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feat : add C implementation for stats/base/dists/truncated-normal/pdf #5056

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Original file line number Diff line number Diff line change
Expand Up @@ -145,6 +145,111 @@ for ( i = 0; i < 25; 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/truncated-normal/pdf.h"
```

#### stdlib_base_dists_truncated_normal_pdf( x, a, b , mu , sigma )

Evaluates the r distribution function (pdf) for an truncated-normal distribution.

```c
double out = stdlib_base_dists_truncated_normal_pdf( 0.9, 0.0, 1.0, 0.0, 1.0 );
// returns ~0.7795
```

The function accepts the following arguments:

- **x**: `[in] double` input value.
- **a**: `[in] double` lower limit.
- **b**: `[in] double` upper limit.
- **mu**: `[in] double` location parameter.
- **sigma**: `[in] double` scale parameter.


```c
double stdlib_base_dists_truncated-normal_pdf( const double x, const double a, const double b , 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/truncated-normal/pdf.h"
#include <stdlib.h>
#include <stdio.h>
#include <math.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 a;
double b;
double mu;
double sigma;
double y;
int i;

for ( i = 0; i < 25; i++ ) {
x = random_uniform( -10.0, 10.0 );
a = random_uniform( -20.0, 0.0 );
b = random_uniform( a, a + 40.0 );
mu = random_uniform( a, b );
sigma = random_uniform( 0.1, 5.0 );
y = stdlib_base_dists_truncated_normal_pdf( x, a, b, mu, sigma );
printf( "x: %lf, a: %lf, b: %lf, mu: %lf, sigma: %lf, f(x;a,b,mu,sigma): %lf\n", x, a, b, mu, sigma, y );
}
}
```

</section>

<!-- /.examples -->

</section>

<!-- /.c -->

<!-- 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
@@ -0,0 +1,111 @@
/**
* @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 bench = require( '@stdlib/bench' );
var Float64Array = require( '@stdlib/array/float64' );
var uniform = require( '@stdlib/random/base/uniform' );
var isnan = require( '@stdlib/math/base/assert/is-nan' );
var pkg = require( './../package.json' ).name;
var pdf = require( './../lib' );


// MAIN //

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

len = 100;
x = new Float64Array( len );
a = new Float64Array( len );
bmin = new Float64Array( len );
bmax = new Float64Array( len );
mu = new Float64Array( len );
sigma = new Float64Array( len );

for ( i = 0; i < len; i++ ) {
x[ i ] = uniform( -10.0, 10.0 );
a[ i ] = uniform( -20.0, 0.0 );
bmin[ i ] = uniform( a[ i ], a[ i ] + 40.0 );
bmax[ i ] = uniform( 0.1, 5.0 );
mu[ i ] = uniform( -5.0, 5.0 );
sigma[ i ] = uniform( 0.1, 5.0 );
}

b.tic();
for ( i = 0; i < b.iterations; i++ ) {
y = pdf( x[ i % len ], a[ i % len ], bmin[ 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();
});

bench( pkg+':factory', function benchmark( b ) {
var mypdf;
var sigma;
var bmin;
var len;
var mu;
var a;
var x;
var y;
var i;

sigma = 1.0;
bmin = 1.0;
len = 100;
mu = 0.5;
a = 0.0;
x = new Float64Array( len );
mypdf = pdf.factory( a, bmin, mu, sigma );
for ( i = 0; i < len; i++ ) {
x[ i ] = uniform( -2.0, 2.0 );
}

b.tic();
for ( i = 0; i < b.iterations; i++ ) {
y = mypdf( x[ 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();
});
Original file line number Diff line number Diff line change
@@ -0,0 +1,80 @@
/**
* @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 uniform = require( '@stdlib/random/base/uniform' );
var isnan = require( '@stdlib/math/base/assert/is-nan' );
var tryRequire = require( '@stdlib/utils/try-require' );
var pkg = require( './../package.json' ).name;


// VARIABLES //

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


// MAIN //

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

len = 100;
x = new Float64Array( len );
a = new Float64Array( len );
bmin = new Float64Array( len );
mu = new Float64Array( len );
sigma = new Float64Array( len );

for ( i = 0; i < len; i++ ) {
x[ i ] = uniform( -10.0, 10.0 );
a[ i ] = uniform( -20.0, 0.0 );
bmin[ i ] = uniform( a[ i ], a[ i ] + 40.0 );
mu[ i ] = uniform( -5.0, 5.0 );
sigma[ i ] = uniform( 0.1, 5.0 );
}

b.tic();
for ( i = 0; i < b.iterations; i++ ) {
y = pdf( x[ i % len ], a[ i % len ], bmin[ 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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