diff --git a/lib/node_modules/@stdlib/ndarray/base/diagonal/README.md b/lib/node_modules/@stdlib/ndarray/base/diagonal/README.md
new file mode 100644
index 000000000000..907883006d4e
--- /dev/null
+++ b/lib/node_modules/@stdlib/ndarray/base/diagonal/README.md
@@ -0,0 +1,164 @@
+
+
+# diagonal
+
+> Return a view of the diagonal of a matrix (or stack of matrices).
+
+
+
+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). For example, given the matrix
+
+
+
+```math
+A = \begin{bmatrix} a_{0,0} & a_{0,1} & a_{0,2} \\ a_{1,0} & a_{1,1} & a_{1,2} \\ a_{2,0} & a_{2,1} & a_{2,2} \end{bmatrix}
+```
+
+
+
+
+
+the main diagonal is `[ a_{0,0}, a_{1,1}, a_{2,2} ]`, the super-diagonal `k = 1` is `[ a_{0,1}, a_{1,2} ]`, and the sub-diagonal `k = -1` is `[ a_{1,0}, a_{2,1} ]`.
+
+
+
+
+
+
+
+## Usage
+
+```javascript
+var diagonal = require( '@stdlib/ndarray/base/diagonal' );
+```
+
+#### diagonal( x, dims, k, writable )
+
+Returns a view of the diagonal of a matrix (or stack of matrices) `x`.
+
+```javascript
+var array = require( '@stdlib/ndarray/array' );
+
+var x = array( [ [ 1.0, 2.0, 3.0 ], [ 4.0, 5.0, 6.0 ], [ 7.0, 8.0, 9.0 ] ] );
+// returns [ [ 1.0, 2.0, 3.0 ], [ 4.0, 5.0, 6.0 ], [ 7.0, 8.0, 9.0 ] ]
+
+var y = diagonal( x, [ 0, 1 ], 0, false );
+// returns [ 1.0, 5.0, 9.0 ]
+```
+
+The function accepts the following arguments:
+
+- **x**: input ndarray.
+- **dims**: dimension indices defining the plane from which to extract the diagonal.
+- **k**: diagonal offset.
+- **writable**: boolean indicating whether the returned ndarray should be writable.
+
+
+
+
+
+
+
+## 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 returns the main diagonal; when `k > 0`, the function returns the diagonal above the main diagonal; and when `k < 0`, the function returns the diagonal below the main diagonal.
+- The returned ndarray is a **view** of the input ndarray. Accordingly, writing to the original ndarray will **mutate** the returned ndarray and vice versa.
+- The `writable` parameter **only** applies to ndarray constructors supporting **read-only** instances.
+
+
+
+
+
+
+
+## Examples
+
+
+
+```javascript
+var uniform = require( '@stdlib/random/uniform' );
+var ndarray2array = require( '@stdlib/ndarray/to-array' );
+var diagonal = require( '@stdlib/ndarray/base/diagonal' );
+
+// Create a stack of matrices:
+var x = uniform( [ 2, 3, 3 ], -10.0, 10.0, {
+ 'dtype': 'float64'
+});
+console.log( ndarray2array( x ) );
+
+// Extract the main diagonals from the stack:
+var y = diagonal( x, [ 1, 2 ], 0, false );
+console.log( ndarray2array( y ) );
+
+// Extract super-diagonals from the stack:
+y = diagonal( x, [ 1, 2 ], 1, false );
+console.log( ndarray2array( y ) );
+
+// Extract sub-diagonals from the stack:
+y = diagonal( x, [ 1, 2 ], -1, false );
+console.log( ndarray2array( y ) );
+```
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
diff --git a/lib/node_modules/@stdlib/ndarray/base/diagonal/benchmark/benchmark.js b/lib/node_modules/@stdlib/ndarray/base/diagonal/benchmark/benchmark.js
new file mode 100644
index 000000000000..7eafaa6c0539
--- /dev/null
+++ b/lib/node_modules/@stdlib/ndarray/base/diagonal/benchmark/benchmark.js
@@ -0,0 +1,272 @@
+/**
+* @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 format = require( '@stdlib/string/format' );
+var pkg = require( './../package.json' ).name;
+var diagonal = require( './../lib' );
+
+
+// MAIN //
+
+bench( format( '%s::ndims=2,ctor=base', pkg ), function benchmark( b ) {
+ var values;
+ var v;
+ var i;
+
+ 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++ ) {
+ v = diagonal( values[ i%values.length ], [ 0, 1 ], 0, false );
+ if ( typeof v !== 'object' ) {
+ b.fail( 'should return an ndarray' );
+ }
+ }
+ b.toc();
+ if ( !isndarrayLike( v ) ) {
+ 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 v;
+ var i;
+
+ /* 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++ ) {
+ v = diagonal( values[ i%values.length ], [ 0, 1 ], 0, false );
+ if ( typeof v !== 'object' ) {
+ b.fail( 'should return an ndarray' );
+ }
+ }
+ b.toc();
+ if ( !isndarrayLike( v ) ) {
+ 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 v;
+ var i;
+
+ 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++ ) {
+ v = diagonal( values[ i%values.length ], [ 1, 2 ], 0, false );
