diff --git a/lib/node_modules/@stdlib/ndarray/flatten/README.md b/lib/node_modules/@stdlib/ndarray/flatten/README.md
new file mode 100644
index 000000000000..156801cd8799
--- /dev/null
+++ b/lib/node_modules/@stdlib/ndarray/flatten/README.md
@@ -0,0 +1,175 @@
+
+
+# flatten
+
+> Return a flattened copy of an input [ndarray][@stdlib/ndarray/ctor].
+
+
+
+
+
+
+
+## Usage
+
+```javascript
+var flatten = require( '@stdlib/ndarray/flatten' );
+```
+
+#### flatten( x\[, options] )
+
+Returns a flattened copy of an input [ndarray][@stdlib/ndarray/ctor].
+
+```javascript
+var array = require( '@stdlib/ndarray/array' );
+var ndarray2array = require( '@stdlib/ndarray/to-array' );
+
+var x = array( [ [ [ 1.0, 2.0 ] ], [ [ 3.0, 4.0 ] ], [ [ 5.0, 6.0 ] ] ] );
+// returns
+
+var y = flatten( x );
+// returns
+
+var arr = ndarray2array( y );
+// returns [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ]
+```
+
+The function accepts the following arguments:
+
+- **x**: input [ndarray][@stdlib/ndarray/ctor].
+- **options**: function options (_optional_).
+
+The function accepts the following options:
+
+- **order**: order in which input [ndarray][@stdlib/ndarray/ctor] elements should be flattened. Must be one of the following:
+
+ - `'row-major'`: flatten elements in lexicographic order. For example, given a two-dimensional input [ndarray][@stdlib/ndarray/ctor] (i.e., a matrix), flattening in lexicographic order means flattening the input [ndarray][@stdlib/ndarray/ctor] row-by-row.
+ - `'column-major'`: flatten elements in colexicographic order. For example, given a two-dimensional input [ndarray][@stdlib/ndarray/ctor] (i.e., a matrix), flattening in colexicographic order means flattening the input [ndarray][@stdlib/ndarray/ctor] column-by-column.
+ - `'any'`: flatten according to the physical layout of the input [ndarray][@stdlib/ndarray/ctor] data in memory, regardless of the stated [order][@stdlib/ndarray/orders] of the input [ndarray][@stdlib/ndarray/ctor].
+ - `'same'`: flatten according to the stated [order][@stdlib/ndarray/orders] of the input [ndarray][@stdlib/ndarray/ctor].
+
+ Default: `'row-major'`.
+
+- **depth**: maximum number of input [ndarray][@stdlib/ndarray/ctor] dimensions to flatten.
+
+By default, the function flattens all dimensions of the input [ndarray][@stdlib/ndarray/ctor]. To flatten to a desired depth, specify the `depth` option.
+
+```javascript
+var array = require( '@stdlib/ndarray/array' );
+var ndarray2array = require( '@stdlib/ndarray/to-array' );
+
+var x = array( [ [ [ 1.0, 2.0 ] ], [ [ 3.0, 4.0 ] ], [ [ 5.0, 6.0 ] ] ] );
+// returns
+
+var y = flatten( x, {
+ 'depth': 1
+});
+// returns
+
+var arr = ndarray2array( y );
+// returns [ [ 1.0, 2.0 ], [ 3.0, 4.0 ], [ 5.0, 6.0 ] ]
+```
+
+By default, the input [ndarray][@stdlib/ndarray/ctor] is flattened in lexicographic order. To flatten elements in a different order, specify the `order` option.
+
+```javascript
+var array = require( '@stdlib/ndarray/array' );
+var ndarray2array = require( '@stdlib/ndarray/to-array' );
+
+var x = array( [ [ [ 1.0, 2.0 ] ], [ [ 3.0, 4.0 ] ], [ [ 5.0, 6.0 ] ] ] );
+// returns
+
+var y = flatten( x, {
+ 'order': 'column-major'
+});
+// returns
+
+var arr = ndarray2array( y );
+// returns [ 1.0, 3.0, 5.0, 2.0, 4.0, 6.0 ]
+```
+
+
+
+
+
+
+
+## Notes
+
+- The function **always** returns a copy of input [ndarray][@stdlib/ndarray/ctor] data, even when an input [ndarray][@stdlib/ndarray/ctor] already has the desired number of dimensions.
+
+
+
+
+
+
+
+## Examples
+
+
+
+```javascript
+var discreteUniform = require( '@stdlib/random/array/discrete-uniform' );
+var array = require( '@stdlib/ndarray/array' );
+var ndarray2array = require( '@stdlib/ndarray/to-array' );
+var flatten = require( '@stdlib/ndarray/flatten' );
+
+var xbuf = discreteUniform( 12, -100, 100, {
+ 'dtype': 'generic'
+});
+
+var x = array( xbuf, {
+ 'shape': [ 2, 2, 3 ],
+ 'dtype': 'generic'
+});
+console.log( ndarray2array( x ) );
+
+var y = flatten( x );
+console.log( ndarray2array( y ) );
+```
+
+
+
+
+
+
+
+
+
+
+
+
+
+[@stdlib/ndarray/ctor]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/ndarray/ctor
+
+[@stdlib/ndarray/orders]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/ndarray/orders
+
+
+
+
+
+
+
+
diff --git a/lib/node_modules/@stdlib/ndarray/flatten/benchmark/benchmark.js b/lib/node_modules/@stdlib/ndarray/flatten/benchmark/benchmark.js
new file mode 100644
index 000000000000..6c9f713addc7
--- /dev/null
+++ b/lib/node_modules/@stdlib/ndarray/flatten/benchmark/benchmark.js
@@ -0,0 +1,310 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+* http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+'use strict';
+
+// MODULES //
+
+var bench = require( '@stdlib/bench' );
+var isndarrayLike = require( '@stdlib/assert/is-ndarray-like' );
+var zeros = require( '@stdlib/ndarray/base/zeros' );
+var pkg = require( './../package.json' ).name;
+var flatten = require( './../lib' );
+
+
+// MAIN //
+
+bench( pkg+'::2d:row-major', function benchmark( b ) {
+ var values;
+ var opts;
+ var y;
+ var i;
+ var j;
+
+ values = [
+ zeros( 'float64', [ 10, 10 ], 'row-major' ),
+ zeros( 'float32', [ 10, 10 ], 'row-major' ),
+ zeros( 'int32', [ 10, 10 ], 'row-major' ),
+ zeros( 'complex128', [ 10, 10 ], 'row-major' ),
+ zeros( 'generic', [ 10, 10 ], 'row-major' )
+ ];
+ opts = {
+ 'depth': 1,
+ 'order': 'row-major'
+ };
+
+ b.tic();
+ for ( i = 0; i < b.iterations; i++ ) {
+ j = i % values.length;
+ y = flatten( values[ j ], opts );
+ if ( typeof y !== 'object' ) {
+ b.fail( 'should return an ndarray' );
+ }
+ }
+ b.toc();
+ if ( !isndarrayLike( y ) ) {
+ b.fail( 'should return an ndarray' );
+ }
+ b.pass( 'benchmark finished' );
+ b.end();
+});
+
+bench( pkg+'::2d:column-major', function benchmark( b ) {
+ var values;
+ var opts;
+ var y;
+ var i;
+ var j;
+
+ values = [
+ zeros( 'float64', [ 10, 10 ], 'row-major' ),
+ zeros( 'float32', [ 10, 10 ], 'row-major' ),
+ zeros( 'int32', [ 10, 10 ], 'row-major' ),
+ zeros( 'complex128', [ 10, 10 ], 'row-major' ),
+ zeros( 'generic', [ 10, 10 ], 'row-major' )
+ ];
+ opts = {
+ 'depth': 1,
+ 'order': 'column-major'
+ };
+
+ b.tic();
+ for ( i = 0; i < b.iterations; i++ ) {
+ j = i % values.length;
+ y = flatten( values[ j ], opts );
+ if ( typeof y !== 'object' ) {
+ b.fail( 'should return an ndarray' );
+ }
+ }
+ b.toc();
+ if ( !isndarrayLike( y ) ) {
+ b.fail( 'should return an ndarray' );
+ }
+ b.pass( 'benchmark finished' );
+ b.end();
+});
+
+bench( pkg+'::3d:row-major', function benchmark( b ) {
+ var values;
+ var opts;
+ var y;
+ var i;
+ var j;
+
+ values = [
+ zeros( 'float64', [ 2, 5, 10 ], 'row-major' ),
+ zeros( 'float32', [ 2, 5, 10 ], 'row-major' ),
+ zeros( 'int32', [ 2, 5, 10 ], 'row-major' ),
+ zeros( 'complex128', [ 2, 5, 10 ], 'row-major' ),
+ zeros( 'generic', [ 2, 5, 10 ], 'row-major' )
+ ];
+ opts = {
+ 'depth': 2,
+ 'order': 'row-major'
+ };
+
+ b.tic();
+ for ( i = 0; i < b.iterations; i++ ) {
+ j = i % values.length;
+ y = flatten( values[ j ], opts );
+ if ( typeof y !== 'object' ) {
+ b.fail( 'should return an ndarray' );
+ }
+ }
+ b.toc();
+ if ( !isndarrayLike( y ) ) {
+ b.fail( 'should return an ndarray' );
+ }
+ b.pass( 'benchmark finished' );
+ b.end();
+});
+
+bench( pkg+'::3d:column-major', function benchmark( b ) {
+ var values;
+ var opts;
+ var y;
+ var i;
+ var j;
+
+ values = [
+ zeros( 'float64', [ 2, 5, 10 ], 'row-major' ),
+ zeros( 'float32', [ 2, 5, 10 ], 'row-major' ),
+ zeros( 'int32', [ 2, 5, 10 ], 'row-major' ),
+ zeros( 'complex128', [ 2, 5, 10 ], 'row-major' ),
+ zeros( 'generic', [ 2, 5, 10 ], 'row-major' )
+ ];
+ opts = {
+ 'depth': 2,
+ 'order': 'column-major'
+ };
+
+ b.tic();
+ for ( i = 0; i < b.iterations; i++ ) {
+ j = i % values.length;
+ y = flatten( values[ j ], opts );
+ if ( typeof y !== 'object' ) {
+ b.fail( 'should return an ndarray' );
+ }
+ }
+ b.toc();
+ if ( !isndarrayLike( y ) ) {
+ b.fail( 'should return an ndarray' );
+ }
+ b.pass( 'benchmark finished' );
+ b.end();
+});
+
+bench( pkg+'::4d:row-major', function benchmark( b ) {
+ var values;
+ var opts;
+ var y;
+ var i;
+ var j;
+
+ values = [
+ zeros( 'float64', [ 2, 5, 2, 5 ], 'row-major' ),
+ zeros( 'float32', [ 2, 5, 2, 5 ], 'row-major' ),
+ zeros( 'int32', [ 2, 5, 2, 5 ], 'row-major' ),
+ zeros( 'complex128', [ 2, 5, 2, 5 ], 'row-major' ),
+ zeros( 'generic', [ 2, 5, 2, 5 ], 'row-major' )
+ ];
+ opts = {
+ 'depth': 3,
+ 'order': 'row-major'
+ };
+
+ b.tic();
