diff --git a/lib/node_modules/@stdlib/blas/ext/cusome/README.md b/lib/node_modules/@stdlib/blas/ext/cusome/README.md
new file mode 100644
index 000000000000..310989a611cf
--- /dev/null
+++ b/lib/node_modules/@stdlib/blas/ext/cusome/README.md
@@ -0,0 +1,202 @@
+
+
+# cusome
+
+> Cumulatively test whether at least `k` elements along one or more [ndarray][@stdlib/ndarray/ctor] dimensions are truthy.
+
+
+
+## Usage
+
+```javascript
+var cusome = require( '@stdlib/blas/ext/cusome' );
+```
+
+#### cusome( x, k\[, options] )
+
+Cumulatively tests whether at least `k` elements along one or more [ndarray][@stdlib/ndarray/ctor] dimensions are truthy.
+
+```javascript
+var array = require( '@stdlib/ndarray/array' );
+
+var x = array( [ 0.0, 1.0, 1.0, 0.0 ] );
+
+var y = cusome( x, 2 );
+// returns [ false, false, true, true ]
+```
+
+The function has the following parameters:
+
+- **x**: input [ndarray][@stdlib/ndarray/ctor].
+- **k**: minimum number of truthy elements. May be either a scalar value or an [ndarray][@stdlib/ndarray/ctor] having an integer index or "generic" [data type][@stdlib/ndarray/dtypes]. If provided an [ndarray][@stdlib/ndarray/ctor], the value must have a shape which is [broadcast-compatible][@stdlib/ndarray/base/broadcast-shapes] with the complement of the shape defined by `options.dims`. For example, given the input shape `[2, 3, 4]` and `options.dims=[0]`, an [ndarray][@stdlib/ndarray/ctor] value must have a shape which is [broadcast-compatible][@stdlib/ndarray/base/broadcast-shapes] with the shape `[3, 4]`. Similarly, when performing the operation over all elements in a provided input [ndarray][@stdlib/ndarray/ctor], an [ndarray][@stdlib/ndarray/ctor] value must be a zero-dimensional [ndarray][@stdlib/ndarray/ctor].
+- **options**: function options (_optional_).
+
+The function accepts the following options:
+
+- **dims**: list of dimensions over which to perform operation. If not provided, the function performs the operation over all elements in a provided input [ndarray][@stdlib/ndarray/ctor].
+- **dtype**: output ndarray [data type][@stdlib/ndarray/dtypes]. Must be a boolean or "generic" [data type][@stdlib/ndarray/dtypes].
+
+By default, the function performs the operation over all elements in a provided input [ndarray][@stdlib/ndarray/ctor]. To perform the operation over specific dimensions, provide a `dims` option.
+
+```javascript
+var array = require( '@stdlib/ndarray/array' );
+
+var x = array( [ 1.0, 1.0, 0.0, 1.0 ], {
+ 'shape': [ 2, 2 ],
+ 'order': 'row-major'
+});
+
+var y = cusome( x, 2, {
+ 'dims': [ 0 ]
+});
+// returns [ [ false, false ], [ false, true ] ]
+
+y = cusome( x, 2, {
+ 'dims': [ 1 ]
+});
+// returns [ [ false, true ], [ false, false ] ]
+
+y = cusome( x, 2, {
+ 'dims': [ 0, 1 ]
+});
+// returns [ [ false, true ], [ true, true ] ]
+```
+
+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( [ 0.0, 1.0, 1.0, 0.0 ] );
+
+var y = cusome( x, 2, {
+ 'dtype': 'generic'
+});
+// returns
+
+var dt = String( getDType( y ) );
+// returns 'generic'
+```
+
+#### cusome.assign( x, k, out\[, options] )
+
+Cumulatively tests whether at least `k` elements along one or more [ndarray][@stdlib/ndarray/ctor] dimensions are truthy and assigns results to a provided output [ndarray][@stdlib/ndarray/ctor].
+
+```javascript
+var array = require( '@stdlib/ndarray/array' );
+var falses = require( '@stdlib/ndarray/falses' );
+
+var x = array( [ 0.0, 1.0, 1.0, 0.0 ] );
+var y = falses( [ 4 ] );
+
+var out = cusome.assign( x, 2, y );
+// returns [ false, false, true, true ]
+
+var bool = ( out === y );
+// returns true
+```
+
+The method has the following parameters:
+
+- **x**: input [ndarray][@stdlib/ndarray/ctor].
+- **k**: minimum number of truthy elements. May be either a scalar value or an [ndarray][@stdlib/ndarray/ctor] having an integer index or "generic" [data type][@stdlib/ndarray/dtypes]. If provided an [ndarray][@stdlib/ndarray/ctor], the value must have a shape which is [broadcast-compatible][@stdlib/ndarray/base/broadcast-shapes] with the complement of the shape defined by `options.dims`. For example, given the input shape `[2, 3, 4]` and `options.dims=[0]`, an [ndarray][@stdlib/ndarray/ctor] value must have a shape which is [broadcast-compatible][@stdlib/ndarray/base/broadcast-shapes] with the shape `[3, 4]`. Similarly, when performing the operation over all elements in a provided input [ndarray][@stdlib/ndarray/ctor], an [ndarray][@stdlib/ndarray/ctor] value must be a zero-dimensional [ndarray][@stdlib/ndarray/ctor].
+- **out**: output [ndarray][@stdlib/ndarray/ctor].
+- **options**: function options (_optional_).
+
+The method accepts the following options:
+
+- **dims**: list of dimensions over which to perform operation. If not provided, the function performs the operation over all elements in a provided input [ndarray][@stdlib/ndarray/ctor].
+
+
+
+
+
+
+
+## Notes
+
+- Both functions iterate over [ndarray][@stdlib/ndarray/ctor] elements according to the memory layout of the input [ndarray][@stdlib/ndarray/ctor]. Accordingly, performance degradation is possible when operating over multiple dimensions of a large non-contiguous multi-dimensional input [ndarray][@stdlib/ndarray/ctor]. In such scenarios, one may want to copy an input [ndarray][@stdlib/ndarray/ctor] to contiguous memory before performing the operation.
+- 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 a boolean or "generic" [data type][@stdlib/ndarray/dtypes]. For the `assign` method, the output [ndarray][@stdlib/ndarray/ctor] is allowed to have any supported output [data type][@stdlib/ndarray/dtypes].
+- Both functions explicitly treat `NaN` values as falsy.
+
+
+
+
+
+
+
+## Examples
+
+
+
+```javascript
+var bernoulli = require( '@stdlib/random/bernoulli' );
+var getDType = require( '@stdlib/ndarray/dtype' );
+var ndarray2array = require( '@stdlib/ndarray/to-array' );
+var cusome = require( '@stdlib/blas/ext/cusome' );
+
+// Generate an ndarray of random numbers:
+var x = bernoulli( [ 5, 5 ], 0.3, {
+ 'dtype': 'generic'
+});
+console.log( ndarray2array( x ) );
+
+// Perform operation:
+var y = cusome( x, 2, {
+ '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/blas/ext/cusome/benchmark/benchmark.assign.js b/lib/node_modules/@stdlib/blas/ext/cusome/benchmark/benchmark.assign.js
new file mode 100644
index 000000000000..79d54eadcf26
--- /dev/null
+++ b/lib/node_modules/@stdlib/blas/ext/cusome/benchmark/benchmark.assign.js
@@ -0,0 +1,111 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2026 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 isBoolean = require( '@stdlib/assert/is-boolean' ).isPrimitive;
+var pow = require( '@stdlib/math/base/special/pow' );
+var falsesLike = require( '@stdlib/ndarray/falses-like' );
+var zeros = require( '@stdlib/ndarray/zeros' );
+var format = require( '@stdlib/string/format' );
+var pkg = require( './../package.json' ).name;
+var cusome = 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 = zeros( [ len ], options );
+ out = falsesLike( x, {
+ 'dtype': 'bool'
+ });
+
+ 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 = cusome.assign( x, 2, out );
+ if ( typeof o !== 'object' ) {
+ b.fail( 'should return an ndarray' );
+ }
+ }
+ b.toc();
+ if ( !isBoolean( o.get( i%len ) ) ) {
+ b.fail( 'should return a boolean' );
+ }
+ 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( format( '%s:assign:dtype=%s,len=%d', pkg, options.dtype, len ), f );
+ }
+}
+
+main();
diff --git a/lib/node_modules/@stdlib/blas/ext/cusome/benchmark/benchmark.js b/lib/node_modules/@stdlib/blas/ext/cusome/benchmark/benchmark.js
new file mode 100644
index 000000000000..10cd0bdbc9d9
--- /dev/null
+++ b/lib/node_modules/@stdlib/blas/ext/cusome/benchmark/benchmark.js
@@ -0,0 +1,103 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2026 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 isBoolean = require( '@stdlib/assert/is-boolean' ).isPrimitive;
+var pow = require( '@stdlib/math/base/special/pow' );
+var zeros = require( '@stdlib/ndarray/zeros' );
+var format = require( '@stdlib/string/format' );
+var pkg = require( './../package.json' ).name;
+var cusome = 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 = zeros( [ len ], options );
+ 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 = cusome( x, 2 );
+ if ( typeof o !== 'object' ) {
+ b.fail( 'should return an ndarray' );
+ }
+ }
+ b.toc();
+ if ( !isBoolean( o.get( i%len ) ) ) {
+ b.fail( 'should return a boolean' );
+ }
+ 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( format( '%s:dtype=%s,len=%d', pkg, options.dtype, len ), f );
+ }
+}
+
+main();
diff --git a/lib/node_modules/@stdlib/blas/ext/cusome/docs/repl.txt b/lib/node_modules/@stdlib/blas/ext/cusome/docs/repl.txt
new file mode 100644
index 000000000000..775b2b5122bd
--- /dev/null
+++ b/lib/node_modules/@stdlib/blas/ext/cusome/docs/repl.txt
@@ -0,0 +1,92 @@
+
+{{alias}}( x, k[, options] )
+ Cumulatively tests whether at least `k` elements along one or more ndarray
+ dimensions are truthy.
+
+ Parameters
+ ----------
+ x: ndarray
+ Input array.
+
+ k: ndarray|integer
+ Minimum number of truthy elements. May be either a scalar value or an
+ ndarray having an integer index or "generic" data type. If provided an
+ ndarray, the value must have a shape which is broadcast compatible with
+ the complement of the shape defined by `options.dims`. For example,
+ given the input shape [2, 3, 4] and `options.dims=[0]`, an ndarray
+ value must have a shape which is broadcast compatible with the shape
+ [3, 4]. Similarly, when performing the operation over all elements in
+ a provided input ndarray, an ndarray value must be a zero-dimensional
+ ndarray.
