fix: update C implementation for stats/base/dists/kumaraswamy/median

PR-URL: #5452
Closes: #5047

Co-authored-by: Karan Anand <[email protected]>
Co-authored-by: stdlib-bot <[email protected]>
Co-authored-by: Philipp Burckhardt <[email protected]>
Reviewed-by: Philipp Burckhardt <[email protected]>
Reviewed-by: Karan Anand <[email protected]>
Signed-off-by: Gautam sharma <[email protected]>

Author: 4 people

Diff for: lib/node_modules/@stdlib/stats/base/dists/kumaraswamy/median/README.md

@@ -174,8 +174,8 @@ for ( i = 0; i < 10; i++ ) {
 Returns the [median][median] of a [Kumaraswamy's double bounded][kumaraswamy-distribution] distribution with first shape parameter `a` and second shape parameter `b`.
 
 ```c
-double out = stdlib_base_dists_kumaraswamy_median( 2.0, 3.0 );
-// returns ~1.817
+double out = stdlib_base_dists_kumaraswamy_median( 1.0, 1.0 );
+// returns 0.5
 ```
 
 The function accepts the following arguments:
@@ -212,7 +212,7 @@ double stdlib_base_dists_kumaraswamy_median( const double a, const double b );
 
 static double random_uniform( const double min, const double max ) {
     double v = (double)rand() / ( (double)RAND_MAX + 1.0 );
-    return min + ( v * (max - min) );
+    return min + ( v*(max-min) );
 }
 
 int main( void ) {
@@ -225,7 +225,7 @@ int main( void ) {
         a = random_uniform( 0.1, 10.0 );
         b = random_uniform( 0.1, 10.0 );
         y = stdlib_base_dists_kumaraswamy_median( a, b );
-        printf( "a: %lf, b: %lf, Median(a, b): %lf\n", a, b, y );
+        printf( "a: %lf, b: %lf, Median(X;a,b): %lf\n", a, b, y );
     }
 
     return 0;

Diff for: lib/node_modules/@stdlib/stats/base/dists/kumaraswamy/median/benchmark/benchmark.js

@@ -22,7 +22,7 @@
 
 var bench = require( '@stdlib/bench' );
 var Float64Array = require( '@stdlib/array/float64' );
-var randu = require( '@stdlib/random/base/randu' );
+var uniform = require( '@stdlib/random/base/uniform' );
 var isnan = require( '@stdlib/math/base/assert/is-nan' );
 var EPS = require( '@stdlib/constants/float64/eps' );
 var pkg = require( './../package.json' ).name;
@@ -42,8 +42,8 @@ bench( pkg, function benchmark( b ) {
 	alpha = new Float64Array( len );
 	beta = new Float64Array( len );
 	for ( i = 0; i < len; i++ ) {
-		alpha[ i ] = ( randu() * 10.0 ) + EPS;
-		beta[ i ] = ( randu() * 10.0 ) + EPS;
+		alpha[ i ] = uniform( EPS, 10.0 );
+		beta[ i ] = uniform( EPS, 10.0 );
 	}
 
 	b.tic();

Diff for: lib/node_modules/@stdlib/stats/base/dists/kumaraswamy/median/benchmark/benchmark.native.js

@@ -23,7 +23,7 @@
 var resolve = require( 'path' ).resolve;
 var bench = require( '@stdlib/bench' );
 var Float64Array = require( '@stdlib/array/float64' );
-var randu = require( '@stdlib/random/base/randu' );
+var uniform = require( '@stdlib/random/base/uniform' );
 var EPS = require( '@stdlib/constants/float64/eps' );
 var isnan = require( '@stdlib/math/base/assert/is-nan' );
 var tryRequire = require( '@stdlib/utils/try-require' );
@@ -51,8 +51,8 @@ bench( pkg+'::native', opts, function benchmark( b ) {
 	alpha = new Float64Array( len );
 	beta = new Float64Array( len );
 	for ( i = 0; i < len; i++ ) {
-		alpha[ i ] = ( randu() * 10.0 ) + EPS;
-		beta[ i ] = ( randu() * 10.0 ) + EPS;
+		alpha[ i ] = uniform( EPS, 10.0 );
+		beta[ i ] = uniform( EPS, 10.0 );
 	}
 
 	b.tic();

