diff --git a/lib/node_modules/@stdlib/differentiate/strided/ggradient/README.md b/lib/node_modules/@stdlib/differentiate/strided/ggradient/README.md
new file mode 100644
index 000000000000..9b555037b43d
--- /dev/null
+++ b/lib/node_modules/@stdlib/differentiate/strided/ggradient/README.md
@@ -0,0 +1,194 @@
+
+
+# ggradient
+
+> Compute the gradient of a strided array.
+
+
+
+## Usage
+
+```javascript
+var ggradient = require( '@stdlib/differentiate/strided/ggradient' );
+```
+
+#### ggradient( N, edgeOrder, x, strideX, h, strideH, out, strideOut )
+
+Computes the gradient of a strided array.
+
+```javascript
+var x = [ 0.0, 1.0, 9.0, 36.0, 100.0 ];
+var h = [ 1.0, 2.0, 3.0, 4.0 ];
+var out = [ 0.0, 0.0, 0.0, 0.0, 0.0 ];
+
+ggradient( x.length, 1, x, 1, h, 1, out, 1 );
+// out => [ 1.0, 2.0, 6.0, 12.0, 16.0 ]
+```
+
+The function has the following parameters:
+
+- **N**: number of indexed elements.
+- **edgeOrder**: approximation order at the boundaries.
+- **x**: input [`Array`][mdn-array] or [`typed array`][mdn-typed-array].
+- **strideX**: stride length for `x`.
+- **h**: spacing [`Array`][mdn-array] or [`typed array`][mdn-typed-array].
+- **strideH**: stride length for `h`.
+- **out**: output [`Array`][mdn-array] or [`typed array`][mdn-typed-array].
+- **strideOut**: stride length for `out`.
+
+The `N` and stride parameters determine which elements in the strided arrays are accessed at runtime. For example, to compute the gradient of every other element:
+
+```javascript
+var x = [ 0.0, -1.0, 1.0, -1.0, 4.0, -1.0, 9.0, -1.0, 16.0 ];
+var h = [ 1.0 ];
+var out = [ 0.0, -1.0, 0.0, -1.0, 0.0, -1.0, 0.0, -1.0, 0.0 ];
+
+ggradient( 5, 2, x, 2, h, 0, out, 2 );
+// out => [ 0.0, -1.0, 2.0, -1.0, 4.0, -1.0, 6.0, -1.0, 8.0 ]
+```
+
+Note that indexing is relative to the first index. To introduce an offset, use [`typed array`][mdn-typed-array] views.
+
+```javascript
+var Float64Array = require( '@stdlib/array/float64' );
+
+// Initial arrays:
+var xbuf = new Float64Array( [ -1.0, -1.0, 0.0, 1.0, 9.0, 36.0, 100.0 ] );
+var hbuf = new Float64Array( [ 0.0, 1.0, 2.0, 3.0, 4.0 ] );
+var obuf = new Float64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] );
+
+// Create offset views:
+var x1 = new Float64Array( xbuf.buffer, xbuf.BYTES_PER_ELEMENT*2 ); // start at 3rd element
+var h1 = new Float64Array( hbuf.buffer, hbuf.BYTES_PER_ELEMENT*1 ); // start at 2nd element
+var out1 = new Float64Array( obuf.buffer, obuf.BYTES_PER_ELEMENT*2 );
+
+// Compute the gradient of the last 5 elements:
+ggradient( 5, 1, x1, 1, h1, 1, out1, 1 );
+// obuf => [ 0.0, 0.0, 1.0, 2.0, 6.0, 12.0, 16.0 ]
+```
+
+
+
+#### ggradient.ndarray( N, edgeOrder, x, strideX, offsetX, h, strideH, offsetH, out, strideOut, offsetOut )
+
+
+
+Computes the gradient of a strided array using alternative indexing semantics.
+
+```javascript
+var x = [ 0.0, 1.0, 9.0, 36.0, 100.0 ];
+var h = [ 1.0, 2.0, 3.0, 4.0 ];
+var out = [ 0.0, 0.0, 0.0, 0.0, 0.0 ];
+
+ggradient.ndarray( x.length, 1, x, 1, 0, h, 1, 0, out, 1, 0 );
+// out => [ 1.0, 2.0, 6.0, 12.0, 16.0 ]
+```
+
+The function has the following additional parameters:
+
+- **offsetX**: starting index for `x`.
+- **offsetH**: starting index for `h`.
+- **offsetOut**: starting index for `out`.
+
+While [`typed array`][mdn-typed-array] views mandate a view offset based on the underlying buffer, the offset parameters support indexing semantics based on starting indices. For example, to compute the gradient of the last five elements:
+
+```javascript
+var x = [ -1.0, -1.0, 0.0, 1.0, 9.0, 36.0, 100.0 ];
+var h = [ 1.0, 2.0, 3.0, 4.0 ];
+var out = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];
+
+ggradient.ndarray( 5, 1, x, 1, 2, h, 1, 0, out, 1, 2 );
+// out => [ 0.0, 0.0, 1.0, 2.0, 6.0, 12.0, 16.0 ]
+```
+
+
+
+
+
+
+
+## Notes
+
+- If `N <= 0` or `N === 1`, both functions return `out` unchanged.
+- Both functions support first-order (i.e., `edgeOrder = 1`) and second-order (i.e., `edgeOrder = 2`) finite-difference approximations at the boundaries.
+- Both functions support array-like objects having getter and setter accessors for array element access (e.g., [`@stdlib/array/base/accessor`][@stdlib/array/base/accessor]).
+
+
+
+
+
+
+
+## Examples
+
+
+
+```javascript
+var ggradient = require( '@stdlib/differentiate/strided/ggradient' );
+
+// Approximate the gradient of f(t) = 3t^2 at t = 0, 1, 2, 3, 4 with uniform spacing...
+var x = [ 0.0, 3.0, 12.0, 27.0, 48.0 ];
+var h = [ 1.0 ];
+var out = [ 0.0, 0.0, 0.0, 0.0, 0.0 ];
+
+ggradient( x.length, 2, x, 1, h, 0, out, 1 );
+console.log( out );
+// => [ 0.0, 6.0, 12.0, 18.0, 24.0 ]
+
+// Approximate the gradient of f(t) = 3t^2 at t = 0, 1, 3, 4, 7 with non-uniform spacing...
+x = [ 0.0, 3.0, 27.0, 48.0, 147.0 ];
+h = [ 1.0, 2.0, 1.0, 3.0 ];
+out = [ 0.0, 0.0, 0.0, 0.0, 0.0 ];
+
+ggradient( x.length, 2, x, 1, h, 1, out, 1 );
+console.log( out );
+// => [ 0.0, 6.0, 18.0, 24.0, 42.0 ]
+```
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+[mdn-array]: https://developer.mozilla.org/en-US/docs/Web/JavaScript/Reference/Global_Objects/Array
+
+[mdn-typed-array]: https://developer.mozilla.org/en-US/docs/Web/JavaScript/Reference/Global_Objects/TypedArray
+
+[@stdlib/array/base/accessor]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/array/base/accessor
+
+
+
+
+
+
+
+
diff --git a/lib/node_modules/@stdlib/differentiate/strided/ggradient/benchmark/benchmark.non_uniform_spacing.js b/lib/node_modules/@stdlib/differentiate/strided/ggradient/benchmark/benchmark.non_uniform_spacing.js
new file mode 100644
index 000000000000..9eebc3ebf788
--- /dev/null
+++ b/lib/node_modules/@stdlib/differentiate/strided/ggradient/benchmark/benchmark.non_uniform_spacing.js
@@ -0,0 +1,109 @@
+/**
+* @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 uniform = require( '@stdlib/random/array/uniform' );
+var isnan = require( '@stdlib/math/base/assert/is-nan' );
+var pow = require( '@stdlib/math/base/special/pow' );
+var format = require( '@stdlib/string/format' );
+var pkg = require( './../package.json' ).name;
+var ggradient = require( './../lib/main.js' );
+
+
+// VARIABLES //
+
+var options = {
+ 'dtype': 'generic'
+};
+
+
+// FUNCTIONS //
+
+/**
+* Create a benchmark function.
+*
+* @private
+* @param {PositiveInteger} len - array length
+* @returns {Function} benchmark function
+*/
+function createBenchmark( len ) {
+ var out;
+ var h;
+ var x;
+
+ x = uniform( len, -100.0, 100.0, options );
+ h = uniform( len-1, 0.1, 2.0, options );
+ out = uniform( len, -100.0, 100.0, options );
+ return benchmark;
+
+ /**
+ * Benchmark function.
+ *
+ * @private
+ * @param {Benchmark} b - benchmark instance
+ */
+ function benchmark( b ) {
+ var v;
+ var i;
+
+ b.tic();
+ for ( i = 0; i < b.iterations; i++ ) {
+ v = ggradient( x.length, 2, x, 1, h, 1, out, 1 );
+ if ( typeof v !== 'object' ) {
+ b.fail( 'should return an object' );
+ }
+ }
+ b.toc();
+ if ( isnan( out[ i%len ] ) ) {
+ b.fail( 'should not return NaN' );
+ }
+ b.pass( 'benchmark finished' );
+ b.end();
+ }
+}
+
+
+// MAIN //
+
+/**
+* Main execution sequence.
+*
+* @private
+*/
+function main() {
+ var len;
+ var min;
+ var max;
+ var f;
+ var i;
+
+ min = 1; // 10^min
+ max = 6; // 10^max
+
+ for ( i = min; i <= max; i++ ) {
+ len = pow( 10, i );
+ f = createBenchmark( len );
+ bench( format( '%s::non_uniform_spacing:len=%d', pkg, len ), f );
+ }
+}
+
+main();
diff --git a/lib/node_modules/@stdlib/differentiate/strided/ggradient/benchmark/benchmark.uniform_spacing.js b/lib/node_modules/@stdlib/differentiate/strided/ggradient/benchmark/benchmark.uniform_spacing.js
new file mode 100644
index 000000000000..a343d2c175b5
--- /dev/null
+++ b/lib/node_modules/@stdlib/differentiate/strided/ggradient/benchmark/benchmark.uniform_spacing.js
@@ -0,0 +1,109 @@
+/**
+* @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 uniform = require( '@stdlib/random/array/uniform' );
+var isnan = require( '@stdlib/math/base/assert/is-nan' );
+var pow = require( '@stdlib/math/base/special/pow' );
+var format = require( '@stdlib/string/format' );
+var pkg = require( './../package.json' ).name;
+var ggradient = require( './../lib/main.js' );
+
+
+// VARIABLES //
+
+var options = {
+ 'dtype': 'generic'
+};
+
+
+// FUNCTIONS //
+
+/**
+* Create a benchmark function.
+*
+* @private
+* @param {PositiveInteger} len - array length
+* @returns {Function} benchmark function
+*/
+function createBenchmark( len ) {
+ var out;
+ var h;
+ var x;
+
+ x = uniform( len, -100.0, 100.0, options );
+ h = uniform( 1, 0.1, 2.0, options );
+ out = uniform( len, -100.0, 100.0, options );
+ return benchmark;
+
+ /**
+ * Benchmark function.
+ *
+ * @private
+ * @param {Benchmark} b - benchmark instance
+ */
+ function benchmark( b ) {
+ var v;
+ var i;
+
+ b.tic();
+ for ( i = 0; i < b.iterations; i++ ) {
+ v = ggradient( x.length, 2, x, 1, h, 0, out, 1 );
+ if ( typeof v !== 'object' ) {
+ b.fail( 'should return an object' );
+ }
+ }
+ b.toc();
+ if ( isnan( out[ i%len ] ) ) {
+ b.fail( 'should not return NaN' );
+ }
+ b.pass( 'benchmark finished' );
+ b.end();
+ }
+}
+
+
+// MAIN //
+
+/**
+* Main execution sequence.
+*
+* @private
+*/
+function main() {
+ var len;
+ var min;
+ var max;
+ var f;
+ var i;
+
+ min = 1; // 10^min
+ max = 6; // 10^max
+
+ for ( i = min; i <= max; i++ ) {
+ len = pow( 10, i );
+ f = createBenchmark( len );
+ bench( format( '%s::uniform_spacing:len=%d', pkg, len ), f );
+ }
+}
+
+main();
diff --git a/lib/node_modules/@stdlib/differentiate/strided/ggradient/docs/repl.txt b/lib/node_modules/@stdlib/differentiate/strided/ggradient/docs/repl.txt
new file mode 100644
index 000000000000..0e3fca8c038e
--- /dev/null
+++ b/lib/node_modules/@stdlib/differentiate/strided/ggradient/docs/repl.txt
@@ -0,0 +1,143 @@
+
+{{alias}}( N, edgeOrder, x, strideX, h, strideH, out, strideOut )
+ Computes the gradient of a strided array.
+
+ The `N` and stride parameters determine which elements in the strided arrays
+ are accessed at runtime.
+
+ Indexing is relative to the first index. To introduce an offset, use typed
+ array views.
+
+ If `N <= 0` or `N == 1`, the function returns `out` unchanged.
