diff --git a/lib/node_modules/@stdlib/stats/strided/distances/dcosine-similarity/README.md b/lib/node_modules/@stdlib/stats/strided/distances/dcosine-similarity/README.md
new file mode 100644
index 000000000000..ec5817daf035
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/strided/distances/dcosine-similarity/README.md
@@ -0,0 +1,338 @@
+
+
+# dcosineSimilarity
+
+> Compute the cosine similarity of two double-precision floating-point strided arrays.
+
+
+
+The [cosine similarity][wikipedia-cosine-similarity] is defined as
+
+
+
+```math
+sim = \frac{A \cdot B}{\|A\| \, \|B\|}
+```
+
+
+
+
+
+
+
+
+
+
+
+## Usage
+
+```javascript
+var dcosineSimilarity = require( '@stdlib/stats/strided/distances/dcosine-similarity' );
+```
+
+#### dcosineSimilarity( N, x, strideX, y, strideY )
+
+Computes the cosine similarity of two double-precision floating-point strided arrays.
+
+```javascript
+var Float64Array = require( '@stdlib/array/float64' );
+
+var x = new Float64Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] );
+var y = new Float64Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] );
+
+var z = dcosineSimilarity( x.length, x, 1, y, 1 );
+// returns ~-0.061
+```
+
+The function has the following parameters:
+
+- **N**: number of indexed elements.
+- **x**: input [`Float64Array`][@stdlib/array/float64].
+- **strideX**: stride length of `x`.
+- **y**: input [`Float64Array`][@stdlib/array/float64].
+- **strideY**: stride length of `y`.
+
+The `N` and stride parameters determine which elements in the strided arrays are accessed at runtime. For example, to calculate the cosine similarity of every other value in `x` and the first `N` elements of `y` in reverse order,
+
+```javascript
+var Float64Array = require( '@stdlib/array/float64' );
+
+var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );
+var y = new Float64Array( [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ] );
+
+var z = dcosineSimilarity( 3, x, 2, y, -1 );
+// returns ~0.878
+```
+
+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 x0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );
+var y0 = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );
+
+// Create offset views...
+var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element
+var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 ); // start at 4th element
+
+var z = dcosineSimilarity( 3, x1, 1, y1, 1 );
+// returns ~0.982
+```
+
+#### dcosineSimilarity.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )
+
+Computes the cosine similarity of two double-precision floating-point strided arrays using alternative indexing semantics.
+
+```javascript
+var Float64Array = require( '@stdlib/array/float64' );
+
+var x = new Float64Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] );
+var y = new Float64Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] );
+
+var z = dcosineSimilarity.ndarray( x.length, x, 1, 0, y, 1, 0 );
+// returns ~-0.061
+```
+
+The function has the following additional parameters:
+
+- **offsetX**: starting index for `x`.
+- **offsetY**: starting index for `y`.
+
+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 calculate the cosine similarity of every other value in `x` starting from the second value with the last 3 elements in `y` in reverse order
+
+```javascript
+var Float64Array = require( '@stdlib/array/float64' );
+
+var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );
+var y = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );
+
+var z = dcosineSimilarity.ndarray( 3, x, 2, 1, y, -1, y.length-1 );
+// returns ~0.895
+```
+
+
+
+
+
+
+
+## Notes
+
+- If `N <= 0`, both functions return `0.0`.
+
+
+
+
+
+
+
+## Examples
+
+
+
+```javascript
+var discreteUniform = require( '@stdlib/random/array/discrete-uniform' );
+var dcosineSimilarity = require( '@stdlib/stats/strided/distances/dcosine-similarity' );
+
+var opts = {
+ 'dtype': 'float64'
+};
+var x = discreteUniform( 10, 0, 100, opts );
+console.log( x );
+
+var y = discreteUniform( x.length, 0, 10, opts );
+console.log( y );
+
+var out = dcosineSimilarity.ndarray( x.length, x, 1, 0, y, -1, y.length-1 );
+console.log( out );
+```
+
+
+
+
+
+
+
+* * *
+
+
+
+## C APIs
+
+
+
+
+
+
+
+
+
+
+
+### Usage
+
+```c
+#include "stdlib/stats/strided/distances/dcosine_similarity.h"
+```
+
+#### stdlib_strided_dcosine_similarity( N, \*X, strideX, \*Y, strideY )
+
+Computes the cosine similarity of two double-precision floating-point strided arrays.
+
+```c
+const double x[] = { 4.0, 2.0, -3.0, 5.0, -1.0 };
+const double y[] = { 2.0, 6.0, -1.0, -4.0, 8.0 };
+
+double v = stdlib_strided_dcosine_similarity( 5, x, 1, y, 1 );
+// returns ~-0.061
+```
+
+The function accepts the following arguments:
+
+- **N**: `[in] CBLAS_INT` number of indexed elements.
+- **X**: `[in] double*` first input array.
+- **strideX**: `[in] CBLAS_INT` stride length of `X`.
+- **Y**: `[in] double*` second input array.
+- **strideY**: `[in] CBLAS_INT` stride length of `Y`.
+
+```c
+double stdlib_strided_dcosine_similarity( const CBLAS_INT N, const double *X, const CBLAS_INT strideX, const double *Y, const CBLAS_INT strideY );
+```
+
+
+
+#### stdlib_strided_dcosine_similarity_ndarray( N, \*X, strideX, offsetX, \*Y, strideY, offsetY )
+
+
+
+Computes the cosine similarity of two double-precision floating-point strided arrays using alternative indexing semantics.
+
+```c
+const double x[] = { 4.0, 2.0, -3.0, 5.0, -1.0 };
+const double y[] = { 2.0, 6.0, -1.0, -4.0, 8.0 };
+
+double v = stdlib_strided_dcosine_similarity_ndarray( 5, x, -1, 4, y, -1, 4 );
+// returns ~0.061
+```
+
+The function accepts the following arguments:
+
+- **N**: `[in] CBLAS_INT` number of indexed elements.
+- **X**: `[in] double*` first input array.
+- **strideX**: `[in] CBLAS_INT` stride length of `X`.
+- **offsetX**: `[in] CBLAS_INT` starting index for `X`.
+- **Y**: `[in] double*` second input array.
+- **strideY**: `[in] CBLAS_INT` stride length of `Y`.
+- **offsetY**: `[in] CBLAS_INT` starting index for `Y`.