+ for ( i = 0; i < b.iterations; i++ ) {
+ j = i % values.length;
+ y = flatten( values[ j ], opts );
+ if ( typeof y !== 'object' ) {
+ b.fail( 'should return an ndarray' );
+ }
+ }
+ b.toc();
+ if ( !isndarrayLike( y ) ) {
+ b.fail( 'should return an ndarray' );
+ }
+ b.pass( 'benchmark finished' );
+ b.end();
+});
+
+bench( pkg+'::4d:column-major', function benchmark( b ) {
+ var values;
+ var opts;
+ var y;
+ var i;
+ var j;
+
+ values = [
+ zeros( 'float64', [ 2, 5, 2, 5 ], 'row-major' ),
+ zeros( 'float32', [ 2, 5, 2, 5 ], 'row-major' ),
+ zeros( 'int32', [ 2, 5, 2, 5 ], 'row-major' ),
+ zeros( 'complex128', [ 2, 5, 2, 5 ], 'row-major' ),
+ zeros( 'generic', [ 2, 5, 2, 5 ], 'row-major' )
+ ];
+ opts = {
+ 'depth': 3,
+ 'order': 'column-major'
+ };
+
+ b.tic();
+ for ( i = 0; i < b.iterations; i++ ) {
+ j = i % values.length;
+ y = flatten( values[ j ], opts );
+ if ( typeof y !== 'object' ) {
+ b.fail( 'should return an ndarray' );
+ }
+ }
+ b.toc();
+ if ( !isndarrayLike( y ) ) {
+ b.fail( 'should return an ndarray' );
+ }
+ b.pass( 'benchmark finished' );
+ b.end();
+});
+
+bench( pkg+'::5d:row-major', function benchmark( b ) {
+ var values;
+ var opts;
+ var y;
+ var i;
+ var j;
+
+ values = [
+ zeros( 'float64', [ 2, 5, 2, 5, 1 ], 'row-major' ),
+ zeros( 'float32', [ 2, 5, 2, 5, 1 ], 'row-major' ),
+ zeros( 'int32', [ 2, 5, 2, 5, 1 ], 'row-major' ),
+ zeros( 'complex128', [ 2, 5, 2, 5, 1 ], 'row-major' ),
+ zeros( 'generic', [ 2, 5, 2, 5, 1 ], 'row-major' )
+ ];
+ opts = {
+ 'depth': 4,
+ 'order': 'row-major'
+ };
+
+ b.tic();
+ for ( i = 0; i < b.iterations; i++ ) {
+ j = i % values.length;
+ y = flatten( values[ j ], opts );
+ if ( typeof y !== 'object' ) {
+ b.fail( 'should return an ndarray' );
+ }
+ }
+ b.toc();
+ if ( !isndarrayLike( y ) ) {
+ b.fail( 'should return an ndarray' );
+ }
+ b.pass( 'benchmark finished' );
+ b.end();
+});
+
+bench( pkg+'::5d:column-major', function benchmark( b ) {
+ var values;
+ var opts;
+ var y;
+ var i;
+ var j;
+
+ values = [
+ zeros( 'float64', [ 2, 5, 2, 5, 1 ], 'row-major' ),
+ zeros( 'float32', [ 2, 5, 2, 5, 1 ], 'row-major' ),
+ zeros( 'int32', [ 2, 5, 2, 5, 1 ], 'row-major' ),
+ zeros( 'complex128', [ 2, 5, 2, 5, 1 ], 'row-major' ),
+ zeros( 'generic', [ 2, 5, 2, 5, 1 ], 'row-major' )
+ ];
+ opts = {
+ 'depth': 4,
+ 'order': 'column-major'
+ };
+
+ b.tic();
+ for ( i = 0; i < b.iterations; i++ ) {
+ j = i % values.length;
+ y = flatten( values[ j ], opts );
+ if ( typeof y !== 'object' ) {
+ b.fail( 'should return an ndarray' );
+ }
+ }
+ b.toc();
+ if ( !isndarrayLike( y ) ) {
+ b.fail( 'should return an ndarray' );
+ }
+ b.pass( 'benchmark finished' );
+ b.end();
+});
diff --git a/lib/node_modules/@stdlib/ndarray/flatten/docs/repl.txt b/lib/node_modules/@stdlib/ndarray/flatten/docs/repl.txt
new file mode 100644
index 000000000000..4e2e4208667e
--- /dev/null
+++ b/lib/node_modules/@stdlib/ndarray/flatten/docs/repl.txt
@@ -0,0 +1,45 @@
+
+{{alias}}( x[, options] )
+ Returns a flattened copy of an input ndarray.
+
+ The function always returns a copy of input ndarray data, even when an input
+ ndarray already has the desired number of dimensions.
+
+ Parameters
+ ----------
+ x: ndarray
+ Input ndarray.
+
+ options: Object (optional)
+ Function options.
+
+ options.depth: integer (optional)
+ Maximum number of dimensions to flatten. By default, the function
+ flattens all input ndarray dimensions.
+
+ options.order: string (optional)
+ Order in which input ndarray elements should be flattened. The following
+ orders are supported:
+
+ - row-major: flatten in lexicographic order.
+ - column-major: flatten in colexicographic order.
+ - same: flatten according to the stated order of the input ndarray.
+ - any: flatten according to physical layout of the input ndarray data in
+ memory, regardless of the stated order of the input ndarray.
+
+ Default: 'row-major'.
+
+ Returns
+ -------
+ out: ndarray
+ Output ndarray.
+
+ Examples
+ --------
+ > var x = {{alias:@stdlib/ndarray/array}}( [ [ 1.0, 2.0 ], [ 3.0, 4.0 ] ] );
+ > var y = {{alias}}( x );
+ > var arr = {{alias:@stdlib/ndarray/to-array}}( y )
+ [ 1.0, 2.0, 3.0, 4.0 ]
+
+ See Also
+ --------
diff --git a/lib/node_modules/@stdlib/ndarray/flatten/docs/types/index.d.ts b/lib/node_modules/@stdlib/ndarray/flatten/docs/types/index.d.ts
new file mode 100644
index 000000000000..c7d0484a7b1d
--- /dev/null
+++ b/lib/node_modules/@stdlib/ndarray/flatten/docs/types/index.d.ts
@@ -0,0 +1,86 @@
+/*
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+* http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+// TypeScript Version: 4.1
+
+///
+
+import { ndarray, Order } from '@stdlib/types/ndarray';
+
+/**
+* Interface defining function options.
+*/
+interface Options {
+ /**
+ * Maximum number of dimensions to flatten.
+ *
+ * ## Notes
+ *
+ * - By default, the function flattens all input ndarray dimensions.
+ */
+ depth?: number;
+
+ /**
+ * Order in which input ndarray elements should be flattened.
+ *
+ * ## Notes
+ *
+ * - The following orders are supported:
+ *
+ * - **row-major**: flatten in lexicographic order.
+ * - **column-major**: flatten in colexicographic order.
+ * - **same**: flatten according to the stated order of the input ndarray.
+ * - **any**: flatten according to the physical layout of the input ndarray data in memory, regardless of the stated order of the input ndarray.
+ *
+ * - Default: 'row-major'.
+ */
+ order?: Order | 'same' | 'any';
+}
+
+/**
+* Returns a flattened copy of an input ndarray.
+*
+* ## Notes
+*
+* - The function **always** returns a copy of input ndarray data, even when an input ndarray already has the desired number of dimensions.
+*
+* @param x - input ndarray
+* @param options - function options
+* @param options.depth - maximum number of dimensions to flatten
+* @param options.order - order in which input ndarray elements should be flattened
+* @returns output ndarray
+*
+* @example
+* var array = require( '@stdlib/ndarray/array' );
+* var ndarray2array = require( '@stdlib/ndarray/to-array' );
+*
+* var x = array( [ [ [ 1.0, 2.0 ] ], [ [ 3.0, 4.0 ] ], [ [ 5.0, 6.0 ] ] ] );;
+* // return
+*
+* var y = flatten( x );
+* // returns
+*
+* var arr = ndarray2array( y );
+* // returns [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ]
+*/
+declare function flatten( x: T, options?: Options ): T;
+
+
+// EXPORTS //
+
+export = flatten;
diff --git a/lib/node_modules/@stdlib/ndarray/flatten/docs/types/test.ts b/lib/node_modules/@stdlib/ndarray/flatten/docs/types/test.ts
new file mode 100644
index 000000000000..bc9d1cf920bc
--- /dev/null
+++ b/lib/node_modules/@stdlib/ndarray/flatten/docs/types/test.ts
@@ -0,0 +1,137 @@
+/*
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+* http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+import zeros = require( '@stdlib/ndarray/base/zeros' );
+import flatten = require( './index' );
+
+
+// TESTS //
+
+// The function returns an ndarray...
+{
+ flatten( zeros( 'float64', [ 2, 2, 2 ], 'row-major' ) ); // $ExpectType float64ndarray
+ flatten( zeros( 'complex128', [ 2, 2, 2 ], 'row-major' ) ); // $ExpectType complex128ndarray
+ flatten( zeros( 'generic', [ 2, 2, 2 ], 'row-major' ) ); // $ExpectType genericndarray
+
+ flatten( zeros( 'float64', [ 2, 2, 2 ], 'row-major' ), {} ); // $ExpectType float64ndarray
+ flatten( zeros( 'complex128', [ 2, 2, 2 ], 'row-major' ), {} ); // $ExpectType complex128ndarray
+ flatten( zeros( 'generic', [ 2, 2, 2 ], 'row-major' ), {} ); // $ExpectType genericndarray
+}
+
+// The compiler throws an error if the function is provided a first argument which is not an ndarray-like object...
+{
+ flatten( '5' ); // $ExpectError
+ flatten( 5 ); // $ExpectError
+ flatten( true ); // $ExpectError
+ flatten( false ); // $ExpectError
+ flatten( null ); // $ExpectError
+ flatten( undefined ); // $ExpectError
+ flatten( {} ); // $ExpectError
+ flatten( [ 1 ] ); // $ExpectError
+ flatten( ( x: number ): number => x ); // $ExpectError
+
+ flatten( '5', {} ); // $ExpectError
+ flatten( 5, {} ); // $ExpectError
+ flatten( true, {} ); // $ExpectError
+ flatten( false, {} ); // $ExpectError
+ flatten( null, {} ); // $ExpectError
+ flatten( undefined, {} ); // $ExpectError
+ flatten( {}, {} ); // $ExpectError
+ flatten( [ 1 ], {} ); // $ExpectError
+ flatten( ( x: number ): number => x, {} ); // $ExpectError
+}
+
+// The compiler throws an error if the function is provided a second argument which is not an object...
