feat(levy-logpdf): adding all the functionality required for levy logpdf

Author: Aadish Jain

lib/node_modules/@stdlib/stats/base/dists/levy/logpdf/README.md

@@ -146,6 +146,104 @@ 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/levy/logpdf.h"
+```
+
+#### stdlib_base_dists_levy_logpdf( x, mu, c )
+
+Evaluates the logarithm of the [probability density function][pdf] (PDF) for a [Lévy][levy-distribution] distribution with parameters `mu` (location parameter) and `c` (scale parameter).
+
+```c
+double out = stdlib_base_dists_levy_logpdf( 0.5, 0.0, 2.0 );
+// returns ~-1.837
+```
+
+The function accepts the following arguments:
+
+-   **x**: `[in] double` input value.
+-   **mu**: `[in] double` location parameter.
+-   **c**: `[in] double` scale parameter.
+
+```c
+double stdlib_base_dists_levy_logpdf( const double x, const double mu, const double c );
+```
+
+</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/levy/logpdf.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 mu;
+    double c;
+    double y;
+    int i;
+
+    for ( i = 0; i < 25; i++ ) {
+        x = random_uniform( 0.0, 10.0 );
+        mu = random_uniform( -5.0, 5.0 );
+        c = random_uniform( 0.1, 5.0 );
+        y = stdlib_base_dists_levy_logpdf( x, mu, c );
+        printf( "x: %lf, mu: %lf, c: %lf, logpdf(x;mu,c): %lf\n", x, mu, c, y );
+    }
+}
+```
+
+</section>
+
+<!-- /.examples -->
+
+</section>
+
+<!-- /.c -->
+
 <!-- Section for related `stdlib` packages. Do not manually edit this section, as it is automatically populated. -->
 
 <section class="related">

lib/node_modules/@stdlib/stats/base/dists/levy/logpdf/benchmark/benchmark.js

@@ -1,7 +1,7 @@
 /**
 * @license Apache-2.0
 *
-* Copyright (c) 2018 The Stdlib Authors.
+* Copyright (c) 2024 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.
@@ -21,28 +21,37 @@
 // 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' );
 var pkg = require( './../package.json' ).name;
 var logpdf = require( './../lib' );
 
 
 // MAIN //
 
 bench( pkg, function benchmark( b ) {
+	var len;
 	var mu;
-	var s;
+	var c;
 	var x;
 	var y;
 	var i;
 
+	len = 100;
+	x = new Float64Array( len );
+	mu = new Float64Array( len );
+	c = new Float64Array( len );
+	for ( i = 0; i < len; i++ ) {
+		x[ i ] = ( randu() * 10.0 );
+		mu[ i ] = ( randu() * 10.0 ) - 5.0;
+		c[ i ] = ( randu() * 4.9 ) + 0.1;
+	}
+
 	b.tic();
 	for ( i = 0; i < b.iterations; i++ ) {
-		mu = ( randu()*20.0 ) - 10.0;
-		x = ( randu()*40.0 ) + mu;
-		s = ( randu()*5.0 ) + EPS;
-		y = logpdf( x, mu, s );
+		y = logpdf( x[ i % len ], mu[ i % len ], c[ i % len ] );
 		if ( isnan( y ) ) {
 			b.fail( 'should not return NaN' );
 		}
@@ -55,22 +64,22 @@ bench( pkg, function benchmark( b ) {
 	b.end();
 });
 
-bench( pkg+':factory', function benchmark( b ) {
+bench( pkg + ':factory', function benchmark( b ) {
 	var mylogpdf;
 	var mu;
-	var s;
+	var c;
 	var x;
 	var y;
 	var i;
 
-	mu = 10.0;
-	s = 4.0;
-	mylogpdf = logpdf.factory( mu, s );
+	mu = 0.0;
+	c = 1.0;
+	mylogpdf = logpdf.factory( mu, c );
+	x = uniform( 100, -2.0, 2.0 );
 
 	b.tic();
 	for ( i = 0; i < b.iterations; i++ ) {
-		x = randu() * 50.0;
-		y = mylogpdf( x );
+		y = mylogpdf( x[ i % x.length ] );
 		if ( isnan( y ) ) {
 			b.fail( 'should not return NaN' );
 		}

lib/node_modules/@stdlib/stats/base/dists/levy/logpdf/benchmark/benchmark.native.js

@@ -0,0 +1,73 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2024 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 randu = require( '@stdlib/random/base/randu' );
+var isnan = require( '@stdlib/math/base/assert/is-nan' );
+var tryRequire = require( '@stdlib/utils/try-require' );
+var pkg = require( './../package.json' ).name;
+
+
+// VARIABLES //
+
+var logpdf = tryRequire( resolve( __dirname, './../lib/native.js' ) );
+var opts = {
+	'skip': ( logpdf instanceof Error )
+};
+
+
+// MAIN //
+
+bench( pkg + '::native', opts, function benchmark( b ) {
+	var len;
+	var mu;
+	var c;
+	var x;
+	var y;
+	var i;
+
+	len = 100;
+	x = new Float64Array( len );
+	mu = new Float64Array( len );
+	c = new Float64Array( len );
+	for ( i = 0; i < len; i++ ) {
+		x[ i ] = ( randu() * 10.0 );
+		mu[ i ] = ( randu() * 10.0 ) - 5.0;
+		c[ i ] = ( randu() * 4.9 ) + 0.1;
+	}
+
+	b.tic();
+	for ( i = 0; i < b.iterations; i++ ) {
+		y = logpdf( x[ i % len ], mu[ i % len ], c[ 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();
+});