+ if ( typeof v !== 'object' ) {
+ b.fail( 'should return an ndarray' );
+ }
+ }
+ b.toc();
+ if ( !isndarrayLike( v ) ) {
+ 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 v;
+ var i;
+
+ /* 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++ ) {
+ v = diagonal( values[ i%values.length ], [ 1, 2 ], 0, false );
+ if ( typeof v !== 'object' ) {
+ b.fail( 'should return an ndarray' );
+ }
+ }
+ b.toc();
+ if ( !isndarrayLike( v ) ) {
+ 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 v;
+ var i;
+
+ 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++ ) {
+ v = diagonal( values[ i%values.length ], [ 2, 3 ], 0, false );
+ if ( typeof v !== 'object' ) {
+ b.fail( 'should return an ndarray' );
+ }
+ }
+ b.toc();
+ if ( !isndarrayLike( v ) ) {
+ 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 v;
+ var i;
+
+ /* 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++ ) {
+ v = diagonal( values[ i%values.length ], [ 2, 3 ], 0, false );
+ if ( typeof v !== 'object' ) {
+ b.fail( 'should return an ndarray' );
+ }
+ }
+ b.toc();
+ if ( !isndarrayLike( v ) ) {
+ 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 v;
+ var i;
+
+ 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++ ) {
+ v = diagonal( values[ i%values.length ], [ 3, 4 ], 0, false );
+ if ( typeof v !== 'object' ) {
+ b.fail( 'should return an ndarray' );
+ }
+ }
+ b.toc();
+ if ( !isndarrayLike( v ) ) {
+ 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 v;
+ var i;
+
+ /* 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++ ) {
+ v = diagonal( values[ i%values.length ], [ 3, 4 ], 0, false );
+ if ( typeof v !== 'object' ) {
+ b.fail( 'should return an ndarray' );
+ }
+ }
+ b.toc();
+ if ( !isndarrayLike( v ) ) {
+ b.fail( 'should return an ndarray' );
+ }
+ b.pass( 'benchmark finished' );
+ b.end();
+});
diff --git a/lib/node_modules/@stdlib/ndarray/base/diagonal/docs/repl.txt b/lib/node_modules/@stdlib/ndarray/base/diagonal/docs/repl.txt
new file mode 100644
index 000000000000..da74ae936a20
--- /dev/null
+++ b/lib/node_modules/@stdlib/ndarray/base/diagonal/docs/repl.txt
@@ -0,0 +1,51 @@
+
+{{alias}}( x, dims, k, writable )
+ Returns a view of the diagonal of a matrix (or stack of matrices).
+
+ 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 returns the main diagonal; when `k > 0`, the
+ function returns the diagonal above the main diagonal; and when `k < 0`,
+ the function returns the diagonal below the main diagonal.
+
+ The returned ndarray is a *view* of the input ndarray. Accordingly,
+ writing to the original ndarray will mutate the returned ndarray and
+ vice versa.
+
+ The `writable` parameter only applies to ndarray constructors supporting
+ read-only instances.
+
+ Parameters
+ ----------
+ x: ndarray
+ Input array.
+
+ dims: ArrayLikeObject
+ Dimension indices defining the plane from which to extract the diagonal.
+
+ k: integer
+ Diagonal offset.
+
+ writable: boolean
+ Boolean indicating whether the returned ndarray should be writable.
+
+ Returns
+ -------
+ out: ndarray
+ Output array view.
+
+ Examples
+ --------
+ > var x = {{alias:@stdlib/ndarray/array}}( [ [ 1.0, 2.0 ], [ 3.0, 4.0 ] ] )
+ [ [ 1.0, 2.0 ], [ 3.0, 4.0 ] ]
+ > var y = {{alias}}( x, [ 0, 1 ], 0, false )
+ [ 1.0, 4.0 ]
+
+ See Also
+ --------
+
diff --git a/lib/node_modules/@stdlib/ndarray/base/diagonal/docs/types/index.d.ts b/lib/node_modules/@stdlib/ndarray/base/diagonal/docs/types/index.d.ts
new file mode 100644
index 000000000000..2232ced6dfcf
--- /dev/null
+++ b/lib/node_modules/@stdlib/ndarray/base/diagonal/docs/types/index.d.ts
@@ -0,0 +1,57 @@
+/*
+* @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 { typedndarray } from '@stdlib/types/ndarray';
+
+/**
+* Returns a view of the diagonal of a matrix (or stack of matrices).
+*
+* ## 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 returns the main diagonal; when `k > 0`, the function returns the diagonal above the main diagonal; and when `k < 0`, the function returns the diagonal below the main diagonal.
+* - The returned ndarray is a **view** of the input ndarray. Accordingly, writing to the original ndarray will **mutate** the returned ndarray and vice versa.
+* - The `writable` parameter **only** applies to ndarray constructors supporting **read-only** instances.
