From e2df0c7c1980af5bf5b87e940d59c9917ac97a15 Mon Sep 17 00:00:00 2001
From: headlessNode <harriskhan047@outlook.com>
Date: Fri, 8 May 2026 04:25:26 +0500
Subject: [PATCH] feat: add ndarray/base/assign-diagonal

---
 .../ndarray/base/assign-diagonal/README.md    | 158 +++++
 .../assign-diagonal/benchmark/benchmark.js    | 297 +++++++++
 .../base/assign-diagonal/docs/repl.txt        |  52 ++
 .../assign-diagonal/docs/types/index.d.ts     |  63 ++
 .../base/assign-diagonal/docs/types/test.ts   |  85 +++
 .../base/assign-diagonal/examples/index.js    |  40 ++
 .../ndarray/base/assign-diagonal/lib/index.js |  51 ++
 .../ndarray/base/assign-diagonal/lib/main.js  |  88 +++
 .../ndarray/base/assign-diagonal/package.json |  65 ++
 .../ndarray/base/assign-diagonal/test/test.js | 587 ++++++++++++++++++
 10 files changed, 1486 insertions(+)
 create mode 100644 lib/node_modules/@stdlib/ndarray/base/assign-diagonal/README.md
 create mode 100644 lib/node_modules/@stdlib/ndarray/base/assign-diagonal/benchmark/benchmark.js
 create mode 100644 lib/node_modules/@stdlib/ndarray/base/assign-diagonal/docs/repl.txt
 create mode 100644 lib/node_modules/@stdlib/ndarray/base/assign-diagonal/docs/types/index.d.ts
 create mode 100644 lib/node_modules/@stdlib/ndarray/base/assign-diagonal/docs/types/test.ts
 create mode 100644 lib/node_modules/@stdlib/ndarray/base/assign-diagonal/examples/index.js
 create mode 100644 lib/node_modules/@stdlib/ndarray/base/assign-diagonal/lib/index.js
 create mode 100644 lib/node_modules/@stdlib/ndarray/base/assign-diagonal/lib/main.js
 create mode 100644 lib/node_modules/@stdlib/ndarray/base/assign-diagonal/package.json
 create mode 100644 lib/node_modules/@stdlib/ndarray/base/assign-diagonal/test/test.js

diff --git a/lib/node_modules/@stdlib/ndarray/base/assign-diagonal/README.md b/lib/node_modules/@stdlib/ndarray/base/assign-diagonal/README.md
new file mode 100644
index 000000000000..0aa4c32050e7
--- /dev/null
+++ b/lib/node_modules/@stdlib/ndarray/base/assign-diagonal/README.md
@@ -0,0 +1,158 @@
+<!--
+
+@license Apache-2.0
+
+Copyright (c) 2026 The Stdlib Authors.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+   http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+
+-->
+
+# assignDiagonal
+
+> Assign elements from a broadcasted input [`ndarray`][@stdlib/ndarray/ctor] to a specified diagonal of an output [`ndarray`][@stdlib/ndarray/ctor].
+
+<section class="intro">
+
+For an `M`-by-`N` matrix `A`, the `k`-th diagonal is defined as
+
+<!-- <equation class="equation" label="eq:diagonal_definition" align="center" raw="D_k = \{\, A_{i,j} : j - i = k \,\}" alt="Definition of the k-th diagonal of a matrix."> -->
+
+```math
+D_k = \{\, A_{i,j} : j - i = k \,\}
+```
+
+<!-- <div class="equation" align="center" data-raw-text="D_k = \{\, A_{i,j} : j - i = k \,\}" data-equation="eq:diagonal_definition">
+    <img src="" alt="Definition of the k-th diagonal of a matrix.">
+    <br>
+</div> -->
+
+<!-- </equation> -->
+
+where `k = 0` corresponds to the main diagonal, `k > 0` corresponds to the super-diagonals (above the main diagonal), and `k < 0` corresponds to the sub-diagonals (below the main diagonal).
+
+</section>
+
+<!-- /.intro -->
+
+<section class="usage">
+
+## Usage
+
+```javascript
+var assignDiagonal = require( '@stdlib/ndarray/base/assign-diagonal' );
+```
+
+#### assignDiagonal( arrays, dims, k )
+
+Assigns elements from a broadcasted input [`ndarray`][@stdlib/ndarray/ctor] to a specified diagonal of an output [`ndarray`][@stdlib/ndarray/ctor].
+
+```javascript
+var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' );
+var zeros = require( '@stdlib/ndarray/zeros' );
+
+var x = scalar2ndarray( 1.0 );
+// returns <ndarray>
+
+var y = zeros( [ 3, 3 ] );
+// returns <ndarray>[ [ 0.0, 0.0, 0.0 ], [ 0.0, 0.0, 0.0 ], [ 0.0, 0.0, 0.0 ] ]
+
+var out = assignDiagonal( [ x, y ], [ 0, 1 ], 0 );
+// returns <ndarray>[ [ 1.0, 0.0, 0.0 ], [ 0.0, 1.0, 0.0 ], [ 0.0, 0.0, 1.0 ] ]
+
+var bool = ( out === y );
+// returns true
+```
+
+The function accepts the following arguments:
+
+-   **arrays**: array-like object containing one input ndarray and one output ndarray.
+-   **dims**: dimension indices defining the plane in which to assign elements to the diagonal.
+-   **k**: diagonal offset.
+
+</section>
+
+<!-- /.usage -->
+
+<section class="notes">
+
+## Notes
+
+-   The order of the dimension indices contained in `dims` matters. The first element specifies the row-like dimension. The second element specifies the column-like dimension.
+-   Each provided dimension index must reside on the interval `[-ndims, ndims-1]`.
+-   The diagonal offset `k` is interpreted as `column - row`. Accordingly, when `k = 0`, the function assigns to the main diagonal; when `k > 0`, the function assigns to a diagonal above the main diagonal; and when `k < 0`, the function assigns to a diagonal below the main diagonal.
+-   The input ndarray must be [broadcast compatible][@stdlib/ndarray/base/broadcast-shapes] with the output ndarray view defined by the specified diagonal.
+-   The function **mutates** the output ndarray in-place.