+{
+ flatten( zeros( 'float64', [ 2, 2, 2 ], 'row-major' ), '5' ); // $ExpectError
+ flatten( zeros( 'float64', [ 2, 2, 2 ], 'row-major' ), true ); // $ExpectError
+ flatten( zeros( 'float64', [ 2, 2, 2 ], 'row-major' ), false ); // $ExpectError
+ flatten( zeros( 'float64', [ 2, 2, 2 ], 'row-major' ), null ); // $ExpectError
+ flatten( zeros( 'float64', [ 2, 2, 2 ], 'row-major' ), [ 1 ] ); // $ExpectError
+ flatten( zeros( 'float64', [ 2, 2, 2 ], 'row-major' ), ( x: number ): number => x ); // $ExpectError
+
+ flatten( zeros( 'complex128', [ 2, 2, 2 ], 'row-major' ), '5' ); // $ExpectError
+ flatten( zeros( 'complex128', [ 2, 2, 2 ], 'row-major' ), true ); // $ExpectError
+ flatten( zeros( 'complex128', [ 2, 2, 2 ], 'row-major' ), false ); // $ExpectError
+ flatten( zeros( 'complex128', [ 2, 2, 2 ], 'row-major' ), null ); // $ExpectError
+ flatten( zeros( 'complex128', [ 2, 2, 2 ], 'row-major' ), [ 1 ] ); // $ExpectError
+ flatten( zeros( 'complex128', [ 2, 2, 2 ], 'row-major' ), ( x: number ): number => x ); // $ExpectError
+
+ flatten( zeros( 'generic', [ 2, 2, 2 ], 'row-major' ), '5' ); // $ExpectError
+ flatten( zeros( 'generic', [ 2, 2, 2 ], 'row-major' ), true ); // $ExpectError
+ flatten( zeros( 'generic', [ 2, 2, 2 ], 'row-major' ), false ); // $ExpectError
+ flatten( zeros( 'generic', [ 2, 2, 2 ], 'row-major' ), null ); // $ExpectError
+ flatten( zeros( 'generic', [ 2, 2, 2 ], 'row-major' ), [ 1 ] ); // $ExpectError
+ flatten( zeros( 'generic', [ 2, 2, 2 ], 'row-major' ), ( x: number ): number => x ); // $ExpectError
+}
+
+// The compiler throws an error if the function is provided a second argument with invalid `depth` option...
+{
+ flatten( zeros( 'float64', [ 2, 2, 2 ], 'row-major' ), { 'depth': '5' } ); // $ExpectError
+ flatten( zeros( 'float64', [ 2, 2, 2 ], 'row-major' ), { 'depth': true } ); // $ExpectError
+ flatten( zeros( 'float64', [ 2, 2, 2 ], 'row-major' ), { 'depth': false } ); // $ExpectError
+ flatten( zeros( 'float64', [ 2, 2, 2 ], 'row-major' ), { 'depth': null } ); // $ExpectError
+ flatten( zeros( 'float64', [ 2, 2, 2 ], 'row-major' ), { 'depth': [ 1 ] } ); // $ExpectError
+ flatten( zeros( 'float64', [ 2, 2, 2 ], 'row-major' ), { 'depth': ( x: number ): number => x } ); // $ExpectError
+
+ flatten( zeros( 'complex128', [ 2, 2, 2 ], 'row-major' ), { 'depth': '5' } ); // $ExpectError
+ flatten( zeros( 'complex128', [ 2, 2, 2 ], 'row-major' ), { 'depth': true } ); // $ExpectError
+ flatten( zeros( 'complex128', [ 2, 2, 2 ], 'row-major' ), { 'depth': false } ); // $ExpectError
+ flatten( zeros( 'complex128', [ 2, 2, 2 ], 'row-major' ), { 'depth': null } ); // $ExpectError
+ flatten( zeros( 'complex128', [ 2, 2, 2 ], 'row-major' ), { 'depth': [ 1 ] } ); // $ExpectError
+ flatten( zeros( 'complex128', [ 2, 2, 2 ], 'row-major' ), { 'depth': ( x: number ): number => x } ); // $ExpectError
+
+ flatten( zeros( 'generic', [ 2, 2, 2 ], 'row-major' ), { 'depth': '5' } ); // $ExpectError
+ flatten( zeros( 'generic', [ 2, 2, 2 ], 'row-major' ), { 'depth': true } ); // $ExpectError
+ flatten( zeros( 'generic', [ 2, 2, 2 ], 'row-major' ), { 'depth': false } ); // $ExpectError
+ flatten( zeros( 'generic', [ 2, 2, 2 ], 'row-major' ), { 'depth': null } ); // $ExpectError
+ flatten( zeros( 'generic', [ 2, 2, 2 ], 'row-major' ), { 'depth': [ 1 ] } ); // $ExpectError
+ flatten( zeros( 'generic', [ 2, 2, 2 ], 'row-major' ), { 'depth': ( x: number ): number => x } ); // $ExpectError
+}
+
+// The compiler throws an error if the function is provided a second argument with invalid `order` option...
+{
+ flatten( zeros( 'float64', [ 2, 2, 2 ], 'row-major' ), { 'order': '5' } ); // $ExpectError
+ flatten( zeros( 'float64', [ 2, 2, 2 ], 'row-major' ), { 'order': true } ); // $ExpectError
+ flatten( zeros( 'float64', [ 2, 2, 2 ], 'row-major' ), { 'order': false } ); // $ExpectError
+ flatten( zeros( 'float64', [ 2, 2, 2 ], 'row-major' ), { 'order': null } ); // $ExpectError
+ flatten( zeros( 'float64', [ 2, 2, 2 ], 'row-major' ), { 'order': [ 1 ] } ); // $ExpectError
+ flatten( zeros( 'float64', [ 2, 2, 2 ], 'row-major' ), { 'order': ( x: number ): number => x } ); // $ExpectError
+
+ flatten( zeros( 'complex128', [ 2, 2, 2 ], 'row-major' ), { 'order': '5' } ); // $ExpectError
+ flatten( zeros( 'complex128', [ 2, 2, 2 ], 'row-major' ), { 'order': true } ); // $ExpectError
+ flatten( zeros( 'complex128', [ 2, 2, 2 ], 'row-major' ), { 'order': false } ); // $ExpectError
+ flatten( zeros( 'complex128', [ 2, 2, 2 ], 'row-major' ), { 'order': null } ); // $ExpectError
+ flatten( zeros( 'complex128', [ 2, 2, 2 ], 'row-major' ), { 'order': [ 1 ] } ); // $ExpectError
+ flatten( zeros( 'complex128', [ 2, 2, 2 ], 'row-major' ), { 'order': ( x: number ): number => x } ); // $ExpectError
+
+ flatten( zeros( 'generic', [ 2, 2, 2 ], 'row-major' ), { 'order': '5' } ); // $ExpectError
+ flatten( zeros( 'generic', [ 2, 2, 2 ], 'row-major' ), { 'order': true } ); // $ExpectError
+ flatten( zeros( 'generic', [ 2, 2, 2 ], 'row-major' ), { 'order': false } ); // $ExpectError
+ flatten( zeros( 'generic', [ 2, 2, 2 ], 'row-major' ), { 'order': null } ); // $ExpectError
+ flatten( zeros( 'generic', [ 2, 2, 2 ], 'row-major' ), { 'order': [ 1 ] } ); // $ExpectError
+ flatten( zeros( 'generic', [ 2, 2, 2 ], 'row-major' ), { 'order': ( x: number ): number => x } ); // $ExpectError
+}
+
+// The compiler throws an error if the function is provided an unsupported number of arguments...
+{
+ const x = zeros( 'float64', [ 2, 2, 2 ], 'row-major' );
+
+ flatten(); // $ExpectError
+ flatten( x, {}, {} ); // $ExpectError
+}
diff --git a/lib/node_modules/@stdlib/ndarray/flatten/examples/index.js b/lib/node_modules/@stdlib/ndarray/flatten/examples/index.js
new file mode 100644
index 000000000000..f3c5b9214327
--- /dev/null
+++ b/lib/node_modules/@stdlib/ndarray/flatten/examples/index.js
@@ -0,0 +1,37 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+* http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+'use strict';
+
+var discreteUniform = require( '@stdlib/random/array/discrete-uniform' );
+var array = require( '@stdlib/ndarray/array' );
+var ndarray2array = require( '@stdlib/ndarray/to-array' );
+var flatten = require( './../lib' );
+
+var xbuf = discreteUniform( 12, -100, 100, {
+ 'dtype': 'generic'
+});
+
+var x = array( xbuf, {
+ 'shape': [ 2, 2, 3 ],
+ 'dtype': 'generic'
+});
+console.log( ndarray2array( x ) );
+
+var y = flatten( x );
+console.log( ndarray2array( y ) );
diff --git a/lib/node_modules/@stdlib/ndarray/flatten/lib/index.js b/lib/node_modules/@stdlib/ndarray/flatten/lib/index.js
new file mode 100644
index 000000000000..85584b794fd1
--- /dev/null
+++ b/lib/node_modules/@stdlib/ndarray/flatten/lib/index.js
@@ -0,0 +1,50 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+* http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+'use strict';
+
+/**
+* Return a flattened copy of an input ndarray.
+*
+* @module @stdlib/ndarray/flatten
+*
+* @example
+* var array = require( '@stdlib/ndarray/array' );
+* var ndarray2array = require( '@stdlib/ndarray/to-array' );
+* var flatten = require( '@stdlib/ndarray/flatten' );
+*
+* // Create an input ndarray:
+* var x = array( [ [ [ 1.0, 2.0 ] ], [ [ 3.0, 4.0 ] ], [ [ 5.0, 6.0 ] ] ] );
+* // return
+*
+* // Flatten the input ndarray:
+* var y = flatten( x );
+* // returns
+*
+* var arr = ndarray2array( y );
+* // returns [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ]
+*/
+
+// MODULES //
+
+var main = require( './main.js' );
+
+
+// EXPORTS //
+
+module.exports = main;
diff --git a/lib/node_modules/@stdlib/ndarray/flatten/lib/main.js b/lib/node_modules/@stdlib/ndarray/flatten/lib/main.js
new file mode 100644
index 000000000000..22ecfba4112d
--- /dev/null
+++ b/lib/node_modules/@stdlib/ndarray/flatten/lib/main.js
@@ -0,0 +1,358 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+* http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+'use strict';
+
+// MODULES //
+
+var isPlainObject = require( '@stdlib/assert/is-plain-object' );
+var hasOwnProp = require( '@stdlib/assert/has-own-property' );
+var isndarrayLike = require( '@stdlib/assert/is-ndarray-like' );
+var isNonNegativeInteger = require( '@stdlib/assert/is-nonnegative-integer' );
+var isOrder = require( '@stdlib/ndarray/base/assert/is-order' );
+var getShape = require( '@stdlib/ndarray/shape' );
+var getOrder = require( '@stdlib/ndarray/order' );
+var getStrides = require( '@stdlib/ndarray/strides' );
+var getData = require( '@stdlib/ndarray/base/data-buffer' );
+var getDType = require( '@stdlib/ndarray/base/dtype' );
+var shape2strides = require( '@stdlib/ndarray/base/shape2strides' );
+var strides2order = require( '@stdlib/ndarray/base/strides2order' );
+var flattenShape = require( '@stdlib/ndarray/base/flatten-shape' );
+var assign = require( '@stdlib/ndarray/base/assign' );
+var emptyLike = require( '@stdlib/ndarray/empty-like' );
+var ndarray = require( '@stdlib/ndarray/ctor' );
+var format = require( '@stdlib/string/format' );
+
+
+// VARIABLES //
+
+var ROW_MAJOR = 'row-major';
+var COL_MAJOR = 'column-major';
+
+
+// MAIN //
+
+/**
+* Returns a flattened copy of an input ndarray.
