diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/dminabs/README.md b/lib/node_modules/@stdlib/stats/base/ndarray/dminabs/README.md
new file mode 100644
index 000000000000..96f7da6d7b80
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/base/ndarray/dminabs/README.md
@@ -0,0 +1,112 @@
+
+
+# dminabs
+
+> Compute the minimum absolute value of a one-dimensional double-precision floating-point ndarray.
+
+
+
+
+
+
+
+## Usage
+
+```javascript
+var dminabs = require( '@stdlib/stats/base/ndarray/dminabs' );
+```
+
+#### dminabs( arrays )
+
+Computes the minimum absolute value of a one-dimensional double-precision floating-point ndarray.
+
+```javascript
+var Float64Array = require( '@stdlib/array/float64' );
+var ndarray = require( '@stdlib/ndarray/base/ctor' );
+
+var xbuf = new Float64Array( [ -1.0, 3.0, -4.0, 2.0 ] );
+var x = new ndarray( 'float64', xbuf, [ 4 ], [ 1 ], 0, 'row-major' );
+
+var v = dminabs( [ x ] );
+// returns 1.0
+```
+
+The function has the following parameters:
+
+- **arrays**: array-like object containing a one-dimensional input ndarray.
+
+
+
+
+
+
+
+## Notes
+
+- If provided an empty one-dimensional ndarray, the function returns `NaN`.
+
+
+
+
+
+
+
+## Examples
+
+
+
+```javascript
+var discreteUniform = require( '@stdlib/random/array/discrete-uniform' );
+var ndarray = require( '@stdlib/ndarray/base/ctor' );
+var ndarray2array = require( '@stdlib/ndarray/to-array' );
+var dminabs = require( '@stdlib/stats/base/ndarray/dminabs' );
+
+var xbuf = discreteUniform( 10, -50, 50, {
+ 'dtype': 'float64'
+});
+var x = new ndarray( 'float64', xbuf, [ xbuf.length ], [ 1 ], 0, 'row-major' );
+console.log( ndarray2array( x ) );
+
+var v = dminabs( [ x ] );
+console.log( v );
+```
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/dminabs/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/base/ndarray/dminabs/benchmark/benchmark.js
new file mode 100644
index 000000000000..78eeb79d4c8b
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/base/ndarray/dminabs/benchmark/benchmark.js
@@ -0,0 +1,102 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+* http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+'use strict';
+
+// MODULES //
+
+var bench = require( '@stdlib/bench' );
+var uniform = require( '@stdlib/random/array/uniform' );
+var isnan = require( '@stdlib/math/base/assert/is-nan' );
+var pow = require( '@stdlib/math/base/special/pow' );
+var ndarray = require( '@stdlib/ndarray/base/ctor' );
+var pkg = require( './../package.json' ).name;
+var dminabs = require( './../lib' );
+
+
+// VARIABLES //
+
+var options = {
+ 'dtype': 'float64'
+};
+
+
+// FUNCTIONS //
+
+/**
+* Creates a benchmark function.
+*
+* @private
+* @param {PositiveInteger} len - array length
+* @returns {Function} benchmark function
+*/
+function createBenchmark( len ) {
+ var xbuf;
+ var x;
+
+ xbuf = uniform( len, -10.0, 10.0, options );
+ x = new ndarray( options.dtype, xbuf, [ len ], [ 1 ], 0, 'row-major' );
+
+ return benchmark;
+
+ function benchmark( b ) {
+ var v;
+ var i;
+
+ b.tic();
+ for ( i = 0; i < b.iterations; i++ ) {
+ v = dminabs( [ x ] );
+ if ( isnan( v ) ) {
+ b.fail( 'should not return NaN' );
+ }
+ }
+ b.toc();
+ if ( isnan( v ) ) {
+ b.fail( 'should not return NaN' );
+ }
+ b.pass( 'benchmark finished' );
+ b.end();
+ }
+}
+
+
+// MAIN //
+
+/**
+* Main execution sequence.
+*
+* @private
+*/
+function main() {
+ var len;
+ var min;
+ var max;
+ var f;
+ var i;
+
+ min = 1; // 10^min
+ max = 6; // 10^max
+
+ for ( i = min; i <= max; i++ ) {
+ len = pow( 10, i );
+ f = createBenchmark( len );
+ bench( pkg+':len='+len, f );
+ }
+}
+
+main();
diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/dminabs/docs/repl.txt b/lib/node_modules/@stdlib/stats/base/ndarray/dminabs/docs/repl.txt
new file mode 100644
index 000000000000..c364711e5005
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/base/ndarray/dminabs/docs/repl.txt
@@ -0,0 +1,32 @@
+
+{{alias}}( arrays )
+ Computes the minimum absolute value of a one-dimensional double-precision
+ floating-point ndarray.
+
+ If provided an empty ndarray, the function returns `NaN`.
+
+ Parameters
+ ----------
+ arrays: ArrayLikeObject
+ Array-like object containing a one-dimensional input ndarray.
+
+ Returns
+ -------
+ out: number
+ Minimum absolute value.
+
+ Examples
+ --------
+ > var xbuf = new {{alias:@stdlib/array/float64}}( [ 1.0, -2.0, 2.0 ] );
+ > var dt = 'float64';
+ > var sh = [ xbuf.length ];
+ > var sx = [ 1 ];
+ > var ox = 0;
+ > var ord = 'row-major';
+ > var x = new {{alias:@stdlib/ndarray/ctor}}( dt, xbuf, sh, sx, ox, ord );
+ > {{alias}}( [ x ] )
+ 1.0
+
+ See Also
+ --------
+
diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/dminabs/docs/types/index.d.ts b/lib/node_modules/@stdlib/stats/base/ndarray/dminabs/docs/types/index.d.ts
new file mode 100644
index 000000000000..5240aad01ac7
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/base/ndarray/dminabs/docs/types/index.d.ts
@@ -0,0 +1,46 @@
+/*
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+* http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+// TypeScript Version: 4.1
+
+/// } arrays - array-like object containing an input ndarray
+* @returns {number} minimum absolute value
+*
+* @example
+* var Float64Array = require( '@stdlib/array/float64' );
+* var ndarray = require( '@stdlib/ndarray/base/ctor' );
+*
+* var xbuf = new Float64Array( [ -1.0, 3.0, -4.0, 2.0 ] );
+* var x = new ndarray( 'float64', xbuf, [ 4 ], [ 1 ], 0, 'row-major' );
+*
+* var v = dminabs( [ x ] );
+* // returns 1.0
+*/
+function dminabs( arrays ) {
+ var x = arrays[ 0 ];
+ return strided( numelDimension( x, 0 ), getData( x ), getStride( x, 0 ), getOffset( x ) ); // eslint-disable-line max-len
+}
+
+
+// EXPORTS //
+
+module.exports = dminabs;
diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/dminabs/package.json b/lib/node_modules/@stdlib/stats/base/ndarray/dminabs/package.json
new file mode 100644
index 000000000000..c802fa073e44
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/base/ndarray/dminabs/package.json
@@ -0,0 +1,69 @@
+{
+ "name": "@stdlib/stats/base/ndarray/dminabs",
+ "version": "0.0.0",
+ "description": "Compute the minimum absolute value of a one-dimensional double-precision floating-point ndarray.",
+ "license": "Apache-2.0",
+ "author": {
+ "name": "The Stdlib Authors",
+ "url": "https://github.com/stdlib-js/stdlib/graphs/contributors"
+ },
+ "contributors": [
+ {
+ "name": "The Stdlib Authors",
+ "url": "https://github.com/stdlib-js/stdlib/graphs/contributors"
+ }
+ ],
+ "main": "./lib",
+ "directories": {
+ "benchmark": "./benchmark",
+ "doc": "./docs",
+ "example": "./examples",
+ "lib": "./lib",
+ "test": "./test"
+ },
+ "types": "./docs/types",
+ "scripts": {},
+ "homepage": "https://github.com/stdlib-js/stdlib",
+ "repository": {
+ "type": "git",
+ "url": "git://github.com/stdlib-js/stdlib.git"
+ },
+ "bugs": {
+ "url": "https://github.com/stdlib-js/stdlib/issues"
+ },
+ "dependencies": {},
+ "devDependencies": {},
+ "engines": {
+ "node": ">=0.10.0",
+ "npm": ">2.7.0"
+ },
+ "os": [
+ "aix",
+ "darwin",
+ "freebsd",
+ "linux",
+ "macos",
+ "openbsd",
+ "sunos",
+ "win32",
+ "windows"
+ ],
+ "keywords": [
+ "stdlib",
+ "stdmath",
+ "statistics",
+ "stats",
+ "mathematics",
+ "math",
+ "minimum",
+ "min",
+ "absolute",
+ "abs",
+ "range",
+ "extremes",
+ "domain",
+ "extent",
+ "ndarray"
+ ],
+ "__stdlib__": {}
+}
diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/dminabs/test/test.js b/lib/node_modules/@stdlib/stats/base/ndarray/dminabs/test/test.js
new file mode 100644
index 000000000000..1804ae456f5c
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/base/ndarray/dminabs/test/test.js
@@ -0,0 +1,173 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+* http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+'use strict';
+
+// MODULES //
+
+var tape = require( 'tape' );
+var isnan = require( '@stdlib/math/base/assert/is-nan' );
+var isPositiveZero = require( '@stdlib/math/base/assert/is-positive-zero' );
+var Float64Array = require( '@stdlib/array/float64' );
+var ndarray = require( '@stdlib/ndarray/base/ctor' );
+var dminabs = require( './../lib' );
+
+
+// FUNCTIONS //
+
+/**
+* Returns a one-dimensional ndarray.
+*
+* @private
+* @param {Collection} buffer - underlying data buffer
+* @param {NonNegativeInteger} length - number of indexed elements
+* @param {integer} stride - stride length
+* @param {NonNegativeInteger} offset - index offset
+* @returns {ndarray} one-dimensional ndarray
+*/
+function vector( buffer, length, stride, offset ) {
+ return new ndarray( 'float64', buffer, [ length ], [ stride ], offset, 'row-major' );
+}
+
+
+// TESTS //
+
+tape( 'main export is a function', function test( t ) {
+ t.ok( true, __filename );
+ t.strictEqual( typeof dminabs, 'function', 'main export is a function' );
+ t.end();
+});
+
+tape( 'the function has an arity of 1', function test( t ) {
+ t.strictEqual( dminabs.length, 1, 'has expected arity' );
+ t.end();
+});
+
+tape( 'the function calculates the minimum absolute value of a one-dimensional ndarray', function test( t ) {
+ var x;
+ var v;
+
+ x = new Float64Array( [ 1.0, -2.0, -4.0, 5.0, 0.0, 3.0 ] );
+ v = dminabs( [ vector( x, 6, 1, 0 ) ] );
+ t.strictEqual( v, 0.0, 'returns expected value' );
+
+ x = new Float64Array( [ -4.0, -5.0 ] );
+ v = dminabs( [ vector( x, 2, 1, 0 ) ] );
+ t.strictEqual( v, 4.0, 'returns expected value' );
+
+ x = new Float64Array( [ -0.0, 0.0, -0.0 ] );
+ v = dminabs( [ vector( x, 3, 1, 0 ) ] );
+ t.strictEqual( isPositiveZero( v ), true, 'returns expected value' );
+
+ x = new Float64Array( [ NaN ] );
+ v = dminabs( [ vector( x, 1, 1, 0 ) ] );
+ t.strictEqual( isnan( v ), true, 'returns expected value' );
+
+ x = new Float64Array( [ NaN, NaN ] );
+ v = dminabs( [ vector( x, 2, 1, 0 ) ] );
+ t.strictEqual( isnan( v ), true, 'returns expected value' );
+
+ t.end();
+});
+
+tape( 'if provided an empty vector, the function returns `NaN`', function test( t ) {
+ var x;
+ var v;
+
+ x = new Float64Array( [] );
+
+ v = dminabs( [ vector( x, 0, 1, 0 ) ] );
+ t.strictEqual( isnan( v ), true, 'returns expected value' );
+
+ t.end();
+});
+
+tape( 'if provided a vector containing a single element, the function returns that element', function test( t ) {
+ var x;
+ var v;
+
+ x = new Float64Array( [ 1.0 ] );
+
+ v = dminabs( [ vector( x, 1, 1, 0 ) ] );
+ t.strictEqual( v, 1.0, 'returns expected value' );
+
+ t.end();
+});
+
+tape( 'the function supports one-dimensional ndarrays having non-unit strides', function test( t ) {
+ var x;
+ var v;
+
+ x = new Float64Array([
+ 1.0, // 0
+ 2.0,
+ 2.0, // 1
+ -7.0,
+ -2.0, // 2
+ 3.0,
+ 4.0, // 3
+ 2.0
+ ]);
+
+ v = dminabs( [ vector( x, 4, 2, 0 ) ] );
+
+ t.strictEqual( v, 1.0, 'returns expected value' );
+ t.end();
+});
+
+tape( 'the function supports one-dimensional ndarrays having negative strides', function test( t ) {
+ var x;
+ var v;
+
+ x = new Float64Array([
+ 1.0, // 3
+ 2.0,
+ 2.0, // 2
+ -7.0,
+ -2.0, // 1
+ 3.0,
+ 4.0, // 0
+ 2.0
+ ]);
+
+ v = dminabs( [ vector( x, 4, -2, 6 ) ] );
+
+ t.strictEqual( v, 1.0, 'returns expected value' );
+ t.end();
+});
+
+tape( 'the function supports one-dimensional ndarrays having non-zero offsets', function test( t ) {
+ var x;
+ var v;
+
+ x = new Float64Array([
+ 2.0,
+ 1.0, // 0
+ 2.0,
+ -2.0, // 1
+ -2.0,
+ 2.0, // 2
+ 3.0,
+ 4.0 // 3
+ ]);
+
+ v = dminabs( [ vector( x, 4, 2, 1 ) ] );
+ t.strictEqual( v, 1.0, 'returns expected value' );
+
+ t.end();
+});
diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/minabs/README.md b/lib/node_modules/@stdlib/stats/base/ndarray/minabs/README.md
new file mode 100644
index 000000000000..49c27d33b254
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/base/ndarray/minabs/README.md
@@ -0,0 +1,111 @@
+
+
+# minabs
+
+> Compute the minimum absolute value of a one-dimensional ndarray.
+
+
+
+
+
+
+
+## Usage
+
+```javascript
+var minabs = require( '@stdlib/stats/base/ndarray/minabs' );
+```
+
+#### minabs( arrays )
+
+Computes the minimum absolute value of a one-dimensional ndarray.
+
+```javascript
+var ndarray = require( '@stdlib/ndarray/base/ctor' );
+
+var xbuf = [ -1.0, 3.0, -4.0, 2.0 ];
+var x = new ndarray( 'generic', xbuf, [ 4 ], [ 1 ], 0, 'row-major' );
+
+var v = minabs( [ x ] );
+// returns 1.0
+```
+
+The function has the following parameters:
+
+- **arrays**: array-like object containing a one-dimensional input ndarray.
+
+
+
+
+
+
+
+## Notes
+
+- If provided an empty one-dimensional ndarray, the function returns `NaN`.
+
+
+
+
+
+
+
+## Examples
+
+
+
+```javascript
+var discreteUniform = require( '@stdlib/random/array/discrete-uniform' );
+var ndarray = require( '@stdlib/ndarray/base/ctor' );
+var ndarray2array = require( '@stdlib/ndarray/to-array' );
+var minabs = require( '@stdlib/stats/base/ndarray/minabs' );
+
+var xbuf = discreteUniform( 10, -50, 50, {
+ 'dtype': 'generic'
+});
+var x = new ndarray( 'generic', xbuf, [ xbuf.length ], [ 1 ], 0, 'row-major' );
+console.log( ndarray2array( x ) );
+
+var v = minabs( [ x ] );
+console.log( v );
+```
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/minabs/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/base/ndarray/minabs/benchmark/benchmark.js
new file mode 100644
index 000000000000..5076d7ba30ce
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/base/ndarray/minabs/benchmark/benchmark.js
@@ -0,0 +1,102 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+* http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+'use strict';
+
+// MODULES //
+
+var bench = require( '@stdlib/bench' );
+var uniform = require( '@stdlib/random/array/uniform' );
+var isnan = require( '@stdlib/math/base/assert/is-nan' );
+var pow = require( '@stdlib/math/base/special/pow' );
+var ndarray = require( '@stdlib/ndarray/base/ctor' );
+var pkg = require( './../package.json' ).name;
+var minabs = require( './../lib' );
+
+
+// VARIABLES //
+
+var options = {
+ 'dtype': 'generic'
+};
+
+
+// FUNCTIONS //
+
+/**
+* Creates a benchmark function.