+
+ The function supports first-order (i.e., `edgeOrder = 1`) and
+ second-order (i.e., `edgeOrder = 2`) finite-difference approximations at the
+ boundaries.
+
+ Parameters
+ ----------
+ N: integer
+ Number of indexed elements.
+
+ edgeOrder: integer
+ Approximation order at the boundaries.
+
+ x: Array|TypedArray
+ Input array.
+
+ strideX: integer
+ Stride length for `x`.
+
+ h: Array|TypedArray
+ Spacing array.
+
+ strideH: integer
+ Stride length for `h`.
+
+ out: Array|TypedArray
+ Output array.
+
+ strideOut: integer
+ Stride length for `out`.
+
+ Returns
+ -------
+ out: Array|TypedArray
+ Output array.
+
+ Examples
+ --------
+ // Standard Usage:
+ > var x = [ 0.0, 1.0, 9.0, 36.0, 100.0 ];
+ > var h = [ 1.0, 2.0, 3.0, 4.0 ];
+ > var out = [ 0.0, 0.0, 0.0, 0.0, 0.0 ];
+ > {{alias}}( x.length, 1, x, 1, h, 1, out, 1 )
+ [ 1.0, 2.0, 6.0, 12.0, 16.0 ]
+
+ // Using `N` and stride parameters:
+ > x = [ 0.0, -1.0, 1.0, -1.0, 4.0, -1.0, 9.0 ];
+ > h = [ 1.0 ];
+ > out = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];
+ > {{alias}}( 4, 1, x, 2, h, 0, out, 2 )
+ [ 1.0, 0.0, 2.0, 0.0, 4.0, 0.0, 5.0 ]
+
+ // Using view offsets:
+ > var xbuf = [ -1.0, -1.0, 0.0, 1.0, 9.0, 36.0, 100.0 ];
+ > var hbuf = [ 0.0, 1.0, 2.0, 3.0, 4.0 ];
+ > var obuf = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];
+ > var x0 = new {{alias:@stdlib/array/float64}}( xbuf );
+ > var h0 = new {{alias:@stdlib/array/float64}}( hbuf );
+ > var out0 = new {{alias:@stdlib/array/float64}}( obuf );
+ > var x1 = new {{alias:@stdlib/array/float64}}( x0.buffer, x0.BYTES_PER_ELEMENT*2 );
+ > var h1 = new {{alias:@stdlib/array/float64}}( h0.buffer, h0.BYTES_PER_ELEMENT*1 );
+ > var out1 = new {{alias:@stdlib/array/float64}}( out0.buffer, out0.BYTES_PER_ELEMENT*2 );
+ > {{alias}}( 5, 1, x1, 1, h1, 1, out1, 1 )
+ [ 1.0, 2.0, 6.0, 12.0, 16.0 ]
+
+
+{{alias}}.ndarray( N, edgeOrder, x, sx, ox, h, sh, oh, o, so, oo )
+ Computes the gradient of a strided array using alternative indexing
+ semantics.
+
+ While typed array views mandate a view offset based on the underlying
+ buffer, the offset parameters support indexing semantics based on starting
+ indices.
+
+ Parameters
+ ----------
+ N: integer
+ Number of indexed elements.
+
+ edgeOrder: integer
+ Approximation order at the boundaries.
+
+ x: Array|TypedArray
+ Input array.
+
+ sx: integer
+ Stride length for `x`.
+
+ ox: integer
+ Starting index for `x`.
+
+ h: Array|TypedArray
+ Spacing array.
+
+ sh: integer
+ Stride length for `h`.
+
+ oh: integer
+ Starting index for `h`.
+
+ o: Array|TypedArray
+ Output array.
+
+ so: integer
+ Stride length for `out`.
+
+ oo: integer
+ Starting index for `out`.
+
+ Returns
+ -------
+ out: Array|TypedArray
+ Output array.
+
+ Examples
+ --------
+ // Standard Usage:
+ > var x = [ 0.0, 1.0, 9.0, 36.0, 100.0 ];
+ > var h = [ 1.0, 2.0, 3.0, 4.0 ];
+ > var out = [ 0.0, 0.0, 0.0, 0.0, 0.0 ];
+ > {{alias}}.ndarray( x.length, 1, x, 1, 0, h, 1, 0, out, 1, 0 )
+ [ 1.0, 2.0, 6.0, 12.0, 16.0 ]
+
+ // Using index offsets:
+ > x = [ -1.0, -1.0, 0.0, 1.0, 9.0, 36.0, 100.0 ];
+ > h = [ 1.0, 2.0, 3.0, 4.0 ];
+ > out = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];
+ > {{alias}}.ndarray( 5, 1, x, 1, 2, h, 1, 0, out, 1, 2 )
+ [ 0.0, 0.0, 1.0, 2.0, 6.0, 12.0, 16.0 ]
+
+ See Also
+ --------
diff --git a/lib/node_modules/@stdlib/differentiate/strided/ggradient/docs/types/index.d.ts b/lib/node_modules/@stdlib/differentiate/strided/ggradient/docs/types/index.d.ts
new file mode 100644
index 000000000000..bfffbe3e76de
--- /dev/null
+++ b/lib/node_modules/@stdlib/differentiate/strided/ggradient/docs/types/index.d.ts
@@ -0,0 +1,131 @@
+/*
+* @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 { NumericArray, Collection, AccessorArrayLike } from '@stdlib/types/array';
+
+/**
+* Input array.
+*/
+type InputArray = NumericArray | Collection | AccessorArrayLike;
+
+/**
+* Output array.
+*/
+type OutputArray = NumericArray | Collection | AccessorArrayLike;
+
+/**
+* Interface describing `ggradient`.
+*/
+interface Routine {
+ /**
+ * Computes the gradient of a strided array.
+ *
+ * ## Notes
+ *
+ * - The function supports first-order (i.e., `edgeOrder = 1`) and second-order (i.e., `edgeOrder = 2`) finite-difference approximations at the boundaries.
+ *
+ * @param N - number of indexed elements
+ * @param edgeOrder - approximation order at the boundaries
+ * @param x - input array
+ * @param strideX - stride length for `x`
+ * @param h - spacing array
+ * @param strideH - stride length for `h`
+ * @param out - output array
+ * @param strideOut - stride length for `out`
+ * @returns output array
+ *
+ * @example
+ * var x = [ 0.0, 1.0, 9.0, 36.0, 100.0 ];
+ * var h = [ 1.0, 2.0, 3.0, 4.0 ];
+ * var out = [ 0.0, 0.0, 0.0, 0.0, 0.0 ];
+ *
+ * ggradient( x.length, 1, x, 1, h, 1, out, 1 );
+ * // out => [ 1.0, 2.0, 6.0, 12.0, 16.0 ]
+ */
+ ( N: number, edgeOrder: number, x: InputArray, strideX: number, h: InputArray, strideH: number, out: T, strideOut: number ): T;
+
+ /**
+ * Computes the gradient of a strided array using alternative indexing semantics.
+ *
+ * ## Notes
+ *
+ * - The function supports first-order (i.e., `edgeOrder = 1`) and second-order (i.e., `edgeOrder = 2`) finite-difference approximations at the boundaries.
+ *
+ * @param N - number of indexed elements
+ * @param edgeOrder - approximation order at the boundaries
+ * @param x - input array
+ * @param strideX - stride length for `x`
+ * @param offsetX - starting index for `x`
+ * @param h - spacing array
+ * @param strideH - stride length for `h`
+ * @param offsetH - starting index for `h`
+ * @param out - output array
+ * @param strideOut - stride length for `out`
+ * @param offsetOut - starting index for `out`
+ * @returns output array
+ *
+ * @example
+ * var x = [ 0.0, 1.0, 9.0, 36.0, 100.0 ];
+ * var h = [ 1.0, 2.0, 3.0, 4.0 ];
+ * var out = [ 0.0, 0.0, 0.0, 0.0, 0.0 ];
+ *
+ * ggradient.ndarray( x.length, 1, x, 1, 0, h, 1, 0, out, 1, 0 );
+ * // out => [ 1.0, 2.0, 6.0, 12.0, 16.0 ]
+ */
+ ndarray( N: number, edgeOrder: number, x: InputArray, strideX: number, offsetX: number, h: InputArray, strideH: number, offsetH: number, out: T, strideOut: number, offsetOut: number ): T;
+}
+
+/**
+* Computes the gradient of a strided array.
+*
+* @param N - number of indexed elements
+* @param edgeOrder - approximation order at the boundaries
+* @param x - input array
+* @param strideX - stride length for `x`
+* @param h - spacing array
+* @param strideH - stride length for `h`
+* @param out - output array
+* @param strideOut - stride length for `out`
+* @returns output array
+*
+* @example
+* var x = [ 0.0, 1.0, 9.0, 36.0, 100.0 ];
+* var h = [ 1.0, 2.0, 3.0, 4.0 ];
+* var out = [ 0.0, 0.0, 0.0, 0.0, 0.0 ];
+*
+* ggradient( x.length, 1, x, 1, h, 1, out, 1 );
+* // out => [ 1.0, 2.0, 6.0, 12.0, 16.0 ]
+*
+* @example
+* var x = [ 0.0, 1.0, 9.0, 36.0, 100.0 ];
+* var h = [ 1.0, 2.0, 3.0, 4.0 ];
+* var out = [ 0.0, 0.0, 0.0, 0.0, 0.0 ];
+*
+* ggradient.ndarray( x.length, 1, x, 1, 0, h, 1, 0, out, 1, 0 );
+* // out => [ 1.0, 2.0, 6.0, 12.0, 16.0 ]
+*/
+declare var ggradient: Routine;
+
+
+// EXPORTS //
+
+export = ggradient;
diff --git a/lib/node_modules/@stdlib/differentiate/strided/ggradient/docs/types/test.ts b/lib/node_modules/@stdlib/differentiate/strided/ggradient/docs/types/test.ts
new file mode 100644
index 000000000000..4cbfa9c510fd
--- /dev/null
+++ b/lib/node_modules/@stdlib/differentiate/strided/ggradient/docs/types/test.ts
@@ -0,0 +1,386 @@
+/*
+* @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 AccessorArray = require( '@stdlib/array/base/accessor' );
+import ggradient = require( './index' );
+
+
+// TESTS //
+
+// The function returns a numeric array...
+{
+ const x = new Float64Array( 10 );
+ const h = new Float64Array( 9 );
+ const out = new Float64Array( 10 );
+
+ ggradient( x.length, 1, x, 1, h, 1, out, 1 ); // $ExpectType Float64Array
+ ggradient( x.length, 1, new AccessorArray( x ), 1, new AccessorArray( h ), 1, new AccessorArray( out ), 1 ); // $ExpectType AccessorArray
+}
+
+// The compiler throws an error if the function is provided a first argument which is not a number...
+{
+ const x = new Float64Array( 10 );
+ const h = new Float64Array( 9 );
+ const out = new Float64Array( 10 );
+
+ ggradient( '10', 1, x, 1, h, 1, out, 1 ); // $ExpectError
+ ggradient( true, 1, x, 1, h, 1, out, 1 ); // $ExpectError
+ ggradient( false, 1, x, 1, h, 1, out, 1 ); // $ExpectError
+ ggradient( null, 1, x, 1, h, 1, out, 1 ); // $ExpectError
+ ggradient( undefined, 1, x, 1, h, 1, out, 1 ); // $ExpectError
+ ggradient( [], 1, x, 1, h, 1, out, 1 ); // $ExpectError
+ ggradient( {}, 1, x, 1, h, 1, out, 1 ); // $ExpectError
+ ggradient( ( x: number ): number => x, 1, x, 1, h, 1, out, 1 ); // $ExpectError
+}
+
+// The compiler throws an error if the function is provided a second argument which is not a number...
+{
+ const x = new Float64Array( 10 );
+ const h = new Float64Array( 9 );
+ const out = new Float64Array( 10 );
+
+ ggradient( x.length, '10', x, 1, h, 1, out, 1 ); // $ExpectError
+ ggradient( x.length, true, x, 1, h, 1, out, 1 ); // $ExpectError
+ ggradient( x.length, false, x, 1, h, 1, out, 1 ); // $ExpectError
+ ggradient( x.length, null, x, 1, h, 1, out, 1 ); // $ExpectError
+ ggradient( x.length, undefined, x, 1, h, 1, out, 1 ); // $ExpectError
+ ggradient( x.length, [], x, 1, h, 1, out, 1 ); // $ExpectError
+ ggradient( x.length, {}, x, 1, h, 1, out, 1 ); // $ExpectError
+ ggradient( x.length, ( x: number ): number => x, x, 1, h, 1, out, 1 ); // $ExpectError
+}
+
+// The compiler throws an error if the function is provided a third argument which is not a numeric array...
