chore: clean-up

kgryte · kgryte · commit c7294205a503 · 2026-01-16T01:06:00.000-08:00
---
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: passed
  - task: lint_javascript_src
    status: passed
  - 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: passed
  - task: lint_c_examples
    status: na
  - task: lint_c_benchmarks
    status: na
  - task: lint_c_tests_fixtures
    status: na
  - task: lint_shell
    status: na
  - task: lint_typescript_declarations
    status: passed
  - task: lint_typescript_tests
    status: passed
  - task: lint_license_headers
    status: passed
---
diff --git a/lib/node_modules/@stdlib/stats/base/dists/halfnormal/mean/README.md b/lib/node_modules/@stdlib/stats/base/dists/halfnormal/mean/README.md
@@ -70,7 +70,7 @@ y = mean( 0.5 );
 // returns ~0.399
 ```
 
-If provided `NaN` as any argument, the function returns `NaN`.
+If provided `NaN`, the function returns `NaN`.
 
 ```javascript
 var y = mean( NaN );
diff --git a/lib/node_modules/@stdlib/stats/base/dists/halfnormal/mean/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/base/dists/halfnormal/mean/benchmark/benchmark.js
@@ -21,8 +21,7 @@
 // MODULES //
 
 var bench = require( '@stdlib/bench' );
-var Float64Array = require( '@stdlib/array/float64' );
-var randu = require( '@stdlib/random/base/randu' );
+var uniform = require( '@stdlib/random/array/uniform' );
 var isnan = require( '@stdlib/math/base/assert/is-nan' );
 var EPS = require( '@stdlib/constants/float64/eps' );
 var pkg = require( './../package.json' ).name;
@@ -33,19 +32,16 @@ var mean = require( './../lib' );
 
 bench( pkg, function benchmark( b ) {
 	var sigma;
-	var len;
 	var y;
 	var i;
 
-	len = 100;
-	sigma = new Float64Array( len );
-	for ( i = 0; i < len; i++ ) {
-		sigma[ i ] = ( randu() * 20.0 ) + EPS;
-	}
+	sigma = uniform( 100, EPS, 20.0, {
+		'dtype': 'float64'
+	});
 
 	b.tic();
 	for ( i = 0; i < b.iterations; i++ ) {
-		y = mean( sigma[ i % len ] );
+		y = mean( sigma[ i%sigma.length ] );
 		if ( isnan( y ) ) {
 			b.fail( 'should not return NaN' );
 		}
diff --git a/lib/node_modules/@stdlib/stats/base/dists/halfnormal/mean/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/stats/base/dists/halfnormal/mean/benchmark/benchmark.native.js
@@ -22,11 +22,11 @@
 
 var resolve = require( 'path' ).resolve;
 var bench = require( '@stdlib/bench' );
-var Float64Array = require( '@stdlib/array/float64' );
-var uniform = require( '@stdlib/random/base/uniform' );
+var uniform = require( '@stdlib/random/array/uniform' );
 var isnan = require( '@stdlib/math/base/assert/is-nan' );
 var tryRequire = require( '@stdlib/utils/try-require' );
 var EPS = require( '@stdlib/constants/float64/eps' );
+var format = require( '@stdlib/string/format' );
 var pkg = require( './../package.json' ).name;
 
 
@@ -40,20 +40,18 @@ var opts = {
 
 // MAIN //
 
-bench( pkg+'::native', opts, function benchmark( b ) {
+bench( format( '%s::native', pkg ), opts, function benchmark( b ) {
 	var sigma;
-	var len;
 	var y;
 	var i;
 
-	len = 100;
-	sigma = new Float64Array( len );
-	for ( i = 0; i < len; i++ ) {
-		sigma[ i ] = uniform( EPS, 20.0 );
-	}
+	sigma = uniform( 100, EPS, 20.0, {
+		'dtype': 'float64'
+	});
+
 	b.tic();
 	for ( i = 0; i < b.iterations; i++ ) {
-		y = mean( sigma[ i % len ] );
+		y = mean( sigma[ i%sigma.length ] );
 		if ( isnan( y ) ) {
 			b.fail( 'should not return NaN' );
 		}
diff --git a/lib/node_modules/@stdlib/stats/base/dists/halfnormal/mean/docs/repl.txt b/lib/node_modules/@stdlib/stats/base/dists/halfnormal/mean/docs/repl.txt
@@ -3,8 +3,6 @@
     Returns the expected value of a half-normal distribution with scale
     parameter `σ`.
 