+
+ options: Object (optional)
+ Function options.
+
+ options.dtype: string|DataType (optional)
+ Output array data type. Must be a boolean or "generic" data type.
+
+ options.dims: Array (optional)
+ List of dimensions over which to perform operation. If not provided, the
+ function performs the operation over all elements in a provided input
+ ndarray.
+
+ Returns
+ -------
+ out: ndarray
+ Output array.
+
+ Examples
+ --------
+ > var x = {{alias:@stdlib/ndarray/array}}( [ 0.0, 1.0, 1.0, 0.0 ] );
+ > var y = {{alias}}( x, 2 )
+ [ false, false, true, true ]
+
+
+{{alias}}.assign( x, k, out[, options] )
+ Cumulatively tests whether at least `k` elements along one or more ndarray
+ dimensions are truthy and assigns results to a provided output ndarray.
+
+ Parameters
+ ----------
+ x: ndarray
+ Input array.
+
+ k: ndarray|integer
+ Minimum number of truthy elements. May be either a scalar value or an
+ ndarray having an integer index or "generic" data type. If provided an
+ ndarray, the value must have a shape which is broadcast compatible with
+ the complement of the shape defined by `options.dims`. For example,
+ given the input shape [2, 3, 4] and `options.dims=[0]`, an ndarray
+ value must have a shape which is broadcast compatible with the shape
+ [3, 4]. Similarly, when performing the operation over all elements in
+ a provided input ndarray, an ndarray value must be a zero-dimensional
+ ndarray.
+
+ out: ndarray
+ Output array.
+
+ options: Object (optional)
+ Function options.
+
+ options.dims: Array (optional)
+ List of dimensions over which to perform operation. If not provided, the
+ function performs the operation over all elements in a provided input
+ ndarray.
+
+ Returns
+ -------
+ out: ndarray
+ Output array.
+
+ Examples
+ --------
+ > var x = {{alias:@stdlib/ndarray/array}}( [ 0.0, 1.0, 1.0, 0.0 ] );
+ > var out = {{alias:@stdlib/ndarray/falses}}( [ 4 ] );
+ > var y = {{alias}}.assign( x, 2, out )
+ [ false, false, true, true ]
+ > var bool = ( out === y )
+ true
+
+ See Also
+ --------
+
diff --git a/lib/node_modules/@stdlib/blas/ext/cusome/docs/types/index.d.ts b/lib/node_modules/@stdlib/blas/ext/cusome/docs/types/index.d.ts
new file mode 100644
index 000000000000..c2090c7d0933
--- /dev/null
+++ b/lib/node_modules/@stdlib/blas/ext/cusome/docs/types/index.d.ts
@@ -0,0 +1,142 @@
+/*
+* @license Apache-2.0
+*
+* Copyright (c) 2026 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
+
+///
+
+import { ArrayLike } from '@stdlib/types/array';
+import { BooleanAndGenericDataType as DataType, typedndarray } from '@stdlib/types/ndarray';
+
+/**
+* Input array.
+*/
+type InputArray = typedndarray;
+
+/**
+* Minimum number of truthy elements.
+*/
+type K = typedndarray | number;
+
+/**
+* Output array.
+*/
+type OutputArray = typedndarray;
+
+/**
+* Interface defining "base" options.
+*/
+interface BaseOptions {
+ /**
+ * List of dimensions over which to perform operation.
+ */
+ dims?: ArrayLike;
+}
+
+/**
+* Interface defining options.
+*/
+interface Options extends BaseOptions {
+ /**
+ * Output array data type.
+ */
+ dtype?: DataType;
+}
+
+/**
+* Interface for performing an operation on an ndarray.
+*/
+interface Unary {
+ /**
+ * Cumulatively tests whether at least `k` elements along one or more ndarray dimensions are truthy.
+ *
+ * @param x - input ndarray
+ * @param k - minimum number of truthy elements
+ * @param options - function options
+ * @returns output ndarray
+ *
+ * @example
+ * var array = require( '@stdlib/ndarray/array' );
+ *
+ * var x = array( [ 0.0, 1.0, 1.0, 0.0 ] );
+ *
+ * var y = cusome( x, 2 );
+ * // returns [ false, false, true, true ]
+ */
+ ( x: InputArray, k: K, 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`.
+
+ /**
+ * Cumulatively tests whether at least `k` elements along one or more ndarray dimensions are truthy and assigns results to a provided output ndarray.
+ *
+ * @param x - input ndarray
+ * @param k - minimum number of truthy elements
+ * @param out - output ndarray
+ * @param options - function options
+ * @returns output ndarray
+ *
+ * @example
+ * var falses = require( '@stdlib/ndarray/falses' );
+ * var array = require( '@stdlib/ndarray/array' );
+ *
+ * var x = array( [ 0.0, 1.0, 1.0, 0.0 ] );
+ * var y = falses( [ 4 ] );
+ *
+ * var out = cusome.assign( x, 2, y );
+ * // returns [ false, false, true, true ]
+ *
+ * var bool = ( out === y );
+ * // returns true
+ */
+ assign = OutputArray>( x: InputArray, k: K, out: T, options?: BaseOptions ): T;
+}
+
+/**
+* Cumulatively tests whether at least `k` elements along one or more ndarray dimensions are truthy.
+*
+* @param x - input ndarray
+* @param k - minimum number of truthy elements
+* @param options - function options
+* @returns output ndarray
+*
+* @example
+* var array = require( '@stdlib/ndarray/array' );
+*
+* var x = array( [ 0.0, 1.0, 1.0, 0.0 ] );
+*
+* var y = cusome( x, 2 );
+* // returns [ false, false, true, true ]
+*
+* @example
+* var falses = require( '@stdlib/ndarray/falses' );
+* var array = require( '@stdlib/ndarray/array' );
+*
+* var x = array( [ 0.0, 1.0, 1.0, 0.0 ] );
+* var y = falses( [ 4 ] );
+*
+* var out = cusome.assign( x, 2, y );
+* // returns [ false, false, true, true ]
+*
+* var bool = ( out === y );
+* // returns true
+*/
+declare const cusome: Unary;
+
+
+// EXPORTS //
+
+export = cusome;
diff --git a/lib/node_modules/@stdlib/blas/ext/cusome/docs/types/test.ts b/lib/node_modules/@stdlib/blas/ext/cusome/docs/types/test.ts
new file mode 100644
index 000000000000..add44c6dd8d3
--- /dev/null
+++ b/lib/node_modules/@stdlib/blas/ext/cusome/docs/types/test.ts
@@ -0,0 +1,286 @@
+/*
+* @license Apache-2.0
+*
+* Copyright (c) 2026 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 empty = require( '@stdlib/ndarray/empty' );
+import cusome = require( './index' );
+
+
+// TESTS //
+
+// The function returns an ndarray...
+{
+ const x = empty( [ 2, 2 ], {
+ 'dtype': 'float64'
+ });
+ const k = empty( [], {
+ 'dtype': 'int32'
+ });
+
+ cusome( x, 2 ); // $ExpectType OutputArray
+ cusome( x, 2, {} ); // $ExpectType OutputArray
+
+ cusome( x, k ); // $ExpectType OutputArray
+ cusome( x, k, {} ); // $ExpectType OutputArray
+}
+
+// The compiler throws an error if the function is provided a first argument which is not an ndarray...
+{
+ cusome( '5', 2 ); // $ExpectError
+ cusome( 5, 2 ); // $ExpectError
+ cusome( true, 2 ); // $ExpectError
+ cusome( false, 2 ); // $ExpectError
+ cusome( null, 2 ); // $ExpectError
+ cusome( void 0, 2 ); // $ExpectError
+ cusome( {}, 2 ); // $ExpectError
+ cusome( ( x: number ): number => x, 2 ); // $ExpectError
+
+ cusome( '5', 2, {} ); // $ExpectError
+ cusome( 5, 2, {} ); // $ExpectError
+ cusome( true, 2, {} ); // $ExpectError
+ cusome( false, 2, {} ); // $ExpectError
+ cusome( null, 2, {} ); // $ExpectError
+ cusome( void 0, 2, {} ); // $ExpectError
+ cusome( {}, 2, {} ); // $ExpectError
+ cusome( ( x: number ): number => x, 2, {} ); // $ExpectError
+}
+
+// The compiler throws an error if the function is provided a second argument which is not an ndarray or number...
+{
+ const x = empty( [ 2, 2 ], {
+ 'dtype': 'float64'
+ });
+
+ cusome( x, '5' ); // $ExpectError
+ cusome( x, true ); // $ExpectError
+ cusome( x, false ); // $ExpectError
+ cusome( x, null ); // $ExpectError
+ cusome( x, void 0 ); // $ExpectError
+ cusome( x, [] ); // $ExpectError
+ cusome( x, ( x: number ): number => x ); // $ExpectError
+
+ cusome( x, '5', {} ); // $ExpectError
+ cusome( x, true, {} ); // $ExpectError
+ cusome( x, false, {} ); // $ExpectError
+ cusome( x, null, {} ); // $ExpectError
+ cusome( x, void 0, {} ); // $ExpectError
+ cusome( x, [], {} ); // $ExpectError
+ cusome( x, ( x: number ): number => x, {} ); // $ExpectError
+}
+
+// The compiler throws an error if the function is provided a third argument which is not an object...
+{
+ const x = empty( [ 2, 2 ], {
+ 'dtype': 'float64'
+ });
+
+ cusome( x, 2, '5' ); // $ExpectError
+ cusome( x, 2, true ); // $ExpectError
+ cusome( x, 2, false ); // $ExpectError
+ cusome( x, 2, null ); // $ExpectError
+ cusome( x, 2, [] ); // $ExpectError
+ cusome( x, 2, ( x: number ): number => x ); // $ExpectError
+}
+
+// The compiler throws an error if the function is provided an invalid `dtype` option...
+{
+ const x = empty( [ 2, 2 ], {
+ 'dtype': 'float64'
+ });
+
+ cusome( x, 2, { 'dtype': '5' } ); // $ExpectError
+ cusome( x, 2, { 'dtype': 5 } ); // $ExpectError
+ cusome( x, 2, { 'dtype': true } ); // $ExpectError
+ cusome( x, 2, { 'dtype': false } ); // $ExpectError
+ cusome( x, 2, { 'dtype': null } ); // $ExpectError
+ cusome( x, 2, { 'dtype': [] } ); // $ExpectError
+ cusome( x, 2, { 'dtype': {} } ); // $ExpectError
+ cusome( x, 2, { 'dtype': ( x: number ): number => x } ); // $ExpectError
+}
+
+// The compiler throws an error if the function is provided an invalid `dims` option...