+
+</section>
+
+<!-- /.notes -->
+
+<section class="examples">
+
+## Examples
+
+<!-- eslint no-undef: "error" -->
+
+```javascript
+var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' );
+var ndarray2array = require( '@stdlib/ndarray/to-array' );
+var zeros = require( '@stdlib/ndarray/zeros' );
+var assignDiagonal = require( '@stdlib/ndarray/base/assign-diagonal' );
+
+// Create a stack of matrices:
+var y = zeros( [ 2, 3, 3 ] );
+console.log( ndarray2array( y ) );
+
+// Assign a scalar to each main diagonal:
+assignDiagonal( [ scalar2ndarray( 1.0 ), y ], [ 1, 2 ], 0 );
+console.log( ndarray2array( y ) );
+
+// Assign a scalar to each super-diagonal:
+assignDiagonal( [ scalar2ndarray( 2.0 ), y ], [ 1, 2 ], 1 );
+console.log( ndarray2array( y ) );
+
+// Assign a scalar to each sub-diagonal:
+assignDiagonal( [ scalar2ndarray( 3.0 ), y ], [ 1, 2 ], -1 );
+console.log( ndarray2array( y ) );
+```
+
+</section>
+
+<!-- /.examples -->
+
+<section class="references">
+
+</section>
+
+<!-- /.references -->
+
+<!-- Section for related `stdlib` packages. Do not manually edit this section, as it is automatically populated. -->
+
+<section class="related">
+
+</section>
+
+<!-- /.related -->
+
+<!-- Section for all links. Make sure to keep an empty line after the `section` element and another before the `/section` close. -->
+
+<section class="links">
+
+[@stdlib/ndarray/ctor]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/ndarray/ctor
+
+[@stdlib/ndarray/base/broadcast-shapes]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/ndarray/base/broadcast-shapes
+
+</section>
+
+<!-- /.links -->
diff --git a/lib/node_modules/@stdlib/ndarray/base/assign-diagonal/benchmark/benchmark.js b/lib/node_modules/@stdlib/ndarray/base/assign-diagonal/benchmark/benchmark.js
new file mode 100644
index 000000000000..b62466f5d49e
--- /dev/null
+++ b/lib/node_modules/@stdlib/ndarray/base/assign-diagonal/benchmark/benchmark.js
@@ -0,0 +1,297 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2026 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*    http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+'use strict';
+
+// MODULES //
+
+var bench = require( '@stdlib/bench' );
+var isndarrayLike = require( '@stdlib/assert/is-ndarray-like' );
+var baseEmpty = require( '@stdlib/ndarray/base/empty' );
+var empty = require( '@stdlib/ndarray/empty' );
+var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' );
+var format = require( '@stdlib/string/format' );
+var pkg = require( './../package.json' ).name;
+var assignDiagonal = require( './../lib' );
+
+
+// MAIN //
+
+bench( format( '%s:ndims=2,ctor=base', pkg ), function benchmark( b ) {
+	var values;
+	var out;
+	var x;
+	var i;
+
+	x = scalar2ndarray( 1.0 );
+
+	values = [
+		baseEmpty( 'float64', [ 2, 2 ], 'row-major' ),
+		baseEmpty( 'float32', [ 2, 2 ], 'row-major' ),
+		baseEmpty( 'int32', [ 2, 2 ], 'row-major' ),
+		baseEmpty( 'complex128', [ 2, 2 ], 'row-major' ),
+		baseEmpty( 'generic', [ 2, 2 ], 'row-major' )
+	];
+
+	b.tic();
+	for ( i = 0; i < b.iterations; i++ ) {
+		out = assignDiagonal( [ x, values[ i%values.length ] ], [ 0, 1 ], 0 );
+		if ( typeof out !== 'object' ) {
+			b.fail( 'should return an ndarray' );
+		}
+	}
+	b.toc();
+	if ( !isndarrayLike( out ) ) {
+		b.fail( 'should return an ndarray' );
+	}
+	b.pass( 'benchmark finished' );
+	b.end();
+});
+
+bench( format( '%s:ndims=2,ctor=non-base', pkg ), function benchmark( b ) {
+	var values;
+	var out;
+	var x;
+	var i;
+
+	x = scalar2ndarray( 1.0 );
+
+	/* eslint-disable object-curly-newline, stdlib/line-closing-bracket-spacing */
+
+	values = [
+		empty( [ 2, 2 ], { 'dtype': 'float64' } ),
+		empty( [ 2, 2 ], { 'dtype': 'float32' } ),
+		empty( [ 2, 2 ], { 'dtype': 'int32' } ),
+		empty( [ 2, 2 ], { 'dtype': 'complex128' } ),
+		empty( [ 2, 2 ], { 'dtype': 'generic' } )
+	];
+
+	/* eslint-enable object-curly-newline, stdlib/line-closing-bracket-spacing */
+
+	b.tic();
+	for ( i = 0; i < b.iterations; i++ ) {
+		out = assignDiagonal( [ x, values[ i%values.length ] ], [ 0, 1 ], 0 );
+		if ( typeof out !== 'object' ) {
+			b.fail( 'should return an ndarray' );
+		}
+	}
+	b.toc();
+	if ( !isndarrayLike( out ) ) {
+		b.fail( 'should return an ndarray' );
+	}
+	b.pass( 'benchmark finished' );
+	b.end();
+});
+
+bench( format( '%s:ndims=3,ctor=base', pkg ), function benchmark( b ) {
+	var values;
+	var out;
+	var x;
+	var i;
+
+	x = scalar2ndarray( 1.0 );
+
+	values = [
+		baseEmpty( 'float64', [ 2, 2, 2 ], 'row-major' ),
+		baseEmpty( 'float32', [ 2, 2, 2 ], 'row-major' ),
+		baseEmpty( 'int32', [ 2, 2, 2 ], 'row-major' ),
+		baseEmpty( 'complex128', [ 2, 2, 2 ], 'row-major' ),
+		baseEmpty( 'generic', [ 2, 2, 2 ], 'row-major' )
+	];
+
+	b.tic();
+	for ( i = 0; i < b.iterations; i++ ) {
+		out = assignDiagonal( [ x, values[ i%values.length ] ], [ 1, 2 ], 0 );
+		if ( typeof out !== 'object' ) {
+			b.fail( 'should return an ndarray' );
+		}
+	}
+	b.toc();
+	if ( !isndarrayLike( out ) ) {
+		b.fail( 'should return an ndarray' );
+	}
+	b.pass( 'benchmark finished' );
+	b.end();
+});
+
+bench( format( '%s:ndims=3,ctor=non-base', pkg ), function benchmark( b ) {
+	var values;
+	var out;
+	var x;
+	var i;
+
+	x = scalar2ndarray( 1.0 );
+
+	/* eslint-disable object-curly-newline, stdlib/line-closing-bracket-spacing */
+
+	values = [
+		empty( [ 2, 2, 2 ], { 'dtype': 'float64' } ),
+		empty( [ 2, 2, 2 ], { 'dtype': 'float32' } ),
+		empty( [ 2, 2, 2 ], { 'dtype': 'int32' } ),
+		empty( [ 2, 2, 2 ], { 'dtype': 'complex128' } ),
+		empty( [ 2, 2, 2 ], { 'dtype': 'generic' } )
+	];