+
+```c
+double stdlib_strided_dcosine_similarity_ndarray( const CBLAS_INT N, const double *X, const CBLAS_INT strideX, const CBLAS_INT offsetX, const double *Y, const CBLAS_INT strideY, const CBLAS_INT offsetY );
+```
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+### Examples
+
+```c
+#include "stdlib/stats/strided/distances/dcosine_similarity.h"
+#include
+
+int main( void ) {
+ // Create strided arrays:
+ const double x[] = { 1.0, -2.0, 3.0, -4.0, 5.0, -6.0, 7.0, -8.0 };
+ const double y[] = { 1.0, -2.0, 3.0, -4.0, 5.0, -6.0, 7.0, -8.0 };
+
+ // Specify the number of elements:
+ const int N = 8;
+
+ // Specify strides:
+ const int strideX = 1;
+ const int strideY = -1;
+
+ // Compute the cosine similarity of `x` and `y`:
+ double sim = stdlib_strided_dcosine_similarity( N, x, strideX, y, strideY );
+
+ // Print the result:
+ printf( "cosine similarity: %lf\n", sim );
+
+ // Compute the cosine similarity of `x` and `y` with offsets:
+ sim = stdlib_strided_dcosine_similarity_ndarray( N, x, strideX, 0, y, strideY, N-1 );
+
+ // Print the result:
+ printf( "cosine similarity: %lf\n", sim );
+}
+```
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+[@stdlib/array/float64]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/array/float64
+
+[mdn-typed-array]: https://developer.mozilla.org/en-US/docs/Web/JavaScript/Reference/Global_Objects/TypedArray
+
+[wikipedia-cosine-similarity]: https://en.wikipedia.org/wiki/Cosine_similarity
+
+
+
+
+
+
+
+
diff --git a/lib/node_modules/@stdlib/stats/strided/distances/dcosine-similarity/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/strided/distances/dcosine-similarity/benchmark/benchmark.js
new file mode 100644
index 000000000000..52eb393f23c7
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/strided/distances/dcosine-similarity/benchmark/benchmark.js
@@ -0,0 +1,98 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+* http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+'use strict';
+
+// MODULES //
+
+var bench = require( '@stdlib/bench' );
+var 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 dcosineSimilarity = require( './../lib/dcosine_similarity.js' );
+
+
+// VARIABLES //
+
+var options = {
+ 'dtype': 'float64'
+};
+
+
+// FUNCTIONS //
+
+/**
+* Creates a benchmark function.
+*
+* @private
+* @param {PositiveInteger} len - array length
+* @returns {Function} benchmark function
+*/
+function createBenchmark( len ) {
+ var x = uniform( len, -100.0, 100.0, options );
+ var y = uniform( len, -100.0, 100.0, options );
+ return benchmark;
+
+ function benchmark( b ) {
+ var d;
+ var i;
+
+ b.tic();
+ for ( i = 0; i < b.iterations; i++ ) {
+ d = dcosineSimilarity( x.length, x, 1, y, 1 );
+ if ( isnan( d ) ) {
+ b.fail( 'should not return NaN' );
+ }
+ }
+ b.toc();
+ if ( isnan( d ) ) {
+ 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:len=%d', pkg, len ), f );
+ }
+}
+
+main();
diff --git a/lib/node_modules/@stdlib/stats/strided/distances/dcosine-similarity/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/stats/strided/distances/dcosine-similarity/benchmark/benchmark.native.js
new file mode 100644
index 000000000000..43e5b60d0046
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/strided/distances/dcosine-similarity/benchmark/benchmark.native.js
@@ -0,0 +1,103 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+* http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+'use strict';
+
+// MODULES //
+
+var resolve = require( 'path' ).resolve;
+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 tryRequire = require( '@stdlib/utils/try-require' );
+var format = require( '@stdlib/string/format' );
+var pkg = require( './../package.json' ).name;
+
+
+// VARIABLES //
+
+var dcosineSimilarity = tryRequire( resolve( __dirname, './../lib/dcosine_similarity.native.js' ) );
+var opts = {
+ 'skip': ( dcosineSimilarity instanceof Error )
+};
+var options = {
+ 'dtype': 'float64'
+};
+
+
+// FUNCTIONS //
+
+/**
+* Creates a benchmark function.
+*
+* @private
+* @param {PositiveInteger} len - array length
+* @returns {Function} benchmark function
+*/
+function createBenchmark( len ) {
+ var x = uniform( len, -100.0, 100.0, options );
+ var y = uniform( len, -100.0, 100.0, options );
+ return benchmark;
+
+ function benchmark( b ) {
+ var d;
+ var i;
+
+ b.tic();
+ for ( i = 0; i < b.iterations; i++ ) {
+ d = dcosineSimilarity( x.length, x, 1, y, 1 );
+ if ( isnan( d ) ) {
+ b.fail( 'should not return NaN' );
+ }
+ }
+ b.toc();
+ if ( isnan( d ) ) {
+ 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::native:len=%d', pkg, len ), opts, f );
+ }
+}
+
+main();
diff --git a/lib/node_modules/@stdlib/stats/strided/distances/dcosine-similarity/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/stats/strided/distances/dcosine-similarity/benchmark/benchmark.ndarray.js
new file mode 100644
index 000000000000..514cba457482
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/strided/distances/dcosine-similarity/benchmark/benchmark.ndarray.js
@@ -0,0 +1,98 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+* http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+'use strict';
+
+// MODULES //
+
+var bench = require( '@stdlib/bench' );
+var 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 dcosineSimilarity = require( './../lib/ndarray.js' );
+
+
+// VARIABLES //
+
+var options = {
+ 'dtype': 'float64'
+};
+
+
+// FUNCTIONS //
+
+/**
+* Creates a benchmark function.
+*
+* @private
+* @param {PositiveInteger} len - array length
+* @returns {Function} benchmark function
+*/
+function createBenchmark( len ) {
+ var x = uniform( len, -100.0, 100.0, options );
+ var y = uniform( len, -100.0, 100.0, options );
+ return benchmark;
+
+ function benchmark( b ) {
+ var d;
+ var i;
+
+ b.tic();
+ for ( i = 0; i < b.iterations; i++ ) {
+ d = dcosineSimilarity( x.length, x, 1, 0, y, 1, 0 );
+ if ( isnan( d ) ) {
+ b.fail( 'should not return NaN' );
+ }
+ }
+ b.toc();
+ if ( isnan( d ) ) {
+ 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:ndarray:len=%d', pkg, len ), f );
+ }
+}
+
+main();
diff --git a/lib/node_modules/@stdlib/stats/strided/distances/dcosine-similarity/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/stats/strided/distances/dcosine-similarity/benchmark/benchmark.ndarray.native.js
new file mode 100644
index 000000000000..28c9902246f5
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/strided/distances/dcosine-similarity/benchmark/benchmark.ndarray.native.js
@@ -0,0 +1,103 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+* http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+'use strict';
+
+// MODULES //
+
+var resolve = require( 'path' ).resolve;
+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 tryRequire = require( '@stdlib/utils/try-require' );
+var format = require( '@stdlib/string/format' );
+var pkg = require( './../package.json' ).name;
+
+
+// VARIABLES //
+
+var dcosineSimilarity = tryRequire( resolve( __dirname, './../lib/ndarray.native.js' ) );
+var opts = {
+ 'skip': ( dcosineSimilarity instanceof Error )
+};
+var options = {
+ 'dtype': 'float64'
+};
+
+
+// FUNCTIONS //
+
+/**
+* Creates a benchmark function.