+*
+* @param x - input array
+* @param dims - dimension indices defining the plane from which to extract the diagonal
+* @param k - diagonal offset
+* @param writable - boolean indicating whether the returned ndarray should be writable
+* @returns ndarray view
+*
+* @example
+* var array = require( '@stdlib/ndarray/array' );
+*
+* var x = array( [ [ 1.0, 2.0, 3.0 ], [ 4.0, 5.0, 6.0 ], [ 7.0, 8.0, 9.0 ] ] );
+* // returns [ [ 1.0, 2.0, 3.0 ], [ 4.0, 5.0, 6.0 ], [ 7.0, 8.0, 9.0 ] ]
+*
+* var y = diagonal( x, [ 0, 1 ], 0, false );
+* // returns [ 1.0, 5.0, 9.0 ]
+*/
+declare function diagonal = typedndarray>( x: U, dims: Collection, k: number, writable: boolean ): U;
+
+
+// EXPORTS //
+
+export = diagonal;
diff --git a/lib/node_modules/@stdlib/ndarray/base/diagonal/docs/types/test.ts b/lib/node_modules/@stdlib/ndarray/base/diagonal/docs/types/test.ts
new file mode 100644
index 000000000000..017275efe4db
--- /dev/null
+++ b/lib/node_modules/@stdlib/ndarray/base/diagonal/docs/types/test.ts
@@ -0,0 +1,92 @@
+/*
+* @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.
+*/
+
+import zeros = require( '@stdlib/ndarray/zeros' );
+import diagonal = require( './index' );
+
+
+// TESTS //
+
+// The function returns an ndarray...
+{
+ const x = zeros( [ 2, 2 ] );
+
+ diagonal( x, [ 0, 1 ], 0, false ); // $ExpectType float64ndarray
+}
+
+// The compiler throws an error if the function is not provided a first argument which is an ndarray...
+{
+ diagonal( '5', [ 0, 1 ], 0, false ); // $ExpectError
+ diagonal( 5, [ 0, 1 ], 0, false ); // $ExpectError
+ diagonal( true, [ 0, 1 ], 0, false ); // $ExpectError
+ diagonal( false, [ 0, 1 ], 0, false ); // $ExpectError
+ diagonal( null, [ 0, 1 ], 0, false ); // $ExpectError
+ diagonal( {}, [ 0, 1 ], 0, false ); // $ExpectError
+ diagonal( [ '5' ], [ 0, 1 ], 0, false ); // $ExpectError
+ diagonal( ( x: number ): number => x, [ 0, 1 ], 0, false ); // $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 = zeros( [ 2, 2 ] );
+
+ diagonal( x, '5', 0, false ); // $ExpectError
+ diagonal( x, 5, 0, false ); // $ExpectError
+ diagonal( x, true, 0, false ); // $ExpectError
+ diagonal( x, false, 0, false ); // $ExpectError
+ diagonal( x, null, 0, false ); // $ExpectError
+ diagonal( x, {}, 0, false ); // $ExpectError
+ diagonal( x, [ '5' ], 0, false ); // $ExpectError
+ diagonal( x, ( x: number ): number => x, 0, false ); // $ExpectError
+}
+
+// The compiler throws an error if the function is not provided a third argument which is a number...
+{
+ const x = zeros( [ 2, 2 ] );
+
+ diagonal( x, [ 0, 1 ], '5', false ); // $ExpectError
+ diagonal( x, [ 0, 1 ], true, false ); // $ExpectError
+ diagonal( x, [ 0, 1 ], false, false ); // $ExpectError
+ diagonal( x, [ 0, 1 ], null, false ); // $ExpectError
+ diagonal( x, [ 0, 1 ], {}, false ); // $ExpectError
+ diagonal( x, [ 0, 1 ], [], false ); // $ExpectError
+ diagonal( x, [ 0, 1 ], ( x: number ): number => x, false ); // $ExpectError
+}
+
+// The compiler throws an error if the function is not provided a fourth argument which is a boolean...
+{
+ const x = zeros( [ 2, 2 ] );
+
+ diagonal( x, [ 0, 1 ], 0, '5' ); // $ExpectError
+ diagonal( x, [ 0, 1 ], 0, 5 ); // $ExpectError
+ diagonal( x, [ 0, 1 ], 0, null ); // $ExpectError
+ diagonal( x, [ 0, 1 ], 0, {} ); // $ExpectError
+ diagonal( x, [ 0, 1 ], 0, [] ); // $ExpectError
+ diagonal( x, [ 0, 1 ], 0, ( x: number ): number => x ); // $ExpectError
+}
+
+// The compiler throws an error if the function is provided an unsupported number of arguments...
+{
+ const x = zeros( [ 2, 2 ] );
+
+ diagonal(); // $ExpectError
+ diagonal( x ); // $ExpectError
+ diagonal( x, [ 0, 1 ] ); // $ExpectError
+ diagonal( x, [ 0, 1 ], 0 ); // $ExpectError
+ diagonal( x, [ 0, 1 ], 0, false, {} ); // $ExpectError
+}
diff --git a/lib/node_modules/@stdlib/ndarray/base/diagonal/examples/index.js b/lib/node_modules/@stdlib/ndarray/base/diagonal/examples/index.js
new file mode 100644
index 000000000000..e8983375b6e5
--- /dev/null
+++ b/lib/node_modules/@stdlib/ndarray/base/diagonal/examples/index.js
@@ -0,0 +1,41 @@
+/**
+* @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 uniform = require( '@stdlib/random/uniform' );
+var ndarray2array = require( '@stdlib/ndarray/to-array' );
+var diagonal = require( './../lib' );
+
+// Create a stack of matrices:
+var x = uniform( [ 2, 3, 3 ], -10.0, 10.0, {
+ 'dtype': 'float64'
+});
+console.log( ndarray2array( x ) );
+
+// Extract the main diagonals from the stack:
+var y = diagonal( x, [ 1, 2 ], 0, false );
+console.log( ndarray2array( y ) );
+
+// Extract super-diagonals from the stack:
+y = diagonal( x, [ 1, 2 ], 1, false );
+console.log( ndarray2array( y ) );
+
+// Extract sub-diagonals from the stack:
+y = diagonal( x, [ 1, 2 ], -1, false );
+console.log( ndarray2array( y ) );
diff --git a/lib/node_modules/@stdlib/ndarray/base/diagonal/lib/index.js b/lib/node_modules/@stdlib/ndarray/base/diagonal/lib/index.js
new file mode 100644
index 000000000000..bbd5a1f5735b
--- /dev/null
+++ b/lib/node_modules/@stdlib/ndarray/base/diagonal/lib/index.js
@@ -0,0 +1,44 @@
+/**
+* @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';
+
+/**
+* Return a view of the diagonal of a matrix (or stack of matrices).