+
+	/* eslint-enable object-curly-newline, stdlib/line-closing-bracket-spacing */
+
+	b.tic();
+	for ( i = 0; i < b.iterations; i++ ) {
+		out = assignDiagonal( [ x, values[ i%values.length ] ], [ 1, 2 ], 0 );
+		if ( typeof out !== 'object' ) {
+			b.fail( 'should return an ndarray' );
+		}
+	}
+	b.toc();
+	if ( !isndarrayLike( out ) ) {
+		b.fail( 'should return an ndarray' );
+	}
+	b.pass( 'benchmark finished' );
+	b.end();
+});
+
+bench( format( '%s:ndims=4,ctor=base', pkg ), function benchmark( b ) {
+	var values;
+	var out;
+	var x;
+	var i;
+
+	x = scalar2ndarray( 1.0 );
+
+	values = [
+		baseEmpty( 'float64', [ 2, 2, 2, 2 ], 'row-major' ),
+		baseEmpty( 'float32', [ 2, 2, 2, 2 ], 'row-major' ),
+		baseEmpty( 'int32', [ 2, 2, 2, 2 ], 'row-major' ),
+		baseEmpty( 'complex128', [ 2, 2, 2, 2 ], 'row-major' ),
+		baseEmpty( 'generic', [ 2, 2, 2, 2 ], 'row-major' )
+	];
+
+	b.tic();
+	for ( i = 0; i < b.iterations; i++ ) {
+		out = assignDiagonal( [ x, values[ i%values.length ] ], [ 2, 3 ], 0 );
+		if ( typeof out !== 'object' ) {
+			b.fail( 'should return an ndarray' );
+		}
+	}
+	b.toc();
+	if ( !isndarrayLike( out ) ) {
+		b.fail( 'should return an ndarray' );
+	}
+	b.pass( 'benchmark finished' );
+	b.end();
+});
+
+bench( format( '%s:ndims=4,ctor=non-base', pkg ), function benchmark( b ) {
+	var values;
+	var out;
+	var x;
+	var i;
+
+	x = scalar2ndarray( 1.0 );
+
+	/* eslint-disable object-curly-newline, stdlib/line-closing-bracket-spacing */
+
+	values = [
+		empty( [ 2, 2, 2, 2 ], { 'dtype': 'float64' } ),
+		empty( [ 2, 2, 2, 2 ], { 'dtype': 'float32' } ),
+		empty( [ 2, 2, 2, 2 ], { 'dtype': 'int32' } ),
+		empty( [ 2, 2, 2, 2 ], { 'dtype': 'complex128' } ),
+		empty( [ 2, 2, 2, 2 ], { 'dtype': 'generic' } )
+	];
+
+	/* eslint-enable object-curly-newline, stdlib/line-closing-bracket-spacing */
+
+	b.tic();
+	for ( i = 0; i < b.iterations; i++ ) {
+		out = assignDiagonal( [ x, values[ i%values.length ] ], [ 2, 3 ], 0 );
+		if ( typeof out !== 'object' ) {
+			b.fail( 'should return an ndarray' );
+		}
+	}
+	b.toc();
+	if ( !isndarrayLike( out ) ) {
+		b.fail( 'should return an ndarray' );
+	}
+	b.pass( 'benchmark finished' );
+	b.end();
+});
+
+bench( format( '%s:ndims=5,ctor=base', pkg ), function benchmark( b ) {
+	var values;
+	var out;
+	var x;
+	var i;
+
+	x = scalar2ndarray( 1.0 );
+
+	values = [
+		baseEmpty( 'float64', [ 2, 2, 2, 2, 2 ], 'row-major' ),
+		baseEmpty( 'float32', [ 2, 2, 2, 2, 2 ], 'row-major' ),
+		baseEmpty( 'int32', [ 2, 2, 2, 2, 2 ], 'row-major' ),
+		baseEmpty( 'complex128', [ 2, 2, 2, 2, 2 ], 'row-major' ),
+		baseEmpty( 'generic', [ 2, 2, 2, 2, 2 ], 'row-major' )
+	];
+
+	b.tic();
+	for ( i = 0; i < b.iterations; i++ ) {
+		out = assignDiagonal( [ x, values[ i%values.length ] ], [ 3, 4 ], 0 );
+		if ( typeof out !== 'object' ) {
+			b.fail( 'should return an ndarray' );
+		}
+	}
+	b.toc();
+	if ( !isndarrayLike( out ) ) {
+		b.fail( 'should return an ndarray' );
+	}
+	b.pass( 'benchmark finished' );
+	b.end();
+});
+
+bench( format( '%s:ndims=5,ctor=non-base', pkg ), function benchmark( b ) {
+	var values;
+	var out;
+	var x;
+	var i;
+
+	x = scalar2ndarray( 1.0 );
+
+	/* eslint-disable object-curly-newline, stdlib/line-closing-bracket-spacing */
+
+	values = [
+		empty( [ 2, 2, 2, 2, 2 ], { 'dtype': 'float64' } ),
+		empty( [ 2, 2, 2, 2, 2 ], { 'dtype': 'float32' } ),
+		empty( [ 2, 2, 2, 2, 2 ], { 'dtype': 'int32' } ),
+		empty( [ 2, 2, 2, 2, 2 ], { 'dtype': 'complex128' } ),
+		empty( [ 2, 2, 2, 2, 2 ], { 'dtype': 'generic' } )
+	];
+
+	/* eslint-enable object-curly-newline, stdlib/line-closing-bracket-spacing */
+
+	b.tic();
+	for ( i = 0; i < b.iterations; i++ ) {
+		out = assignDiagonal( [ x, values[ i%values.length ] ], [ 3, 4 ], 0 );
+		if ( typeof out !== 'object' ) {
+			b.fail( 'should return an ndarray' );
+		}
+	}
+	b.toc();
+	if ( !isndarrayLike( out ) ) {
+		b.fail( 'should return an ndarray' );
+	}
+	b.pass( 'benchmark finished' );
+	b.end();
+});
diff --git a/lib/node_modules/@stdlib/ndarray/base/assign-diagonal/docs/repl.txt b/lib/node_modules/@stdlib/ndarray/base/assign-diagonal/docs/repl.txt
new file mode 100644
index 000000000000..0f3e23b5d2a3
--- /dev/null
+++ b/lib/node_modules/@stdlib/ndarray/base/assign-diagonal/docs/repl.txt
@@ -0,0 +1,52 @@
+
+{{alias}}( arrays, dims, k )
+    Assigns elements from a broadcasted input ndarray to a specified diagonal
+    of an output ndarray.
+
+    The order of the dimension indices contained in `dims` matters. The first
+    element specifies the row-like dimension. The second element specifies the
+    column-like dimension.
+
+    Each provided dimension index must reside on the interval [-ndims, ndims-1].
+
+    The diagonal offset `k` is interpreted as `column - row`. Accordingly, when
+    `k = 0`, the function assigns to the main diagonal; when `k > 0`, the
+    function assigns to a diagonal above the main diagonal; and when `k < 0`,
+    the function assigns to a diagonal below the main diagonal.
+
+    The input ndarray must be broadcast compatible with the output ndarray view
+    defined by the specified diagonal.
+
+    The function mutates the output ndarray in-place.
+
+    Parameters
+    ----------
+    arrays: ArrayLikeObject<ndarray>
+        Array-like object containing one input array and one output array.
+
+    dims: ArrayLikeObject<integer>
+        Dimension indices defining the plane in which to assign elements to
+        the diagonal.
+
+    k: integer
+        Diagonal offset.
+
+    Returns
+    -------
+    out: ndarray
+        Output ndarray.
