From 5da54027ca853a5028af317b3a50fccbfa029e19 Mon Sep 17 00:00:00 2001
From: headlessNode <harriskhan047@outlook.com>
Date: Sun, 28 Sep 2025 19:43:00 +0500
Subject: [PATCH 1/4] feat: add ndarray/flatten-from

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---
 .../@stdlib/ndarray/flatten-from/README.md    |  203 +++
 .../flatten-from/benchmark/benchmark.js       |  302 ++++
 .../ndarray/flatten-from/docs/repl.txt        |   51 +
 .../flatten-from/docs/types/index.d.ts        |  132 ++
 .../ndarray/flatten-from/docs/types/test.ts   |  187 ++
 .../ndarray/flatten-from/examples/index.js    |   37 +
 .../@stdlib/ndarray/flatten-from/lib/index.js |   57 +
 .../@stdlib/ndarray/flatten-from/lib/main.js  |  362 ++++
 .../@stdlib/ndarray/flatten-from/package.json |   66 +
 .../@stdlib/ndarray/flatten-from/test/test.js | 1518 +++++++++++++++++
 10 files changed, 2915 insertions(+)
 create mode 100644 lib/node_modules/@stdlib/ndarray/flatten-from/README.md
 create mode 100644 lib/node_modules/@stdlib/ndarray/flatten-from/benchmark/benchmark.js
 create mode 100644 lib/node_modules/@stdlib/ndarray/flatten-from/docs/repl.txt
 create mode 100644 lib/node_modules/@stdlib/ndarray/flatten-from/docs/types/index.d.ts
 create mode 100644 lib/node_modules/@stdlib/ndarray/flatten-from/docs/types/test.ts
 create mode 100644 lib/node_modules/@stdlib/ndarray/flatten-from/examples/index.js
 create mode 100644 lib/node_modules/@stdlib/ndarray/flatten-from/lib/index.js
 create mode 100644 lib/node_modules/@stdlib/ndarray/flatten-from/lib/main.js
 create mode 100644 lib/node_modules/@stdlib/ndarray/flatten-from/package.json
 create mode 100644 lib/node_modules/@stdlib/ndarray/flatten-from/test/test.js