+*
+* @module @stdlib/ndarray/base/diagonal
+*
+* @example
+* var array = require( '@stdlib/ndarray/array' );
+* var diagonal = require( '@stdlib/ndarray/base/diagonal' );
+*
+* var x = array( [ [ 1.0, 2.0, 3.0 ], [ 4.0, 5.0, 6.0 ], [ 7.0, 8.0, 9.0 ] ] );
+* // returns [ [ 1.0, 2.0, 3.0 ], [ 4.0, 5.0, 6.0 ], [ 7.0, 8.0, 9.0 ] ]
+*
+* var y = diagonal( x, [ 0, 1 ], 0, false );
+* // returns [ 1.0, 5.0, 9.0 ]
+*/
+
+// MODULES //
+
+var main = require( './main.js' );
+
+
+// EXPORTS //
+
+module.exports = main;
diff --git a/lib/node_modules/@stdlib/ndarray/base/diagonal/lib/main.js b/lib/node_modules/@stdlib/ndarray/base/diagonal/lib/main.js
new file mode 100644
index 000000000000..fdcd57efcbf8
--- /dev/null
+++ b/lib/node_modules/@stdlib/ndarray/base/diagonal/lib/main.js
@@ -0,0 +1,144 @@
+/**
+* @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 toUniqueNormalizedIndices = require( '@stdlib/ndarray/base/to-unique-normalized-indices' );
+var getDType = require( '@stdlib/ndarray/base/dtype' );
+var getShape = require( '@stdlib/ndarray/base/shape' );
+var getStrides = require( '@stdlib/ndarray/base/strides' );
+var getOffset = require( '@stdlib/ndarray/base/offset' );
+var getOrder = require( '@stdlib/ndarray/base/order' );
+var getData = require( '@stdlib/ndarray/base/data-buffer' );
+var join = require( '@stdlib/array/base/join' );
+var min = require( '@stdlib/math/base/special/min' );
+var format = require( '@stdlib/string/format' );
+
+
+// MAIN //
+
+/**
+* Returns a view of the diagonal of a matrix (or stack of matrices).
+*
+* ## 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 returns the main diagonal; when `k > 0`, the function returns the diagonal above the main diagonal; and when `k < 0`, the function returns the diagonal below the main diagonal.
+* - The returned ndarray is a **view** of the input ndarray. Accordingly, writing to the original ndarray will **mutate** the returned ndarray and vice versa.
+* - The `writable` parameter **only** applies to ndarray constructors supporting **read-only** instances.
+*
+* @param {ndarray} x - input array
+* @param {IntegerArray} dims - dimension indices defining the plane from which to extract the diagonal
+* @param {integer} k - diagonal offset
+* @param {boolean} writable - boolean indicating whether the returned ndarray should be writable
+* @throws {RangeError} must provide exactly two dimension indices
+* @throws {RangeError} input ndarray must have at least two dimensions
+* @throws {RangeError} must provide valid dimension indices
+* @throws {Error} must provide unique dimension indices
+* @returns {ndarray} ndarray view
+*
+* @example
+* var array = require( '@stdlib/ndarray/array' );
+*
+* var x = array( [ [ 1.0, 2.0, 3.0 ], [ 4.0, 5.0, 6.0 ], [ 7.0, 8.0, 9.0 ] ] );
+* // returns [ [ 1.0, 2.0, 3.0 ], [ 4.0, 5.0, 6.0 ], [ 7.0, 8.0, 9.0 ] ]
+*
+* var y = diagonal( x, [ 0, 1 ], 0, false );
+* // returns [ 1.0, 5.0, 9.0 ]
+*/
+function diagonal( x, dims, k, writable ) {
+ var strides;
+ var offset;
+ var ndims;
+ var shape;
+ var rows;
+ var cols;
+ var sh;
+ var st;
+ var sr;
+ var sc;
+ var ro;
+ var co;
+ var d;
+ var L;
+ var i;
+
+ if ( dims.length !== 2 ) {
+ throw new RangeError( format( 'invalid argument. Must provide exactly two dimension indices. Value: `[%s]`.', join( dims, ', ' ) ) );
+ }
+ sh = getShape( x );
+ ndims = sh.length;
+ if ( ndims < 2 ) {
+ throw new RangeError( format( 'invalid argument. First argument must be an ndarray having at least two dimensions. Number of dimensions: %d.', ndims ) );
+ }
+ st = getStrides( x );
+
+ // Resolve dimension indices...