+
+    Examples
+    --------
+    > var x = {{alias:@stdlib/ndarray/from-scalar}}( 1.0 )
+    <ndarray>
+    > var y = {{alias:@stdlib/ndarray/zeros}}( [ 3, 3 ] )
+    <ndarray>
+    > var out = {{alias}}( [ x, y ], [ 0, 1 ], 0 )
+    <ndarray>[ [ 1.0, 0.0, 0.0 ], [ 0.0, 1.0, 0.0 ], [ 0.0, 0.0, 1.0 ] ]
+    > var bool = ( out === y )
+    true
+
+    See Also
+    --------
+
diff --git a/lib/node_modules/@stdlib/ndarray/base/assign-diagonal/docs/types/index.d.ts b/lib/node_modules/@stdlib/ndarray/base/assign-diagonal/docs/types/index.d.ts
new file mode 100644
index 000000000000..497c8a1ef1d3
--- /dev/null
+++ b/lib/node_modules/@stdlib/ndarray/base/assign-diagonal/docs/types/index.d.ts
@@ -0,0 +1,63 @@
+/*
+* @license Apache-2.0
+*
+* Copyright (c) 2026 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*    http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+// TypeScript Version: 4.1
+
+/// <reference types="@stdlib/types"/>
+
+import { Collection } from '@stdlib/types/array';
+import { ndarray, typedndarray } from '@stdlib/types/ndarray';
+
+/**
+* Assigns elements from a broadcasted input ndarray to a specified diagonal of an output ndarray.
+*
+* ## Notes
+*
+* -   The order of the dimension indices contained in `dims` matters. The first element specifies the row-like dimension. The second element specifies the column-like dimension.
+* -   Each provided dimension index must reside on the interval `[-ndims, ndims-1]`.
+* -   The diagonal offset `k` is interpreted as `column - row`. Accordingly, when `k = 0`, the function assigns to the main diagonal; when `k > 0`, the function assigns to a diagonal above the main diagonal; and when `k < 0`, the function assigns to a diagonal below the main diagonal.
+* -   The input ndarray must be broadcast compatible with the output ndarray view defined by the specified diagonal.
+* -   The function mutates the output ndarray in-place.
+*
+* @param arrays - array-like object containing one input array and one output array
+* @param dims - dimension indices defining the plane in which to assign elements to the diagonal
+* @param k - diagonal offset
+* @returns output ndarray
+*
+* @example
+* var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' );
+* var zeros = require( '@stdlib/ndarray/zeros' );
+*
+* var x = scalar2ndarray( 1.0 );
+* // returns <ndarray>
+*
+* var y = zeros( [ 3, 3 ] );
+* // returns <ndarray>[ [ 0.0, 0.0, 0.0 ], [ 0.0, 0.0, 0.0 ], [ 0.0, 0.0, 0.0 ] ]
+*
+* var out = assignDiagonal( [ x, y ], [ 0, 1 ], 0 );
+* // returns <ndarray>[ [ 1.0, 0.0, 0.0 ], [ 0.0, 1.0, 0.0 ], [ 0.0, 0.0, 1.0 ] ]
+*
+* var bool = ( out === y );
+* // returns true
+*/
+declare function assignDiagonal<T = unknown, U extends typedndarray<T> = typedndarray<T>>( arrays: [ ndarray, U ], dims: Collection<number>, k: number ): U;
+
+
+// EXPORTS //
+
+export = assignDiagonal;
diff --git a/lib/node_modules/@stdlib/ndarray/base/assign-diagonal/docs/types/test.ts b/lib/node_modules/@stdlib/ndarray/base/assign-diagonal/docs/types/test.ts
new file mode 100644
index 000000000000..7337458115b2
--- /dev/null
+++ b/lib/node_modules/@stdlib/ndarray/base/assign-diagonal/docs/types/test.ts
@@ -0,0 +1,85 @@
+/*
+* @license Apache-2.0
+*
+* Copyright (c) 2026 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*    http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+/* eslint-disable space-in-parens */
+
+import scalar2ndarray = require( '@stdlib/ndarray/from-scalar' );
+import zeros = require( '@stdlib/ndarray/zeros' );
+import assignDiagonal = require( './index' );
+
+
+// TESTS //
+
+// The function returns an ndarray...
+{
+	const x = scalar2ndarray( 1.0 );
+	const y = zeros( [ 2, 2 ] );
+
+	assignDiagonal( [ x, y ], [ 0, 1 ], 0 ); // $ExpectType float64ndarray
+}
+
+// The compiler throws an error if the function is not provided a first argument which is an array-like object containing ndarrays...
+{
+	assignDiagonal( '5', [ 0, 1 ], 0 ); // $ExpectError
+	assignDiagonal( 5, [ 0, 1 ], 0 ); // $ExpectError
+	assignDiagonal( true, [ 0, 1 ], 0 ); // $ExpectError
+	assignDiagonal( false, [ 0, 1 ], 0 ); // $ExpectError
+	assignDiagonal( null, [ 0, 1 ], 0 ); // $ExpectError
+	assignDiagonal( {}, [ 0, 1 ], 0 ); // $ExpectError
+	assignDiagonal( ( x: number ): number => x, [ 0, 1 ], 0 ); // $ExpectError
+}
+
+// The compiler throws an error if the function is not provided a second argument which is an array-like object containing numbers...
+{
+	const x = scalar2ndarray( 1.0 );
+	const y = zeros( [ 2, 2 ] );
+
+	assignDiagonal( [ x, y ], '5', 0 ); // $ExpectError
+	assignDiagonal( [ x, y ], 5, 0 ); // $ExpectError
+	assignDiagonal( [ x, y ], true, 0 ); // $ExpectError
+	assignDiagonal( [ x, y ], false, 0 ); // $ExpectError
+	assignDiagonal( [ x, y ], null, 0 ); // $ExpectError
+	assignDiagonal( [ x, y ], {}, 0 ); // $ExpectError
+	assignDiagonal( [ x, y ], [ '5' ], 0 ); // $ExpectError
+	assignDiagonal( [ x, y ], ( x: number ): number => x, 0 ); // $ExpectError
+}
+
+// The compiler throws an error if the function is not provided a third argument which is a number...
+{
+	const x = scalar2ndarray( 1.0 );
+	const y = zeros( [ 2, 2 ] );
+
+	assignDiagonal( [ x, y ], [ 0, 1 ], '5' ); // $ExpectError
+	assignDiagonal( [ x, y ], [ 0, 1 ], true ); // $ExpectError
+	assignDiagonal( [ x, y ], [ 0, 1 ], false ); // $ExpectError
+	assignDiagonal( [ x, y ], [ 0, 1 ], null ); // $ExpectError
+	assignDiagonal( [ x, y ], [ 0, 1 ], {} ); // $ExpectError
+	assignDiagonal( [ x, y ], [ 0, 1 ], [] ); // $ExpectError
+	assignDiagonal( [ x, y ], [ 0, 1 ], ( x: number ): number => x ); // $ExpectError
+}
+
+// The compiler throws an error if the function is provided an unsupported number of arguments...