+{
+ const h = new Float64Array( 9 );
+ const out = new Float64Array( 10 );
+
+ ggradient( 10, 1, 10, 1, h, 1, out, 1 ); // $ExpectError
+ ggradient( 10, 1, '10', 1, h, 1, out, 1 ); // $ExpectError
+ ggradient( 10, 1, true, 1, h, 1, out, 1 ); // $ExpectError
+ ggradient( 10, 1, false, 1, h, 1, out, 1 ); // $ExpectError
+ ggradient( 10, 1, null, 1, h, 1, out, 1 ); // $ExpectError
+ ggradient( 10, 1, undefined, 1, h, 1, out, 1 ); // $ExpectError
+ ggradient( 10, 1, [ '1' ], 1, h, 1, out, 1 ); // $ExpectError
+ ggradient( 10, 1, {}, 1, h, 1, out, 1 ); // $ExpectError
+ ggradient( 10, 1, ( x: number ): number => x, 1, h, 1, out, 1 ); // $ExpectError
+}
+
+// The compiler throws an error if the function is provided a fourth argument which is not a number...
+{
+ const x = new Float64Array( 10 );
+ const h = new Float64Array( 9 );
+ const out = new Float64Array( 10 );
+
+ ggradient( x.length, 1, x, '10', h, 1, out, 1 ); // $ExpectError
+ ggradient( x.length, 1, x, true, h, 1, out, 1 ); // $ExpectError
+ ggradient( x.length, 1, x, false, h, 1, out, 1 ); // $ExpectError
+ ggradient( x.length, 1, x, null, h, 1, out, 1 ); // $ExpectError
+ ggradient( x.length, 1, x, undefined, h, 1, out, 1 ); // $ExpectError
+ ggradient( x.length, 1, x, [], h, 1, out, 1 ); // $ExpectError
+ ggradient( x.length, 1, x, {}, h, 1, out, 1 ); // $ExpectError
+ ggradient( x.length, 1, x, ( x: number ): number => x, h, 1, out, 1 ); // $ExpectError
+}
+
+// The compiler throws an error if the function is provided a fifth argument which is not a numeric array...
+{
+ const x = new Float64Array( 10 );
+ const out = new Float64Array( 10 );
+
+ ggradient( 10, 1, x, 1, 10, 1, out, 1 ); // $ExpectError
+ ggradient( 10, 1, x, 1, '10', 1, out, 1 ); // $ExpectError
+ ggradient( 10, 1, x, 1, true, 1, out, 1 ); // $ExpectError
+ ggradient( 10, 1, x, 1, false, 1, out, 1 ); // $ExpectError
+ ggradient( 10, 1, x, 1, null, 1, out, 1 ); // $ExpectError
+ ggradient( 10, 1, x, 1, undefined, 1, out, 1 ); // $ExpectError
+ ggradient( 10, 1, x, 1, [ '1' ], 1, out, 1 ); // $ExpectError
+ ggradient( 10, 1, x, 1, {}, 1, out, 1 ); // $ExpectError
+ ggradient( 10, 1, x, 1, ( x: number ): number => x, 1, out, 1 ); // $ExpectError
+}
+
+// The compiler throws an error if the function is provided a sixth argument which is not a number...
+{
+ const x = new Float64Array( 10 );
+ const h = new Float64Array( 9 );
+ const out = new Float64Array( 10 );
+
+ ggradient( x.length, 1, x, 1, h, '10', out, 1 ); // $ExpectError
+ ggradient( x.length, 1, x, 1, h, true, out, 1 ); // $ExpectError
+ ggradient( x.length, 1, x, 1, h, false, out, 1 ); // $ExpectError
+ ggradient( x.length, 1, x, 1, h, null, out, 1 ); // $ExpectError
+ ggradient( x.length, 1, x, 1, h, undefined, out, 1 ); // $ExpectError
+ ggradient( x.length, 1, x, 1, h, [], out, 1 ); // $ExpectError
+ ggradient( x.length, 1, x, 1, h, {}, out, 1 ); // $ExpectError
+ ggradient( x.length, 1, x, 1, h, ( x: number ): number => x, out, 1 ); // $ExpectError
+}
+
+// The compiler throws an error if the function is provided a seventh argument which is not a numeric array...
+{
+ const x = new Float64Array( 10 );
+ const h = new Float64Array( 9 );
+
+ ggradient( 10, 1, x, 1, h, 1, 10, 1 ); // $ExpectError
+ ggradient( 10, 1, x, 1, h, 1, '10', 1 ); // $ExpectError
+ ggradient( 10, 1, x, 1, h, 1, true, 1 ); // $ExpectError
+ ggradient( 10, 1, x, 1, h, 1, false, 1 ); // $ExpectError
+ ggradient( 10, 1, x, 1, h, 1, null, 1 ); // $ExpectError
+ ggradient( 10, 1, x, 1, h, 1, undefined, 1 ); // $ExpectError
+ ggradient( 10, 1, x, 1, h, 1, [ '1' ], 1 ); // $ExpectError
+ ggradient( 10, 1, x, 1, h, 1, {}, 1 ); // $ExpectError
+ ggradient( 10, 1, x, 1, h, 1, ( x: number ): number => x, 1 ); // $ExpectError
+}
+
+// The compiler throws an error if the function is provided an eighth argument which is not a number...
+{
+ const x = new Float64Array( 10 );
+ const h = new Float64Array( 9 );
+ const out = new Float64Array( 10 );
+
+ ggradient( x.length, 1, x, 1, h, 1, out, '10' ); // $ExpectError
+ ggradient( x.length, 1, x, 1, h, 1, out, true ); // $ExpectError
+ ggradient( x.length, 1, x, 1, h, 1, out, false ); // $ExpectError
+ ggradient( x.length, 1, x, 1, h, 1, out, null ); // $ExpectError
+ ggradient( x.length, 1, x, 1, h, 1, out, undefined ); // $ExpectError
+ ggradient( x.length, 1, x, 1, h, 1, out, [] ); // $ExpectError
+ ggradient( x.length, 1, x, 1, h, 1, out, {} ); // $ExpectError
+ ggradient( x.length, 1, x, 1, h, 1, out, ( x: number ): number => x ); // $ExpectError
+}
+
+// The compiler throws an error if the function is provided an unsupported number of arguments...
+{
+ const x = new Float64Array( 10 );
+ const h = new Float64Array( 9 );
+ const out = new Float64Array( 10 );
+
+ ggradient(); // $ExpectError
+ ggradient( x.length ); // $ExpectError
+ ggradient( x.length, 1 ); // $ExpectError
+ ggradient( x.length, 1, x ); // $ExpectError
+ ggradient( x.length, 1, x, 1 ); // $ExpectError
+ ggradient( x.length, 1, x, 1, h ); // $ExpectError
+ ggradient( x.length, 1, x, 1, h, 1 ); // $ExpectError
+ ggradient( x.length, 1, x, 1, h, 1, out ); // $ExpectError
+ ggradient( x.length, 1, x, 1, h, 1, out, 1, {} ); // $ExpectError
+}
+
+// Attached to the main export is an `ndarray` method which returns a numeric array...
+{
+ const x = new Float64Array( 10 );
+ const h = new Float64Array( 9 );
+ const out = new Float64Array( 10 );
+
+ ggradient.ndarray( x.length, 1, x, 1, 0, h, 1, 0, out, 1, 0 ); // $ExpectType Float64Array
+ ggradient.ndarray( x.length, 1, new AccessorArray( x ), 1, 0, new AccessorArray( h ), 1, 0, new AccessorArray( out ), 1, 0 ); // $ExpectType AccessorArray
+}
+
+// The compiler throws an error if the `ndarray` method is provided a first argument which is not a number...
+{
+ const x = new Float64Array( 10 );
+ const h = new Float64Array( 9 );
+ const out = new Float64Array( 10 );
+
+ ggradient.ndarray( '10', 1, x, 1, 0, h, 1, 0, out, 1, 0 ); // $ExpectError
+ ggradient.ndarray( true, 1, x, 1, 0, h, 1, 0, out, 1, 0 ); // $ExpectError
+ ggradient.ndarray( false, 1, x, 1, 0, h, 1, 0, out, 1, 0 ); // $ExpectError
+ ggradient.ndarray( null, 1, x, 1, 0, h, 1, 0, out, 1, 0 ); // $ExpectError
+ ggradient.ndarray( undefined, 1, x, 1, 0, h, 1, 0, out, 1, 0 ); // $ExpectError
+ ggradient.ndarray( [], 1, x, 1, 0, h, 1, 0, out, 1, 0 ); // $ExpectError
+ ggradient.ndarray( {}, 1, x, 1, 0, h, 1, 0, out, 1, 0 ); // $ExpectError
+ ggradient.ndarray( ( x: number ): number => x, 1, x, 1, 0, h, 1, 0, out, 1, 0 ); // $ExpectError
+}
+
+// The compiler throws an error if the `ndarray` method is provided a second argument which is not a number...
+{
+ const x = new Float64Array( 10 );
+ const h = new Float64Array( 9 );
+ const out = new Float64Array( 10 );
+
+ ggradient.ndarray( x.length, '10', x, 1, 0, h, 1, 0, out, 1, 0 ); // $ExpectError
+ ggradient.ndarray( x.length, true, x, 1, 0, h, 1, 0, out, 1, 0 ); // $ExpectError
+ ggradient.ndarray( x.length, false, x, 1, 0, h, 1, 0, out, 1, 0 ); // $ExpectError
+ ggradient.ndarray( x.length, null, x, 1, 0, h, 1, 0, out, 1, 0 ); // $ExpectError
+ ggradient.ndarray( x.length, undefined, x, 1, 0, h, 1, 0, out, 1, 0 ); // $ExpectError
+ ggradient.ndarray( x.length, [], x, 1, 0, h, 1, 0, out, 1, 0 ); // $ExpectError
+ ggradient.ndarray( x.length, {}, x, 1, 0, h, 1, 0, out, 1, 0 ); // $ExpectError
+ ggradient.ndarray( x.length, ( x: number ): number => x, x, 1, 0, h, 1, 0, out, 1, 0 ); // $ExpectError
+}
+
+// The compiler throws an error if the `ndarray` method is provided a third argument which is not a numeric array...
+{
+ const h = new Float64Array( 9 );
+ const out = new Float64Array( 10 );
+
+ ggradient.ndarray( 10, 1, 10, 1, 0, h, 1, 0, out, 1, 0 ); // $ExpectError
+ ggradient.ndarray( 10, 1, '10', 1, 0, h, 1, 0, out, 1, 0 ); // $ExpectError
+ ggradient.ndarray( 10, 1, true, 1, 0, h, 1, 0, out, 1, 0 ); // $ExpectError
+ ggradient.ndarray( 10, 1, false, 1, 0, h, 1, 0, out, 1, 0 ); // $ExpectError
+ ggradient.ndarray( 10, 1, null, 1, 0, h, 1, 0, out, 1, 0 ); // $ExpectError
+ ggradient.ndarray( 10, 1, undefined, 1, 0, h, 1, 0, out, 1, 0 ); // $ExpectError
+ ggradient.ndarray( 10, 1, [ '1' ], 1, 0, h, 1, 0, out, 1, 0 ); // $ExpectError
+ ggradient.ndarray( 10, 1, {}, 1, 0, h, 1, 0, out, 1, 0 ); // $ExpectError
+ ggradient.ndarray( 10, 1, ( x: number ): number => x, 1, 0, h, 1, 0, out, 1, 0 ); // $ExpectError
+}
+
+// The compiler throws an error if the `ndarray` method is provided a fourth argument which is not a number...
+{
+ const x = new Float64Array( 10 );
+ const h = new Float64Array( 9 );
+ const out = new Float64Array( 10 );
+
+ ggradient.ndarray( x.length, 1, x, '10', 0, h, 1, 0, out, 1, 0 ); // $ExpectError
+ ggradient.ndarray( x.length, 1, x, true, 0, h, 1, 0, out, 1, 0 ); // $ExpectError
+ ggradient.ndarray( x.length, 1, x, false, 0, h, 1, 0, out, 1, 0 ); // $ExpectError
+ ggradient.ndarray( x.length, 1, x, null, 0, h, 1, 0, out, 1, 0 ); // $ExpectError
+ ggradient.ndarray( x.length, 1, x, undefined, 0, h, 1, 0, out, 1, 0 ); // $ExpectError
+ ggradient.ndarray( x.length, 1, x, [], 0, h, 1, 0, out, 1, 0 ); // $ExpectError
+ ggradient.ndarray( x.length, 1, x, {}, 0, h, 1, 0, out, 1, 0 ); // $ExpectError
+ ggradient.ndarray( x.length, 1, x, ( x: number ): number => x, 0, h, 1, 0, out, 1, 0 ); // $ExpectError
+}
+
+// The compiler throws an error if the `ndarray` method is provided a fifth argument which is not a number...
+{
+ const x = new Float64Array( 10 );
+ const h = new Float64Array( 9 );
+ const out = new Float64Array( 10 );
+
+ ggradient.ndarray( x.length, 1, x, 1, '10', h, 1, 0, out, 1, 0 ); // $ExpectError
+ ggradient.ndarray( x.length, 1, x, 1, true, h, 1, 0, out, 1, 0 ); // $ExpectError
+ ggradient.ndarray( x.length, 1, x, 1, false, h, 1, 0, out, 1, 0 ); // $ExpectError
+ ggradient.ndarray( x.length, 1, x, 1, null, h, 1, 0, out, 1, 0 ); // $ExpectError
+ ggradient.ndarray( x.length, 1, x, 1, undefined, h, 1, 0, out, 1, 0 ); // $ExpectError
+ ggradient.ndarray( x.length, 1, x, 1, [], h, 1, 0, out, 1, 0 ); // $ExpectError
+ ggradient.ndarray( x.length, 1, x, 1, {}, h, 1, 0, out, 1, 0 ); // $ExpectError
+ ggradient.ndarray( x.length, 1, x, 1, ( x: number ): number => x, h, 1, 0, out, 1, 0 ); // $ExpectError
+}
+
+// The compiler throws an error if the `ndarray` method is provided a sixth argument which is not a numeric array...
