chore: stuff from code review

Neerajpathak07 · Neerajpathak07 · commit 0009cc713a84 · 2025-02-11T09:56:34.000+05:30
diff --git a/lib/node_modules/@stdlib/stats/base/dists/bernoulli/pmf/README.md b/lib/node_modules/@stdlib/stats/base/dists/bernoulli/pmf/README.md
@@ -156,16 +156,16 @@ for ( i = 0; i < 10; i++ ) {
 ### Usage
 
 ```c
-#include "stdlib/stats/base/dists/bernoulli/cdf.h"
+#include "stdlib/stats/base/dists/bernoulli/pmf.h"
 ```
 
 #### stdlib_base_dists_bernoulli_pmf( x, p )
 
 Returns a function for evaluating the [probability mass function][pmf] (PMF) of a [Bernoulli][bernoulli-distribution] distribution with success probability `0 <= p <= 1`.
 
 ```c
-double y = stdlib_base_dists_bernoulli_pmf( 0.5, 0.5 );
-// returns 0.5
+double y = stdlib_base_dists_bernoulli_pmf( 1.0, 0.3 );
+// returns 0.3
 ```
 
 The function accepts the following arguments:
diff --git a/lib/node_modules/@stdlib/stats/base/dists/bernoulli/pmf/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/base/dists/bernoulli/pmf/benchmark/benchmark.js
@@ -22,6 +22,7 @@
 
 var bench = require( '@stdlib/bench' );
 var uniform = require( '@stdlib/random/base/uniform' );
+var discreteUniform = require( '@stdlib/random/base/discrete-uniform' );
 var Float64Array = require( '@stdlib/array/float64' );
 var round = require( '@stdlib/math/base/special/round' );
 var isnan = require( '@stdlib/math/base/assert/is-nan' );
@@ -42,7 +43,7 @@ bench( pkg, function benchmark( b ) {
 	x = new Float64Array( len );
 	p = new Float64Array( len );
 	for ( i = 0; i < len; i++ ) {
-		x[ i ] = round( uniform( 0.0, 3.0 ) );
+		x[ i ] = discreteUniform( 0.0, 3.0 );
 		p[ i ] = uniform( 0.0, 1.0 );
 	}
 
@@ -75,7 +76,7 @@ bench( pkg+':factory', function benchmark( b ) {
 	len = 100;
 	x = new Float64Array( len );
 	for ( i = 0; i < len; i++ ) {
-		x[ i ] = round( uniform( 0.0, 3.0 ) );
+		x[ i ] = discreteUniform( 0.0, 3.0 );
 	}
 
 	b.tic();
diff --git a/lib/node_modules/@stdlib/stats/base/dists/bernoulli/pmf/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/stats/base/dists/bernoulli/pmf/benchmark/benchmark.native.js
@@ -51,7 +51,7 @@ bench( pkg+'::native', opts, function benchmark( b ) {
 	x = new Float64Array( len );
 	p = new Float64Array( len );
 	for ( i = 0; i < len; i++ ) {
-		x[ i ] = round( uniform( 0.0, 3.0 ) );
+		x[ i ] = discreteUniform( 0.0, 3.0 );
 		p[ i ] = uniform( 0.0, 1.0 );
 	}
 
diff --git a/lib/node_modules/@stdlib/stats/base/dists/bernoulli/pmf/docs/types/index.d.ts b/lib/node_modules/@stdlib/stats/base/dists/bernoulli/pmf/docs/types/index.d.ts
@@ -31,7 +31,7 @@ type Unary = ( x: number ) => number;
 */
 interface PMF {
 	/**
-	* Evaluates the probability mass function (PMF) for a Bernoulli distribution with success probability `0 <= p <= 1`.
+	* Evaluates the probability mass function (PMF) for a Bernoulli distribution with success probability `p` at a value `x`.
 	*
 	* ## Notes
 	*
diff --git a/lib/node_modules/@stdlib/stats/base/dists/bernoulli/pmf/include/stdlib/stats/base/dists/bernoulli/pmf.h b/lib/node_modules/@stdlib/stats/base/dists/bernoulli/pmf/include/stdlib/stats/base/dists/bernoulli/pmf.h
@@ -27,7 +27,7 @@ extern "C" {
 #endif
 