+*
+* @param {ndarray} x - input ndarray
+* @param {Options} [options] - function options
+* @param {NonNegativeInteger} [options.depth] - maximum number of dimensions to flatten
+* @param {string} [options.order='row-major'] - order in which input ndarray elements should be flattened
+* @throws {TypeError} first argument must be an ndarray-like object
+* @throws {TypeError} options argument must be an object
+* @throws {TypeError} must provide valid options
+* @returns {ndarray} output ndarray
+*
+* @example
+* var array = require( '@stdlib/ndarray/array' );
+* var ndarray2array = require( '@stdlib/ndarray/to-array' );
+*
+* var x = array( [ [ [ 1.0, 2.0 ] ], [ [ 3.0, 4.0 ] ], [ [ 5.0, 6.0 ] ] ] );
+* // return
+*
+* var y = flatten( x );
+* // returns
+*
+* var arr = ndarray2array( y );
+* // returns [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ]
+*
+* @example
+* var array = require( '@stdlib/ndarray/array' );
+* var ndarray2array = require( '@stdlib/ndarray/to-array' );
+*
+* var x = array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ], {
+* 'shape': [ 2, 3 ],
+* 'order': 'column-major'
+* });
+* // return
+*
+* var y = flatten( x );
+* // returns
+*
+* var arr = ndarray2array( y );
+* // returns [ 1.0, 3.0, 5.0, 2.0, 4.0, 6.0 ]
+*
+* @example
+* var array = require( '@stdlib/ndarray/array' );
+* var ndarray2array = require( '@stdlib/ndarray/to-array' );
+*
+* var x = array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ], {
+* 'shape': [ 2, 3 ],
+* 'order': 'row-major'
+* });
+* // return
+*
+* var y = flatten( x, {
+* 'order': 'column-major'
+* });
+* // returns
+*
+* var arr = ndarray2array( y );
+* // returns [ 1.0, 4.0, 2.0, 5.0, 3.0, 6.0 ]
+*
+* @example
+* var array = require( '@stdlib/ndarray/array' );
+* var ndarray2array = require( '@stdlib/ndarray/to-array' );
+*
+* var x = array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ], {
+* 'shape': [ 2, 3 ],
+* 'order': 'column-major'
+* });
+* // return
+*
+* var y = flatten( x, {
+* 'order': 'row-major'
+* });
+* // returns
+*
+* var arr = ndarray2array( y );
+* // returns [ 1.0, 3.0, 5.0, 2.0, 4.0, 6.0 ]
+*
+* @example
+* var array = require( '@stdlib/ndarray/array' );
+* var ndarray2array = require( '@stdlib/ndarray/to-array' );
+*
+* var x = array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ], {
+* 'shape': [ 2, 3 ],
+* 'order': 'row-major'
+* });
+* // return
+*
+* var y = flatten( x, {
+* 'order': 'same'
+* });
+* // returns
+*
+* var arr = ndarray2array( y );
+* // returns [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ]
+*
+* @example
+* var array = require( '@stdlib/ndarray/array' );
+* var ndarray2array = require( '@stdlib/ndarray/to-array' );
+*
+* var x = array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ], {
+* 'shape': [ 2, 3 ],
+* 'order': 'column-major'
+* });
+* // return
+*
+* var y = flatten( x, {
+* 'order': 'same'
+* });
+* // returns
+*
+* var arr = ndarray2array( y );
+* // returns [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ]
+*
+* @example
+* var ndarray = require( '@stdlib/ndarray/ctor' );
+* var ndarray2array = require( '@stdlib/ndarray/to-array' );
+*
+* var xbuf = [ 1.0, null, 2.0, null, 3.0, null, 4.0, null, 5.0, null, 6.0, null ];
+*
+* var x = new ndarray( 'generic', xbuf, [ 2, 3 ], [ -6, -2 ], 10, 'row-major' );
+* // return
+*
+* var y = flatten( x );
+* // returns
+*
+* var arr = ndarray2array( y );
+* // returns [ 6.0, 5.0, 4.0, 3.0, 2.0, 1.0 ]
+*
+* @example
+* var ndarray = require( '@stdlib/ndarray/ctor' );
+* var ndarray2array = require( '@stdlib/ndarray/to-array' );
+*
+* var xbuf = [ 1.0, null, 2.0, null, 3.0, null, 4.0, null, 5.0, null, 6.0, null ];
+*
+* // Create an ndarray whose stated order is column-major, but which has been transposed:
+* var x = new ndarray( 'generic', xbuf, [ 2, 3 ], [ -6, -2 ], 10, 'column-major' );
+* // return
+*
+* var y = flatten( x );
+* // returns
+*
+* var arr = ndarray2array( y );
+* // returns [ 6.0, 5.0, 4.0, 3.0, 2.0, 1.0 ]
+*
+* @example
+* var ndarray = require( '@stdlib/ndarray/ctor' );
+* var ndarray2array = require( '@stdlib/ndarray/to-array' );
+*
+* var xbuf = [ 1.0, null, 2.0, null, 3.0, null, 4.0, null, 5.0, null, 6.0, null ];
+*
+* // Create an ndarray whose stated order is column-major, but which has been transposed:
+* var x = new ndarray( 'generic', xbuf, [ 2, 3 ], [ -6, -2 ], 10, 'column-major' );
+* // return
+*
+* var y = flatten( x, {
+* 'order': 'same'
+* });
+* // returns
+*
+* var arr = ndarray2array( y );
+* // returns [ 6.0, 3.0, 5.0, 2.0, 4.0, 1.0 ]
+*
+* @example
+* var ndarray = require( '@stdlib/ndarray/ctor' );
+* var ndarray2array = require( '@stdlib/ndarray/to-array' );
+*
+* var xbuf = [ 1.0, null, 2.0, null, 3.0, null, 4.0, null, 5.0, null, 6.0, null ];
+*
+* // Create an ndarray whose stated order is column-major, but which has been transposed:
+* var x = new ndarray( 'generic', xbuf, [ 2, 3 ], [ -6, -2 ], 10, 'column-major' );
+* // return
+*
+* var y = flatten( x, {
+* 'order': 'any'
+* });
+* // returns
+*
+* var arr = ndarray2array( y );
+* // returns [ 6.0, 5.0, 4.0, 3.0, 2.0, 1.0 ]
+*
+* @example
+* var ndarray = require( '@stdlib/ndarray/ctor' );
+* var ndarray2array = require( '@stdlib/ndarray/to-array' );
+*
+* var xbuf = [ 1.0, null, 2.0, null, 3.0, null, 4.0, null, 5.0, null, 6.0, null ];
+*
+* // Create an ndarray whose stated order is row-major, but which has been transposed:
+* var x = new ndarray( 'generic', xbuf, [ 2, 3 ], [ -2, -4 ], 10, 'row-major' );
+* // return
+*
+* var y = flatten( x );
+* // returns
+*
+* var arr = ndarray2array( y );
+* // returns [ 6.0, 4.0, 2.0, 5.0, 3.0, 1.0 ]
+*
+* @example
+* var ndarray = require( '@stdlib/ndarray/ctor' );
+* var ndarray2array = require( '@stdlib/ndarray/to-array' );
+*
+* var xbuf = [ 1.0, null, 2.0, null, 3.0, null, 4.0, null, 5.0, null, 6.0, null ];
+*
+* // Create an ndarray whose stated order is row-major, but which has been transposed:
+* var x = new ndarray( 'generic', xbuf, [ 2, 3 ], [ -2, -4 ], 10, 'row-major' );
+* // return
+*
+* var y = flatten( x, {
+* 'order': 'same'
+* });
+* // returns
+*
+* var arr = ndarray2array( y );
+* // returns [ 6.0, 4.0, 2.0, 5.0, 3.0, 1.0 ]
+*
+* @example
+* var ndarray = require( '@stdlib/ndarray/ctor' );
+* var ndarray2array = require( '@stdlib/ndarray/to-array' );
+*
+* var xbuf = [ 1.0, null, 2.0, null, 3.0, null, 4.0, null, 5.0, null, 6.0, null ];
+*
+* // Create an ndarray whose stated order is row-major, but which has been transposed:
+* var x = new ndarray( 'generic', xbuf, [ 2, 3 ], [ -2, -4 ], 10, 'row-major' );
+* // return
+*
+* var y = flatten( x, {
+* 'order': 'any'
+* });
+* // returns
+*
+* var arr = ndarray2array( y );
+* // returns [ 6.0, 5.0, 4.0, 3.0, 2.0, 1.0 ]
+*/
+function flatten( x, options ) {
+ var nargs;
+ var view;
+ var opts;
+ var xsh;
+ var st;
+ var o;
+ var y;
+
+ if ( !isndarrayLike( x ) ) {
+ throw new TypeError( format( 'invalid argument. First argument must be an ndarray-like object. Value: `%s`.', x ) );
+ }
+ nargs = arguments.length;
+ xsh = getShape( x );
+
+ // Define default options:
+ opts = {
+ 'depth': xsh.length, // by default, flatten to a one-dimensional ndarray
+ 'order': ROW_MAJOR // by default, flatten in lexicographic order (i.e., trailing dimensions first; e.g., if `x` is a matrix, flatten row-by-row)
+ };
+
+ // Resolve function options...
+ if ( nargs === 2 ) {
+ if ( !isPlainObject( options ) ) {
+ throw new TypeError( format( 'invalid argument. Options argument must be an object. Value: `%s`.', options ) );
+ }
+ if ( hasOwnProp( options, 'depth' ) ) {
+ if ( !isNonNegativeInteger( options.depth ) ) {
+ throw new TypeError( format( 'invalid option. `%s` option must be a nonnegative integer. Option: `%s`.', options.depth ) );
+ }
+ opts.depth = options.depth;
+ }
+ if ( hasOwnProp( options, 'order' ) ) {
+ if ( options.order === 'any' ) {
+ // When 'any', we want to flatten according to the physical layout of the data in memory...