+{
+	const x = scalar2ndarray( 1.0 );
+	const y = zeros( [ 2, 2 ] );
+
+	assignDiagonal(); // $ExpectError
+	assignDiagonal( [ x, y ] ); // $ExpectError
+	assignDiagonal( [ x, y ], [ 0, 1 ] ); // $ExpectError
+	assignDiagonal( [ x, y ], [ 0, 1 ], 0, {} ); // $ExpectError
+}
diff --git a/lib/node_modules/@stdlib/ndarray/base/assign-diagonal/examples/index.js b/lib/node_modules/@stdlib/ndarray/base/assign-diagonal/examples/index.js
new file mode 100644
index 000000000000..5e889a112cc8
--- /dev/null
+++ b/lib/node_modules/@stdlib/ndarray/base/assign-diagonal/examples/index.js
@@ -0,0 +1,40 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2026 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*    http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+'use strict';
+
+var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' );
+var ndarray2array = require( '@stdlib/ndarray/to-array' );
+var zeros = require( '@stdlib/ndarray/zeros' );
+var assignDiagonal = require( './../lib' );
+
+// Create a stack of matrices:
+var y = zeros( [ 2, 3, 3 ] );
+console.log( ndarray2array( y ) );
+
+// Assign a scalar to each main diagonal:
+assignDiagonal( [ scalar2ndarray( 1.0 ), y ], [ 1, 2 ], 0 );
+console.log( ndarray2array( y ) );
+
+// Assign a scalar to each super-diagonal:
+assignDiagonal( [ scalar2ndarray( 2.0 ), y ], [ 1, 2 ], 1 );
+console.log( ndarray2array( y ) );
+
+// Assign a scalar to each sub-diagonal:
+assignDiagonal( [ scalar2ndarray( 3.0 ), y ], [ 1, 2 ], -1 );
+console.log( ndarray2array( y ) );
diff --git a/lib/node_modules/@stdlib/ndarray/base/assign-diagonal/lib/index.js b/lib/node_modules/@stdlib/ndarray/base/assign-diagonal/lib/index.js
new file mode 100644
index 000000000000..976c185770f1
--- /dev/null
+++ b/lib/node_modules/@stdlib/ndarray/base/assign-diagonal/lib/index.js
@@ -0,0 +1,51 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2026 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*    http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+'use strict';
+
+/**
+* Assign elements from a broadcasted input ndarray to a specified diagonal of an output ndarray.
+*
+* @module @stdlib/ndarray/base/assign-diagonal
+*
+* @example
+* var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' );
+* var zeros = require( '@stdlib/ndarray/zeros' );
+* var assignDiagonal = require( '@stdlib/ndarray/base/assign-diagonal' );
+*
+* var x = scalar2ndarray( 1.0 );
+* // returns <ndarray>
+*
+* var y = zeros( [ 3, 3 ] );
+* // returns <ndarray>[ [ 0.0, 0.0, 0.0 ], [ 0.0, 0.0, 0.0 ], [ 0.0, 0.0, 0.0 ] ]
+*
+* var out = assignDiagonal( [ x, y ], [ 0, 1 ], 0 );
+* // returns <ndarray>[ [ 1.0, 0.0, 0.0 ], [ 0.0, 1.0, 0.0 ], [ 0.0, 0.0, 1.0 ] ]
+*
+* var bool = ( out === y );
+* // returns true
+*/
+
+// MODULES //
+
+var main = require( './main.js' );
+
+
+// EXPORTS //
+
+module.exports = main;
diff --git a/lib/node_modules/@stdlib/ndarray/base/assign-diagonal/lib/main.js b/lib/node_modules/@stdlib/ndarray/base/assign-diagonal/lib/main.js
new file mode 100644
index 000000000000..7830ea38f4ed
--- /dev/null
+++ b/lib/node_modules/@stdlib/ndarray/base/assign-diagonal/lib/main.js
@@ -0,0 +1,88 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2026 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*    http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+'use strict';
+
+// MODULES //
+
+var broadcast = require( '@stdlib/ndarray/base/broadcast-array' );
+var diagonal = require( '@stdlib/ndarray/base/diagonal' );
+var getShape = require( '@stdlib/ndarray/base/shape' );
+var assign = require( '@stdlib/ndarray/base/assign' );
+
+
+// MAIN //
+
+/**
+* Assigns elements from a broadcasted input ndarray to a specified diagonal of an output ndarray.
+*
+* ## Notes
+*
+* -   The order of the dimension indices contained in `dims` matters. The first element specifies the row-like dimension. The second element specifies the column-like dimension.
+* -   Each provided dimension index must reside on the interval `[-ndims, ndims-1]`.
+* -   The diagonal offset `k` is interpreted as `column - row`. Accordingly, when `k = 0`, the function assigns to the main diagonal; when `k > 0`, the function assigns to a diagonal above the main diagonal; and when `k < 0`, the function assigns to a diagonal below the main diagonal.
+* -   The input ndarray must be broadcast compatible with the output ndarray view defined by the specified diagonal.
+* -   The function mutates the output ndarray in-place.
+*
+* @param {ArrayLikeObject<ndarray>} arrays - array-like object containing one input array and one output array
+* @param {IntegerArray} dims - dimension indices defining the plane in which to assign elements to the diagonal
+* @param {integer} k - diagonal offset
+* @throws {RangeError} must provide exactly two dimension indices
+* @throws {RangeError} output ndarray must have at least two dimensions
+* @throws {RangeError} must provide valid dimension indices
+* @throws {Error} must provide unique dimension indices
+* @throws {Error} input ndarray must be broadcast compatible with the output ndarray diagonal view
+* @returns {ndarray} output ndarray
+*
+* @example
+* var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' );
+* var zeros = require( '@stdlib/ndarray/zeros' );
+*
+* var x = scalar2ndarray( 1.0 );
+* // returns <ndarray>
+*
+* var y = zeros( [ 3, 3 ] );
+* // returns <ndarray>[ [ 0.0, 0.0, 0.0 ], [ 0.0, 0.0, 0.0 ], [ 0.0, 0.0, 0.0 ] ]
+*
+* var out = assignDiagonal( [ x, y ], [ 0, 1 ], 0 );
+* // returns <ndarray>[ [ 1.0, 0.0, 0.0 ], [ 0.0, 1.0, 0.0 ], [ 0.0, 0.0, 1.0 ] ]
+*
+* var bool = ( out === y );
+* // returns true
+*/
+function assignDiagonal( arrays, dims, k ) {
+	var view;
+	var x;
+
+	// Resolve a writable output array view of the specified diagonal:
+	view = diagonal( arrays[ 1 ], dims, k, true );