diff --git a/lib/node_modules/@stdlib/ndarray/flatten-from/README.md b/lib/node_modules/@stdlib/ndarray/flatten-from/README.md
new file mode 100644
index 000000000000..1f80b6360406
--- /dev/null
+++ b/lib/node_modules/@stdlib/ndarray/flatten-from/README.md
@@ -0,0 +1,203 @@
+<!--
+
+@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.
+
+-->
+
+# flattenFrom
+
+> Return a copy of an input [ndarray][@stdlib/ndarray/ctor], where all dimensions of the input [ndarray][@stdlib/ndarray/ctor] are flattened starting from a specific dimension.
+
+<section class="intro">
+
+</section>
+
+<!-- /.intro -->
+
+<section class="usage">
+
+## Usage
+
+```javascript
+var flattenFrom = require( '@stdlib/ndarray/flatten-from' );
+```
+
+#### flattenFrom( x, dim\[, options] )
+
+Returns a copy of an input [ndarray][@stdlib/ndarray/ctor], where all dimensions of the input [ndarray][@stdlib/ndarray/ctor] are flattened starting from a specific dimension.
+
+```javascript
+var array = require( '@stdlib/ndarray/array' );
+var shape = require( '@stdlib/ndarray/shape' );
+var ndarray2array = require( '@stdlib/ndarray/to-array' );
+
+var x = array( [ [ [ 1.0, 2.0 ] ], [ [ 3.0, 4.0 ] ], [ [ 5.0, 6.0 ] ] ] );
+// returns <ndarray>
+
+var shx = shape( x );
+// returns [ 3, 1, 2 ]
+
+var y = flattenFrom( x, 1 );
+// returns <ndarray>
+
+var shy = shape( y );
+// returns [ 3, 2 ]
+
+var arr = ndarray2array( y );
+// returns [ [ 1, 2 ], [ 3, 4 ], [ 5, 6 ] ]
+```
+
+The function accepts the following arguments:
+
+-   **x**: input [ndarray][@stdlib/ndarray/ctor].
+-   **dim**: dimension to start flattening from. If provided an integer less than zero, the dimension index is resolved relative to the last dimension, with the last dimension corresponding to the value `-1`.
+-   **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'`.
+
+-   **dtype**: output ndarray [data type][@stdlib/ndarray/dtypes]. By default, the function returns an [ndarray][@stdlib/ndarray/ctor] having the same [data type][@stdlib/ndarray/dtypes] as a provided input [ndarray][@stdlib/ndarray/ctor].
+
+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 shape = require( '@stdlib/ndarray/shape' );
+var ndarray2array = require( '@stdlib/ndarray/to-array' );
+
+var x = array( [ [ [ 1.0, 2.0 ] ], [ [ 3.0, 4.0 ] ], [ [ 5.0, 6.0 ] ] ] );
+// returns <ndarray>
+
+var shx = shape( x );
+// returns [ 3, 1, 2 ]
+
+var y = flattenFrom( x, 0, {
+    'order': 'column-major'
+});
+// returns <ndarray>
+
+var shy = shape( y );
+// returns [ 6 ]
+
+var arr = ndarray2array( y );
+// returns [ 1.0, 3.0, 5.0, 2.0, 4.0, 6.0 ]
+```
+
+By default, the output ndarray [data type][@stdlib/ndarray/dtypes] is inferred from the input [ndarray][@stdlib/ndarray/ctor]. To return an ndarray with a different [data type][@stdlib/ndarray/dtypes], specify the `dtype` option.
+
+```javascript
+var array = require( '@stdlib/ndarray/array' );
+var dtype = require( '@stdlib/ndarray/dtype' );
+var shape = require( '@stdlib/ndarray/shape' );
+var ndarray2array = require( '@stdlib/ndarray/to-array' );
+
+var x = array( [ [ [ 1.0, 2.0 ] ], [ [ 3.0, 4.0 ] ], [ [ 5.0, 6.0 ] ] ] );
+// returns <ndarray>
+
+var shx = shape( x );
+// returns [ 3, 1, 2 ]
+
+var y = flattenFrom( x, 0, {
+    'dtype': 'float32'
+});
+// returns <ndarray>
+
+var shy = shape( y );
+// returns [ 6 ]
+
+var dt = dtype( y );
+// returns 'float32'
+
+var arr = ndarray2array( y );
+// returns [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ]
+```
+
+</section>
+
+<!-- /.usage -->
+
+<section class="notes">
+
+## 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.
+
+</section>
+
+<!-- /.notes -->
+
+<section class="examples">
+
+## Examples
+
+<!-- eslint no-undef: "error" -->
+
+```javascript
+var discreteUniform = require( '@stdlib/random/array/discrete-uniform' );
+var array = require( '@stdlib/ndarray/array' );
+var ndarray2array = require( '@stdlib/ndarray/to-array' );
+var flattenFrom = require( '@stdlib/ndarray/flatten-from' );
+
+var xbuf = discreteUniform( 12, -100, 100, {
+    'dtype': 'generic'
+});
+
+var x = array( xbuf, {
+    'shape': [ 2, 2, 3 ],
+    'dtype': 'generic'
+});
+console.log( ndarray2array( x ) );
+
+var y = flattenFrom( x, 1 );
+console.log( ndarray2array( y ) );
+```
+
+</section>
+
+<!-- /.examples -->
+
+<!-- Section for related `stdlib` packages. Do not manually edit this section, as it is automatically populated. -->
+
+<section class="related">
+
+</section>
+
+<!-- /.related -->
+
+<section class="links">
+
+[@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/orders]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/ndarray/orders
+
+<!-- <related-links> -->
+
+<!-- </related-links> -->
+
+</section>
+
+<!-- /.links -->
diff --git a/lib/node_modules/@stdlib/ndarray/flatten-from/benchmark/benchmark.js b/lib/node_modules/@stdlib/ndarray/flatten-from/benchmark/benchmark.js
new file mode 100644
index 000000000000..b86770566ddc
--- /dev/null
+++ b/lib/node_modules/@stdlib/ndarray/flatten-from/benchmark/benchmark.js
@@ -0,0 +1,302 @@
+/**
+* @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 flattenFrom = 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 = {
+		'order': 'row-major'
+	};
+
+	b.tic();
+	for ( i = 0; i < b.iterations; i++ ) {
+		j = i % values.length;
+		y = flattenFrom( values[ j ], 0, 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 = {
+		'order': 'column-major'
+	};
+
+	b.tic();
+	for ( i = 0; i < b.iterations; i++ ) {
+		j = i % values.length;
+		y = flattenFrom( values[ j ], 0, 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 = {
+		'order': 'row-major'
+	};
+
+	b.tic();
+	for ( i = 0; i < b.iterations; i++ ) {
+		j = i % values.length;
+		y = flattenFrom( values[ j ], 0, 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 = {
+		'order': 'column-major'
+	};
+
+	b.tic();
+	for ( i = 0; i < b.iterations; i++ ) {
+		j = i % values.length;
+		y = flattenFrom( values[ j ], 0, 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 = {
+		'order': 'row-major'
+	};
+
+	b.tic();
+	for ( i = 0; i < b.iterations; i++ ) {
+		j = i % values.length;
+		y = flattenFrom( values[ j ], 0, 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 = {
+		'order': 'column-major'
+	};
+
+	b.tic();
+	for ( i = 0; i < b.iterations; i++ ) {
+		j = i % values.length;
+		y = flattenFrom( values[ j ], 0, 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 = {
+		'order': 'row-major'
+	};
+
+	b.tic();
+	for ( i = 0; i < b.iterations; i++ ) {
+		j = i % values.length;
+		y = flattenFrom( values[ j ], 0, 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 = {
+		'order': 'column-major'
+	};
+
+	b.tic();
+	for ( i = 0; i < b.iterations; i++ ) {
+		j = i % values.length;
+		y = flattenFrom( values[ j ], 0, 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-from/docs/repl.txt b/lib/node_modules/@stdlib/ndarray/flatten-from/docs/repl.txt
new file mode 100644
index 000000000000..fd55a15c6063
--- /dev/null
+++ b/lib/node_modules/@stdlib/ndarray/flatten-from/docs/repl.txt
@@ -0,0 +1,51 @@
+
+{{alias}}( x, dim[, options] )
+    Returns a copy of an input ndarray, where all dimensions of the input
+    ndarray are flattened starting from a specific dimension.
+
+    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.
+
+    dim: integer
+        Dimension to start flattening from. If provided an integer less than
+        zero, the dimension index is resolved relative to the last dimension,
+        with the last dimension corresponding to the value `-1`.
+
+    options: Object (optional)
+        Function options.
+
+    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'.
+
+    options.dtype: string (optional)
+        Output ndarray data type. By default, the function returns an ndarray
+        having the same data type as the provided input ndarray.
+
+    Returns
+    -------
+    out: ndarray
+        Output ndarray.
+
+    Examples
+    --------
+    > var x = {{alias:@stdlib/ndarray/array}}( [ [ 1.0, 2.0 ], [ 3.0, 4.0 ] ] );
+    > var y = {{alias}}( x, 0 );
+    > 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-from/docs/types/index.d.ts b/lib/node_modules/@stdlib/ndarray/flatten-from/docs/types/index.d.ts
new file mode 100644
index 000000000000..ac7b5e99fb09
--- /dev/null
+++ b/lib/node_modules/@stdlib/ndarray/flatten-from/docs/types/index.d.ts
@@ -0,0 +1,132 @@
+/*
+* @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
+
+/// <reference types="@stdlib/types"/>
+
+import { ndarray, typedndarray, Order, DataTypeMap } from '@stdlib/types/ndarray';
+
+/**
+* Interface defining "base" function options.
+*/
+interface BaseOptions {
+	/**
+	* 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';
+}
+
+/**
+* Function options.
+*/
+type Options<U> = BaseOptions & {
+	/**
+	* Output ndarray data type.
+	*/
+	dtype: U;
+};
+
+/**
+* Returns a copy of an input ndarray, where all dimensions of the input ndarray are flattened starting from a specific dimension.
+*
+* ## Notes
+*
+* -   The function **always** returns a copy of input ndarray data, even when an input ndarray already has the desired number of dimensions.
+* -   By default, the function returns an ndarray having the same data type as a provided input ndarray.
+*
+* @param x - input ndarray
+* @param dim - dimension to start flattening from
+* @param options - function options
+* @param options.order - order in which input ndarray elements should be flattened
+* @param options.dtype - output ndarray data type
+* @returns output ndarray
+*
+* @example
+* var array = require( '@stdlib/ndarray/array' );
+* var shape = require( '@stdlib/ndarray/shape' );
+* var ndarray2array = require( '@stdlib/ndarray/to-array' );
+*
+* var x = array( [ [ [ 1.0, 2.0 ] ], [ [ 3.0, 4.0 ] ], [ [ 5.0, 6.0 ] ] ] );
+* // returns <ndarray>
+*
+* var shx = shape( x );
+* // returns [ 3, 1, 2 ]
+*
+* var y = flattenFrom( x, 1 );
+* // returns <ndarray>
+*
+* var shy = shape( y );
+* // returns [ 3, 2 ]
+*
+* var arr = ndarray2array( y );
+* // returns [ [ 1, 2 ], [ 3, 4 ], [ 5, 6 ] ]
+*/
+declare function flattenFrom<T extends ndarray>( x: T, dim: number, options?: BaseOptions ): T;
+
+/**
+* Returns a copy of an input ndarray, where all dimensions of the input ndarray are flattened starting from a specific dimension.
+*
+* ## 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 dim - dimension to start flattening from
+* @param options - function options
+* @param options.order - order in which input ndarray elements should be flattened
+* @param options.dtype - output ndarray data type
+* @returns output ndarray
+*
+* @example
+* var array = require( '@stdlib/ndarray/array' );
+* var shape = require( '@stdlib/ndarray/shape' );
+* var ndarray2array = require( '@stdlib/ndarray/to-array' );
+*
+* var x = array( [ [ [ 1.0, 2.0 ] ], [ [ 3.0, 4.0 ] ], [ [ 5.0, 6.0 ] ] ] );
+* // returns <ndarray>
+*
+* var shx = shape( x );
+* // returns [ 3, 1, 2 ]
+*
+* var y = flattenFrom( x, 1 );
+* // returns <ndarray>
+*
+* var shy = shape( y );
+* // returns [ 3, 2 ]
+*
+* var arr = ndarray2array( y );
+* // returns [ [ 1, 2 ], [ 3, 4 ], [ 5, 6 ] ]
+*/
+declare function flattenFrom<T = unknown, U extends keyof DataTypeMap<T> = 'generic'>( x: typedndarray<T>, dim: number, options: Options<U> ): DataTypeMap<T>[U];
+
+
+// EXPORTS //
+
+export = flattenFrom;
diff --git a/lib/node_modules/@stdlib/ndarray/flatten-from/docs/types/test.ts b/lib/node_modules/@stdlib/ndarray/flatten-from/docs/types/test.ts
new file mode 100644
index 000000000000..8e95897392de
--- /dev/null
+++ b/lib/node_modules/@stdlib/ndarray/flatten-from/docs/types/test.ts
@@ -0,0 +1,187 @@
+/*
+* @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 flattenFrom = require( './index' );
+
+
+// TESTS //
+
+// The function returns an ndarray...
+{
+	flattenFrom( zeros( 'float64', [ 2, 2, 2 ], 'row-major' ), 0 ); // $ExpectType float64ndarray
+	flattenFrom( zeros( 'complex128', [ 2, 2, 2 ], 'row-major' ), 0 ); // $ExpectType complex128ndarray
+	flattenFrom( zeros( 'generic', [ 2, 2, 2 ], 'row-major' ), 0 ); // $ExpectType genericndarray<number>
+
+	flattenFrom( zeros( 'float64', [ 2, 2, 2 ], 'row-major' ), 0, {} ); // $ExpectType float64ndarray
+	flattenFrom( zeros( 'complex128', [ 2, 2, 2 ], 'row-major' ), 0, {} ); // $ExpectType complex128ndarray
+	flattenFrom( zeros( 'generic', [ 2, 2, 2 ], 'row-major' ), 0, {} ); // $ExpectType genericndarray<number>
+
+	flattenFrom( zeros( 'float64', [ 2, 2, 2 ], 'row-major' ), 0, { 'dtype': 'float32' } ); // $ExpectType float32ndarray
+	flattenFrom( zeros( 'int32', [ 2, 2, 2 ], 'row-major' ), 0, { 'dtype': 'float64' } ); // $ExpectType float64ndarray
+	flattenFrom( zeros( 'int32', [ 2, 2, 2 ], 'row-major' ), 0, { 'dtype': 'generic' } ); // $ExpectType genericndarray<number>
+}
+
+// The compiler throws an error if the function is provided a first argument which is not an ndarray-like object...
+{
+	flattenFrom( '5', 0 ); // $ExpectError
+	flattenFrom( 5, 0 ); // $ExpectError
+	flattenFrom( true, 0 ); // $ExpectError
+	flattenFrom( false, 0 ); // $ExpectError
+	flattenFrom( null, 0 ); // $ExpectError
+	flattenFrom( undefined, 0 ); // $ExpectError
+	flattenFrom( {}, 0 ); // $ExpectError
+	flattenFrom( [ 1 ], 0 ); // $ExpectError
+	flattenFrom( ( x: number ): number => x, 0 ); // $ExpectError
+
+	flattenFrom( '5', 0, {} ); // $ExpectError
+	flattenFrom( 5, 0, {} ); // $ExpectError
+	flattenFrom( true, 0, {} ); // $ExpectError
+	flattenFrom( false, 0, {} ); // $ExpectError
+	flattenFrom( null, 0, {} ); // $ExpectError
+	flattenFrom( undefined, 0, {} ); // $ExpectError
