/array/float64' );
var uniform = require( '@stdlib/random/array/uniform' );
var randu = require( '@stdlib/random/base/randu' );
var isnan = require( '@stdlib/math/base/assert/is-nan' );
var EPS = require( '@stdlib/constants/float64/eps' );
Expand All @@ -31,18 +33,25 @@ var logcdf = require( './../lib' );
// MAIN //

bench( pkg, function benchmark( b ) {
var len;
var sigma;
var mu;
var x;
var y;
var i;

len = 100;
x = new Float64Array( len );
mu = new Float64Array( len );
sigma = new Float64Array( len );
for ( i = 0; i < len; i++ ) {
x[ i ] = ( randu() * 200.0 ) - 100;
mu[ i ] = ( randu() * 100.0 ) - 50.0;
sigma[ i ] = ( randu() * 20.0 ) + EPS;
}
b.tic();
for ( i = 0; i < b.iterations; i++ ) {
x = ( randu()*200.0 ) - 100;
mu = ( randu()*100.0 ) - 50.0;
sigma = ( randu()*20.0 ) + EPS;
y = logcdf( x, mu, sigma );
y = logcdf( x[ i % len ], mu[ i % len ], sigma[ i % len ] );
if ( isnan( y ) ) {
b.fail( 'should not return NaN' );
}
Expand All @@ -66,11 +75,11 @@ bench( pkg+':factory', function benchmark( b ) {
mu = 0.0;
sigma = 1.5;
mylogcdf = logcdf.factory( mu, sigma );
x = uniform( 100, -3.0, 6.0 );

b.tic();
for ( i = 0; i < b.iterations; i++ ) {
x = ( randu()*6.0 ) - 3.0;
y = mylogcdf( x );
y = mylogcdf( x[ i % x.length ] );
if ( isnan( y ) ) {
b.fail( 'should not return NaN' );
}
Expand Down
Original file line number Diff line number Diff line change
@@ -0,0 +1,73 @@
/**
* @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.
*/

'use strict';

// MODULES //

var resolve = require( 'path' ).resolve;
var bench = require( '@stdlib/bench' );
var Float64Array = require( '@stdlib/array/float64' );
var tryRequire = require( '@stdlib/utils/try-require' );
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( '@stdlib/stats/base/dists/lognormal/logcdf/package.json' ).name;


// VARIABLES //

var logcdf = tryRequire( resolve( __dirname, './../lib/native.js' ) );
var opts = {
'skip': ( logcdf instanceof Error )
};


// MAIN //

bench( pkg+'::native', opts, function benchmark( b ) {
var len;
var sigma;
var mu;
var x;
var y;
var i;

len = 100;
x = new Float64Array( len );
mu = new Float64Array( len );
sigma = new Float64Array( len );
for ( i = 0; i < len; i++ ) {
x[ i ] = ( randu() * 200.0 ) - 100;
mu[ i ] = ( randu() * 100.0 ) - 50.0;
sigma[ i ] = ( randu() * 20.0 ) + EPS;
}
b.tic();
for ( i = 0; i < b.iterations; i++ ) {
y = logcdf( x[ i % len ], mu[ i % len ], sigma[ i % len ] );
if ( isnan( y ) ) {
b.fail( 'should not return NaN' );
}
}
b.toc();
if ( isnan( y ) ) {
b.fail( 'should not return NaN' );
}
b.pass( 'benchmark finished' );
b.end();
});
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