+*
+* @private
+* @param {PositiveInteger} len - array length
+* @returns {Function} benchmark function
+*/
+function createBenchmark( len ) {
+ var xbuf;
+ var x;
+
+ xbuf = uniform( len, -10.0, 10.0, options );
+ x = new ndarray( options.dtype, xbuf, [ len ], [ 1 ], 0, 'row-major' );
+
+ return benchmark;
+
+ function benchmark( b ) {
+ var v;
+ var i;
+
+ b.tic();
+ for ( i = 0; i < b.iterations; i++ ) {
+ v = minabs( [ x ] );
+ if ( isnan( v ) ) {
+ b.fail( 'should not return NaN' );
+ }
+ }
+ b.toc();
+ if ( isnan( v ) ) {
+ b.fail( 'should not return NaN' );
+ }
+ b.pass( 'benchmark finished' );
+ b.end();
+ }
+}
+
+
+// MAIN //
+
+/**
+* Main execution sequence.
+*
+* @private
+*/
+function main() {
+ var len;
+ var min;
+ var max;
+ var f;
+ var i;
+
+ min = 1; // 10^min
+ max = 6; // 10^max
+
+ for ( i = min; i <= max; i++ ) {
+ len = pow( 10, i );
+ f = createBenchmark( len );
+ bench( pkg+':len='+len, f );
+ }
+}
+
+main();
diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/minabs/docs/repl.txt b/lib/node_modules/@stdlib/stats/base/ndarray/minabs/docs/repl.txt
new file mode 100644
index 000000000000..5c8551bd2682
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/base/ndarray/minabs/docs/repl.txt
@@ -0,0 +1,31 @@
+
+{{alias}}( arrays )
+ Computes the minimum absolute value of a one-dimensional ndarray.
+
+ If provided an empty ndarray, the function returns `NaN`.
+
+ Parameters
+ ----------
+ arrays: ArrayLikeObject
+ Array-like object containing a one-dimensional input ndarray.
+
+ Returns
+ -------
+ out: number
+ Minimum absolute value.
+
+ Examples
+ --------
+ > var xbuf = [ 1.0, -2.0, 2.0 ];
+ > var dt = 'generic';
+ > var sh = [ xbuf.length ];
+ > var sx = [ 1 ];
+ > var ox = 0;
+ > var ord = 'row-major';
+ > var x = new {{alias:@stdlib/ndarray/ctor}}( dt, xbuf, sh, sx, ox, ord );
+ > {{alias}}( [ x ] )
+ 1.0
+
+ See Also
+ --------
+
diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/minabs/docs/types/index.d.ts b/lib/node_modules/@stdlib/stats/base/ndarray/minabs/docs/types/index.d.ts
new file mode 100644
index 000000000000..f7fb60549e77
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/base/ndarray/minabs/docs/types/index.d.ts
@@ -0,0 +1,45 @@
+/*
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+* http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+// TypeScript Version: 4.1
+
+/// ( arrays: [ T ] ): number;
+
+
+// EXPORTS //
+
+export = minabs;
diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/minabs/docs/types/test.ts b/lib/node_modules/@stdlib/stats/base/ndarray/minabs/docs/types/test.ts
new file mode 100644
index 000000000000..21964be6636d
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/base/ndarray/minabs/docs/types/test.ts
@@ -0,0 +1,57 @@
+/*
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+* http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+/* eslint-disable space-in-parens */
+
+import zeros = require( '@stdlib/ndarray/zeros' );
+import minabs = require( './index' );
+
+
+// TESTS //
+
+// The function returns a number...
+{
+ const x = zeros( [ 10 ], {
+ 'dtype': 'generic'
+ });
+
+ minabs( [ x ] ); // $ExpectType number
+}
+
+// The compiler throws an error if the function is provided a first argument which is not an array of ndarrays...
+{
+ minabs( '10' ); // $ExpectError
+ minabs( 10 ); // $ExpectError
+ minabs( true ); // $ExpectError
+ minabs( false ); // $ExpectError
+ minabs( null ); // $ExpectError
+ minabs( undefined ); // $ExpectError
+ minabs( [] ); // $ExpectError
+ minabs( {} ); // $ExpectError
+ minabs( ( x: number ): number => x ); // $ExpectError
+}
+
+// The compiler throws an error if the function is provided an unsupported number of arguments...
+{
+ const x = zeros( [ 10 ], {
+ 'dtype': 'generic'
+ });
+
+ minabs(); // $ExpectError
+ minabs( [ x ], {} ); // $ExpectError
+}
diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/minabs/examples/index.js b/lib/node_modules/@stdlib/stats/base/ndarray/minabs/examples/index.js
new file mode 100644
index 000000000000..b39e9ebe864b
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/base/ndarray/minabs/examples/index.js
@@ -0,0 +1,33 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+* http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+'use strict';
+
+var discreteUniform = require( '@stdlib/random/array/discrete-uniform' );
+var ndarray = require( '@stdlib/ndarray/base/ctor' );
+var ndarray2array = require( '@stdlib/ndarray/to-array' );
+var minabs = require( './../lib' );
+
+var xbuf = discreteUniform( 10, -50, 50, {
+ 'dtype': 'generic'
+});
+var x = new ndarray( 'generic', xbuf, [ xbuf.length ], [ 1 ], 0, 'row-major' );
+console.log( ndarray2array( x ) );
+
+var v = minabs( [ x ] );
+console.log( v );
diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/minabs/lib/index.js b/lib/node_modules/@stdlib/stats/base/ndarray/minabs/lib/index.js
new file mode 100644
index 000000000000..0fa9243ad026
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/base/ndarray/minabs/lib/index.js
@@ -0,0 +1,44 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+* http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+'use strict';
+
+/**
+* Compute the minimum absolute value of a one-dimensional ndarray.
+*
+* @module @stdlib/stats/base/ndarray/minabs
+*
+* @example
+* var ndarray = require( '@stdlib/ndarray/base/ctor' );
+* var minabs = require( '@stdlib/stats/base/ndarray/minabs' );
+*
+* var xbuf = [ -1.0, 3.0, -4.0, 2.0 ];
+* var x = new ndarray( 'generic', xbuf, [ 4 ], [ 1 ], 0, 'row-major' );
+*
+* var v = minabs( [ x ] );
+* // returns 1.0
+*/
+
+// MODULES //
+
+var main = require( './main.js' );
+
+
+// EXPORTS //
+
+module.exports = main;
diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/minabs/lib/main.js b/lib/node_modules/@stdlib/stats/base/ndarray/minabs/lib/main.js
new file mode 100644
index 000000000000..e069e5784029
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/base/ndarray/minabs/lib/main.js
@@ -0,0 +1,55 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+* http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+'use strict';
+
+// MODULES //
+
+var numelDimension = require( '@stdlib/ndarray/base/numel-dimension' );
+var getStride = require( '@stdlib/ndarray/base/stride' );
+var getOffset = require( '@stdlib/ndarray/base/offset' );
+var getData = require( '@stdlib/ndarray/base/data-buffer' );
+var strided = require( '@stdlib/stats/strided/minabs' ).ndarray;
+
+
+// MAIN //
+
+/**
+* Computes the minimum absolute value of a one-dimensional ndarray.
+*
+* @param {ArrayLikeObject} arrays - array-like object containing an input ndarray
+* @returns {number} minimum absolute value
+*
+* @example
+* var ndarray = require( '@stdlib/ndarray/base/ctor' );
+*
+* var xbuf = [ -1.0, 3.0, -4.0, 2.0 ];
+* var x = new ndarray( 'generic', xbuf, [ 4 ], [ 1 ], 0, 'row-major' );
+*
+* var v = minabs( [ x ] );
+* // returns 1.0
+*/
+function minabs( arrays ) {
+ var x = arrays[ 0 ];
+ return strided( numelDimension( x, 0 ), getData( x ), getStride( x, 0 ), getOffset( x ) ); // eslint-disable-line max-len
+}
+
+
+// EXPORTS //
+
+module.exports = minabs;
diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/minabs/package.json b/lib/node_modules/@stdlib/stats/base/ndarray/minabs/package.json
new file mode 100644
index 000000000000..df3121aca601
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/base/ndarray/minabs/package.json
@@ -0,0 +1,69 @@
+{
+ "name": "@stdlib/stats/base/ndarray/minabs",
+ "version": "0.0.0",
+ "description": "Compute the minimum absolute value of a one-dimensional ndarray.",
+ "license": "Apache-2.0",
+ "author": {
+ "name": "The Stdlib Authors",
+ "url": "https://github.com/stdlib-js/stdlib/graphs/contributors"
+ },
+ "contributors": [
+ {
+ "name": "The Stdlib Authors",
+ "url": "https://github.com/stdlib-js/stdlib/graphs/contributors"
+ }
+ ],
+ "main": "./lib",
+ "directories": {
+ "benchmark": "./benchmark",
+ "doc": "./docs",
+ "example": "./examples",
+ "lib": "./lib",
+ "test": "./test"
+ },
+ "types": "./docs/types",
+ "scripts": {},
+ "homepage": "https://github.com/stdlib-js/stdlib",
+ "repository": {
+ "type": "git",
+ "url": "git://github.com/stdlib-js/stdlib.git"
+ },
+ "bugs": {
+ "url": "https://github.com/stdlib-js/stdlib/issues"
+ },
+ "dependencies": {},
+ "devDependencies": {},
+ "engines": {
+ "node": ">=0.10.0",
+ "npm": ">2.7.0"
+ },
+ "os": [
+ "aix",
+ "darwin",
+ "freebsd",
+ "linux",
+ "macos",
+ "openbsd",
+ "sunos",
+ "win32",
+ "windows"
+ ],
+ "keywords": [
+ "stdlib",
+ "stdmath",
+ "statistics",
+ "stats",
+ "mathematics",
+ "math",
+ "minimum",
+ "min",
+ "absolute",
+ "abs",
+ "range",
+ "extremes",
+ "domain",
+ "extent",
+ "ndarray"
+ ],
+ "__stdlib__": {}
+}
diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/minabs/test/test.js b/lib/node_modules/@stdlib/stats/base/ndarray/minabs/test/test.js
new file mode 100644
index 000000000000..9592cb39dedb
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/base/ndarray/minabs/test/test.js
@@ -0,0 +1,172 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+* http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+'use strict';
+
+// MODULES //
+
+var tape = require( 'tape' );
+var isnan = require( '@stdlib/math/base/assert/is-nan' );
+var isPositiveZero = require( '@stdlib/math/base/assert/is-positive-zero' );
+var ndarray = require( '@stdlib/ndarray/base/ctor' );
+var minabs = require( './../lib' );
+
+
+// FUNCTIONS //
+
+/**
+* Returns a one-dimensional ndarray.
+*
+* @private
+* @param {Collection} buffer - underlying data buffer
+* @param {NonNegativeInteger} length - number of indexed elements
+* @param {integer} stride - stride length
+* @param {NonNegativeInteger} offset - index offset
+* @returns {ndarray} one-dimensional ndarray
+*/
+function vector( buffer, length, stride, offset ) {
+ return new ndarray( 'generic', buffer, [ length ], [ stride ], offset, 'row-major' );
+}
+
+
+// TESTS //
+
+tape( 'main export is a function', function test( t ) {
+ t.ok( true, __filename );
+ t.strictEqual( typeof minabs, 'function', 'main export is a function' );
+ t.end();
+});
+
+tape( 'the function has an arity of 1', function test( t ) {
+ t.strictEqual( minabs.length, 1, 'has expected arity' );
+ t.end();
+});
+
+tape( 'the function calculates the minimum absolute value of a one-dimensional ndarray', function test( t ) {
+ var x;
+ var v;
+
+ x = [ 1.0, -2.0, -4.0, 5.0, 0.0, 3.0 ];
+ v = minabs( [ vector( x, 6, 1, 0 ) ] );
+ t.strictEqual( v, 0.0, 'returns expected value' );
+
+ x = [ -4.0, -5.0 ];
+ v = minabs( [ vector( x, 2, 1, 0 ) ] );
+ t.strictEqual( v, 4.0, 'returns expected value' );
+
+ x = [ -0.0, 0.0, -0.0 ];
+ v = minabs( [ vector( x, 3, 1, 0 ) ] );
+ t.strictEqual( isPositiveZero( v ), true, 'returns expected value' );
+
+ x = [ NaN ];
+ v = minabs( [ vector( x, 1, 1, 0 ) ] );
+ t.strictEqual( isnan( v ), true, 'returns expected value' );
+
+ x = [ NaN, NaN ];
+ v = minabs( [ vector( x, 2, 1, 0 ) ] );
+ t.strictEqual( isnan( v ), true, 'returns expected value' );
+
+ t.end();
+});
+
+tape( 'if provided an empty vector, the function returns `NaN`', function test( t ) {
+ var x;
+ var v;
+
+ x = [];
+
+ v = minabs( [ vector( x, 0, 1, 0 ) ] );
+ t.strictEqual( isnan( v ), true, 'returns expected value' );
+
+ t.end();
+});
+
+tape( 'if provided a vector containing a single element, the function returns that element', function test( t ) {
+ var x;
+ var v;
+
+ x = [ 1.0 ];
+
+ v = minabs( [ vector( x, 1, 1, 0 ) ] );
+ t.strictEqual( v, 1.0, 'returns expected value' );
+
+ t.end();
+});
+
+tape( 'the function supports one-dimensional ndarrays having non-unit strides', function test( t ) {
+ var x;
+ var v;
+
+ x = [
+ 1.0, // 0
+ 2.0,
+ 2.0, // 1
+ -7.0,
+ -2.0, // 2
+ 3.0,
+ 4.0, // 3
+ 2.0
+ ];
+
+ v = minabs( [ vector( x, 4, 2, 0 ) ] );
+
+ t.strictEqual( v, 1.0, 'returns expected value' );
+ t.end();
+});
+
+tape( 'the function supports one-dimensional ndarrays having negative strides', function test( t ) {
+ var x;
+ var v;
+
+ x = [
+ 1.0, // 3
+ 2.0,
+ 2.0, // 2
+ -7.0,
+ -2.0, // 1
+ 3.0,
+ 4.0, // 0
+ 2.0
+ ];
+
+ v = minabs( [ vector( x, 4, -2, 6 ) ] );
+
+ t.strictEqual( v, 1.0, 'returns expected value' );
+ t.end();
+});
+
+tape( 'the function supports one-dimensional ndarrays having non-zero offsets', function test( t ) {
+ var x;
+ var v;
+
+ x = [
+ 2.0,
+ 1.0, // 0
+ 2.0,
+ -2.0, // 1
+ -2.0,
+ 2.0, // 2
+ 3.0,
+ 4.0 // 3
+ ];
+
+ v = minabs( [ vector( x, 4, 2, 1 ) ] );
+ t.strictEqual( v, 1.0, 'returns expected value' );
+
+ t.end();
+});
diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/sminabs/README.md b/lib/node_modules/@stdlib/stats/base/ndarray/sminabs/README.md
new file mode 100644
index 000000000000..1bc1a625aabb
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/base/ndarray/sminabs/README.md
@@ -0,0 +1,112 @@
+
+
+# sminabs
+
+> Compute the minimum absolute value of a one-dimensional single-precision floating-point ndarray.
+
+
+
+
+
+
+
+## Usage
+
+```javascript
+var sminabs = require( '@stdlib/stats/base/ndarray/sminabs' );
+```
+
+#### sminabs( arrays )
+
+Computes the minimum absolute value of a one-dimensional single-precision floating-point ndarray.