+
+	// Broadcast the input array to the diagonal view shape:
+	x = broadcast( arrays[ 0 ], getShape( view, true ) );
+
+	// Assign elements from the broadcasted input array to the output array view:
+	assign( [ x, view ] );
+
+	// Return the original output ndarray:
+	return arrays[ 1 ];
+}
+
+
+// EXPORTS //
+
+module.exports = assignDiagonal;
diff --git a/lib/node_modules/@stdlib/ndarray/base/assign-diagonal/package.json b/lib/node_modules/@stdlib/ndarray/base/assign-diagonal/package.json
new file mode 100644
index 000000000000..14f2f63f6693
--- /dev/null
+++ b/lib/node_modules/@stdlib/ndarray/base/assign-diagonal/package.json
@@ -0,0 +1,65 @@
+{
+  "name": "@stdlib/ndarray/base/assign-diagonal",
+  "version": "0.0.0",
+  "description": "Assign elements from a broadcasted input ndarray to a specified diagonal of an output ndarray.",
+  "license": "Apache-2.0",
+  "author": {
+    "name": "The Stdlib Authors",
+    "url": "https://github.com/stdlib-js/stdlib/graphs/contributors"
+  },
+  "contributors": [
+    {
+      "name": "The Stdlib Authors",
+      "url": "https://github.com/stdlib-js/stdlib/graphs/contributors"
+    }
+  ],
+  "main": "./lib",
+  "directories": {
+    "benchmark": "./benchmark",
+    "doc": "./docs",
+    "example": "./examples",
+    "lib": "./lib",
+    "test": "./test"
+  },
+  "types": "./docs/types",
+  "scripts": {},
+  "homepage": "https://github.com/stdlib-js/stdlib",
+  "repository": {
+    "type": "git",
+    "url": "git://github.com/stdlib-js/stdlib.git"
+  },
+  "bugs": {
+    "url": "https://github.com/stdlib-js/stdlib/issues"
+  },
+  "dependencies": {},
+  "devDependencies": {},
+  "engines": {
+    "node": ">=0.10.0",
+    "npm": ">2.7.0"
+  },
+  "os": [
+    "aix",
+    "darwin",
+    "freebsd",
+    "linux",
+    "macos",
+    "openbsd",
+    "sunos",
+    "win32",
+    "windows"
+  ],
+  "keywords": [
+    "stdlib",
+    "stdtypes",
+    "types",
+    "base",
+    "data",
+    "structure",
+    "ndarray",
+    "diagonal",
+    "assign",
+    "broadcast",
+    "matrix",
+    "stack"
+  ]
+}
diff --git a/lib/node_modules/@stdlib/ndarray/base/assign-diagonal/test/test.js b/lib/node_modules/@stdlib/ndarray/base/assign-diagonal/test/test.js
new file mode 100644
index 000000000000..e15120cf8f9c
--- /dev/null
+++ b/lib/node_modules/@stdlib/ndarray/base/assign-diagonal/test/test.js
@@ -0,0 +1,587 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2026 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*    http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+'use strict';
+
+// MODULES //
+
+var tape = require( 'tape' );
+var Float64Array = require( '@stdlib/array/float64' );
+var Complex128Array = require( '@stdlib/array/complex128' );
+var Complex128 = require( '@stdlib/complex/float64/ctor' );
+var isSameComplex128Array = require( '@stdlib/assert/is-same-complex128array' );
+var array = require( '@stdlib/ndarray/array' );
+var ndarray = require( '@stdlib/ndarray/base/ctor' );
+var ndarray2array = require( '@stdlib/ndarray/to-array' );
+var zeros = require( '@stdlib/ndarray/base/zeros' );
+var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' );
+var getData = require( '@stdlib/ndarray/data-buffer' );
+var assignDiagonal = require( './../lib' );
+
+
+// TESTS //
+
+tape( 'main export is a function', function test( t ) {
+	t.ok( true, __filename );
+	t.strictEqual( typeof assignDiagonal, 'function', 'main export is a function' );
+	t.end();
+});
+
+tape( 'the function throws an error if not provided exactly two dimension indices', function test( t ) {
+	var values;
+	var x;
+	var y;
+	var i;
+
+	x = scalar2ndarray( 1.0 );
+	y = new ndarray( 'float64', new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] ), [ 2, 2 ], [ 2, 1 ], 0, 'row-major' );
+
+	values = [
+		[],
+		[ 0 ],
+		[ 0, 1, 0 ],
+		[ 0, 1, 0, 1 ]
+	];
+	for ( i = 0; i < values.length; i++ ) {
+		t.throws( badValue( values[ i ] ), RangeError, 'throws an error when provided ' + values[ i ].length + ' dimension indices' );
+	}
+	t.end();
+
+	function badValue( dims ) {
+		return function badValue() {
+			assignDiagonal( [ x, y ], dims, 0 );
+		};
+	}
+});
+
+tape( 'the function throws an error if provided an output ndarray with fewer than two dimensions', function test( t ) {
+	var values;
+	var x;
+	var i;
+
+	x = scalar2ndarray( 1.0 );
+
+	values = [
+		new ndarray( 'float64', new Float64Array( [ 5.0 ] ), [], [ 0 ], 0, 'row-major' ),
+		new ndarray( 'float64', new Float64Array( [ 1.0, 2.0, 3.0 ] ), [ 3 ], [ 1 ], 0, 'row-major' )
+	];
+	for ( i = 0; i < values.length; i++ ) {
+		t.throws( badValue( values[ i ] ), RangeError, 'throws an error when provided an output ndarray with ' + values[ i ].ndims + ' dimensions' );
+	}
+	t.end();
+
+	function badValue( y ) {
+		return function badValue() {
+			assignDiagonal( [ x, y ], [ 0, 1 ], 0 );
+		};
+	}
+});
+
+tape( 'the function throws an error if provided out-of-bounds dimension indices', function test( t ) {
+	var values;
+	var x;
+	var y;
+	var i;
+
+	x = scalar2ndarray( 1.0 );
+	y = new ndarray( 'float64', new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] ), [ 2, 2 ], [ 2, 1 ], 0, 'row-major' );
+
+	values = [
+		[ 0, 2 ],
+		[ 2, 0 ],
+		[ -3, 0 ],
+		[ 0, -3 ],
+		[ 10, 0 ],
+		[ 0, 10 ]
+	];
+	for ( i = 0; i < values.length; i++ ) {
+		t.throws( badValue( values[ i ] ), RangeError, 'throws an error when provided dimension indices [' + values[ i ] + ']' );
+	}
+	t.end();
+
+	function badValue( dims ) {
+		return function badValue() {
+			assignDiagonal( [ x, y ], dims, 0 );
+		};
+	}
+});
+
+tape( 'the function throws an error if provided duplicate dimension indices', function test( t ) {
+	var values;
+	var x;
+	var y;
+	var i;
+
+	x = scalar2ndarray( 1.0 );