+*
+* @private
+* @param {PositiveInteger} len - array length
+* @returns {Function} benchmark function
+*/
+function createBenchmark( len ) {
+ var x = uniform( len, -100.0, 100.0, options );
+ var y = uniform( len, -100.0, 100.0, options );
+ return benchmark;
+
+ function benchmark( b ) {
+ var d;
+ var i;
+
+ b.tic();
+ for ( i = 0; i < b.iterations; i++ ) {
+ d = dcosineSimilarity( x.length, x, 1, 0, y, 1, 0 );
+ if ( isnan( d ) ) {
+ b.fail( 'should not return NaN' );
+ }
+ }
+ b.toc();
+ if ( isnan( d ) ) {
+ 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::native:ndarray:len=%d', pkg, len ), opts, f );
+ }
+}
+
+main();
diff --git a/lib/node_modules/@stdlib/stats/strided/distances/dcosine-similarity/benchmark/c/Makefile b/lib/node_modules/@stdlib/stats/strided/distances/dcosine-similarity/benchmark/c/Makefile
new file mode 100644
index 000000000000..cce2c865d7ad
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/strided/distances/dcosine-similarity/benchmark/c/Makefile
@@ -0,0 +1,146 @@
+#/
+# @license Apache-2.0
+#
+# Copyright (c) 2025 The Stdlib Authors.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+# http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+#/
+
+# VARIABLES #
+
+ifndef VERBOSE
+ QUIET := @
+else
+ QUIET :=
+endif
+
+# Determine the OS ([1][1], [2][2]).
+#
+# [1]: https://en.wikipedia.org/wiki/Uname#Examples
+# [2]: http://stackoverflow.com/a/27776822/2225624
+OS ?= $(shell uname)
+ifneq (, $(findstring MINGW,$(OS)))
+ OS := WINNT
+else
+ifneq (, $(findstring MSYS,$(OS)))
+ OS := WINNT
+else
+ifneq (, $(findstring CYGWIN,$(OS)))
+ OS := WINNT
+else
+ifneq (, $(findstring Windows_NT,$(OS)))
+ OS := WINNT
+endif
+endif
+endif
+endif
+
+# Define the program used for compiling C source files:
+ifdef C_COMPILER
+ CC := $(C_COMPILER)
+else
+ CC := gcc
+endif
+
+# Define the command-line options when compiling C files:
+CFLAGS ?= \
+ -std=c99 \
+ -O3 \
+ -Wall \
+ -pedantic
+
+# Determine whether to generate position independent code ([1][1], [2][2]).
+#
+# [1]: https://gcc.gnu.org/onlinedocs/gcc/Code-Gen-Options.html#Code-Gen-Options
+# [2]: http://stackoverflow.com/questions/5311515/gcc-fpic-option
+ifeq ($(OS), WINNT)
+ fPIC ?=
+else
+ fPIC ?= -fPIC
+endif
+
+# List of includes (e.g., `-I /foo/bar -I /beep/boop/include`):
+INCLUDE ?=
+
+# List of source files:
+SOURCE_FILES ?=
+
+# List of libraries (e.g., `-lopenblas -lpthread`):
+LIBRARIES ?=
+
+# List of library paths (e.g., `-L /foo/bar -L /beep/boop`):
+LIBPATH ?=
+
+# List of C targets:
+c_targets := benchmark.length.out
+
+
+# RULES #
+
+#/
+# Compiles source files.
+#
+# @param {string} [C_COMPILER] - C compiler (e.g., `gcc`)
+# @param {string} [CFLAGS] - C compiler options
+# @param {(string|void)} [fPIC] - compiler flag determining whether to generate position independent code (e.g., `-fPIC`)
+# @param {string} [INCLUDE] - list of includes (e.g., `-I /foo/bar -I /beep/boop/include`)
+# @param {string} [SOURCE_FILES] - list of source files
+# @param {string} [LIBPATH] - list of library paths (e.g., `-L /foo/bar -L /beep/boop`)
+# @param {string} [LIBRARIES] - list of libraries (e.g., `-lopenblas -lpthread`)
+#
+# @example
+# make
+#
+# @example
+# make all
+#/
+all: $(c_targets)
+
+.PHONY: all
+
+#/
+# Compiles C source files.
+#
+# @private
+# @param {string} CC - C compiler (e.g., `gcc`)
+# @param {string} CFLAGS - C compiler options
+# @param {(string|void)} fPIC - compiler flag determining whether to generate position independent code (e.g., `-fPIC`)
+# @param {string} INCLUDE - list of includes (e.g., `-I /foo/bar`)
+# @param {string} SOURCE_FILES - list of source files
+# @param {string} LIBPATH - list of library paths (e.g., `-L /foo/bar`)
+# @param {string} LIBRARIES - list of libraries (e.g., `-lopenblas`)
+#/
+$(c_targets): %.out: %.c
+ $(QUIET) $(CC) $(CFLAGS) $(fPIC) $(INCLUDE) -o $@ $(SOURCE_FILES) $< $(LIBPATH) -lm $(LIBRARIES)
+
+#/
+# Runs compiled benchmarks.
+#
+# @example
+# make run
+#/
+run: $(c_targets)
+ $(QUIET) ./$<
+
+.PHONY: run
+
+#/
+# Removes generated files.
+#
+# @example
+# make clean
+#/
+clean:
+ $(QUIET) -rm -f *.o *.out
+
+.PHONY: clean
diff --git a/lib/node_modules/@stdlib/stats/strided/distances/dcosine-similarity/benchmark/c/benchmark.length.c b/lib/node_modules/@stdlib/stats/strided/distances/dcosine-similarity/benchmark/c/benchmark.length.c
new file mode 100644
index 000000000000..16929f60c541
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/strided/distances/dcosine-similarity/benchmark/c/benchmark.length.c
@@ -0,0 +1,203 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+* http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+#include "stdlib/stats/strided/distances/dcosine_similarity.h"
+#include
+#include
+#include
+#include
+#include
+
+#define NAME "dcosine_similarity"
+#define ITERATIONS 10000000
+#define REPEATS 3
+#define MIN 1
+#define MAX 6
+
+/**
+* Prints the TAP version.
+*/
+static void print_version( void ) {
+ printf( "TAP version 13\n" );
+}
+
+/**
+* Prints the TAP summary.
+*
+* @param total total number of tests
+* @param passing total number of passing tests
+*/
+static void print_summary( int total, int passing ) {
+ printf( "#\n" );
+ printf( "1..%d\n", total ); // TAP plan
+ printf( "# total %d\n", total );
+ printf( "# pass %d\n", passing );
+ printf( "#\n" );
+ printf( "# ok\n" );
+}
+
+/**
+* Prints benchmarks results.
+*
+* @param iterations number of iterations
+* @param elapsed elapsed time in seconds
+*/
+static void print_results( int iterations, double elapsed ) {
+ double rate = (double)iterations / elapsed;
+ printf( " ---\n" );
+ printf( " iterations: %d\n", iterations );
+ printf( " elapsed: %0.9f\n", elapsed );
+ printf( " rate: %0.9f\n", rate );
+ printf( " ...\n" );
+}
+
+/**
+* Returns a clock time.