+{
+ const x = empty( [ 2, 2 ], {
+ 'dtype': 'float64'
+ });
+
+ cusome( x, 2, { 'dims': '5' } ); // $ExpectError
+ cusome( x, 2, { 'dims': 5 } ); // $ExpectError
+ cusome( x, 2, { 'dims': true } ); // $ExpectError
+ cusome( x, 2, { 'dims': false } ); // $ExpectError
+ cusome( x, 2, { 'dims': null } ); // $ExpectError
+ cusome( x, 2, { 'dims': {} } ); // $ExpectError
+ cusome( x, 2, { 'dims': ( x: number ): number => x } ); // $ExpectError
+}
+
+// The compiler throws an error if the function is provided an unsupported number of arguments...
+{
+ const x = empty( [ 2, 2 ], {
+ 'dtype': 'float64'
+ });
+
+ cusome(); // $ExpectError
+ cusome( x ); // $ExpectError
+ cusome( x, 2, {}, {} ); // $ExpectError
+}
+
+// Attached to the function is an `assign` method which returns an ndarray...
+{
+ const x = empty( [ 2, 2 ], {
+ 'dtype': 'float64'
+ });
+ const k = empty( [], {
+ 'dtype': 'int32'
+ });
+ const out = empty( [ 2, 2 ], {
+ 'dtype': 'bool'
+ });
+
+ cusome.assign( x, 2, out ); // $ExpectType boolndarray
+ cusome.assign( x, 2, out, {} ); // $ExpectType boolndarray
+
+ cusome.assign( x, k, out ); // $ExpectType boolndarray
+ cusome.assign( x, k, out, {} ); // $ExpectType boolndarray
+}
+
+// The compiler throws an error if the `assign` method is provided a first argument which is not an ndarray...
+{
+ const out = empty( [ 2, 2 ], {
+ 'dtype': 'bool'
+ });
+
+ cusome.assign( '5', 2, out ); // $ExpectError
+ cusome.assign( 5, 2, out ); // $ExpectError
+ cusome.assign( true, 2, out ); // $ExpectError
+ cusome.assign( false, 2, out ); // $ExpectError
+ cusome.assign( null, 2, out ); // $ExpectError
+ cusome.assign( void 0, 2, out ); // $ExpectError
+ cusome.assign( {}, 2, out ); // $ExpectError
+ cusome.assign( ( x: number ): number => x, 2, out ); // $ExpectError
+
+ cusome.assign( '5', 2, out, {} ); // $ExpectError
+ cusome.assign( 5, 2, out, {} ); // $ExpectError
+ cusome.assign( true, 2, out, {} ); // $ExpectError
+ cusome.assign( false, 2, out, {} ); // $ExpectError
+ cusome.assign( null, 2, out, {} ); // $ExpectError
+ cusome.assign( void 0, 2, out, {} ); // $ExpectError
+ cusome.assign( {}, 2, out, {} ); // $ExpectError
+ cusome.assign( ( x: number ): number => x, 2, out, {} ); // $ExpectError
+}
+
+// The compiler throws an error if the `assign` method is provided a second argument which is not an ndarray or number...
+{
+ const x = empty( [ 2, 2 ], {
+ 'dtype': 'float64'
+ });
+ const out = empty( [ 2, 2 ], {
+ 'dtype': 'bool'
+ });
+
+ cusome.assign( x, '5', out ); // $ExpectError
+ cusome.assign( x, true, out ); // $ExpectError
+ cusome.assign( x, false, out ); // $ExpectError
+ cusome.assign( x, null, out ); // $ExpectError
+ cusome.assign( x, void 0, out ); // $ExpectError
+ cusome.assign( x, [], out ); // $ExpectError
+ cusome.assign( x, ( x: number ): number => x, out ); // $ExpectError
+
+ cusome.assign( x, '5', out, {} ); // $ExpectError
+ cusome.assign( x, true, out, {} ); // $ExpectError
+ cusome.assign( x, false, out, {} ); // $ExpectError
+ cusome.assign( x, null, out, {} ); // $ExpectError
+ cusome.assign( x, void 0, out, {} ); // $ExpectError
+ cusome.assign( x, [], out, {} ); // $ExpectError
+ cusome.assign( x, ( x: number ): number => x, out, {} ); // $ExpectError
+}
+
+// The compiler throws an error if the `assign` method is provided a third argument which is not an ndarray...
+{
+ const x = empty( [ 2, 2 ], {
+ 'dtype': 'float64'
+ });
+
+ cusome.assign( x, 2, '5' ); // $ExpectError
+ cusome.assign( x, 2, 5 ); // $ExpectError
+ cusome.assign( x, 2, true ); // $ExpectError
+ cusome.assign( x, 2, false ); // $ExpectError
+ cusome.assign( x, 2, null ); // $ExpectError
+ cusome.assign( x, 2, void 0 ); // $ExpectError
+ cusome.assign( x, 2, ( x: number ): number => x ); // $ExpectError
+
+ cusome.assign( x, 2, '5', {} ); // $ExpectError
+ cusome.assign( x, 2, 5, {} ); // $ExpectError
+ cusome.assign( x, 2, true, {} ); // $ExpectError
+ cusome.assign( x, 2, false, {} ); // $ExpectError
+ cusome.assign( x, 2, null, {} ); // $ExpectError
+ cusome.assign( x, 2, void 0, {} ); // $ExpectError
+ cusome.assign( x, 2, ( x: number ): number => x, {} ); // $ExpectError
+}
+
+// The compiler throws an error if the `assign` method is provided a fourth argument which is not an object...
+{
+ const x = empty( [ 2, 2 ], {
+ 'dtype': 'float64'
+ });
+ const out = empty( [ 2, 2 ], {
+ 'dtype': 'bool'
+ });
+
+ cusome.assign( x, 2, out, '5' ); // $ExpectError
+ cusome.assign( x, 2, out, true ); // $ExpectError
+ cusome.assign( x, 2, out, false ); // $ExpectError
+ cusome.assign( x, 2, out, null ); // $ExpectError
+ cusome.assign( x, 2, out, [] ); // $ExpectError
+ cusome.assign( x, 2, out, ( x: number ): number => x ); // $ExpectError
+}
+
+// The compiler throws an error if the `assign` method is provided an invalid `dims` option...
+{
+ const x = empty( [ 2, 2 ], {
+ 'dtype': 'float64'
+ });
+ const out = empty( [ 2, 2 ], {
+ 'dtype': 'bool'
+ });
+
+ cusome.assign( x, 2, out, { 'dims': '5' } ); // $ExpectError
+ cusome.assign( x, 2, out, { 'dims': 5 } ); // $ExpectError
+ cusome.assign( x, 2, out, { 'dims': true } ); // $ExpectError
+ cusome.assign( x, 2, out, { 'dims': false } ); // $ExpectError
+ cusome.assign( x, 2, out, { 'dims': null } ); // $ExpectError
+ cusome.assign( x, 2, out, { 'dims': {} } ); // $ExpectError
+ cusome.assign( x, 2, out, { 'dims': ( x: number ): number => x } ); // $ExpectError
+}
+
+// The compiler throws an error if the `assign` method is provided an unsupported number of arguments...
+{
+ const x = empty( [ 2, 2 ], {
+ 'dtype': 'float64'
+ });
+ const out = empty( [ 2, 2 ], {
+ 'dtype': 'bool'
+ });
+
+ cusome.assign(); // $ExpectError
+ cusome.assign( x ); // $ExpectError
+ cusome.assign( x, 2 ); // $ExpectError
+ cusome.assign( x, 2, out, {}, {} ); // $ExpectError
+}
diff --git a/lib/node_modules/@stdlib/blas/ext/cusome/examples/index.js b/lib/node_modules/@stdlib/blas/ext/cusome/examples/index.js
new file mode 100644
index 000000000000..cb80c2bb053d
--- /dev/null
+++ b/lib/node_modules/@stdlib/blas/ext/cusome/examples/index.js
@@ -0,0 +1,42 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2026 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 bernoulli = require( '@stdlib/random/bernoulli' );
+var getDType = require( '@stdlib/ndarray/dtype' );
+var ndarray2array = require( '@stdlib/ndarray/to-array' );
+var cusome = require( './../lib' );
+
+// Generate an ndarray of random numbers:
+var x = bernoulli( [ 5, 5 ], 0.3, {
+ 'dtype': 'generic'
+});
+console.log( ndarray2array( x ) );
+
+// Perform operation:
+var y = cusome( x, 2, {
+ '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/blas/ext/cusome/lib/assign.js b/lib/node_modules/@stdlib/blas/ext/cusome/lib/assign.js
new file mode 100644
index 000000000000..5b71732bada4
--- /dev/null
+++ b/lib/node_modules/@stdlib/blas/ext/cusome/lib/assign.js
@@ -0,0 +1,159 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2026 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 hasOwnProp = require( '@stdlib/assert/has-own-property' );
+var isPlainObject = require( '@stdlib/assert/is-plain-object' );
+var isInteger = require( '@stdlib/assert/is-integer' ).isPrimitive;
+var isndarrayLike = require( '@stdlib/assert/is-ndarray-like' );
+var broadcastScalar = require( '@stdlib/ndarray/base/broadcast-scalar' );
+var maybeBroadcastArray = require( '@stdlib/ndarray/base/maybe-broadcast-array' );
+var nonCoreShape = require( '@stdlib/ndarray/base/complement-shape' );
+var getShape = require( '@stdlib/ndarray/shape' );
+var getOrder = require( '@stdlib/ndarray/order' );
+var ndims = require( '@stdlib/ndarray/base/ndims' );
+var format = require( '@stdlib/string/format' );
+var defaults = require( '@stdlib/ndarray/defaults' );
+var base = require( './base.js' ).assign;
+
+
+// VARIABLES //
+
+var DEFAULT_DTYPE = defaults.get( 'dtypes.integer_index' );
+
+
+// MAIN //
+
+/**
+* Cumulatively tests whether at least `k` elements along one or more ndarray dimensions are truthy and assigns the results to a provided output ndarray.