+ d = toUniqueNormalizedIndices( dims, ndims-1 );
+ if ( d === null ) {
+ throw new RangeError( format( 'invalid argument. Specified dimension index is out-of-bounds. Must be on the interval: [-%u, %u]. Value: `[%s]`.', ndims, ndims-1, join( dims, ', ' ) ) );
+ }
+ if ( d.length !== dims.length ) {
+ throw new Error( format( 'invalid argument. Must provide unique dimension indices. Value: `[%s]`.', join( dims, ', ' ) ) );
+ }
+ sr = st[ d[0] ];
+ sc = st[ d[1] ];
+
+ // Resolve the row and column offsets corresponding to the diagonal offset `k = column - row`:
+ co = ( k > 0 ) ? k : 0;
+ ro = co - k;
+
+ // Compute the length of the diagonal:
+ rows = sh[ d[0] ] - ro;
+ cols = sh[ d[1] ] - co;
+ L = min( rows, cols );
+ if ( L < 0 ) {
+ L = 0;
+ }
+
+ // Adjust the offset so that we point to the first element along the specified diagonal:
+ offset = getOffset( x );
+ if ( L > 0 ) {
+ offset += ( co*sc ) + ( ro*sr );
+ }
+
+ // Drop the specified dimensions and append the diagonal dimension:
+ shape = [];
+ strides = [];
+ for ( i = 0; i < ndims; i++ ) {
+ if ( i === d[0] || i === d[1] ) {
+ continue;
+ }
+ shape.push( sh[ i ] );
+ strides.push( st[ i ] );
+ }
+ shape.push( L );
+ strides.push( sr + sc );
+
+ return new x.constructor( getDType( x ), getData( x ), shape, strides, offset, getOrder( x ), { // eslint-disable-line max-len
+ 'readonly': !writable
+ });
+}
+
+
+// EXPORTS //
+
+module.exports = diagonal;
diff --git a/lib/node_modules/@stdlib/ndarray/base/diagonal/package.json b/lib/node_modules/@stdlib/ndarray/base/diagonal/package.json
new file mode 100644
index 000000000000..b8dd826a0f34
--- /dev/null
+++ b/lib/node_modules/@stdlib/ndarray/base/diagonal/package.json
@@ -0,0 +1,64 @@
+{
+ "name": "@stdlib/ndarray/base/diagonal",
+ "version": "0.0.0",
+ "description": "Return a view of the diagonal of a matrix (or stack of matrices).",
+ "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",
+ "matrix",
+ "stack",
+ "view"
+ ]
+}
diff --git a/lib/node_modules/@stdlib/ndarray/base/diagonal/test/test.js b/lib/node_modules/@stdlib/ndarray/base/diagonal/test/test.js
new file mode 100644
index 000000000000..bc05c4633aed
--- /dev/null
+++ b/lib/node_modules/@stdlib/ndarray/base/diagonal/test/test.js
@@ -0,0 +1,619 @@
+/**
+* @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 array = require( '@stdlib/ndarray/array' );
+var ndarray = require( '@stdlib/ndarray/base/ctor' );
+var ndarray2array = require( '@stdlib/ndarray/to-array' );
+var getShape = require( '@stdlib/ndarray/shape' );
+var getStrides = require( '@stdlib/ndarray/strides' );
+var getStride = require( '@stdlib/ndarray/stride' );
+var getOffset = require( '@stdlib/ndarray/offset' );
+var getData = require( '@stdlib/ndarray/data-buffer' );
+var getOrder = require( '@stdlib/ndarray/order' );
+var isReadOnly = require( '@stdlib/ndarray/base/assert/is-read-only' );
+var diagonal = require( './../lib' );
+
+
+// TESTS //
+
+tape( 'main export is a function', function test( t ) {
+ t.ok( true, __filename );
+ t.strictEqual( typeof diagonal, '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 i;
+
+ x = new ndarray( 'float64', new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] ), [ 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() {
+ diagonal( x, dims, 0, false );
+ };
+ }
+});
+
+tape( 'the function throws an error if provided an input ndarray with fewer than two dimensions', function test( t ) {
+ var values;
+ var i;
+
+ 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 input ndarray with '+values[ i ].ndims+' dimensions' );
+ }
+ t.end();
+
+ function badValue( x ) {
+ return function badValue() {
+ diagonal( x, [ 0, 1 ], 0, false );
+ };
+ }
+});
+
+tape( 'the function throws an error if provided out-of-bounds dimension indices', function test( t ) {
+ var values;
+ var x;
+ var i;
+
+ x = new ndarray( 'float64', new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] ), [ 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() {
+ diagonal( x, dims, 0, false );
+ };
+ }
+});
+