Diff for: lib/node_modules/@stdlib/stats/base/dists/kumaraswamy/median/benchmark/c/benchmark.c

@@ -93,9 +93,9 @@ static double random_uniform( const double min, const double max ) {
 * @return elapsed time in seconds
 */
 static double benchmark( void ) {
-	double elapsed;
 	double a[ 100 ];
 	double b[ 100 ];
+	double elapsed;
 	double y;
 	double t;
 	int i;

Diff for: lib/node_modules/@stdlib/stats/base/dists/kumaraswamy/median/examples/c/example.c

@@ -36,7 +36,7 @@ int main( void ) {
 		b = random_uniform( 0.1, 10.0 );
 
 		y = stdlib_base_dists_kumaraswamy_median( a, b );
-		printf( "a: %lf, b: %lf, Median(a,b): %lf\n", a, b, y );
+		printf( "a: %lf, b: %lf, Median(X;a,b): %lf\n", a, b, y );
 	}
 
 	return 0;

Diff for: lib/node_modules/@stdlib/stats/base/dists/kumaraswamy/median/include/stdlib/stats/base/dists/kumaraswamy/median.h

@@ -27,7 +27,7 @@ extern "C" {
 #endif
 
 /**
-* Returns the median of a Kumaraswamy distribution.
+* Returns the median of a Kumaraswamy's double bounded distribution.
 */
 double stdlib_base_dists_kumaraswamy_median( const double a, const double b );
 

Diff for: lib/node_modules/@stdlib/stats/base/dists/kumaraswamy/median/lib/native.js

@@ -26,23 +26,39 @@ var addon = require( './../src/addon.node' );
 // MAIN //
 
 /**
-* Returns the median of a Kumaraswamy distribution.
+* Returns the median of a Kumaraswamy's double bounded distribution.
 *
 * @private
-* @param {number} a - shape parameter
-* @param {number} b - shape parameter
-* @returns {number} median
+* @param {PositiveNumber} a - first shape parameter
+* @param {PositiveNumber} b - second shape parameter
+* @returns {PositiveNumber} median
 *
 * @example
-* var v = median( 2.0, 3.0 );
-* // returns ~0.2062994740159002
+* var v = median( 0.5, 1.0 );
+* // returns 0.25
 *
 * @example
-* var v = median( 1.0, 5.0 );
-* // returns ~0.12944943670387588
+* var v = median( 4.0, 12.0 );
+* // returns ~0.487
 *
 * @example
-* var v = median( 2.0, -0.5 );
+* var v = median( 12.0, 2.0 );
+* // returns ~0.903
+*
+* @example
+* var v = median( 1.0, -0.1 );
+* // returns NaN
+*
+* @example
+* var v = median( -0.1, 1.0 );
+* // returns NaN
+*
+* @example
+* var v = median( 2.0, NaN );
+* // returns NaN
+*
+* @example
+* var v = median( NaN, 2.0 );
 * // returns NaN
 */
 function median( a, b ) {

Diff for: lib/node_modules/@stdlib/stats/base/dists/kumaraswamy/median/manifest.json

@@ -40,8 +40,7 @@
       "dependencies": [
         "@stdlib/math/base/napi/binary",
         "@stdlib/math/base/assert/is-nan",
-        "@stdlib/math/base/special/pow",
-        "@stdlib/constants/float64/eps"
+        "@stdlib/math/base/special/pow"
       ]
     },
     {
@@ -74,8 +73,7 @@
       "libpath": [],
       "dependencies": [
         "@stdlib/math/base/assert/is-nan",
-        "@stdlib/math/base/special/pow",
-        "@stdlib/constants/float64/eps"
+        "@stdlib/math/base/special/pow"
       ]
     }
   ]

Diff for: lib/node_modules/@stdlib/stats/base/dists/kumaraswamy/median/src/main.c

@@ -21,15 +21,15 @@
 #include "stdlib/math/base/special/pow.h"
 