-    If provided `NaN` as any argument, the function returns `NaN`.
-
     If provided `σ <= 0`, the function returns `NaN`.
 
     Parameters
@@ -20,9 +18,9 @@
     Examples
     --------
     > var y = {{alias}}( 1.0 )
-    ~0.7978845608
+    ~0.79788
     > y = {{alias}}( 5.0 )
-    ~3.989422804
+    ~3.98942
     > y = {{alias}}( NaN )
     NaN
     > y = {{alias}}( 0.0 )
diff --git a/lib/node_modules/@stdlib/stats/base/dists/halfnormal/mean/docs/types/index.d.ts b/lib/node_modules/@stdlib/stats/base/dists/halfnormal/mean/docs/types/index.d.ts
@@ -30,11 +30,11 @@
 *
 * @example
 * var y = mean( 1.0 );
-* // returns ~0.7978845608
+* // returns ~0.79788
 *
 * @example
 * var y = mean( 5.0 );
-* // returns ~3.989422804
+* // returns ~3.98942
 *
 * @example
 * var y = mean( NaN );
diff --git a/lib/node_modules/@stdlib/stats/base/dists/halfnormal/mean/lib/main.js b/lib/node_modules/@stdlib/stats/base/dists/halfnormal/mean/lib/main.js
@@ -25,6 +25,11 @@ var sqrt = require( '@stdlib/math/base/special/sqrt' );
 var PI = require( '@stdlib/constants/float64/pi' );
 
 
+// VARIABLES //
+
+var SQRT_TWO_OVER_PI = sqrt( 2.0 / PI );
+
+
 // MAIN //
 
 /**
@@ -50,13 +55,10 @@ var PI = require( '@stdlib/constants/float64/pi' );
 * // returns NaN
 */
 function mean( sigma ) {
-	if (
-		isnan( sigma ) ||
-		sigma <= 0.0
-	) {
+	if ( isnan( sigma ) || sigma <= 0.0 ) {
 		return NaN;
 	}
-	return sigma * sqrt( 2.0 / PI );
+	return sigma * SQRT_TWO_OVER_PI;
 }
 
 
diff --git a/lib/node_modules/@stdlib/stats/base/dists/halfnormal/mean/lib/native.js b/lib/node_modules/@stdlib/stats/base/dists/halfnormal/mean/lib/native.js
@@ -38,7 +38,7 @@ var addon = require( './../src/addon.node' );
 *
 * @example
 * var y = mean( 4.0 );
-* // returns ~3.1915382432114616
+* // returns ~3.192
 *
 * @example
 * var y = mean( NaN );
diff --git a/lib/node_modules/@stdlib/stats/base/dists/halfnormal/mean/src/addon.c b/lib/node_modules/@stdlib/stats/base/dists/halfnormal/mean/src/addon.c
@@ -19,5 +19,4 @@
 #include "stdlib/stats/base/dists/halfnormal/mean.h"
 #include "stdlib/math/base/napi/unary.h"
 
-// cppcheck-suppress shadowFunction
 STDLIB_MATH_BASE_NAPI_MODULE_D_D( stdlib_base_dists_halfnormal_mean )
diff --git a/lib/node_modules/@stdlib/stats/base/dists/halfnormal/mean/src/main.c b/lib/node_modules/@stdlib/stats/base/dists/halfnormal/mean/src/main.c
@@ -21,6 +21,8 @@
 #include "stdlib/math/base/special/sqrt.h"
 #include "stdlib/constants/float64/pi.h"
 
+static const double SQRT_TWO_OVER_PI = stdlib_base_sqrt( 2.0 / STDLIB_CONSTANT_FLOAT64_PI );
+
 /**
 * Returns the expected value for a half-normal distribution with scale parameter `sigma`.
 *
@@ -35,5 +37,5 @@ double stdlib_base_dists_halfnormal_mean( const double sigma ) {
 	if ( stdlib_base_is_nan( sigma ) || sigma <= 0.0 ) {
 		return 0.0 / 0.0; // NaN
 	}
-	return sigma * stdlib_base_sqrt( 2.0 / STDLIB_CONSTANT_FLOAT64_PI );
+	return sigma * SQRT_TWO_OVER_PI;
 }
diff --git a/lib/node_modules/@stdlib/stats/base/dists/halfnormal/mean/test/fixtures/julia/runner.jl b/lib/node_modules/@stdlib/stats/base/dists/halfnormal/mean/test/fixtures/julia/runner.jl
@@ -21,13 +21,19 @@ import JSON
 """
 	gen( sigma, name )
 
-Generate fixture data for the mean of a half-normal distribution
-and write to file.
+Generate fixture data and write to file.
 