+	y = new ndarray( 'float64', new Float64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] ), [ 2, 2, 2 ], [ 4, 2, 1 ], 0, 'row-major' );
+
+	values = [
+		[ 0, 0 ],
+		[ 1, 1 ],
+		[ 2, 2 ],
+		[ 0, -3 ],
+		[ -2, 1 ],
+		[ -1, 2 ]
+	];
+	for ( i = 0; i < values.length; i++ ) {
+		t.throws( badValue( values[ i ] ), Error, 'throws an error when provided dimension indices [' + values[ i ] + ']' );
+	}
+	t.end();
+
+	function badValue( dims ) {
+		return function badValue() {
+			assignDiagonal( [ x, y ], dims, 0 );
+		};
+	}
+});
+
+tape( 'the function throws an error if provided an input ndarray which is not broadcast compatible with the output ndarray diagonal view', function test( t ) {
+	var values;
+	var y;
+	var i;
+
+	y = zeros( 'float64', [ 3, 3 ], 'row-major' );
+
+	values = [
+		array( [ 1.0, 2.0, 3.0, 4.0 ] ),
+		array( [ [ 1.0, 2.0, 3.0 ] ] ),
+		array( [ [ 1.0, 2.0, 3.0 ], [ 4.0, 5.0, 6.0 ] ] )
+	];
+	for ( i = 0; i < values.length; i++ ) {
+		t.throws( badValue( values[ i ] ), Error, 'throws an error when provided an input ndarray having shape [' + values[ i ].shape.join( ',' ) + ']' );
+	}
+	t.end();
+
+	function badValue( x ) {
+		return function badValue() {
+			assignDiagonal( [ x, y ], [ 0, 1 ], 0 );
+		};
+	}
+});
+
+tape( 'the function assigns a broadcasted scalar to the main diagonal of a square matrix', function test( t ) {
+	var expected;
+	var out;
+	var x;
+	var y;
+
+	x = scalar2ndarray( 1.0 );
+	y = zeros( 'float64', [ 3, 3 ], 'row-major' );
+
+	out = assignDiagonal( [ x, y ], [ 0, 1 ], 0 );
+
+	expected = [ [ 1.0, 0.0, 0.0 ], [ 0.0, 1.0, 0.0 ], [ 0.0, 0.0, 1.0 ] ];
+
+	t.deepEqual( ndarray2array( out ), expected, 'returns expected value' );
+	t.strictEqual( out, y, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function assigns a vector to the main diagonal of a square matrix', function test( t ) {
+	var expected;
+	var out;
+	var x;
+	var y;
+
+	x = array( [ 1.0, 2.0, 3.0 ] );
+	y = zeros( 'float64', [ 3, 3 ], 'row-major' );
+
+	out = assignDiagonal( [ x, y ], [ 0, 1 ], 0 );
+
+	expected = [ [ 1.0, 0.0, 0.0 ], [ 0.0, 2.0, 0.0 ], [ 0.0, 0.0, 3.0 ] ];
+
+	t.deepEqual( ndarray2array( out ), expected, 'returns expected value' );
+	t.strictEqual( out, y, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function assigns to the super-diagonal of a square matrix', function test( t ) {
+	var expected;
+	var out;
+	var x;
+	var y;
+
+	x = array( [ 1.0, 2.0 ] );
+	y = zeros( 'float64', [ 3, 3 ], 'row-major' );
+
+	out = assignDiagonal( [ x, y ], [ 0, 1 ], 1 );
+
+	expected = [ [ 0.0, 1.0, 0.0 ], [ 0.0, 0.0, 2.0 ], [ 0.0, 0.0, 0.0 ] ];
+
+	t.deepEqual( ndarray2array( out ), expected, 'returns expected value' );
+
+	x = array( [ 7.0 ] );
+	y = zeros( 'float64', [ 3, 3 ], 'row-major' );
+
+	out = assignDiagonal( [ x, y ], [ 0, 1 ], 2 );
+
+	expected = [ [ 0.0, 0.0, 7.0 ], [ 0.0, 0.0, 0.0 ], [ 0.0, 0.0, 0.0 ] ];
+
+	t.deepEqual( ndarray2array( out ), expected, 'returns expected value' );
+	t.strictEqual( out, y, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function assigns to the sub-diagonal of a square matrix', function test( t ) {
+	var expected;
+	var out;
+	var x;
+	var y;
+
+	x = array( [ 1.0, 2.0 ] );
+	y = zeros( 'float64', [ 3, 3 ], 'row-major' );
+
+	out = assignDiagonal( [ x, y ], [ 0, 1 ], -1 );
+
+	expected = [ [ 0.0, 0.0, 0.0 ], [ 1.0, 0.0, 0.0 ], [ 0.0, 2.0, 0.0 ] ];
+
+	t.deepEqual( ndarray2array( out ), expected, 'returns expected value' );
+
+	x = scalar2ndarray( 7.0 );
+	y = zeros( 'float64', [ 3, 3 ], 'row-major' );
+
+	out = assignDiagonal( [ x, y ], [ 0, 1 ], -2 );
+
+	expected = [ [ 0.0, 0.0, 0.0 ], [ 0.0, 0.0, 0.0 ], [ 7.0, 0.0, 0.0 ] ];
+
+	t.deepEqual( ndarray2array( out ), expected, 'returns expected value' );
+	t.strictEqual( out, y, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function assigns to the diagonal of a non-square matrix (M < N)', function test( t ) {
+	var expected;
+	var out;
+	var x;
+	var y;
+
+	x = scalar2ndarray( 1.0 );
+	y = zeros( 'float64', [ 2, 4 ], 'row-major' );
+
+	out = assignDiagonal( [ x, y ], [ 0, 1 ], 0 );
+
+	expected = [ [ 1.0, 0.0, 0.0, 0.0 ], [ 0.0, 1.0, 0.0, 0.0 ] ];
+
+	t.deepEqual( ndarray2array( out ), expected, 'returns expected value' );
+	t.strictEqual( out, y, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function assigns to the diagonal of a non-square matrix (M > N)', function test( t ) {
+	var expected;
+	var out;
+	var x;
+	var y;
+
+	x = scalar2ndarray( 1.0 );
+	y = zeros( 'float64', [ 4, 2 ], 'row-major' );
+
+	out = assignDiagonal( [ x, y ], [ 0, 1 ], 0 );
+
+	expected = [ [ 1.0, 0.0 ], [ 0.0, 1.0 ], [ 0.0, 0.0 ], [ 0.0, 0.0 ] ];
+
+	t.deepEqual( ndarray2array( out ), expected, 'returns expected value' );
+	t.strictEqual( out, y, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function returns the output ndarray unchanged when the diagonal offset is out-of-bounds', function test( t ) {
+	var expected;
+	var out;
+	var x;
+	var y;
+
+	x = scalar2ndarray( -1.0 );
+	y = array( [ [ 1.0, 2.0, 3.0 ], [ 4.0, 5.0, 6.0 ], [ 7.0, 8.0, 9.0 ] ] );
+
+	out = assignDiagonal( [ x, y ], [ 0, 1 ], 3 );
+
+	expected = [ [ 1.0, 2.0, 3.0 ], [ 4.0, 5.0, 6.0 ], [ 7.0, 8.0, 9.0 ] ];
+
+	t.deepEqual( ndarray2array( out ), expected, 'returns expected value' );
+	t.strictEqual( out, y, 'returns expected value' );
+
+	out = assignDiagonal( [ x, y ], [ 0, 1 ], -3 );
+
+	t.deepEqual( ndarray2array( out ), expected, 'returns expected value' );
+	t.strictEqual( out, y, 'returns expected value' );
+
+	out = assignDiagonal( [ x, y ], [ 0, 1 ], 100 );
+
+	t.deepEqual( ndarray2array( out ), expected, 'returns expected value' );
+	t.strictEqual( out, y, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function swaps the row-like and column-like dimensions when `dims` is reversed', function test( t ) {
+	var expected;
+	var out;
+	var x;
+	var y;
+
+	x = scalar2ndarray( 1.0 );