+tape( 'the function throws an error if provided duplicate dimension indices', function test( t ) {
+ var values;
+ var x;
+ var i;
+
+ x = new ndarray( 'float64', new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] ), [ 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() {
+ diagonal( x, dims, 0, false );
+ };
+ }
+});
+
+tape( 'the function returns a view of the main diagonal of a square matrix', function test( t ) {
+ var expected;
+ var x;
+ var y;
+
+ x = array( [ [ 1, 2, 3 ], [ 4, 5, 6 ], [ 7, 8, 9 ] ] );
+
+ y = diagonal( x, [ 0, 1 ], 0, false );
+
+ expected = [ 3 ];
+ t.deepEqual( getShape( y ), expected, 'returns expected value' );
+
+ expected = [ 1, 5, 9 ];
+ t.deepEqual( ndarray2array( y ), expected, 'returns expected value' );
+
+ t.strictEqual( getData( y ), getData( x ), 'returns expected value' );
+
+ t.end();
+});
+
+tape( 'the function returns a view of the super-diagonal of a square matrix', function test( t ) {
+ var expected;
+ var x;
+ var y;
+
+ x = array( [ [ 1, 2, 3 ], [ 4, 5, 6 ], [ 7, 8, 9 ] ] );
+
+ y = diagonal( x, [ 0, 1 ], 1, false );
+
+ expected = [ 2 ];
+ t.deepEqual( getShape( y ), expected, 'returns expected value' );
+
+ expected = [ 2, 6 ];
+ t.deepEqual( ndarray2array( y ), expected, 'returns expected value' );
+
+ y = diagonal( x, [ 0, 1 ], 2, false );
+
+ expected = [ 1 ];
+ t.deepEqual( getShape( y ), expected, 'returns expected value' );
+
+ expected = [ 3 ];
+ t.deepEqual( ndarray2array( y ), expected, 'returns expected value' );
+
+ t.end();
+});
+
+tape( 'the function returns a view of the sub-diagonal of a square matrix', function test( t ) {
+ var expected;
+ var x;
+ var y;
+
+ x = array( [ [ 1, 2, 3 ], [ 4, 5, 6 ], [ 7, 8, 9 ] ] );
+
+ y = diagonal( x, [ 0, 1 ], -1, false );
+
+ expected = [ 2 ];
+ t.deepEqual( getShape( y ), expected, 'returns expected value' );
+
+ expected = [ 4, 8 ];
+ t.deepEqual( ndarray2array( y ), expected, 'returns expected value' );
+
+ y = diagonal( x, [ 0, 1 ], -2, false );
+
+ expected = [ 1 ];
+ t.deepEqual( getShape( y ), expected, 'returns expected value' );
+
+ expected = [ 7 ];
+ t.deepEqual( ndarray2array( y ), expected, 'returns expected value' );
+
+ t.end();
+});
+
+tape( 'the function returns a view of the diagonal of a non-square matrix (M < N)', function test( t ) {
+ var expected;
+ var x;
+ var y;
+
+ x = array( [ [ 1, 2, 3, 4 ], [ 5, 6, 7, 8 ] ] );
+
+ y = diagonal( x, [ 0, 1 ], 0, false );
+
+ expected = [ 2 ];
+ t.deepEqual( getShape( y ), expected, 'returns expected value' );
+
+ expected = [ 1, 6 ];
+ t.deepEqual( ndarray2array( y ), expected, 'returns expected value' );
+
+ y = diagonal( x, [ 0, 1 ], 2, false );
+
+ expected = [ 2 ];
+ t.deepEqual( getShape( y ), expected, 'returns expected value' );
+
+ expected = [ 3, 8 ];
+ t.deepEqual( ndarray2array( y ), expected, 'returns expected value' );
+
+ y = diagonal( x, [ 0, 1 ], -1, false );
+
+ expected = [ 1 ];
+ t.deepEqual( getShape( y ), expected, 'returns expected value' );
+
+ expected = [ 5 ];
+ t.deepEqual( ndarray2array( y ), expected, 'returns expected value' );
+
+ t.end();
+});
+
+tape( 'the function returns a view of the diagonal of a non-square matrix (M > N)', function test( t ) {
+ var expected;
+ var x;
+ var y;
+
+ x = array( [ [ 1, 2 ], [ 3, 4 ], [ 5, 6 ], [ 7, 8 ] ] );
+
+ y = diagonal( x, [ 0, 1 ], 0, false );
+
+ expected = [ 2 ];
+ t.deepEqual( getShape( y ), expected, 'returns expected value' );
+
+ expected = [ 1, 4 ];
+ t.deepEqual( ndarray2array( y ), expected, 'returns expected value' );
+
+ y = diagonal( x, [ 0, 1 ], -2, false );
+
+ expected = [ 2 ];
+ t.deepEqual( getShape( y ), expected, 'returns expected value' );
+
+ expected = [ 5, 8 ];
+ t.deepEqual( ndarray2array( y ), expected, 'returns expected value' );
+
+ y = diagonal( x, [ 0, 1 ], 1, false );
+
+ expected = [ 1 ];
+ t.deepEqual( getShape( y ), expected, 'returns expected value' );
+
+ expected = [ 2 ];
+ t.deepEqual( ndarray2array( y ), expected, 'returns expected value' );
+
+ t.end();
+});
+
+tape( 'the function returns an empty view when the diagonal offset is out-of-bounds', function test( t ) {