+
+```javascript
+var Float32Array = require( '@stdlib/array/float32' );
+var ndarray = require( '@stdlib/ndarray/base/ctor' );
+
+var xbuf = new Float32Array( [ -1.0, 3.0, -4.0, 2.0 ] );
+var x = new ndarray( 'float32', xbuf, [ 4 ], [ 1 ], 0, 'row-major' );
+
+var v = sminabs( [ x ] );
+// returns 1.0
+```
+
+The function has the following parameters:
+
+- **arrays**: array-like object containing a one-dimensional input ndarray.
+
+
+
+
+
+
+
+## Notes
+
+- If provided an empty one-dimensional ndarray, the function returns `NaN`.
+
+
+
+
+
+
+
+## Examples
+
+
+
+```javascript
+var discreteUniform = require( '@stdlib/random/array/discrete-uniform' );
+var ndarray = require( '@stdlib/ndarray/base/ctor' );
+var ndarray2array = require( '@stdlib/ndarray/to-array' );
+var sminabs = require( '@stdlib/stats/base/ndarray/sminabs' );
+
+var xbuf = discreteUniform( 10, -50, 50, {
+ 'dtype': 'float32'
+});
+var x = new ndarray( 'float32', xbuf, [ xbuf.length ], [ 1 ], 0, 'row-major' );
+console.log( ndarray2array( x ) );
+
+var v = sminabs( [ x ] );
+console.log( v );
+```
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/sminabs/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/base/ndarray/sminabs/benchmark/benchmark.js
new file mode 100644
index 000000000000..b0b4e4c556cb
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/base/ndarray/sminabs/benchmark/benchmark.js
@@ -0,0 +1,102 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+* http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+'use strict';
+
+// MODULES //
+
+var bench = require( '@stdlib/bench' );
+var uniform = require( '@stdlib/random/array/uniform' );
+var isnan = require( '@stdlib/math/base/assert/is-nan' );
+var pow = require( '@stdlib/math/base/special/pow' );
+var ndarray = require( '@stdlib/ndarray/base/ctor' );
+var pkg = require( './../package.json' ).name;
+var sminabs = require( './../lib' );
+
+
+// VARIABLES //
+
+var options = {
+ 'dtype': 'float32'
+};
+
+
+// FUNCTIONS //
+
+/**
+* Creates a benchmark function.
+*
+* @private
+* @param {PositiveInteger} len - array length
+* @returns {Function} benchmark function
+*/
+function createBenchmark( len ) {
+ var xbuf;
+ var x;
+
+ xbuf = uniform( len, -10.0, 10.0, options );
+ x = new ndarray( options.dtype, xbuf, [ len ], [ 1 ], 0, 'row-major' );
+
+ return benchmark;
+
+ function benchmark( b ) {
+ var v;
+ var i;
+
+ b.tic();
+ for ( i = 0; i < b.iterations; i++ ) {
+ v = sminabs( [ x ] );
+ if ( isnan( v ) ) {
+ b.fail( 'should not return NaN' );
+ }
+ }
+ b.toc();
+ if ( isnan( v ) ) {
+ b.fail( 'should not return NaN' );
+ }
+ b.pass( 'benchmark finished' );
+ b.end();
+ }
+}
+
+
+// MAIN //
+
+/**
+* Main execution sequence.
+*
+* @private
+*/
+function main() {
+ var len;
+ var min;
+ var max;
+ var f;
+ var i;
+
+ min = 1; // 10^min
+ max = 6; // 10^max
+
+ for ( i = min; i <= max; i++ ) {
+ len = pow( 10, i );
+ f = createBenchmark( len );
+ bench( pkg+':len='+len, f );
+ }
+}
+
+main();
diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/sminabs/docs/repl.txt b/lib/node_modules/@stdlib/stats/base/ndarray/sminabs/docs/repl.txt
new file mode 100644
index 000000000000..0bf14d78ab2a
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/base/ndarray/sminabs/docs/repl.txt
@@ -0,0 +1,32 @@
+
+{{alias}}( arrays )
+ Computes the minimum absolute value of a one-dimensional single-precision
+ floating-point ndarray.
+
+ If provided an empty ndarray, the function returns `NaN`.
+
+ Parameters
+ ----------
+ arrays: ArrayLikeObject
+ Array-like object containing a one-dimensional input ndarray.
+
+ Returns
+ -------
+ out: number
+ Minimum absolute value.
+
+ Examples
+ --------
+ > var xbuf = new {{alias:@stdlib/array/float32}}( [ 1.0, -2.0, 2.0 ] );
+ > var dt = 'float32';
+ > var sh = [ xbuf.length ];
+ > var sx = [ 1 ];
+ > var ox = 0;
+ > var ord = 'row-major';
+ > var x = new {{alias:@stdlib/ndarray/ctor}}( dt, xbuf, sh, sx, ox, ord );
+ > {{alias}}( [ x ] )
+ 1.0
+
+ See Also
+ --------
+
diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/sminabs/docs/types/index.d.ts b/lib/node_modules/@stdlib/stats/base/ndarray/sminabs/docs/types/index.d.ts
new file mode 100644
index 000000000000..587fc1d146df
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/base/ndarray/sminabs/docs/types/index.d.ts
@@ -0,0 +1,46 @@
+/*
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+* http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+// TypeScript Version: 4.1
+
+/// } arrays - array-like object containing an input ndarray
+* @returns {number} minimum value
+*
+* @example
+* var Float32Array = require( '@stdlib/array/float32' );
+* var ndarray = require( '@stdlib/ndarray/base/ctor' );
+*
+* var xbuf = new Float32Array( [ -1.0, 3.0, -4.0, 2.0 ] );
+* var x = new ndarray( 'float32', xbuf, [ 4 ], [ 1 ], 0, 'row-major' );
+*
+* var v = sminabs( [ x ] );
+* // returns 1.0
+*/
+function sminabs( arrays ) {
+ var x = arrays[ 0 ];
+ return strided( numelDimension( x, 0 ), getData( x ), getStride( x, 0 ), getOffset( x ) ); // eslint-disable-line max-len
+}
+
+
+// EXPORTS //
+
+module.exports = sminabs;
diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/sminabs/package.json b/lib/node_modules/@stdlib/stats/base/ndarray/sminabs/package.json
new file mode 100644
index 000000000000..bc770d82f654
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/base/ndarray/sminabs/package.json
@@ -0,0 +1,69 @@
+{
+ "name": "@stdlib/stats/base/ndarray/sminabs",
+ "version": "0.0.0",
+ "description": "Compute the minimum absolute value of a one-dimensional single-precision floating-point ndarray.",
+ "license": "Apache-2.0",
+ "author": {
+ "name": "The Stdlib Authors",
+ "url": "https://github.com/stdlib-js/stdlib/graphs/contributors"
+ },
+ "contributors": [
+ {
+ "name": "The Stdlib Authors",
+ "url": "https://github.com/stdlib-js/stdlib/graphs/contributors"
+ }
+ ],
+ "main": "./lib",
+ "directories": {
+ "benchmark": "./benchmark",
+ "doc": "./docs",
+ "example": "./examples",
+ "lib": "./lib",
+ "test": "./test"
+ },
+ "types": "./docs/types",
+ "scripts": {},
+ "homepage": "https://github.com/stdlib-js/stdlib",
+ "repository": {
+ "type": "git",
+ "url": "git://github.com/stdlib-js/stdlib.git"
+ },
+ "bugs": {
+ "url": "https://github.com/stdlib-js/stdlib/issues"
+ },
+ "dependencies": {},
+ "devDependencies": {},
+ "engines": {
+ "node": ">=0.10.0",
+ "npm": ">2.7.0"
+ },
+ "os": [
+ "aix",
+ "darwin",
+ "freebsd",
+ "linux",
+ "macos",
+ "openbsd",
+ "sunos",
+ "win32",
+ "windows"
+ ],
+ "keywords": [
+ "stdlib",
+ "stdmath",
+ "statistics",
+ "stats",
+ "mathematics",
+ "math",
+ "minimum",
+ "min",
+ "absolute",
+ "abs",
+ "range",
+ "extremes",
+ "domain",
+ "extent",
+ "ndarray"
+ ],
+ "__stdlib__": {}
+}
diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/sminabs/test/test.js b/lib/node_modules/@stdlib/stats/base/ndarray/sminabs/test/test.js
new file mode 100644
index 000000000000..e850a461d92c
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/base/ndarray/sminabs/test/test.js
@@ -0,0 +1,173 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+* http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+'use strict';
+
+// MODULES //
+
+var tape = require( 'tape' );
+var isnan = require( '@stdlib/math/base/assert/is-nan' );
+var isPositiveZero = require( '@stdlib/math/base/assert/is-positive-zero' );
+var Float32Array = require( '@stdlib/array/float32' );
+var ndarray = require( '@stdlib/ndarray/base/ctor' );
+var sminabs = require( './../lib' );
+
+
+// FUNCTIONS //
+
+/**
+* Returns a one-dimensional ndarray.
+*
+* @private
+* @param {Collection} buffer - underlying data buffer
+* @param {NonNegativeInteger} length - number of indexed elements
+* @param {integer} stride - stride length
+* @param {NonNegativeInteger} offset - index offset
+* @returns {ndarray} one-dimensional ndarray
+*/
+function vector( buffer, length, stride, offset ) {
+ return new ndarray( 'float32', buffer, [ length ], [ stride ], offset, 'row-major' );
+}
+
+
+// TESTS //
+
+tape( 'main export is a function', function test( t ) {
+ t.ok( true, __filename );
+ t.strictEqual( typeof sminabs, 'function', 'main export is a function' );
+ t.end();
+});
+
+tape( 'the function has an arity of 1', function test( t ) {
+ t.strictEqual( sminabs.length, 1, 'has expected arity' );
+ t.end();
+});
+
+tape( 'the function calculates the minimum absolute value of a one-dimensional ndarray', function test( t ) {
+ var x;
+ var v;
+
+ x = new Float32Array( [ 1.0, -2.0, -4.0, 5.0, 0.0, 3.0 ] );
+ v = sminabs( [ vector( x, 6, 1, 0 ) ] );
+ t.strictEqual( v, 0.0, 'returns expected value' );
+
+ x = new Float32Array( [ -4.0, -5.0 ] );
+ v = sminabs( [ vector( x, 2, 1, 0 ) ] );
+ t.strictEqual( v, 4.0, 'returns expected value' );
+
+ x = new Float32Array( [ -0.0, 0.0, -0.0 ] );
+ v = sminabs( [ vector( x, 3, 1, 0 ) ] );
+ t.strictEqual( isPositiveZero( v ), true, 'returns expected value' );
+
+ x = new Float32Array( [ NaN ] );
+ v = sminabs( [ vector( x, 1, 1, 0 ) ] );
+ t.strictEqual( isnan( v ), true, 'returns expected value' );
+
+ x = new Float32Array( [ NaN, NaN ] );
+ v = sminabs( [ vector( x, 2, 1, 0 ) ] );
+ t.strictEqual( isnan( v ), true, 'returns expected value' );
+
+ t.end();
+});
+
+tape( 'if provided an empty vector, the function returns `NaN`', function test( t ) {
+ var x;
+ var v;
+
+ x = new Float32Array( [] );
+
+ v = sminabs( [ vector( x, 0, 1, 0 ) ] );
+ t.strictEqual( isnan( v ), true, 'returns expected value' );
+
+ t.end();
+});
+
+tape( 'if provided a vector containing a single element, the function returns that element', function test( t ) {
+ var x;
+ var v;
+
+ x = new Float32Array( [ 1.0 ] );
+
+ v = sminabs( [ vector( x, 1, 1, 0 ) ] );
+ t.strictEqual( v, 1.0, 'returns expected value' );
+
+ t.end();
+});
+
+tape( 'the function supports one-dimensional ndarrays having non-unit strides', function test( t ) {
+ var x;
+ var v;
+
+ x = new Float32Array([
+ 1.0, // 0
+ 2.0,
+ 2.0, // 1
+ -7.0,
+ -2.0, // 2
+ 3.0,
+ 4.0, // 3
+ 2.0
+ ]);
+
+ v = sminabs( [ vector( x, 4, 2, 0 ) ] );
+
+ t.strictEqual( v, 1.0, 'returns expected value' );
+ t.end();
+});
+
+tape( 'the function supports one-dimensional ndarrays having negative strides', function test( t ) {
+ var x;
+ var v;
+
+ x = new Float32Array([
+ 1.0, // 3
+ 2.0,
+ 2.0, // 2
+ -7.0,
+ -2.0, // 1
+ 3.0,
+ 4.0, // 0
+ 2.0
+ ]);
+
+ v = sminabs( [ vector( x, 4, -2, 6 ) ] );
+
+ t.strictEqual( v, 1.0, 'returns expected value' );
+ t.end();
+});
+
+tape( 'the function supports one-dimensional ndarrays having non-zero offsets', function test( t ) {
+ var x;
+ var v;
+
+ x = new Float32Array([
+ 2.0,
+ 1.0, // 0
+ 2.0,
+ -2.0, // 1
+ -2.0,
+ 2.0, // 2
+ 3.0,
+ 4.0 // 3
+ ]);
+
+ v = sminabs( [ vector( x, 4, 2, 1 ) ] );
+ t.strictEqual( v, 1.0, 'returns expected value' );
+
+ t.end();
+});
diff --git a/lib/node_modules/@stdlib/stats/minabs/README.md b/lib/node_modules/@stdlib/stats/minabs/README.md
new file mode 100644
index 000000000000..2f7ce02d6cf0
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/minabs/README.md
@@ -0,0 +1,266 @@
+
+
+# minabs
+
+> Compute the minimum absolute value along one or more [ndarray][@stdlib/ndarray/ctor] dimensions.
+
+
+
+## Usage
+
+```javascript
+var minabs = require( '@stdlib/stats/minabs' );
+```
+
+#### minabs( x\[, options] )
+
+Computes the minimum absolute value along one or more [ndarray][@stdlib/ndarray/ctor] dimensions.
+
+```javascript
+var array = require( '@stdlib/ndarray/array' );
+
+var x = array( [ -1.0, 2.0, -3.0 ] );
+
+var y = minabs( x );
+// returns
+
+var v = y.get();
+// returns 1.0
+```
+
+The function has the following parameters:
+
+- **x**: input [ndarray][@stdlib/ndarray/ctor]. Must have a real-valued or "generic" [data type][@stdlib/ndarray/dtypes].
+- **options**: function options (_optional_).
+
+The function accepts the following options:
+
+- **dims**: list of dimensions over which to perform a reduction. If not provided, the function performs a reduction over all elements in a provided input [ndarray][@stdlib/ndarray/ctor].
+- **dtype**: output ndarray [data type][@stdlib/ndarray/dtypes]. Must be a real-valued or "generic" [data type][@stdlib/ndarray/dtypes].
+- **keepdims**: boolean indicating whether the reduced dimensions should be included in the returned [ndarray][@stdlib/ndarray/ctor] as singleton dimensions. Default: `false`.
+
+By default, the function performs a reduction over all elements in a provided input [ndarray][@stdlib/ndarray/ctor]. To perform a reduction over specific dimensions, provide a `dims` option.
+
+```javascript
+var ndarray2array = require( '@stdlib/ndarray/to-array' );
+var array = require( '@stdlib/ndarray/array' );
+
+var x = array( [ -1.0, 2.0, -3.0, 4.0 ], {
+ 'shape': [ 2, 2 ],
+ 'order': 'row-major'
+});
+var v = ndarray2array( x );
+// returns [ [ -1.0, 2.0 ], [ -3.0, 4.0 ] ]
+
+var y = minabs( x, {
+ 'dims': [ 0 ]
+});
+// returns
+
+v = ndarray2array( y );
+// returns [ 1.0, 2.0 ]
+
+y = minabs( x, {
+ 'dims': [ 1 ]
+});
+// returns
+
+v = ndarray2array( y );
+// returns [ 1.0, 3.0 ]
+
+y = minabs( x, {
+ 'dims': [ 0, 1 ]
+});
+// returns
+
+v = y.get();
+// returns 1.0
+```
+
+By default, the function excludes reduced dimensions from the output [ndarray][@stdlib/ndarray/ctor]. To include the reduced dimensions as singleton dimensions, set the `keepdims` option to `true`.