 /**
-* Evaluates the probability mass function (PMF) for a Bernoulli distribution with success probability `0 <= p <= 1`.
+* * Evaluates the probability mass function (PMF) for a Bernoulli distribution with success probability `p` at a value `x`.
 */
 double stdlib_base_dists_bernoulli_pmf( const double x, const double p );
 
diff --git a/lib/node_modules/@stdlib/stats/base/dists/bernoulli/pmf/lib/main.js b/lib/node_modules/@stdlib/stats/base/dists/bernoulli/pmf/lib/main.js
@@ -26,7 +26,7 @@ var isnan = require( '@stdlib/math/base/assert/is-nan' );
 // MAIN //
 
 /**
-* Evaluates the moment-generating function (MGF) for a Bernoulli distribution with success probability `p` at a value `t`.
+* Evaluates the probability mass function (PMF) for a Bernoulli distribution with success probability `p` at a value `x`.
 *
 * @param {number} x - input value
 * @param {Probability} p - success probability
diff --git a/lib/node_modules/@stdlib/stats/base/dists/bernoulli/pmf/lib/native.js b/lib/node_modules/@stdlib/stats/base/dists/bernoulli/pmf/lib/native.js
@@ -26,7 +26,7 @@ var addon = require( './../src/addon.node' );
 // MAIN //
 
 /**
-* Evaluates the moment-generating function (MGF) for a Bernoulli distribution with success probability `p` at a value `t`.
+* Evaluates the probability mass function (PMF) for a Bernoulli distribution with success probability `p` at a value `x`.
 *
 * @private
 * @param {number} x - input value
diff --git a/lib/node_modules/@stdlib/stats/base/dists/bernoulli/pmf/src/main.c b/lib/node_modules/@stdlib/stats/base/dists/bernoulli/pmf/src/main.c
@@ -20,15 +20,15 @@
 #include "stdlib/math/base/assert/is_nan.h"
 
 /**
-* Evaluates the probability mass function (PMF) for a Bernoulli distribution with success probability `0 <= p <= 1`.
+* Evaluates the probability mass function (PMF) for a Bernoulli distribution with success probability `p` at a value `x`.
 *
 * @param x    input value
 * @param p    success probability
 * @return     evaluated PMF
 *
 * @example
-* double y = stdlib_base_dists_bernoulli_pmf( 0.5, 0.5 );
-* // returns 0.5
+* double y = stdlib_base_dists_bernoulli_pmf( 1.0, 0.3 );
+* // returns 0.3
 */
 double stdlib_base_dists_bernoulli_pmf( const double x, const double p ) {
 	if (
@@ -45,5 +45,5 @@ double stdlib_base_dists_bernoulli_pmf( const double x, const double p ) {
 	if ( x == 1.0 ) {
 		return p;
 	}
-	return 0.0 ;
+	return 0.0;
 }
diff --git a/lib/node_modules/@stdlib/stats/base/dists/bernoulli/pmf/test/test.native.js b/lib/node_modules/@stdlib/stats/base/dists/bernoulli/pmf/test/test.native.js
@@ -24,9 +24,7 @@ var resolve = require( 'path' ).resolve;
 var tape = require( 'tape' );
 var isnan = require( '@stdlib/math/base/assert/is-nan' );
 var tryRequire = require( '@stdlib/utils/try-require' );
-var abs = require( '@stdlib/math/base/special/abs' );
 var PINF = require( '@stdlib/constants/float64/pinf' );
-var EPS = require( '@stdlib/constants/float64/eps' );
 
 
 // FIXTURES //
@@ -105,8 +103,6 @@ tape( 'if provided a success probability `p` outside of `[0,1]`, the function al
 
 tape( 'the function evaluates the pmf for `x` given small parameter `p`', opts, function test( t ) {
 	var expected;
-	var delta;
-	var tol;
 	var x;
 	var p;
 	var y;
@@ -117,21 +113,13 @@ tape( 'the function evaluates the pmf for `x` given small parameter `p`', opts,
 	p = smallP.p;
 	for ( i = 0; i < x.length; i++ ) {
 		y = pmf( x[i], p[i] );
-		if ( y === expected[i] ) {
-			t.equal( y, expected[i], 'x: '+x[i]+'. p:'+p[i]+', y: '+y+', expected: '+expected[i] );
-		} else {
-			delta = abs( y - expected[ i ] );
-			tol = 2.0 * EPS * abs( expected[ i ] );
-			t.ok( delta <= tol, 'within tolerance. x: '+x[ i ]+'. p: '+p[i]+'. y: '+y+'. E: '+expected[ i ]+'. Δ: '+delta+'. tol: '+tol+'.' );
-		}
+		t.equal( y, expected[i], 'x: '+x[i]+'. p:'+p[i]+', y: '+y+', expected: '+expected[i] );
 	}
 	t.end();
 });
 