 /**
-* Returns the median of a Kumaraswamy distribution.
+* Returns the median of a Kumaraswamy's double bounded distribution.
 *
 * @param a       first shape parameter
 * @param b       second shape parameter
 * @return        median
 *
 * @example
-* double y = stdlib_base_dists_kumaraswamy_median( 2.0, 3.0 );
-* // returns 1.0
+* double y = stdlib_base_dists_kumaraswamy_median( 0.5, 1.0 );
+* // returns 0.25
 */
 double stdlib_base_dists_kumaraswamy_median( const double a, const double b ) {
 	if (
@@ -39,5 +39,5 @@ double stdlib_base_dists_kumaraswamy_median( const double a, const double b ) {
 	) {
 		return 0.0/0.0; // NaN
 	}
-	return 1.0 - stdlib_base_pow( 0.5, 1.0 / b );
+	return stdlib_base_pow( 1.0 - stdlib_base_pow( 2.0, -1.0/b ), 1.0/a );
 }

Diff for: lib/node_modules/@stdlib/stats/base/dists/kumaraswamy/median/test/fixtures/julia/runner.jl

@@ -26,8 +26,8 @@ Generate fixture data and write to file.
 
 # Arguments
 
-* `a`: shape parameter a (must be positive)
-* `b`: shape parameter b (must be positive)
+* `a`: first shape parameter
+* `b`: second shape parameter
 * `name::AbstractString`: output filename
 
 # Examples

Diff for: lib/node_modules/@stdlib/stats/base/dists/kumaraswamy/median/test/test.js

@@ -44,10 +44,10 @@ tape( 'main export is a function', function test( t ) {
 
 tape( 'if provided `NaN` for any parameter, the function returns `NaN`', function test( t ) {
 	var v = median( NaN, 0.5 );
-	t.equal( isnan( v ), true, 'returns NaN' );
+	t.equal( isnan( v ), true, 'returns expected value' );
 
 	v = median( 10.0, NaN );
-	t.equal( isnan( v ), true, 'returns NaN' );
+	t.equal( isnan( v ), true, 'returns expected value' );
 
 	t.end();
 });
@@ -56,25 +56,25 @@ tape( 'if provided a nonpositive `a`, the function returns `NaN`', function test
 	var y;
 
 	y = median( 0.0, 2.0 );
-	t.equal( isnan( y ), true, 'returns NaN' );
+	t.equal( isnan( y ), true, 'returns expected value' );
 
 	y = median( -1.0, 2.0 );
-	t.equal( isnan( y ), true, 'returns NaN' );
+	t.equal( isnan( y ), true, 'returns expected value' );
 
 	y = median( -1.0, 2.0 );
-	t.equal( isnan( y ), true, 'returns NaN' );
+	t.equal( isnan( y ), true, 'returns expected value' );
 
 	y = median( NINF, 1.0 );
-	t.equal( isnan( y ), true, 'returns NaN' );
+	t.equal( isnan( y ), true, 'returns expected value' );
 
 	y = median( NINF, PINF );
-	t.equal( isnan( y ), true, 'returns NaN' );
+	t.equal( isnan( y ), true, 'returns expected value' );
 
 	y = median( NINF, NINF );
-	t.equal( isnan( y ), true, 'returns NaN' );
+	t.equal( isnan( y ), true, 'returns expected value' );
 
 	y = median( NINF, NaN );
-	t.equal( isnan( y ), true, 'returns NaN' );
+	t.equal( isnan( y ), true, 'returns expected value' );
 
 	t.end();
 });
@@ -83,25 +83,25 @@ tape( 'if provided a nonpositive `b`, the function returns `NaN`', function test
 	var y;
 
 	y = median( 2.0, 0.0 );
-	t.equal( isnan( y ), true, 'returns NaN' );
+	t.equal( isnan( y ), true, 'returns expected value' );
 
 	y = median( 2.0, -1.0 );
-	t.equal( isnan( y ), true, 'returns NaN' );
+	t.equal( isnan( y ), true, 'returns expected value' );
 