+
+```javascript
+var ndarray2array = require( '@stdlib/ndarray/to-array' );
+var array = require( '@stdlib/ndarray/array' );
+
+var x = array( [ -1.0, 2.0, -3.0, 4.0 ], {
+ 'shape': [ 2, 2 ],
+ 'order': 'row-major'
+});
+
+var v = ndarray2array( x );
+// returns [ [ -1.0, 2.0 ], [ -3.0, 4.0 ] ]
+
+var y = minabs( x, {
+ 'dims': [ 0 ],
+ 'keepdims': true
+});
+// returns
+
+v = ndarray2array( y );
+// returns [ [ 1.0, 2.0 ] ]
+
+y = minabs( x, {
+ 'dims': [ 1 ],
+ 'keepdims': true
+});
+// returns
+
+v = ndarray2array( y );
+// returns [ [ 1.0 ], [ 3.0 ] ]
+
+y = minabs( x, {
+ 'dims': [ 0, 1 ],
+ 'keepdims': true
+});
+// returns
+
+v = ndarray2array( y );
+// returns [ [ 1.0 ] ]
+```
+
+By default, the function returns an [ndarray][@stdlib/ndarray/ctor] having a [data type][@stdlib/ndarray/dtypes] determined by the function's output data type [policy][@stdlib/ndarray/output-dtype-policies]. To override the default behavior, set the `dtype` option.
+
+```javascript
+var getDType = require( '@stdlib/ndarray/dtype' );
+var array = require( '@stdlib/ndarray/array' );
+
+var x = array( [ -1.0, 2.0, -3.0 ], {
+ 'dtype': 'generic'
+});
+
+var y = minabs( x, {
+ 'dtype': 'float64'
+});
+// returns
+
+var dt = getDType( y );
+// returns 'float64'
+```
+
+#### minabs.assign( x, out\[, options] )
+
+Computes the minimum absolute value along one or more [ndarray][@stdlib/ndarray/ctor] dimensions and assigns results to a provided output [ndarray][@stdlib/ndarray/ctor].
+
+```javascript
+var array = require( '@stdlib/ndarray/array' );
+var zeros = require( '@stdlib/ndarray/zeros' );
+
+var x = array( [ -1.0, 2.0, -3.0 ] );
+var y = zeros( [] );
+
+var out = minabs.assign( x, y );
+// returns
+
+var v = out.get();
+// returns 1.0
+
+var bool = ( out === y );
+// returns true
+```
+
+The method has the following parameters:
+
+- **x**: input [ndarray][@stdlib/ndarray/ctor]. Must have a real-valued or generic [data type][@stdlib/ndarray/dtypes].
+- **out**: output [ndarray][@stdlib/ndarray/ctor].
+- **options**: function options (_optional_).
+
+The method accepts the following options:
+
+- **dims**: list of dimensions over which to perform a reduction. If not provided, the function performs a reduction over all elements in a provided input [ndarray][@stdlib/ndarray/ctor].
+
+
+
+
+
+
+
+## Notes
+
+- Setting the `keepdims` option to `true` can be useful when wanting to ensure that the output [ndarray][@stdlib/ndarray/ctor] is [broadcast-compatible][@stdlib/ndarray/base/broadcast-shapes] with ndarrays having the same shape as the input [ndarray][@stdlib/ndarray/ctor].
+- The output data type [policy][@stdlib/ndarray/output-dtype-policies] only applies to the main function and specifies that, by default, the function must return an [ndarray][@stdlib/ndarray/ctor] having the same [data type][@stdlib/ndarray/dtypes] as the input [ndarray][@stdlib/ndarray/ctor]. For the `assign` method, the output [ndarray][@stdlib/ndarray/ctor] is allowed to have any supported output [data type][@stdlib/ndarray/dtypes].
+
+
+
+
+
+
+
+## Examples
+
+
+
+```javascript
+var discreteUniform = require( '@stdlib/random/array/discrete-uniform' );
+var getDType = require( '@stdlib/ndarray/dtype' );
+var ndarray2array = require( '@stdlib/ndarray/to-array' );
+var ndarray = require( '@stdlib/ndarray/ctor' );
+var minabs = require( '@stdlib/stats/minabs' );
+
+// Generate an array of random numbers:
+var xbuf = discreteUniform( 25, -10, 10, {
+ 'dtype': 'generic'
+});
+
+// Wrap in an ndarray:
+var x = new ndarray( 'generic', xbuf, [ 5, 5 ], [ 5, 1 ], 0, 'row-major' );
+console.log( ndarray2array( x ) );
+
+// Perform a reduction:
+var y = minabs( x, {
+ 'dims': [ 0 ]
+});
+
+// Resolve the output array data type:
+var dt = getDType( y );
+console.log( dt );
+
+// Print the results:
+console.log( ndarray2array( y ) );
+```
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+[@stdlib/ndarray/ctor]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/ndarray/ctor
+
+[@stdlib/ndarray/dtypes]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/ndarray/dtypes
+
+[@stdlib/ndarray/output-dtype-policies]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/ndarray/output-dtype-policies
+
+[@stdlib/ndarray/base/broadcast-shapes]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/ndarray/base/broadcast-shapes
+
+
+
+
diff --git a/lib/node_modules/@stdlib/stats/minabs/benchmark/benchmark.assign.js b/lib/node_modules/@stdlib/stats/minabs/benchmark/benchmark.assign.js
new file mode 100644
index 000000000000..8431d516a627
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/minabs/benchmark/benchmark.assign.js
@@ -0,0 +1,111 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+* http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+'use strict';
+
+// MODULES //
+
+var bench = require( '@stdlib/bench' );
+var isnan = require( '@stdlib/math/base/assert/is-nan' );
+var pow = require( '@stdlib/math/base/special/pow' );
+var uniform = require( '@stdlib/random/array/uniform' );
+var zeros = require( '@stdlib/array/zeros' );
+var ndarray = require( '@stdlib/ndarray/base/ctor' );
+var pkg = require( './../package.json' ).name;
+var minabs = require( './../lib' );
+
+
+// VARIABLES //
+
+var options = {
+ 'dtype': 'float64'
+};
+
+
+// FUNCTIONS //
+
+/**
+* Creates a benchmark function.
+*
+* @private
+* @param {PositiveInteger} len - array length
+* @returns {Function} benchmark function
+*/
+function createBenchmark( len ) {
+ var out;
+ var x;
+
+ x = uniform( len, -50.0, 50.0, options );
+ x = new ndarray( options.dtype, x, [ len ], [ 1 ], 0, 'row-major' );
+
+ out = new ndarray( options.dtype, zeros( 1, options.dtype ), [], [ 0 ], 0, 'row-major' );
+
+ return benchmark;
+
+ /**
+ * Benchmark function.
+ *
+ * @private
+ * @param {Benchmark} b - benchmark instance
+ */
+ function benchmark( b ) {
+ var o;
+ var i;
+
+ b.tic();
+ for ( i = 0; i < b.iterations; i++ ) {
+ o = minabs.assign( x, out );
+ if ( typeof o !== 'object' ) {
+ b.fail( 'should return an ndarray' );
+ }
+ }
+ b.toc();
+ if ( isnan( o.get() ) ) {
+ b.fail( 'should not return NaN' );
+ }
+ b.pass( 'benchmark finished' );
+ b.end();
+ }
+}
+
+
+// MAIN //
+
+/**
+* Main execution sequence.
+*
+* @private
+*/
+function main() {
+ var len;
+ var min;
+ var max;
+ var f;
+ var i;
+
+ min = 1; // 10^min
+ max = 6; // 10^max
+
+ for ( i = min; i <= max; i++ ) {
+ len = pow( 10, i );
+ f = createBenchmark( len );
+ bench( pkg+':assign:dtype='+options.dtype+',len='+len, f );
+ }
+}
+
+main();
diff --git a/lib/node_modules/@stdlib/stats/minabs/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/minabs/benchmark/benchmark.js
new file mode 100644
index 000000000000..6de9cfe2a39f
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/minabs/benchmark/benchmark.js
@@ -0,0 +1,105 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+* http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+'use strict';
+
+// MODULES //
+
+var bench = require( '@stdlib/bench' );
+var isnan = require( '@stdlib/math/base/assert/is-nan' );
+var pow = require( '@stdlib/math/base/special/pow' );
+var uniform = require( '@stdlib/random/array/uniform' );
+var ndarray = require( '@stdlib/ndarray/base/ctor' );
+var pkg = require( './../package.json' ).name;
+var minabs = require( './../lib' );
+
+
+// VARIABLES //
+
+var options = {
+ 'dtype': 'float64'
+};
+
+
+// FUNCTIONS //
+
+/**
+* Creates a benchmark function.
+*
+* @private
+* @param {PositiveInteger} len - array length
+* @returns {Function} benchmark function
+*/
+function createBenchmark( len ) {
+ var x = uniform( len, -50.0, 50.0, options );
+ x = new ndarray( options.dtype, x, [ len ], [ 1 ], 0, 'row-major' );
+
+ return benchmark;
+
+ /**
+ * Benchmark function.
+ *
+ * @private
+ * @param {Benchmark} b - benchmark instance
+ */
+ function benchmark( b ) {
+ var o;
+ var i;
+
+ b.tic();
+ for ( i = 0; i < b.iterations; i++ ) {
+ o = minabs( x );
+ if ( typeof o !== 'object' ) {
+ b.fail( 'should return an ndarray' );
+ }
+ }
+ b.toc();
+ if ( isnan( o.get() ) ) {
+ b.fail( 'should not return NaN' );
+ }
+ b.pass( 'benchmark finished' );
+ b.end();
+ }
+}
+
+
+// MAIN //
+
+/**
+* Main execution sequence.
+*
+* @private
+*/
+function main() {
+ var len;
+ var min;
+ var max;
+ var f;
+ var i;
+
+ min = 1; // 10^min
+ max = 6; // 10^max
+
+ for ( i = min; i <= max; i++ ) {
+ len = pow( 10, i );
+ f = createBenchmark( len );
+ bench( pkg+':dtype='+options.dtype+',len='+len, f );
+ }
+}
+
+main();
diff --git a/lib/node_modules/@stdlib/stats/minabs/docs/repl.txt b/lib/node_modules/@stdlib/stats/minabs/docs/repl.txt
new file mode 100644
index 000000000000..f5079e8df2ab
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/minabs/docs/repl.txt
@@ -0,0 +1,76 @@
+
+{{alias}}( x[, options] )
+ Computes the minimum absolute value along one or more ndarray dimensions.
+
+ Parameters
+ ----------
+ x: ndarray
+ Input array. Must have a real-valued or "generic" data type.
+
+ options: Object (optional)
+ Function options.
+
+ options.dtype: string (optional)
+ Output array data type. Must be a real-valued or "generic" data type.
+
+ options.dims: Array (optional)
+ List of dimensions over which to perform a reduction. If not provided,
+ the function performs a reduction over all elements in a provided input
+ ndarray.
+
+ options.keepdims: boolean (optional)
+ Boolean indicating whether the reduced dimensions should be included in
+ the returned ndarray as singleton dimensions. Default: false.
+
+ Returns
+ -------
+ out: ndarray
+ Output array.
+
+ Examples
+ --------
+ > var x = {{alias:@stdlib/ndarray/array}}( [ -1.0, 2.0, -3.0, -4.0 ] );
+ > var y = {{alias}}( x );
+ > var v = y.get()
+ 1.0
+
+
+{{alias}}.assign( x, out[, options] )
+ Computes the minimum absolute value along one or more ndarray dimensions
+ and assigns results to a provided output ndarray.
+
+ Parameters
+ ----------
+ x: ndarray
+ Input array. Must have a real-valued or generic data type.
+
+ out: ndarray
+ Output array.
+
+ options: Object (optional)
+ Function options.
+
+ options.dims: Array (optional)
+ List of dimensions over which to perform a reduction. If not provided,
+ the function performs a reduction over all elements in a provided input
+ ndarray.
+
+ Returns
+ -------
+ out: ndarray
+ Output array.
+
+ Examples
+ --------
+ > var x = {{alias:@stdlib/ndarray/array}}( [ -1.0, 2.0, -3.0, -4.0 ] );
+ > var out = {{alias:@stdlib/ndarray/zeros}}( [] );
+ > var y = {{alias}}.assign( x, out )
+
+ > var bool = ( out === y )
+ true
+ > var v = out.get()
+ 1.0
+
+ See Also
+ --------
+
diff --git a/lib/node_modules/@stdlib/stats/minabs/docs/types/index.d.ts b/lib/node_modules/@stdlib/stats/minabs/docs/types/index.d.ts
new file mode 100644
index 000000000000..0ac1d555a1f9
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/minabs/docs/types/index.d.ts
@@ -0,0 +1,151 @@
+/*
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+* http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+// TypeScript Version: 4.1
+
+/// = typedndarray;
+
+/**
+* Output array.
+*/
+type OutputArray = typedndarray;
+
+/**
+* Interface defining "base" options.
+*/
+interface BaseOptions {
+ /**
+ * List of dimensions over which to perform a reduction.
+ */
+ dims?: ArrayLike;
+}
+
+/**
+* Interface defining options.
+*/
+interface Options extends BaseOptions {
+ /**
+ * Output array data type.
+ */
+ dtype?: DataType;
+
+ /**
+ * Boolean indicating whether the reduced dimensions should be included in the returned array as singleton dimensions. Default: `false`.
+ */
+ keepdims?: boolean;
+}
+
+/**
+* Interface for performing a reduction on an ndarray.
+*/
+interface Unary {
+ /**
+ * Computes the minimum absolute value along one or more ndarray dimensions.
+ *
+ * @param x - input ndarray
+ * @param options - function options
+ * @returns output ndarray
+ *
+ * @example
+ * var array = require( '@stdlib/ndarray/array' );
+ *
+ * var x = array( [ -1.0, 2.0, -3.0 ] );
+ *
+ * var y = minabs( x );
+ * // returns
+ *
+ * var v = y.get();
+ * // returns 1.0
+ */
+ ( x: InputArray, options?: Options ): OutputArray; // NOTE: we lose type specificity here, but retaining specificity would likely be difficult and/or tedious to completely enumerate, as the output ndarray data type is dependent on how `x` interacts with output data type policy and whether that policy has been overridden by `options.dtype`.
+
+ /**
+ * Computes the minimum absolute value along one or more ndarray dimensions and assigns results to a provided output ndarray.
+ *
+ * @param x - input ndarray
+ * @param out - output ndarray
+ * @param options - function options
+ * @returns output ndarray
+ *
+ * @example
+ * var array = require( '@stdlib/ndarray/array' );
+ * var zeros = require( '@stdlib/ndarray/zeros' );
+ *
+ * var x = array( [ -1.0, 2.0, -3.0 ] );
+ * var y = zeros( [] );
+ *
+ * var out = minabs.assign( x, y );
+ * // returns
+ *
+ * var v = out.get();
+ * // returns 1.0
+ *
+ * var bool = ( out === y );
+ * // returns true
+ */
+ assign = OutputArray>( x: InputArray, out: U, options?: BaseOptions ): U;
+}
+
+/**
+* Computes the minimum absolute value along one or more ndarray dimensions.