 # Arguments
 
-* `sigma::AbstractVector{<:Real}`: scale parameter (σ > 0)
+* `sigma`: scale parameter
 * `name::AbstractString`: output filename
+
+# Examples
+
+``` julia
+julia> sigma = rand( 1000 );
+julia> gen( sigma, \"data.json\" );
+```
 """
 function gen( sigma, name )
 	c = sqrt( 2.0 / π )
@@ -41,17 +47,28 @@ function gen( sigma, name )
 		end
 	end
 
-	data = Dict(
-		"sigma" => sigma,
-		"expected" => expected
-	)
+	# Store data to be written to file as a collection:
+	data = Dict([
+		("sigma", sigma),
+		("expected", z)
+	]);
 
-	open( name, "w" ) do io
-		write( io, JSON.json( data ) )
-		write( io, "\n" )
-	end
+	# Based on the script directory, create an output filepath:
+	filepath = joinpath( dir, name )
+
+	# Write the data to the output filepath as JSON:
+	outfile = open( filepath, "w" );
+	write( outfile, JSON.json(data) );
+	write( outfile, "\n" );
+	close( outfile );
 end
 
+# Get the filename:
+file = @__FILE__;
+
+# Extract the directory in which this file resides:
+dir = dirname( file );
+
 # Generate fixtures:
-sigma = rand( 1000 ) .* 5.0
-gen( sigma, "data.json" )
+sigma = rand( 1000 ) .* 5.0;
+gen( sigma, "data.json" );
diff --git a/lib/node_modules/@stdlib/stats/base/dists/halfnormal/mean/test/test.js b/lib/node_modules/@stdlib/stats/base/dists/halfnormal/mean/test/test.js
@@ -47,7 +47,7 @@ tape( 'if provided `NaN` for `sigma`, the function returns `NaN`', function test
 	t.end();
 });
 
-tape( 'if provided a value less than or equal to 0 for `sigma`, the function returns `NaN`', function test( t ) {
+tape( 'if provided a nonpositive `sigma`, the function returns `NaN`', function test( t ) {
 	var y;
 
 	y = mean( 0.0 );
@@ -70,21 +70,17 @@ tape( 'the function returns the expected value of a half-normal distribution', f
 	var y;
 	var i;
 
-	// Test cases (sigma, expected)
 	sigma = data.sigma;
 	expected = data.expected;
 