 tape( 'the function evaluates the pmf for `x` given large parameter `p`', opts, function test( t ) {
 	var expected;
-	var delta;
-	var tol;
 	var x;
 	var p;
 	var y;
@@ -142,13 +130,7 @@ tape( 'the function evaluates the pmf for `x` given large parameter `p`', opts,
 	p = largeP.p;
 	for ( i = 0; i < x.length; i++ ) {
 		y = pmf( x[i], p[i] );
-		if ( y === expected[i] ) {
-			t.equal( y, expected[i], 'x: '+x[i]+'. p: '+p[i]+', y: '+y+', expected: '+expected[i] );
-		} else {
-			delta = abs( y - expected[ i ] );
-			tol = 1.5 * EPS * abs( expected[ i ] );
-			t.ok( delta <= tol, 'within tolerance. x: '+x[ i ]+'. p: '+p[i]+'. y: '+y+'. E: '+expected[ i ]+'. Δ: '+delta+'. tol: '+tol+'.' );
-		}
+		t.equal( y, expected[i], 'x: '+x[i]+'. p: '+p[i]+', y: '+y+', expected: '+expected[i] );
 	}
 	t.end();
 });
diff --git a/lib/node_modules/@stdlib/stats/base/dists/bernoulli/pmf/test/test.pmf.js b/lib/node_modules/@stdlib/stats/base/dists/bernoulli/pmf/test/test.pmf.js
@@ -22,9 +22,7 @@
 
 var tape = require( 'tape' );
 var isnan = require( '@stdlib/math/base/assert/is-nan' );
-var abs = require( '@stdlib/math/base/special/abs' );
 var PINF = require( '@stdlib/constants/float64/pinf' );
-var EPS = require( '@stdlib/constants/float64/eps' );
 var pmf = require( './../lib' );
 
 
@@ -96,8 +94,6 @@ tape( 'if provided a success probability `p` outside of `[0,1]`, the function al
 
 tape( 'the function evaluates the pmf for `x` given small parameter `p`', function test( t ) {
 	var expected;
-	var delta;
-	var tol;
 	var x;
 	var p;
 	var y;
@@ -108,21 +104,13 @@ tape( 'the function evaluates the pmf for `x` given small parameter `p`', functi
 	p = smallP.p;
 	for ( i = 0; i < x.length; i++ ) {
 		y = pmf( x[i], p[i] );
-		if ( y === expected[i] ) {
-			t.equal( y, expected[i], 'x: '+x[i]+'. p:'+p[i]+', y: '+y+', expected: '+expected[i] );
-		} else {
-			delta = abs( y - expected[ i ] );
-			tol = 2.0 * EPS * abs( expected[ i ] );
-			t.ok( delta <= tol, 'within tolerance. x: '+x[ i ]+'. p: '+p[i]+'. y: '+y+'. E: '+expected[ i ]+'. Δ: '+delta+'. tol: '+tol+'.' );
-		}
+		t.equal( y, expected[i], 'x: '+x[i]+'. p:'+p[i]+', y: '+y+', expected: '+expected[i] );
 	}
 	t.end();
 });
 
 tape( 'the function evaluates the pmf for `x` given large parameter `p`', function test( t ) {
 	var expected;
-	var delta;
-	var tol;
 	var x;
 	var p;
 	var y;
@@ -133,13 +121,7 @@ tape( 'the function evaluates the pmf for `x` given large parameter `p`', functi
 	p = largeP.p;
 	for ( i = 0; i < x.length; i++ ) {
 		y = pmf( x[i], p[i] );
-		if ( y === expected[i] ) {
-			t.equal( y, expected[i], 'x: '+x[i]+'. p: '+p[i]+', y: '+y+', expected: '+expected[i] );
-		} else {
-			delta = abs( y - expected[ i ] );
-			tol = 1.5 * EPS * abs( expected[ i ] );
-			t.ok( delta <= tol, 'within tolerance. x: '+x[ i ]+'. p: '+p[i]+'. y: '+y+'. E: '+expected[ i ]+'. Δ: '+delta+'. tol: '+tol+'.' );
-		}
+		t.equal( y, expected[i], 'x: '+x[i]+'. p: '+p[i]+', y: '+y+', expected: '+expected[i] );
 	}
 	t.end();
 });