+*
+* @param x - input ndarray
+* @param options - function options
+* @returns output ndarray
+*
+* @example
+* var array = require( '@stdlib/ndarray/array' );
+*
+* var x = array( [ -1.0, 2.0, -3.0 ] );
+*
+* var y = minabs( x );
+* // returns
+*
+* var v = y.get();
+* // returns 1.0
+*
+* @example
+* var array = require( '@stdlib/ndarray/array' );
+* var zeros = require( '@stdlib/ndarray/zeros' );
+*
+* var x = array( [ -1.0, 2.0, -3.0 ] );
+* var y = zeros( [] );
+*
+* var out = minabs.assign( x, y );
+* // returns
+*
+* var v = out.get();
+* // returns 1.0
+*
+* var bool = ( out === y );
+* // returns true
+*/
+declare const minabs: Unary;
+
+
+// EXPORTS //
+
+export = minabs;
diff --git a/lib/node_modules/@stdlib/stats/minabs/docs/types/test.ts b/lib/node_modules/@stdlib/stats/minabs/docs/types/test.ts
new file mode 100644
index 000000000000..49e4e6453d3c
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/minabs/docs/types/test.ts
@@ -0,0 +1,225 @@
+/*
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+* http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+/* eslint-disable @typescript-eslint/no-unused-expressions, space-in-parens */
+
+/// ( x ); // $ExpectType OutputArray
+ minabs( x, {} ); // $ExpectType OutputArray
+}
+
+// The compiler throws an error if the function is provided a first argument which is not an ndarray...
+{
+ minabs( '5' ); // $ExpectError
+ minabs( 5 ); // $ExpectError
+ minabs( true ); // $ExpectError
+ minabs( false ); // $ExpectError
+ minabs( null ); // $ExpectError
+ minabs( void 0 ); // $ExpectError
+ minabs( {} ); // $ExpectError
+ minabs( ( x: number ): number => x ); // $ExpectError
+
+ minabs( '5', {} ); // $ExpectError
+ minabs( 5, {} ); // $ExpectError
+ minabs( true, {} ); // $ExpectError
+ minabs( false, {} ); // $ExpectError
+ minabs( null, {} ); // $ExpectError
+ minabs( void 0, {} ); // $ExpectError
+ minabs( {}, {} ); // $ExpectError
+ minabs( ( x: number ): number => x, {} ); // $ExpectError
+}
+
+// The compiler throws an error if the function is provided a second argument which is not an object...
+{
+ const x = zeros( [ 2, 2 ], {
+ 'dtype': 'float64'
+ });
+
+ minabs( x, '5' ); // $ExpectError
+ minabs( x, true ); // $ExpectError
+ minabs( x, false ); // $ExpectError
+ minabs( x, null ); // $ExpectError
+ minabs( x, [] ); // $ExpectError
+ minabs( x, ( x: number ): number => x ); // $ExpectError
+}
+
+// The compiler throws an error if the function is provided an invalid `dtype` option...
+{
+ const x = zeros( [ 2, 2 ], {
+ 'dtype': 'float64'
+ });
+
+ minabs( x, { 'dtype': '5' } ); // $ExpectError
+ minabs( x, { 'dtype': 5 } ); // $ExpectError
+ minabs( x, { 'dtype': true } ); // $ExpectError
+ minabs( x, { 'dtype': false } ); // $ExpectError
+ minabs( x, { 'dtype': null } ); // $ExpectError
+ minabs( x, { 'dtype': [] } ); // $ExpectError
+ minabs( x, { 'dtype': {} } ); // $ExpectError
+ minabs( x, { 'dtype': ( x: number ): number => x } ); // $ExpectError
+}
+
+// The compiler throws an error if the function is provided an invalid `keepdims` option...
+{
+ const x = zeros( [ 2, 2 ], {
+ 'dtype': 'float64'
+ });
+
+ minabs( x, { 'keepdims': '5' } ); // $ExpectError
+ minabs( x, { 'keepdims': 5 } ); // $ExpectError
+ minabs( x, { 'keepdims': null } ); // $ExpectError
+ minabs( x, { 'keepdims': [] } ); // $ExpectError
+ minabs( x, { 'keepdims': {} } ); // $ExpectError
+ minabs( x, { 'keepdims': ( x: number ): number => x } ); // $ExpectError
+}
+
+// The compiler throws an error if the function is provided an invalid `dims` option...
+{
+ const x = zeros( [ 2, 2 ], {
+ 'dtype': 'float64'
+ });
+
+ minabs( x, { 'dims': '5' } ); // $ExpectError
+ minabs( x, { 'dims': 5 } ); // $ExpectError
+ minabs( x, { 'dims': true } ); // $ExpectError
+ minabs( x, { 'dims': false } ); // $ExpectError
+ minabs( x, { 'dims': null } ); // $ExpectError
+ minabs( x, { 'dims': {} } ); // $ExpectError
+ minabs( x, { 'dims': ( x: number ): number => x } ); // $ExpectError
+}
+
+// The compiler throws an error if the function is provided an unsupported number of arguments...
+{
+ const x = zeros( [ 2, 2 ], {
+ 'dtype': 'float64'
+ });
+
+ minabs(); // $ExpectError
+ minabs( x, {}, {} ); // $ExpectError
+}
+
+// Attached to the function is an `assign` method which returns an ndarray...
+{
+ const x = zeros( [ 2, 2 ], {
+ 'dtype': 'float64'
+ });
+
+ minabs.assign( x, x ); // $ExpectType float64ndarray
+ minabs.assign( x, x, {} ); // $ExpectType float64ndarray
+}
+
+// The compiler throws an error if the `assign` method is provided a first argument which is not an ndarray...
+{
+ const x = zeros( [ 2, 2 ], {
+ 'dtype': 'float64'
+ });
+
+ minabs.assign( '5', x ); // $ExpectError
+ minabs.assign( 5, x ); // $ExpectError
+ minabs.assign( true, x ); // $ExpectError
+ minabs.assign( false, x ); // $ExpectError
+ minabs.assign( null, x ); // $ExpectError
+ minabs.assign( void 0, x ); // $ExpectError
+ minabs.assign( {}, x ); // $ExpectError
+ minabs.assign( ( x: number ): number => x, x ); // $ExpectError
+
+ minabs.assign( '5', x, {} ); // $ExpectError
+ minabs.assign( 5, x, {} ); // $ExpectError
+ minabs.assign( true, x, {} ); // $ExpectError
+ minabs.assign( false, x, {} ); // $ExpectError
+ minabs.assign( null, x, {} ); // $ExpectError
+ minabs.assign( void 0, x, {} ); // $ExpectError
+ minabs.assign( {}, x, {} ); // $ExpectError
+ minabs.assign( ( x: number ): number => x, x, {} ); // $ExpectError
+}
+
+// The compiler throws an error if the `assign` method is provided a second argument which is not an ndarray...
+{
+ const x = zeros( [ 2, 2 ], {
+ 'dtype': 'float64'
+ });
+
+ minabs.assign( x, '5' ); // $ExpectError
+ minabs.assign( x, 5 ); // $ExpectError
+ minabs.assign( x, true ); // $ExpectError
+ minabs.assign( x, false ); // $ExpectError
+ minabs.assign( x, null ); // $ExpectError
+ minabs.assign( x, void 0 ); // $ExpectError
+ minabs.assign( x, ( x: number ): number => x ); // $ExpectError
+
+ minabs.assign( x, '5', {} ); // $ExpectError
+ minabs.assign( x, 5, {} ); // $ExpectError
+ minabs.assign( x, true, {} ); // $ExpectError
+ minabs.assign( x, false, {} ); // $ExpectError
+ minabs.assign( x, null, {} ); // $ExpectError
+ minabs.assign( x, void 0, {} ); // $ExpectError
+ minabs.assign( x, ( x: number ): number => x, {} ); // $ExpectError
+}
+
+// The compiler throws an error if the `assign` method is provided a third argument which is not an object...
+{
+ const x = zeros( [ 2, 2 ], {
+ 'dtype': 'float64'
+ });
+
+ minabs.assign( x, x, '5' ); // $ExpectError
+ minabs.assign( x, x, true ); // $ExpectError
+ minabs.assign( x, x, false ); // $ExpectError
+ minabs.assign( x, x, null ); // $ExpectError
+ minabs.assign( x, x, [] ); // $ExpectError
+ minabs.assign( x, x, ( x: number ): number => x ); // $ExpectError
+}
+
+// The compiler throws an error if the `assign` method is provided an invalid `dims` option...
+{
+ const x = zeros( [ 2, 2 ], {
+ 'dtype': 'float64'
+ });
+
+ minabs.assign( x, x, { 'dims': '5' } ); // $ExpectError
+ minabs.assign( x, x, { 'dims': 5 } ); // $ExpectError
+ minabs.assign( x, x, { 'dims': true } ); // $ExpectError
+ minabs.assign( x, x, { 'dims': false } ); // $ExpectError
+ minabs.assign( x, x, { 'dims': null } ); // $ExpectError
+ minabs.assign( x, x, { 'dims': {} } ); // $ExpectError
+ minabs.assign( x, x, { 'dims': ( x: number ): number => x } ); // $ExpectError
+}
+
+// The compiler throws an error if the `assign` method is provided an unsupported number of arguments...
+{
+ const x = zeros( [ 2, 2 ], {
+ 'dtype': 'float64'
+ });
+
+ minabs.assign(); // $ExpectError
+ minabs.assign( x ); // $ExpectError
+ minabs.assign( x, x, {}, {} ); // $ExpectError
+}
diff --git a/lib/node_modules/@stdlib/stats/minabs/examples/index.js b/lib/node_modules/@stdlib/stats/minabs/examples/index.js
new file mode 100644
index 000000000000..8a5a77694fc9
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/minabs/examples/index.js
@@ -0,0 +1,46 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+* http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+'use strict';
+
+var discreteUniform = require( '@stdlib/random/array/discrete-uniform' );
+var getDType = require( '@stdlib/ndarray/dtype' );
+var ndarray2array = require( '@stdlib/ndarray/to-array' );
+var ndarray = require( '@stdlib/ndarray/ctor' );
+var minabs = require( './../lib' );
+
+// Generate an array of random numbers:
+var xbuf = discreteUniform( 25, -10, 10, {
+ 'dtype': 'generic'
+});
+
+// Wrap in an ndarray:
+var x = new ndarray( 'generic', xbuf, [ 5, 5 ], [ 5, 1 ], 0, 'row-major' );
+console.log( ndarray2array( x ) );
+
+// Perform a reduction:
+var y = minabs( x, {
+ 'dims': [ 0 ]
+});
+
+// Resolve the output array data type:
+var dt = getDType( y );
+console.log( dt );
+
+// Print the results:
+console.log( ndarray2array( y ) );
diff --git a/lib/node_modules/@stdlib/stats/minabs/lib/index.js b/lib/node_modules/@stdlib/stats/minabs/lib/index.js
new file mode 100644
index 000000000000..be18a83af862
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/minabs/lib/index.js
@@ -0,0 +1,63 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+* http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+'use strict';
+
+/**
+* Compute the minimum absolute value along one or more ndarray dimensions.
+*
+* @module @stdlib/stats/minabs
+*
+* @example
+* var Float64Array = require( '@stdlib/array/float64' );
+* var ndarray = require( '@stdlib/ndarray/ctor' );
+* var minabs = require( '@stdlib/stats/minabs' );
+*
+* // Create a data buffer:
+* var xbuf = new Float64Array( [ 0.0, 2.0, 3.0, 0.0, 0.0, 6.0, 7.0, 0.0, 0.0, 10.0, 11.0, 0.0 ] );
+*
+* // Define the shape of the input array:
+* var sh = [ 3, 1, 2 ];
+*
+* // Define the array strides:
+* var sx = [ 4, 4, 1 ];
+*
+* // Define the index offset:
+* var ox = 1;
+*
+* // Create an input ndarray:
+* var x = new ndarray( 'float64', xbuf, sh, sx, ox, 'row-major' );
+*
+* // Perform reduction:
+* var out = minabs( x );
+* // returns
+*
+* var v = out.get();
+* // returns 2.0
+*/
+
+// MODULES //
+
+var main = require( './main.js' );
+
+
+// EXPORTS //
+
+module.exports = main;
+
+// exports: { "assign": "main.assign" }
diff --git a/lib/node_modules/@stdlib/stats/minabs/lib/main.js b/lib/node_modules/@stdlib/stats/minabs/lib/main.js
new file mode 100644
index 000000000000..1d5d2553a0e6
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/minabs/lib/main.js
@@ -0,0 +1,101 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+* http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+'use strict';
+
+// MODULES //
+
+var dtypes = require( '@stdlib/ndarray/dtypes' );
+var gminabs = require( '@stdlib/stats/base/ndarray/minabs' );
+var dminabs = require( '@stdlib/stats/base/ndarray/dminabs' );
+var sminabs = require( '@stdlib/stats/base/ndarray/sminabs' );
+var factory = require( '@stdlib/ndarray/base/unary-reduce-strided1d-dispatch-factory' );
+
+
+// VARIABLES //
+
+var idtypes = dtypes( 'real_and_generic' );
+var odtypes = dtypes( 'real_and_generic' );
+var policies = {
+ 'output': 'same',
+ 'casting': 'none'
+};
+var table = {
+ 'types': [
+ 'float64', // input
+ 'float32' // input
+ ],
+ 'fcns': [
+ dminabs,
+ sminabs
+ ],
+ 'default': gminabs
+};
+
+
+// MAIN //
+
+/**
+* Computes the minimum absolute value along one or more ndarray dimensions.