+{
+ const x = new Float64Array( 10 );
+ const out = new Float64Array( 10 );
+
+ ggradient.ndarray( 10, 1, x, 1, 0, 10, 1, 0, out, 1, 0 ); // $ExpectError
+ ggradient.ndarray( 10, 1, x, 1, 0, '10', 1, 0, out, 1, 0 ); // $ExpectError
+ ggradient.ndarray( 10, 1, x, 1, 0, true, 1, 0, out, 1, 0 ); // $ExpectError
+ ggradient.ndarray( 10, 1, x, 1, 0, false, 1, 0, out, 1, 0 ); // $ExpectError
+ ggradient.ndarray( 10, 1, x, 1, 0, null, 1, 0, out, 1, 0 ); // $ExpectError
+ ggradient.ndarray( 10, 1, x, 1, 0, undefined, 1, 0, out, 1, 0 ); // $ExpectError
+ ggradient.ndarray( 10, 1, x, 1, 0, [ '1' ], 1, 0, out, 1, 0 ); // $ExpectError
+ ggradient.ndarray( 10, 1, x, 1, 0, {}, 1, 0, out, 1, 0 ); // $ExpectError
+ ggradient.ndarray( 10, 1, x, 1, 0, ( x: number ): number => x, 1, 0, out, 1, 0 ); // $ExpectError
+}
+
+// The compiler throws an error if the `ndarray` method is provided a seventh argument which is not a number...
+{
+ const x = new Float64Array( 10 );
+ const h = new Float64Array( 9 );
+ const out = new Float64Array( 10 );
+
+ ggradient.ndarray( x.length, 1, x, 1, 0, h, '10', 0, out, 1, 0 ); // $ExpectError
+ ggradient.ndarray( x.length, 1, x, 1, 0, h, true, 0, out, 1, 0 ); // $ExpectError
+ ggradient.ndarray( x.length, 1, x, 1, 0, h, false, 0, out, 1, 0 ); // $ExpectError
+ ggradient.ndarray( x.length, 1, x, 1, 0, h, null, 0, out, 1, 0 ); // $ExpectError
+ ggradient.ndarray( x.length, 1, x, 1, 0, h, undefined, 0, out, 1, 0 ); // $ExpectError
+ ggradient.ndarray( x.length, 1, x, 1, 0, h, [], 0, out, 1, 0 ); // $ExpectError
+ ggradient.ndarray( x.length, 1, x, 1, 0, h, {}, 0, out, 1, 0 ); // $ExpectError
+ ggradient.ndarray( x.length, 1, x, 1, 0, h, ( x: number ): number => x, 0, out, 1, 0 ); // $ExpectError
+}
+
+// The compiler throws an error if the `ndarray` method is provided an eighth argument which is not a number...
+{
+ const x = new Float64Array( 10 );
+ const h = new Float64Array( 9 );
+ const out = new Float64Array( 10 );
+
+ ggradient.ndarray( x.length, 1, x, 1, 0, h, 1, '10', out, 1, 0 ); // $ExpectError
+ ggradient.ndarray( x.length, 1, x, 1, 0, h, 1, true, out, 1, 0 ); // $ExpectError
+ ggradient.ndarray( x.length, 1, x, 1, 0, h, 1, false, out, 1, 0 ); // $ExpectError
+ ggradient.ndarray( x.length, 1, x, 1, 0, h, 1, null, out, 1, 0 ); // $ExpectError
+ ggradient.ndarray( x.length, 1, x, 1, 0, h, 1, undefined, out, 1, 0 ); // $ExpectError
+ ggradient.ndarray( x.length, 1, x, 1, 0, h, 1, [], out, 1, 0 ); // $ExpectError
+ ggradient.ndarray( x.length, 1, x, 1, 0, h, 1, {}, out, 1, 0 ); // $ExpectError
+ ggradient.ndarray( x.length, 1, x, 1, 0, h, 1, ( x: number ): number => x, out, 1, 0 ); // $ExpectError
+}
+
+// The compiler throws an error if the `ndarray` method is provided a ninth argument which is not a numeric array...
+{
+ const x = new Float64Array( 10 );
+ const h = new Float64Array( 9 );
+
+ ggradient.ndarray( 10, 1, x, 1, 0, h, 1, 0, 10, 1, 0 ); // $ExpectError
+ ggradient.ndarray( 10, 1, x, 1, 0, h, 1, 0, '10', 1, 0 ); // $ExpectError
+ ggradient.ndarray( 10, 1, x, 1, 0, h, 1, 0, true, 1, 0 ); // $ExpectError
+ ggradient.ndarray( 10, 1, x, 1, 0, h, 1, 0, false, 1, 0 ); // $ExpectError
+ ggradient.ndarray( 10, 1, x, 1, 0, h, 1, 0, null, 1, 0 ); // $ExpectError
+ ggradient.ndarray( 10, 1, x, 1, 0, h, 1, 0, undefined, 1, 0 ); // $ExpectError
+ ggradient.ndarray( 10, 1, x, 1, 0, h, 1, 0, [ '1' ], 1, 0 ); // $ExpectError
+ ggradient.ndarray( 10, 1, x, 1, 0, h, 1, 0, {}, 1, 0 ); // $ExpectError
+ ggradient.ndarray( 10, 1, x, 1, 0, h, 1, 0, ( x: number ): number => x, 1, 0 ); // $ExpectError
+}
+
+// The compiler throws an error if the `ndarray` method is provided a tenth argument which is not a number...
+{
+ const x = new Float64Array( 10 );
+ const h = new Float64Array( 9 );
+ const out = new Float64Array( 10 );
+
+ ggradient.ndarray( x.length, 1, x, 1, 0, h, 1, 0, out, '10', 0 ); // $ExpectError
+ ggradient.ndarray( x.length, 1, x, 1, 0, h, 1, 0, out, true, 0 ); // $ExpectError
+ ggradient.ndarray( x.length, 1, x, 1, 0, h, 1, 0, out, false, 0 ); // $ExpectError
+ ggradient.ndarray( x.length, 1, x, 1, 0, h, 1, 0, out, null, 0 ); // $ExpectError
+ ggradient.ndarray( x.length, 1, x, 1, 0, h, 1, 0, out, undefined, 0 ); // $ExpectError
+ ggradient.ndarray( x.length, 1, x, 1, 0, h, 1, 0, out, [], 0 ); // $ExpectError
+ ggradient.ndarray( x.length, 1, x, 1, 0, h, 1, 0, out, {}, 0 ); // $ExpectError
+ ggradient.ndarray( x.length, 1, x, 1, 0, h, 1, 0, out, ( x: number ): number => x, 0 ); // $ExpectError
+}
+
+// The compiler throws an error if the `ndarray` method is provided an eleventh argument which is not a number...
+{
+ const x = new Float64Array( 10 );
+ const h = new Float64Array( 9 );
+ const out = new Float64Array( 10 );
+
+ ggradient.ndarray( x.length, 1, x, 1, 0, h, 1, 0, out, 1, '10' ); // $ExpectError
+ ggradient.ndarray( x.length, 1, x, 1, 0, h, 1, 0, out, 1, true ); // $ExpectError
+ ggradient.ndarray( x.length, 1, x, 1, 0, h, 1, 0, out, 1, false ); // $ExpectError
+ ggradient.ndarray( x.length, 1, x, 1, 0, h, 1, 0, out, 1, null ); // $ExpectError
+ ggradient.ndarray( x.length, 1, x, 1, 0, h, 1, 0, out, 1, undefined ); // $ExpectError
+ ggradient.ndarray( x.length, 1, x, 1, 0, h, 1, 0, out, 1, [] ); // $ExpectError
+ ggradient.ndarray( x.length, 1, x, 1, 0, h, 1, 0, out, 1, {} ); // $ExpectError
+ ggradient.ndarray( x.length, 1, x, 1, 0, h, 1, 0, out, 1, ( x: number ): number => x ); // $ExpectError
+}
+
+// The compiler throws an error if the `ndarray` method is provided an unsupported number of arguments...
+{
+ const x = new Float64Array( 10 );
+ const h = new Float64Array( 9 );
+ const out = new Float64Array( 10 );
+
+ ggradient.ndarray(); // $ExpectError
+ ggradient.ndarray( x.length ); // $ExpectError
+ ggradient.ndarray( x.length, 1 ); // $ExpectError
+ ggradient.ndarray( x.length, 1, x ); // $ExpectError
+ ggradient.ndarray( x.length, 1, x, 1 ); // $ExpectError
+ ggradient.ndarray( x.length, 1, x, 1, 0 ); // $ExpectError
+ ggradient.ndarray( x.length, 1, x, 1, 0, h ); // $ExpectError
+ ggradient.ndarray( x.length, 1, x, 1, 0, h, 1 ); // $ExpectError
+ ggradient.ndarray( x.length, 1, x, 1, 0, h, 1, 0 ); // $ExpectError
+ ggradient.ndarray( x.length, 1, x, 1, 0, h, 1, 0, out ); // $ExpectError
+ ggradient.ndarray( x.length, 1, x, 1, 0, h, 1, 0, out, 1 ); // $ExpectError
+ ggradient.ndarray( x.length, 1, x, 1, 0, h, 1, 0, out, 1, 0, {} ); // $ExpectError
+}
diff --git a/lib/node_modules/@stdlib/differentiate/strided/ggradient/examples/index.js b/lib/node_modules/@stdlib/differentiate/strided/ggradient/examples/index.js
new file mode 100644
index 000000000000..7ecc3f039e91
--- /dev/null
+++ b/lib/node_modules/@stdlib/differentiate/strided/ggradient/examples/index.js
@@ -0,0 +1,39 @@
+/**
+* @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 ggradient = require( './../lib' );
+
+// Approximate the gradient of f(t) = 3t^2 at t = 0, 1, 2, 3, 4 with uniform spacing...
+var x = [ 0.0, 3.0, 12.0, 27.0, 48.0 ];
+var h = [ 1.0 ];
+var out = [ 0.0, 0.0, 0.0, 0.0, 0.0 ];
+
+ggradient( x.length, 2, x, 1, h, 0, out, 1 );
+console.log( out );
+// => [ 0.0, 6.0, 12.0, 18.0, 24.0 ]
+
+// Approximate the gradient of f(t) = 3t^2 at t = 0, 1, 3, 4, 7 with non-uniform spacing...
+x = [ 0.0, 3.0, 27.0, 48.0, 147.0 ];
+h = [ 1.0, 2.0, 1.0, 3.0 ];
+out = [ 0.0, 0.0, 0.0, 0.0, 0.0 ];
+
+ggradient( x.length, 2, x, 1, h, 1, out, 1 );
+console.log( out );
+// => [ 0.0, 6.0, 18.0, 24.0, 42.0 ]
diff --git a/lib/node_modules/@stdlib/differentiate/strided/ggradient/lib/accessors.js b/lib/node_modules/@stdlib/differentiate/strided/ggradient/lib/accessors.js
new file mode 100644
index 000000000000..a46f098a1d48
--- /dev/null
+++ b/lib/node_modules/@stdlib/differentiate/strided/ggradient/lib/accessors.js
@@ -0,0 +1,152 @@
+/**
+* @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 max-params, max-len */
+
+'use strict';
+
+// MAIN //
+
+/**
+* Computes the gradient of a strided array using alternative indexing semantics and accessor arrays.
+*
+* ## Notes
+*
+* - The function supports first-order (i.e., `edgeOrder = 1`) and second-order (i.e., `edgeOrder = 2`) finite-difference approximations at the boundaries.