+	flattenFrom( {}, 0, {} ); // $ExpectError
+	flattenFrom( [ 1 ], 0, {} ); // $ExpectError
+	flattenFrom( ( x: number ): number => x, 0, {} ); // $ExpectError
+}
+
+// The compiler throws an error if the function is provided a second argument which is not an integer...
+{
+	flattenFrom( zeros( 'float64', [ 2, 2, 2 ], 'row-major' ), '5' ); // $ExpectError
+	flattenFrom( zeros( 'float64', [ 2, 2, 2 ], 'row-major' ), true ); // $ExpectError
+	flattenFrom( zeros( 'float64', [ 2, 2, 2 ], 'row-major' ), false ); // $ExpectError
+	flattenFrom( zeros( 'float64', [ 2, 2, 2 ], 'row-major' ), null ); // $ExpectError
+	flattenFrom( zeros( 'float64', [ 2, 2, 2 ], 'row-major' ), [ 1 ] ); // $ExpectError
+	flattenFrom( zeros( 'float64', [ 2, 2, 2 ], 'row-major' ), ( x: number ): number => x ); // $ExpectError
+
+	flattenFrom( zeros( 'complex128', [ 2, 2, 2 ], 'row-major' ), '5' ); // $ExpectError
+	flattenFrom( zeros( 'complex128', [ 2, 2, 2 ], 'row-major' ), true ); // $ExpectError
+	flattenFrom( zeros( 'complex128', [ 2, 2, 2 ], 'row-major' ), false ); // $ExpectError
+	flattenFrom( zeros( 'complex128', [ 2, 2, 2 ], 'row-major' ), null ); // $ExpectError
+	flattenFrom( zeros( 'complex128', [ 2, 2, 2 ], 'row-major' ), [ 1 ] ); // $ExpectError
+	flattenFrom( zeros( 'complex128', [ 2, 2, 2 ], 'row-major' ), ( x: number ): number => x ); // $ExpectError
+
+	flattenFrom( zeros( 'generic', [ 2, 2, 2 ], 'row-major' ), '5' ); // $ExpectError
+	flattenFrom( zeros( 'generic', [ 2, 2, 2 ], 'row-major' ), true ); // $ExpectError
+	flattenFrom( zeros( 'generic', [ 2, 2, 2 ], 'row-major' ), false ); // $ExpectError
+	flattenFrom( zeros( 'generic', [ 2, 2, 2 ], 'row-major' ), null ); // $ExpectError
+	flattenFrom( zeros( 'generic', [ 2, 2, 2 ], 'row-major' ), [ 1 ] ); // $ExpectError
+	flattenFrom( zeros( 'generic', [ 2, 2, 2 ], 'row-major' ), ( x: number ): number => x ); // $ExpectError
+
+	flattenFrom( zeros( 'float64', [ 2, 2, 2 ], 'row-major' ), '5', {} ); // $ExpectError
+	flattenFrom( zeros( 'float64', [ 2, 2, 2 ], 'row-major' ), true, {} ); // $ExpectError
+	flattenFrom( zeros( 'float64', [ 2, 2, 2 ], 'row-major' ), false, {} ); // $ExpectError
+	flattenFrom( zeros( 'float64', [ 2, 2, 2 ], 'row-major' ), null, {} ); // $ExpectError
+	flattenFrom( zeros( 'float64', [ 2, 2, 2 ], 'row-major' ), [ 1 ], {} ); // $ExpectError
+	flattenFrom( zeros( 'float64', [ 2, 2, 2 ], 'row-major' ), ( x: number ): number => x, {} ); // $ExpectError
+
+	flattenFrom( zeros( 'complex128', [ 2, 2, 2 ], 'row-major' ), '5', {} ); // $ExpectError
+	flattenFrom( zeros( 'complex128', [ 2, 2, 2 ], 'row-major' ), true, {} ); // $ExpectError
+	flattenFrom( zeros( 'complex128', [ 2, 2, 2 ], 'row-major' ), false, {} ); // $ExpectError
+	flattenFrom( zeros( 'complex128', [ 2, 2, 2 ], 'row-major' ), null, {} ); // $ExpectError
+	flattenFrom( zeros( 'complex128', [ 2, 2, 2 ], 'row-major' ), [ 1 ], {} ); // $ExpectError
+	flattenFrom( zeros( 'complex128', [ 2, 2, 2 ], 'row-major' ), ( x: number ): number => x, {} ); // $ExpectError
+
+	flattenFrom( zeros( 'generic', [ 2, 2, 2 ], 'row-major' ), '5', {} ); // $ExpectError
+	flattenFrom( zeros( 'generic', [ 2, 2, 2 ], 'row-major' ), true, {} ); // $ExpectError
+	flattenFrom( zeros( 'generic', [ 2, 2, 2 ], 'row-major' ), false, {} ); // $ExpectError
+	flattenFrom( zeros( 'generic', [ 2, 2, 2 ], 'row-major' ), null, {} ); // $ExpectError
+	flattenFrom( zeros( 'generic', [ 2, 2, 2 ], 'row-major' ), [ 1 ], {} ); // $ExpectError
+	flattenFrom( zeros( 'generic', [ 2, 2, 2 ], 'row-major' ), ( x: number ): number => x, {} ); // $ExpectError
+}
+
+
+// The compiler throws an error if the function is provided an options argument which is not an object...
+{
+	flattenFrom( zeros( 'float64', [ 2, 2, 2 ], 'row-major' ), 0, '5' ); // $ExpectError
+	flattenFrom( zeros( 'float64', [ 2, 2, 2 ], 'row-major' ), 0, true ); // $ExpectError
+	flattenFrom( zeros( 'float64', [ 2, 2, 2 ], 'row-major' ), 0, false ); // $ExpectError
+	flattenFrom( zeros( 'float64', [ 2, 2, 2 ], 'row-major' ), 0, null ); // $ExpectError
+	flattenFrom( zeros( 'float64', [ 2, 2, 2 ], 'row-major' ), 0, [ 1 ] ); // $ExpectError
+	flattenFrom( zeros( 'float64', [ 2, 2, 2 ], 'row-major' ), 0, ( x: number ): number => x ); // $ExpectError
+
+	flattenFrom( zeros( 'complex128', [ 2, 2, 2 ], 'row-major' ), 0, '5' ); // $ExpectError
+	flattenFrom( zeros( 'complex128', [ 2, 2, 2 ], 'row-major' ), 0, true ); // $ExpectError
+	flattenFrom( zeros( 'complex128', [ 2, 2, 2 ], 'row-major' ), 0, false ); // $ExpectError
+	flattenFrom( zeros( 'complex128', [ 2, 2, 2 ], 'row-major' ), 0, null ); // $ExpectError
+	flattenFrom( zeros( 'complex128', [ 2, 2, 2 ], 'row-major' ), 0, [ 1 ] ); // $ExpectError
+	flattenFrom( zeros( 'complex128', [ 2, 2, 2 ], 'row-major' ), 0, ( x: number ): number => x ); // $ExpectError
+
+	flattenFrom( zeros( 'generic', [ 2, 2, 2 ], 'row-major' ), 0, '5' ); // $ExpectError
+	flattenFrom( zeros( 'generic', [ 2, 2, 2 ], 'row-major' ), 0, true ); // $ExpectError
+	flattenFrom( zeros( 'generic', [ 2, 2, 2 ], 'row-major' ), 0, false ); // $ExpectError
+	flattenFrom( zeros( 'generic', [ 2, 2, 2 ], 'row-major' ), 0, null ); // $ExpectError
+	flattenFrom( zeros( 'generic', [ 2, 2, 2 ], 'row-major' ), 0, [ 1 ] ); // $ExpectError
+	flattenFrom( zeros( 'generic', [ 2, 2, 2 ], 'row-major' ), 0, ( x: number ): number => x ); // $ExpectError
+}
+
+// The compiler throws an error if the function is provided a second argument with invalid `order` option...
+{
+	flattenFrom( zeros( 'float64', [ 2, 2, 2 ], 'row-major' ), 0, { 'order': '5' } ); // $ExpectError
+	flattenFrom( zeros( 'float64', [ 2, 2, 2 ], 'row-major' ), 0, { 'order': true } ); // $ExpectError
+	flattenFrom( zeros( 'float64', [ 2, 2, 2 ], 'row-major' ), 0, { 'order': false } ); // $ExpectError
+	flattenFrom( zeros( 'float64', [ 2, 2, 2 ], 'row-major' ), 0, { 'order': null } ); // $ExpectError
+	flattenFrom( zeros( 'float64', [ 2, 2, 2 ], 'row-major' ), 0, { 'order': [ 1 ] } ); // $ExpectError
+	flattenFrom( zeros( 'float64', [ 2, 2, 2 ], 'row-major' ), 0, { 'order': ( x: number ): number => x } ); // $ExpectError
+
+	flattenFrom( zeros( 'complex128', [ 2, 2, 2 ], 'row-major' ), 0, { 'order': '5' } ); // $ExpectError
+	flattenFrom( zeros( 'complex128', [ 2, 2, 2 ], 'row-major' ), 0, { 'order': true } ); // $ExpectError
+	flattenFrom( zeros( 'complex128', [ 2, 2, 2 ], 'row-major' ), 0, { 'order': false } ); // $ExpectError
+	flattenFrom( zeros( 'complex128', [ 2, 2, 2 ], 'row-major' ), 0, { 'order': null } ); // $ExpectError
+	flattenFrom( zeros( 'complex128', [ 2, 2, 2 ], 'row-major' ), 0, { 'order': [ 1 ] } ); // $ExpectError
+	flattenFrom( zeros( 'complex128', [ 2, 2, 2 ], 'row-major' ), 0, { 'order': ( x: number ): number => x } ); // $ExpectError
+
+	flattenFrom( zeros( 'generic', [ 2, 2, 2 ], 'row-major' ), 0, { 'order': '5' } ); // $ExpectError
+	flattenFrom( zeros( 'generic', [ 2, 2, 2 ], 'row-major' ), 0, { 'order': true } ); // $ExpectError
+	flattenFrom( zeros( 'generic', [ 2, 2, 2 ], 'row-major' ), 0, { 'order': false } ); // $ExpectError
+	flattenFrom( zeros( 'generic', [ 2, 2, 2 ], 'row-major' ), 0, { 'order': null } ); // $ExpectError
+	flattenFrom( zeros( 'generic', [ 2, 2, 2 ], 'row-major' ), 0, { 'order': [ 1 ] } ); // $ExpectError
+	flattenFrom( zeros( 'generic', [ 2, 2, 2 ], 'row-major' ), 0, { 'order': ( x: number ): number => x } ); // $ExpectError
+}
+
+// The compiler throws an error if the function is provided a second argument with invalid `dtype` option...
+{
+	flattenFrom( zeros( 'float64', [ 2, 2, 2 ], 'row-major' ), 0, { 'dtype': '5' } ); // $ExpectError
+	flattenFrom( zeros( 'float64', [ 2, 2, 2 ], 'row-major' ), 0, { 'dtype': true } ); // $ExpectError
+	flattenFrom( zeros( 'float64', [ 2, 2, 2 ], 'row-major' ), 0, { 'dtype': false } ); // $ExpectError
+	flattenFrom( zeros( 'float64', [ 2, 2, 2 ], 'row-major' ), 0, { 'dtype': null } ); // $ExpectError
+	flattenFrom( zeros( 'float64', [ 2, 2, 2 ], 'row-major' ), 0, { 'dtype': [ 1 ] } ); // $ExpectError
+	flattenFrom( zeros( 'float64', [ 2, 2, 2 ], 'row-major' ), 0, { 'dtype': ( x: number ): number => x } ); // $ExpectError
+
+	flattenFrom( zeros( 'complex128', [ 2, 2, 2 ], 'row-major' ), 0, { 'dtype': '5' } ); // $ExpectError
+	flattenFrom( zeros( 'complex128', [ 2, 2, 2 ], 'row-major' ), 0, { 'dtype': true } ); // $ExpectError
+	flattenFrom( zeros( 'complex128', [ 2, 2, 2 ], 'row-major' ), 0, { 'dtype': false } ); // $ExpectError
+	flattenFrom( zeros( 'complex128', [ 2, 2, 2 ], 'row-major' ), 0, { 'dtype': null } ); // $ExpectError
+	flattenFrom( zeros( 'complex128', [ 2, 2, 2 ], 'row-major' ), 0, { 'dtype': [ 1 ] } ); // $ExpectError
+	flattenFrom( zeros( 'complex128', [ 2, 2, 2 ], 'row-major' ), 0, { 'dtype': ( x: number ): number => x } ); // $ExpectError
+
+	flattenFrom( zeros( 'generic', [ 2, 2, 2 ], 'row-major' ), 0, { 'dtype': '5' } ); // $ExpectError
+	flattenFrom( zeros( 'generic', [ 2, 2, 2 ], 'row-major' ), 0, { 'dtype': true } ); // $ExpectError
+	flattenFrom( zeros( 'generic', [ 2, 2, 2 ], 'row-major' ), 0, { 'dtype': false } ); // $ExpectError
+	flattenFrom( zeros( 'generic', [ 2, 2, 2 ], 'row-major' ), 0, { 'dtype': null } ); // $ExpectError
+	flattenFrom( zeros( 'generic', [ 2, 2, 2 ], 'row-major' ), 0, { 'dtype': [ 1 ] } ); // $ExpectError
+	flattenFrom( zeros( 'generic', [ 2, 2, 2 ], 'row-major' ), 0, { 'dtype': ( 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' );
+
+	flattenFrom( x ); // $ExpectError
+	flattenFrom( x, 0, {}, {} ); // $ExpectError
+}
diff --git a/lib/node_modules/@stdlib/ndarray/flatten-from/examples/index.js b/lib/node_modules/@stdlib/ndarray/flatten-from/examples/index.js
new file mode 100644
index 000000000000..5bec663f17fe
--- /dev/null
+++ b/lib/node_modules/@stdlib/ndarray/flatten-from/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 flattenFrom = 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 = flattenFrom( x, 1 );
+console.log( ndarray2array( y ) );
diff --git a/lib/node_modules/@stdlib/ndarray/flatten-from/lib/index.js b/lib/node_modules/@stdlib/ndarray/flatten-from/lib/index.js
new file mode 100644
index 000000000000..674954209bbe
--- /dev/null
+++ b/lib/node_modules/@stdlib/ndarray/flatten-from/lib/index.js
@@ -0,0 +1,57 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*    http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+'use strict';
+
+/**
+* Return a copy of an input ndarray, where all dimensions of the input ndarray are flattened starting from a specific dimension.
+*
+* @module @stdlib/ndarray/flatten-from
+*
+* @example
+* var array = require( '@stdlib/ndarray/array' );
+* var shape = require( '@stdlib/ndarray/shape' );
+* var ndarray2array = require( '@stdlib/ndarray/to-array' );
+* var flattenFrom = require( '@stdlib/ndarray/flatten-from' );
+*
+* // Create an input ndarray:
+* var x = array( [ [ [ 1.0, 2.0 ] ], [ [ 3.0, 4.0 ] ], [ [ 5.0, 6.0 ] ] ] );
+* // returns <ndarray>
+*
+* var shx = shape( x );
+* // returns [ 3, 1, 2 ]
+*
+* // Flatten the input ndarray:
+* var y = flattenFrom( x, 1 );
+* // returns <ndarray>
+*
+* var shy = shape( y );
+* // returns [ 3, 2 ]
+*
+* var arr = ndarray2array( y );
+* // returns [ [ 1, 2 ], [ 3, 4 ], [ 5, 6 ] ]
+*/
+
+// MODULES //
+
+var main = require( './main.js' );
+
+
+// EXPORTS //
+
+module.exports = main;
diff --git a/lib/node_modules/@stdlib/ndarray/flatten-from/lib/main.js b/lib/node_modules/@stdlib/ndarray/flatten-from/lib/main.js
new file mode 100644
index 000000000000..19415b3b4fff
--- /dev/null
+++ b/lib/node_modules/@stdlib/ndarray/flatten-from/lib/main.js
@@ -0,0 +1,362 @@
+/**
+* @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 isInteger = require( '@stdlib/assert/is-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 flattenShapeFrom = require( '@stdlib/ndarray/base/flatten-shape-from' );
+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 copy of an input ndarray, where all dimensions of the input ndarray are flattened starting from a specific dimension.
+*
+* @param {ndarray} x - input ndarray
+* @param {integer} dim - dimension to start flattening from.
+* @param {Options} [options] - function options
+* @param {string} [options.order='row-major'] - order in which input ndarray elements should be flattened
+* @param {*} [options.dtype] - output ndarray data type
+* @throws {TypeError} first argument must be an ndarray-like object
+* @throws {TypeError} second argument must be an integer
+* @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 ] ] ] );
+* // returns <ndarray>
+*
+* var y = flattenFrom( x, 1 );
+* // returns <ndarray>
+*
+* var arr = ndarray2array( y );
+* // returns [ [ 1, 2 ], [ 3, 4 ], [ 5, 6 ] ]
+*
+* @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'
+* });
+* // returns <ndarray>
+*
+* var y = flattenFrom( x, 0 );
+* // returns <ndarray>
+*
+* 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'
+* });
+* // returns <ndarray>
+*
+* var y = flattenFrom( x, 0, {
+*     'order': 'column-major'
+* });
+* // returns <ndarray>
+*
+* 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'
+* });
+* // returns <ndarray>
+*
+* var y = flattenFrom( x, 0, {
+*     'order': 'row-major'
+* });
+* // returns <ndarray>
+*
+* 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'
+* });
+* // returns <ndarray>
+*
+* var y = flattenFrom( x, 0, {
+*     'order': 'same'
+* });
+* // returns <ndarray>
+*
+* 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'
+* });
+* // returns <ndarray>
+*
+* var y = flattenFrom( x, 0, {
+*     'order': 'same'
+* });
+* // returns <ndarray>
+*