+*
+* @name minabs
+* @type {Function}
+* @param {ndarray} x - input ndarray
+* @param {Options} [options] - function options
+* @param {IntegerArray} [options.dims] - list of dimensions over which to perform a reduction
+* @param {boolean} [options.keepdims=false] - boolean indicating whether the reduced dimensions should be included in the returned ndarray as singleton dimensions
+* @param {string} [options.dtype] - output ndarray data type
+* @throws {TypeError} first argument must be an ndarray-like object
+* @throws {TypeError} options argument must be an object
+* @throws {RangeError} dimension indices must not exceed input ndarray bounds
+* @throws {RangeError} number of dimension indices must not exceed the number of input ndarray dimensions
+* @throws {Error} must provide valid options
+* @returns {ndarray} output ndarray
+*
+* @example
+* var Float64Array = require( '@stdlib/array/float64' );
+* var ndarray = require( '@stdlib/ndarray/ctor' );
+*
+* // Create a data buffer:
+* var xbuf = new Float64Array( [ 0.0, 2.0, 3.0, 0.0, 0.0, 6.0, 7.0, 0.0, 0.0, 10.0, 11.0, 0.0 ] );
+*
+* // Define the shape of the input array:
+* var sh = [ 3, 1, 2 ];
+*
+* // Define the array strides:
+* var sx = [ 4, 4, 1 ];
+*
+* // Define the index offset:
+* var ox = 1;
+*
+* // Create an input ndarray:
+* var x = new ndarray( 'float64', xbuf, sh, sx, ox, 'row-major' );
+*
+* // Perform reduction:
+* var out = minabs( x );
+* // returns
+*
+* var v = out.get();
+* // returns 2.0
+*/
+var minabs = factory( table, [ idtypes ], odtypes, policies );
+
+
+// EXPORTS //
+
+module.exports = minabs;
diff --git a/lib/node_modules/@stdlib/stats/minabs/package.json b/lib/node_modules/@stdlib/stats/minabs/package.json
new file mode 100644
index 000000000000..462888641bf7
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/minabs/package.json
@@ -0,0 +1,67 @@
+{
+ "name": "@stdlib/stats/minabs",
+ "version": "0.0.0",
+ "description": "Compute the minimum absolute value along one or more ndarray dimensions.",
+ "license": "Apache-2.0",
+ "author": {
+ "name": "The Stdlib Authors",
+ "url": "https://github.com/stdlib-js/stdlib/graphs/contributors"
+ },
+ "contributors": [
+ {
+ "name": "The Stdlib Authors",
+ "url": "https://github.com/stdlib-js/stdlib/graphs/contributors"
+ }
+ ],
+ "main": "./lib",
+ "directories": {
+ "benchmark": "./benchmark",
+ "doc": "./docs",
+ "example": "./examples",
+ "lib": "./lib",
+ "test": "./test"
+ },
+ "types": "./docs/types",
+ "scripts": {},
+ "homepage": "https://github.com/stdlib-js/stdlib",
+ "repository": {
+ "type": "git",
+ "url": "git://github.com/stdlib-js/stdlib.git"
+ },
+ "bugs": {
+ "url": "https://github.com/stdlib-js/stdlib/issues"
+ },
+ "dependencies": {},
+ "devDependencies": {},
+ "engines": {
+ "node": ">=0.10.0",
+ "npm": ">2.7.0"
+ },
+ "os": [
+ "aix",
+ "darwin",
+ "freebsd",
+ "linux",
+ "macos",
+ "openbsd",
+ "sunos",
+ "win32",
+ "windows"
+ ],
+ "keywords": [
+ "stdlib",
+ "stdmath",
+ "statistics",
+ "stats",
+ "mathematics",
+ "math",
+ "minimum",
+ "min",
+ "range",
+ "extremes",
+ "domain",
+ "extent",
+ "ndarray"
+ ],
+ "__stdlib__": {}
+}
diff --git a/lib/node_modules/@stdlib/stats/minabs/test/test.assign.js b/lib/node_modules/@stdlib/stats/minabs/test/test.assign.js
new file mode 100644
index 000000000000..c6d19982d020
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/minabs/test/test.assign.js
@@ -0,0 +1,717 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+* http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+'use strict';
+
+// MODULES //
+
+var tape = require( 'tape' );
+var ndarray = require( '@stdlib/ndarray/ctor' );
+var zeros = require( '@stdlib/ndarray/zeros' );
+var empty = require( '@stdlib/ndarray/empty' );
+var emptyLike = require( '@stdlib/ndarray/empty-like' );
+var ndarray2array = require( '@stdlib/ndarray/to-array' );
+var minabs = require( './../lib' ).assign;
+
+
+// TESTS //
+
+tape( 'main export is a function', function test( t ) {
+ t.ok( true, __filename );
+ t.strictEqual( typeof minabs, 'function', 'main export is a function' );
+ t.end();
+});
+
+tape( 'the function throws an error if provided a first argument which is not an ndarray-like object', function test( t ) {
+ var values;
+ var out;
+ var i;
+
+ out = zeros( [ 2, 2 ], {
+ 'dtype': 'generic'
+ });
+
+ values = [
+ '5',
+ 5,
+ NaN,
+ true,
+ false,
+ null,
+ void 0,
+ [],
+ {},
+ function noop() {}
+ ];
+ for ( i = 0; i < values.length; i++ ) {
+ t.throws( badValue( values[ i ] ), TypeError, 'throws an error when provided ' + values[ i ] );
+ }
+ t.end();
+
+ function badValue( value ) {
+ return function badValue() {
+ minabs( value, out );
+ };
+ }
+});
+
+tape( 'the function throws an error if provided a first argument which is not an ndarray-like object (options)', function test( t ) {
+ var values;
+ var out;
+ var i;
+
+ out = zeros( [ 2, 2 ], {
+ 'dtype': 'generic'
+ });
+
+ values = [
+ '5',
+ 5,
+ NaN,
+ true,
+ false,
+ null,
+ void 0,
+ [],
+ {},
+ function noop() {}
+ ];
+ for ( i = 0; i < values.length; i++ ) {
+ t.throws( badValue( values[ i ] ), TypeError, 'throws an error when provided ' + values[ i ] );
+ }
+ t.end();
+
+ function badValue( value ) {
+ return function badValue() {
+ minabs( value, out, {} );
+ };
+ }
+});
+
+tape( 'the function throws an error if provided a first argument which is not an ndarray-like object having a supported data type', function test( t ) {
+ var values;
+ var out;
+ var i;
+
+ out = zeros( [ 2, 2 ], {
+ 'dtype': 'generic'
+ });
+
+ values = [
+ empty( [ 2, 2 ], {
+ 'dtype': 'bool'
+ })
+ ];
+ for ( i = 0; i < values.length; i++ ) {
+ t.throws( badValue( values[ i ] ), TypeError, 'throws an error when provided ' + values[ i ] );
+ }
+ t.end();
+
+ function badValue( value ) {
+ return function badValue() {
+ minabs( value, out );
+ };
+ }
+});
+
+tape( 'the function throws an error if provided a first argument which is not an ndarray-like object having a supported data type (options)', function test( t ) {
+ var values;
+ var out;
+ var i;
+
+ out = zeros( [ 2, 2 ], {
+ 'dtype': 'generic'
+ });
+
+ values = [
+ empty( [ 2, 2 ], {
+ 'dtype': 'bool'
+ })
+ ];
+ for ( i = 0; i < values.length; i++ ) {
+ t.throws( badValue( values[ i ] ), TypeError, 'throws an error when provided ' + values[ i ] );
+ }
+ t.end();
+
+ function badValue( value ) {
+ return function badValue() {
+ minabs( value, out, {} );
+ };
+ }
+});
+
+tape( 'the function throws an error if provided a second argument which is not an ndarray-like object', function test( t ) {
+ var values;
+ var x;
+ var i;
+
+ x = zeros( [ 2, 2 ], {
+ 'dtype': 'generic'
+ });
+
+ values = [
+ '5',
+ 5,
+ NaN,
+ true,
+ false,
+ null,
+ void 0,
+ [],
+ {},
+ function noop() {}
+ ];
+ for ( i = 0; i < values.length; i++ ) {
+ t.throws( badValue( values[ i ] ), TypeError, 'throws an error when provided ' + values[ i ] );
+ }
+ t.end();
+
+ function badValue( value ) {
+ return function badValue() {
+ minabs( x, value );
+ };
+ }
+});
+
+tape( 'the function throws an error if provided a second argument which is not an ndarray-like object (options)', function test( t ) {
+ var values;
+ var x;
+ var i;
+
+ x = zeros( [ 2, 2 ], {
+ 'dtype': 'generic'
+ });
+
+ values = [
+ '5',
+ 5,
+ NaN,
+ true,
+ false,
+ null,
+ void 0,
+ [],
+ {},
+ function noop() {}
+ ];
+ for ( i = 0; i < values.length; i++ ) {
+ t.throws( badValue( values[ i ] ), TypeError, 'throws an error when provided ' + values[ i ] );
+ }
+ t.end();
+
+ function badValue( value ) {
+ return function badValue() {
+ minabs( x, value, {} );
+ };
+ }
+});
+
+tape( 'the function throws an error if provided a third argument which is not an object', function test( t ) {
+ var values;
+ var out;
+ var x;
+ var i;
+
+ x = zeros( [ 2, 2 ], {
+ 'dtype': 'generic'
+ });
+ out = zeros( [], {
+ 'dtype': 'generic'
+ });
+
+ values = [
+ '5',
+ 5,
+ NaN,
+ true,
+ false,
+ null,
+ void 0,
+ [],
+ function noop() {}
+ ];
+ for ( i = 0; i < values.length; i++ ) {
+ t.throws( badValue( values[ i ] ), TypeError, 'throws an error when provided ' + values[ i ] );
+ }
+ t.end();
+
+ function badValue( value ) {
+ return function badValue() {
+ minabs( x, out, value );
+ };
+ }
+});
+
+tape( 'the function throws an error if provided a `dims` option which is not an array-like object of integers', function test( t ) {
+ var values;
+ var out;
+ var x;
+ var i;
+
+ x = zeros( [ 2, 2 ], {
+ 'dtype': 'generic'
+ });
+ out = zeros( [], {
+ 'dtype': 'generic'
+ });
+
+ values = [
+ '5',
+ 5,
+ NaN,
+ true,
+ false,
+ null,
+ void 0,
+ [ 'a' ],
+ {},
+ function noop() {}
+ ];
+ for ( i = 0; i < values.length; i++ ) {
+ t.throws( badValue( values[ i ] ), TypeError, 'throws an error when provided ' + values[ i ] );
+ }
+ t.end();
+
+ function badValue( value ) {
+ return function badValue() {
+ minabs( x, out, {
+ 'dims': value
+ });
+ };
+ }
+});
+
+tape( 'the function throws an error if provided a `dims` option which contains out-of-bounds indices', function test( t ) {
+ var values;
+ var out;
+ var x;
+ var i;
+
+ x = zeros( [ 2, 2 ], {
+ 'dtype': 'generic'
+ });
+ out = zeros( [ 2 ], {
+ 'dtype': 'generic'
+ });
+
+ values = [
+ [ -10 ],
+ [ 20 ]
+ ];
+ for ( i = 0; i < values.length; i++ ) {
+ t.throws( badValue( values[ i ] ), RangeError, 'throws an error when provided ' + values[ i ] );
+ }
+ t.end();
+
+ function badValue( value ) {
+ return function badValue() {
+ minabs( x, out, {
+ 'dims': value
+ });
+ };
+ }
+});
+
+tape( 'the function throws an error if provided a `dims` option which contains too many indices', function test( t ) {
+ var values;
+ var out;
+ var x;
+ var i;
+
+ x = zeros( [ 2, 2 ], {
+ 'dtype': 'generic'
+ });
+ out = zeros( [], {
+ 'dtype': 'generic'
+ });
+
+ values = [
+ [ 0, 1, 2 ],
+ [ 0, 1, 2, 3 ]
+ ];
+ for ( i = 0; i < values.length; i++ ) {
+ t.throws( badValue( values[ i ] ), RangeError, 'throws an error when provided ' + values[ i ] );
+ }
+ t.end();
+
+ function badValue( value ) {
+ return function badValue() {
+ minabs( x, out, {
+ 'dims': value
+ });
+ };
+ }
+});
+
+tape( 'the function throws an error if provided a `dims` option which contains duplicate indices', function test( t ) {
+ var values;
+ var out;
+ var x;
+ var i;
+
+ x = zeros( [ 2, 2 ], {
+ 'dtype': 'generic'
+ });
+ out = zeros( [], {
+ 'dtype': 'generic'
+ });
+
+ values = [
+ [ 0, 0 ],
+ [ 1, 1 ],
+ [ 0, 1, 0 ],
+ [ 1, 0, 1 ]
+ ];
+ for ( i = 0; i < values.length; i++ ) {
+ t.throws( badValue( values[ i ] ), Error, 'throws an error when provided ' + values[ i ] );
+ }
+ t.end();
+
+ function badValue( value ) {
+ return function badValue() {
+ minabs( x, out, {
+ 'dims': value
+ });
+ };
+ }
+});
+
+tape( 'the function throws an error if provided an output array which has an invalid shape (default)', function test( t ) {
+ var values;
+ var x;
+ var i;
+
+ x = zeros( [ 2, 2 ], {
+ 'dtype': 'generic'
+ });
+
+ values = [
+ [ 2, 2 ],
+ [ 2 ],
+ [ 4, 4 ],
+ [ 4 ],
+ [ 1 ],
+ [ 1, 1 ]
+ ];
+ for ( i = 0; i < values.length; i++ ) {
+ t.throws( badValue( values[ i ] ), Error, 'throws an error when provided ' + values[ i ] );
+ }
+ t.end();
+
+ function badValue( value ) {
+ return function badValue() {
+ var out = zeros( value, {
+ 'dtype': 'generic'
+ });
+ minabs( x, out );
+ };
+ }
+});
+
+tape( 'the function throws an error if provided an output array which has an invalid shape (all dimensions)', function test( t ) {
+ var values;
+ var x;
+ var i;
+
+ x = zeros( [ 2, 2 ], {
+ 'dtype': 'generic'
+ });
+
+ values = [
+ [ 2, 2 ],
+ [ 2 ],
+ [ 4, 4 ],
+ [ 4 ],
+ [ 1 ],
+ [ 1, 1 ]
+ ];
+ for ( i = 0; i < values.length; i++ ) {
+ t.throws( badValue( values[ i ] ), Error, 'throws an error when provided ' + values[ i ] );
+ }
+ t.end();
+
+ function badValue( value ) {
+ return function badValue() {
+ var out = zeros( value, {
+ 'dtype': 'generic'
+ });
+ minabs( x, out, {
+ 'dims': [ 0, 1 ]
+ });
+ };
+ }
+});
+
+tape( 'the function throws an error if provided an output array which has an invalid shape (some dimensions)', function test( t ) {
+ var values;
+ var x;
+ var i;
+
+ x = zeros( [ 2, 2 ], {
+ 'dtype': 'generic'
+ });
+
+ values = [
+ [],
+ [ 4, 4 ],
+ [ 4 ],
+ [ 1 ],
+ [ 1, 1 ]
+ ];
+ for ( i = 0; i < values.length; i++ ) {
+ t.throws( badValue( values[ i ] ), Error, 'throws an error when provided ' + values[ i ] );
+ }
+ t.end();
+
+ function badValue( value ) {
+ return function badValue() {
+ var out = zeros( value, {
+ 'dtype': 'generic'
+ });
+ minabs( x, out, {
+ 'dims': [ 0 ]
+ });
+ };
+ }
+});
+
+tape( 'the function performs a reduction on an ndarray (default, row-major)', function test( t ) {
+ var expected;
+ var actual;
+ var xbuf;
+ var out;
+ var x;
+
+ xbuf = [ -1.0, 2.0, -3.0, 4.0 ];
+ x = new ndarray( 'generic', xbuf, [ 2, 2 ], [ 2, 1 ], 0, 'row-major' );
+
+ out = emptyLike( x, {
+ 'shape': []
+ });
+
+ actual = minabs( x, out );
+ expected = 1.0;
+
+ t.strictEqual( actual, out, 'returns expected value' );
+ t.strictEqual( actual.get(), expected, 'returns expected value' );
+
+ t.end();
+});
+
+tape( 'the function performs a reduction on an ndarray (default, column-major)', function test( t ) {
+ var expected;
+ var actual;
+ var xbuf;
+ var out;
+ var x;
+
+ xbuf = [ -1.0, 2.0, -3.0, 4.0 ];
+ x = new ndarray( 'generic', xbuf, [ 2, 2 ], [ 1, 2 ], 0, 'column-major' );
+
