chore: minor clean-up

Planeshifter · Planeshifter · commit b7867cbb3a4f · 2024-12-23T18:09:59.000-06:00
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---
type: pre_push_report
description: Results of running various checks prior to pushing changes.
report:
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---
diff --git a/lib/node_modules/@stdlib/math/base/special/boxcox1pinv/src/main.c b/lib/node_modules/@stdlib/math/base/special/boxcox1pinv/src/main.c
@@ -30,7 +30,7 @@
 * @return          inverse of the Box-Cox transformation
 *
 * @example
-* var v = boxcox1pinv( 1.0, 2.5 );
+* double v = boxcox1pinv( 1.0, 2.5 );
 * // returns ~0.6505
 */
 double stdlib_base_boxcox1pinv( const double y, const double lambda ) {
diff --git a/lib/node_modules/@stdlib/math/base/special/boxcoxinv/src/main.c b/lib/node_modules/@stdlib/math/base/special/boxcoxinv/src/main.c
@@ -29,7 +29,7 @@
 * @return          inverse of the Box-Cox transformation
 *
 * @example
-* var v = boxcoxinv( 1.0, 2.5 );
+* double v = boxcoxinv( 1.0, 2.5 );
 * // returns ~1.6505
 */
 double stdlib_base_boxcoxinv( const double y, const double lambda ) {
diff --git a/lib/node_modules/@stdlib/math/base/special/csch/src/main.c b/lib/node_modules/@stdlib/math/base/special/csch/src/main.c
@@ -26,11 +26,11 @@
 * @return     hyperbolic cosecant
 *
 * @example
-* var v = stdlib_base_csch( 2.0 );
+* double v = stdlib_base_csch( 2.0 );
 * // returns ~0.2757
 *
 * @example
-* var v = stdlib_base_csch( -2.0 );
+* double v = stdlib_base_csch( -2.0 );
 * // returns ~-0.2757
 */
 double stdlib_base_csch( const double x ) {
diff --git a/lib/node_modules/@stdlib/math/base/special/gammasgn/src/main.c b/lib/node_modules/@stdlib/math/base/special/gammasgn/src/main.c
@@ -27,7 +27,7 @@
 * @return        sign of the gamma function
 *
 * @example
-* var v = gammasgn( 1.0 );
+* double v = gammasgn( 1.0 );
 * // returns 1.0
 */
 double stdlib_base_gammasgn( const double x ) {
diff --git a/lib/node_modules/@stdlib/stats/base/dists/bernoulli/mean/benchmark/c/benchmark.c b/lib/node_modules/@stdlib/stats/base/dists/bernoulli/mean/benchmark/c/benchmark.c
@@ -75,13 +75,15 @@ static double tic( void ) {
 }
 
 /**
-* Generates a random number on the interval [0,1).
+* Generates a random number on the interval [min,max).
 *
-* @return random number
+* @param min    minimum value (inclusive)
+* @param max    maximum value (exclusive)
+* @return       random number
 */
-static double rand_double( void ) {
-	int r = rand();
-	return (double)r / ( (double)RAND_MAX + 1.0 );
+static double random_uniform( const double min, const double max ) {
+	double v = (double)rand() / ( (double)RAND_MAX + 1.0 );
+	return min + ( v*(max-min) );
 }
 
 /**
@@ -97,7 +99,7 @@ static double benchmark( void ) {
 	int i;
 
 	for ( i = 0; i < 100; i++ ) {
-		p[ i ] = rand_double();
+		p[ i ] = random_uniform( 0.0, 1.0 );
 	}
 
 	t = tic();
diff --git a/lib/node_modules/@stdlib/stats/base/dists/bernoulli/mode/benchmark/c/benchmark.c b/lib/node_modules/@stdlib/stats/base/dists/bernoulli/mode/benchmark/c/benchmark.c
@@ -75,13 +75,15 @@ static double tic( void ) {
 }
 
 /**
-* Generates a random number on the interval [0,1).
+* Generates a random number on the interval [min,max).
 *
-* @return random number
+* @param min    minimum value (inclusive)
+* @param max    maximum value (exclusive)
+* @return       random number
 */
-static double rand_double( void ) {
-	int r = rand();
-	return (double)r / ( (double)RAND_MAX + 1.0 );
+static double random_uniform( const double min, const double max ) {
+	double v = (double)rand() / ( (double)RAND_MAX + 1.0 );
+	return min + ( v*(max-min) );
 }
 