+*
+* @param {ndarrayLike} x - input ndarray
+* @param {(ndarrayLike|integer)} k - minimum number of truthy elements
+* @param {ndarrayLike} out - output ndarray
+* @param {Options} [options] - function options
+* @param {IntegerArray} [options.dims] - list of dimensions over which to perform operation
+* @throws {TypeError} first argument must be an ndarray-like object
+* @throws {TypeError} second argument must be either an ndarray-like object or an integer
+* @throws {TypeError} third 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 BooleanArray = require( '@stdlib/array/bool' );
+* var ndarray = require( '@stdlib/ndarray/ctor' );
+*
+* // Create data buffers:
+* var xbuf = new Float64Array( [ 0.0, 1.0, 0.0, 4.0, 3.0, 0.0 ] );
+* var ybuf = new BooleanArray( 6 );
+*
+* // Define the shape of the input array:
+* var shape = [ 3, 1, 2 ];
+*
+* // Define the array strides:
+* var strides = [ 2, 2, 1 ];
+*
+* // Define the index offset:
+* var offset = 0;
+*
+* // Create an input ndarray:
+* var x = new ndarray( 'float64', xbuf, shape, strides, offset, 'row-major' );
+*
+* // Create an output ndarray:
+* var y = new ndarray( 'bool', ybuf, shape, strides, offset, 'row-major' );
+*
+* // Perform operation:
+* var out = assign( x, 2, y );
+* // returns [ [ [ false, false ] ], [ [ false, true ] ], [ [ true, true ] ] ]
+*
+* var bool = ( out === y );
+* // returns true
+*/
+function assign( x, k, out ) {
+ var options;
+ var nargs;
+ var opts;
+ var iflg;
+ var ord;
+ var sh;
+ var v;
+
+ nargs = arguments.length;
+ if ( !isndarrayLike( x ) ) {
+ throw new TypeError( format( 'invalid argument. First argument must be an ndarray. Value: `%s`.', x ) );
+ }
+ // Resolve input ndarray meta data:
+ ord = getOrder( x );
+
+ // Initialize an options object:
+ opts = {};
+
+ // Initialize a flag indicating whether the `k` argument is a scalar:
+ iflg = true;
+
+ // Case: assign( x, k_ndarray, out, ... )
+ if ( isndarrayLike( k ) ) {
+ iflg = false;
+ }
+ // Case: assign( x, ???, out, ... )
+ else if ( !isInteger( k ) ) {
+ throw new TypeError( format( 'invalid argument. Second argument must be either an ndarray or an integer. Value: `%s`.', k ) );
+ }
+ if ( !isndarrayLike( out ) ) {
+ throw new TypeError( format( 'invalid argument. Third argument must be an ndarray. Value: `%s`.', out ) );
+ }
+ // Case: assign( x, k, out, options )
+ if ( nargs > 3 ) {
+ options = arguments[ 3 ];
+ if ( !isPlainObject( options ) ) {
+ throw new TypeError( format( 'invalid argument. Options argument must be an object. Value: `%s`.', options ) );
+ }
+ // Resolve provided options...
+ if ( hasOwnProp( options, 'dims' ) ) {
+ opts.dims = options.dims;
+ }
+ }
+ // Resolve the shape of the non-core dimensions, noting that, when not provided `dims`, the operation is performed across all dimensions:
+ if ( hasOwnProp( opts, 'dims' ) ) {
+ sh = nonCoreShape( getShape( x ), opts.dims );
+ } else {
+ sh = [];
+ }
+ // Broadcast `k` to match the shape of the non-core dimensions, noting that, when not provided `dims`, `k` must be a zero-dimensional ndarray, as the operation is performed across all dimensions...
+ if ( iflg ) {
+ v = broadcastScalar( k, DEFAULT_DTYPE, sh, ord );
+ } else if ( hasOwnProp( opts, 'dims' ) ) {
+ v = maybeBroadcastArray( k, sh );
+ } else if ( ndims( k ) === 0 ) {
+ v = k;
+ } else {
+ throw new TypeError( 'invalid argument. Second argument must be a zero-dimensional ndarray.' );
+ }
+ return base( x, v, out, opts );
+}
+
+
+// EXPORTS //
+
+module.exports = assign;
diff --git a/lib/node_modules/@stdlib/blas/ext/cusome/lib/base.js b/lib/node_modules/@stdlib/blas/ext/cusome/lib/base.js
new file mode 100644
index 000000000000..f205d1e11a41
--- /dev/null
+++ b/lib/node_modules/@stdlib/blas/ext/cusome/lib/base.js
@@ -0,0 +1,116 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2026 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 array-element-newline */
+
+'use strict';
+
+// MODULES //
+
+var dtypes = require( '@stdlib/ndarray/dtypes' );
+var gcusome = require( '@stdlib/blas/ext/base/ndarray/gcusome' );
+var dcusome = require( '@stdlib/blas/ext/base/ndarray/dcusome' );
+var scusome = require( '@stdlib/blas/ext/base/ndarray/scusome' );
+var factory = require( '@stdlib/ndarray/base/unary-strided1d-dispatch-factory' );
+
+
+// VARIABLES //
+
+var idtypes0 = dtypes( 'all' ); // input ndarray
+var idtypes1 = dtypes( 'integer_index_and_generic' ); // minimum number of truthy elements ndarray
+var odtypes = dtypes( 'boolean_and_generic' );
+var policies = {
+ 'output': 'boolean_and_generic',
+ 'casting': 'none'
+};
+var table = {
+ 'types': [
+ 'float64', 'bool', // input, output
+ 'float32', 'bool' // input, output
+
+ // FIXME: add specialized support for `ccusome` and `zcusome` once the corresponding packages are implemented
+ ],
+ 'fcns': [
+ dcusome,
+ scusome
+ ],
+ 'default': gcusome
+};
+var options = {
+ 'strictTraversalOrder': true
+};
+
+
+// MAIN //
+
+/**
+* Cumulatively tests whether at least `k` elements along one or more ndarray dimensions are truthy.
+*
+* @private
+* @name cusome
+* @type {Function}
+* @param {ndarray} x - input ndarray
+* @param {ndarray} k - ndarray containing the minimum number of truthy elements
+* @param {Options} [options] - function options
+* @param {IntegerArray} [options.dims] - list of dimensions over which to perform operation
+* @param {*} [options.dtype] - output ndarray data type
+* @throws {TypeError} first argument must be an ndarray-like object
+* @throws {TypeError} second 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 scalar2ndarray = require( '@stdlib/ndarray/from-scalar' );
+* var ndarray = require( '@stdlib/ndarray/ctor' );
+*
+* // Create a data buffer:
+* var xbuf = new Float64Array( [ 0.0, 1.0, 0.0, 4.0, 3.0, 0.0 ] );
+*
+* // Define the shape of the input array:
+* var sh = [ 3, 1, 2 ];
+*
+* // Define the array strides:
+* var sx = [ 2, 2, 1 ];
+*
+* // Define the index offset:
+* var ox = 0;
+*
+* // Create an input ndarray:
+* var x = new ndarray( 'float64', xbuf, sh, sx, ox, 'row-major' );
+*
+* // Create an ndarray containing the minimum number of truthy elements:
+* var k = scalar2ndarray( 2, {
+* 'dtype': 'int32'
+* });
+*
+* // Perform operation:
+* var out = cusome( x, k );
+* // returns [ [ [ false, false ] ], [ [ false, true ] ], [ [ true, true ] ] ]
+*/
+var cusome = factory( table, [ idtypes0, idtypes1 ], odtypes, policies, options ); // eslint-disable-line max-len
+
+
+// EXPORTS //
+
+module.exports = cusome;
+
+// exports: { "assign": "cusome.assign" }
diff --git a/lib/node_modules/@stdlib/blas/ext/cusome/lib/index.js b/lib/node_modules/@stdlib/blas/ext/cusome/lib/index.js
new file mode 100644
index 000000000000..828b35cbb89d
--- /dev/null
+++ b/lib/node_modules/@stdlib/blas/ext/cusome/lib/index.js
@@ -0,0 +1,67 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2026 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';
+
+/**
+* Cumulatively test whether at least `k` elements along one or more ndarray dimensions are truthy.
+*
+* @module @stdlib/blas/ext/cusome
+*
+* @example
+* var Float64Array = require( '@stdlib/array/float64' );
+* var ndarray = require( '@stdlib/ndarray/ctor' );
+* var cusome = require( '@stdlib/blas/ext/cusome' );
+*
+* // Create a data buffer:
+* var xbuf = new Float64Array( [ 0.0, 1.0, 0.0, 4.0, 3.0, 0.0 ] );
+*
+* // Define the shape of the input array:
+* var sh = [ 3, 1, 2 ];
+*
+* // Define the array strides:
+* var sx = [ 2, 2, 1 ];
+*
+* // Define the index offset:
+* var ox = 0;
+*
+* // Create an input ndarray:
+* var x = new ndarray( 'float64', xbuf, sh, sx, ox, 'row-major' );
+*
+* // Perform operation:
+* var out = cusome( x, 2 );
+* // returns [ [ [ false, false ] ], [ [ false, true ] ], [ [ true, true ] ] ]
+*/
+
+// MODULES //
+
+var setReadOnly = require( '@stdlib/utils/define-nonenumerable-read-only-property' );
+var main = require( './main.js' );
+var assign = require( './assign.js' );
+
+
+// MAIN //
+
+setReadOnly( main, 'assign', assign );
+
+
+// EXPORTS //
+
+module.exports = main;
+
+// exports: { "assign": "main.assign" }
diff --git a/lib/node_modules/@stdlib/blas/ext/cusome/lib/main.js b/lib/node_modules/@stdlib/blas/ext/cusome/lib/main.js
new file mode 100644
index 000000000000..0838e6f456c7
--- /dev/null
+++ b/lib/node_modules/@stdlib/blas/ext/cusome/lib/main.js
@@ -0,0 +1,150 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2026 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 hasOwnProp = require( '@stdlib/assert/has-own-property' );
+var isPlainObject = require( '@stdlib/assert/is-plain-object' );
+var isInteger = require( '@stdlib/assert/is-integer' ).isPrimitive;
+var isndarrayLike = require( '@stdlib/assert/is-ndarray-like' );
+var broadcastScalar = require( '@stdlib/ndarray/base/broadcast-scalar' );
+var maybeBroadcastArray = require( '@stdlib/ndarray/base/maybe-broadcast-array' );
+var nonCoreShape = require( '@stdlib/ndarray/base/complement-shape' );
+var getShape = require( '@stdlib/ndarray/shape' );
+var getOrder = require( '@stdlib/ndarray/order' );
+var ndims = require( '@stdlib/ndarray/base/ndims' );
+var format = require( '@stdlib/string/format' );
+var defaults = require( '@stdlib/ndarray/defaults' );
+var base = require( './base.js' );
+
+
+// VARIABLES //
+
+var DEFAULT_DTYPE = defaults.get( 'dtypes.integer_index' );
+
+
+// MAIN //
+
+/**
+* Cumulatively tests whether at least `k` elements along one or more ndarray dimensions are truthy.