+ out = emptyLike( x, {
+ 'shape': []
+ });
+
+ actual = minabs( x, out );
+ expected = 1.0;
+
+ t.strictEqual( actual, out, 'returns expected value' );
+ t.strictEqual( actual.get(), expected, 'returns expected value' );
+
+ t.end();
+});
+
+tape( 'the function performs a reduction on an ndarray (all dimensions, row-major)', function test( t ) {
+ var expected;
+ var actual;
+ var xbuf;
+ var out;
+ var x;
+
+ xbuf = [ -1.0, 2.0, -3.0, 4.0 ];
+ x = new ndarray( 'generic', xbuf, [ 2, 2 ], [ 2, 1 ], 0, 'row-major' );
+
+ out = emptyLike( x, {
+ 'shape': []
+ });
+
+ actual = minabs( x, out, {
+ 'dims': [ 0, 1 ]
+ });
+ expected = 1.0;
+
+ t.strictEqual( actual, out, 'returns expected value' );
+ t.strictEqual( actual.get(), expected, 'returns expected value' );
+
+ t.end();
+});
+
+tape( 'the function performs a reduction on an ndarray (all dimensions, column-major)', function test( t ) {
+ var expected;
+ var actual;
+ var xbuf;
+ var out;
+ var x;
+
+ xbuf = [ -1.0, 2.0, -3.0, 4.0 ];
+ x = new ndarray( 'generic', xbuf, [ 2, 2 ], [ 1, 2 ], 0, 'column-major' );
+
+ out = emptyLike( x, {
+ 'shape': []
+ });
+
+ actual = minabs( x, out, {
+ 'dims': [ 0, 1 ]
+ });
+ expected = 1.0;
+
+ t.strictEqual( actual, out, 'returns expected value' );
+ t.strictEqual( actual.get(), expected, 'returns expected value' );
+
+ t.end();
+});
+
+tape( 'the function performs a reduction on an ndarray (no dimensions, row-major)', function test( t ) {
+ var expected;
+ var actual;
+ var xbuf;
+ var out;
+ var x;
+
+ xbuf = [ -1.0, 2.0, -3.0, 4.0 ];
+ x = new ndarray( 'generic', xbuf, [ 2, 2 ], [ 2, 1 ], 0, 'row-major' );
+
+ out = emptyLike( x, {
+ 'shape': [ 2, 2 ]
+ });
+
+ actual = minabs( x, out, {
+ 'dims': []
+ });
+ expected = [ [ 1.0, 2.0 ], [ 3.0, 4.0 ] ];
+
+ t.strictEqual( actual, out, 'returns expected value' );
+ t.deepEqual( ndarray2array( actual ), expected, 'returns expected value' );
+
+ t.end();
+});
+
+tape( 'the function performs a reduction on an ndarray (no dimensions, column-major)', function test( t ) {
+ var expected;
+ var actual;
+ var xbuf;
+ var out;
+ var x;
+
+ xbuf = [ -1.0, 2.0, -3.0, 4.0 ];
+ x = new ndarray( 'generic', xbuf, [ 2, 2 ], [ 1, 2 ], 0, 'column-major' );
+
+ out = emptyLike( x, {
+ 'shape': [ 2, 2 ]
+ });
+
+ actual = minabs( x, out, {
+ 'dims': []
+ });
+ expected = [ [ 1.0, 3.0 ], [ 2.0, 4.0 ] ];
+
+ t.strictEqual( actual, out, 'returns expected value' );
+ t.deepEqual( ndarray2array( actual ), expected, 'returns expected value' );
+
+ t.end();
+});
+
+tape( 'the function supports specifying reduction dimensions (row-major)', function test( t ) {
+ var expected;
+ var actual;
+ var xbuf;
+ var out;
+ var x;
+
+ xbuf = [ -1.0, 2.0, -3.0, 4.0 ];
+ x = new ndarray( 'generic', xbuf, [ 2, 2 ], [ 2, 1 ], 0, 'row-major' );
+
+ out = emptyLike( x, {
+ 'shape': [ 2 ]
+ });
+
+ actual = minabs( x, out, {
+ 'dims': [ 0 ]
+ });
+ expected = [ 1.0, 2.0 ];
+
+ t.strictEqual( actual, out, 'returns expected value' );
+ t.deepEqual( ndarray2array( actual ), expected, 'returns expected value' );
+
+ xbuf = [ -1.0, 2.0, -3.0, 4.0 ];
+ x = new ndarray( 'generic', xbuf, [ 2, 2 ], [ 2, 1 ], 0, 'row-major' );
+
+ out = emptyLike( x, {
+ 'shape': [ 2 ]
+ });
+
+ actual = minabs( x, out, {
+ 'dims': [ 1 ]
+ });
+ expected = [ 1.0, 3.0 ];
+
+ t.strictEqual( actual, out, 'returns expected value' );
+ t.deepEqual( ndarray2array( actual ), expected, 'returns expected value' );
+
+ t.end();
+});
+
+tape( 'the function supports specifying reduction dimensions (column-major)', function test( t ) {
+ var expected;
+ var actual;
+ var xbuf;
+ var out;
+ var x;
+
+ xbuf = [ -1.0, 2.0, -3.0, 4.0 ];
+ x = new ndarray( 'generic', xbuf, [ 2, 2 ], [ 1, 2 ], 0, 'column-major' );
+
+ out = emptyLike( x, {
+ 'shape': [ 2 ]
+ });
+
+ actual = minabs( x, out, {
+ 'dims': [ 0 ]
+ });
+ expected = [ 1.0, 3.0 ];
+
+ t.strictEqual( actual, out, 'returns expected value' );
+ t.deepEqual( ndarray2array( actual ), expected, 'returns expected value' );
+
+ xbuf = [ -1.0, 2.0, -3.0, 4.0 ];
+ x = new ndarray( 'generic', xbuf, [ 2, 2 ], [ 1, 2 ], 0, 'column-major' );
+
+ out = emptyLike( x, {
+ 'shape': [ 2 ]
+ });
+
+ actual = minabs( x, out, {
+ 'dims': [ 1 ]
+ });
+ expected = [ 1.0, 2.0 ];
+
+ t.strictEqual( actual, out, 'returns expected value' );
+ t.deepEqual( ndarray2array( actual ), expected, 'returns expected value' );
+
+ t.end();
+});
diff --git a/lib/node_modules/@stdlib/stats/minabs/test/test.js b/lib/node_modules/@stdlib/stats/minabs/test/test.js
new file mode 100644
index 000000000000..0dd9f163dbd2
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/minabs/test/test.js
@@ -0,0 +1,39 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+* http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+'use strict';
+
+// MODULES //
+
+var tape = require( 'tape' );
+var isMethod = require( '@stdlib/assert/is-method' );
+var minabs = require( './../lib' );
+
+
+// TESTS //
+
+tape( 'main export is a function', function test( t ) {
+ t.ok( true, __filename );
+ t.strictEqual( typeof minabs, 'function', 'main export is a function' );
+ t.end();
+});
+
+tape( 'attached to the main export is an `assign` method', function test( t ) {
+ t.strictEqual( isMethod( minabs, 'assign' ), true, 'returns expected value' );
+ t.end();
+});
diff --git a/lib/node_modules/@stdlib/stats/minabs/test/test.main.js b/lib/node_modules/@stdlib/stats/minabs/test/test.main.js
new file mode 100644
index 000000000000..3bbcf6b9b835
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/minabs/test/test.main.js
@@ -0,0 +1,753 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+* http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+'use strict';
+
+// MODULES //
+
+var tape = require( 'tape' );
+var isndarrayLike = require( '@stdlib/assert/is-ndarray-like' );
+var ndarray = require( '@stdlib/ndarray/ctor' );
+var zeros = require( '@stdlib/ndarray/zeros' );
+var empty = require( '@stdlib/ndarray/empty' );
+var ndarray2array = require( '@stdlib/ndarray/to-array' );
+var getDType = require( '@stdlib/ndarray/dtype' );
+var getShape = require( '@stdlib/ndarray/shape' );
+var getOrder = require( '@stdlib/ndarray/order' );
+var minabs = require( './../lib' );
+
+
+// TESTS //
+
+tape( 'main export is a function', function test( t ) {
+ t.ok( true, __filename );
+ t.strictEqual( typeof minabs, 'function', 'main export is a function' );
+ t.end();
+});
+
+tape( 'the function throws an error if provided a first argument which is not an ndarray-like object', function test( t ) {
+ var values;
+ var i;
+
+ values = [
+ '5',
+ 5,
+ NaN,
+ true,
+ false,
+ null,
+ void 0,
+ [],
+ {},
+ function noop() {}
+ ];
+ for ( i = 0; i < values.length; i++ ) {
+ t.throws( badValue( values[ i ] ), TypeError, 'throws an error when provided ' + values[ i ] );
+ }
+ t.end();
+
+ function badValue( value ) {
+ return function badValue() {
+ minabs( value );
+ };
+ }
+});
+
+tape( 'the function throws an error if provided a first argument which is not an ndarray-like object (options)', function test( t ) {
+ var values;
+ var i;
+
+ values = [
+ '5',
+ 5,
+ NaN,
+ true,
+ false,
+ null,
+ void 0,
+ [],
+ {},
+ function noop() {}
+ ];
+ for ( i = 0; i < values.length; i++ ) {
+ t.throws( badValue( values[ i ] ), TypeError, 'throws an error when provided ' + values[ i ] );
+ }
+ t.end();
+
+ function badValue( value ) {
+ return function badValue() {
+ minabs( value, {} );
+ };
+ }
+});
+
+tape( 'the function throws an error if provided a first argument which is not an ndarray-like object having a supported data type', function test( t ) {
+ var values;
+ var i;
+
+ values = [
+ empty( [ 2, 2 ], {
+ 'dtype': 'bool'
+ })
+ ];
+ for ( i = 0; i < values.length; i++ ) {
+ t.throws( badValue( values[ i ] ), TypeError, 'throws an error when provided ' + values[ i ] );
+ }
+ t.end();
+
+ function badValue( value ) {
+ return function badValue() {
+ minabs( value );
+ };
+ }
+});
+
+tape( 'the function throws an error if provided a first argument which is not an ndarray-like object having a supported data type (options)', function test( t ) {
+ var values;
+ var i;
+
+ values = [
+ empty( [ 2, 2 ], {
+ 'dtype': 'bool'
+ })
+ ];
+ for ( i = 0; i < values.length; i++ ) {
+ t.throws( badValue( values[ i ] ), TypeError, 'throws an error when provided ' + values[ i ] );
+ }
+ t.end();
+
+ function badValue( value ) {
+ return function badValue() {
+ minabs( value, {} );
+ };
+ }
+});
+
+tape( 'the function throws an error if provided a second argument which is not an object', function test( t ) {
+ var values;
+ var x;
+ var i;
+
+ x = zeros( [ 2, 2 ], {
+ 'dtype': 'generic'
+ });
+
+ values = [
+ '5',
+ 5,
+ NaN,
+ true,
+ false,
+ null,
+ void 0,
+ [],
+ function noop() {}
+ ];
+ for ( i = 0; i < values.length; i++ ) {
+ t.throws( badValue( values[ i ] ), TypeError, 'throws an error when provided ' + values[ i ] );
+ }
+ t.end();
+
+ function badValue( value ) {
+ return function badValue() {
+ minabs( x, value );
+ };
+ }
+});
+
+tape( 'the function throws an error if provided a `dtype` option which is not a supported data type', function test( t ) {
+ var values;
+ var x;
+ var i;
+
+ x = zeros( [ 2, 2 ], {
+ 'dtype': 'generic'
+ });
+
+ values = [
+ 'foo',
+ 'bar',
+ 'beep',
+ 'boop'
+ ];
+ for ( i = 0; i < values.length; i++ ) {
+ t.throws( badValue( values[ i ] ), TypeError, 'throws an error when provided ' + values[ i ] );
+ }
+ t.end();
+
+ function badValue( value ) {
+ return function badValue() {
+ minabs( x, {
+ 'dtype': value
+ });
+ };
+ }
+});
+
+tape( 'the function throws an error if provided a `keepdims` option which is not a boolean', function test( t ) {
+ var values;
+ var x;
+ var i;
+
+ x = zeros( [ 2, 2 ], {
+ 'dtype': 'generic'
+ });
+
+ values = [
+ '5',
+ 5,
+ NaN,
+ null,
+ void 0,
+ [],
+ {},
+ function noop() {}
+ ];
+ for ( i = 0; i < values.length; i++ ) {
+ t.throws( badValue( values[ i ] ), TypeError, 'throws an error when provided ' + values[ i ] );
+ }
+ t.end();
+
+ function badValue( value ) {
+ return function badValue() {
+ minabs( x, {
+ 'keepdims': value
+ });
+ };
+ }
+});
+
+tape( 'the function throws an error if provided a `dims` option which is not an array-like object of integers', function test( t ) {
+ var values;
+ var x;
+ var i;
+
+ x = zeros( [ 2, 2 ], {
+ 'dtype': 'generic'
+ });
+
+ values = [
+ '5',
+ 5,
+ NaN,
+ true,
+ false,
+ null,
+ void 0,
+ [ 'a' ],
+ {},
+ function noop() {}
+ ];
+ for ( i = 0; i < values.length; i++ ) {
+ t.throws( badValue( values[ i ] ), TypeError, 'throws an error when provided ' + values[ i ] );
+ }
+ t.end();
+
+ function badValue( value ) {
+ return function badValue() {
+ minabs( x, {
+ 'dims': value
+ });
+ };
+ }
+});
+
+tape( 'the function throws an error if provided a `dims` option which contains out-of-bounds indices', function test( t ) {
+ var values;
+ var x;
+ var i;
+
+ x = zeros( [ 2, 2 ], {
+ 'dtype': 'generic'
+ });
+
+ values = [
+ [ -10 ],
+ [ 0, 20 ],
+ [ 20 ]
+ ];
+ for ( i = 0; i < values.length; i++ ) {
+ t.throws( badValue( values[ i ] ), RangeError, 'throws an error when provided ' + values[ i ] );
+ }
+ t.end();
+
+ function badValue( value ) {
+ return function badValue() {
+ minabs( x, {
+ 'dims': value
+ });
+ };
+ }
+});
+
+tape( 'the function throws an error if provided a `dims` option which contains too many indices', function test( t ) {
+ var values;
+ var x;
+ var i;
+
+ x = zeros( [ 2, 2 ], {
+ 'dtype': 'generic'
+ });
+
+ values = [
+ [ 0, 1, 2 ],
+ [ 0, 1, 2, 3 ]
+ ];
+ for ( i = 0; i < values.length; i++ ) {
+ t.throws( badValue( values[ i ] ), RangeError, 'throws an error when provided ' + values[ i ] );
+ }
+ t.end();
+
+ function badValue( value ) {
+ return function badValue() {
+ minabs( x, {
+ 'dims': value
+ });
+ };
+ }
+});
+
+tape( 'the function throws an error if provided a `dims` option which contains duplicate indices', function test( t ) {
+ var values;
+ var x;
+ var i;
+
+ x = zeros( [ 2, 2 ], {
+ 'dtype': 'generic'
+ });
+
+ values = [
+ [ 0, 0 ],
+ [ 1, 1 ],
+ [ 0, 1, 0 ],
+ [ 1, 0, 1 ]
+ ];
+ for ( i = 0; i < values.length; i++ ) {
+ t.throws( badValue( values[ i ] ), Error, 'throws an error when provided ' + values[ i ] );
+ }
+ t.end();
+
+ function badValue( value ) {
+ return function badValue() {
+ minabs( x, {
+ 'dims': value
+ });
+ };
+ }
+});
+
+tape( 'the function performs a reduction on an ndarray (default, row-major)', function test( t ) {
+ var expected;
+ var actual;
+ var xbuf;
+ var x;
+
+ xbuf = [ -1.0, 2.0, -3.0, 4.0 ];
+ x = new ndarray( 'generic', xbuf, [ 2, 2 ], [ 2, 1 ], 0, 'row-major' );
+
+ actual = minabs( x );
+ expected = 1.0;
+
+ t.strictEqual( isndarrayLike( actual ), true, 'returns expected value' );
+ t.strictEqual( getDType( actual ), 'generic', 'returns expected value' );
+ t.deepEqual( getShape( actual ), [], 'returns expected value' );
+ t.strictEqual( getOrder( actual ), getOrder( x ), 'returns expected value' );
+ t.strictEqual( actual.get(), expected, 'returns expected value' );
+
+ t.end();
+});
+
+tape( 'the function performs a reduction on an ndarray (default, column-major)', function test( t ) {
+ var expected;
+ var actual;
+ var xbuf;
+ var x;
+
+ xbuf = [ -1.0, 2.0, -3.0, 4.0 ];
+ x = new ndarray( 'generic', xbuf, [ 2, 2 ], [ 1, 2 ], 0, 'column-major' );
+
+ actual = minabs( x );
+ expected = 1.0;