 /**
@@ -97,7 +99,7 @@ static double benchmark( void ) {
 	int i;
 
 	for ( i = 0; i < 100; i++ ) {
-		p[ i ] = rand_double();
+		p[ i ] = random_uniform( 0.0, 1.0 );
 	}
 
 	t = tic();
diff --git a/lib/node_modules/@stdlib/stats/base/dists/exponential/mean/test/test.native.js b/lib/node_modules/@stdlib/stats/base/dists/exponential/mean/test/test.native.js
@@ -24,9 +24,7 @@ var resolve = require( 'path' ).resolve;
 var tape = require( 'tape' );
 var tryRequire = require( '@stdlib/utils/try-require' );
 var isnan = require( '@stdlib/math/base/assert/is-nan' );
-var abs = require( '@stdlib/math/base/special/abs' );
 var NINF = require( '@stdlib/constants/float64/ninf' );
-var EPS = require( '@stdlib/constants/float64/eps' );
 
 
 // VARIABLES //
@@ -68,25 +66,17 @@ tape( 'if provided a rate parameter `lambda` that is not a nonnegative number, t
 	t.end();
 });
 
-tape( 'the function returns the mean of an exponential distribution', opts, function test( t ) {
+tape( 'the function returns the expected value of an exponential distribution', opts, function test( t ) {
 	var expected;
 	var lambda;
-	var delta;
-	var tol;
 	var i;
 	var y;
 
 	expected = data.expected;
 	lambda = data.lambda;
 	for ( i = 0; i < expected.length; i++ ) {
 		y = mean( lambda[i] );
-		if ( y === expected[ i ] ) {
-			t.equal( y, expected[i], 'lambda: '+lambda[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. lambda: '+lambda[i]+'. y: '+y+'. E: '+expected[ i ]+'. Δ: '+delta+'. tol: '+tol+'.' );
-		}
+		t.equal( y, expected[i], 'lambda: '+lambda[i]+', y: '+y+', expected: '+expected[i] );
 	}
 	t.end();
 });
diff --git a/lib/node_modules/@stdlib/stats/base/dists/f/skewness/benchmark/c/benchmark.c b/lib/node_modules/@stdlib/stats/base/dists/f/skewness/benchmark/c/benchmark.c
@@ -102,7 +102,7 @@ static double benchmark( void ) {
 
 	for ( i = 0; i < 100; i++ ) {
 		d1[ i ] = random_uniform( 0.0, 10.0 ) + STDLIB_CONSTANT_FLOAT64_EPS;
-		d2[ i ] = random_uniform( 0.0, 10.0 ) + STDLIB_CONSTANT_FLOAT64_EPS;
+		d2[ i ] = random_uniform( 0.0, 10.0 ) + 6.0 + STDLIB_CONSTANT_FLOAT64_EPS;
 	}
 
 	t = tic();
diff --git a/lib/node_modules/@stdlib/stats/base/dists/gamma/kurtosis/README.md b/lib/node_modules/@stdlib/stats/base/dists/gamma/kurtosis/README.md
@@ -170,7 +170,7 @@ for ( i = 0; i < 10; i++ ) {
 
 #### stdlib_base_dists_gamma_kurtosis( alpha, beta )
 
-Returns the kurtosis of a gamma distribution.
+Returns the [excess kurtosis][kurtosis] of a [gamma][gamma-distribution] distribution with parameters `alpha` (shape parameter) and `beta` (rate parameter).
 
 ```c
 double out = stdlib_base_dists_gamma_kurtosis( 1.0, 1.0 );
diff --git a/lib/node_modules/@stdlib/stats/base/dists/gamma/kurtosis/src/main.c b/lib/node_modules/@stdlib/stats/base/dists/gamma/kurtosis/src/main.c
@@ -28,7 +28,7 @@
 *
 * @example
 * double y = stdlib_base_gamma_kurtosis( 1.0, 1.0 );
-* // returns 1.0
+* // returns 6.0
 */
 double stdlib_base_dists_gamma_kurtosis( const double alpha, const double beta ) {
 	if (
diff --git a/lib/node_modules/@stdlib/stats/base/dists/gamma/mean/README.md b/lib/node_modules/@stdlib/stats/base/dists/gamma/mean/README.md
@@ -172,7 +172,7 @@ for ( i = 0; i < 10; i++ ) {
 
 #### stdlib_base_dists_gamma_mean( alpha, beta )
 
-Returns the mean of a gamma distribution.
+Returns the [expected value][expected-value] of a [gamma][gamma-distribution] distribution with parameters `alpha` (shape parameter) and `beta` (rate parameter).
 