+*
+* @private
+* @param {PositiveInteger} N - number of indexed elements
+* @param {PositiveInteger} edgeOrder - approximation order at the boundaries
+* @param {Object} x - input array object
+* @param {Collection} x.data - input array data
+* @param {Array} x.accessors - array element accessors
+* @param {integer} strideX - stride length for `x`
+* @param {NonNegativeInteger} offsetX - starting index for `x`
+* @param {Object} h - spacing array object
+* @param {Collection} h.data - spacing array data
+* @param {Array} h.accessors - array element accessors
+* @param {integer} strideH - stride length for `h`
+* @param {NonNegativeInteger} offsetH - starting index for `h`
+* @param {Object} out - output array object
+* @param {Collection} out.data - output array data
+* @param {Array} out.accessors - array element accessors
+* @param {integer} strideOut - stride length for `out`
+* @param {NonNegativeInteger} offsetOut - starting index for `out`
+* @returns {Object} output array object
+*
+* @example
+* var toAccessorArray = require( '@stdlib/array/base/to-accessor-array' );
+* var arraylike2object = require( '@stdlib/array/base/arraylike2object' );
+*
+* var x = [ 0.0, 1.0, 9.0, 36.0, 100.0 ];
+* var h = [ 1.0, 2.0, 3.0, 4.0 ];
+* var out = [ 0.0, 0.0, 0.0, 0.0, 0.0 ];
+*
+* ggradient( x.length, 1, arraylike2object( toAccessorArray( x ) ), 1, 0, arraylike2object( toAccessorArray( h ) ), 1, 0, arraylike2object( toAccessorArray( out ) ), 1, 0 );
+*
+* console.log( out );
+* // => [ 1.0, 2.0, 6.0, 12.0, 16.0 ]
+*/
+function ggradient( N, edgeOrder, x, strideX, offsetX, h, strideH, offsetH, out, strideOut, offsetOut ) {
+ var xbuf;
+ var hbuf;
+ var obuf;
+ var xget;
+ var hget;
+ var oset;
+ var prev;
+ var curr;
+ var hL;
+ var hR;
+ var d1;
+ var d2;
+ var ix;
+ var ih;
+ var io;
+ var a;
+ var b;
+ var c;
+ var s;
+ var i;
+
+ // Cache references to array data and accessors:
+ xbuf = x.data;
+ hbuf = h.data;
+ obuf = out.data;
+ xget = x.accessors[ 0 ];
+ hget = h.accessors[ 0 ];
+ oset = out.accessors[ 1 ];
+
+ // Left boundary...
+ d1 = hget( hbuf, offsetH );
+ if ( edgeOrder >= 2 && N >= 3 ) {
+ d2 = hget( hbuf, offsetH + strideH );
+ s = d1 + d2;
+ a = -(d1 + s) / ( d1 * s );
+ b = s / ( d1 * d2 );
+ c = -d1 / ( d2 * s );
+ oset( obuf, offsetOut, ( a*xget( xbuf, offsetX ) ) + ( b*xget( xbuf, offsetX + strideX ) ) + ( c*xget( xbuf, offsetX + (2*strideX) ) ) );
+ } else {
+ oset( obuf, offsetOut, ( xget( xbuf, offsetX + strideX ) - xget( xbuf, offsetX ) ) / d1 );
+ }
+
+ // N=2: right boundary equals left boundary formula (first-order only)...
+ if ( N === 2 ) {
+ oset( obuf, offsetOut + strideOut, ( xget( xbuf, offsetX + strideX ) - xget( xbuf, offsetX ) ) / d1 );
+ return out;
+ }
+
+ // Interior points...
+ ix = offsetX + strideX;
+ ih = offsetH;
+ io = offsetOut + strideOut;
+ prev = xget( xbuf, offsetX );
+ for ( i = 1; i < N-1; i++ ) {
+ curr = xget( xbuf, ix );
+ hL = hget( hbuf, ih );
+ hR = hget( hbuf, ih + strideH );
+ s = hL + hR;
+ a = -hR / ( hL * s );
+ b = (hR - hL) / ( hL * hR );
+ c = hL / ( hR * s );
+ oset( obuf, io, ( a*prev ) + ( b*curr ) + ( c*xget( xbuf, ix + strideX ) ) );
+ prev = curr;
+ ix += strideX;
+ ih += strideH;
+ io += strideOut;
+ }
+
+ // Right boundary...
+ d2 = hget( hbuf, ih );
+ if ( edgeOrder >= 2 ) {
+ d1 = hget( hbuf, ih - strideH );
+ s = d1 + d2;
+ a = d2 / ( d1 * s );
+ b = -s / ( d1 * d2 );
+ c = (d2 + s) / ( d2 * s );
+ oset( obuf, io, ( a*xget( xbuf, ix - (2*strideX) ) ) + ( b*prev ) + ( c*xget( xbuf, ix ) ) );
+ } else {
+ oset( obuf, io, ( xget( xbuf, ix ) - prev ) / d2 );
+ }
+ return out;
+}
+
+
+// EXPORTS //
+
+module.exports = ggradient;
diff --git a/lib/node_modules/@stdlib/differentiate/strided/ggradient/lib/index.js b/lib/node_modules/@stdlib/differentiate/strided/ggradient/lib/index.js
new file mode 100644
index 000000000000..f03a5702b862
--- /dev/null
+++ b/lib/node_modules/@stdlib/differentiate/strided/ggradient/lib/index.js
@@ -0,0 +1,61 @@
+/**
+* @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';
+
+/**
+* Compute the gradient of a strided array.
+*
+* @module @stdlib/differentiate/strided/ggradient
+*
+* @example
+* var ggradient = require( '@stdlib/differentiate/strided/ggradient' );
+*
+* var x = [ 0.0, 1.0, 9.0, 36.0, 100.0 ];
+* var h = [ 1.0, 2.0, 3.0, 4.0 ];
+* var out = [ 0.0, 0.0, 0.0, 0.0, 0.0 ];
+*
+* ggradient( x.length, 1, x, 1, h, 1, out, 1 );
+* // out => [ 1.0, 2.0, 6.0, 12.0, 16.0 ]
+*
+* @example
+* var ggradient = require( '@stdlib/differentiate/strided/ggradient' );
+*
+* var x = [ 0.0, 1.0, 9.0, 36.0, 100.0 ];
+* var h = [ 1.0, 2.0, 3.0, 4.0 ];
+* var out = [ 0.0, 0.0, 0.0, 0.0, 0.0 ];
+*
+* ggradient.ndarray( x.length, 1, x, 1, 0, h, 1, 0, out, 1, 0 );
+* // out => [ 1.0, 2.0, 6.0, 12.0, 16.0 ]
+*/
+
+// MODULES //
+
+var setReadOnly = require( '@stdlib/utils/define-nonenumerable-read-only-property' );
+var main = require( './main.js' );
+var ndarray = require( './ndarray.js' );
+
+
+// MAIN //
+
+setReadOnly( main, 'ndarray', ndarray );
+
+
+// EXPORTS //
+
+module.exports = main;
diff --git a/lib/node_modules/@stdlib/differentiate/strided/ggradient/lib/main.js b/lib/node_modules/@stdlib/differentiate/strided/ggradient/lib/main.js
new file mode 100644
index 000000000000..7601cad24275
--- /dev/null
+++ b/lib/node_modules/@stdlib/differentiate/strided/ggradient/lib/main.js
@@ -0,0 +1,61 @@
+/**
+* @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 stride2offset = require( '@stdlib/strided/base/stride2offset' );
+var ndarray = require( './ndarray.js' );
+
+
+// MAIN //
+
+/**
+* Computes the gradient of a strided array.
+*
+* ## Notes
+*
+* - The function supports first-order (i.e., `edgeOrder = 1`) and second-order (i.e., `edgeOrder = 2`) finite-difference approximations at the boundaries.
+*
+* @param {PositiveInteger} N - number of indexed elements
+* @param {PositiveInteger} edgeOrder - approximation order at the boundaries
+* @param {NumericArray} x - input array
+* @param {integer} strideX - stride length for `x`
+* @param {NumericArray} h - spacing array
+* @param {integer} strideH - stride length for `h`
+* @param {NumericArray} out - output array
+* @param {integer} strideOut - stride length for `out`
+* @returns {NumericArray} output array
+*
+* @example
+* var x = [ 0.0, 1.0, 9.0, 36.0, 100.0 ];
+* var h = [ 1.0, 2.0, 3.0, 4.0 ];
+* var out = [ 0.0, 0.0, 0.0, 0.0, 0.0 ];
+*
+* ggradient( x.length, 1, x, 1, h, 1, out, 1 );
+* // out => [ 1.0, 2.0, 6.0, 12.0, 16.0 ]
+*/
+function ggradient( N, edgeOrder, x, strideX, h, strideH, out, strideOut ) {
+ return ndarray( N, edgeOrder, x, strideX, stride2offset( N, strideX ), h, strideH, stride2offset( N-1, strideH ), out, strideOut, stride2offset( N, strideOut ) ); // eslint-disable-line max-len
+}
+
+
+// EXPORTS //
+
+module.exports = ggradient;
diff --git a/lib/node_modules/@stdlib/differentiate/strided/ggradient/lib/ndarray.js b/lib/node_modules/@stdlib/differentiate/strided/ggradient/lib/ndarray.js
new file mode 100644
index 000000000000..4cbf5d43f142
--- /dev/null
+++ b/lib/node_modules/@stdlib/differentiate/strided/ggradient/lib/ndarray.js
@@ -0,0 +1,146 @@
+/**
+* @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 max-params, max-len */
+
+'use strict';
+
+// MODULES //
+
+var arraylike2object = require( '@stdlib/array/base/arraylike2object' );
+var accessors = require( './accessors.js' );
+
+
+// MAIN //
+
+/**
+* Computes the gradient of a strided array using alternative indexing semantics.
+*
+* ## Notes
+*
+* - The function supports first-order (i.e., `edgeOrder = 1`) and second-order (i.e., `edgeOrder = 2`) finite-difference approximations at the boundaries.
+*
+* @param {PositiveInteger} N - number of indexed elements
+* @param {PositiveInteger} edgeOrder - approximation order at the boundaries
+* @param {NumericArray} x - input array
+* @param {integer} strideX - stride length for `x`
+* @param {NonNegativeInteger} offsetX - starting index for `x`
+* @param {NumericArray} h - spacing array
+* @param {integer} strideH - stride length for `h`
+* @param {NonNegativeInteger} offsetH - starting index for `h`
+* @param {NumericArray} out - output array
+* @param {integer} strideOut - stride length for `out`
+* @param {NonNegativeInteger} offsetOut - starting index for `out`
+* @returns {NumericArray} output array
+*
+* @example
+* var x = [ 0.0, 1.0, 9.0, 36.0, 100.0 ];
+* var h = [ 1.0, 2.0, 3.0, 4.0 ];
+* var out = [ 0.0, 0.0, 0.0, 0.0, 0.0 ];
+*
+* ggradient( x.length, 1, x, 1, 0, h, 1, 0, out, 1, 0 );
+* // out => [ 1.0, 2.0, 6.0, 12.0, 16.0 ]
+*/
+function ggradient( N, edgeOrder, x, strideX, offsetX, h, strideH, offsetH, out, strideOut, offsetOut ) {
+ var prev;
+ var curr;
+ var xo;
+ var ho;
+ var oo;
+ var hL;
+ var hR;
+ var d1;
+ var d2;
+ var ix;
+ var ih;
+ var io;
+ var a;
+ var b;
+ var c;
+ var s;
+ var i;
+
+ if ( N <= 0 || N === 1 ) {
+ return out;
+ }
+ xo = arraylike2object( x );
+ ho = arraylike2object( h );
+ oo = arraylike2object( out );
+ if ( xo.accessorProtocol || ho.accessorProtocol || oo.accessorProtocol ) {
+ accessors( N, edgeOrder, xo, strideX, offsetX, ho, strideH, offsetH, oo, strideOut, offsetOut );
+ return out;
+ }
+
+ // Left boundary...
+ d1 = h[ offsetH ];
+ if ( edgeOrder >= 2 && N >= 3 ) {
+ d2 = h[ offsetH + strideH ];
+ s = d1 + d2;
+ a = -(d1 + s) / ( d1 * s );
+ b = s / ( d1 * d2 );
+ c = -d1 / ( d2 * s );
+ out[ offsetOut ] = ( a*x[ offsetX ] ) + ( b*x[ offsetX + strideX ] ) + ( c*x[ offsetX + (2*strideX) ] );
+ } else {
+ out[ offsetOut ] = ( x[ offsetX + strideX ] - x[ offsetX ] ) / d1;
+ }
+
+ // N=2: right boundary equals left boundary formula (first-order only)...
+ if ( N === 2 ) {
+ out[ offsetOut + strideOut ] = ( x[ offsetX + strideX ] - x[ offsetX ] ) / d1;
+ return out;
+ }
+
+ // Interior points...
+ ix = offsetX + strideX;
+ ih = offsetH;
+ io = offsetOut + strideOut;
+ prev = x[ offsetX ];
+ for ( i = 1; i < N-1; i++ ) {
+ curr = x[ ix ];
+ hL = h[ ih ];
+ hR = h[ ih + strideH ];
+ s = hL + hR;
+ a = -hR / ( hL * s );
+ b = (hR - hL) / ( hL * hR );
+ c = hL / ( hR * s );
+ out[ io ] = ( a*prev ) + ( b*curr ) + ( c*x[ ix + strideX ] );
+ prev = curr;
+ ix += strideX;
+ ih += strideH;
+ io += strideOut;
+ }
+
+ // Right boundary...