+ o = strides2order( getStrides( x ) );
+ if ( o === 1 ) {
+ // Data is currently arranged in row-major order:
+ opts.order = ROW_MAJOR;
+ } else if ( o === 2 ) {
+ // Data is currently arranged in column-major order:
+ opts.order = COL_MAJOR;
+ } else { // o === 0 || o === 3 (i.e., neither row- nor column-major || both row- and column-major
+ // When the data is either both row- and column-major (e.g., a one-dimensional ndarray) or neither row- nor column-major (e.g., unordered strides), fallback to flattening according to the stated order of the input ndarray:
+ opts.order = getOrder( x );
+ }
+ } else if ( options.order === 'same' ) {
+ // When 'same', we want to flatten according to the stated order of the input ndarray:
+ opts.order = getOrder( x );
+ } else if ( isOrder( options.order ) ) {
+ // When provided a specific order, flatten according to that order regardless of the order of the input ndarray:
+ opts.order = options.order;
+ } else {
+ throw new TypeError( format( 'invalid option. `%s` option must be a recognized order. Option: `%s`.', 'order', options.order ) );
+ }
+ }
+ }
+ // Create an output ndarray having contiguous memory:
+ y = emptyLike( x, {
+ 'shape': flattenShape( xsh, opts.depth ),
+ 'order': opts.order
+ });
+
+ // Create a view on top of output ndarray having the same shape as the input ndarray:
+ st = ( xsh.length > 0 ) ? shape2strides( xsh, opts.order ) : [ 0 ];
+ view = ndarray( getDType( y ), getData( y ), xsh, st, 0, opts.order );
+
+ // Copy elements to the output ndarray:
+ assign( [ x, view ] );
+
+ return y;
+}
+
+
+// EXPORTS //
+
+module.exports = flatten;
diff --git a/lib/node_modules/@stdlib/ndarray/flatten/package.json b/lib/node_modules/@stdlib/ndarray/flatten/package.json
new file mode 100644
index 000000000000..317642b2cdde
--- /dev/null
+++ b/lib/node_modules/@stdlib/ndarray/flatten/package.json
@@ -0,0 +1,65 @@
+{
+ "name": "@stdlib/ndarray/flatten",
+ "version": "0.0.0",
+ "description": "Return a flattened copy of an input ndarray.",
+ "license": "Apache-2.0",
+ "author": {
+ "name": "The Stdlib Authors",
+ "url": "https://github.com/stdlib-js/stdlib/graphs/contributors"
+ },
+ "contributors": [
+ {
+ "name": "The Stdlib Authors",
+ "url": "https://github.com/stdlib-js/stdlib/graphs/contributors"
+ }
+ ],
+ "main": "./lib",
+ "directories": {
+ "benchmark": "./benchmark",
+ "doc": "./docs",
+ "example": "./examples",
+ "lib": "./lib",
+ "test": "./test"
+ },
+ "types": "./docs/types",
+ "scripts": {},
+ "homepage": "https://github.com/stdlib-js/stdlib",
+ "repository": {
+ "type": "git",
+ "url": "git://github.com/stdlib-js/stdlib.git"
+ },
+ "bugs": {
+ "url": "https://github.com/stdlib-js/stdlib/issues"
+ },
+ "dependencies": {},
+ "devDependencies": {},
+ "engines": {
+ "node": ">=0.10.0",
+ "npm": ">2.7.0"
+ },
+ "os": [
+ "aix",
+ "darwin",
+ "freebsd",
+ "linux",
+ "macos",
+ "openbsd",
+ "sunos",
+ "win32",
+ "windows"
+ ],
+ "keywords": [
+ "stdlib",
+ "multidimensional",
+ "array",
+ "ndarray",
+ "tensor",
+ "matrix",
+ "flat",
+ "flatten",
+ "reshape",
+ "copy",
+ "transform"
+ ],
+ "__stdlib__": {}
+}
diff --git a/lib/node_modules/@stdlib/ndarray/flatten/test/test.js b/lib/node_modules/@stdlib/ndarray/flatten/test/test.js
new file mode 100644
index 000000000000..02a079145248
--- /dev/null
+++ b/lib/node_modules/@stdlib/ndarray/flatten/test/test.js
@@ -0,0 +1,1360 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+* http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+/* eslint-disable max-len */
+
+'use strict';
+
+// MODULES //
+
+var tape = require( 'tape' );
+var isSameFloat64Array = require( '@stdlib/assert/is-same-float64array' );
+var zeros = require( '@stdlib/ndarray/zeros' );
+var ndarray = require( '@stdlib/ndarray/ctor' );
+var Float64Array = require( '@stdlib/array/float64' );
+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 shape2strides = require( '@stdlib/ndarray/base/shape2strides' );
+var strides2offset = require( '@stdlib/ndarray/base/strides2offset' );
+var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' );
+var ndarray2array = require( '@stdlib/ndarray/to-array' );
+var flatten = require( './../lib' );
+
+
+// TESTS //
+
+tape( 'main export is a function', function test( t ) {
+ t.ok( true, __filename );
+ t.strictEqual( typeof flatten, 'function', 'main export is a function' );
+ t.end();
+});
+
+tape( 'the function throws an error if provided a first argument which is not an 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() {
+ flatten( value );
+ };
+ }
+});
+
+tape( 'the function throws an error if provided a first argument which is not an 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() {
+ flatten( value, {} );
+ };
+ }
+});
+
+tape( 'the function throws an error if provided an options argument which is not an 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() {
+ flatten( zeros( [ 2, 2, 2 ] ), value );
+ };
+ }
+});
+
+tape( 'the function throws an error if provided an invalid `depth` option', function test( t ) {
+ var values;
+ var opts;
+ 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() {
+ opts = {
+ 'depth': value
+ };
+ flatten( zeros( [ 2 ] ), opts );
+ };
+ }
+});
+
+tape( 'the function throws an error if provided an invalid `order` option', function test( t ) {
+ var values;
+ var opts;
+ var i;
+
+ values = [
+ '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() {
+ opts = {
+ 'order': value
+ };
+ flatten( zeros( [ 2 ] ), opts );
+ };
+ }
+});
+
+tape( 'by default, the function flattens all dimensions of a provided input ndarray in lexicographic order (row-major, contiguous)', function test( t ) {
+ var expected;
+ var xbuf;
+ var ord;
+ var sh;
+ var st;
+ var dt;
+ var o;
+ var x;
+ var y;
+
+ dt = 'float64';
+ ord = 'row-major';
+ sh = [ 2, 2, 2 ];
+ st = shape2strides( sh, ord );
+ o = strides2offset( sh, st );
+
+ /*
+ * [
+ * [
+ * [ 1.0, 2.0 ],
+ * [ 3.0, 4.0 ]
+ * ],
+ * [
+ * [ 5.0, 6.0 ],
+ * [ 7.0, 8.0 ]
+ * ]
+ * ]
+ */
+ xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] );
+ x = new ndarray( dt, xbuf, sh, st, o, ord );
+
+ y = flatten( x );
+ expected = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] );
+
+ t.notEqual( y, x, 'returns expected value' );
+ t.notEqual( getData( y ), xbuf, 'returns expected value' );
+ t.strictEqual( isSameFloat64Array( getData( y ), expected ), true, 'returns expected value' );
+ t.deepEqual( getShape( y ), [ 8 ], 'returns expected value' );
+ t.strictEqual( getDType( y ), dt, 'returns expected value' );
+ t.strictEqual( getOrder( y ), 'row-major', 'returns expected value' );
+
+ t.end();
+});
+
+tape( 'by default, the function flattens all dimensions of a provided input ndarray in lexicographic order (row-major, non-contiguous)', function test( t ) {
+ var expected;
+ var xbuf;
+ var ord;
+ var sh;
+ var st;
+ var dt;
+ var o;
+ var x;
+ var y;
+
+ dt = 'float64';
+ ord = 'row-major';
+ sh = [ 2, 2, 2 ];
+ st = [ 8, 4, 2 ];
+ o = strides2offset( sh, st );
+
+ /*
+ * [
+ * [
+ * [ 1.0, 2.0 ],
+ * [ 3.0, 4.0 ]
+ * ],
+ * [
+ * [ 5.0, 6.0 ],
+ * [ 7.0, 8.0 ]
+ * ]
+ * ]
+ */
+ xbuf = new Float64Array( [ 1.0, NaN, 2.0, NaN, 3.0, NaN, 4.0, NaN, 5.0, NaN, 6.0, NaN, 7.0, NaN, 8.0, NaN ] );
+ x = new ndarray( dt, xbuf, sh, st, o, ord );
+
+ y = flatten( x );
+ expected = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] );
+
+ t.notEqual( y, x, 'returns expected value' );
+ t.notEqual( getData( y ), xbuf, 'returns expected value' );
+ t.strictEqual( isSameFloat64Array( getData( y ), expected ), true, 'returns expected value' );
+ t.deepEqual( getShape( y ), [ 8 ], 'returns expected value' );
+ t.strictEqual( getDType( y ), dt, 'returns expected value' );
+ t.strictEqual( getOrder( y ), 'row-major', 'returns expected value' );
+
+ t.end();
+});
+
+tape( 'by default, the function flattens all dimensions of a provided input ndarray in lexicographic order (column-major, contiguous)', function test( t ) {
+ var expected;
+ var xbuf;
+ var ord;
+ var sh;
+ var st;
+ var dt;
+ var o;
+ var x;
+ var y;
+
+ dt = 'float64';
+ ord = 'column-major';
+ sh = [ 2, 2, 2 ];
+ st = shape2strides( sh, ord );
+ o = strides2offset( sh, st );
+
+ /*
+ * [
+ * [
+ * [ 1.0, 2.0 ],
+ * [ 3.0, 4.0 ]
+ * ],
+ * [
+ * [ 5.0, 6.0 ],
+ * [ 7.0, 8.0 ]
+ * ]
+ * ]
+ */
+ xbuf = new Float64Array( [ 1.0, 5.0, 3.0, 7.0, 2.0, 6.0, 4.0, 8.0 ] );
+ x = new ndarray( dt, xbuf, sh, st, o, ord );
+
+ y = flatten( x );
+ expected = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] );
+
+ t.notEqual( y, x, 'returns expected value' );
+ t.notEqual( getData( y ), xbuf, 'returns expected value' );
+ t.strictEqual( isSameFloat64Array( getData( y ), expected ), true, 'returns expected value' );
+ t.deepEqual( getShape( y ), [ 8 ], 'returns expected value' );
+ t.strictEqual( getDType( y ), dt, 'returns expected value' );
+ t.strictEqual( getOrder( y ), 'row-major', 'returns expected value' );
+
+ t.end();
+});
+
+tape( 'by default, the function flattens all dimensions of a provided input ndarray in lexicographic order (column-major, non-contiguous)', function test( t ) {
+ var expected;
+ var xbuf;
+ var ord;
+ var sh;
+ var st;
+ var dt;
+ var o;
+ var x;
+ var y;
+
+ dt = 'float64';
+ ord = 'column-major';
+ sh = [ 2, 2, 2 ];
+ st = [ 2, 4, 8 ];
+ o = strides2offset( sh, st );