+* 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' );
+* // returns <ndarray>
+*
+* var y = flattenFrom( x, 0 );
+* // returns <ndarray>
+*
+* 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' );
+* // returns <ndarray>
+*
+* var y = flattenFrom( x, 0 );
+* // returns <ndarray>
+*
+* 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' );
+* // returns <ndarray>
+*
+* var y = flattenFrom( x, 0, {
+*     'order': 'same'
+* });
+* // returns <ndarray>
+*
+* 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' );
+* // returns <ndarray>
+*
+* var y = flattenFrom( x, 0, {
+*     'order': 'any'
+* });
+* // returns <ndarray>
+*
+* 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' );
+* // returns <ndarray>
+*
+* var y = flattenFrom( x, 0 );
+* // returns <ndarray>
+*
+* 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' );
+* // returns <ndarray>
+*
+* var y = flattenFrom( x, 0, {
+*     'order': 'same'
+* });
+* // returns <ndarray>
+*
+* 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' );
+* // returns <ndarray>
+*
+* var y = flattenFrom( x, 0, {
+*     'order': 'any'
+* });
+* // returns <ndarray>
+*
+* var arr = ndarray2array( y );
+* // returns [ 6.0, 5.0, 4.0, 3.0, 2.0, 1.0 ]
+*/
+function flattenFrom( x, dim, 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 ) );
+	}
+	if ( !isInteger( dim ) ) {
+		throw new TypeError( format( 'invalid argument. Second argument must be an integer. Value: `%s`.', dim ) );
+	}
+	nargs = arguments.length;
+	xsh = getShape( x );
+
+	// Define default options:
+	opts = {
+		'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)
+		'dtype': getDType( x )
+	};
+
+	// 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, '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 ) );
+			}
+		}
+		if ( hasOwnProp( options, 'dtype' ) ) {
+			// Delegate `dtype` validation to `emptyLike` during output array creation:
+			opts.dtype = options.dtype;
+		}
+	}
+	// Create an output ndarray having contiguous memory:
+	y = emptyLike( x, {
+		'shape': flattenShapeFrom( xsh, dim ),
+		'order': opts.order,
+		'dtype': opts.dtype
+	});
+
+	// 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( opts.dtype, getData( y ), xsh, st, 0, opts.order );
+
+	// Copy elements to the output ndarray:
+	assign( [ x, view ] );
+
+	return y;
+}
+
+
+// EXPORTS //
+
+module.exports = flattenFrom;
diff --git a/lib/node_modules/@stdlib/ndarray/flatten-from/package.json b/lib/node_modules/@stdlib/ndarray/flatten-from/package.json
new file mode 100644
index 000000000000..7a2dc47d4805
--- /dev/null
+++ b/lib/node_modules/@stdlib/ndarray/flatten-from/package.json
@@ -0,0 +1,66 @@
+{
+  "name": "@stdlib/ndarray/flatten-from",
+  "version": "0.0.0",
+  "description": "Return a copy of an input ndarray, where all dimensions of the input ndarray are flattened starting from a specific dimension.",
+  "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",
+    "flatten-from",
+    "reshape",
+    "copy",
+    "transform"
+  ],
+  "__stdlib__": {}
+}
diff --git a/lib/node_modules/@stdlib/ndarray/flatten-from/test/test.js b/lib/node_modules/@stdlib/ndarray/flatten-from/test/test.js
new file mode 100644
index 000000000000..2cdc03d39235
--- /dev/null
+++ b/lib/node_modules/@stdlib/ndarray/flatten-from/test/test.js
@@ -0,0 +1,1518 @@
+/**
+* @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 isSameFloat32Array = require( '@stdlib/assert/is-same-float32array' );
+var zeros = require( '@stdlib/ndarray/zeros' );
+var ndarray = require( '@stdlib/ndarray/ctor' );
+var Float64Array = require( '@stdlib/array/float64' );
+var Float32Array = require( '@stdlib/array/float32' );
+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 flattenFrom = require( './../lib' );
+
+
+// TESTS //
+
+tape( 'main export is a function', function test( t ) {
+	t.ok( true, __filename );
+	t.strictEqual( typeof flattenFrom, '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() {
+			flattenFrom( value, 0 );
+		};
+	}
+});
+
+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() {
+			flattenFrom( value, 0, {} );
+		};
+	}
+});
+
+tape( 'the function throws an error if provided a second argument which is not an integer', function test( t ) {
+	var values;
+	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() {
+			flattenFrom( zeros( [ 2, 2 ] ), value );
+		};
+	}
+});
+
+tape( 'the function throws an error if provided a second argument which is not an integer (options)', function test( t ) {
+	var values;
+	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() {
+			flattenFrom( zeros( [ 2, 2 ] ), 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() {
+			flattenFrom( zeros( [ 2, 2, 2 ] ), 0, value );
+		};
+	}
+});
+
+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
+			};
+			flattenFrom( zeros( [ 2 ] ), 0, opts );
+		};
+	}
+});
+
+tape( 'the function throws an error if provided an invalid `dtype` option', function test( t ) {
+	var values;
+	var i;
+
+	values = [
+		'foo',
+		'bar',
+		1,
+		NaN,
+		true,
+		false,
+		void 0,
+		null,
+		[],
+		{},
+		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 opts = {
+				'dtype': value
+			};
+			flattenFrom( zeros( [ 2 ] ), 0, opts );
+		};
+	}
+});
+
+tape( 'by default, the function flattens all dimensions of a provided input ndarray starting from a specific dimension 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 = flattenFrom( x, 0 );
+	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 = flattenFrom( x, 1 );
+	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 ), [ 2, 4 ], 'returns expected value' );
+	t.strictEqual( getDType( y ), dt, 'returns expected value' );
+	t.strictEqual( getOrder( y ), 'row-major', 'returns expected value' );
+
+	y = flattenFrom( x, 2 );
+	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 ), [ 2, 2, 2 ], '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 starting from a specific dimension 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 = flattenFrom( x, 0 );
+	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 = flattenFrom( x, 1 );
+	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 ), [ 2, 4 ], 'returns expected value' );
+	t.strictEqual( getDType( y ), dt, 'returns expected value' );
+	t.strictEqual( getOrder( y ), 'row-major', 'returns expected value' );
+
+	y = flattenFrom( x, 2 );
+	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 ), [ 2, 2, 2 ], '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 starting from a specific dimension 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 = flattenFrom( x, 0 );
+	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 = flattenFrom( x, 1 );
+	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 ), [ 2, 4 ], 'returns expected value' );
+	t.strictEqual( getDType( y ), dt, 'returns expected value' );
+	t.strictEqual( getOrder( y ), 'row-major', 'returns expected value' );
+
+	y = flattenFrom( x, 2 );
+	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 ), [ 2, 2, 2 ], '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 starting from a specific dimension 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 = flattenFrom( x, 0 );
+	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 = flattenFrom( x, 1 );
+	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 ), [ 2, 4 ], 'returns expected value' );
+	t.strictEqual( getDType( y ), dt, 'returns expected value' );
+	t.strictEqual( getOrder( y ), 'row-major', 'returns expected value' );
+
+	y = flattenFrom( x, 2 );
+	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 ), [ 2, 2, 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 (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 = flattenFrom( x, 0, {
+		'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 = flattenFrom( x, 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 ), [ 2, 4 ], 'returns expected value' );
+	t.strictEqual( getDType( y ), dt, 'returns expected value' );
+	t.strictEqual( getOrder( y ), 'row-major', 'returns expected value' );
+
+	y = flattenFrom( x, 2, {
+		'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 ), [ 2, 2, 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 = flattenFrom( x, 0, {
+		'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 = flattenFrom( x, 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 ), [ 2, 4 ], 'returns expected value' );
+	t.strictEqual( getDType( y ), dt, 'returns expected value' );
+	t.strictEqual( getOrder( y ), 'row-major', 'returns expected value' );
+
+	y = flattenFrom( x, 2, {
+		'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 ), [ 2, 2, 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 = flattenFrom( x, 0, {
+		'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 = flattenFrom( x, 1, {
+		'order': 'column-major'
+	});
+	expected = [
+		[ 1.0, 3.0, 2.0, 4.0 ],
+		[ 5.0, 7.0, 6.0, 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, 4 ], 'returns expected value' );
+	t.strictEqual( getDType( y ), dt, 'returns expected value' );
+	t.strictEqual( getOrder( y ), 'column-major', 'returns expected value' );
+
+	y = flattenFrom( x, 2, {
+		'order': 'column-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 ), [ 2, 2, 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 = flattenFrom( x, 0, {
+		'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 = flattenFrom( x, 1, {
+		'order': 'column-major'
+	});
+	expected = [
+		[ 1.0, 3.0, 2.0, 4.0 ],
+		[ 5.0, 7.0, 6.0, 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, 4 ], 'returns expected value' );
+	t.strictEqual( getDType( y ), dt, 'returns expected value' );
+	t.strictEqual( getOrder( y ), 'column-major', 'returns expected value' );
+
+	y = flattenFrom( x, 2, {
+		'order': 'column-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 ), [ 2, 2, 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 = flattenFrom( x, 0, {
+		'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 = flattenFrom( x, 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 ), [ 2, 4 ], 'returns expected value' );
+	t.strictEqual( getDType( y ), dt, 'returns expected value' );
+	t.strictEqual( getOrder( y ), 'row-major', 'returns expected value' );
+
+	y = flattenFrom( x, 2, {
+		'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 ), [ 2, 2, 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 = flattenFrom( x, 0, {
+		'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 = flattenFrom( x, 1, {
+		'order': 'same'
+	});
+	expected = [
+		[ 1.0, 3.0, 2.0, 4.0 ],
+		[ 5.0, 7.0, 6.0, 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, 4 ], 'returns expected value' );
+	t.strictEqual( getDType( y ), dt, 'returns expected value' );
+	t.strictEqual( getOrder( y ), 'column-major', 'returns expected value' );
+
+	y = flattenFrom( x, 2, {
+		'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 ), [ 2, 2, 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 = flattenFrom( x, 0, {
+		'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 = flattenFrom( x, 1, {
+		'order': 'any'
+	});
+	expected = [
+		[ 8.0, 6.0, 4.0, 2.0 ],
+		[ 7.0, 5.0, 3.0, 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 ), [ 2, 4 ], 'returns expected value' );
+	t.strictEqual( getDType( y ), dt, 'returns expected value' );
+	t.strictEqual( getOrder( y ), 'column-major', 'returns expected value' );
+
+	y = flattenFrom( x, 2, {
+		'order': 'any'
+	});
+	expected = [
+		[
+			[ 8.0, 4.0 ],
+			[ 6.0, 2.0 ]
+		],
+		[
+			[ 7.0, 3.0 ],
+			[ 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 ), [ 2, 2, 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 = flattenFrom( x, 0, {
+		'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 = flattenFrom( x, 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 ), [ 2, 4 ], 'returns expected value' );
+	t.strictEqual( getDType( y ), dt, 'returns expected value' );
+	t.strictEqual( getOrder( y ), 'row-major', 'returns expected value' );
+
+	y = flattenFrom( x, 2, {
+		'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 ), [ 2, 2, 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 = flattenFrom( x, 0 );
+	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 = flattenFrom( x, 1 );
+	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 = flattenFrom( x, 0, {
+		'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 = flattenFrom( x, 1, {
+		'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 = flattenFrom( x, 0, {
+		'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 = flattenFrom( x, 1, {
+		'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 = flattenFrom( x, 0 );
+	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 = flattenFrom( x, 1 );
+	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 = flattenFrom( x, 0, {
+		'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 = flattenFrom( x, 1, {
+		'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 = flattenFrom( x, 0, {
+		'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 = flattenFrom( x, 1, {
+		'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();
+});
+
+tape( 'the function supports specifying the output ndarray data type', 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 = flattenFrom( x, 0, {
+		'dtype': 'float32'
+	});
+	expected = new Float32Array( [ 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( isSameFloat32Array( getData( y ), expected ), true, 'returns expected value' );
+	t.deepEqual( getShape( y ), [ 8 ], 'returns expected value' );
+	t.strictEqual( getDType( y ), 'float32', 'returns expected value' );
+	t.strictEqual( getOrder( y ), ord, 'returns expected value' );
+
+	t.end();
+});