+ d2 = h[ ih ];
+ if ( edgeOrder >= 2 ) {
+ d1 = h[ ih - strideH ];
+ s = d1 + d2;
+ a = d2 / ( d1 * s );
+ b = -s / ( d1 * d2 );
+ c = (d2 + s) / ( d2 * s );
+ out[ io ] = ( a*x[ ix - (2*strideX) ] ) + ( b*prev ) + ( c*x[ ix ] );
+ } else {
+ out[ io ] = ( x[ ix ] - prev ) / d2;
+ }
+ return out;
+}
+
+
+// EXPORTS //
+
+module.exports = ggradient;
diff --git a/lib/node_modules/@stdlib/differentiate/strided/ggradient/package.json b/lib/node_modules/@stdlib/differentiate/strided/ggradient/package.json
new file mode 100644
index 000000000000..39de9037c088
--- /dev/null
+++ b/lib/node_modules/@stdlib/differentiate/strided/ggradient/package.json
@@ -0,0 +1,68 @@
+{
+ "name": "@stdlib/differentiate/strided/ggradient",
+ "version": "0.0.0",
+ "description": "Compute the gradient of a strided array.",
+ "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",
+ "stdmath",
+ "mathematics",
+ "math",
+ "differentiate",
+ "gradient",
+ "finite",
+ "difference",
+ "numerical",
+ "strided",
+ "array",
+ "vector",
+ "generic",
+ "ggradient"
+ ],
+ "__stdlib__": {}
+}
diff --git a/lib/node_modules/@stdlib/differentiate/strided/ggradient/test/test.js b/lib/node_modules/@stdlib/differentiate/strided/ggradient/test/test.js
new file mode 100644
index 000000000000..afe2f5b75e01
--- /dev/null
+++ b/lib/node_modules/@stdlib/differentiate/strided/ggradient/test/test.js
@@ -0,0 +1,38 @@
+/**
+* @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 ggradient = require( './../lib' );
+
+
+// TESTS //
+
+tape( 'main export is a function', function test( t ) {
+ t.ok( true, __filename );
+ t.strictEqual( typeof ggradient, 'function', 'main export is a function' );
+ t.end();
+});
+
+tape( 'attached to the main export is a method providing an ndarray interface', function test( t ) {
+ t.strictEqual( typeof ggradient.ndarray, 'function', 'method is a function' );
+ t.end();
+});
diff --git a/lib/node_modules/@stdlib/differentiate/strided/ggradient/test/test.main.js b/lib/node_modules/@stdlib/differentiate/strided/ggradient/test/test.main.js
new file mode 100644
index 000000000000..6a97b8d0c5ff
--- /dev/null
+++ b/lib/node_modules/@stdlib/differentiate/strided/ggradient/test/test.main.js
@@ -0,0 +1,496 @@
+/**
+* @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 toAccessorArray = require( '@stdlib/array/base/to-accessor-array' );
+var ggradient = require( './../lib/main.js' );
+
+
+// TESTS //
+
+tape( 'main export is a function', function test( t ) {
+ t.ok( true, __filename );
+ t.strictEqual( typeof ggradient, 'function', 'main export is a function' );
+ t.end();
+});
+
+tape( 'the function has an arity of 8', function test( t ) {
+ t.strictEqual( ggradient.length, 8, 'has expected arity' );
+ t.end();
+});
+
+tape( 'the function returns a reference to the output array', function test( t ) {
+ var out;
+ var x;
+ var y;
+ var h;
+
+ x = [ 1.0, 2.0, 3.0 ];
+ h = [ 1.0 ];
+ y = [ 0.0, 0.0, 0.0 ];
+
+ out = ggradient( x.length, 1, x, 1, h, 1, y, 1 );
+
+ t.strictEqual( out, y, 'same reference' );
+ t.end();
+});
+
+tape( 'the function returns a reference to the output array (accessors)', function test( t ) {
+ var out;
+ var x;
+ var y;
+ var h;
+
+ x = toAccessorArray( [ 1.0, 2.0, 3.0 ] );
+ h = toAccessorArray( [ 1.0 ] );
+ y = toAccessorArray( [ 0.0, 0.0, 0.0 ] );
+
+ out = ggradient( x.length, 1, x, 1, h, 1, y, 1 );
+
+ t.strictEqual( out, y, 'same reference' );
+ t.end();
+});
+
+tape( 'if provided an `N` parameter less than or equal to `0`, the function returns the output array unchanged', function test( t ) {
+ var expected;
+ var out;
+ var x;
+ var h;
+
+ x = [ 1.0, 2.0, 3.0 ];
+ h = [ 1.0 ];
+ out = [ 0.0, 0.0, 0.0 ];
+ expected = [ 0.0, 0.0, 0.0 ];
+
+ ggradient( 0, 1, x, 1, h, 0, out, 1 );
+
+ t.deepEqual( out, expected, 'returns expected value' );
+ t.end();
+});
+
+tape( 'if provided an `N` parameter equal to `1`, the function returns the output array unchanged', function test( t ) {
+ var expected;
+ var out;
+ var x;
+ var h;
+
+ x = [ 5.0 ];
+ h = [ 1.0 ];
+ out = [ 99.0 ];
+
+ ggradient( 1, 1, x, 1, h, 0, out, 1 );
+
+ expected = [ 99.0 ];
+ t.deepEqual( out, expected, 'returns expected value' );
+ t.end();
+});
+
+tape( 'if provided an `N` parameter equal to `1`, the function returns the output array unchanged (accessors)', function test( t ) {
+ var expected;
+ var out;
+ var x;
+ var h;
+
+ x = [ 5.0 ];
+ h = [ 1.0 ];
+ out = [ 99.0 ];
+
+ ggradient( 1, 1, toAccessorArray( x ), 1, toAccessorArray( h ), 0, toAccessorArray( out ), 1 ); // eslint-disable-line max-len
+
+ expected = [ 99.0 ];
+ t.deepEqual( out, expected, 'returns expected value' );
+ t.end();
+});
+
+tape( 'if provided an `N` parameter equal to `2`, the function computes the gradient using the first-order boundary approximation', function test( t ) {
+ var expected;
+ var out;
+ var x;
+ var h;
+
+ x = [ 2.0, 5.0 ];
+ h = [ 3.0 ];
+ out = [ 0.0, 0.0 ];
+
+ ggradient( 2, 1, x, 1, h, 0, out, 1 );
+
+ expected = [ 1.0, 1.0 ];
+ t.deepEqual( out, expected, 'returns expected value' );
+ t.end();
+});
+
+tape( 'if provided an `N` parameter equal to `2`, the function computes the gradient using the first-order boundary approximation (accessors)', function test( t ) {
+ var expected;
+ var out;
+ var x;
+ var h;
+
+ x = [ 2.0, 5.0 ];
+ h = [ 3.0 ];
+ out = [ 0.0, 0.0 ];
+
+ ggradient( 2, 1, toAccessorArray( x ), 1, toAccessorArray( h ), 0, toAccessorArray( out ), 1 ); // eslint-disable-line max-len
+
+ expected = [ 1.0, 1.0 ];
+ t.deepEqual( out, expected, 'returns expected value' );
+ t.end();
+});
+
+tape( 'if provided an `N` parameter equal to `2` and `edgeOrder` equal to `2`, the function computes the gradient using the first-order boundary approximation', function test( t ) {
+ var expected;
+ var out;
+ var x;
+ var h;
+
+ x = [ 2.0, 5.0 ];
+ h = [ 3.0 ];
+ out = [ 0.0, 0.0 ];
+
+ ggradient( 2, 2, x, 1, h, 0, out, 1 );
+
+ expected = [ 1.0, 1.0 ];
+ t.deepEqual( out, expected, 'returns expected value' );
+ t.end();
+});
+
+tape( 'if provided an `N` parameter equal to `2` and `edgeOrder` equal to `2`, the function computes the gradient using the first-order boundary approximation (accessors)', function test( t ) {
+ var expected;
+ var out;
+ var x;
+ var h;
+
+ x = [ 2.0, 5.0 ];
+ h = [ 3.0 ];
+ out = [ 0.0, 0.0 ];
+
+ ggradient( 2, 2, toAccessorArray( x ), 1, toAccessorArray( h ), 0, toAccessorArray( out ), 1 ); // eslint-disable-line max-len
+
+ expected = [ 1.0, 1.0 ];
+ t.deepEqual( out, expected, 'returns expected value' );
+ t.end();
+});
+
+tape( 'the function computes the gradient (uniform spacing, edgeOrder=1)', function test( t ) {
+ var expected;
+ var out;
+ var x;
+ var h;
+
+ x = [ 0.0, 1.0, 4.0, 9.0, 16.0 ];
+ h = [ 1.0 ];
+ out = [ 0.0, 0.0, 0.0, 0.0, 0.0 ];
+
+ ggradient( x.length, 1, x, 1, h, 0, out, 1 );
+
+ expected = [ 1.0, 2.0, 4.0, 6.0, 7.0 ];
+ t.deepEqual( out, expected, 'returns expected value' );
+ t.end();
+});
+
+tape( 'the function computes the gradient (uniform spacing, edgeOrder=1, accessors)', function test( t ) {
+ var expected;
+ var out;
+ var x;
+ var h;
+
+ x = [ 0.0, 1.0, 4.0, 9.0, 16.0 ];
+ h = [ 1.0 ];
+ out = [ 0.0, 0.0, 0.0, 0.0, 0.0 ];
+
+ ggradient( x.length, 1, toAccessorArray( x ), 1, toAccessorArray( h ), 0, toAccessorArray( out ), 1 ); // eslint-disable-line max-len
+
+ expected = [ 1.0, 2.0, 4.0, 6.0, 7.0 ];
+ t.deepEqual( out, expected, 'returns expected value' );
+ t.end();
+});
+
+tape( 'the function computes the gradient (uniform spacing, edgeOrder=2)', function test( t ) {
+ var expected;
+ var out;
+ var x;
+ var h;
+
+ x = [ 0.0, 1.0, 4.0, 9.0, 16.0 ];
+ h = [ 1.0 ];
+ out = [ 0.0, 0.0, 0.0, 0.0, 0.0 ];
+
+ ggradient( x.length, 2, x, 1, h, 0, out, 1 );
+
+ expected = [ 0.0, 2.0, 4.0, 6.0, 8.0 ];
+ t.deepEqual( out, expected, 'returns expected value' );
+ t.end();
+});
+
+tape( 'the function computes the gradient (uniform spacing, edgeOrder=2, accessors)', function test( t ) {
+ var expected;
+ var out;
+ var x;
+ var h;
+
+ x = [ 0.0, 1.0, 4.0, 9.0, 16.0 ];
+ h = [ 1.0 ];
+ out = [ 0.0, 0.0, 0.0, 0.0, 0.0 ];
+
+ ggradient( x.length, 2, toAccessorArray( x ), 1, toAccessorArray( h ), 0, toAccessorArray( out ), 1 ); // eslint-disable-line max-len
+
+ expected = [ 0.0, 2.0, 4.0, 6.0, 8.0 ];
+ t.deepEqual( out, expected, 'returns expected value' );
+ t.end();
+});
+
+tape( 'the function computes the gradient (non-uniform spacing, edgeOrder=1)', function test( t ) {
+ var expected;
+ var out;
+ var x;
+ var h;
+
+ x = [ 0.0, 12.0, 108.0, 192.0, 588.0 ];
+ h = [ 1.0, 2.0, 1.0, 3.0 ];
+ out = [ 0.0, 0.0, 0.0, 0.0, 0.0 ];
+
+ ggradient( x.length, 1, x, 1, h, 1, out, 1 );
+
+ expected = [ 12.0, 24.0, 72.0, 96.0, 132.0 ];
+ t.deepEqual( out, expected, 'returns expected value' );
+ t.end();
+});
+
+tape( 'the function computes the gradient (non-uniform spacing, edgeOrder=1, accessors)', function test( t ) {
+ var expected;
+ var out;
+ var x;
+ var h;
+
+ x = [ 0.0, 12.0, 108.0, 192.0, 588.0 ];
+ h = [ 1.0, 2.0, 1.0, 3.0 ];
+ out = [ 0.0, 0.0, 0.0, 0.0, 0.0 ];
+
+ ggradient( x.length, 1, toAccessorArray( x ), 1, toAccessorArray( h ), 1, toAccessorArray( out ), 1 ); // eslint-disable-line max-len
+
+ expected = [ 12.0, 24.0, 72.0, 96.0, 132.0 ];
+ t.deepEqual( out, expected, 'returns expected value' );
