chore: clean-up

---
type: pre_commit_static_analysis_report
description: Results of running static analysis checks when committing changes.
report:
  - task: lint_filenames
    status: passed
  - task: lint_editorconfig
    status: passed
  - task: lint_markdown
    status: passed
  - task: lint_package_json
    status: na
  - task: lint_repl_help
    status: na
  - task: lint_javascript_src
    status: na
  - task: lint_javascript_cli
    status: na
  - task: lint_javascript_examples
    status: na
  - task: lint_javascript_tests
    status: passed
  - task: lint_javascript_benchmarks
    status: passed
  - task: lint_python
    status: na
  - task: lint_r
    status: na
  - task: lint_c_src
    status: na
  - task: lint_c_examples
    status: na
  - task: lint_c_benchmarks
    status: passed
  - task: lint_c_tests_fixtures
    status: na
  - task: lint_shell
    status: na
  - task: lint_typescript_declarations
    status: na
  - task: lint_typescript_tests
    status: na
  - task: lint_license_headers
    status: passed
---

Author: kgryte

lib/node_modules/@stdlib/stats/base/dists/cosine/mean/README.md

@@ -157,7 +157,7 @@ for ( i = 0; i < 10; i++ ) {
 #include "stdlib/stats/base/dists/cosine/mean.h"
 ```
 
-#### stdlib_base_dists_cosine_mean( a, b )
+#### stdlib_base_dists_cosine_mean( mu, s )
 
 Returns the [expected value][mean] for a [raised cosine][cosine-distribution] distribution with location parameter `mu` and scale parameter `s`.
 

lib/node_modules/@stdlib/stats/base/dists/cosine/mean/benchmark/benchmark.native.js

@@ -20,18 +20,27 @@
 
 // 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 EPS = require( '@stdlib/constants/float64/eps' );
+var tryRequire = require( '@stdlib/utils/try-require' );
 var pkg = require( './../package.json' ).name;
-var mean = require( './../lib' );
+
+
+// VARIABLES //
+
+var mean = tryRequire( resolve( __dirname, './../lib/native.js' ) );
+var opts = {
+	'skip': ( mean instanceof Error )
+};
 
 
 // MAIN //
 
-bench( pkg, function benchmark( b ) {
+bench( pkg+'::native', opts, function benchmark( b ) {
 	var len;
 	var mu;
 	var s;

lib/node_modules/@stdlib/stats/base/dists/cosine/mean/benchmark/c/benchmark.c

@@ -74,24 +74,39 @@ static double tic( void ) {
 	return (double)now.tv_sec + (double)now.tv_usec/1.0e6;
 }
 
+/**
+* Generates a random number on the interval [min,max).
+*
+* @param min    minimum value (inclusive)
+* @param max    maximum value (exclusive)
+* @return       random number
+*/
+static double random_uniform( const double min, const double max ) {
+	double v = (double)rand() / ( (double)RAND_MAX + 1.0 );
+	return min + ( v*(max-min) );
+}
+
 /**
 * Runs a benchmark.
 *
 * @return elapsed time in seconds
 */
 static double benchmark( void ) {
 	double elapsed;
-	double mu;
-	double s;
+	double mu[ 100 ];
+	double s[ 100 ];
 	double y;
 	double t;
 	int i;
 
+	for ( i = 0; i < 100; i++ ) {
+		mu[ i ] = random_uniform( -50.0, 50.0 );
+		s[ i ] = random_uniform( 1.0, 20.0 );
+	}
+
 	t = tic();
 	for ( i = 0; i < ITERATIONS; i++ ) {
-		mu = 100.0*( (double)rand() / (double)RAND_MAX ) - 50.0;
-		s = 20.0*( (double)rand() / (double)RAND_MAX );
-		y = stdlib_base_dists_cosine_mean( mu, s );
+		y = stdlib_base_dists_cosine_mean( mu[ i%100 ], s[ i%100 ] );
 		if ( y != y ) {
 			printf( "should not return NaN\n" );
 			break;

lib/node_modules/@stdlib/stats/base/dists/cosine/mean/test/test.js

@@ -22,10 +22,8 @@
 
 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 NINF = require( '@stdlib/constants/float64/ninf' );
-var EPS = require( '@stdlib/constants/float64/eps' );
 var mean = require( './../lib' );
 
 
@@ -79,8 +77,6 @@ tape( 'if provided a nonpositive `s`, the function returns `NaN`', function test
 
 tape( 'the function returns the expected value of a raised cosine distribution', function test( t ) {
 	var expected;
-	var delta;
-	var tol;
 	var mu;
 	var s;
 	var y;
@@ -91,15 +87,7 @@ tape( 'the function returns the expected value of a raised cosine distribution',
 	s = data.s;
 	for ( i = 0; i < mu.length; i++ ) {
 		y = mean( mu[i], s[i] );
-		if ( expected[i] !== null ) {
-			if ( y === expected[i] ) {
-				t.equal( y, expected[i], 'mu:'+mu[i]+', s: '+s[i]+', y: '+y+', expected: '+expected[i] );
-			} else {
-				delta = abs( y - expected[ i ] );
-				tol = 1.0 * EPS * abs( expected[ i ] );
-				t.ok( delta <= tol, 'within tolerance. mu: '+mu[i]+'. s: '+s[i]+'. y: '+y+'. E: '+expected[ i ]+'. Δ: '+delta+'. tol: '+tol+'.' );
-			}
-		}
+		t.equal( y, expected[i], 'mu:'+mu[i]+', s: '+s[i]+', y: '+y+', expected: '+expected[i] );
 	}
 	t.end();
 });

lib/node_modules/@stdlib/stats/base/dists/cosine/mean/test/test.native.js

@@ -23,11 +23,9 @@
 var resolve = require( 'path' ).resolve;
 var tape = require( 'tape' );
 var tryRequire = require( '@stdlib/utils/try-require' );
-var abs = require( '@stdlib/math/base/special/abs' );
 var isnan = require( '@stdlib/math/base/assert/is-nan' );
 var PINF = require( '@stdlib/constants/float64/pinf' );
 var NINF = require( '@stdlib/constants/float64/ninf' );
-var EPS = require( '@stdlib/constants/float64/eps' );
 
 
 // VARIABLES //
@@ -84,25 +82,17 @@ tape( 'if provided `s <= 0.0`, the function returns `NaN`', opts, function test(
 
 tape( 'the function returns the mean of a cosine distribution', opts, function test( t ) {
 	var expected;
-	var delta;
-	var tol;
 	var mu;
 	var s;
-	var i;
 	var y;
+	var i;
 
 	expected = data.expected;
 	mu = data.mu;
 	s = data.s;
-	for ( i = 0; i < expected.length; i++ ) {
+	for ( i = 0; i < mu.length; i++ ) {
 		y = mean( mu[i], s[i] );
-		if ( y === expected[i] ) {
-			t.equal( y, expected[i], 'mu: '+mu[i]+', s: '+s[i]+', y: '+y+', expected: '+expected[i] );
-		} else {
-			delta = abs( y - expected[ i ] );
-			tol = 1.0 * EPS * abs( expected[ i ] );
-			t.ok( delta <= tol, 'within tolerance. mu: '+mu[i]+'. s: '+s[i]+'. y: '+y+'. E: '+expected[ i ]+'. Δ: '+delta+'. tol: '+tol+'.' );
-		}
+		t.equal( y, expected[i], 'mu:'+mu[i]+', s: '+s[i]+', y: '+y+', expected: '+expected[i] );
 	}
 	t.end();
 });