+*
+* @param {ndarrayLike} x - input ndarray
+* @param {(ndarrayLike|integer)} k - minimum number of truthy elements
+* @param {Options} [options] - function options
+* @param {IntegerArray} [options.dims] - list of dimensions over which to perform operation
+* @param {*} [options.dtype] - output ndarray data type
+* @throws {TypeError} first argument must be an ndarray-like object
+* @throws {TypeError} second argument must be either an ndarray-like object or an integer
+* @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, 1.0, 0.0, 4.0, 3.0, 0.0 ] );
+*
+* // Define the shape of the input array:
+* var sh = [ 3, 1, 2 ];
+*
+* // Define the array strides:
+* var sx = [ 2, 2, 1 ];
+*
+* // Define the index offset:
+* var ox = 0;
+*
+* // Create an input ndarray:
+* var x = new ndarray( 'float64', xbuf, sh, sx, ox, 'row-major' );
+*
+* // Perform operation:
+* var out = cusome( x, 2 );
+* // returns [ [ [ false, false ] ], [ [ false, true ] ], [ [ true, true ] ] ]
+*/
+function cusome( x, k ) {
+ var options;
+ var nargs;
+ var opts;
+ var iflg;
+ var ord;
+ var sh;
+ var v;
+
+ nargs = arguments.length;
+ if ( !isndarrayLike( x ) ) {
+ throw new TypeError( format( 'invalid argument. First argument must be an ndarray. Value: `%s`.', x ) );
+ }
+ // Resolve input ndarray meta data:
+ ord = getOrder( x );
+
+ // Initialize an options object:
+ opts = {};
+
+ // Initialize a flag indicating whether the `k` argument is a scalar:
+ iflg = true;
+
+ // Case: cusome( x, k_ndarray, ... )
+ if ( isndarrayLike( k ) ) {
+ iflg = false;
+ }
+ // Case: cusome( x, ???, ... )
+ else if ( !isInteger( k ) ) {
+ throw new TypeError( format( 'invalid argument. Second argument must be either an ndarray or an integer. Value: `%s`.', k ) );
+ }
+ // Case: cusome( x, k, options )
+ if ( nargs > 2 ) {
+ options = arguments[ 2 ];
+ if ( !isPlainObject( options ) ) {
+ throw new TypeError( format( 'invalid argument. Options argument must be an object. Value: `%s`.', options ) );
+ }
+ // Resolve provided options...
+ if ( hasOwnProp( options, 'dims' ) ) {
+ opts.dims = options.dims;
+ }
+ if ( hasOwnProp( options, 'dtype' ) ) {
+ opts.dtype = options.dtype;
+ }
+ }
+ // Resolve the shape of the non-core dimensions, noting that, when not provided `dims`, the operation is performed across all dimensions:
+ if ( hasOwnProp( opts, 'dims' ) ) {
+ sh = nonCoreShape( getShape( x ), opts.dims );
+ } else {
+ sh = [];
+ }
+ // Broadcast `k` to match the shape of the non-core dimensions, noting that, when not provided `dims`, `k` must be a zero-dimensional ndarray, as the operation is performed across all dimensions...
+ if ( iflg ) {
+ v = broadcastScalar( k, DEFAULT_DTYPE, sh, ord );
+ } else if ( hasOwnProp( opts, 'dims' ) ) {
+ v = maybeBroadcastArray( k, sh );
+ } else if ( ndims( k ) === 0 ) {
+ v = k;
+ } else {
+ throw new TypeError( 'invalid argument. Second argument must be a zero-dimensional ndarray.' );
+ }
+ return base( x, v, opts );
+}
+
+
+// EXPORTS //
+
+module.exports = cusome;
diff --git a/lib/node_modules/@stdlib/blas/ext/cusome/package.json b/lib/node_modules/@stdlib/blas/ext/cusome/package.json
new file mode 100644
index 000000000000..92e6d2551283
--- /dev/null
+++ b/lib/node_modules/@stdlib/blas/ext/cusome/package.json
@@ -0,0 +1,66 @@
+{
+ "name": "@stdlib/blas/ext/cusome",
+ "version": "0.0.0",
+ "description": "Cumulatively test whether at least `k` elements along one or more ndarray dimensions are truthy.",
+ "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",
+ "mathematics",
+ "math",
+ "blas",
+ "extended",
+ "cumulative",
+ "some",
+ "cusome",
+ "truthy",
+ "test",
+ "ndarray"
+ ],
+ "__stdlib__": {}
+}
diff --git a/lib/node_modules/@stdlib/blas/ext/cusome/test/test.assign.js b/lib/node_modules/@stdlib/blas/ext/cusome/test/test.assign.js
new file mode 100644
index 000000000000..9898ddb9f970
--- /dev/null
+++ b/lib/node_modules/@stdlib/blas/ext/cusome/test/test.assign.js
@@ -0,0 +1,1203 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2026 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 isSameArray = require( '@stdlib/assert/is-same-array' );
+var ndarray = require( '@stdlib/ndarray/ctor' );
+var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' );
+var zeros = require( '@stdlib/ndarray/zeros' );
+var emptyLike = require( '@stdlib/ndarray/empty-like' );
+var ndarray2array = require( '@stdlib/ndarray/to-array' );
+var getData = require( '@stdlib/ndarray/data-buffer' );
+var cusome = require( './../lib' ).assign;
+
+
+// TESTS //
+
+tape( 'main export is a function', function test( t ) {
+ t.ok( true, __filename );
+ t.strictEqual( typeof cusome, '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() {
+ cusome( value, 2, 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() {
+ cusome( value, 2, out, {} );
+ };
+ }
+});
+
+tape( 'the function throws an error if provided a first argument which is not an ndarray-like object (k ndarray)', 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() {
+ var k = scalar2ndarray( 2, {
+ 'dtype': 'int32'
+ });
+ cusome( value, k, out );
+ };
+ }
+});
+
+tape( 'the function throws an error if provided a first argument which is not an ndarray-like object (k ndarray, 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() {
+ var k = scalar2ndarray( 2, {
+ 'dtype': 'int32'
+ });
+ cusome( value, k, out, {} );
+ };
+ }
+});
+
+tape( 'the function throws an error if provided a third 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() {
+ cusome( x, 2, value );
+ };
+ }
+});
+
+tape( 'the function throws an error if provided a third 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() {
+ cusome( x, 2, value, {} );
+ };
+ }
+});
+
+tape( 'the function throws an error if provided a third argument which is not an ndarray-like object (k ndarray)', 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() {
+ var k = scalar2ndarray( 2, {
+ 'dtype': 'int32'
+ });
+ cusome( x, k, value );
+ };
+ }
+});
+
+tape( 'the function throws an error if provided a third argument which is not an ndarray-like object (k ndarray, 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() {
+ var k = scalar2ndarray( 2, {
+ 'dtype': 'int32'
+ });
+ cusome( x, k, value, {} );
+ };
+ }
+});
+
+tape( 'the function throws an error if provided a fourth 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( [ 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() {
+ cusome( x, 2, out, value );
+ };
+ }
+});
+
+tape( 'the function throws an error if provided a fourth argument which is not an object (k ndarray)', function test( t ) {
+ var values;
+ var out;
+ var x;
+ var i;
+
+ x = zeros( [ 2, 2 ], {
+ 'dtype': 'generic'
+ });
+ 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() {
+ var k = scalar2ndarray( 2, {
+ 'dtype': 'int32'
+ });
+ cusome( x, k, out, value );
+ };
+ }
+});
+
+tape( 'the function throws an error if provided a `k` argument which is not an ndarray-like object or an integer', function test( t ) {
+ var values;
+ var out;
+ var x;
+ var i;
+
+ x = zeros( [ 2, 2 ], {
+ 'dtype': 'generic'
+ });
+ out = zeros( [ 2, 2 ], {
+ 'dtype': 'generic'
+ });
+
+ values = [
+ '5',
+ 3.14,
+ 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() {
+ cusome( x, value, out );
+ };
+ }
+});
+
+tape( 'the function throws an error if provided a `k` argument which is not an ndarray-like object or an integer (options)', function test( t ) {
+ var values;
+ var out;
+ var x;
+ var i;
+
+ x = zeros( [ 2, 2 ], {
+ 'dtype': 'generic'
+ });
+ out = zeros( [ 2, 2 ], {
+ 'dtype': 'generic'
+ });
+
+ values = [
+ '5',
+ 3.14,
+ 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() {
+ cusome( x, value, out, {} );
+ };
+ }
+});
+
+tape( 'the function throws an error if provided a `k` argument which is not broadcast-compatible', function test( t ) {
+ var values;
+ var out;
+ var x;
+ var i;
+
+ x = zeros( [ 2, 2 ], {
+ 'dtype': 'generic'
+ });
+ out = zeros( [ 2, 2 ], {
+ 'dtype': 'generic'
+ });
+
+ values = [
+ zeros( [ 3 ], {
+ 'dtype': 'int32'
+ }),
+ zeros( [ 2, 2 ], {
+ 'dtype': 'int32'
+ })
+ ];
+ 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() {
+ cusome( x, value, out );
+ };
+ }
+});
+
+tape( 'the function throws an error if provided a `k` argument which is not broadcast-compatible (options)', function test( t ) {
+ var values;
+ var out;
+ var x;
+ var i;
+
+ x = zeros( [ 2, 2 ], {
+ 'dtype': 'generic'
+ });
+ out = zeros( [ 2, 2 ], {
+ 'dtype': 'generic'
+ });
+
+ values = [
+ zeros( [ 3 ], {
+ 'dtype': 'int32'
+ }),
+ zeros( [ 2, 2 ], {
+ 'dtype': 'int32'
+ })
+ ];
+ 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() {
+ cusome( x, value, out, {
+ 'dims': [ 0 ]
+ });
+ };
+ }
+});
+
+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( [ 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() {
+ cusome( x, 2, out, {
+ 'dims': value
+ });
+ };
+ }
+});
+
+tape( 'the function throws an error if provided a `dims` option which is not an array-like object of integers (k ndarray)', function test( t ) {
+ var values;
+ var out;
+ var x;
+ var i;
+