+	y = zeros( 'float64', [ 3, 3 ], 'row-major' );
+
+	out = assignDiagonal( [ x, y ], [ 1, 0 ], 1 );
+
+	expected = [ [ 0.0, 0.0, 0.0 ], [ 1.0, 0.0, 0.0 ], [ 0.0, 1.0, 0.0 ] ];
+
+	t.deepEqual( ndarray2array( out ), expected, 'returns expected value' );
+
+	y = zeros( 'float64', [ 3, 3 ], 'row-major' );
+
+	out = assignDiagonal( [ x, y ], [ 1, 0 ], -1 );
+
+	expected = [ [ 0.0, 1.0, 0.0 ], [ 0.0, 0.0, 1.0 ], [ 0.0, 0.0, 0.0 ] ];
+
+	t.deepEqual( ndarray2array( out ), expected, 'returns expected value' );
+	t.strictEqual( out, y, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function assigns to the diagonals of a stack of matrices', function test( t ) {
+	var expected;
+	var out;
+	var x;
+	var y;
+
+	x = scalar2ndarray( 1.0 );
+	y = zeros( 'float64', [ 2, 2, 2 ], 'row-major' );
+
+	out = assignDiagonal( [ x, y ], [ 1, 2 ], 0 );
+
+	expected = [
+		[ [ 1.0, 0.0 ], [ 0.0, 1.0 ] ],
+		[ [ 1.0, 0.0 ], [ 0.0, 1.0 ] ]
+	];
+
+	t.deepEqual( ndarray2array( out ), expected, 'returns expected value' );
+	t.strictEqual( out, y, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function broadcasts a per-stack diagonal vector across a stack of matrices', function test( t ) {
+	var expected;
+	var out;
+	var x;
+	var y;
+
+	x = array( [ 1.0, 2.0 ] );
+	y = zeros( 'float64', [ 3, 2, 2 ], 'row-major' );
+
+	out = assignDiagonal( [ x, y ], [ 1, 2 ], 0 );
+
+	expected = [
+		[ [ 1.0, 0.0 ], [ 0.0, 2.0 ] ],
+		[ [ 1.0, 0.0 ], [ 0.0, 2.0 ] ],
+		[ [ 1.0, 0.0 ], [ 0.0, 2.0 ] ]
+	];
+
+	t.deepEqual( ndarray2array( out ), expected, 'returns expected value' );
+	t.strictEqual( out, y, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function assigns to the diagonal when `dims` selects non-adjacent dimensions', function test( t ) {
+	var expected;
+	var out;
+	var x;
+	var y;
+
+	x = scalar2ndarray( 1.0 );
+	y = zeros( 'float64', [ 2, 2, 3 ], 'row-major' );
+
+	out = assignDiagonal( [ x, y ], [ 0, 2 ], 0 );
+
+	expected = [
+		[ [ 1.0, 0.0, 0.0 ], [ 1.0, 0.0, 0.0 ] ],
+		[ [ 0.0, 1.0, 0.0 ], [ 0.0, 1.0, 0.0 ] ]
+	];
+
+	t.deepEqual( ndarray2array( out ), expected, 'returns expected value' );
+	t.strictEqual( out, y, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function supports output ndarrays having a non-zero buffer offset', function test( t ) {
+	var expected;
+	var buf;
+	var out;
+	var x;
+	var y;
+
+	buf = [ -1.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];
+	y = new ndarray( 'generic', buf, [ 3, 3 ], [ 3, 1 ], 1, 'row-major' );
+	x = scalar2ndarray( 1.0 );
+
+	out = assignDiagonal( [ x, y ], [ 0, 1 ], 0 );
+
+	expected = [ [ 1.0, 0.0, 0.0 ], [ 0.0, 1.0, 0.0 ], [ 0.0, 0.0, 1.0 ] ];
+
+	t.deepEqual( ndarray2array( out ), expected, 'returns expected value' );
+	t.strictEqual( buf[ 0 ], -1.0, 'returns expected value' );
+	t.strictEqual( out, y, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function normalizes negative dimension indices', function test( t ) {
+	var expected;
+	var out;
+	var x;
+	var y;
+
+	x = scalar2ndarray( 1.0 );
+	y = zeros( 'float64', [ 3, 3 ], 'row-major' );
+
+	out = assignDiagonal( [ x, y ], [ -2, -1 ], 0 );
+
+	expected = [ [ 1.0, 0.0, 0.0 ], [ 0.0, 1.0, 0.0 ], [ 0.0, 0.0, 1.0 ] ];
+
+	t.deepEqual( ndarray2array( out ), expected, 'returns expected value' );
+	t.strictEqual( out, y, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function supports column-major output ndarrays', function test( t ) {
+	var expected;
+	var out;
+	var x;
+	var y;
+
+	x = scalar2ndarray( 1.0 );
+	y = zeros( 'float64', [ 3, 3 ], 'column-major' );
+
+	out = assignDiagonal( [ x, y ], [ 0, 1 ], 0 );
+
+	expected = [ [ 1.0, 0.0, 0.0 ], [ 0.0, 1.0, 0.0 ], [ 0.0, 0.0, 1.0 ] ];
+
+	t.deepEqual( ndarray2array( out ), expected, 'returns expected value' );
+	t.strictEqual( out, y, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function assigns to non-trailing dimensions of higher-dimensional ndarrays', function test( t ) {
+	var expected;
+	var out;
+	var x;
+	var y;
+
+	x = scalar2ndarray( 1.0 );
+	y = zeros( 'float64', [ 2, 3, 2 ], 'row-major' );
+
+	out = assignDiagonal( [ x, y ], [ 0, 1 ], 0 );
+
+	expected = [
+		[
+			[ 1.0, 1.0 ],
+			[ 0.0, 0.0 ],
+			[ 0.0, 0.0 ]
+		],
+		[
+			[ 0.0, 0.0 ],
+			[ 1.0, 1.0 ],
+			[ 0.0, 0.0 ]
+		]
+	];
+
+	t.deepEqual( ndarray2array( out ), expected, 'returns expected value' );
+	t.strictEqual( out, y, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function supports negative dimension indices combined with a non-zero `k`', function test( t ) {
+	var expected;
+	var out;
+	var x;
+	var y;
+
+	x = scalar2ndarray( 1.0 );
+	y = zeros( 'float64', [ 3, 3 ], 'row-major' );
+
+	out = assignDiagonal( [ x, y ], [ -2, -1 ], 1 );
+
+	expected = [ [ 0.0, 1.0, 0.0 ], [ 0.0, 0.0, 1.0 ], [ 0.0, 0.0, 0.0 ] ];
+
+	t.deepEqual( ndarray2array( out ), expected, 'returns expected value' );
+
+	y = zeros( 'float64', [ 3, 3 ], 'row-major' );
+
+	out = assignDiagonal( [ x, y ], [ -2, -1 ], -1 );
+
+	expected = [ [ 0.0, 0.0, 0.0 ], [ 1.0, 0.0, 0.0 ], [ 0.0, 1.0, 0.0 ] ];
+
+	t.deepEqual( ndarray2array( out ), expected, 'returns expected value' );
+	t.strictEqual( out, y, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function assigns to the diagonal of a complex128 ndarray', function test( t ) {
+	var expected;
+	var out;
+	var x;
+	var y;
+
+	x = scalar2ndarray( new Complex128( 1.0, 2.0 ), {
+		'dtype': 'complex128'
+	});
+	y = zeros( 'complex128', [ 3, 3 ], 'row-major' );
+
+	out = assignDiagonal( [ x, y ], [ 0, 1 ], 0 );
+
+	expected = new Complex128Array([
+		1.0,
+		2.0,
+		0.0,
+		0.0,
+		0.0,
+		0.0,
+		0.0,
+		0.0,
+		1.0,
+		2.0,
+		0.0,
+		0.0,
+		0.0,
+		0.0,
+		0.0,
+		0.0,
+		1.0,
+		2.0
+	]);
+
+	t.strictEqual( isSameComplex128Array( getData( out ), expected ), true, 'returns expected value' );
+	t.strictEqual( out, y, 'returns expected value' );
+
+	t.end();
+});