From 558f8d1b9b97d7009a332680df75e497c0227b0d Mon Sep 17 00:00:00 2001
From: headlessNode <harriskhan047@outlook.com>
Date: Mon, 29 Sep 2025 20:19:07 +0500
Subject: [PATCH 2/4] refactor: apply suggestions from code review

---
type: pre_commit_static_analysis_report
description: Results of running static analysis checks when committing changes.
report:
  - task: lint_filenames
    status: passed
  - task: lint_editorconfig
    status: passed
  - task: lint_markdown
    status: passed
  - task: lint_package_json
    status: passed
  - task: lint_repl_help
    status: passed
  - task: lint_javascript_src
    status: passed
  - task: lint_javascript_cli
    status: na
  - task: lint_javascript_examples
    status: na
  - task: lint_javascript_tests
    status: passed
  - task: lint_javascript_benchmarks
    status: na
  - task: lint_python
    status: na
  - task: lint_r
    status: na
  - task: lint_c_src
    status: na
  - task: lint_c_examples
    status: na
  - task: lint_c_benchmarks
    status: na
  - task: lint_c_tests_fixtures
    status: na
  - task: lint_shell
    status: na
  - task: lint_typescript_declarations
    status: passed
  - task: lint_typescript_tests
    status: passed
  - task: lint_license_headers
    status: passed
---
---
 .../@stdlib/ndarray/flatten-from/README.md    |  25 +-
 .../ndarray/flatten-from/docs/repl.txt        |   2 +-
 .../flatten-from/docs/types/index.d.ts        |   4 +-
 .../@stdlib/ndarray/flatten-from/lib/index.js |   9 +-
 .../@stdlib/ndarray/flatten-from/lib/main.js  |   2 +-
 .../@stdlib/ndarray/flatten-from/package.json |   2 +-
 .../@stdlib/ndarray/flatten-from/test/test.js | 284 +++++++++++++++++-
 7 files changed, 288 insertions(+), 40 deletions(-)