+ x = zeros( [ 2, 2 ], {
+ 'dtype': 'generic'
+ });
+ out = 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() {
+ var k = scalar2ndarray( 2, {
+ 'dtype': 'int32'
+ });
+ cusome( x, k, 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, 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() {
+ cusome( x, 2, out, {
+ 'dims': value
+ });
+ };
+ }
+});
+
+tape( 'the function throws an error if provided a `dims` option which contains out-of-bounds indices (k ndarray)', function test( t ) {
+ var values;
+ var out;
+ var x;
+ var i;
+
+ x = zeros( [ 2, 2 ], {
+ 'dtype': 'generic'
+ });
+ out = zeros( [ 2, 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() {
+ var k = scalar2ndarray( 2, {
+ 'dtype': 'int32'
+ });
+ cusome( x, k, 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( [ 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() {
+ cusome( x, 2, out, {
+ 'dims': value
+ });
+ };
+ }
+});
+
+tape( 'the function throws an error if provided a `dims` option which contains too many indices (k ndarray)', function test( t ) {
+ var values;
+ var out;
+ var x;
+ var i;
+
+ x = zeros( [ 2, 2 ], {
+ 'dtype': 'generic'
+ });
+ out = 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() {
+ var k = scalar2ndarray( 2, {
+ 'dtype': 'int32'
+ });
+ cusome( x, k, 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( [ 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() {
+ cusome( x, 2, out, {
+ 'dims': value
+ });
+ };
+ }
+});
+
+tape( 'the function throws an error if provided a `dims` option which contains duplicate indices (k ndarray)', function test( t ) {
+ var values;
+ var out;
+ var x;
+ var i;
+
+ x = zeros( [ 2, 2 ], {
+ 'dtype': 'generic'
+ });
+ out = 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() {
+ var k = scalar2ndarray( 2, {
+ 'dtype': 'int32'
+ });
+ cusome( x, k, 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 ],
+ [ 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'
+ });
+ cusome( x, 2, 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 ],
+ [ 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'
+ });
+ cusome( x, 2, 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 = [
+ [],
+ [ 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'
+ });
+ cusome( x, 2, out, {
+ 'dims': [ 0 ]
+ });
+ };
+ }
+});
+
+tape( 'the function cumulatively tests whether at least `k` elements in an ndarray are truthy (default, row-major)', function test( t ) {
+ var expected;
+ var actual;
+ var xbuf;
+ var out;
+ var x;
+
+ xbuf = [ 0.0, 1.0, 1.0, 0.0 ];
+ x = new ndarray( 'generic', xbuf, [ 2, 2 ], [ 2, 1 ], 0, 'row-major' );
+
+ out = emptyLike( x );
+
+ actual = cusome( x, 2, out );
+ expected = [ false, false, true, true ];
+
+ t.strictEqual( actual, out, 'returns expected value' );
+ t.strictEqual( isSameArray( getData( actual ), expected ), true, 'returns expected value' );
+
+ t.end();
+});
+
+tape( 'the function cumulatively tests whether at least `k` elements in an ndarray are truthy (default, column-major)', function test( t ) {
+ var expected;
+ var actual;
+ var xbuf;
+ var out;
+ var x;
+
+ xbuf = [ 0.0, 1.0, 1.0, 0.0 ];
+ x = new ndarray( 'generic', xbuf, [ 2, 2 ], [ 1, 2 ], 0, 'column-major' );
+
+ out = emptyLike( x );
+
+ actual = cusome( x, 2, out );
+ expected = [ false, false, true, true ];
+
+ t.strictEqual( actual, out, 'returns expected value' );
+ t.strictEqual( isSameArray( getData( actual ), expected ), true, 'returns expected value' );
+
+ t.end();
+});
+
+tape( 'the function cumulatively tests whether at least `k` elements in an ndarray are truthy (all dimensions, row-major)', function test( t ) {
+ var expected;
+ var actual;
+ var xbuf;
+ var out;
+ var x;
+
+ xbuf = [ 0.0, 1.0, 1.0, 0.0 ];
+ x = new ndarray( 'generic', xbuf, [ 2, 2 ], [ 2, 1 ], 0, 'row-major' );
+
+ out = emptyLike( x );
+
+ actual = cusome( x, 2, out, {
+ 'dims': [ 0, 1 ]
+ });
+ expected = [ false, false, true, true ];
+
+ t.strictEqual( actual, out, 'returns expected value' );
+ t.strictEqual( isSameArray( getData( actual ), expected ), true, 'returns expected value' );
+
+ t.end();
+});
+
+tape( 'the function cumulatively tests whether at least `k` elements in an ndarray are truthy (all dimensions, column-major)', function test( t ) {
+ var expected;
+ var actual;
+ var xbuf;
+ var out;
+ var x;
+
+ xbuf = [ 0.0, 1.0, 1.0, 0.0 ];
+ x = new ndarray( 'generic', xbuf, [ 2, 2 ], [ 1, 2 ], 0, 'column-major' );
+
+ out = emptyLike( x );
+
+ actual = cusome( x, 2, out, {
+ 'dims': [ 0, 1 ]
+ });
+ expected = [ false, false, true, true ];
+
+ t.strictEqual( actual, out, 'returns expected value' );
+ t.strictEqual( isSameArray( getData( actual ), expected ), true, 'returns expected value' );
+
+ t.end();
+});
+
+tape( 'the function cumulatively tests whether at least `k` elements in an ndarray are truthy (no dimensions, row-major)', function test( t ) {
+ var expected;
+ var actual;
+ var xbuf;
+ var out;
+ var x;
+
+ xbuf = [ 0.0, 1.0, 1.0, 0.0 ];
+ x = new ndarray( 'generic', xbuf, [ 2, 2 ], [ 2, 1 ], 0, 'row-major' );
+
+ out = emptyLike( x );
+
+ actual = cusome( x, 1, out, {
+ 'dims': []
+ });
+ expected = [ [ false, true ], [ true, false ] ];
+
+ t.strictEqual( actual, out, 'returns expected value' );
+ t.deepEqual( ndarray2array( actual ), expected, 'returns expected value' );
+
+ t.end();
+});
+
+tape( 'the function cumulatively tests whether at least `k` elements in an ndarray are truthy (no dimensions, column-major)', function test( t ) {
+ var expected;
+ var actual;
+ var xbuf;
+ var out;
+ var x;
+
+ xbuf = [ 0.0, 1.0, 1.0, 0.0 ];
+ x = new ndarray( 'generic', xbuf, [ 2, 2 ], [ 1, 2 ], 0, 'column-major' );
+
+ out = emptyLike( x );
+
+ actual = cusome( x, 1, out, {
+ 'dims': []
+ });
+ expected = [ [ false, true ], [ true, false ] ];
+
+ t.strictEqual( actual, out, 'returns expected value' );
+ t.deepEqual( ndarray2array( actual ), expected, 'returns expected value' );
+
+ t.end();
+});
+
+tape( 'the function supports specifying operation dimensions (row-major)', function test( t ) {
+ var expected;
+ var actual;
+ var xbuf;
+ var out;
+ var x;
+
+ xbuf = [ 1.0, 1.0, 0.0, 1.0 ];
+ x = new ndarray( 'generic', xbuf, [ 2, 2 ], [ 2, 1 ], 0, 'row-major' );
+
+ out = emptyLike( x );
+
+ actual = cusome( x, 2, out, {
+ 'dims': [ 0 ]
+ });
+ expected = [ [ false, false ], [ false, true ] ];
+
+ t.strictEqual( actual, out, 'returns expected value' );
+ t.deepEqual( ndarray2array( actual ), expected, 'returns expected value' );
+
+ xbuf = [ 1.0, 1.0, 0.0, 1.0 ];
+ x = new ndarray( 'generic', xbuf, [ 2, 2 ], [ 2, 1 ], 0, 'row-major' );
+
+ out = emptyLike( x );
+
+ actual = cusome( x, 2, out, {
+ 'dims': [ 1 ]
+ });
+ expected = [ [ false, true ], [ false, false ] ];
+
+ t.strictEqual( actual, out, 'returns expected value' );
+ t.deepEqual( ndarray2array( actual ), expected, 'returns expected value' );
+
+ t.end();
+});
+
+tape( 'the function supports specifying operation dimensions (column-major)', function test( t ) {
+ var expected;
+ var actual;
+ var xbuf;
+ var out;
+ var x;
+
+ xbuf = [ 1.0, 1.0, 0.0, 1.0 ];
+ x = new ndarray( 'generic', xbuf, [ 2, 2 ], [ 1, 2 ], 0, 'column-major' );
+
+ out = emptyLike( x );
+
+ actual = cusome( x, 2, out, {
+ 'dims': [ 0 ]
+ });
+ expected = [ [ false, false ], [ true, false ] ];
+
+ t.strictEqual( actual, out, 'returns expected value' );
+ t.deepEqual( ndarray2array( actual ), expected, 'returns expected value' );
+
+ xbuf = [ 1.0, 1.0, 0.0, 1.0 ];
+ x = new ndarray( 'generic', xbuf, [ 2, 2 ], [ 1, 2 ], 0, 'column-major' );
+
+ out = emptyLike( x );
+
+ actual = cusome( x, 2, out, {
+ 'dims': [ 1 ]
+ });
+ expected = [ [ false, false ], [ false, true ] ];
+
+ t.strictEqual( actual, out, 'returns expected value' );
+ t.deepEqual( ndarray2array( actual ), expected, 'returns expected value' );
+
+ t.end();
+});
+
+tape( 'the function supports specifying a minimum number of truthy elements (0d ndarray)', function test( t ) {
+ var expected;
+ var actual;
+ var xbuf;
+ var out;
+ var x;
+ var k;
+
+ xbuf = [ 0.0, 1.0, 1.0, 0.0 ];
+ x = new ndarray( 'generic', xbuf, [ 2, 2 ], [ 2, 1 ], 0, 'row-major' );
+
+ out = emptyLike( x );
+
+ k = scalar2ndarray( 2, {
+ 'dtype': 'int32'
+ });
+
+ actual = cusome( x, k, out );
+ expected = [ false, false, true, true ];
+
+ t.strictEqual( actual, out, 'returns expected value' );
+ t.strictEqual( isSameArray( getData( actual ), expected ), true, 'returns expected value' );
+
+ t.end();
+});
+
+tape( 'the function supports specifying a minimum number of truthy elements (0d ndarray, options)', function test( t ) {
+ var expected;
+ var actual;
+ var xbuf;
+ var out;
+ var x;
+ var k;
+
+ xbuf = [ 1.0, 1.0, 0.0, 1.0 ];
+ x = new ndarray( 'generic', xbuf, [ 2, 2 ], [ 2, 1 ], 0, 'row-major' );
+
+ out = emptyLike( x );
+
+ k = scalar2ndarray( 2, {
+ 'dtype': 'int32'
+ });
+
+ actual = cusome( x, k, out, {
+ 'dims': [ 1 ]
+ });
+ expected = [ [ false, true ], [ false, false ] ];
+
+ t.strictEqual( actual, out, 'returns expected value' );
+ t.deepEqual( ndarray2array( actual ), expected, 'returns expected value' );
+