Original file line number	Diff line number	Diff line change
`@@ -51,7 +51,7 @@ bench( pkg+'::native', opts, function benchmark( b ) {`
`51`	`51`	`x = new Float64Array( len );`
`52`	`52`	`p = new Float64Array( len );`
`53`	`53`	`for ( i = 0; i < len; i++ ) {`
`54`		`- x[ i ] = round( uniform( 0.0, 3.0 ) );`
	`54`	`+ x[ i ] = discreteUniform( 0.0, 3.0 );`
`55`	`55`	`p[ i ] = uniform( 0.0, 1.0 );`
`56`	`56`	`}`
`57`	`57`
Original file line number	Diff line number	Diff line change
`@@ -31,7 +31,7 @@ type Unary = ( x: number ) => number;`
`31`	`31`	`*/`
`32`	`32`	`interface PMF {`
`33`	`33`	`/**`
`34`		- * Evaluates the probability mass function (PMF) for a Bernoulli distribution with success probability `0 <= p <= 1`.
	`34`	+ * Evaluates the probability mass function (PMF) for a Bernoulli distribution with success probability `p` at a value `x`.
`35`	`35`	`*`
`36`	`36`	`* ## Notes`
`37`	`37`	`*`
Original file line number	Diff line number	Diff line change
`@@ -26,7 +26,7 @@ var isnan = require( '@stdlib/math/base/assert/is-nan' );`
`26`	`26`	`// MAIN //`
`27`	`27`
`28`	`28`	`/**`
`29`		-* Evaluates the moment-generating function (MGF) for a Bernoulli distribution with success probability `p` at a value `t`.
	`29`	+* Evaluates the probability mass function (PMF) for a Bernoulli distribution with success probability `p` at a value `x`.
`30`	`30`	`*`
`31`	`31`	`* @param {number} x - input value`
`32`	`32`	`* @param {Probability} p - success probability`
Original file line number	Diff line number	Diff line change
`@@ -26,7 +26,7 @@ var addon = require( './../src/addon.node' );`
`26`	`26`	`// MAIN //`
`27`	`27`
`28`	`28`	`/**`
`29`		-* Evaluates the moment-generating function (MGF) for a Bernoulli distribution with success probability `p` at a value `t`.
	`29`	+* Evaluates the probability mass function (PMF) for a Bernoulli distribution with success probability `p` at a value `x`.
`30`	`30`	`*`
`31`	`31`	`* @private`
`32`	`32`	`* @param {number} x - input value`
Original file line number	Diff line number	Diff line change
`@@ -20,15 +20,15 @@`
`20`	`20`	`#include "stdlib/math/base/assert/is_nan.h"`
`21`	`21`
`22`	`22`	`/**`
`23`		-* Evaluates the probability mass function (PMF) for a Bernoulli distribution with success probability `0 <= p <= 1`.
	`23`	+* Evaluates the probability mass function (PMF) for a Bernoulli distribution with success probability `p` at a value `x`.
`24`	`24`	`*`
`25`	`25`	`* @param x input value`
`26`	`26`	`* @param p success probability`
`27`	`27`	`* @return evaluated PMF`
`28`	`28`	`*`
`29`	`29`	`* @example`
`30`		`-* double y = stdlib_base_dists_bernoulli_pmf( 0.5, 0.5 );`
`31`		`-* // returns 0.5`
	`30`	`+* double y = stdlib_base_dists_bernoulli_pmf( 1.0, 0.3 );`
	`31`	`+* // returns 0.3`
`32`	`32`	`*/`
`33`	`33`	`double stdlib_base_dists_bernoulli_pmf( const double x, const double p ) {`
`34`	`34`	`if (`
`@@ -45,5 +45,5 @@ double stdlib_base_dists_bernoulli_pmf( const double x, const double p ) {`
`45`	`45`	`if ( x == 1.0 ) {`
`46`	`46`	`return p;`
`47`	`47`	`}`
`48`		`- return 0.0 ;`
	`48`	`+ return 0.0;`
`49`	`49`	`}`