+*
+* @return clock time
+*/
+static double tic( void ) {
+ struct timeval now;
+ gettimeofday( &now, NULL );
+ return (double)now.tv_sec + (double)now.tv_usec/1.0e6;
+}
+
+/**
+* Generates a random number on the interval [0,1).
+*
+* @return random number
+*/
+static double rand_double( void ) {
+ int r = rand();
+ return (double)r / ( (double)RAND_MAX + 1.0 );
+}
+
+/**
+* Runs a benchmark.
+*
+* @param iterations number of iterations
+* @param len array length
+* @return elapsed time in seconds
+*/
+static double benchmark1( int iterations, int len ) {
+ double elapsed;
+ double *x;
+ double *y;
+ double z;
+ double t;
+ int i;
+
+ x = (double *) malloc( len * sizeof( double ) );
+ y = (double *) malloc( len * sizeof( double ) );
+ for ( i = 0; i < len; i++ ) {
+ x[ i ] = ( rand_double()*20000.0 ) - 10000.0;
+ y[ i ] = ( rand_double()*20000.0 ) - 10000.0;
+ }
+ z = 0.0;
+ t = tic();
+ for ( i = 0; i < iterations; i++ ) {
+ z = stdlib_strided_dcosine_similarity( len, x, 1, y, 1 );
+ if ( z != z ) {
+ printf( "should not return NaN\n" );
+ break;
+ }
+ }
+ elapsed = tic() - t;
+ if ( z != z ) {
+ printf( "should not return NaN\n" );
+ }
+ free( x );
+ free( y );
+ return elapsed;
+}
+
+/**
+* Runs a benchmark.
+*
+* @param iterations number of iterations
+* @param len array length
+* @return elapsed time in seconds
+*/
+static double benchmark2( int iterations, int len ) {
+ double elapsed;
+ double *x;
+ double *y;
+ double z;
+ double t;
+ int i;
+
+ x = (double *) malloc( len * sizeof( double ) );
+ y = (double *) malloc( len * sizeof( double ) );
+ for ( i = 0; i < len; i++ ) {
+ x[ i ] = ( rand_double()*20000.0 ) - 10000.0;
+ y[ i ] = ( rand_double()*20000.0 ) - 10000.0;
+ }
+ z = 0.0;
+ t = tic();
+ for ( i = 0; i < iterations; i++ ) {
+ z = stdlib_strided_dcosine_similarity_ndarray( len, x, 1, 0, y, 1, 0 );
+ if ( z != z ) {
+ printf( "should not return NaN\n" );
+ break;
+ }
+ }
+ elapsed = tic() - t;
+ if ( z != z ) {
+ printf( "should not return NaN\n" );
+ }
+ free( x );
+ free( y );
+ return elapsed;
+}
+
+/**
+* Main execution sequence.
+*/
+int main( void ) {
+ double elapsed;
+ int count;
+ int iter;
+ int len;
+ int i;
+ int j;
+
+ // Use the current time to seed the random number generator:
+ srand( time( NULL ) );
+
+ print_version();
+ count = 0;
+ for ( i = MIN; i <= MAX; i++ ) {
+ len = pow( 10, i );
+ iter = ITERATIONS / pow( 10, i-1 );
+ for ( j = 0; j < REPEATS; j++ ) {
+ count += 1;
+ printf( "# c::%s:len=%d\n", NAME, len );
+ elapsed = benchmark1( iter, len );
+ print_results( iter, elapsed );
+ printf( "ok %d benchmark finished\n", count );
+ }
+ for ( j = 0; j < REPEATS; j++ ) {
+ count += 1;
+ printf( "# c::%s:ndarray:len=%d\n", NAME, len );
+ elapsed = benchmark2( iter, len );
+ print_results( iter, elapsed );
+ printf( "ok %d benchmark finished\n", count );
+ }
+ }
+ print_summary( count, count );
+}
diff --git a/lib/node_modules/@stdlib/stats/strided/distances/dcosine-similarity/binding.gyp b/lib/node_modules/@stdlib/stats/strided/distances/dcosine-similarity/binding.gyp
new file mode 100644
index 000000000000..08de71a2020e
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/strided/distances/dcosine-similarity/binding.gyp
@@ -0,0 +1,265 @@
+# @license Apache-2.0
+#
+# Copyright (c) 2025 The Stdlib Authors.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+# http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+# A `.gyp` file for building a Node.js native add-on.
+#
+# [1]: https://gyp.gsrc.io/docs/InputFormatReference.md
+# [2]: https://gyp.gsrc.io/docs/UserDocumentation.md
+{
+ # List of files to include in this file:
+ 'includes': [
+ './include.gypi',
+ ],
+
+ # Define variables to be used throughout the configuration for all targets:
+ 'variables': {
+ # Target name should match the add-on export name:
+ 'addon_target_name%': 'addon',
+
+ # Fortran compiler (to override -Dfortran_compiler=):
+ 'fortran_compiler%': 'gfortran',
+
+ # Fortran compiler flags:
+ 'fflags': [
+ # Specify the Fortran standard to which a program is expected to conform:
+ '-std=f95',
+
+ # Indicate that the layout is free-form source code:
+ '-ffree-form',
+
+ # Aggressive optimization:
+ '-O3',
+
+ # Enable commonly used warning options:
+ '-Wall',
+
+ # Warn if source code contains problematic language features:
+ '-Wextra',
+
+ # Warn if a procedure is called without an explicit interface:
+ '-Wimplicit-interface',
+
+ # Do not transform names of entities specified in Fortran source files by appending underscores (i.e., don't mangle names, thus allowing easier usage in C wrappers):
+ '-fno-underscoring',
+
+ # Warn if source code contains Fortran 95 extensions and C-language constructs:
+ '-pedantic',
+
+ # Compile but do not link (output is an object file):
+ '-c',
+ ],
+
+ # Set variables based on the host OS:
+ 'conditions': [
+ [
+ 'OS=="win"',
+ {
+ # Define the object file suffix:
+ 'obj': 'obj',
+ },
+ {
+ # Define the object file suffix:
+ 'obj': 'o',
+ }
+ ], # end condition (OS=="win")
+ ], # end conditions
+ }, # end variables
+
+ # Define compile targets:
+ 'targets': [
+
+ # Target to generate an add-on:
+ {
+ # The target name should match the add-on export name:
+ 'target_name': '<(addon_target_name)',
+
+ # Define dependencies:
+ 'dependencies': [],
+
+ # Define directories which contain relevant include headers:
+ 'include_dirs': [
+ # Local include directory:
+ '<@(include_dirs)',
+ ],
+
+ # List of source files:
+ 'sources': [
+ '<@(src_files)',
+ ],
+
+ # Settings which should be applied when a target's object files are used as linker input:
+ 'link_settings': {
+ # Define libraries:
+ 'libraries': [
+ '<@(libraries)',
+ ],
+
+ # Define library directories:
+ 'library_dirs': [
+ '<@(library_dirs)',
+ ],
+ },
+
+ # C/C++ compiler flags:
+ 'cflags': [
+ # Enable commonly used warning options:
+ '-Wall',
+
+ # Aggressive optimization:
+ '-O3',
+ ],
+
+ # C specific compiler flags:
+ 'cflags_c': [
+ # Specify the C standard to which a program is expected to conform:
+ '-std=c99',
+ ],
+
+ # C++ specific compiler flags:
+ 'cflags_cpp': [
+ # Specify the C++ standard to which a program is expected to conform:
+ '-std=c++11',
+ ],
+
+ # Linker flags:
+ 'ldflags': [],
+
+ # Apply conditions based on the host OS:
+ 'conditions': [
+ [
+ 'OS=="mac"',
+ {
+ # Linker flags:
+ 'ldflags': [
+ '-undefined dynamic_lookup',
+ '-Wl,-no-pie',
+ '-Wl,-search_paths_first',
+ ],
+ },
+ ], # end condition (OS=="mac")
+ [
+ 'OS!="win"',
+ {
+ # C/C++ flags:
+ 'cflags': [
+ # Generate platform-independent code:
+ '-fPIC',
+ ],
+ },
+ ], # end condition (OS!="win")
+ ], # end conditions
+
+ # Define custom build actions for particular inputs:
+ 'rules': [
+ {
+ # Define a rule for processing Fortran files:
+ 'extension': 'f',
+
+ # Define the pathnames to be used as inputs when performing processing:
+ 'inputs': [
+ # Full path of the current input:
+ '<(RULE_INPUT_PATH)'
+ ],
+
+ # Define the outputs produced during processing:
+ 'outputs': [
+ # Store an output object file in a directory for placing intermediate results (only accessible within a single target):
+ '<(INTERMEDIATE_DIR)/<(RULE_INPUT_ROOT).<(obj)'
+ ],
+
+ # Define the rule for compiling Fortran based on the host OS:
+ 'conditions': [
+ [
+ 'OS=="win"',
+
+ # Rule to compile Fortran on Windows:
+ {
+ 'rule_name': 'compile_fortran_windows',
+ 'message': 'Compiling Fortran file <(RULE_INPUT_PATH) on Windows...',
+
+ 'process_outputs_as_sources': 0,
+
+ # Define the command-line invocation:
+ 'action': [
+ '<(fortran_compiler)',
+ '<@(fflags)',
+ '<@(_inputs)',
+ '-o',
+ '<@(_outputs)',
+ ],
+ },
+
+ # Rule to compile Fortran on non-Windows:
+ {
+ 'rule_name': 'compile_fortran_linux',
+ 'message': 'Compiling Fortran file <(RULE_INPUT_PATH) on Linux...',
+
+ 'process_outputs_as_sources': 1,
+
+ # Define the command-line invocation:
+ 'action': [
+ '<(fortran_compiler)',
+ '<@(fflags)',
+ '-fPIC', # generate platform-independent code
+ '<@(_inputs)',
+ '-o',
+ '<@(_outputs)',
+ ],
+ }
+ ], # end condition (OS=="win")
+ ], # end conditions
+ }, # end rule (extension=="f")
+ ], # end rules
+ }, # end target <(addon_target_name)
+
+ # Target to copy a generated add-on to a standard location:
+ {
+ 'target_name': 'copy_addon',
+
+ # Declare that the output of this target is not linked:
+ 'type': 'none',
+
+ # Define dependencies:
+ 'dependencies': [
+ # Require that the add-on be generated before building this target:
+ '<(addon_target_name)',
+ ],
+
+ # Define a list of actions:
+ 'actions': [
+ {
+ 'action_name': 'copy_addon',
+ 'message': 'Copying addon...',
+
+ # Explicitly list the inputs in the command-line invocation below:
+ 'inputs': [],
+
+ # Declare the expected outputs:
+ 'outputs': [
+ '<(addon_output_dir)/<(addon_target_name).node',
+ ],
+
+ # Define the command-line invocation:
+ 'action': [
+ 'cp',
+ '<(PRODUCT_DIR)/<(addon_target_name).node',
+ '<(addon_output_dir)/<(addon_target_name).node',
+ ],
+ },
+ ], # end actions
+ }, # end target copy_addon
+ ], # end targets
+}
diff --git a/lib/node_modules/@stdlib/stats/strided/distances/dcosine-similarity/docs/repl.txt b/lib/node_modules/@stdlib/stats/strided/distances/dcosine-similarity/docs/repl.txt
new file mode 100644
index 000000000000..8f40db2406ad
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/strided/distances/dcosine-similarity/docs/repl.txt
@@ -0,0 +1,116 @@
+
+{{alias}}( N, x, strideX, y, strideY )
+ Computes the cosine similarity of two double-precision floating-point
+ strided arrays.
+
+ 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 a typed
+ array view.
+
+ If `N <= 0`, the function returns `0`.
+
+ Parameters
+ ----------
+ N: integer
+ Number of indexed elements.
+
+ x: Float64Array
+ First input array.
+
+ strideX: integer
+ Index increment for `x`.
+
+ y: Float64Array
+ Second input array.
+
+ strideY: integer
+ Index increment for `y`.
+
+ Returns
+ -------
+ out: number
+ Cosine similarity.
+
+ Examples
+ --------
+ // Standard usage:
+ > var x = new {{alias:@stdlib/array/float64}}( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] );
+ > var y = new {{alias:@stdlib/array/float64}}( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] );
+ > var out = {{alias}}( x.length, x, 1, y, 1 )
+ ~-0.061
+
+ // Strides:
+ > x = new {{alias:@stdlib/array/float64}}( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );
+ > y = new {{alias:@stdlib/array/float64}}( [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ] );
+ > var y1 = new Float64Array( y.buffer, y.BYTES_PER_ELEMENT*2 );
+ > out = {{alias}}( 3, x, 1, y, -1 )
+ ~0.926
+
+ // Using view offsets:
+ > x = new {{alias:@stdlib/array/float64}}( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );
+ > y = new {{alias:@stdlib/array/float64}}( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );
+ > var x1 = new {{alias:@stdlib/array/float64}}( x.buffer, x.BYTES_PER_ELEMENT*1 );
+ > var y1 = new {{alias:@stdlib/array/float64}}( y.buffer, y.BYTES_PER_ELEMENT*3 );
+ > out = {{alias}}( 3, x1, 1, y1, 1 )
+ ~0.982
+
+
+{{alias}}.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )
+ Computes the cosine similarity of two double-precision floating-point
+ strided arrays using alternative indexing semantics.
+
+ While typed array views mandate a view offset based on the underlying
+ buffer, the offset parameters support indexing based on a starting index.
+
+ Parameters
+ ----------
+ N: integer
+ Number of indexed elements.
+
+ x: Float64Array
+ First input array.
+
+ strideX: integer
+ Index increment for `x`.
+
+ offsetX: integer
+ Starting index for `x`.
+
+ y: Float64Array
+ Second input array.
+
+ strideY: integer
+ Index increment for `y`.