+ t.end();
+});
+
+tape( 'the function supports specifying a minimum number of truthy elements (1d ndarray)', function test( t ) {
+ var expected;
+ var actual;
+ var xbuf;
+ var kbuf;
+ var out;
+ var x;
+ var k;
+
+ xbuf = [ 0.0, 1.0, 1.0, 0.0 ];
+ x = new ndarray( 'generic', xbuf, [ 2, 2 ], [ 2, 1 ], 0, 'row-major' );
+
+ out = emptyLike( x );
+
+ kbuf = [ 1, 2 ];
+ k = new ndarray( 'generic', kbuf, [ 2 ], [ 1 ], 0, 'row-major' );
+
+ actual = cusome( x, k, out, {
+ 'dims': [ 1 ]
+ });
+ expected = [ [ false, true ], [ false, false ] ];
+
+ t.strictEqual( actual, out, 'returns expected value' );
+ t.deepEqual( ndarray2array( actual ), expected, 'returns expected value' );
+
+ t.end();
+});
diff --git a/lib/node_modules/@stdlib/blas/ext/cusome/test/test.js b/lib/node_modules/@stdlib/blas/ext/cusome/test/test.js
new file mode 100644
index 000000000000..8660523e9d5f
--- /dev/null
+++ b/lib/node_modules/@stdlib/blas/ext/cusome/test/test.js
@@ -0,0 +1,39 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2026 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 cusome = require( './../lib' );
+
+
+// TESTS //
+
+tape( 'main export is a function', function test( t ) {
+ t.ok( true, __filename );
+ t.strictEqual( typeof cusome, 'function', 'main export is a function' );
+ t.end();
+});
+
+tape( 'attached to the main export is an `assign` method', function test( t ) {
+ t.strictEqual( isMethod( cusome, 'assign' ), true, 'returns expected value' );
+ t.end();
+});
diff --git a/lib/node_modules/@stdlib/blas/ext/cusome/test/test.main.js b/lib/node_modules/@stdlib/blas/ext/cusome/test/test.main.js
new file mode 100644
index 000000000000..1382b7977c61
--- /dev/null
+++ b/lib/node_modules/@stdlib/blas/ext/cusome/test/test.main.js
@@ -0,0 +1,998 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2026 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 isSameArray = require( '@stdlib/assert/is-same-array' );
+var isEqualBooleanArray = require( '@stdlib/assert/is-equal-booleanarray' );
+var BooleanArray = require( '@stdlib/array/bool' );
+var ndarray = require( '@stdlib/ndarray/ctor' );
+var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' );
+var zeros = require( '@stdlib/ndarray/zeros' );
+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 getData = require( '@stdlib/ndarray/data-buffer' );
+var cusome = require( './../lib' );
+
+
+// TESTS //
+
+tape( 'main export is a function', function test( t ) {
+ t.ok( true, __filename );
+ t.strictEqual( typeof cusome, '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() {
+ cusome( value, 2 );
+ };
+ }
+});
+
+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() {
+ cusome( value, 2, {} );
+ };
+ }
+});
+
+tape( 'the function throws an error if provided a first argument which is not an ndarray-like object (k ndarray)', 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() {
+ var k = scalar2ndarray( 2, {
+ 'dtype': 'int32'
+ });
+ cusome( value, k );
+ };
+ }
+});
+
+tape( 'the function throws an error if provided a first argument which is not an ndarray-like object (k ndarray, 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() {
+ var k = scalar2ndarray( 2, {
+ 'dtype': 'int32'
+ });
+ cusome( value, k, {} );
+ };
+ }
+});
+
+tape( 'the function throws an error if provided a third 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() {
+ cusome( x, 2, value );
+ };
+ }
+});
+
+tape( 'the function throws an error if provided a third argument which is not an object (k ndarray)', 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() {
+ var k = scalar2ndarray( 2, {
+ 'dtype': 'int32'
+ });
+ cusome( x, k, value );
+ };
+ }
+});
+
+tape( 'the function throws an error if provided a `k` argument which is not an ndarray-like object or an integer', function test( t ) {
+ var values;
+ var x;
+ var i;
+
+ x = zeros( [ 2, 2 ], {
+ 'dtype': 'generic'
+ });
+
+ values = [
+ '5',
+ 3.14,
+ 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() {
+ cusome( x, value );
+ };
+ }
+});
+
+tape( 'the function throws an error if provided a `k` argument which is not an ndarray-like object or an integer (options)', function test( t ) {
+ var values;
+ var x;
+ var i;
+
+ x = zeros( [ 2, 2 ], {
+ 'dtype': 'generic'
+ });
+
+ values = [
+ '5',
+ 3.14,
+ 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() {
+ cusome( x, value, {} );
+ };
+ }
+});
+
+tape( 'the function throws an error if provided a `k` argument which is not broadcast-compatible', function test( t ) {
+ var values;
+ var x;
+ var i;
+
+ x = zeros( [ 2, 2 ], {
+ 'dtype': 'generic'
+ });
+
+ values = [
+ zeros( [ 3 ], {
+ 'dtype': 'int32'
+ }),
+ zeros( [ 2, 2 ], {
+ 'dtype': 'int32'
+ })
+ ];
+ 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() {
+ cusome( x, value );
+ };
+ }
+});
+
+tape( 'the function throws an error if provided a `k` argument which is not broadcast-compatible (options)', function test( t ) {
+ var values;
+ var x;
+ var i;
+
+ x = zeros( [ 2, 2 ], {
+ 'dtype': 'generic'
+ });
+
+ values = [
+ zeros( [ 3 ], {
+ 'dtype': 'int32'
+ }),
+ zeros( [ 2, 2 ], {
+ 'dtype': 'int32'
+ })
+ ];
+ 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() {
+ cusome( x, value, {
+ 'dims': [ 0 ]
+ });
+ };
+ }
+});
+
+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',
+ 'float64',
+ 'int32'
+ ];
+ 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() {
+ cusome( x, 2, {
+ 'dtype': value
+ });
+ };
+ }
+});
+
+tape( 'the function throws an error if provided a `dtype` option which is not a supported data type (k ndarray)', function test( t ) {
+ var values;
+ var x;
+ var i;
+
+ x = zeros( [ 2, 2 ], {
+ 'dtype': 'generic'
+ });
+
+ values = [
+ 'foo',
+ 'bar',
+ 'beep',
+ 'boop',
+ 'float64',
+ 'int32'
+ ];
+ 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() {
+ var k = scalar2ndarray( 2, {
+ 'dtype': 'int32'
+ });
+ cusome( x, k, {
+ 'dtype': 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() {
+ cusome( x, 2, {
+ 'dims': value
+ });
+ };
+ }
+});
+
+tape( 'the function throws an error if provided a `dims` option which is not an array-like object of integers (k ndarray)', 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() {
+ var k = scalar2ndarray( 2, {
+ 'dtype': 'int32'
+ });
+ cusome( x, k, {
+ '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() {
+ cusome( x, 2, {
+ 'dims': value
+ });
+ };
+ }
+});
+
+tape( 'the function throws an error if provided a `dims` option which contains out-of-bounds indices (k ndarray)', 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() {
+ var k = scalar2ndarray( 2, {
+ 'dtype': 'int32'
+ });
+ cusome( x, k, {
+ '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() {
+ cusome( x, 2, {
+ 'dims': value
+ });
+ };
+ }
+});
+
+tape( 'the function throws an error if provided a `dims` option which contains too many indices (k ndarray)', 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() {
+ var k = scalar2ndarray( 2, {
+ 'dtype': 'int32'
+ });
+ cusome( x, k, {
+ '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() {
+ cusome( x, 2, {
+ 'dims': value
+ });
+ };
+ }
+});
+
+tape( 'the function throws an error if provided a `dims` option which contains duplicate indices (k ndarray)', 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() {
+ var k = scalar2ndarray( 2, {
+ 'dtype': 'int32'
+ });
+ cusome( x, k, {
+ 'dims': value
+ });
+ };
+ }
+});
+
+tape( 'the function cumulatively tests whether at least `k` elements in an ndarray are truthy (default, row-major)', function test( t ) {
+ var expected;
+ var actual;
+ var xbuf;
+ var x;
+
+ xbuf = [ 0.0, 1.0, 1.0, 0.0 ];
+ x = new ndarray( 'generic', xbuf, [ 2, 2 ], [ 2, 1 ], 0, 'row-major' );
+
+ actual = cusome( x, 2 );
+ expected = [ false, false, true, true ];
+
+ t.strictEqual( isndarrayLike( actual ), true, 'returns expected value' );
+ t.strictEqual( String( getDType( actual ) ), 'generic', 'returns expected value' );
+ t.deepEqual( getShape( actual ), getShape( x ), 'returns expected value' );
+ t.strictEqual( getOrder( actual ), getOrder( x ), 'returns expected value' );
+ t.strictEqual( isSameArray( getData( actual ), expected ), true, 'returns expected value' );
+
+ t.end();
+});
+
+tape( 'the function cumulatively tests whether at least `k` elements in an ndarray are truthy (default, column-major)', function test( t ) {
+ var expected;
+ var actual;
+ var xbuf;
+ var x;
+
+ xbuf = [ 0.0, 1.0, 1.0, 0.0 ];
+ x = new ndarray( 'generic', xbuf, [ 2, 2 ], [ 1, 2 ], 0, 'column-major' );
+
+ actual = cusome( x, 2 );
+ expected = [ false, false, true, true ];
+
+ t.strictEqual( isndarrayLike( actual ), true, 'returns expected value' );
+ t.strictEqual( String( getDType( actual ) ), 'generic', 'returns expected value' );
+ t.deepEqual( getShape( actual ), getShape( x ), 'returns expected value' );
+ t.strictEqual( getOrder( actual ), getOrder( x ), 'returns expected value' );
+ t.strictEqual( isSameArray( getData( actual ), expected ), true, 'returns expected value' );
+
+ t.end();
+});
+
+tape( 'the function cumulatively tests whether at least `k` elements in an ndarray are truthy (all dimensions, row-major)', function test( t ) {