diff --git a/lib/node_modules/@stdlib/ndarray/flatten-from/README.md b/lib/node_modules/@stdlib/ndarray/flatten-from/README.md
index 1f80b6360406..7dd6a9354fc9 100644
--- a/lib/node_modules/@stdlib/ndarray/flatten-from/README.md
+++ b/lib/node_modules/@stdlib/ndarray/flatten-from/README.md
@@ -20,7 +20,7 @@ limitations under the License.
 
 # flattenFrom
 
-> Return a copy of an input [ndarray][@stdlib/ndarray/ctor], where all dimensions of the input [ndarray][@stdlib/ndarray/ctor] are flattened starting from a specific dimension.
+> Return a copy of an input [ndarray][@stdlib/ndarray/ctor], where all dimensions of the input [ndarray][@stdlib/ndarray/ctor] are flattened starting from a specified dimension.
 
 <section class="intro">
 
@@ -38,25 +38,18 @@ var flattenFrom = require( '@stdlib/ndarray/flatten-from' );
 
 #### flattenFrom( x, dim\[, options] )
 
-Returns a copy of an input [ndarray][@stdlib/ndarray/ctor], where all dimensions of the input [ndarray][@stdlib/ndarray/ctor] are flattened starting from a specific dimension.
+Returns a copy of an input [ndarray][@stdlib/ndarray/ctor], where all dimensions of the input [ndarray][@stdlib/ndarray/ctor] are flattened starting from a specified dimension.
 
 ```javascript
 var array = require( '@stdlib/ndarray/array' );
-var shape = require( '@stdlib/ndarray/shape' );
 var ndarray2array = require( '@stdlib/ndarray/to-array' );
 
 var x = array( [ [ [ 1.0, 2.0 ] ], [ [ 3.0, 4.0 ] ], [ [ 5.0, 6.0 ] ] ] );
 // returns <ndarray>
 
-var shx = shape( x );
-// returns [ 3, 1, 2 ]
-
 var y = flattenFrom( x, 1 );
 // returns <ndarray>
 
-var shy = shape( y );
-// returns [ 3, 2 ]
-
 var arr = ndarray2array( y );
 // returns [ [ 1, 2 ], [ 3, 4 ], [ 5, 6 ] ]
 ```
@@ -84,23 +77,16 @@ By default, the input [ndarray][@stdlib/ndarray/ctor] is flattened in lexicograp
 
 ```javascript
 var array = require( '@stdlib/ndarray/array' );
-var shape = require( '@stdlib/ndarray/shape' );
 var ndarray2array = require( '@stdlib/ndarray/to-array' );
 
 var x = array( [ [ [ 1.0, 2.0 ] ], [ [ 3.0, 4.0 ] ], [ [ 5.0, 6.0 ] ] ] );
 // returns <ndarray>
 
-var shx = shape( x );
-// returns [ 3, 1, 2 ]
-
 var y = flattenFrom( x, 0, {
     'order': 'column-major'
 });
 // returns <ndarray>
 
-var shy = shape( y );
-// returns [ 6 ]
-
 var arr = ndarray2array( y );
 // returns [ 1.0, 3.0, 5.0, 2.0, 4.0, 6.0 ]
 ```
@@ -110,23 +96,16 @@ By default, the output ndarray [data type][@stdlib/ndarray/dtypes] is inferred f
 ```javascript
 var array = require( '@stdlib/ndarray/array' );
 var dtype = require( '@stdlib/ndarray/dtype' );
-var shape = require( '@stdlib/ndarray/shape' );
 var ndarray2array = require( '@stdlib/ndarray/to-array' );
 
 var x = array( [ [ [ 1.0, 2.0 ] ], [ [ 3.0, 4.0 ] ], [ [ 5.0, 6.0 ] ] ] );
 // returns <ndarray>
 
-var shx = shape( x );
-// returns [ 3, 1, 2 ]
-
 var y = flattenFrom( x, 0, {
     'dtype': 'float32'
 });
 // returns <ndarray>
 
-var shy = shape( y );
-// returns [ 6 ]
-
 var dt = dtype( y );
 // returns 'float32'
 
diff --git a/lib/node_modules/@stdlib/ndarray/flatten-from/docs/repl.txt b/lib/node_modules/@stdlib/ndarray/flatten-from/docs/repl.txt
index fd55a15c6063..72be6e9cec51 100644
--- a/lib/node_modules/@stdlib/ndarray/flatten-from/docs/repl.txt
+++ b/lib/node_modules/@stdlib/ndarray/flatten-from/docs/repl.txt
@@ -1,7 +1,7 @@
 
 {{alias}}( x, dim[, options] )
     Returns a copy of an input ndarray, where all dimensions of the input
-    ndarray are flattened starting from a specific dimension.
+    ndarray are flattened starting from a specified dimension.
 
     The function always returns a copy of input ndarray data, even when an input
     ndarray already has the desired number of dimensions.
diff --git a/lib/node_modules/@stdlib/ndarray/flatten-from/docs/types/index.d.ts b/lib/node_modules/@stdlib/ndarray/flatten-from/docs/types/index.d.ts
index ac7b5e99fb09..0fb2135968c4 100644
--- a/lib/node_modules/@stdlib/ndarray/flatten-from/docs/types/index.d.ts
+++ b/lib/node_modules/@stdlib/ndarray/flatten-from/docs/types/index.d.ts
@@ -54,7 +54,7 @@ type Options<U> = BaseOptions & {
 };
 
 /**
-* Returns a copy of an input ndarray, where all dimensions of the input ndarray are flattened starting from a specific dimension.
+* Returns a copy of an input ndarray, where all dimensions of the input ndarray are flattened starting from a specified dimension.
 *
 * ## Notes
 *
@@ -91,7 +91,7 @@ type Options<U> = BaseOptions & {
 declare function flattenFrom<T extends ndarray>( x: T, dim: number, options?: BaseOptions ): T;
 
 /**
-* Returns a copy of an input ndarray, where all dimensions of the input ndarray are flattened starting from a specific dimension.
+* Returns a copy of an input ndarray, where all dimensions of the input ndarray are flattened starting from a specified dimension.
 *
 * ## Notes
 *
diff --git a/lib/node_modules/@stdlib/ndarray/flatten-from/lib/index.js b/lib/node_modules/@stdlib/ndarray/flatten-from/lib/index.js
index 674954209bbe..9c3e12ff5121 100644
--- a/lib/node_modules/@stdlib/ndarray/flatten-from/lib/index.js
+++ b/lib/node_modules/@stdlib/ndarray/flatten-from/lib/index.js
@@ -19,13 +19,12 @@
 'use strict';
 
 /**
-* Return a copy of an input ndarray, where all dimensions of the input ndarray are flattened starting from a specific dimension.
+* Return a copy of an input ndarray, where all dimensions of the input ndarray are flattened starting from a specified dimension.
 *
 * @module @stdlib/ndarray/flatten-from
 *
 * @example
 * var array = require( '@stdlib/ndarray/array' );
-* var shape = require( '@stdlib/ndarray/shape' );
 * var ndarray2array = require( '@stdlib/ndarray/to-array' );
 * var flattenFrom = require( '@stdlib/ndarray/flatten-from' );
 *
@@ -33,16 +32,10 @@
 * var x = array( [ [ [ 1.0, 2.0 ] ], [ [ 3.0, 4.0 ] ], [ [ 5.0, 6.0 ] ] ] );
 * // returns <ndarray>
 *
-* var shx = shape( x );
-* // returns [ 3, 1, 2 ]
-*
 * // Flatten the input ndarray:
 * var y = flattenFrom( x, 1 );
 * // returns <ndarray>
 *
-* var shy = shape( y );
-* // returns [ 3, 2 ]
-*
 * var arr = ndarray2array( y );
 * // returns [ [ 1, 2 ], [ 3, 4 ], [ 5, 6 ] ]
 */
diff --git a/lib/node_modules/@stdlib/ndarray/flatten-from/lib/main.js b/lib/node_modules/@stdlib/ndarray/flatten-from/lib/main.js
index 19415b3b4fff..d7e55865aae8 100644
--- a/lib/node_modules/@stdlib/ndarray/flatten-from/lib/main.js
+++ b/lib/node_modules/@stdlib/ndarray/flatten-from/lib/main.js
@@ -48,7 +48,7 @@ var COL_MAJOR = 'column-major';
 // MAIN //
 
 /**
-* Returns a copy of an input ndarray, where all dimensions of the input ndarray are flattened starting from a specific dimension.
+* Returns a copy of an input ndarray, where all dimensions of the input ndarray are flattened starting from a specified dimension.
 *
 * @param {ndarray} x - input ndarray
 * @param {integer} dim - dimension to start flattening from.
diff --git a/lib/node_modules/@stdlib/ndarray/flatten-from/package.json b/lib/node_modules/@stdlib/ndarray/flatten-from/package.json
index 7a2dc47d4805..3531908dfc2a 100644
--- a/lib/node_modules/@stdlib/ndarray/flatten-from/package.json
+++ b/lib/node_modules/@stdlib/ndarray/flatten-from/package.json
@@ -1,7 +1,7 @@
 {
   "name": "@stdlib/ndarray/flatten-from",
   "version": "0.0.0",
-  "description": "Return a copy of an input ndarray, where all dimensions of the input ndarray are flattened starting from a specific dimension.",
+  "description": "Return a copy of an input ndarray, where all dimensions of the input ndarray are flattened starting from a specified dimension.",
   "license": "Apache-2.0",
   "author": {
     "name": "The Stdlib Authors",
diff --git a/lib/node_modules/@stdlib/ndarray/flatten-from/test/test.js b/lib/node_modules/@stdlib/ndarray/flatten-from/test/test.js
index 2cdc03d39235..11f8379018ba 100644
--- a/lib/node_modules/@stdlib/ndarray/flatten-from/test/test.js
+++ b/lib/node_modules/@stdlib/ndarray/flatten-from/test/test.js
@@ -248,7 +248,7 @@ tape( 'the function throws an error if provided an invalid `dtype` option', func
 	}
 });
 
-tape( 'by default, the function flattens all dimensions of a provided input ndarray starting from a specific dimension in lexicographic order (row-major, contiguous)', function test( t ) {
+tape( 'by default, the function flattens all dimensions of a provided input ndarray starting from a specified dimension in lexicographic order (row-major, contiguous)', function test( t ) {
 	var expected;
 	var xbuf;
 	var ord;
@@ -310,10 +310,20 @@ tape( 'by default, the function flattens all dimensions of a provided input ndar
 	t.strictEqual( getDType( y ), dt, 'returns expected value' );
 	t.strictEqual( getOrder( y ), 'row-major', 'returns expected value' );
 
+	y = flattenFrom( x, -1 );
+	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 ), [ 2, 2, 2 ], '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 starting from a specific dimension in lexicographic order (row-major, non-contiguous)', function test( t ) {
+tape( 'by default, the function flattens all dimensions of a provided input ndarray starting from a specified dimension in lexicographic order (row-major, non-contiguous)', function test( t ) {
 	var expected;
 	var xbuf;
 	var ord;
@@ -375,10 +385,20 @@ tape( 'by default, the function flattens all dimensions of a provided input ndar
 	t.strictEqual( getDType( y ), dt, 'returns expected value' );
 	t.strictEqual( getOrder( y ), 'row-major', 'returns expected value' );
 
+	y = flattenFrom( x, -1 );
+	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 ), [ 2, 2, 2 ], '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 starting from a specific dimension in lexicographic order (column-major, contiguous)', function test( t ) {
+tape( 'by default, the function flattens all dimensions of a provided input ndarray starting from a specified dimension in lexicographic order (column-major, contiguous)', function test( t ) {
 	var expected;
 	var xbuf;
 	var ord;
@@ -440,10 +460,20 @@ tape( 'by default, the function flattens all dimensions of a provided input ndar
 	t.strictEqual( getDType( y ), dt, 'returns expected value' );
 	t.strictEqual( getOrder( y ), 'row-major', 'returns expected value' );
 
+	y = flattenFrom( x, -1 );
+	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 ), [ 2, 2, 2 ], '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 starting from a specific dimension in lexicographic order (column-major, non-contiguous)', function test( t ) {
+tape( 'by default, the function flattens all dimensions of a provided input ndarray starting from a specified dimension in lexicographic order (column-major, non-contiguous)', function test( t ) {
 	var expected;
 	var xbuf;
 	var ord;
@@ -505,6 +535,16 @@ tape( 'by default, the function flattens all dimensions of a provided input ndar
 	t.strictEqual( getDType( y ), dt, 'returns expected value' );
 	t.strictEqual( getOrder( y ), 'row-major', 'returns expected value' );
 
+	y = flattenFrom( x, -1 );
+	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 ), [ 2, 2, 2 ], 'returns expected value' );
+	t.strictEqual( getDType( y ), dt, 'returns expected value' );
+	t.strictEqual( getOrder( y ), 'row-major', 'returns expected value' );
+
 	t.end();
 });
 
@@ -588,6 +628,27 @@ tape( 'the function supports flattening a provided input ndarray in lexicographi
 	t.strictEqual( getDType( y ), dt, 'returns expected value' );
 	t.strictEqual( getOrder( y ), 'row-major', 'returns expected value' );
 
+	y = flattenFrom( x, -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 ), [ 2, 2, 2 ], 'returns expected value' );
+	t.strictEqual( getDType( y ), dt, 'returns expected value' );
+	t.strictEqual( getOrder( y ), 'row-major', 'returns expected value' );
+
 	t.end();
 });
 
@@ -671,6 +732,27 @@ tape( 'the function supports flattening a provided input ndarray in lexicographi
 	t.strictEqual( getDType( y ), dt, 'returns expected value' );
 	t.strictEqual( getOrder( y ), 'row-major', 'returns expected value' );
 
+	y = flattenFrom( x, -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 ), [ 2, 2, 2 ], 'returns expected value' );
+	t.strictEqual( getDType( y ), dt, 'returns expected value' );
+	t.strictEqual( getOrder( y ), 'row-major', 'returns expected value' );
+
 	t.end();
 });
 
@@ -754,6 +836,27 @@ tape( 'the function supports flattening a provided input ndarray in colexicograp
 	t.strictEqual( getDType( y ), dt, 'returns expected value' );
 	t.strictEqual( getOrder( y ), 'column-major', 'returns expected value' );
 
+	y = flattenFrom( x, -1, {
+		'order': 'column-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 ), [ 2, 2, 2 ], 'returns expected value' );
+	t.strictEqual( getDType( y ), dt, 'returns expected value' );
+	t.strictEqual( getOrder( y ), 'column-major', 'returns expected value' );
+
 	t.end();
 });
 
@@ -837,6 +940,27 @@ tape( 'the function supports flattening a provided input ndarray in colexicograp
 	t.strictEqual( getDType( y ), dt, 'returns expected value' );
 	t.strictEqual( getOrder( y ), 'column-major', 'returns expected value' );
 
+	y = flattenFrom( x, -1, {
+		'order': 'column-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 ), [ 2, 2, 2 ], 'returns expected value' );
+	t.strictEqual( getDType( y ), dt, 'returns expected value' );
+	t.strictEqual( getOrder( y ), 'column-major', 'returns expected value' );
+
 	t.end();
 });
 
@@ -920,6 +1044,27 @@ tape( 'the function supports flattening a provided input ndarray in same order a
 	t.strictEqual( getDType( y ), dt, 'returns expected value' );
 	t.strictEqual( getOrder( y ), 'row-major', 'returns expected value' );
 
+	y = flattenFrom( x, -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 ), [ 2, 2, 2 ], 'returns expected value' );
+	t.strictEqual( getDType( y ), dt, 'returns expected value' );
+	t.strictEqual( getOrder( y ), 'row-major', 'returns expected value' );
+
 	t.end();
 });
 
@@ -1003,6 +1148,27 @@ tape( 'the function supports flattening a provided input ndarray in same order a
 	t.strictEqual( getDType( y ), dt, 'returns expected value' );
 	t.strictEqual( getOrder( y ), 'column-major', 'returns expected value' );
 
+	y = flattenFrom( x, -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 ), [ 2, 2, 2 ], 'returns expected value' );
+	t.strictEqual( getDType( y ), dt, 'returns expected value' );
+	t.strictEqual( getOrder( y ), 'column-major', 'returns expected value' );
+
 	t.end();
 });
 
@@ -1086,6 +1252,27 @@ tape( 'the function supports flattening a provided input ndarray according to th
 	t.strictEqual( getDType( y ), dt, 'returns expected value' );
 	t.strictEqual( getOrder( y ), 'column-major', 'returns expected value' );
 
+	y = flattenFrom( x, -1, {
+		'order': 'any'
+	});
+	expected = [
+		[
+			[ 8.0, 4.0 ],
+			[ 6.0, 2.0 ]
+		],
+		[
+			[ 7.0, 3.0 ],
+			[ 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 ), [ 2, 2, 2 ], 'returns expected value' );
+	t.strictEqual( getDType( y ), dt, 'returns expected value' );
+	t.strictEqual( getOrder( y ), 'column-major', 'returns expected value' );
+
 	t.end();
 });
 
@@ -1169,6 +1356,27 @@ tape( 'the function supports flattening a provided input ndarray according to th
 	t.strictEqual( getDType( y ), dt, 'returns expected value' );
 	t.strictEqual( getOrder( y ), 'row-major', 'returns expected value' );
 
+	y = flattenFrom( x, -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 ), [ 2, 2, 2 ], 'returns expected value' );
+	t.strictEqual( getDType( y ), dt, 'returns expected value' );
+	t.strictEqual( getOrder( y ), 'row-major', 'returns expected value' );
+
 	t.end();
 });
 
@@ -1211,6 +1419,16 @@ tape( 'the function supports flattening a zero-dimensional input ndarray', funct
 	t.strictEqual( getDType( y ), dt, 'returns expected value' );
 	t.strictEqual( getOrder( y ), 'row-major', 'returns expected value' );
 
+	y = flattenFrom( x, -1 );
+	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();
 });
 
@@ -1257,6 +1475,18 @@ tape( 'the function supports flattening a zero-dimensional input ndarray (order=
 	t.strictEqual( getDType( y ), dt, 'returns expected value' );
 	t.strictEqual( getOrder( y ), 'column-major', 'returns expected value' );
 
+	y = flattenFrom( x, -1, {
+		'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();
 });
 
@@ -1303,6 +1533,18 @@ tape( 'the function supports flattening a zero-dimensional input ndarray (order=
 	t.strictEqual( getDType( y ), dt, 'returns expected value' );
 	t.strictEqual( getOrder( y ), 'column-major', 'returns expected value' );
 
+	y = flattenFrom( x, -1, {
+		'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();
 });
 
@@ -1355,6 +1597,16 @@ tape( 'the function supports flattening a one-dimensional input ndarray', functi
 	t.strictEqual( getDType( y ), dt, 'returns expected value' );
 	t.strictEqual( getOrder( y ), 'row-major', 'returns expected value' );
 
+	y = flattenFrom( x, -1 );
+	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();
 });
 
@@ -1411,6 +1663,18 @@ tape( 'the function supports flattening a one-dimensional input ndarray (order=s
 	t.strictEqual( getDType( y ), dt, 'returns expected value' );
 	t.strictEqual( getOrder( y ), 'column-major', 'returns expected value' );
 
+	y = flattenFrom( x, -1, {
+		'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();
 });
 
@@ -1467,6 +1731,18 @@ tape( 'the function supports flattening a one-dimensional input ndarray (order=a
 	t.strictEqual( getDType( y ), dt, 'returns expected value' );
 	t.strictEqual( getOrder( y ), 'column-major', 'returns expected value' );
 
+	y = flattenFrom( x, -1, {
+		'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();
 });
 

From fd1aff4fdb04cb275a1d050f2b93adc7d9c81da0 Mon Sep 17 00:00:00 2001
From: Athan <kgryte@gmail.com>
Date: Fri, 3 Oct 2025 10:39:16 +0100
Subject: [PATCH 3/4] chore: clean-up

---
type: pre_commit_static_analysis_report
description: Results of running static analysis checks when committing changes.
report:
  - task: lint_filenames
    status: passed
  - task: lint_editorconfig
    status: passed
  - task: lint_markdown
    status: passed
  - task: lint_package_json
    status: passed
  - task: lint_repl_help
    status: passed
  - task: lint_javascript_src
    status: passed
  - task: lint_javascript_cli
    status: na
  - task: lint_javascript_examples
    status: na
  - task: lint_javascript_tests
    status: passed
  - task: lint_javascript_benchmarks
    status: na
  - task: lint_python
    status: na
  - task: lint_r
    status: na
  - task: lint_c_src
    status: na
  - task: lint_c_examples
    status: na
  - task: lint_c_benchmarks
    status: na
  - task: lint_c_tests_fixtures
    status: na
  - task: lint_shell
    status: na
  - task: lint_typescript_declarations
    status: passed
  - task: lint_typescript_tests
    status: passed
  - task: lint_license_headers
    status: passed
---
---
 .../@stdlib/ndarray/flatten-from/README.md    |   8 +-
 .../ndarray/flatten-from/docs/repl.txt        |   6 +-
 .../flatten-from/docs/types/index.d.ts        |   8 +-
 .../ndarray/flatten-from/docs/types/test.ts   |   4 +-
 .../@stdlib/ndarray/flatten-from/lib/index.js |   4 +-
 .../@stdlib/ndarray/flatten-from/lib/main.js  |  22 +-
 .../@stdlib/ndarray/flatten-from/package.json |   2 +-
 .../@stdlib/ndarray/flatten-from/test/test.js | 283 +++---------------
 8 files changed, 71 insertions(+), 266 deletions(-)

diff --git a/lib/node_modules/@stdlib/ndarray/flatten-from/README.md b/lib/node_modules/@stdlib/ndarray/flatten-from/README.md
index 7dd6a9354fc9..6e28f0881530 100644
--- a/lib/node_modules/@stdlib/ndarray/flatten-from/README.md
+++ b/lib/node_modules/@stdlib/ndarray/flatten-from/README.md
@@ -20,7 +20,7 @@ limitations under the License.
 
 # flattenFrom
 
-> Return a copy of an input [ndarray][@stdlib/ndarray/ctor], where all dimensions of the input [ndarray][@stdlib/ndarray/ctor] are flattened starting from a specified dimension.
+> Return a copy of an input [ndarray][@stdlib/ndarray/ctor] where all dimensions of the input [ndarray][@stdlib/ndarray/ctor] are flattened starting from a specified dimension.
 
 <section class="intro">
 
@@ -38,7 +38,7 @@ var flattenFrom = require( '@stdlib/ndarray/flatten-from' );
 
 #### flattenFrom( x, dim\[, options] )
 
-Returns a copy of an input [ndarray][@stdlib/ndarray/ctor], where all dimensions of the input [ndarray][@stdlib/ndarray/ctor] are flattened starting from a specified dimension.
+Returns a copy of an input [ndarray][@stdlib/ndarray/ctor] where all dimensions of the input [ndarray][@stdlib/ndarray/ctor] are flattened starting from a specified dimension.
 