+
+ /*
+ * [
+ * [
+ * [ 1.0, 2.0 ],
+ * [ 3.0, 4.0 ]
+ * ],
+ * [
+ * [ 5.0, 6.0 ],
+ * [ 7.0, 8.0 ]
+ * ]
+ * ]
+ */
+ xbuf = new Float64Array( [ 1.0, NaN, 5.0, NaN, 3.0, NaN, 7.0, NaN, 2.0, NaN, 6.0, NaN, 4.0, NaN, 8.0, NaN ] );
+ x = new ndarray( dt, xbuf, sh, st, o, ord );
+
+ y = flatten( x );
+ expected = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] );
+
+ t.notEqual( y, x, 'returns expected value' );
+ t.notEqual( getData( y ), xbuf, 'returns expected value' );
+ t.strictEqual( isSameFloat64Array( getData( y ), expected ), true, 'returns expected value' );
+ t.deepEqual( getShape( y ), [ 8 ], 'returns expected value' );
+ t.strictEqual( getDType( y ), dt, 'returns expected value' );
+ t.strictEqual( getOrder( y ), 'row-major', 'returns expected value' );
+
+ t.end();
+});
+
+tape( 'the function supports specifying the maximum number of dimensions to flatten (row-major)', function test( t ) {
+ var expected;
+ var xbuf;
+ var ord;
+ var sh;
+ var st;
+ var dt;
+ var o;
+ var x;
+ var y;
+
+ dt = 'float64';
+ ord = 'row-major';
+ sh = [ 2, 2, 2 ];
+ st = shape2strides( sh, ord );
+ o = strides2offset( sh, st );
+
+ /*
+ * [
+ * [
+ * [ 1.0, 2.0 ],
+ * [ 3.0, 4.0 ]
+ * ],
+ * [
+ * [ 5.0, 6.0 ],
+ * [ 7.0, 8.0 ]
+ * ]
+ * ]
+ */
+ xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] );
+ x = new ndarray( dt, xbuf, sh, st, o, ord );
+
+ y = flatten( x, {
+ 'depth': 0
+ });
+ expected = [
+ [
+ [ 1.0, 2.0 ],
+ [ 3.0, 4.0 ]
+ ],
+ [
+ [ 5.0, 6.0 ],
+ [ 7.0, 8.0 ]
+ ]
+ ];
+
+ t.notEqual( y, x, 'returns expected value' );
+ t.notEqual( getData( y ), xbuf, 'returns expected value' );
+ t.deepEqual( ndarray2array( y ), expected, 'returns expected value' );
+ t.deepEqual( getShape( y ), [ 2, 2, 2 ], 'returns expected value' );
+ t.strictEqual( getDType( y ), dt, 'returns expected value' );
+ t.strictEqual( getOrder( y ), 'row-major', 'returns expected value' );
+
+ y = flatten( x, {
+ 'depth': 1
+ });
+ expected = [
+ [ 1.0, 2.0 ],
+ [ 3.0, 4.0 ],
+ [ 5.0, 6.0 ],
+ [ 7.0, 8.0 ]
+ ];
+
+ t.notEqual( y, x, 'returns expected value' );
+ t.notEqual( getData( y ), xbuf, 'returns expected value' );
+ t.deepEqual( ndarray2array( y ), expected, 'returns expected value' );
+ t.deepEqual( getShape( y ), [ 4, 2 ], 'returns expected value' );
+ t.strictEqual( getDType( y ), dt, 'returns expected value' );
+ t.strictEqual( getOrder( y ), 'row-major', 'returns expected value' );
+
+ y = flatten( x, {
+ 'depth': 2
+ });
+ expected = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ];
+
+ t.notEqual( y, x, 'returns expected value' );
+ t.notEqual( getData( y ), xbuf, 'returns expected value' );
+ t.deepEqual( ndarray2array( y ), expected, 'returns expected value' );
+ t.deepEqual( getShape( y ), [ 8 ], 'returns expected value' );
+ t.strictEqual( getDType( y ), dt, 'returns expected value' );
+ t.strictEqual( getOrder( y ), 'row-major', 'returns expected value' );
+
+ t.end();
+});
+
+tape( 'the function supports specifying the maximum number of dimensions to flatten (column-major)', function test( t ) {
+ var expected;
+ var xbuf;
+ var ord;
+ var sh;
+ var st;
+ var dt;
+ var o;
+ var x;
+ var y;
+
+ dt = 'float64';
+ ord = 'column-major';
+ sh = [ 2, 2, 2 ];
+ st = shape2strides( sh, ord );
+ o = strides2offset( sh, st );
+
+ /*
+ * [
+ * [
+ * [ 1.0, 2.0 ],
+ * [ 3.0, 4.0 ]
+ * ],
+ * [
+ * [ 5.0, 6.0 ],
+ * [ 7.0, 8.0 ]
+ * ]
+ * ]
+ */
+ xbuf = new Float64Array( [ 1.0, 5.0, 3.0, 7.0, 2.0, 6.0, 4.0, 8.0 ] );
+ x = new ndarray( dt, xbuf, sh, st, o, ord );
+
+ y = flatten( x, {
+ 'depth': 0
+ });
+ expected = [
+ [
+ [ 1.0, 2.0 ],
+ [ 3.0, 4.0 ]
+ ],
+ [
+ [ 5.0, 6.0 ],
+ [ 7.0, 8.0 ]
+ ]
+ ];
+
+ t.notEqual( y, x, 'returns expected value' );
+ t.notEqual( getData( y ), xbuf, 'returns expected value' );
+ t.deepEqual( ndarray2array( y ), expected, 'returns expected value' );
+ t.deepEqual( getShape( y ), [ 2, 2, 2 ], 'returns expected value' );
+ t.strictEqual( getDType( y ), dt, 'returns expected value' );
+ t.strictEqual( getOrder( y ), 'row-major', 'returns expected value' );
+
+ y = flatten( x, {
+ 'depth': 1
+ });
+ expected = [
+ [ 1.0, 2.0 ],
+ [ 3.0, 4.0 ],
+ [ 5.0, 6.0 ],
+ [ 7.0, 8.0 ]
+ ];
+
+ t.notEqual( y, x, 'returns expected value' );
+ t.notEqual( getData( y ), xbuf, 'returns expected value' );
+ t.deepEqual( ndarray2array( y ), expected, 'returns expected value' );
+ t.deepEqual( getShape( y ), [ 4, 2 ], 'returns expected value' );
+ t.strictEqual( getDType( y ), dt, 'returns expected value' );
+ t.strictEqual( getOrder( y ), 'row-major', 'returns expected value' );
+
+ y = flatten( x, {
+ 'depth': 2
+ });
+ expected = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ];
+
+ t.notEqual( y, x, 'returns expected value' );
+ t.notEqual( getData( y ), xbuf, 'returns expected value' );
+ t.deepEqual( ndarray2array( y ), expected, 'returns expected value' );
+ t.deepEqual( getShape( y ), [ 8 ], 'returns expected value' );
+ t.strictEqual( getDType( y ), dt, 'returns expected value' );
+ t.strictEqual( getOrder( y ), 'row-major', 'returns expected value' );
+
+ t.end();
+});
+
+tape( 'the function supports flattening a provided input ndarray in lexicographic order (row-major)', function test( t ) {
+ var expected;
+ var xbuf;
+ var ord;
+ var sh;
+ var st;
+ var dt;
+ var o;
+ var x;
+ var y;
+
+ dt = 'float64';
+ ord = 'row-major';
+ sh = [ 2, 2, 2 ];
+ st = shape2strides( sh, ord );
+ o = strides2offset( sh, st );
+
+ /*
+ * [
+ * [
+ * [ 1.0, 2.0 ],
+ * [ 3.0, 4.0 ]
+ * ],
+ * [
+ * [ 5.0, 6.0 ],
+ * [ 7.0, 8.0 ]
+ * ]
+ * ]
+ */
+ xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] );
+ x = new ndarray( dt, xbuf, sh, st, o, ord );
+
+ y = flatten( x, {
+ 'order': 'row-major'
+ });
+ expected = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] );
+
+ t.notEqual( y, x, 'returns expected value' );
+ t.notEqual( getData( y ), xbuf, 'returns expected value' );
+ t.strictEqual( isSameFloat64Array( getData( y ), expected ), true, 'returns expected value' );
+ t.deepEqual( getShape( y ), [ 8 ], 'returns expected value' );
+ t.strictEqual( getDType( y ), dt, 'returns expected value' );
+ t.strictEqual( getOrder( y ), 'row-major', 'returns expected value' );
+
+ y = flatten( x, {
+ 'depth': 1,
+ 'order': 'row-major'
+ });
+ expected = [
+ [ 1.0, 2.0 ],
+ [ 3.0, 4.0 ],
+ [ 5.0, 6.0 ],
+ [ 7.0, 8.0 ]
+ ];
+
+ t.notEqual( y, x, 'returns expected value' );
+ t.notEqual( getData( y ), xbuf, 'returns expected value' );
+ t.deepEqual( ndarray2array( y ), expected, 'returns expected value' );
+ t.deepEqual( getShape( y ), [ 4, 2 ], 'returns expected value' );
+ t.strictEqual( getDType( y ), dt, 'returns expected value' );
+ t.strictEqual( getOrder( y ), 'row-major', 'returns expected value' );
+
+ t.end();
+});
+
+tape( 'the function supports flattening a provided input ndarray in lexicographic order (column-major)', function test( t ) {
+ var expected;
+ var xbuf;
+ var ord;
+ var sh;
+ var st;
+ var dt;
+ var o;
+ var x;
+ var y;
+
+ dt = 'float64';
+ ord = 'column-major';
+ sh = [ 2, 2, 2 ];
+ st = shape2strides( sh, ord );
+ o = strides2offset( sh, st );
+
+ /*
+ * [
+ * [
+ * [ 1.0, 2.0 ],
+ * [ 3.0, 4.0 ]
+ * ],
+ * [
+ * [ 5.0, 6.0 ],
+ * [ 7.0, 8.0 ]
+ * ]
+ * ]
+ */
+ xbuf = new Float64Array( [ 1.0, 5.0, 3.0, 7.0, 2.0, 6.0, 4.0, 8.0 ] );
+ x = new ndarray( dt, xbuf, sh, st, o, ord );
+
+ y = flatten( x, {
+ 'order': 'row-major'
+ });
+ expected = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] );
+
+ t.notEqual( y, x, 'returns expected value' );
+ t.notEqual( getData( y ), xbuf, 'returns expected value' );
+ t.strictEqual( isSameFloat64Array( getData( y ), expected ), true, 'returns expected value' );
+ t.deepEqual( getShape( y ), [ 8 ], 'returns expected value' );
+ t.strictEqual( getDType( y ), dt, 'returns expected value' );
+ t.strictEqual( getOrder( y ), 'row-major', 'returns expected value' );
+
+ y = flatten( x, {
+ 'depth': 1,
+ 'order': 'row-major'
+ });
+ expected = [
+ [ 1.0, 2.0 ],
+ [ 3.0, 4.0 ],
+ [ 5.0, 6.0 ],
+ [ 7.0, 8.0 ]
+ ];
+
+ t.notEqual( y, x, 'returns expected value' );
+ t.notEqual( getData( y ), xbuf, 'returns expected value' );
+ t.deepEqual( ndarray2array( y ), expected, 'returns expected value' );
+ t.deepEqual( getShape( y ), [ 4, 2 ], 'returns expected value' );
+ t.strictEqual( getDType( y ), dt, 'returns expected value' );
+ t.strictEqual( getOrder( y ), 'row-major', 'returns expected value' );
+
+ t.end();
+});
+
+tape( 'the function supports flattening a provided input ndarray in colexicographic order (row-major)', function test( t ) {
+ var expected;
+ var xbuf;
+ var ord;
+ var sh;
+ var st;
+ var dt;
+ var o;
+ var x;
+ var y;
+
+ dt = 'float64';
+ ord = 'row-major';
+ sh = [ 2, 2, 2 ];
+ st = shape2strides( sh, ord );
+ o = strides2offset( sh, st );
+
+ /*
+ * [
+ * [
+ * [ 1.0, 2.0 ],
+ * [ 3.0, 4.0 ]
+ * ],
+ * [
+ * [ 5.0, 6.0 ],
+ * [ 7.0, 8.0 ]
+ * ]
+ * ]
+ */
+ xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] );
+ x = new ndarray( dt, xbuf, sh, st, o, ord );
+
+ y = flatten( x, {
+ 'order': 'column-major'
+ });
+ expected = new Float64Array( [ 1.0, 5.0, 3.0, 7.0, 2.0, 6.0, 4.0, 8.0 ] );
+
+ t.notEqual( y, x, 'returns expected value' );
+ t.notEqual( getData( y ), xbuf, 'returns expected value' );
+ t.strictEqual( isSameFloat64Array( getData( y ), expected ), true, 'returns expected value' );