 ```c
 double out = stdlib_base_dists_gamma_mean( 1.0, 1.0 );
diff --git a/lib/node_modules/@stdlib/stats/base/dists/gamma/mean/include/stdlib/stats/base/dists/gamma/mean.h b/lib/node_modules/@stdlib/stats/base/dists/gamma/mean/include/stdlib/stats/base/dists/gamma/mean.h
@@ -27,7 +27,7 @@ extern "C" {
 #endif
 
 /**
-* Returns the mean of a gamma distribution.
+* Returns the expected value of a gamma distribution.
 */
 double stdlib_base_dists_gamma_mean( const double alpha, const double beta );
 
diff --git a/lib/node_modules/@stdlib/stats/base/dists/gamma/mean/src/main.c b/lib/node_modules/@stdlib/stats/base/dists/gamma/mean/src/main.c
@@ -19,11 +19,11 @@
 #include "stdlib/stats/base/dists/gamma/mean.h"
 
 /**
-* Returns the mean of a gamma distribution.
+* Returns the expected value of a gamma distribution.
 *
 * @param alpha    shape parameter
 * @param beta     rate parameter
-* @return         mean
+* @return         expected value
 *
 * @example
 * double y = stdlib_base_gamma_mean( 1.0, 1.0 );
diff --git a/lib/node_modules/@stdlib/stats/base/dists/gamma/mean/test/test.native.js b/lib/node_modules/@stdlib/stats/base/dists/gamma/mean/test/test.native.js
@@ -121,7 +121,7 @@ tape( 'the function returns the mean of a gamma distribution', opts, function te
 			t.equal( y, expected[i], 'alpha: '+alpha[i]+', beta: '+beta[i]+', y: '+y+', expected: '+expected[i] );
 		} else {
 			delta = abs( y - expected[ i ] );
-			tol = 2.0 * EPS * abs( expected[ i ] );
+			tol = 1.0 * EPS * abs( expected[ i ] );
 			t.ok( delta <= tol, 'within tolerance. alpha: '+alpha[i]+'. beta: '+beta[i]+'. y: '+y+'. E: '+expected[ i ]+'. Δ: '+delta+'. tol: '+tol+'.' );
 		}
 	}
diff --git a/lib/node_modules/@stdlib/stats/base/dists/poisson/mean/benchmark/c/benchmark.c b/lib/node_modules/@stdlib/stats/base/dists/poisson/mean/benchmark/c/benchmark.c
@@ -75,13 +75,15 @@ static double tic( void ) {
 }
 
 /**
-* Generates a random number on the interval [0,20).
+* Generates a random number on the interval [min,max).
 *
-* @return random number
+* @param min    minimum value (inclusive)
+* @param max    maximum value (exclusive)
+* @return       random number
 */
-static double rand_double( void ) {
-	int r = rand();
-	return 20.0*(double)r / ( (double)RAND_MAX + 1.0 );
+static double random_uniform( const double min, const double max ) {
+	double v = (double)rand() / ( (double)RAND_MAX + 1.0 );
+	return min + ( v*(max-min) );
 }
 
 /**
@@ -97,7 +99,7 @@ static double benchmark( void ) {
 	int i;
 
 	for ( i = 0; i < 100; i++ ) {
-		lambda[ i ] = rand_double();
+		lambda[ i ] = random_uniform( 0.0, 20.0 );
 	}
 
 	t = tic();
diff --git a/lib/node_modules/@stdlib/stats/base/dists/triangular/mean/include/stdlib/stats/base/dists/triangular/mean.h b/lib/node_modules/@stdlib/stats/base/dists/triangular/mean/include/stdlib/stats/base/dists/triangular/mean.h
@@ -27,7 +27,7 @@ extern "C" {
 #endif
 
 /**
-* Returns the mean of a triangular distribution with lower bound `a`, upper bound `b`, and mode `c`.
+* Returns the mean of a triangular distribution.
 */
 double stdlib_base_dists_triangular_mean( const double a, const double b, const double c );
 