+ t.end();
+});
+
+tape( 'the function computes the gradient (non-uniform spacing, edgeOrder=2)', function test( t ) {
+ var expected;
+ var out;
+ var x;
+ var h;
+
+ x = [ 0.0, 12.0, 108.0, 192.0, 588.0 ];
+ h = [ 1.0, 2.0, 1.0, 3.0 ];
+ out = [ 0.0, 0.0, 0.0, 0.0, 0.0 ];
+
+ ggradient( x.length, 2, x, 1, h, 1, out, 1 );
+
+ expected = [ 0.0, 24.0, 72.0, 96.0, 168.0 ];
+ t.deepEqual( out, expected, 'returns expected value' );
+ t.end();
+});
+
+tape( 'the function computes the gradient (non-uniform spacing, edgeOrder=2, accessors)', function test( t ) {
+ var expected;
+ var out;
+ var x;
+ var h;
+
+ x = [ 0.0, 12.0, 108.0, 192.0, 588.0 ];
+ h = [ 1.0, 2.0, 1.0, 3.0 ];
+ out = [ 0.0, 0.0, 0.0, 0.0, 0.0 ];
+
+ ggradient( x.length, 2, toAccessorArray( x ), 1, toAccessorArray( h ), 1, toAccessorArray( out ), 1 ); // eslint-disable-line max-len
+
+ expected = [ 0.0, 24.0, 72.0, 96.0, 168.0 ];
+ t.deepEqual( out, expected, 'returns expected value' );
+ t.end();
+});
+
+tape( 'the function supports a negative `x` stride', function test( t ) {
+ var expected;
+ var out;
+ var x;
+ var h;
+
+ x = [ 16.0, 9.0, 4.0, 1.0, 0.0 ];
+ h = [ 1.0 ];
+ out = [ 0.0, 0.0, 0.0, 0.0, 0.0 ];
+
+ ggradient( x.length, 1, x, -1, h, 0, out, 1 );
+
+ expected = [ 1.0, 2.0, 4.0, 6.0, 7.0 ];
+ t.deepEqual( out, expected, 'returns expected value' );
+ t.end();
+});
+
+tape( 'the function supports a negative `x` stride (accessors)', function test( t ) {
+ var expected;
+ var out;
+ var x;
+ var h;
+
+ x = [ 16.0, 9.0, 4.0, 1.0, 0.0 ];
+ h = [ 1.0 ];
+ out = [ 0.0, 0.0, 0.0, 0.0, 0.0 ];
+
+ ggradient( x.length, 1, toAccessorArray( x ), -1, toAccessorArray( h ), 0, toAccessorArray( out ), 1 ); // eslint-disable-line max-len
+
+ expected = [ 1.0, 2.0, 4.0, 6.0, 7.0 ];
+ t.deepEqual( out, expected, 'returns expected value' );
+ t.end();
+});
+
+tape( 'the function supports a negative output stride', function test( t ) {
+ var expected;
+ var out;
+ var x;
+ var h;
+
+ x = [ 0.0, 1.0, 4.0, 9.0, 16.0 ];
+ h = [ 1.0 ];
+ out = [ 0.0, 0.0, 0.0, 0.0, 0.0 ];
+
+ ggradient( x.length, 1, x, 1, h, 0, out, -1 );
+
+ expected = [ 7.0, 6.0, 4.0, 2.0, 1.0 ];
+ t.deepEqual( out, expected, 'returns expected value' );
+ t.end();
+});
+
+tape( 'the function supports a negative output stride (accessors)', function test( t ) {
+ var expected;
+ var out;
+ var x;
+ var h;
+
+ x = [ 0.0, 1.0, 4.0, 9.0, 16.0 ];
+ h = [ 1.0 ];
+ out = [ 0.0, 0.0, 0.0, 0.0, 0.0 ];
+
+ ggradient( x.length, 1, toAccessorArray( x ), 1, toAccessorArray( h ), 0, toAccessorArray( out ), -1 ); // eslint-disable-line max-len
+
+ expected = [ 7.0, 6.0, 4.0, 2.0, 1.0 ];
+ t.deepEqual( out, expected, 'returns expected value' );
+ t.end();
+});
+
+tape( 'the function supports non-unit strides', function test( t ) {
+ var expected;
+ var out;
+ var x;
+ var h;
+
+ x = [ 0.0, -1.0, 1.0, -1.0, 4.0, -1.0, 9.0, -1.0, 16.0 ];
+ h = [ 1.0 ];
+ out = [ 0.0, -1.0, 0.0, -1.0, 0.0, -1.0, 0.0, -1.0, 0.0 ];
+
+ ggradient( 5, 1, x, 2, h, 0, out, 2 );
+
+ expected = [ 1.0, -1.0, 2.0, -1.0, 4.0, -1.0, 6.0, -1.0, 7.0 ];
+ t.deepEqual( out, expected, 'returns expected value' );
+ t.end();
+});
+
+tape( 'the function supports non-unit strides (accessors)', function test( t ) {
+ var expected;
+ var out;
+ var x;
+ var h;
+
+ x = [ 0.0, -1.0, 1.0, -1.0, 4.0, -1.0, 9.0, -1.0, 16.0 ];
+ h = [ 1.0 ];
+ out = [ 0.0, -1.0, 0.0, -1.0, 0.0, -1.0, 0.0, -1.0, 0.0 ];
+
+ ggradient( 5, 1, toAccessorArray( x ), 2, toAccessorArray( h ), 0, toAccessorArray( out ), 2 ); // eslint-disable-line max-len
+
+ expected = [ 1.0, -1.0, 2.0, -1.0, 4.0, -1.0, 6.0, -1.0, 7.0 ];
+ t.deepEqual( out, expected, 'returns expected value' );
+ t.end();
+});
+
+tape( 'the function supports a zero `x` stride', function test( t ) {
+ var expected;
+ var out;
+ var x;
+ var h;
+
+ x = [ 5.0 ];
+ h = [ 1.0 ];
+ out = [ 0.0, 0.0, 0.0, 0.0, 0.0 ];
+
+ ggradient( 5, 1, x, 0, h, 0, out, 1 );
+
+ expected = [ 0.0, 0.0, 0.0, 0.0, 0.0 ];
+ t.deepEqual( out, expected, 'returns expected value' );
+ t.end();
+});
+
+tape( 'the function supports a zero `x` stride (accessors)', function test( t ) {
+ var expected;
+ var out;
+ var x;
+ var h;
+
+ x = [ 5.0 ];
+ h = [ 1.0 ];
+ out = [ 0.0, 0.0, 0.0, 0.0, 0.0 ];
+
+ ggradient( 5, 1, toAccessorArray( x ), 0, toAccessorArray( h ), 0, toAccessorArray( out ), 1 ); // eslint-disable-line max-len
+
+ expected = [ 0.0, 0.0, 0.0, 0.0, 0.0 ];
+ t.deepEqual( out, expected, 'returns expected value' );
+ t.end();
+});
+
+tape( 'the function supports a non-unit `h` stride', function test( t ) {
+ var expected;
+ var out;
+ var x;
+ var h;
+
+ x = [ 0.0, 12.0, 108.0, 192.0, 588.0 ];
+ h = [ 1.0, -1.0, 2.0, -1.0, 1.0, -1.0, 3.0 ];
+ out = [ 0.0, 0.0, 0.0, 0.0, 0.0 ];
+
+ ggradient( x.length, 1, x, 1, h, 2, out, 1 );
+
+ expected = [ 12.0, 24.0, 72.0, 96.0, 132.0 ];
+ t.deepEqual( out, expected, 'returns expected value' );
+ t.end();
+});
+
+tape( 'the function supports a non-unit `h` stride (accessors)', function test( t ) {
+ var expected;
+ var out;
+ var x;
+ var h;
+
+ x = [ 0.0, 12.0, 108.0, 192.0, 588.0 ];
+ h = [ 1.0, -1.0, 2.0, -1.0, 1.0, -1.0, 3.0 ];
+ out = [ 0.0, 0.0, 0.0, 0.0, 0.0 ];
+
+ ggradient( x.length, 1, toAccessorArray( x ), 1, toAccessorArray( h ), 2, toAccessorArray( out ), 1 ); // eslint-disable-line max-len
+
+ expected = [ 12.0, 24.0, 72.0, 96.0, 132.0 ];
+ t.deepEqual( out, expected, 'returns expected value' );
+ t.end();
+});
diff --git a/lib/node_modules/@stdlib/differentiate/strided/ggradient/test/test.ndarray.js b/lib/node_modules/@stdlib/differentiate/strided/ggradient/test/test.ndarray.js
new file mode 100644
index 000000000000..e48f455ab758
--- /dev/null
+++ b/lib/node_modules/@stdlib/differentiate/strided/ggradient/test/test.ndarray.js
@@ -0,0 +1,496 @@
+/**
+* @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 toAccessorArray = require( '@stdlib/array/base/to-accessor-array' );
+var ggradient = require( './../lib/ndarray.js' );
+
+
+// TESTS //
+
+tape( 'main export is a function', function test( t ) {
+ t.ok( true, __filename );
+ t.strictEqual( typeof ggradient, 'function', 'main export is a function' );
+ t.end();
+});
+
+tape( 'the function has an arity of 11', function test( t ) {
+ t.strictEqual( ggradient.length, 11, 'has expected arity' );
+ t.end();
+});
+
+tape( 'the function returns a reference to the output array', function test( t ) {
+ var out;
+ var x;
+ var y;
+ var h;
+
+ x = [ 1.0, 2.0, 3.0 ];
+ h = [ 1.0 ];
+ y = [ 0.0, 0.0, 0.0 ];
+
+ out = ggradient( x.length, 1, x, 1, 0, h, 0, 0, y, 1, 0 );
+
+ t.strictEqual( out, y, 'same reference' );
+ t.end();
+});
+
+tape( 'the function returns a reference to the output array (accessors)', function test( t ) {
+ var out;
+ var x;
+ var y;
+ var h;
+
+ x = toAccessorArray( [ 1.0, 2.0, 3.0 ] );
+ h = toAccessorArray( [ 1.0 ] );
+ y = toAccessorArray( [ 0.0, 0.0, 0.0 ] );
+
+ out = ggradient( x.length, 1, x, 1, 0, h, 0, 0, y, 1, 0 );
+
+ t.strictEqual( out, y, 'same reference' );
+ t.end();
+});
+
+tape( 'if provided an `N` parameter less than or equal to `0`, the function returns the output array unchanged', function test( t ) {
+ var expected;
+ var out;
+ var x;
+ var h;
+
+ x = [ 1.0, 2.0, 3.0 ];
+ h = [ 1.0 ];
+ out = [ 0.0, 0.0, 0.0 ];
+ expected = [ 0.0, 0.0, 0.0 ];
+
+ ggradient( 0, 1, x, 1, 0, h, 0, 0, out, 1, 0 );
+
+ t.deepEqual( out, expected, 'returns expected value' );
+ t.end();
+});
+
+tape( 'if provided an `N` parameter equal to `1`, the function returns the output array unchanged', function test( t ) {
+ var expected;
+ var out;
+ var x;
+ var h;
+
+ x = [ 5.0 ];
+ h = [ 1.0 ];
+ out = [ 99.0 ];
+
+ ggradient( 1, 1, x, 1, 0, h, 0, 0, out, 1, 0 );
+
+ expected = [ 99.0 ];
+ t.deepEqual( out, expected, 'returns expected value' );
+ t.end();
+});
+
+tape( 'if provided an `N` parameter equal to `1`, the function returns the output array unchanged (accessors)', function test( t ) {
+ var expected;
+ var out;
+ var x;
+ var h;
+
+ x = [ 5.0 ];
+ h = [ 1.0 ];
+ out = [ 99.0 ];
+
+ ggradient( 1, 1, toAccessorArray( x ), 1, 0, toAccessorArray( h ), 0, 0, toAccessorArray( out ), 1, 0 ); // eslint-disable-line max-len
+
+ expected = [ 99.0 ];
+ t.deepEqual( out, expected, 'returns expected value' );
+ t.end();
+});
+
+tape( 'if provided an `N` parameter equal to `2`, the function computes the gradient using the first-order boundary approximation', function test( t ) {
+ var expected;
+ var out;
+ var x;
+ var h;
+
+ x = [ 2.0, 5.0 ];
+ h = [ 3.0 ];
+ out = [ 0.0, 0.0 ];
+
+ ggradient( 2, 1, x, 1, 0, h, 0, 0, out, 1, 0 );
+
+ expected = [ 1.0, 1.0 ];
+ t.deepEqual( out, expected, 'returns expected value' );
+ t.end();
+});
+
+tape( 'if provided an `N` parameter equal to `2`, the function computes the gradient using the first-order boundary approximation (accessors)', function test( t ) {
+ var expected;
+ var out;
+ var x;
+ var h;
+
+ x = [ 2.0, 5.0 ];
+ h = [ 3.0 ];
+ out = [ 0.0, 0.0 ];
+
+ ggradient( 2, 1, toAccessorArray( x ), 1, 0, toAccessorArray( h ), 0, 0, toAccessorArray( out ), 1, 0 ); // eslint-disable-line max-len
+
+ expected = [ 1.0, 1.0 ];
+ t.deepEqual( out, expected, 'returns expected value' );
+ t.end();
+});
+