+ t.deepEqual( getShape( y ), [ 8 ], 'returns expected value' );
+ t.strictEqual( getDType( y ), dt, 'returns expected value' );
+ t.strictEqual( getOrder( y ), 'column-major', 'returns expected value' );
+
+ y = flatten( x, {
+ 'depth': 1,
+ 'order': 'column-major'
+ });
+ expected = [
+ [ 1.0, 2.0 ],
+ [ 5.0, 6.0 ],
+ [ 3.0, 4.0 ],
+ [ 7.0, 8.0 ]
+ ];
+
+ t.notEqual( y, x, 'returns expected value' );
+ t.notEqual( getData( y ), xbuf, 'returns expected value' );
+ t.deepEqual( ndarray2array( y ), expected, 'returns expected value' );
+ t.deepEqual( getShape( y ), [ 4, 2 ], 'returns expected value' );
+ t.strictEqual( getDType( y ), dt, 'returns expected value' );
+ t.strictEqual( getOrder( y ), 'column-major', 'returns expected value' );
+
+ t.end();
+});
+
+tape( 'the function supports flattening a provided input ndarray in colexicographic order (column-major)', function test( t ) {
+ var expected;
+ var xbuf;
+ var ord;
+ var sh;
+ var st;
+ var dt;
+ var o;
+ var x;
+ var y;
+
+ dt = 'float64';
+ ord = 'column-major';
+ sh = [ 2, 2, 2 ];
+ st = shape2strides( sh, ord );
+ o = strides2offset( sh, st );
+
+ /*
+ * [
+ * [
+ * [ 1.0, 2.0 ],
+ * [ 3.0, 4.0 ]
+ * ],
+ * [
+ * [ 5.0, 6.0 ],
+ * [ 7.0, 8.0 ]
+ * ]
+ * ]
+ */
+ xbuf = new Float64Array( [ 1.0, 5.0, 3.0, 7.0, 2.0, 6.0, 4.0, 8.0 ] );
+ x = new ndarray( dt, xbuf, sh, st, o, ord );
+
+ y = flatten( x, {
+ 'order': 'column-major'
+ });
+ expected = new Float64Array( [ 1.0, 5.0, 3.0, 7.0, 2.0, 6.0, 4.0, 8.0 ] );
+
+ t.notEqual( y, x, 'returns expected value' );
+ t.notEqual( getData( y ), xbuf, 'returns expected value' );
+ t.strictEqual( isSameFloat64Array( getData( y ), expected ), true, 'returns expected value' );
+ t.deepEqual( getShape( y ), [ 8 ], 'returns expected value' );
+ t.strictEqual( getDType( y ), dt, 'returns expected value' );
+ t.strictEqual( getOrder( y ), 'column-major', 'returns expected value' );
+
+ y = flatten( x, {
+ 'depth': 1,
+ 'order': 'column-major'
+ });
+ expected = [
+ [ 1.0, 2.0 ],
+ [ 5.0, 6.0 ],
+ [ 3.0, 4.0 ],
+ [ 7.0, 8.0 ]
+ ];
+
+ t.notEqual( y, x, 'returns expected value' );
+ t.notEqual( getData( y ), xbuf, 'returns expected value' );
+ t.deepEqual( ndarray2array( y ), expected, 'returns expected value' );
+ t.deepEqual( getShape( y ), [ 4, 2 ], 'returns expected value' );
+ t.strictEqual( getDType( y ), dt, 'returns expected value' );
+ t.strictEqual( getOrder( y ), 'column-major', 'returns expected value' );
+
+ t.end();
+});
+
+tape( 'the function supports flattening a provided input ndarray in same order as the input ndarray (row-major)', function test( t ) {
+ var expected;
+ var xbuf;
+ var ord;
+ var sh;
+ var st;
+ var dt;
+ var o;
+ var x;
+ var y;
+
+ dt = 'float64';
+ ord = 'row-major';
+ sh = [ 2, 2, 2 ];
+ st = shape2strides( sh, ord );
+ o = strides2offset( sh, st );
+
+ /*
+ * [
+ * [
+ * [ 1.0, 2.0 ],
+ * [ 3.0, 4.0 ]
+ * ],
+ * [
+ * [ 5.0, 6.0 ],
+ * [ 7.0, 8.0 ]
+ * ]
+ * ]
+ */
+ xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] );
+ x = new ndarray( dt, xbuf, sh, st, o, ord );
+
+ y = flatten( x, {
+ 'order': 'same'
+ });
+ expected = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] );
+
+ t.notEqual( y, x, 'returns expected value' );
+ t.notEqual( getData( y ), xbuf, 'returns expected value' );
+ t.strictEqual( isSameFloat64Array( getData( y ), expected ), true, 'returns expected value' );
+ t.deepEqual( getShape( y ), [ 8 ], 'returns expected value' );
+ t.strictEqual( getDType( y ), dt, 'returns expected value' );
+ t.strictEqual( getOrder( y ), 'row-major', 'returns expected value' );
+
+ y = flatten( x, {
+ 'depth': 1,
+ 'order': 'same'
+ });
+ expected = [
+ [ 1.0, 2.0 ],
+ [ 3.0, 4.0 ],
+ [ 5.0, 6.0 ],
+ [ 7.0, 8.0 ]
+ ];
+
+ t.notEqual( y, x, 'returns expected value' );
+ t.notEqual( getData( y ), xbuf, 'returns expected value' );
+ t.deepEqual( ndarray2array( y ), expected, 'returns expected value' );
+ t.deepEqual( getShape( y ), [ 4, 2 ], 'returns expected value' );
+ t.strictEqual( getDType( y ), dt, 'returns expected value' );
+ t.strictEqual( getOrder( y ), 'row-major', 'returns expected value' );
+
+ t.end();
+});
+
+tape( 'the function supports flattening a provided input ndarray in same order as the input ndarray (column-major)', function test( t ) {
+ var expected;
+ var xbuf;
+ var ord;
+ var sh;
+ var st;
+ var dt;
+ var o;
+ var x;
+ var y;
+
+ dt = 'float64';
+ ord = 'column-major';
+ sh = [ 2, 2, 2 ];
+ st = shape2strides( sh, ord );
+ o = strides2offset( sh, st );
+
+ /*
+ * [
+ * [
+ * [ 1.0, 2.0 ],
+ * [ 3.0, 4.0 ]
+ * ],
+ * [
+ * [ 5.0, 6.0 ],
+ * [ 7.0, 8.0 ]
+ * ]
+ * ]
+ */
+ xbuf = new Float64Array( [ 1.0, 5.0, 3.0, 7.0, 2.0, 6.0, 4.0, 8.0 ] );
+ x = new ndarray( dt, xbuf, sh, st, o, ord );
+
+ y = flatten( x, {
+ 'order': 'same'
+ });
+ expected = new Float64Array( [ 1.0, 5.0, 3.0, 7.0, 2.0, 6.0, 4.0, 8.0 ] );
+
+ t.notEqual( y, x, 'returns expected value' );
+ t.notEqual( getData( y ), xbuf, 'returns expected value' );
+ t.strictEqual( isSameFloat64Array( getData( y ), expected ), true, 'returns expected value' );
+ t.deepEqual( getShape( y ), [ 8 ], 'returns expected value' );
+ t.strictEqual( getDType( y ), dt, 'returns expected value' );
+ t.strictEqual( getOrder( y ), 'column-major', 'returns expected value' );
+
+ y = flatten( x, {
+ 'depth': 1,
+ 'order': 'same'
+ });
+ expected = [
+ [ 1.0, 2.0 ],
+ [ 5.0, 6.0 ],
+ [ 3.0, 4.0 ],
+ [ 7.0, 8.0 ]
+ ];
+
+ t.notEqual( y, x, 'returns expected value' );
+ t.notEqual( getData( y ), xbuf, 'returns expected value' );
+ t.deepEqual( ndarray2array( y ), expected, 'returns expected value' );
+ t.deepEqual( getShape( y ), [ 4, 2 ], 'returns expected value' );
+ t.strictEqual( getDType( y ), dt, 'returns expected value' );
+ t.strictEqual( getOrder( y ), 'column-major', 'returns expected value' );
+
+ t.end();
+});
+
+tape( 'the function supports flattening a provided input ndarray according to the physical layout of the input ndarray (row-major)', function test( t ) {
+ var expected;
+ var xbuf;
+ var ord;
+ var sh;
+ var st;
+ var dt;
+ var o;
+ var x;
+ var y;
+
+ dt = 'float64';
+ ord = 'row-major';
+ sh = [ 2, 2, 2 ];
+ st = [ -1, -2, -4 ]; // reversing and negating the strides simulates a flipped and reversed view
+ o = strides2offset( sh, st );
+
+ /*
+ * [
+ * [
+ * [ 8.0, 4.0 ],
+ * [ 6.0, 2.0 ]
+ * ],
+ * [
+ * [ 7.0, 3.0 ],
+ * [ 5.0, 1.0 ]
+ * ]
+ * ]
+ */
+ xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] );
+ x = new ndarray( dt, xbuf, sh, st, o, ord );
+
+ y = flatten( x, {
+ 'order': 'any'
+ });
+ expected = new Float64Array( [ 8.0, 7.0, 6.0, 5.0, 4.0, 3.0, 2.0, 1.0 ] );
+
+ t.notEqual( y, x, 'returns expected value' );
+ t.notEqual( getData( y ), xbuf, 'returns expected value' );
+ t.strictEqual( isSameFloat64Array( getData( y ), expected ), true, 'returns expected value' );
+ t.deepEqual( getShape( y ), [ 8 ], 'returns expected value' );
+ t.strictEqual( getDType( y ), dt, 'returns expected value' );
+ t.strictEqual( getOrder( y ), 'column-major', 'returns expected value' );
+
+ y = flatten( x, {
+ 'depth': 1,
+ 'order': 'any'
+ });
+ expected = [
+ [ 8.0, 4.0 ],
+ [ 7.0, 3.0 ],
+ [ 6.0, 2.0 ],
+ [ 5.0, 1.0 ]
+ ];
+
+ t.notEqual( y, x, 'returns expected value' );
+ t.notEqual( getData( y ), xbuf, 'returns expected value' );
+ t.deepEqual( ndarray2array( y ), expected, 'returns expected value' );
+ t.deepEqual( getShape( y ), [ 4, 2 ], 'returns expected value' );
+ t.strictEqual( getDType( y ), dt, 'returns expected value' );
+ t.strictEqual( getOrder( y ), 'column-major', 'returns expected value' );
+
+ t.end();
+});
+
+tape( 'the function supports flattening a provided input ndarray according to the physical layout of the input ndarray (column-major)', function test( t ) {
+ var expected;
+ var xbuf;
+ var ord;
+ var sh;
+ var st;
+ var dt;
+ var o;
+ var x;
+ var y;
+
+ dt = 'float64';
+ ord = 'column-major';
+ sh = [ 2, 2, 2 ];
+ st = [ -4, -2, -1 ]; // reversing and negating the strides simulates a flipped and reversed view
+ o = strides2offset( sh, st );
+
+ /*
+ * [
+ * [
+ * [ 8.0, 7.0 ],
+ * [ 6.0, 5.0 ]
+ * ],
+ * [
+ * [ 4.0, 3.0 ],
+ * [ 2.0, 1.0 ]
+ * ]
+ * ]
+ */
+ xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] );
+ x = new ndarray( dt, xbuf, sh, st, o, ord );
+
+ y = flatten( x, {
+ 'order': 'any'
+ });
+ expected = new Float64Array( [ 8.0, 7.0, 6.0, 5.0, 4.0, 3.0, 2.0, 1.0 ] );
+
+ t.notEqual( y, x, 'returns expected value' );
+ t.notEqual( getData( y ), xbuf, 'returns expected value' );
+ t.strictEqual( isSameFloat64Array( getData( y ), expected ), true, 'returns expected value' );
+ t.deepEqual( getShape( y ), [ 8 ], 'returns expected value' );
+ t.strictEqual( getDType( y ), dt, 'returns expected value' );
+ t.strictEqual( getOrder( y ), 'row-major', 'returns expected value' );
+
+ y = flatten( x, {
+ 'depth': 1,
+ 'order': 'any'
+ });
+ expected = [
+ [ 8.0, 7.0 ],
+ [ 6.0, 5.0 ],
+ [ 4.0, 3.0 ],
+ [ 2.0, 1.0 ]
+ ];
+
+ t.notEqual( y, x, 'returns expected value' );
+ t.notEqual( getData( y ), xbuf, 'returns expected value' );
+ t.deepEqual( ndarray2array( y ), expected, 'returns expected value' );
+ t.deepEqual( getShape( y ), [ 4, 2 ], 'returns expected value' );
+ t.strictEqual( getDType( y ), dt, 'returns expected value' );