+ var expected;
+ var actual;
+ var xbuf;
+ var x;
+
+ xbuf = [ 0.0, 1.0, 1.0, 0.0 ];
+ x = new ndarray( 'generic', xbuf, [ 2, 2 ], [ 2, 1 ], 0, 'row-major' );
+
+ actual = cusome( x, 2, {
+ 'dims': [ 0, 1 ]
+ });
+ expected = [ false, false, true, true ];
+
+ t.strictEqual( isndarrayLike( actual ), true, 'returns expected value' );
+ t.strictEqual( String( getDType( actual ) ), 'generic', 'returns expected value' );
+ t.deepEqual( getShape( actual ), getShape( x ), 'returns expected value' );
+ t.strictEqual( getOrder( actual ), getOrder( x ), 'returns expected value' );
+ t.strictEqual( isSameArray( getData( actual ), expected ), true, 'returns expected value' );
+
+ t.end();
+});
+
+tape( 'the function cumulatively tests whether at least `k` elements in an ndarray are truthy (all dimensions, column-major)', function test( t ) {
+ var expected;
+ var actual;
+ var xbuf;
+ var x;
+
+ xbuf = [ 0.0, 1.0, 1.0, 0.0 ];
+ x = new ndarray( 'generic', xbuf, [ 2, 2 ], [ 1, 2 ], 0, 'column-major' );
+
+ actual = cusome( x, 2, {
+ 'dims': [ 0, 1 ]
+ });
+ expected = [ false, false, true, true ];
+
+ t.strictEqual( isndarrayLike( actual ), true, 'returns expected value' );
+ t.strictEqual( String( getDType( actual ) ), 'generic', 'returns expected value' );
+ t.deepEqual( getShape( actual ), getShape( x ), 'returns expected value' );
+ t.strictEqual( getOrder( actual ), getOrder( x ), 'returns expected value' );
+ t.strictEqual( isSameArray( getData( actual ), expected ), true, 'returns expected value' );
+
+ t.end();
+});
+
+tape( 'the function cumulatively tests whether at least `k` elements in an ndarray are truthy (no dimensions, row-major)', function test( t ) {
+ var expected;
+ var actual;
+ var xbuf;
+ var x;
+
+ xbuf = [ 0.0, 1.0, 1.0, 0.0 ];
+ x = new ndarray( 'generic', xbuf, [ 2, 2 ], [ 2, 1 ], 0, 'row-major' );
+
+ actual = cusome( x, 1, {
+ 'dims': []
+ });
+ expected = [ [ false, true ], [ true, false ] ];
+
+ t.strictEqual( isndarrayLike( actual ), true, 'returns expected value' );
+ t.strictEqual( String( getDType( actual ) ), 'generic', 'returns expected value' );
+ t.deepEqual( getShape( actual ), getShape( x ), '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 cumulatively tests whether at least `k` elements in an ndarray are truthy (no dimensions, column-major)', function test( t ) {
+ var expected;
+ var actual;
+ var xbuf;
+ var x;
+
+ xbuf = [ 0.0, 1.0, 1.0, 0.0 ];
+ x = new ndarray( 'generic', xbuf, [ 2, 2 ], [ 1, 2 ], 0, 'column-major' );
+
+ actual = cusome( x, 1, {
+ 'dims': []
+ });
+ expected = [ [ false, true ], [ true, false ] ];
+
+ t.strictEqual( isndarrayLike( actual ), true, 'returns expected value' );
+ t.strictEqual( String( getDType( actual ) ), 'generic', 'returns expected value' );
+ t.deepEqual( getShape( actual ), getShape( x ), '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 operation dimensions (row-major)', function test( t ) {
+ var expected;
+ var actual;
+ var xbuf;
+ var x;
+
+ xbuf = [ 1.0, 1.0, 0.0, 1.0 ];
+ x = new ndarray( 'generic', xbuf, [ 2, 2 ], [ 2, 1 ], 0, 'row-major' );
+
+ actual = cusome( x, 2, {
+ 'dims': [ 0 ]
+ });
+ expected = [ [ false, false ], [ false, true ] ];
+
+ t.strictEqual( isndarrayLike( actual ), true, 'returns expected value' );
+ t.strictEqual( String( getDType( actual ) ), 'generic', 'returns expected value' );
+ t.deepEqual( getShape( actual ), getShape( x ), 'returns expected value' );
+ t.strictEqual( getOrder( actual ), getOrder( x ), 'returns expected value' );
+ t.deepEqual( ndarray2array( actual ), expected, 'returns expected value' );
+
+ xbuf = [ 1.0, 1.0, 0.0, 1.0 ];
+ x = new ndarray( 'generic', xbuf, [ 2, 2 ], [ 2, 1 ], 0, 'row-major' );
+
+ actual = cusome( x, 2, {
+ 'dims': [ 1 ]
+ });
+ expected = [ [ false, true ], [ false, false ] ];
+
+ t.strictEqual( isndarrayLike( actual ), true, 'returns expected value' );
+ t.strictEqual( String( getDType( actual ) ), 'generic', 'returns expected value' );
+ t.deepEqual( getShape( actual ), getShape( x ), '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 operation dimensions (column-major)', function test( t ) {
+ var expected;
+ var actual;
+ var xbuf;
+ var x;
+
+ xbuf = [ 1.0, 1.0, 0.0, 1.0 ];
+ x = new ndarray( 'generic', xbuf, [ 2, 2 ], [ 1, 2 ], 0, 'column-major' );
+
+ actual = cusome( x, 2, {
+ 'dims': [ 0 ]
+ });
+ expected = [ [ false, false ], [ true, false ] ];
+
+ t.strictEqual( isndarrayLike( actual ), true, 'returns expected value' );
+ t.strictEqual( String( getDType( actual ) ), 'generic', 'returns expected value' );
+ t.deepEqual( getShape( actual ), getShape( x ), 'returns expected value' );
+ t.strictEqual( getOrder( actual ), getOrder( x ), 'returns expected value' );
+ t.deepEqual( ndarray2array( actual ), expected, 'returns expected value' );
+
+ xbuf = [ 1.0, 1.0, 0.0, 1.0 ];
+ x = new ndarray( 'generic', xbuf, [ 2, 2 ], [ 1, 2 ], 0, 'column-major' );
+
+ actual = cusome( x, 2, {
+ 'dims': [ 1 ]
+ });
+ expected = [ [ false, false ], [ false, true ] ];
+
+ t.strictEqual( isndarrayLike( actual ), true, 'returns expected value' );
+ t.strictEqual( String( getDType( actual ) ), 'generic', 'returns expected value' );
+ t.deepEqual( getShape( actual ), getShape( x ), '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 = [ 0.0, 1.0, 1.0, 0.0 ];
+ x = new ndarray( 'generic', xbuf, [ 2, 2 ], [ 2, 1 ], 0, 'row-major' );
+
+ actual = cusome( x, 2, {
+ 'dtype': 'bool'
+ });
+ expected = new BooleanArray( [ false, false, true, true ] );
+
+ t.strictEqual( isndarrayLike( actual ), true, 'returns expected value' );
+ t.strictEqual( String( getDType( actual ) ), 'bool', 'returns expected value' );
+ t.deepEqual( getShape( actual ), getShape( x ), 'returns expected value' );
+ t.strictEqual( getOrder( actual ), getOrder( x ), 'returns expected value' );
+ t.strictEqual( isEqualBooleanArray( getData( actual ), expected ), true, 'returns expected value' );
+
+ xbuf = [ 0.0, 1.0, 1.0, 0.0 ];
+ x = new ndarray( 'generic', xbuf, [ 2, 2 ], [ 1, 2 ], 0, 'column-major' );
+
+ actual = cusome( x, 2, {
+ 'dtype': 'bool'
+ });
+ expected = new BooleanArray( [ false, false, true, true ] );
+
+ t.strictEqual( isndarrayLike( actual ), true, 'returns expected value' );
+ t.strictEqual( String( getDType( actual ) ), 'bool', 'returns expected value' );
+ t.deepEqual( getShape( actual ), getShape( x ), 'returns expected value' );
+ t.strictEqual( getOrder( actual ), getOrder( x ), 'returns expected value' );
+ t.strictEqual( isEqualBooleanArray( getData( actual ), expected ), true, 'returns expected value' );
+
+ t.end();
+});
+
+tape( 'the function supports specifying a minimum number of truthy elements (0d ndarray)', function test( t ) {
+ var expected;
+ var actual;
+ var xbuf;
+ var x;
+ var k;
+
+ xbuf = [ 0.0, 1.0, 1.0, 0.0 ];
+ x = new ndarray( 'generic', xbuf, [ 2, 2 ], [ 2, 1 ], 0, 'row-major' );
+
+ k = scalar2ndarray( 2, {
+ 'dtype': 'int32'
+ });
+
+ actual = cusome( x, k );
+ expected = [ false, false, true, true ];
+
+ t.strictEqual( isndarrayLike( actual ), true, 'returns expected value' );
+ t.strictEqual( String( getDType( actual ) ), 'generic', 'returns expected value' );
+ t.deepEqual( getShape( actual ), getShape( x ), 'returns expected value' );
+ t.strictEqual( getOrder( actual ), getOrder( x ), 'returns expected value' );
+ t.strictEqual( isSameArray( getData( actual ), expected ), true, 'returns expected value' );
+
+ t.end();
+});
+
+tape( 'the function supports specifying a minimum number of truthy elements (0d ndarray, options)', function test( t ) {
+ var expected;
+ var actual;
+ var xbuf;
+ var x;
+ var k;
+
+ xbuf = [ 1.0, 1.0, 0.0, 1.0 ];
+ x = new ndarray( 'generic', xbuf, [ 2, 2 ], [ 2, 1 ], 0, 'row-major' );
+
+ k = scalar2ndarray( 2, {
+ 'dtype': 'int32'
+ });
+
+ actual = cusome( x, k, {
+ 'dims': [ 1 ]
+ });
+ expected = [ [ false, true ], [ false, false ] ];
+
+ t.strictEqual( isndarrayLike( actual ), true, 'returns expected value' );
+ t.strictEqual( String( getDType( actual ) ), 'generic', 'returns expected value' );
+ t.deepEqual( getShape( actual ), getShape( x ), '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 a minimum number of truthy elements (1d ndarray)', function test( t ) {
+ var expected;
+ var actual;
+ var xbuf;
+ var kbuf;
+ var x;
+ var k;
+
+ xbuf = [ 0.0, 1.0, 1.0, 0.0 ];
+ x = new ndarray( 'generic', xbuf, [ 2, 2 ], [ 2, 1 ], 0, 'row-major' );
+
+ kbuf = [ 1, 2 ];
+ k = new ndarray( 'generic', kbuf, [ 2 ], [ 1 ], 0, 'row-major' );
+
+ actual = cusome( x, k, {
+ 'dims': [ 1 ]
+ });
+ expected = [ [ false, true ], [ false, false ] ];
+
+ t.strictEqual( isndarrayLike( actual ), true, 'returns expected value' );
+ t.strictEqual( String( getDType( actual ) ), 'generic', 'returns expected value' );
+ t.deepEqual( getShape( actual ), getShape( x ), 'returns expected value' );
+ t.strictEqual( getOrder( actual ), getOrder( x ), 'returns expected value' );
+ t.deepEqual( ndarray2array( actual ), expected, 'returns expected value' );
+
+ t.end();
+});