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 @@
+
+
+# assignDiagonal
+
+> Assign elements from a broadcasted input [`ndarray`][@stdlib/ndarray/ctor] to a specified diagonal of an output [`ndarray`][@stdlib/ndarray/ctor].
+
+
+
+For an `M`-by-`N` matrix `A`, the `k`-th diagonal is defined as
+
+
+
+```math
+D_k = \{\, A_{i,j} : j - i = k \,\}
+```
+
+
+
+
+
+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).
+
+
+
+
+
+
+
+## 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
+
+var y = zeros( [ 3, 3 ] );
+// returns [ [ 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 [ [ 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.
+
+
+
+
+
+
+
+## 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.
+
+
+
+
+
+
+
+## Examples
+
+
+
+```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 ) );
+```
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+[@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
+
+
+
+
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
+ Array-like object containing one input array and one output array.
+
+ dims: ArrayLikeObject
+ 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 )
+
+ > var y = {{alias:@stdlib/ndarray/zeros}}( [ 3, 3 ] )
+
+ > var out = {{alias}}( [ x, y ], [ 0, 1 ], 0 )
+ [ [ 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
+
+///
+
+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
+*
+* var y = zeros( [ 3, 3 ] );
+* // returns [ [ 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 [ [ 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 = typedndarray>( arrays: [ ndarray, U ], dims: Collection, 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
+*
+* var y = zeros( [ 3, 3 ] );
+* // returns [ [ 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 [ [ 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} 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
+*
+* var y = zeros( [ 3, 3 ] );
+* // returns [ [ 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 [ [ 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();
+});