+ t.strictEqual( getOrder( y ), 'row-major', 'returns expected value' );
+
+ t.end();
+});
+
+tape( 'the function supports flattening a zero-dimensional input ndarray', function test( t ) {
+ var expected;
+ var xbuf;
+ var dt;
+ var x;
+ var y;
+
+ dt = 'float64';
+ x = scalar2ndarray( 3.0, {
+ 'dtype': dt,
+ 'order': 'row-major'
+ });
+
+ y = flatten( x );
+ expected = new Float64Array( [ 3.0 ] );
+
+ t.notEqual( y, x, 'returns expected value' );
+ t.notEqual( getData( y ), xbuf, 'returns expected value' );
+ t.strictEqual( isSameFloat64Array( getData( y ), expected ), true, 'returns expected value' );
+ t.deepEqual( getShape( y ), [], 'returns expected value' );
+ t.strictEqual( getDType( y ), dt, 'returns expected value' );
+ t.strictEqual( getOrder( y ), 'row-major', 'returns expected value' );
+
+ dt = 'float64';
+ x = scalar2ndarray( 3.0, {
+ 'dtype': dt,
+ 'order': 'column-major'
+ });
+
+ y = flatten( x );
+ expected = new Float64Array( [ 3.0 ] );
+
+ t.notEqual( y, x, 'returns expected value' );
+ t.notEqual( getData( y ), xbuf, 'returns expected value' );
+ t.strictEqual( isSameFloat64Array( getData( y ), expected ), true, 'returns expected value' );
+ t.deepEqual( getShape( y ), [], 'returns expected value' );
+ t.strictEqual( getDType( y ), dt, 'returns expected value' );
+ t.strictEqual( getOrder( y ), 'row-major', 'returns expected value' );
+
+ t.end();
+});
+
+tape( 'the function supports flattening a zero-dimensional input ndarray (order=same)', function test( t ) {
+ var expected;
+ var xbuf;
+ var dt;
+ var x;
+ var y;
+
+ dt = 'float64';
+ x = scalar2ndarray( 3.0, {
+ 'dtype': dt,
+ 'order': 'row-major'
+ });
+
+ y = flatten( x, {
+ 'order': 'same'
+ });
+ expected = new Float64Array( [ 3.0 ] );
+
+ t.notEqual( y, x, 'returns expected value' );
+ t.notEqual( getData( y ), xbuf, 'returns expected value' );
+ t.strictEqual( isSameFloat64Array( getData( y ), expected ), true, 'returns expected value' );
+ t.deepEqual( getShape( y ), [], 'returns expected value' );
+ t.strictEqual( getDType( y ), dt, 'returns expected value' );
+ t.strictEqual( getOrder( y ), 'row-major', 'returns expected value' );
+
+ dt = 'float64';
+ x = scalar2ndarray( 3.0, {
+ 'dtype': dt,
+ 'order': 'column-major'
+ });
+
+ y = flatten( x, {
+ 'order': 'same'
+ });
+ expected = new Float64Array( [ 3.0 ] );
+
+ t.notEqual( y, x, 'returns expected value' );
+ t.notEqual( getData( y ), xbuf, 'returns expected value' );
+ t.strictEqual( isSameFloat64Array( getData( y ), expected ), true, 'returns expected value' );
+ t.deepEqual( getShape( y ), [], 'returns expected value' );
+ t.strictEqual( getDType( y ), dt, 'returns expected value' );
+ t.strictEqual( getOrder( y ), 'column-major', 'returns expected value' );
+
+ t.end();
+});
+
+tape( 'the function supports flattening a zero-dimensional input ndarray (order=any)', function test( t ) {
+ var expected;
+ var xbuf;
+ var dt;
+ var x;
+ var y;
+
+ dt = 'float64';
+ x = scalar2ndarray( 3.0, {
+ 'dtype': dt,
+ 'order': 'row-major'
+ });
+
+ y = flatten( x, {
+ 'order': 'any'
+ });
+ expected = new Float64Array( [ 3.0 ] );
+
+ t.notEqual( y, x, 'returns expected value' );
+ t.notEqual( getData( y ), xbuf, 'returns expected value' );
+ t.strictEqual( isSameFloat64Array( getData( y ), expected ), true, 'returns expected value' );
+ t.deepEqual( getShape( y ), [], 'returns expected value' );
+ t.strictEqual( getDType( y ), dt, 'returns expected value' );
+ t.strictEqual( getOrder( y ), 'row-major', 'returns expected value' );
+
+ dt = 'float64';
+ x = scalar2ndarray( 3.0, {
+ 'dtype': dt,
+ 'order': 'column-major'
+ });
+
+ y = flatten( x, {
+ 'order': 'any'
+ });
+ expected = new Float64Array( [ 3.0 ] );
+
+ t.notEqual( y, x, 'returns expected value' );
+ t.notEqual( getData( y ), xbuf, 'returns expected value' );
+ t.strictEqual( isSameFloat64Array( getData( y ), expected ), true, 'returns expected value' );
+ t.deepEqual( getShape( y ), [], 'returns expected value' );
+ t.strictEqual( getDType( y ), dt, 'returns expected value' );
+ t.strictEqual( getOrder( y ), 'column-major', 'returns expected value' );
+
+ t.end();
+});
+
+tape( 'the function supports flattening a one-dimensional input ndarray', function test( t ) {
+ var expected;
+ var xbuf;
+ var ord;
+ var sh;
+ var st;
+ var dt;
+ var o;
+ var x;
+ var y;
+
+ dt = 'float64';
+ ord = 'row-major';
+ sh = [ 8 ];
+ st = shape2strides( sh, ord );
+ o = strides2offset( sh, st );
+
+ xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] );
+ x = new ndarray( dt, xbuf, sh, st, o, ord );
+
+ y = flatten( x );
+ expected = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] );
+
+ t.notEqual( y, x, 'returns expected value' );
+ t.notEqual( getData( y ), xbuf, 'returns expected value' );
+ t.strictEqual( isSameFloat64Array( getData( y ), expected ), true, 'returns expected value' );
+ t.deepEqual( getShape( y ), [ 8 ], 'returns expected value' );
+ t.strictEqual( getDType( y ), dt, 'returns expected value' );
+ t.strictEqual( getOrder( y ), 'row-major', 'returns expected value' );
+
+ dt = 'float64';
+ ord = 'column-major';
+ sh = [ 8 ];
+ st = shape2strides( sh, ord );
+ o = strides2offset( sh, st );
+
+ xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] );
+ x = new ndarray( dt, xbuf, sh, st, o, ord );
+
+ y = flatten( x );
+ expected = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] );
+
+ t.notEqual( y, x, 'returns expected value' );
+ t.notEqual( getData( y ), xbuf, 'returns expected value' );
+ t.strictEqual( isSameFloat64Array( getData( y ), expected ), true, 'returns expected value' );
+ t.deepEqual( getShape( y ), [ 8 ], 'returns expected value' );
+ t.strictEqual( getDType( y ), dt, 'returns expected value' );
+ t.strictEqual( getOrder( y ), 'row-major', 'returns expected value' );
+
+ t.end();
+});
+
+tape( 'the function supports flattening a one-dimensional input ndarray (order=same)', function test( t ) {
+ var expected;
+ var xbuf;
+ var ord;
+ var sh;
+ var st;
+ var dt;
+ var o;
+ var x;
+ var y;
+
+ dt = 'float64';
+ ord = 'row-major';
+ sh = [ 8 ];
+ st = shape2strides( sh, ord );
+ o = strides2offset( sh, st );
+
+ xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] );
+ x = new ndarray( dt, xbuf, sh, st, o, ord );
+
+ y = flatten( x, {
+ 'order': 'same'
+ });
+ expected = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] );
+
+ t.notEqual( y, x, 'returns expected value' );
+ t.notEqual( getData( y ), xbuf, 'returns expected value' );
+ t.strictEqual( isSameFloat64Array( getData( y ), expected ), true, 'returns expected value' );
+ t.deepEqual( getShape( y ), [ 8 ], 'returns expected value' );
+ t.strictEqual( getDType( y ), dt, 'returns expected value' );
+ t.strictEqual( getOrder( y ), 'row-major', 'returns expected value' );
+
+ dt = 'float64';
+ ord = 'column-major';
+ sh = [ 8 ];
+ st = shape2strides( sh, ord );
+ o = strides2offset( sh, st );
+
+ xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] );
+ x = new ndarray( dt, xbuf, sh, st, o, ord );
+
+ y = flatten( x, {
+ 'order': 'same'
+ });
+ expected = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] );
+
+ t.notEqual( y, x, 'returns expected value' );
+ t.notEqual( getData( y ), xbuf, 'returns expected value' );
+ t.strictEqual( isSameFloat64Array( getData( y ), expected ), true, 'returns expected value' );
+ t.deepEqual( getShape( y ), [ 8 ], 'returns expected value' );
+ t.strictEqual( getDType( y ), dt, 'returns expected value' );
+ t.strictEqual( getOrder( y ), 'column-major', 'returns expected value' );
+
+ t.end();
+});
+
+tape( 'the function supports flattening a one-dimensional input ndarray (order=any)', function test( t ) {
+ var expected;
+ var xbuf;
+ var ord;
+ var sh;
+ var st;
+ var dt;
+ var o;
+ var x;
+ var y;
+
+ dt = 'float64';
+ ord = 'row-major';
+ sh = [ 8 ];
+ st = shape2strides( sh, ord );
+ o = strides2offset( sh, st );
+
+ xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] );
+ x = new ndarray( dt, xbuf, sh, st, o, ord );
+
+ y = flatten( x, {
+ 'order': 'any'
+ });
+ expected = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] );
+
+ t.notEqual( y, x, 'returns expected value' );
+ t.notEqual( getData( y ), xbuf, 'returns expected value' );
+ t.strictEqual( isSameFloat64Array( getData( y ), expected ), true, 'returns expected value' );
+ t.deepEqual( getShape( y ), [ 8 ], 'returns expected value' );
+ t.strictEqual( getDType( y ), dt, 'returns expected value' );
+ t.strictEqual( getOrder( y ), 'row-major', 'returns expected value' );
+
+ dt = 'float64';
+ ord = 'column-major';
+ sh = [ 8 ];
+ st = shape2strides( sh, ord );
+ o = strides2offset( sh, st );
+
+ xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] );
+ x = new ndarray( dt, xbuf, sh, st, o, ord );
+
+ y = flatten( x, {
+ 'order': 'any'
+ });
+ expected = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] );
+
+ t.notEqual( y, x, 'returns expected value' );
+ t.notEqual( getData( y ), xbuf, 'returns expected value' );
+ t.strictEqual( isSameFloat64Array( getData( y ), expected ), true, 'returns expected value' );
+ t.deepEqual( getShape( y ), [ 8 ], 'returns expected value' );
+ t.strictEqual( getDType( y ), dt, 'returns expected value' );
+ t.strictEqual( getOrder( y ), 'column-major', 'returns expected value' );
+
+ t.end();
+});