 ```javascript
 var array = require( '@stdlib/ndarray/array' );
@@ -51,12 +51,12 @@ var y = flattenFrom( x, 1 );
 // returns <ndarray>
 
 var arr = ndarray2array( y );
-// returns [ [ 1, 2 ], [ 3, 4 ], [ 5, 6 ] ]
+// 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].
+-   **x**: input [ndarray][@stdlib/ndarray/ctor]. Must have one or more dimensions.
 -   **dim**: dimension to start flattening from. If provided an integer less than zero, the dimension index is resolved relative to the last dimension, with the last dimension corresponding to the value `-1`.
 -   **options**: function options (_optional_).
 
diff --git a/lib/node_modules/@stdlib/ndarray/flatten-from/docs/repl.txt b/lib/node_modules/@stdlib/ndarray/flatten-from/docs/repl.txt
index 72be6e9cec51..bfe2f6ea9597 100644
--- a/lib/node_modules/@stdlib/ndarray/flatten-from/docs/repl.txt
+++ b/lib/node_modules/@stdlib/ndarray/flatten-from/docs/repl.txt
@@ -1,7 +1,7 @@
 
 {{alias}}( x, dim[, options] )
-    Returns a copy of an input ndarray, where all dimensions of the input
-    ndarray are flattened starting from a specified dimension.
+    Returns a copy of an input ndarray where all dimensions of the input ndarray
+    are flattened starting from a specified dimension.
 
     The function always returns a copy of input ndarray data, even when an input
     ndarray already has the desired number of dimensions.
@@ -9,7 +9,7 @@
     Parameters
     ----------
     x: ndarray
-        Input ndarray.
+        Input ndarray. Must have one or more dimensions.
 
     dim: integer
         Dimension to start flattening from. If provided an integer less than
diff --git a/lib/node_modules/@stdlib/ndarray/flatten-from/docs/types/index.d.ts b/lib/node_modules/@stdlib/ndarray/flatten-from/docs/types/index.d.ts
index 0fb2135968c4..e917c415ba16 100644
--- a/lib/node_modules/@stdlib/ndarray/flatten-from/docs/types/index.d.ts
+++ b/lib/node_modules/@stdlib/ndarray/flatten-from/docs/types/index.d.ts
@@ -54,7 +54,7 @@ type Options<U> = BaseOptions & {
 };
 
 /**
-* Returns a copy of an input ndarray, where all dimensions of the input ndarray are flattened starting from a specified dimension.
+* Returns a copy of an input ndarray where all dimensions of the input ndarray are flattened starting from a specified dimension.
 *
 * ## Notes
 *
@@ -86,12 +86,12 @@ type Options<U> = BaseOptions & {
 * // returns [ 3, 2 ]
 *
 * var arr = ndarray2array( y );
-* // returns [ [ 1, 2 ], [ 3, 4 ], [ 5, 6 ] ]
+* // returns [ [ 1.0, 2.0 ], [ 3.0, 4.0 ], [ 5.0, 6.0 ] ]
 */
 declare function flattenFrom<T extends ndarray>( x: T, dim: number, options?: BaseOptions ): T;
 
 /**
-* Returns a copy of an input ndarray, where all dimensions of the input ndarray are flattened starting from a specified dimension.
+* Returns a copy of an input ndarray where all dimensions of the input ndarray are flattened starting from a specified dimension.
 *
 * ## Notes
 *
@@ -122,7 +122,7 @@ declare function flattenFrom<T extends ndarray>( x: T, dim: number, options?: Ba
 * // returns [ 3, 2 ]
 *
 * var arr = ndarray2array( y );
-* // returns [ [ 1, 2 ], [ 3, 4 ], [ 5, 6 ] ]
+* // returns [ [ 1.0, 2.0 ], [ 3.0, 4.0 ], [ 5.0, 6.0 ] ]
 */
 declare function flattenFrom<T = unknown, U extends keyof DataTypeMap<T> = 'generic'>( x: typedndarray<T>, dim: number, options: Options<U> ): DataTypeMap<T>[U];
 
diff --git a/lib/node_modules/@stdlib/ndarray/flatten-from/docs/types/test.ts b/lib/node_modules/@stdlib/ndarray/flatten-from/docs/types/test.ts
index 8e95897392de..98275aba15cf 100644
--- a/lib/node_modules/@stdlib/ndarray/flatten-from/docs/types/test.ts
+++ b/lib/node_modules/@stdlib/ndarray/flatten-from/docs/types/test.ts
@@ -130,7 +130,7 @@ import flattenFrom = require( './index' );
 	flattenFrom( zeros( 'generic', [ 2, 2, 2 ], 'row-major' ), 0, ( x: number ): number => x ); // $ExpectError
 }
 
-// The compiler throws an error if the function is provided a second argument with invalid `order` option...
+// The compiler throws an error if the function is provided a second argument with an invalid `order` option...
 {
 	flattenFrom( zeros( 'float64', [ 2, 2, 2 ], 'row-major' ), 0, { 'order': '5' } ); // $ExpectError
 	flattenFrom( zeros( 'float64', [ 2, 2, 2 ], 'row-major' ), 0, { 'order': true } ); // $ExpectError
@@ -154,7 +154,7 @@ import flattenFrom = require( './index' );
 	flattenFrom( zeros( 'generic', [ 2, 2, 2 ], 'row-major' ), 0, { 'order': ( x: number ): number => x } ); // $ExpectError
 }
 
-// The compiler throws an error if the function is provided a second argument with invalid `dtype` option...
+// The compiler throws an error if the function is provided a second argument with an invalid `dtype` option...
 {
 	flattenFrom( zeros( 'float64', [ 2, 2, 2 ], 'row-major' ), 0, { 'dtype': '5' } ); // $ExpectError
 	flattenFrom( zeros( 'float64', [ 2, 2, 2 ], 'row-major' ), 0, { 'dtype': true } ); // $ExpectError
diff --git a/lib/node_modules/@stdlib/ndarray/flatten-from/lib/index.js b/lib/node_modules/@stdlib/ndarray/flatten-from/lib/index.js
index 9c3e12ff5121..b2ad4f7665b2 100644
--- a/lib/node_modules/@stdlib/ndarray/flatten-from/lib/index.js
+++ b/lib/node_modules/@stdlib/ndarray/flatten-from/lib/index.js
@@ -19,7 +19,7 @@
 'use strict';
 
 /**
-* Return a copy of an input ndarray, where all dimensions of the input ndarray are flattened starting from a specified dimension.
+* Return a copy of an input ndarray where all dimensions of the input ndarray are flattened starting from a specified dimension.
 *
 * @module @stdlib/ndarray/flatten-from
 *
@@ -37,7 +37,7 @@
 * // returns <ndarray>
 *
 * var arr = ndarray2array( y );
-* // returns [ [ 1, 2 ], [ 3, 4 ], [ 5, 6 ] ]
+* // returns [ [ 1.0, 2.0 ], [ 3.0, 4.0 ], [ 5.0, 6.0 ] ]
 */
 
 // MODULES //
diff --git a/lib/node_modules/@stdlib/ndarray/flatten-from/lib/main.js b/lib/node_modules/@stdlib/ndarray/flatten-from/lib/main.js
index d7e55865aae8..1891baa27fec 100644
--- a/lib/node_modules/@stdlib/ndarray/flatten-from/lib/main.js
+++ b/lib/node_modules/@stdlib/ndarray/flatten-from/lib/main.js
@@ -48,14 +48,14 @@ var COL_MAJOR = 'column-major';
 // MAIN //
 
 /**
-* Returns a copy of an input ndarray, where all dimensions of the input ndarray are flattened starting from a specified dimension.
+* Returns a copy of an input ndarray where all dimensions of the input ndarray are flattened starting from a specified dimension.
 *
 * @param {ndarray} x - input ndarray
-* @param {integer} dim - dimension to start flattening from.
+* @param {integer} dim - dimension to start flattening from
 * @param {Options} [options] - function options
 * @param {string} [options.order='row-major'] - order in which input ndarray elements should be flattened
 * @param {*} [options.dtype] - output ndarray data type
-* @throws {TypeError} first argument must be an ndarray-like object
+* @throws {TypeError} first argument must be an ndarray having one or more dimensions
 * @throws {TypeError} second argument must be an integer
 * @throws {TypeError} options argument must be an object
 * @throws {TypeError} must provide valid options
@@ -72,7 +72,7 @@ var COL_MAJOR = 'column-major';
 * // returns <ndarray>
 *
 * var arr = ndarray2array( y );
-* // returns [ [ 1, 2 ], [ 3, 4 ], [ 5, 6 ] ]
+* // returns [ [ 1.0, 2.0 ], [ 3.0, 4.0 ], [ 5.0, 6.0 ] ]
 *
 * @example
 * var array = require( '@stdlib/ndarray/array' );
@@ -282,7 +282,6 @@ var COL_MAJOR = 'column-major';
 * // returns [ 6.0, 5.0, 4.0, 3.0, 2.0, 1.0 ]
 */
 function flattenFrom( x, dim, options ) {
-	var nargs;
 	var view;
 	var opts;
 	var xsh;
@@ -291,14 +290,15 @@ function flattenFrom( x, dim, options ) {
 	var y;
 
 	if ( !isndarrayLike( x ) ) {
-		throw new TypeError( format( 'invalid argument. First argument must be an ndarray-like object. Value: `%s`.', x ) );
+		throw new TypeError( format( 'invalid argument. First argument must be an ndarray. Value: `%s`.', x ) );
 	}
 	if ( !isInteger( dim ) ) {
 		throw new TypeError( format( 'invalid argument. Second argument must be an integer. Value: `%s`.', dim ) );
 	}
-	nargs = arguments.length;
 	xsh = getShape( x );
-
+	if ( xsh.length < 1 ) {
+		throw new TypeError( format( 'invalid argument. First argument must be an ndarray having one or more dimensions. Number of dimensions: %d.', xsh.length ) );
+	}
 	// Define default options:
 	opts = {
 		'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)
@@ -306,7 +306,7 @@ function flattenFrom( x, dim, options ) {
 	};
 