diff --git a/lib/node_modules/@stdlib/stats/base/dists/triangular/mean/lib/native.js b/lib/node_modules/@stdlib/stats/base/dists/triangular/mean/lib/native.js
@@ -29,9 +29,9 @@ var addon = require( './../src/addon.node' );
 * Returns the expected value (mean) of a triangular distribution.
 *
 * @private
-* @param {NonNegativeNumber} a - lower bound
-* @param {NonNegativeNumber} b - upper bound
-* @param {NonNegativeNumber} c - mode (peak)
+* @param {NonNegativeNumber} a - minimum support
+* @param {NonNegativeNumber} b - maximum support
+* @param {NonNegativeNumber} c - mode
 * @returns {NonNegativeNumber} expected value (mean)
 *
 * @example
diff --git a/lib/node_modules/@stdlib/stats/base/dists/triangular/mode/README.md b/lib/node_modules/@stdlib/stats/base/dists/triangular/mode/README.md
@@ -222,7 +222,7 @@ int main( void ) {
     for ( i = 0; i < 25; i++ ) {
         a = random_uniform( 0.0, 10.0 );
         b = random_uniform( 0.0, 10.0 ) + a;
-        c = a + (b - a) * random_uniform( 0.0, 1.0 ); // mode between a and b
+        c = random_uniform( a, b ); // mode between a and b
         y = stdlib_base_dists_triangular_mode( a, b, c );
         printf( "a: %lf, b: %lf, c: %lf, M(X;a,b,c): %lf\n", a, b, c, y );
     }
diff --git a/lib/node_modules/@stdlib/stats/base/dists/triangular/mode/benchmark/c/benchmark.c b/lib/node_modules/@stdlib/stats/base/dists/triangular/mode/benchmark/c/benchmark.c
@@ -75,13 +75,15 @@ static double tic( void ) {
 }
 
 /**
-* Generates a random number on the interval [0,20).
+* Generates a random number on the interval [min,max).
 *
-* @return random number
+* @param min    minimum value (inclusive)
+* @param max    maximum value (exclusive)
+* @return       random number
 */
-static double rand_double( void ) {
-	int r = rand();
-	return 20.0*(double)r / ( (double)RAND_MAX + 1.0 );
+static double random_uniform( const double min, const double max ) {
+	double v = (double)rand() / ( (double)RAND_MAX + 1.0 );
+	return min + ( v*(max-min) );
 }
 
 /**
@@ -98,9 +100,9 @@ static double benchmark( void ) {
 
 	// Generate random parameters for the triangular distribution
 	for ( i = 0; i < 100; i++ ) {
-		a[ i ] = rand_double() * 20.0;  // Lower bound
-		b[ i ] = ( rand_double() * 20.0 ) + a[ i ];  // Upper bound
-		c[ i ] = ( rand_double() * ( b[i] - a[i] ) ) + a[i];  // Mode
+		a[ i ] = random_uniform( 0.0, 20.0 ); // Lower bound
+		b[ i ] = random_uniform( a[i], 40.0 ); // Upper bound
+		c[ i ] = random_uniform( a[i], b[i] ); // Mode
 	}
 
 	t = tic();
diff --git a/lib/node_modules/@stdlib/stats/base/dists/triangular/mode/examples/c/example.c b/lib/node_modules/@stdlib/stats/base/dists/triangular/mode/examples/c/example.c
@@ -35,7 +35,7 @@ int main( void ) {
 	for ( i = 0; i < 25; i++ ) {
 		a = random_uniform( 0.0, 10.0 );
 		b = random_uniform( 0.0, 10.0 ) + a;
-		c = a + (b - a) * random_uniform( 0.0, 1.0 ); // mode between a and b
+		c = random_uniform( a, b ); // mode between a and b
 		y = stdlib_base_dists_triangular_mode( a, b, c );
 		printf( "a: %lf, b: %lf, c: %lf, M(X;a,b,c): %lf\n", a, b, c, y );
 	}
diff --git a/lib/node_modules/@stdlib/stats/base/dists/triangular/mode/include/stdlib/stats/base/dists/triangular/mode.h b/lib/node_modules/@stdlib/stats/base/dists/triangular/mode/include/stdlib/stats/base/dists/triangular/mode.h
@@ -27,7 +27,7 @@ extern "C" {
 #endif
 
 /**
-* Returns the mode of a triangular distribution with lower bound `a`, upper bound `b`, and mode `c`.
+* Returns the mode of a triangular distribution.
 */
 double stdlib_base_dists_triangular_mode( const double a, const double b, const double c );
 