+tape( 'if provided an `N` parameter equal to `2` and `edgeOrder` equal to `2`, the function computes the gradient using the first-order boundary approximation', function test( t ) {
+ var expected;
+ var out;
+ var x;
+ var h;
+
+ x = [ 2.0, 5.0 ];
+ h = [ 3.0 ];
+ out = [ 0.0, 0.0 ];
+
+ ggradient( 2, 2, x, 1, 0, h, 0, 0, out, 1, 0 );
+
+ expected = [ 1.0, 1.0 ];
+ t.deepEqual( out, expected, 'returns expected value' );
+ t.end();
+});
+
+tape( 'if provided an `N` parameter equal to `2` and `edgeOrder` equal to `2`, the function computes the gradient using the first-order boundary approximation (accessors)', function test( t ) {
+ var expected;
+ var out;
+ var x;
+ var h;
+
+ x = [ 2.0, 5.0 ];
+ h = [ 3.0 ];
+ out = [ 0.0, 0.0 ];
+
+ ggradient( 2, 2, toAccessorArray( x ), 1, 0, toAccessorArray( h ), 0, 0, toAccessorArray( out ), 1, 0 ); // eslint-disable-line max-len
+
+ expected = [ 1.0, 1.0 ];
+ t.deepEqual( out, expected, 'returns expected value' );
+ t.end();
+});
+
+tape( 'the function computes the gradient (uniform spacing, edgeOrder=1)', function test( t ) {
+ var expected;
+ var out;
+ var x;
+ var h;
+
+ x = [ 0.0, 1.0, 4.0, 9.0, 16.0 ];
+ h = [ 1.0 ];
+ out = [ 0.0, 0.0, 0.0, 0.0, 0.0 ];
+
+ ggradient( x.length, 1, x, 1, 0, h, 0, 0, out, 1, 0 );
+
+ expected = [ 1.0, 2.0, 4.0, 6.0, 7.0 ];
+ t.deepEqual( out, expected, 'returns expected value' );
+ t.end();
+});
+
+tape( 'the function computes the gradient (uniform spacing, edgeOrder=1, accessors)', function test( t ) {
+ var expected;
+ var out;
+ var x;
+ var h;
+
+ x = [ 0.0, 1.0, 4.0, 9.0, 16.0 ];
+ h = [ 1.0 ];
+ out = [ 0.0, 0.0, 0.0, 0.0, 0.0 ];
+
+ ggradient( x.length, 1, toAccessorArray( x ), 1, 0, toAccessorArray( h ), 0, 0, toAccessorArray( out ), 1, 0 ); // eslint-disable-line max-len
+
+ expected = [ 1.0, 2.0, 4.0, 6.0, 7.0 ];
+ t.deepEqual( out, expected, 'returns expected value' );
+ t.end();
+});
+
+tape( 'the function computes the gradient (uniform spacing, edgeOrder=2)', function test( t ) {
+ var expected;
+ var out;
+ var x;
+ var h;
+
+ x = [ 0.0, 1.0, 4.0, 9.0, 16.0 ];
+ h = [ 1.0 ];
+ out = [ 0.0, 0.0, 0.0, 0.0, 0.0 ];
+
+ ggradient( x.length, 2, x, 1, 0, h, 0, 0, out, 1, 0 );
+
+ expected = [ 0.0, 2.0, 4.0, 6.0, 8.0 ];
+ t.deepEqual( out, expected, 'returns expected value' );
+ t.end();
+});
+
+tape( 'the function computes the gradient (uniform spacing, edgeOrder=2, accessors)', function test( t ) {
+ var expected;
+ var out;
+ var x;
+ var h;
+
+ x = [ 0.0, 1.0, 4.0, 9.0, 16.0 ];
+ h = [ 1.0 ];
+ out = [ 0.0, 0.0, 0.0, 0.0, 0.0 ];
+
+ ggradient( x.length, 2, toAccessorArray( x ), 1, 0, toAccessorArray( h ), 0, 0, toAccessorArray( out ), 1, 0 ); // eslint-disable-line max-len
+
+ expected = [ 0.0, 2.0, 4.0, 6.0, 8.0 ];
+ t.deepEqual( out, expected, 'returns expected value' );
+ t.end();
+});
+
+tape( 'the function computes the gradient (non-uniform spacing, edgeOrder=1)', function test( t ) {
+ var expected;
+ var out;
+ var x;
+ var h;
+
+ x = [ 0.0, 12.0, 108.0, 192.0, 588.0 ];
+ h = [ 1.0, 2.0, 1.0, 3.0 ];
+ out = [ 0.0, 0.0, 0.0, 0.0, 0.0 ];
+
+ ggradient( x.length, 1, x, 1, 0, h, 1, 0, out, 1, 0 );
+
+ expected = [ 12.0, 24.0, 72.0, 96.0, 132.0 ];
+ t.deepEqual( out, expected, 'returns expected value' );
+ t.end();
+});
+
+tape( 'the function computes the gradient (non-uniform spacing, edgeOrder=1, accessors)', function test( t ) {
+ var expected;
+ var out;
+ var x;
+ var h;
+
+ x = [ 0.0, 12.0, 108.0, 192.0, 588.0 ];
+ h = [ 1.0, 2.0, 1.0, 3.0 ];
+ out = [ 0.0, 0.0, 0.0, 0.0, 0.0 ];
+
+ ggradient( x.length, 1, toAccessorArray( x ), 1, 0, toAccessorArray( h ), 1, 0, toAccessorArray( out ), 1, 0 ); // eslint-disable-line max-len
+
+ expected = [ 12.0, 24.0, 72.0, 96.0, 132.0 ];
+ t.deepEqual( out, expected, 'returns expected value' );
+ t.end();
+});
+
+tape( 'the function computes the gradient (non-uniform spacing, edgeOrder=2)', function test( t ) {
+ var expected;
+ var out;
+ var x;
+ var h;
+
+ x = [ 0.0, 12.0, 108.0, 192.0, 588.0 ];
+ h = [ 1.0, 2.0, 1.0, 3.0 ];
+ out = [ 0.0, 0.0, 0.0, 0.0, 0.0 ];
+
+ ggradient( x.length, 2, x, 1, 0, h, 1, 0, out, 1, 0 );
+
+ expected = [ 0.0, 24.0, 72.0, 96.0, 168.0 ];
+ t.deepEqual( out, expected, 'returns expected value' );
+ t.end();
+});
+
+tape( 'the function computes the gradient (non-uniform spacing, edgeOrder=2, accessors)', function test( t ) {
+ var expected;
+ var out;
+ var x;
+ var h;
+
+ x = [ 0.0, 12.0, 108.0, 192.0, 588.0 ];
+ h = [ 1.0, 2.0, 1.0, 3.0 ];
+ out = [ 0.0, 0.0, 0.0, 0.0, 0.0 ];
+
+ ggradient( x.length, 2, toAccessorArray( x ), 1, 0, toAccessorArray( h ), 1, 0, toAccessorArray( out ), 1, 0 ); // eslint-disable-line max-len
+
+ expected = [ 0.0, 24.0, 72.0, 96.0, 168.0 ];
+ t.deepEqual( out, expected, 'returns expected value' );
+ t.end();
+});
+
+tape( 'the function supports index offsets', function test( t ) {
+ var expected;
+ var out;
+ var x;
+ var h;
+
+ x = [ -1.0, -1.0, 0.0, 1.0, 4.0, 9.0, 16.0 ];
+ h = [ 1.0 ];
+ out = [ -1.0, -1.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];
+
+ ggradient( 5, 1, x, 1, 2, h, 0, 0, out, 1, 2 );
+
+ expected = [ -1.0, -1.0, 1.0, 2.0, 4.0, 6.0, 7.0 ];
+ t.deepEqual( out, expected, 'returns expected value' );
+ t.end();
+});
+
+tape( 'the function supports index offsets (accessors)', function test( t ) {
+ var expected;
+ var out;
+ var x;
+ var h;
+
+ x = [ -1.0, -1.0, 0.0, 1.0, 4.0, 9.0, 16.0 ];
+ h = [ 1.0 ];
+ out = [ -1.0, -1.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];
+
+ ggradient( 5, 1, toAccessorArray( x ), 1, 2, toAccessorArray( h ), 0, 0, toAccessorArray( out ), 1, 2 ); // eslint-disable-line max-len
+
+ expected = [ -1.0, -1.0, 1.0, 2.0, 4.0, 6.0, 7.0 ];
+ t.deepEqual( out, expected, 'returns expected value' );
+ t.end();
+});
+
+tape( 'the function supports negative strides', function test( t ) {
+ var expected;
+ var out;
+ var x;
+ var h;
+
+ x = [ 16.0, 9.0, 4.0, 1.0, 0.0 ];
+ h = [ 1.0 ];
+ out = [ 0.0, 0.0, 0.0, 0.0, 0.0 ];
+
+ ggradient( 5, 1, x, -1, 4, h, 0, 0, out, -1, 4 );
+
+ expected = [ 7.0, 6.0, 4.0, 2.0, 1.0 ];
+ t.deepEqual( out, expected, 'returns expected value' );
+ t.end();
+});
+
+tape( 'the function supports negative strides (accessors)', function test( t ) {
+ var expected;
+ var out;
+ var x;
+ var h;
+
+ x = [ 16.0, 9.0, 4.0, 1.0, 0.0 ];
+ h = [ 1.0 ];
+ out = [ 0.0, 0.0, 0.0, 0.0, 0.0 ];
+
+ ggradient( 5, 1, toAccessorArray( x ), -1, 4, toAccessorArray( h ), 0, 0, toAccessorArray( out ), -1, 4 ); // eslint-disable-line max-len
+
+ expected = [ 7.0, 6.0, 4.0, 2.0, 1.0 ];
+ t.deepEqual( out, expected, 'returns expected value' );
+ t.end();
+});
+
+tape( 'the function supports a zero `x` stride', function test( t ) {
+ var expected;
+ var out;
+ var x;
+ var h;
+
+ x = [ 5.0 ];
+ h = [ 1.0 ];
+ out = [ 0.0, 0.0, 0.0, 0.0, 0.0 ];
+
+ ggradient( 5, 1, x, 0, 0, h, 0, 0, out, 1, 0 );
+
+ expected = [ 0.0, 0.0, 0.0, 0.0, 0.0 ];
+ t.deepEqual( out, expected, 'returns expected value' );
+ t.end();
+});
+
+tape( 'the function supports a zero `x` stride (accessors)', function test( t ) {
+ var expected;
+ var out;
+ var x;
+ var h;
+
+ x = [ 5.0 ];
+ h = [ 1.0 ];
+ out = [ 0.0, 0.0, 0.0, 0.0, 0.0 ];
+
+ ggradient( 5, 1, toAccessorArray( x ), 0, 0, toAccessorArray( h ), 0, 0, toAccessorArray( out ), 1, 0 ); // eslint-disable-line max-len
+
+ expected = [ 0.0, 0.0, 0.0, 0.0, 0.0 ];
+ t.deepEqual( out, expected, 'returns expected value' );
+ t.end();
+});
+
+tape( 'the function supports a non-unit `h` stride', function test( t ) {
+ var expected;
+ var out;
+ var x;
+ var h;
+
+ x = [ 0.0, 12.0, 108.0, 192.0, 588.0 ];
+ h = [ 1.0, -1.0, 2.0, -1.0, 1.0, -1.0, 3.0 ];
+ out = [ 0.0, 0.0, 0.0, 0.0, 0.0 ];
+
+ ggradient( x.length, 1, x, 1, 0, h, 2, 0, out, 1, 0 );
+
+ expected = [ 12.0, 24.0, 72.0, 96.0, 132.0 ];
+ t.deepEqual( out, expected, 'returns expected value' );
+ t.end();
+});
+
+tape( 'the function supports a non-unit `h` stride (accessors)', function test( t ) {
+ var expected;
+ var out;
+ var x;
+ var h;
+
+ x = [ 0.0, 12.0, 108.0, 192.0, 588.0 ];
+ h = [ 1.0, -1.0, 2.0, -1.0, 1.0, -1.0, 3.0 ];
+ out = [ 0.0, 0.0, 0.0, 0.0, 0.0 ];
+
+ ggradient( x.length, 1, toAccessorArray( x ), 1, 0, toAccessorArray( h ), 2, 0, toAccessorArray( out ), 1, 0 ); // eslint-disable-line max-len
+
+ expected = [ 12.0, 24.0, 72.0, 96.0, 132.0 ];
+ t.deepEqual( out, expected, 'returns expected value' );
+ t.end();
+});
+
+tape( 'the function supports an `h` offset', function test( t ) {
+ var expected;
+ var out;
+ var x;
+ var h;
+
+ x = [ 0.0, 12.0, 108.0, 192.0, 588.0 ];
+ h = [ -1.0, 1.0, 2.0, 1.0, 3.0 ];
+ out = [ 0.0, 0.0, 0.0, 0.0, 0.0 ];
+
+ ggradient( x.length, 1, x, 1, 0, h, 1, 1, out, 1, 0 );
+
+ expected = [ 12.0, 24.0, 72.0, 96.0, 132.0 ];
+ t.deepEqual( out, expected, 'returns expected value' );
+ t.end();
+});
+
+tape( 'the function supports an `h` offset (accessors)', function test( t ) {
+ var expected;
+ var out;
+ var x;
+ var h;
+
+ x = [ 0.0, 12.0, 108.0, 192.0, 588.0 ];
+ h = [ -1.0, 1.0, 2.0, 1.0, 3.0 ];
+ out = [ 0.0, 0.0, 0.0, 0.0, 0.0 ];
+
+ ggradient( x.length, 1, toAccessorArray( x ), 1, 0, toAccessorArray( h ), 1, 1, toAccessorArray( out ), 1, 0 ); // eslint-disable-line max-len
+
+ expected = [ 12.0, 24.0, 72.0, 96.0, 132.0 ];
+ t.deepEqual( out, expected, 'returns expected value' );
+ t.end();
+});