+
+ offsetY: integer
+ Starting index for `y`.
+
+ Returns
+ -------
+ out: number
+ Cosine similarity.
+
+ Examples
+ --------
+ // Standard usage:
+ > var x = new {{alias:@stdlib/array/float64}}( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] );
+ > var y = new {{alias:@stdlib/array/float64}}( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] );
+ > var out = {{alias}}.ndarray( x.length, x, 1, 0, y, 1, 0 )
+ ~-0.061
+
+ // Strides:
+ > x = new {{alias:@stdlib/array/float64}}( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );
+ > y = new {{alias:@stdlib/array/float64}}( [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ] );
+ > out = {{alias}}.ndarray( 3, x, 1, 0, y, -1, 2 )
+ ~0.926
+
+ // Using offset indices:
+ > x = new {{alias:@stdlib/array/float64}}( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );
+ > y = new {{alias:@stdlib/array/float64}}( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );
+ > out = {{alias}}.ndarray( 3, x, 1, 1, y, 1, 3 )
+ ~0.982
+
+ See Also
+ --------
diff --git a/lib/node_modules/@stdlib/stats/strided/distances/dcosine-similarity/docs/types/index.d.ts b/lib/node_modules/@stdlib/stats/strided/distances/dcosine-similarity/docs/types/index.d.ts
new file mode 100644
index 000000000000..f180faecd267
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/strided/distances/dcosine-similarity/docs/types/index.d.ts
@@ -0,0 +1,103 @@
+/*
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+* http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+// TypeScript Version: 4.1
+
+/**
+* Interface describing `dcosineSimilarity`.
+*/
+interface Routine {
+ /**
+ * Computes the cosine similarity of two double-precision floating-point strided arrays.
+ *
+ * @param N - number of indexed elements
+ * @param x - first input array
+ * @param strideX - `x` stride length
+ * @param y - second input array
+ * @param strideY - `y` stride length
+ * @returns cosine similarity
+ *
+ * @example
+ * var Float64Array = require( '@stdlib/array/float64' );
+ *
+ * var x = new Float64Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] );
+ * var y = new Float64Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] );
+ *
+ * var z = dcosineSimilarity( x.length, x, 1, y, 1 );
+ * // returns ~-0.061
+ */
+ ( N: number, x: Float64Array, strideX: number, y: Float64Array, strideY: number ): number;
+
+ /**
+ * Computes the cosine similarity of two double-precision floating-point strided arrays using alternative indexing semantics.
+ *
+ * @param N - number of indexed elements
+ * @param x - first input array
+ * @param strideX - `x` stride length
+ * @param offsetX - starting index for `x`
+ * @param y - second input array
+ * @param strideY - `y` stride length
+ * @param offsetY - starting index for `y`
+ * @returns cosine similarity
+ *
+ * @example
+ * var Float64Array = require( '@stdlib/array/float64' );
+ *
+ * var x = new Float64Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] );
+ * var y = new Float64Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] );
+ *
+ * var z = dcosineSimilarity.ndarray( x.length, x, 1, 0, y, 1, 0 );
+ * // returns ~-0.061
+ */
+ ndarray( N: number, x: Float64Array, strideX: number, offsetX: number, y: Float64Array, strideY: number, offsetY: number ): number;
+}
+
+/**
+* Computes the cosine similarity of two double-precision floating-point strided arrays.
+*
+* @param N - number of indexed elements
+* @param x - first input array
+* @param strideX - `x` stride length
+* @param y - second input array
+* @param strideY - `y` stride length
+* @returns cosine similarity
+*
+* @example
+* var Float64Array = require( '@stdlib/array/float64' );
+*
+* var x = new Float64Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] );
+* var y = new Float64Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] );
+*
+* var z = dcosineSimilarity( x.length, x, 1, y, 1 );
+* // returns ~-0.061
+*
+* @example
+* var Float64Array = require( '@stdlib/array/float64' );
+*
+* var x = new Float64Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] );
+* var y = new Float64Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] );
+*
+* var z = dcosineSimilarity.ndarray( x.length, x, 1, 0, y, 1, 0 );
+* // returns ~-0.061
+*/
+declare var dcosineSimilarity: Routine;
+
+
+// EXPORTS //
+
+export = dcosineSimilarity;
diff --git a/lib/node_modules/@stdlib/stats/strided/distances/dcosine-similarity/docs/types/test.ts b/lib/node_modules/@stdlib/stats/strided/distances/dcosine-similarity/docs/types/test.ts
new file mode 100644
index 000000000000..6f931dd9efec
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/strided/distances/dcosine-similarity/docs/types/test.ts
@@ -0,0 +1,248 @@
+/*
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+* http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+import dcosineSimilarity = require( './index' );
+
+
+// TESTS //
+
+// The function returns a number...
+{
+ const x = new Float64Array( 10 );
+ const y = new Float64Array( 10 );
+
+ dcosineSimilarity( x.length, x, 1, y, 1 ); // $ExpectType number
+}
+
+// The compiler throws an error if the function is provided a first argument which is not a number...
+{
+ const x = new Float64Array( 10 );
+ const y = new Float64Array( 10 );
+
+ dcosineSimilarity( '10', x, 1, y, 1 ); // $ExpectError
+ dcosineSimilarity( true, x, 1, y, 1 ); // $ExpectError
+ dcosineSimilarity( false, x, 1, y, 1 ); // $ExpectError
+ dcosineSimilarity( null, x, 1, y, 1 ); // $ExpectError
+ dcosineSimilarity( undefined, x, 1, y, 1 ); // $ExpectError
+ dcosineSimilarity( [], x, 1, y, 1 ); // $ExpectError
+ dcosineSimilarity( {}, x, 1, y, 1 ); // $ExpectError
+ dcosineSimilarity( ( x: number ): number => x, x, 1, y, 1 ); // $ExpectError
+}
+
+// The compiler throws an error if the function is provided a second argument which is not a Float64Array...
+{
+ const x = new Float64Array( 10 );
+ const y = new Float64Array( 10 );
+
+ dcosineSimilarity( x.length, 10, 1, y, 1 ); // $ExpectError
+ dcosineSimilarity( x.length, '10', 1, y, 1 ); // $ExpectError
+ dcosineSimilarity( x.length, true, 1, y, 1 ); // $ExpectError
+ dcosineSimilarity( x.length, false, 1, y, 1 ); // $ExpectError
+ dcosineSimilarity( x.length, null, 1, y, 1 ); // $ExpectError
+ dcosineSimilarity( x.length, undefined, 1, y, 1 ); // $ExpectError
+ dcosineSimilarity( x.length, [], 1, y, 1 ); // $ExpectError
+ dcosineSimilarity( x.length, {}, 1, y, 1 ); // $ExpectError
+ dcosineSimilarity( x.length, ( x: number ): number => x, 1, y, 1 ); // $ExpectError
+}
+
+// The compiler throws an error if the function is provided a third argument which is not a number...