+ var expected;
+ var x;
+ var y;
+
+ x = array( [ [ 1, 2, 3 ], [ 4, 5, 6 ], [ 7, 8, 9 ] ] );
+
+ y = diagonal( x, [ 0, 1 ], 3, false );
+
+ expected = [ 0 ];
+ t.deepEqual( getShape( y ), expected, 'returns expected value' );
+
+ expected = [];
+ t.deepEqual( ndarray2array( y ), expected, 'returns expected value' );
+
+ y = diagonal( x, [ 0, 1 ], -3, false );
+
+ expected = [ 0 ];
+ t.deepEqual( getShape( y ), expected, 'returns expected value' );
+
+ expected = [];
+ t.deepEqual( ndarray2array( y ), expected, 'returns expected value' );
+
+ y = diagonal( x, [ 0, 1 ], 100, false );
+
+ expected = [ 0 ];
+ t.deepEqual( getShape( y ), expected, 'returns expected value' );
+
+ expected = [];
+ t.deepEqual( ndarray2array( y ), expected, '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 x;
+ var y;
+
+ x = array( [ [ 1, 2, 3 ], [ 4, 5, 6 ], [ 7, 8, 9 ] ] );
+
+ y = diagonal( x, [ 1, 0 ], 1, false );
+
+ expected = [ 2 ];
+ t.deepEqual( getShape( y ), expected, 'returns expected value' );
+
+ expected = [ 4, 8 ];
+ t.deepEqual( ndarray2array( y ), expected, 'returns expected value' );
+
+ y = diagonal( x, [ 1, 0 ], -1, false );
+
+ expected = [ 2 ];
+ t.deepEqual( getShape( y ), expected, 'returns expected value' );
+
+ expected = [ 2, 6 ];
+ t.deepEqual( ndarray2array( y ), expected, 'returns expected value' );
+
+ t.end();
+});
+
+tape( 'the function returns a view of the diagonals of a stack of matrices', function test( t ) {
+ var expected;
+ var x;
+ var y;
+
+ x = array( [ [ [ 1, 2 ], [ 3, 4 ] ], [ [ 5, 6 ], [ 7, 8 ] ] ] );
+
+ y = diagonal( x, [ 1, 2 ], 0, false );
+
+ expected = [ 2, 2 ];
+ t.deepEqual( getShape( y ), expected, 'returns expected value' );
+
+ expected = [ [ 1, 4 ], [ 5, 8 ] ];
+ t.deepEqual( ndarray2array( y ), expected, 'returns expected value' );
+
+ y = diagonal( x, [ 1, 2 ], 1, false );
+
+ expected = [ 2, 1 ];
+ t.deepEqual( getShape( y ), expected, 'returns expected value' );
+
+ expected = [ [ 2 ], [ 6 ] ];
+ t.deepEqual( ndarray2array( y ), expected, 'returns expected value' );
+
+ y = diagonal( x, [ 1, 2 ], -1, false );
+
+ expected = [ 2, 1 ];
+ t.deepEqual( getShape( y ), expected, 'returns expected value' );
+
+ expected = [ [ 3 ], [ 7 ] ];
+ t.deepEqual( ndarray2array( y ), expected, 'returns expected value' );
+
+ t.end();
+});
+
+tape( 'the function appends the diagonal dimension as the trailing dimension of the output ndarray', function test( t ) {
+ var expected;
+ var x;
+ var y;
+
+ x = array( [ [ [ 1, 2, 3 ], [ 4, 5, 6 ] ], [ [ 7, 8, 9 ], [ 10, 11, 12 ] ] ] );
+
+ y = diagonal( x, [ 0, 2 ], 0, false );
+
+ expected = [ 2, 2 ];
+ t.deepEqual( getShape( y ), expected, 'returns expected value' );
+
+ expected = [ [ 1, 8 ], [ 4, 11 ] ];
+ t.deepEqual( ndarray2array( y ), expected, 'returns expected value' );
+
+ t.end();
+});
+
+tape( 'the function normalizes negative dimension indices', function test( t ) {
+ var expected;
+ var x;
+ var y;
+
+ x = array( [ [ 1, 2, 3 ], [ 4, 5, 6 ], [ 7, 8, 9 ] ] );
+
+ y = diagonal( x, [ -2, -1 ], 0, false );
+
+ expected = [ 3 ];
+ t.deepEqual( getShape( y ), expected, 'returns expected value' );
+
+ expected = [ 1, 5, 9 ];
+ t.deepEqual( ndarray2array( y ), expected, 'returns expected value' );
+
+ t.end();
+});
+
+tape( 'the function returns a column-major ndarray when the input ndarray is column-major', function test( t ) {
+ var expected;
+ var x;
+ var y;
+
+ x = ndarray( 'generic', [ 1, 4, 7, 2, 5, 8, 3, 6, 9 ], [ 3, 3 ], [ 1, 3 ], 0, 'column-major' );
+
+ y = diagonal( x, [ 0, 1 ], 0, false );
+
+ expected = 'column-major';
+ t.strictEqual( getOrder( y ), expected, 'returns expected value' );
+
+ expected = [ 3 ];
+ t.deepEqual( getShape( y ), expected, 'returns expected value' );
+
+ expected = [ 1, 5, 9 ];
+ t.deepEqual( ndarray2array( y ), expected, 'returns expected value' );
+
+ t.end();
+});
+
+tape( 'the function returns a writable ndarray when `writable` is `true`', function test( t ) {
+ var x;
+ var y;
+
+ x = array( [ [ 1, 2, 3 ], [ 4, 5, 6 ], [ 7, 8, 9 ] ] );