 	y = median( 2.0, -1/0 );
-	t.equal( isnan( y ), true, 'returns NaN' );
+	t.equal( isnan( y ), true, 'returns expected value' );
 
 	y = median( 1.0, NINF );
-	t.equal( isnan( y ), true, 'returns NaN' );
+	t.equal( isnan( y ), true, 'returns expected value' );
 
 	y = median( PINF, NINF );
-	t.equal( isnan( y ), true, 'returns NaN' );
+	t.equal( isnan( y ), true, 'returns expected value' );
 
 	y = median( NINF, NINF );
-	t.equal( isnan( y ), true, 'returns NaN' );
+	t.equal( isnan( y ), true, 'returns expected value' );
 
 	y = median( NaN, NINF );
-	t.equal( isnan( y ), true, 'returns NaN' );
+	t.equal( isnan( y ), true, 'returns expected value' );
 
 	t.end();
 });

Diff for: lib/node_modules/@stdlib/stats/base/dists/kumaraswamy/median/test/test.native.js

@@ -53,31 +53,64 @@ tape( 'main export is a function', opts, function test( t ) {
 
 tape( 'if provided `NaN` for any parameter, the function returns `NaN`', opts, function test( t ) {
 	var v = median( NaN, 0.5 );
-	t.equal( isnan( v ), true, 'returns NaN' );
+	t.equal( isnan( v ), true, 'returns expected value' );
 
-	v = median( 10, NaN );
-	t.equal( isnan( v ), true, 'returns NaN' );
+	v = median( 10.0, NaN );
+	t.equal( isnan( v ), true, 'returns expected value' );
 
-	v = median( NaN, NaN );
-	t.equal( isnan( v ), true, 'returns NaN' );
+	t.end();
+});
+
+tape( 'if provided a nonpositive `a`, the function returns `NaN`', opts, function test( t ) {
+	var y;
+
+	y = median( 0.0, 2.0 );
+	t.equal( isnan( y ), true, 'returns expected value' );
+
+	y = median( -1.0, 2.0 );
+	t.equal( isnan( y ), true, 'returns expected value' );
+
+	y = median( -1.0, 2.0 );
+	t.equal( isnan( y ), true, 'returns expected value' );
+
+	y = median( NINF, 1.0 );
+	t.equal( isnan( y ), true, 'returns expected value' );
+
+	y = median( NINF, PINF );
+	t.equal( isnan( y ), true, 'returns expected value' );
+
+	y = median( NINF, NINF );
+	t.equal( isnan( y ), true, 'returns expected value' );
+
+	y = median( NINF, NaN );
+	t.equal( isnan( y ), true, 'returns expected value' );
 
 	t.end();
 });
 
-tape( 'if provided a nonpositive `gamma`, the function always returns `NaN`', opts, function test( t ) {
+tape( 'if provided a nonpositive `b`, the function returns `NaN`', opts, function test( t ) {
 	var y;
 
-	y = median( 0.0, 0.0 );
-	t.equal( isnan( y ), true, 'returns NaN' );
+	y = median( 2.0, 0.0 );
+	t.equal( isnan( y ), true, 'returns expected value' );
 
-	y = median( 0.0, -1.0 );
-	t.equal( isnan( y ), true, 'returns NaN' );
+	y = median( 2.0, -1.0 );
+	t.equal( isnan( y ), true, 'returns expected value' );
 
-	y = median( 0.0, NINF );
-	t.equal( isnan( y ), true, 'returns NaN' );
+	y = median( 2.0, -1/0 );
+	t.equal( isnan( y ), true, 'returns expected value' );
+
+	y = median( 1.0, NINF );
+	t.equal( isnan( y ), true, 'returns expected value' );
 
 	y = median( PINF, NINF );
-	t.equal( isnan( y ), true, 'returns NaN' );
+	t.equal( isnan( y ), true, 'returns expected value' );
+
+	y = median( NINF, NINF );
+	t.equal( isnan( y ), true, 'returns expected value' );
+
+	y = median( NaN, NINF );
+	t.equal( isnan( y ), true, 'returns expected value' );
 
 	t.end();
 });