+{
+ const x = new Float64Array( 10 );
+ const y = new Float64Array( 10 );
+
+ dcosineSimilarity( x.length, x, '10', y, 1 ); // $ExpectError
+ dcosineSimilarity( x.length, x, true, y, 1 ); // $ExpectError
+ dcosineSimilarity( x.length, x, false, y, 1 ); // $ExpectError
+ dcosineSimilarity( x.length, x, null, y, 1 ); // $ExpectError
+ dcosineSimilarity( x.length, x, undefined, y, 1 ); // $ExpectError
+ dcosineSimilarity( x.length, x, [], y, 1 ); // $ExpectError
+ dcosineSimilarity( x.length, x, {}, y, 1 ); // $ExpectError
+ dcosineSimilarity( x.length, x, ( x: number ): number => x, y, 1 ); // $ExpectError
+}
+
+// The compiler throws an error if the function is provided a fourth argument which is not a Float64Array...
+{
+ const x = new Float64Array( 10 );
+
+ dcosineSimilarity( x.length, x, 1, 10, 1 ); // $ExpectError
+ dcosineSimilarity( x.length, x, 1, '10', 1 ); // $ExpectError
+ dcosineSimilarity( x.length, x, 1, true, 1 ); // $ExpectError
+ dcosineSimilarity( x.length, x, 1, false, 1 ); // $ExpectError
+ dcosineSimilarity( x.length, x, 1, null, 1 ); // $ExpectError
+ dcosineSimilarity( x.length, x, 1, undefined, 1 ); // $ExpectError
+ dcosineSimilarity( x.length, x, 1, [], 1 ); // $ExpectError
+ dcosineSimilarity( x.length, x, 1, {}, 1 ); // $ExpectError
+ dcosineSimilarity( x.length, x, 1, ( x: number ): number => x, 1 ); // $ExpectError
+}
+
+// The compiler throws an error if the function is provided a fifth argument which is not a number...
+{
+ const x = new Float64Array( 10 );
+ const y = new Float64Array( 10 );
+
+ dcosineSimilarity( x.length, x, 1, y, '10' ); // $ExpectError
+ dcosineSimilarity( x.length, x, 1, y, true ); // $ExpectError
+ dcosineSimilarity( x.length, x, 1, y, false ); // $ExpectError
+ dcosineSimilarity( x.length, x, 1, y, null ); // $ExpectError
+ dcosineSimilarity( x.length, x, 1, y, undefined ); // $ExpectError
+ dcosineSimilarity( x.length, x, 1, y, [] ); // $ExpectError
+ dcosineSimilarity( x.length, x, 1, y, {} ); // $ExpectError
+ dcosineSimilarity( x.length, x, 1, y, ( 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 y = new Float64Array( 10 );
+
+ dcosineSimilarity(); // $ExpectError
+ dcosineSimilarity( x.length ); // $ExpectError
+ dcosineSimilarity( x.length, x ); // $ExpectError
+ dcosineSimilarity( x.length, x, 1 ); // $ExpectError
+ dcosineSimilarity( x.length, x, 1, y ); // $ExpectError
+ dcosineSimilarity( x.length, x, 1, y, 1, 10 ); // $ExpectError
+}
+
+// Attached to main export is an `ndarray` method which returns a number...
+{
+ const x = new Float64Array( 10 );
+ const y = new Float64Array( 10 );
+
+ dcosineSimilarity.ndarray( x.length, x, 1, 0, y, 1, 0 ); // $ExpectType number
+}
+
+// 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 y = new Float64Array( 10 );
+
+ dcosineSimilarity.ndarray( '10', x, 1, 0, y, 1, 0 ); // $ExpectError
+ dcosineSimilarity.ndarray( true, x, 1, 0, y, 1, 0 ); // $ExpectError
+ dcosineSimilarity.ndarray( false, x, 1, 0, y, 1, 0 ); // $ExpectError
+ dcosineSimilarity.ndarray( null, x, 1, 0, y, 1, 0 ); // $ExpectError
+ dcosineSimilarity.ndarray( undefined, x, 1, 0, y, 1, 0 ); // $ExpectError
+ dcosineSimilarity.ndarray( [], x, 1, 0, y, 1, 0 ); // $ExpectError
+ dcosineSimilarity.ndarray( {}, x, 1, 0, y, 1, 0 ); // $ExpectError
+ dcosineSimilarity.ndarray( ( x: number ): number => x, x, 1, 0, y, 1, 0 ); // $ExpectError
+}
+
+// The compiler throws an error if the `ndarray` method is provided a second argument which is not a Float64Array...
+{
+ const x = new Float64Array( 10 );
+ const y = new Float64Array( 10 );
+
+ dcosineSimilarity.ndarray( x.length, 10, 1, 0, y, 1, 0 ); // $ExpectError
+ dcosineSimilarity.ndarray( x.length, '10', 1, 0, y, 1, 0 ); // $ExpectError
+ dcosineSimilarity.ndarray( x.length, true, 1, 0, y, 1, 0 ); // $ExpectError
+ dcosineSimilarity.ndarray( x.length, false, 1, 0, y, 1, 0 ); // $ExpectError
+ dcosineSimilarity.ndarray( x.length, null, 1, 0, y, 1, 0 ); // $ExpectError
+ dcosineSimilarity.ndarray( x.length, undefined, 1, 0, y, 1, 0 ); // $ExpectError
+ dcosineSimilarity.ndarray( x.length, [], 1, 0, y, 1, 0 ); // $ExpectError
+ dcosineSimilarity.ndarray( x.length, {}, 1, 0, y, 1, 0 ); // $ExpectError
+ dcosineSimilarity.ndarray( x.length, ( x: number ): number => x, 1, 0, y, 1, 0 ); // $ExpectError
+}
+
+// The compiler throws an error if the `ndarray` method is provided a third argument which is not a number...
+{
+ const x = new Float64Array( 10 );
+ const y = new Float64Array( 10 );
+
+ dcosineSimilarity.ndarray( x.length, x, '10', 0, y, 1, 0 ); // $ExpectError
+ dcosineSimilarity.ndarray( x.length, x, true, 0, y, 1, 0 ); // $ExpectError
+ dcosineSimilarity.ndarray( x.length, x, false, 0, y, 1, 0 ); // $ExpectError
+ dcosineSimilarity.ndarray( x.length, x, null, 0, y, 1, 0 ); // $ExpectError
+ dcosineSimilarity.ndarray( x.length, x, undefined, 0, y, 1, 0 ); // $ExpectError
+ dcosineSimilarity.ndarray( x.length, x, [], 0, y, 1, 0 ); // $ExpectError
+ dcosineSimilarity.ndarray( x.length, x, {}, 0, y, 1, 0 ); // $ExpectError
+ dcosineSimilarity.ndarray( x.length, x, ( x: number ): number => x, 0, y, 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 y = new Float64Array( 10 );
+
+ dcosineSimilarity.ndarray( x.length, x, 1, '10', y, 1, 0 ); // $ExpectError
+ dcosineSimilarity.ndarray( x.length, x, 1, true, y, 1, 0 ); // $ExpectError
+ dcosineSimilarity.ndarray( x.length, x, 1, false, y, 1, 0 ); // $ExpectError
+ dcosineSimilarity.ndarray( x.length, x, 1, null, y, 1, 0 ); // $ExpectError
+ dcosineSimilarity.ndarray( x.length, x, 1, undefined, y, 1, 0 ); // $ExpectError
+ dcosineSimilarity.ndarray( x.length, x, 1, [], y, 1, 0 ); // $ExpectError
+ dcosineSimilarity.ndarray( x.length, x, 1, {}, y, 1, 0 ); // $ExpectError
+ dcosineSimilarity.ndarray( x.length, x, 1, ( x: number ): number => x, y, 1, 0 ); // $ExpectError
+}
+
+// The compiler throws an error if the `ndarray` method is provided a fifth argument which is not a Float64Array...