+ y = diagonal( x, [ 0, 1 ], 0, true );
+
+ t.strictEqual( isReadOnly( y ), false, 'returns expected value' );
+ t.strictEqual( getData( y ), getData( x ), 'returns expected value' );
+
+ t.end();
+});
+
+tape( 'the function returns a read-only ndarray when `writable` is `false`', function test( t ) {
+ var x;
+ var y;
+
+ x = array( [ [ 1, 2, 3 ], [ 4, 5, 6 ], [ 7, 8, 9 ] ] );
+ y = diagonal( x, [ 0, 1 ], 0, false );
+
+ t.strictEqual( isReadOnly( y ), true, 'returns expected value' );
+
+ t.end();
+});
+
+tape( 'the function constructs the output by retaining all dimensions except the specified dimensions and appending the diagonal dimension', function test( t ) {
+ var expected;
+ var x;
+ var y;
+
+ x = array( [ 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12 ], {
+ 'shape': [ 3, 2, 2 ]
+ });
+
+ y = diagonal( x, [ 1, 2 ], 0, false );
+
+ expected = [ 3, 2 ];
+ t.deepEqual( getShape( y ), expected, 'returns expected value' );
+
+ expected = [ 4, 3 ];
+ t.deepEqual( getStrides( y ), expected, 'returns expected value' );
+
+ expected = getOffset( x );
+ t.strictEqual( getOffset( y ), expected, 'returns expected value' );
+
+ t.end();
+});
+
+tape( 'the function adjusts the offset to point to the first element of the requested diagonal', function test( t ) {
+ var expected;
+ var x;
+ var y;
+
+ x = array( [ [ 1, 2, 3 ], [ 4, 5, 6 ], [ 7, 8, 9 ] ] );
+
+ y = diagonal( x, [ 0, 1 ], 1, false );
+
+ expected = getOffset( x ) + getStride( x, 1 );
+ t.strictEqual( getOffset( y ), expected, 'returns expected value' );
+
+ y = diagonal( x, [ 0, 1 ], -1, false );
+
+ expected = getOffset( x ) + getStride( x, 0 );
+ t.strictEqual( getOffset( y ), expected, 'returns expected value' );
+
+ t.end();
+});
+
+tape( 'the function supports input ndarrays having a non-zero buffer offset', function test( t ) {
+ var expected;
+ var x;
+ var y;
+
+ x = ndarray( 'generic', [ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9 ], [ 3, 3 ], [ 3, 1 ], 1, 'row-major' );
+
+ y = diagonal( x, [ 0, 1 ], 0, false );
+
+ expected = [ 3 ];
+ t.deepEqual( getShape( y ), expected, 'returns expected value' );
+
+ expected = [ 1, 5, 9 ];
+ t.deepEqual( ndarray2array( y ), expected, 'returns expected value' );
+
+ t.strictEqual( getData( y ), getData( x ), 'returns expected value' );
+
+ y = diagonal( x, [ 0, 1 ], 1, false );
+
+ expected = [ 2, 6 ];
+ t.deepEqual( ndarray2array( y ), expected, 'returns expected value' );
+
+ y = diagonal( x, [ 0, 1 ], -1, false );
+
+ expected = [ 4, 8 ];
+ t.deepEqual( ndarray2array( y ), expected, 'returns expected value' );
+
+ t.end();
+});
+
+tape( 'the function supports 4D inputs with non-trailing `dims`', function test( t ) {
+ var expected;
+ var arr;
+ var x;
+ var y;
+
+ arr = [
+ [
+ [
+ [ 0, 1 ],
+ [ 2, 3 ],
+ [ 4, 5 ]
+ ],
+ [
+ [ 6, 7 ],
+ [ 8, 9 ],
+ [ 10, 11 ]
+ ],
+ [
+ [ 12, 13 ],
+ [ 14, 15 ],
+ [ 16, 17 ]
+ ]
+ ],
+ [
+ [
+ [ 18, 19 ],
+ [ 20, 21 ],
+ [ 22, 23 ]
+ ],
+ [
+ [ 24, 25 ],
+ [ 26, 27 ],
+ [ 28, 29 ]
+ ],
+ [
+ [ 30, 31 ],
+ [ 32, 33 ],
+ [ 34, 35 ]
+ ]
+ ]
+ ];
+ x = array( arr );
+ y = diagonal( x, [ 1, 2 ], 0, false );
+ expected = [ 2, 2, 3 ];
+
+ t.deepEqual( getShape( y ), expected, 'returns expected value' );
+
+ expected = [
+ [
+ [ 0, 8, 16 ],
+ [ 1, 9, 17 ]
+ ],
+ [
+ [ 18, 26, 34 ],
+ [ 19, 27, 35 ]
+ ]
+ ];
+
+ t.deepEqual( ndarray2array( y ), expected, 'returns expected value' );
+ t.strictEqual( getData( y ), getData( x ), 'returns expected value' );
+
+ t.end();
+});
+
+tape( 'the function supports negative dimension indices combined with a non-zero `k`', function test( t ) {
+ var expected;
+ var x;
+ var y;
+
+ x = array( [ [ 1, 2, 3 ], [ 4, 5, 6 ], [ 7, 8, 9 ] ] );
+ y = diagonal( x, [ -2, -1 ], 1, false );
+
+ expected = [ 2 ];
+ t.deepEqual( getShape( y ), expected, 'returns expected value' );
+
+ expected = [ 2, 6 ];
+ t.deepEqual( ndarray2array( y ), expected, 'returns expected value' );
+
+ y = diagonal( x, [ -2, -1 ], -1, false );
+
+ expected = [ 4, 8 ];
+ t.deepEqual( ndarray2array( y ), expected, 'returns expected value' );
+
+ t.end();
+});