 	for ( i = 0; i < sigma.length; i++ ) {
 		y = mean( sigma[i] );
 		delta = abs( y - expected[i] );
 		tol = 1.0 * EPS * abs( expected[i] );
-
-		if ( expected[i] !== null ) {
-			if ( y === expected[i] || delta <= tol ) {
-				t.strictEqual( y, expected[i], 'sigma: '+sigma[i] );
-			} else {
-				t.ok( delta <= tol, 'within tolerance. σ: '+sigma[i]+'. y: '+y+'. E: '+expected[ i ]+'. Δ: '+delta+'. tol: '+tol+'.' );
-			}
+		if ( y === expected[i] ) {
+			t.strictEqual( y, expected[i], 'sigma: '+sigma[i] );
+		} else {
+			t.ok( delta <= tol, 'within tolerance. σ: '+sigma[i]+'. y: '+y+'. E: '+expected[ i ]+'. Δ: '+delta+'. tol: '+tol+'.' );
 		}
 	}
 	t.end();
diff --git a/lib/node_modules/@stdlib/stats/base/dists/halfnormal/mean/test/test.native.js b/lib/node_modules/@stdlib/stats/base/dists/halfnormal/mean/test/test.native.js
@@ -82,13 +82,10 @@ tape( 'the function returns the expected value of a half-normal distribution', o
 		y = mean( sigma[i] );
 		delta = abs( y - expected[i] );
 		tol = 1.0 * EPS * abs( expected[i] );
-
-		if ( expected[i] !== null ) {
-			if ( y === expected[i] || delta <= tol ) {
-				t.strictEqual( y, expected[i], 'sigma: '+sigma[i] );
-			} else {
-				t.ok( delta <= tol, 'within tolerance. σ: '+sigma[i]+'. y: '+y+'. E: '+expected[ i ]+'. Δ: '+delta+'. tol: '+tol+'.' );
-			}
+		if ( y === expected[i] ) {
+			t.strictEqual( y, expected[i], 'sigma: '+sigma[i] );
+		} else {
+			t.ok( delta <= tol, 'within tolerance. σ: '+sigma[i]+'. y: '+y+'. E: '+expected[ i ]+'. Δ: '+delta+'. tol: '+tol+'.' );
 		}
 	}
 	t.end();
diff --git a/lib/node_modules/@stdlib/stats/base/dists/halfnormal/stdev/test/fixtures/julia/runner.jl b/lib/node_modules/@stdlib/stats/base/dists/halfnormal/stdev/test/fixtures/julia/runner.jl
@@ -36,33 +36,34 @@ julia> sigma = rand( 1000 );
 julia> gen( sigma, \"data.json\" );
 ```
 """
-# Get the filename:
-file = @__FILE__
-
-# Extract the directory in which this file resides:
-dir = dirname(file)
-
 function gen( sigma, name )
 	z = Array{Float64}( undef, length(sigma) )
 	for i in eachindex(sigma)
 		z[i] = sqrt( var( HalfNormal( sigma[i] ) ) )
 	end
+
 	# Store data to be written to file as a collection:
 	data = Dict([
 		("sigma", sigma),
 		("expected", z)
 	]);
 
 	# Based on the script directory, create an output filepath:
-	filepath = joinpath(dir, name)
+	filepath = joinpath( dir, name )
 
 	# Write the data to the output filepath as JSON:
-	open(filepath, "w") do outfile
-		write(outfile, JSON.json(data))
-		write(outfile, "\n")
-	end
+	outfile = open( filepath, "w" );
+	write( outfile, JSON.json(data) );
+	write( outfile, "\n" );
+	close( outfile );
 end
 
+# Get the filename:
+file = @__FILE__;
+
+# Extract the directory in which this file resides:
+dir = dirname( file );
+
 # Generate fixtures:
-sigma = ( rand(50) .* 20.0 ) .+ 2.0
-gen(sigma, "data.json")
+sigma = ( rand(50) .* 20.0 ) .+ 2.0;
+gen( sigma, "data.json" );

Original file line number	Diff line number	Diff line change
`@@ -30,11 +30,11 @@`
`30`	`30`	`*`
`31`	`31`	`* @example`
`32`	`32`	`* var y = mean( 1.0 );`
`33`		`-* // returns ~0.7978845608`
	`33`	`+* // returns ~0.79788`
`34`	`34`	`*`
`35`	`35`	`* @example`
`36`	`36`	`* var y = mean( 5.0 );`
`37`		`-* // returns ~3.989422804`
	`37`	`+* // returns ~3.98942`
`38`	`38`	`*`
`39`	`39`	`* @example`
`40`	`40`	`* var y = mean( NaN );`
Original file line number	Diff line number	Diff line change
`@@ -38,7 +38,7 @@ var addon = require( './../src/addon.node' );`
`38`	`38`	`*`
`39`	`39`	`* @example`
`40`	`40`	`* var y = mean( 4.0 );`
`41`		`-* // returns ~3.1915382432114616`
	`41`	`+* // returns ~3.192`
`42`	`42`	`*`
`43`	`43`	`* @example`
`44`	`44`	`* var y = mean( NaN );`
Original file line number	Diff line number	Diff line change
`@@ -21,6 +21,8 @@`
`21`	`21`	`#include "stdlib/math/base/special/sqrt.h"`
`22`	`22`	`#include "stdlib/constants/float64/pi.h"`
`23`	`23`
	`24`	`+static const double SQRT_TWO_OVER_PI = stdlib_base_sqrt( 2.0 / STDLIB_CONSTANT_FLOAT64_PI );`
	`25`	`+`
`24`	`26`	`/**`
`25`	`27`	* Returns the expected value for a half-normal distribution with scale parameter `sigma`.
`26`	`28`	`*`
`@@ -35,5 +37,5 @@ double stdlib_base_dists_halfnormal_mean( const double sigma ) {`
`35`	`37`	`if ( stdlib_base_is_nan( sigma ) \|\| sigma <= 0.0 ) {`
`36`	`38`	`return 0.0 / 0.0; // NaN`
`37`	`39`	`}`
`38`		`- return sigma * stdlib_base_sqrt( 2.0 / STDLIB_CONSTANT_FLOAT64_PI );`
	`40`	`+ return sigma * SQRT_TWO_OVER_PI;`
`39`	`41`	`}`