+
+ t.strictEqual( isndarrayLike( actual ), true, 'returns expected value' );
+ t.strictEqual( getDType( actual ), 'generic', 'returns expected value' );
+ t.deepEqual( getShape( actual ), [], 'returns expected value' );
+ t.strictEqual( getOrder( actual ), getOrder( x ), 'returns expected value' );
+ t.strictEqual( actual.get(), expected, 'returns expected value' );
+
+ t.end();
+});
+
+tape( 'the function performs a reduction on an ndarray (all dimensions, row-major)', function test( t ) {
+ var expected;
+ var actual;
+ var xbuf;
+ var x;
+
+ xbuf = [ -1.0, 2.0, -3.0, 4.0 ];
+ x = new ndarray( 'generic', xbuf, [ 2, 2 ], [ 2, 1 ], 0, 'row-major' );
+
+ actual = minabs( x, {
+ 'dims': [ 0, 1 ]
+ });
+ expected = 1.0;
+
+ t.strictEqual( isndarrayLike( actual ), true, 'returns expected value' );
+ t.strictEqual( getDType( actual ), 'generic', 'returns expected value' );
+ t.deepEqual( getShape( actual ), [], 'returns expected value' );
+ t.strictEqual( getOrder( actual ), getOrder( x ), 'returns expected value' );
+ t.strictEqual( actual.get(), expected, 'returns expected value' );
+
+ xbuf = [ -1.0, 2.0, -3.0, 4.0 ];
+ x = new ndarray( 'generic', xbuf, [ 2, 2 ], [ 2, 1 ], 0, 'row-major' );
+
+ actual = minabs( x, {
+ 'dims': [ 0, 1 ],
+ 'keepdims': false
+ });
+ expected = 1.0;
+
+ t.strictEqual( isndarrayLike( actual ), true, 'returns expected value' );
+ t.strictEqual( getDType( actual ), 'generic', 'returns expected value' );
+ t.deepEqual( getShape( actual ), [], 'returns expected value' );
+ t.strictEqual( getOrder( actual ), getOrder( x ), 'returns expected value' );
+ t.strictEqual( actual.get(), expected, 'returns expected value' );
+
+ xbuf = [ -1.0, 2.0, -3.0, 4.0 ];
+ x = new ndarray( 'generic', xbuf, [ 2, 2 ], [ 2, 1 ], 0, 'row-major' );
+
+ actual = minabs( x, {
+ 'dims': [ 0, 1 ],
+ 'keepdims': true
+ });
+ expected = [ [ 1.0 ] ];
+
+ t.strictEqual( isndarrayLike( actual ), true, 'returns expected value' );
+ t.strictEqual( getDType( actual ), 'generic', 'returns expected value' );
+ t.deepEqual( getShape( actual ), [ 1, 1 ], 'returns expected value' );
+ t.strictEqual( getOrder( actual ), getOrder( x ), 'returns expected value' );
+ t.deepEqual( ndarray2array( actual ), expected, 'returns expected value' );
+
+ t.end();
+});
+
+tape( 'the function performs a reduction on an ndarray (all dimensions, column-major)', function test( t ) {
+ var expected;
+ var actual;
+ var xbuf;
+ var x;
+
+ xbuf = [ -1.0, 2.0, -3.0, 4.0 ];
+ x = new ndarray( 'generic', xbuf, [ 2, 2 ], [ 1, 2 ], 0, 'column-major' );
+
+ actual = minabs( x, {
+ 'dims': [ 0, 1 ]
+ });
+ expected = 1.0;
+
+ t.strictEqual( isndarrayLike( actual ), true, 'returns expected value' );
+ t.strictEqual( getDType( actual ), 'generic', 'returns expected value' );
+ t.deepEqual( getShape( actual ), [], 'returns expected value' );
+ t.strictEqual( getOrder( actual ), getOrder( x ), 'returns expected value' );
+ t.strictEqual( actual.get(), expected, 'returns expected value' );
+
+ xbuf = [ -1.0, 2.0, -3.0, 4.0 ];
+ x = new ndarray( 'generic', xbuf, [ 2, 2 ], [ 1, 2 ], 0, 'column-major' );
+
+ actual = minabs( x, {
+ 'dims': [ 0, 1 ],
+ 'keepdims': false
+ });
+ expected = 1.0;
+
+ t.strictEqual( isndarrayLike( actual ), true, 'returns expected value' );
+ t.strictEqual( getDType( actual ), 'generic', 'returns expected value' );
+ t.deepEqual( getShape( actual ), [], 'returns expected value' );
+ t.strictEqual( getOrder( actual ), getOrder( x ), 'returns expected value' );
+ t.strictEqual( actual.get(), expected, 'returns expected value' );
+
+ xbuf = [ -1.0, 2.0, -3.0, 4.0 ];
+ x = new ndarray( 'generic', xbuf, [ 2, 2 ], [ 1, 2 ], 0, 'column-major' );
+
+ actual = minabs( x, {
+ 'dims': [ 0, 1 ],
+ 'keepdims': true
+ });
+ expected = [ [ 1.0 ] ];
+
+ t.strictEqual( isndarrayLike( actual ), true, 'returns expected value' );
+ t.strictEqual( getDType( actual ), 'generic', 'returns expected value' );
+ t.deepEqual( getShape( actual ), [ 1, 1 ], 'returns expected value' );
+ t.strictEqual( getOrder( actual ), getOrder( x ), 'returns expected value' );
+ t.deepEqual( ndarray2array( actual ), expected, 'returns expected value' );
+
+ t.end();
+});
+
+tape( 'the function performs a reduction on an ndarray (no dimensions, row-major)', function test( t ) {
+ var expected;
+ var actual;
+ var xbuf;
+ var x;
+
+ xbuf = [ -1.0, 2.0, -3.0, 4.0 ];
+ x = new ndarray( 'generic', xbuf, [ 2, 2 ], [ 2, 1 ], 0, 'row-major' );
+
+ actual = minabs( x, {
+ 'dims': [],
+ 'keepdims': false
+ });
+ expected = [ [ 1.0, 2.0 ], [ 3.0, 4.0 ] ];
+
+ t.strictEqual( isndarrayLike( actual ), true, 'returns expected value' );
+ t.strictEqual( getDType( actual ), 'generic', 'returns expected value' );
+ t.deepEqual( getShape( actual ), [ 2, 2 ], 'returns expected value' );
+ t.strictEqual( getOrder( actual ), getOrder( x ), 'returns expected value' );
+ t.deepEqual( ndarray2array( actual ), expected, 'returns expected value' );
+
+ xbuf = [ -1.0, 2.0, -3.0, 4.0 ];
+ x = new ndarray( 'generic', xbuf, [ 2, 2 ], [ 2, 1 ], 0, 'row-major' );
+
+ actual = minabs( x, {
+ 'dims': [],
+ 'keepdims': true
+ });
+ expected = [ [ 1.0, 2.0 ], [ 3.0, 4.0 ] ];
+
+ t.strictEqual( isndarrayLike( actual ), true, 'returns expected value' );
+ t.strictEqual( getDType( actual ), 'generic', 'returns expected value' );
+ t.deepEqual( getShape( actual ), [ 2, 2 ], 'returns expected value' );
+ t.strictEqual( getOrder( actual ), getOrder( x ), 'returns expected value' );
+ t.deepEqual( ndarray2array( actual ), expected, 'returns expected value' );
+
+ t.end();
+});
+
+tape( 'the function performs a reduction on an ndarray (no dimensions, column-major)', function test( t ) {
+ var expected;
+ var actual;
+ var xbuf;
+ var x;
+
+ xbuf = [ -1.0, 2.0, -3.0, 4.0 ];
+ x = new ndarray( 'generic', xbuf, [ 2, 2 ], [ 1, 2 ], 0, 'column-major' );
+
+ actual = minabs( x, {
+ 'dims': [],
+ 'keepdims': false
+ });
+ expected = [ [ 1.0, 3.0 ], [ 2.0, 4.0 ] ];
+
+ t.strictEqual( isndarrayLike( actual ), true, 'returns expected value' );
+ t.strictEqual( getDType( actual ), 'generic', 'returns expected value' );
+ t.deepEqual( getShape( actual ), [ 2, 2 ], 'returns expected value' );
+ t.strictEqual( getOrder( actual ), getOrder( x ), 'returns expected value' );
+ t.deepEqual( ndarray2array( actual ), expected, 'returns expected value' );
+
+ xbuf = [ -1.0, 2.0, -3.0, 4.0 ];
+ x = new ndarray( 'generic', xbuf, [ 2, 2 ], [ 1, 2 ], 0, 'column-major' );
+
+ actual = minabs( x, {
+ 'dims': [],
+ 'keepdims': true
+ });
+ expected = [ [ 1.0, 3.0 ], [ 2.0, 4.0 ] ];
+
+ t.strictEqual( isndarrayLike( actual ), true, 'returns expected value' );
+ t.strictEqual( getDType( actual ), 'generic', 'returns expected value' );
+ t.deepEqual( getShape( actual ), [ 2, 2 ], 'returns expected value' );
+ t.strictEqual( getOrder( actual ), getOrder( x ), 'returns expected value' );
+ t.deepEqual( ndarray2array( actual ), expected, 'returns expected value' );
+
+ t.end();
+});
+
+tape( 'the function supports specifying reduction dimensions (row-major)', function test( t ) {
+ var expected;
+ var actual;
+ var xbuf;
+ var x;
+
+ xbuf = [ -1.0, 2.0, -3.0, 4.0 ];
+ x = new ndarray( 'generic', xbuf, [ 2, 2 ], [ 2, 1 ], 0, 'row-major' );
+
+ actual = minabs( x, {
+ 'dims': [ 0 ],
+ 'keepdims': false
+ });
+ expected = [ 1.0, 2.0 ];
+
+ t.strictEqual( isndarrayLike( actual ), true, 'returns expected value' );
+ t.strictEqual( getDType( actual ), 'generic', 'returns expected value' );
+ t.deepEqual( getShape( actual ), [ 2 ], 'returns expected value' );
+ t.strictEqual( getOrder( actual ), getOrder( x ), 'returns expected value' );
+ t.deepEqual( ndarray2array( actual ), expected, 'returns expected value' );
+
+ xbuf = [ -1.0, 2.0, -3.0, 4.0 ];
+ x = new ndarray( 'generic', xbuf, [ 2, 2 ], [ 2, 1 ], 0, 'row-major' );
+
+ actual = minabs( x, {
+ 'dims': [ 0 ],
+ 'keepdims': true
+ });
+ expected = [ [ 1.0, 2.0 ] ];
+
+ t.strictEqual( isndarrayLike( actual ), true, 'returns expected value' );
+ t.strictEqual( getDType( actual ), 'generic', 'returns expected value' );
+ t.deepEqual( getShape( actual ), [ 1, 2 ], 'returns expected value' );
+ t.strictEqual( getOrder( actual ), getOrder( x ), 'returns expected value' );
+ t.deepEqual( ndarray2array( actual ), expected, 'returns expected value' );
+
+ xbuf = [ -1.0, 2.0, -3.0, 4.0 ];
+ x = new ndarray( 'generic', xbuf, [ 2, 2 ], [ 2, 1 ], 0, 'row-major' );
+
+ actual = minabs( x, {
+ 'dims': [ 1 ],
+ 'keepdims': false
+ });
+ expected = [ 1.0, 3.0 ];
+
+ t.strictEqual( isndarrayLike( actual ), true, 'returns expected value' );
+ t.strictEqual( getDType( actual ), 'generic', 'returns expected value' );
+ t.deepEqual( getShape( actual ), [ 2 ], 'returns expected value' );
+ t.strictEqual( getOrder( actual ), getOrder( x ), 'returns expected value' );
+ t.deepEqual( ndarray2array( actual ), expected, 'returns expected value' );
+
+ xbuf = [ -1.0, 2.0, -3.0, 4.0 ];
+ x = new ndarray( 'generic', xbuf, [ 2, 2 ], [ 2, 1 ], 0, 'row-major' );
+
+ actual = minabs( x, {
+ 'dims': [ 1 ],
+ 'keepdims': true
+ });
+ expected = [ [ 1.0 ], [ 3.0 ] ];
+
+ t.strictEqual( isndarrayLike( actual ), true, 'returns expected value' );
+ t.strictEqual( getDType( actual ), 'generic', 'returns expected value' );
+ t.deepEqual( getShape( actual ), [ 2, 1 ], 'returns expected value' );
+ t.strictEqual( getOrder( actual ), getOrder( x ), 'returns expected value' );
+ t.deepEqual( ndarray2array( actual ), expected, 'returns expected value' );
+
+ t.end();
+});
+
+tape( 'the function supports specifying reduction dimensions (column-major)', function test( t ) {
+ var expected;
+ var actual;
+ var xbuf;
+ var x;
+
+ xbuf = [ -1.0, 2.0, -3.0, 4.0 ];
+ x = new ndarray( 'generic', xbuf, [ 2, 2 ], [ 1, 2 ], 0, 'column-major' );
+
+ actual = minabs( x, {
+ 'dims': [ 0 ],
+ 'keepdims': false
+ });
+ expected = [ 1.0, 3.0 ];
+
+ t.strictEqual( isndarrayLike( actual ), true, 'returns expected value' );
+ t.strictEqual( getDType( actual ), 'generic', 'returns expected value' );
+ t.deepEqual( getShape( actual ), [ 2 ], 'returns expected value' );
+ t.strictEqual( getOrder( actual ), getOrder( x ), 'returns expected value' );
+ t.deepEqual( ndarray2array( actual ), expected, 'returns expected value' );
+
+ xbuf = [ -1.0, 2.0, -3.0, 4.0 ];
+ x = new ndarray( 'generic', xbuf, [ 2, 2 ], [ 1, 2 ], 0, 'column-major' );
+
+ actual = minabs( x, {
+ 'dims': [ 0 ],
+ 'keepdims': true
+ });
+ expected = [ [ 1.0, 3.0 ] ];
+
+ t.strictEqual( isndarrayLike( actual ), true, 'returns expected value' );
+ t.strictEqual( getDType( actual ), 'generic', 'returns expected value' );
+ t.deepEqual( getShape( actual ), [ 1, 2 ], 'returns expected value' );
+ t.strictEqual( getOrder( actual ), getOrder( x ), 'returns expected value' );
+ t.deepEqual( ndarray2array( actual ), expected, 'returns expected value' );
+
+ xbuf = [ -1.0, 2.0, -3.0, 4.0 ];
+ x = new ndarray( 'generic', xbuf, [ 2, 2 ], [ 1, 2 ], 0, 'column-major' );
+
+ actual = minabs( x, {
+ 'dims': [ 1 ],
+ 'keepdims': false
+ });
+ expected = [ 1.0, 2.0 ];
+
+ t.strictEqual( isndarrayLike( actual ), true, 'returns expected value' );
+ t.strictEqual( getDType( actual ), 'generic', 'returns expected value' );
+ t.deepEqual( getShape( actual ), [ 2 ], 'returns expected value' );
+ t.strictEqual( getOrder( actual ), getOrder( x ), 'returns expected value' );
+ t.deepEqual( ndarray2array( actual ), expected, 'returns expected value' );
+
+ xbuf = [ -1.0, 2.0, -3.0, 4.0 ];
+ x = new ndarray( 'generic', xbuf, [ 2, 2 ], [ 1, 2 ], 0, 'column-major' );
+
+ actual = minabs( x, {
+ 'dims': [ 1 ],
+ 'keepdims': true
+ });
+ expected = [ [ 1.0 ], [ 2.0 ] ];
+
+ t.strictEqual( isndarrayLike( actual ), true, 'returns expected value' );
+ t.strictEqual( getDType( actual ), 'generic', 'returns expected value' );
+ t.deepEqual( getShape( actual ), [ 2, 1 ], 'returns expected value' );
+ t.strictEqual( getOrder( actual ), getOrder( x ), 'returns expected value' );
+ t.deepEqual( ndarray2array( actual ), expected, 'returns expected value' );
+
+ t.end();
+});
+
+tape( 'the function supports specifying the output array data type', function test( t ) {
+ var expected;
+ var actual;
+ var xbuf;
+ var x;
+
+ xbuf = [ -1.0, 2.0, -3.0, 4.0 ];
+ x = new ndarray( 'generic', xbuf, [ 2, 2 ], [ 2, 1 ], 0, 'row-major' );
+
+ actual = minabs( x, {
+ 'dtype': 'float64'
+ });
+ expected = 1.0;
+
+ t.strictEqual( isndarrayLike( actual ), true, 'returns expected value' );
+ t.strictEqual( getDType( actual ), 'float64', 'returns expected value' );
+ t.deepEqual( getShape( actual ), [], 'returns expected value' );
+ t.strictEqual( getOrder( actual ), getOrder( x ), 'returns expected value' );
+ t.strictEqual( actual.get(), expected, 'returns expected value' );
+
+ xbuf = [ -1.0, 2.0, -3.0, 4.0 ];
+ x = new ndarray( 'generic', xbuf, [ 2, 2 ], [ 1, 2 ], 0, 'column-major' );
+
+ actual = minabs( x, {
+ 'dtype': 'float64'
+ });
+ expected = 1.0;
+
+ t.strictEqual( isndarrayLike( actual ), true, 'returns expected value' );
+ t.strictEqual( getDType( actual ), 'float64', 'returns expected value' );
+ t.deepEqual( getShape( actual ), [], 'returns expected value' );
+ t.strictEqual( getOrder( actual ), getOrder( x ), 'returns expected value' );
+ t.strictEqual( actual.get(), expected, 'returns expected value' );
+
+ t.end();
+});