 	// Resolve function options...
-	if ( nargs > 2 ) {
+	if ( arguments.length > 2 ) {
 		if ( !isPlainObject( options ) ) {
 			throw new TypeError( format( 'invalid argument. Options argument must be an object. Value: `%s`.', options ) );
 		}
@@ -341,12 +341,12 @@ function flattenFrom( x, dim, options ) {
 	}
 	// Create an output ndarray having contiguous memory:
 	y = emptyLike( x, {
-		'shape': flattenShapeFrom( xsh, dim ),
+		'shape': flattenShapeFrom( xsh, dim ), // note: delegate to `flattenShapeFrom` to handle `dim` normalization
 		'order': opts.order,
 		'dtype': opts.dtype
 	});
 
-	// Create a view on top of output ndarray having the same shape as the input ndarray:
+	// Create a view on top of the output ndarray having the same shape as the input ndarray:
 	st = ( xsh.length > 0 ) ? shape2strides( xsh, opts.order ) : [ 0 ];
 	view = ndarray( opts.dtype, getData( y ), xsh, st, 0, opts.order );
 
diff --git a/lib/node_modules/@stdlib/ndarray/flatten-from/package.json b/lib/node_modules/@stdlib/ndarray/flatten-from/package.json
index 3531908dfc2a..30a33c2a05b3 100644
--- a/lib/node_modules/@stdlib/ndarray/flatten-from/package.json
+++ b/lib/node_modules/@stdlib/ndarray/flatten-from/package.json
@@ -1,7 +1,7 @@
 {
   "name": "@stdlib/ndarray/flatten-from",
   "version": "0.0.0",
-  "description": "Return a copy of an input ndarray, where all dimensions of the input ndarray are flattened starting from a specified dimension.",
+  "description": "Return a copy of an input ndarray where all dimensions of the input ndarray are flattened starting from a specified dimension.",
   "license": "Apache-2.0",
   "author": {
     "name": "The Stdlib Authors",
diff --git a/lib/node_modules/@stdlib/ndarray/flatten-from/test/test.js b/lib/node_modules/@stdlib/ndarray/flatten-from/test/test.js
index 11f8379018ba..835601dee284 100644
--- a/lib/node_modules/@stdlib/ndarray/flatten-from/test/test.js
+++ b/lib/node_modules/@stdlib/ndarray/flatten-from/test/test.js
@@ -76,6 +76,26 @@ tape( 'the function throws an error if provided a first argument which is not an
 	}
 });
 
+tape( 'the function throws an error if provided a first argument which is not an ndarray having one or more dimensions', function test( t ) {
+	var values;
+	var i;
+
+	values = [
+		scalar2ndarray( 3.0 ),
+		scalar2ndarray( true )
+	];
+	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() {
+			flattenFrom( value, 0 );
+		};
+	}
+});
+
 tape( 'the function throws an error if provided a first argument which is not an ndarray (options)', function test( t ) {
 	var values;
 	var i;
@@ -170,6 +190,7 @@ tape( 'the function throws an error if provided an options argument which is not
 		false,
 		null,
 		void 0,
+		[],
 		function noop() {}
 	];
 	for ( i = 0; i < values.length; i++ ) {
@@ -628,24 +649,18 @@ tape( 'the function supports flattening a provided input ndarray in lexicographi
 	t.strictEqual( getDType( y ), dt, 'returns expected value' );
 	t.strictEqual( getOrder( y ), 'row-major', 'returns expected value' );
 
-	y = flattenFrom( x, -1, {
+	y = flattenFrom( x, -2, {
 		'order': 'row-major'
 	});
 	expected = [
-		[
-			[ 1.0, 2.0 ],
-			[ 3.0, 4.0 ]
-		],
-		[
-			[ 5.0, 6.0 ],
-			[ 7.0, 8.0 ]
-		]
+		[ 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.deepEqual( getShape( y ), [ 2, 4 ], 'returns expected value' );
 	t.strictEqual( getDType( y ), dt, 'returns expected value' );
 	t.strictEqual( getOrder( y ), 'row-major', 'returns expected value' );
 
@@ -732,24 +747,18 @@ tape( 'the function supports flattening a provided input ndarray in lexicographi
 	t.strictEqual( getDType( y ), dt, 'returns expected value' );
 	t.strictEqual( getOrder( y ), 'row-major', 'returns expected value' );
 
-	y = flattenFrom( x, -1, {
+	y = flattenFrom( x, -2, {
 		'order': 'row-major'
 	});
 	expected = [
-		[
-			[ 1.0, 2.0 ],
-			[ 3.0, 4.0 ]
-		],
-		[
-			[ 5.0, 6.0 ],
-			[ 7.0, 8.0 ]
-		]
+		[ 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.deepEqual( getShape( y ), [ 2, 4 ], 'returns expected value' );
 	t.strictEqual( getDType( y ), dt, 'returns expected value' );
 	t.strictEqual( getOrder( y ), 'row-major', 'returns expected value' );
 
@@ -836,24 +845,15 @@ tape( 'the function supports flattening a provided input ndarray in colexicograp
 	t.strictEqual( getDType( y ), dt, 'returns expected value' );
 	t.strictEqual( getOrder( y ), 'column-major', 'returns expected value' );
 
-	y = flattenFrom( x, -1, {
+	y = flattenFrom( x, -3, {
 		'order': 'column-major'
 	});
-	expected = [
-		[
-			[ 1.0, 2.0 ],
-			[ 3.0, 4.0 ]
-		],
-		[
-			[ 5.0, 6.0 ],
-			[ 7.0, 8.0 ]
-		]
-	];
+	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.deepEqual( ndarray2array( y ), expected, 'returns expected value' );
-	t.deepEqual( getShape( y ), [ 2, 2, 2 ], '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' );
 
@@ -940,24 +940,15 @@ tape( 'the function supports flattening a provided input ndarray in colexicograp
 	t.strictEqual( getDType( y ), dt, 'returns expected value' );
 	t.strictEqual( getOrder( y ), 'column-major', 'returns expected value' );
 
-	y = flattenFrom( x, -1, {
+	y = flattenFrom( x, -3, {
 		'order': 'column-major'
 	});
-	expected = [
-		[
-			[ 1.0, 2.0 ],
-			[ 3.0, 4.0 ]
-		],
-		[
-			[ 5.0, 6.0 ],
-			[ 7.0, 8.0 ]
-		]
-	];
+	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.deepEqual( ndarray2array( y ), expected, 'returns expected value' );
-	t.deepEqual( getShape( y ), [ 2, 2, 2 ], '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' );
 
@@ -1252,24 +1243,15 @@ tape( 'the function supports flattening a provided input ndarray according to th
 	t.strictEqual( getDType( y ), dt, 'returns expected value' );
 	t.strictEqual( getOrder( y ), 'column-major', 'returns expected value' );
 
-	y = flattenFrom( x, -1, {
+	y = flattenFrom( x, -3, {
 		'order': 'any'
 	});
-	expected = [
-		[
-			[ 8.0, 4.0 ],
-			[ 6.0, 2.0 ]
-		],
-		[
-			[ 7.0, 3.0 ],
-			[ 5.0, 1.0 ]
-		]
-	];
+	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.deepEqual( ndarray2array( y ), expected, 'returns expected value' );
-	t.deepEqual( getShape( y ), [ 2, 2, 2 ], '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' );
 
@@ -1356,195 +1338,18 @@ tape( 'the function supports flattening a provided input ndarray according to th
 	t.strictEqual( getDType( y ), dt, 'returns expected value' );
 	t.strictEqual( getOrder( y ), 'row-major', 'returns expected value' );
 
-	y = flattenFrom( x, -1, {
+	y = flattenFrom( x, -3, {
 		'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 ), [ 2, 2, 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 = flattenFrom( x, 0 );
-	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 = flattenFrom( x, 1 );
-	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' );
-
-	y = flattenFrom( x, -1 );
-	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 = flattenFrom( x, 0, {
-		'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 = flattenFrom( x, 1, {
-		'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' );
-
-	y = flattenFrom( x, -1, {
-		'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 = flattenFrom( x, 0, {
-		'order': 'any'
-	});
-	expected = new Float64Array( [ 3.0 ] );
+	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 ), [], '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';
-	x = scalar2ndarray( 3.0, {
-		'dtype': dt,
-		'order': 'column-major'
-	});
-
-	y = flattenFrom( x, 1, {
-		'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' );
-
-	y = flattenFrom( x, -1, {
-		'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();
 });
 

From a0e71b2a88d7bdc5250c8f86223873b0862b9935 Mon Sep 17 00:00:00 2001
From: Athan <kgryte@gmail.com>
Date: Fri, 3 Oct 2025 11:12:38 +0100
Subject: [PATCH 4/4] refactor: use base constructor and remove unreachable
 branch

---
type: pre_commit_static_analysis_report
description: Results of running static analysis checks when committing changes.
report:
  - task: lint_filenames
    status: passed
  - task: lint_editorconfig
    status: passed
  - task: lint_markdown
    status: na
  - task: lint_package_json
    status: na
  - task: lint_repl_help
    status: na
  - task: lint_javascript_src
    status: passed
  - task: lint_javascript_cli
    status: na
  - task: lint_javascript_examples
    status: na
  - task: lint_javascript_tests
    status: na
  - task: lint_javascript_benchmarks
    status: na
  - task: lint_python
    status: na
  - task: lint_r
    status: na
  - task: lint_c_src
    status: na
  - task: lint_c_examples
    status: na
  - task: lint_c_benchmarks
    status: na
  - task: lint_c_tests_fixtures
    status: na
  - task: lint_shell
    status: na
  - task: lint_typescript_declarations
    status: passed
  - task: lint_typescript_tests
    status: na
  - task: lint_license_headers
    status: passed
---
---
 lib/node_modules/@stdlib/ndarray/flatten-from/lib/main.js | 6 ++----
 1 file changed, 2 insertions(+), 4 deletions(-)

diff --git a/lib/node_modules/@stdlib/ndarray/flatten-from/lib/main.js b/lib/node_modules/@stdlib/ndarray/flatten-from/lib/main.js
index 1891baa27fec..dc47ec8736e0 100644
--- a/lib/node_modules/@stdlib/ndarray/flatten-from/lib/main.js
+++ b/lib/node_modules/@stdlib/ndarray/flatten-from/lib/main.js
@@ -34,8 +34,8 @@ var shape2strides = require( '@stdlib/ndarray/base/shape2strides' );
 var strides2order = require( '@stdlib/ndarray/base/strides2order' );
 var flattenShapeFrom = require( '@stdlib/ndarray/base/flatten-shape-from' );
 var assign = require( '@stdlib/ndarray/base/assign' );
+var ndarray = require( '@stdlib/ndarray/base/ctor' );
 var emptyLike = require( '@stdlib/ndarray/empty-like' );
-var ndarray = require( '@stdlib/ndarray/ctor' );
 var format = require( '@stdlib/string/format' );
 
 
@@ -285,7 +285,6 @@ function flattenFrom( x, dim, options ) {
 	var view;
 	var opts;
 	var xsh;
-	var st;
 	var o;
 	var y;
 
@@ -347,8 +346,7 @@ function flattenFrom( x, dim, options ) {
 	});
 
 	// Create a view on top of the output ndarray having the same shape as the input ndarray:
-	st = ( xsh.length > 0 ) ? shape2strides( xsh, opts.order ) : [ 0 ];
-	view = ndarray( opts.dtype, getData( y ), xsh, st, 0, opts.order );
+	view = new ndarray( opts.dtype, getData( y ), xsh, shape2strides( xsh, opts.order ), 0, opts.order ); // eslint-disable-line max-len
 
 	// Copy elements to the output ndarray:
 	assign( [ x, view ] );