diff --git a/lib/node_modules/@stdlib/stats/base/dists/triangular/mode/lib/native.js b/lib/node_modules/@stdlib/stats/base/dists/triangular/mode/lib/native.js
@@ -29,10 +29,10 @@ var addon = require( './../src/addon.node' );
 * Returns the mode of a triangular distribution.
 *
 * @private
-* @param {NonNegativeNumber} a - lower bound
-* @param {NonNegativeNumber} b - upper bound
-* @param {NonNegativeNumber} c - mode (peak)
-* @returns {NonNegativeNumber} mode
+* @param {number} a - minimum support
+* @param {number} b - maximum support
+* @param {number} c - mode
+* @returns {number} mode
 *
 * @example
 * var v = mode( 0.0, 10.0, 5.0 );
diff --git a/lib/node_modules/@stdlib/stats/base/dists/triangular/mode/src/main.c b/lib/node_modules/@stdlib/stats/base/dists/triangular/mode/src/main.c
@@ -22,13 +22,13 @@
 /**
 * Returns the mode of a triangular distribution.
 *
-* @param a  lower bound
-* @param b  upper bound
-* @param c  mode (peak)
+* @param a  minimum support
+* @param b  maximum support
+* @param c  mode
 * @returns  mode
 *
 * @example
-* var v = mode( 0.0, 10.0, 5.0 );
+* double v = mode( 0.0, 10.0, 5.0 );
 * // returns 5.0
 */
 double stdlib_base_dists_triangular_mode( const double a, const double b, const double c ) {

Original file line number	Diff line number	Diff line change
`@@ -30,7 +30,7 @@`
`30`	`30`	`* @return inverse of the Box-Cox transformation`
`31`	`31`	`*`
`32`	`32`	`* @example`
`33`		`-* var v = boxcox1pinv( 1.0, 2.5 );`
	`33`	`+* double v = boxcox1pinv( 1.0, 2.5 );`
`34`	`34`	`* // returns ~0.6505`
`35`	`35`	`*/`
`36`	`36`	`double stdlib_base_boxcox1pinv( const double y, const double lambda ) {`
Original file line number	Diff line number	Diff line change
`@@ -29,7 +29,7 @@`
`29`	`29`	`* @return inverse of the Box-Cox transformation`
`30`	`30`	`*`
`31`	`31`	`* @example`
`32`		`-* var v = boxcoxinv( 1.0, 2.5 );`
	`32`	`+* double v = boxcoxinv( 1.0, 2.5 );`
`33`	`33`	`* // returns ~1.6505`
`34`	`34`	`*/`
`35`	`35`	`double stdlib_base_boxcoxinv( const double y, const double lambda ) {`
Original file line number	Diff line number	Diff line change
`@@ -26,11 +26,11 @@`
`26`	`26`	`* @return hyperbolic cosecant`
`27`	`27`	`*`
`28`	`28`	`* @example`
`29`		`-* var v = stdlib_base_csch( 2.0 );`
	`29`	`+* double v = stdlib_base_csch( 2.0 );`
`30`	`30`	`* // returns ~0.2757`
`31`	`31`	`*`
`32`	`32`	`* @example`
`33`		`-* var v = stdlib_base_csch( -2.0 );`
	`33`	`+* double v = stdlib_base_csch( -2.0 );`
`34`	`34`	`* // returns ~-0.2757`
`35`	`35`	`*/`
`36`	`36`	`double stdlib_base_csch( const double x ) {`
Original file line number	Diff line number	Diff line change
`@@ -27,7 +27,7 @@`
`27`	`27`	`* @return sign of the gamma function`
`28`	`28`	`*`
`29`	`29`	`* @example`
`30`		`-* var v = gammasgn( 1.0 );`
	`30`	`+* double v = gammasgn( 1.0 );`
`31`	`31`	`* // returns 1.0`
`32`	`32`	`*/`
`33`	`33`	`double stdlib_base_gammasgn( const double x ) {`
Original file line number	Diff line number	Diff line change
`@@ -102,7 +102,7 @@ static double benchmark( void ) {`
`102`	`102`
`103`	`103`	`for ( i = 0; i < 100; i++ ) {`
`104`	`104`	`d1[ i ] = random_uniform( 0.0, 10.0 ) + STDLIB_CONSTANT_FLOAT64_EPS;`
`105`		`- d2[ i ] = random_uniform( 0.0, 10.0 ) + STDLIB_CONSTANT_FLOAT64_EPS;`
	`105`	`+ d2[ i ] = random_uniform( 0.0, 10.0 ) + 6.0 + STDLIB_CONSTANT_FLOAT64_EPS;`
`106`	`106`	`}`
`107`	`107`
`108`	`108`	`t = tic();`
Original file line number	Diff line number	Diff line change
`@@ -28,7 +28,7 @@`
`28`	`28`	`*`
`29`	`29`	`* @example`
`30`	`30`	`* double y = stdlib_base_gamma_kurtosis( 1.0, 1.0 );`
`31`		`-* // returns 1.0`
	`31`	`+* // returns 6.0`
`32`	`32`	`*/`
`33`	`33`	`double stdlib_base_dists_gamma_kurtosis( const double alpha, const double beta ) {`
`34`	`34`	`if (`