+{
+ const x = new Float64Array( 10 );
+
+ dcosineSimilarity.ndarray( x.length, x, 1, 0, 10, 1, 0 ); // $ExpectError
+ dcosineSimilarity.ndarray( x.length, x, 1, 0, '10', 1, 0 ); // $ExpectError
+ dcosineSimilarity.ndarray( x.length, x, 1, 0, true, 1, 0 ); // $ExpectError
+ dcosineSimilarity.ndarray( x.length, x, 1, 0, false, 1, 0 ); // $ExpectError
+ dcosineSimilarity.ndarray( x.length, x, 1, 0, null, 1, 0 ); // $ExpectError
+ dcosineSimilarity.ndarray( x.length, x, 1, 0, undefined, 1, 0 ); // $ExpectError
+ dcosineSimilarity.ndarray( x.length, x, 1, 0, [], 1, 0 ); // $ExpectError
+ dcosineSimilarity.ndarray( x.length, x, 1, 0, {}, 1, 0 ); // $ExpectError
+ dcosineSimilarity.ndarray( x.length, x, 1, 0, ( x: number ): number => x, 1, 0 ); // $ExpectError
+}
+
+// The compiler throws an error if the `ndarray` method is provided a sixth argument which is not a number...
+{
+ const x = new Float64Array( 10 );
+ const y = new Float64Array( 10 );
+
+ dcosineSimilarity.ndarray( x.length, x, 1, 0, y, '10', 0 ); // $ExpectError
+ dcosineSimilarity.ndarray( x.length, x, 1, 0, y, true, 0 ); // $ExpectError
+ dcosineSimilarity.ndarray( x.length, x, 1, 0, y, false, 0 ); // $ExpectError
+ dcosineSimilarity.ndarray( x.length, x, 1, 0, y, null, 0 ); // $ExpectError
+ dcosineSimilarity.ndarray( x.length, x, 1, 0, y, undefined, 0 ); // $ExpectError
+ dcosineSimilarity.ndarray( x.length, x, 1, 0, y, [], 0 ); // $ExpectError
+ dcosineSimilarity.ndarray( x.length, x, 1, 0, y, {}, 0 ); // $ExpectError
+ dcosineSimilarity.ndarray( x.length, x, 1, 0, y, ( x: number ): number => x, 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 y = new Float64Array( 10 );
+
+ dcosineSimilarity.ndarray( x.length, x, 1, 0, y, 1, '10' ); // $ExpectError
+ dcosineSimilarity.ndarray( x.length, x, 1, 0, y, 1, true ); // $ExpectError
+ dcosineSimilarity.ndarray( x.length, x, 1, 0, y, 1, false ); // $ExpectError
+ dcosineSimilarity.ndarray( x.length, x, 1, 0, y, 1, null ); // $ExpectError
+ dcosineSimilarity.ndarray( x.length, x, 1, 0, y, 1, undefined ); // $ExpectError
+ dcosineSimilarity.ndarray( x.length, x, 1, 0, y, 1, [] ); // $ExpectError
+ dcosineSimilarity.ndarray( x.length, x, 1, 0, y, 1, {} ); // $ExpectError
+ dcosineSimilarity.ndarray( x.length, x, 1, 0, y, 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 y = new Float64Array( 10 );
+
+ dcosineSimilarity.ndarray(); // $ExpectError
+ dcosineSimilarity.ndarray( x.length ); // $ExpectError
+ dcosineSimilarity.ndarray( x.length, x ); // $ExpectError
+ dcosineSimilarity.ndarray( x.length, x, 1 ); // $ExpectError
+ dcosineSimilarity.ndarray( x.length, x, 1, 0 ); // $ExpectError
+ dcosineSimilarity.ndarray( x.length, x, 1, 0, y ); // $ExpectError
+ dcosineSimilarity.ndarray( x.length, x, 1, 0, y, 1 ); // $ExpectError
+ dcosineSimilarity.ndarray( x.length, x, 1, 0, y, 1, 0, 10 ); // $ExpectError
+}
diff --git a/lib/node_modules/@stdlib/stats/strided/distances/dcosine-similarity/examples/c/Makefile b/lib/node_modules/@stdlib/stats/strided/distances/dcosine-similarity/examples/c/Makefile
new file mode 100644
index 000000000000..25ced822f96a
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/strided/distances/dcosine-similarity/examples/c/Makefile
@@ -0,0 +1,146 @@
+#/
+# @license Apache-2.0
+#
+# Copyright (c) 2025 The Stdlib Authors.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+# http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+#/
+
+# VARIABLES #
+
+ifndef VERBOSE
+ QUIET := @
+else
+ QUIET :=
+endif
+
+# Determine the OS ([1][1], [2][2]).
+#
+# [1]: https://en.wikipedia.org/wiki/Uname#Examples
+# [2]: http://stackoverflow.com/a/27776822/2225624
+OS ?= $(shell uname)
+ifneq (, $(findstring MINGW,$(OS)))
+ OS := WINNT
+else
+ifneq (, $(findstring MSYS,$(OS)))
+ OS := WINNT
+else
+ifneq (, $(findstring CYGWIN,$(OS)))
+ OS := WINNT
+else
+ifneq (, $(findstring Windows_NT,$(OS)))
+ OS := WINNT
+endif
+endif
+endif
+endif
+
+# Define the program used for compiling C source files:
+ifdef C_COMPILER
+ CC := $(C_COMPILER)
+else
+ CC := gcc
+endif
+
+# Define the command-line options when compiling C files:
+CFLAGS ?= \
+ -std=c99 \
+ -O3 \
+ -Wall \
+ -pedantic
+
+# Determine whether to generate position independent code ([1][1], [2][2]).
+#
+# [1]: https://gcc.gnu.org/onlinedocs/gcc/Code-Gen-Options.html#Code-Gen-Options
+# [2]: http://stackoverflow.com/questions/5311515/gcc-fpic-option
+ifeq ($(OS), WINNT)
+ fPIC ?=
+else
+ fPIC ?= -fPIC
+endif
+
+# List of includes (e.g., `-I /foo/bar -I /beep/boop/include`):
+INCLUDE ?=
+
+# List of source files:
+SOURCE_FILES ?=
+
+# List of libraries (e.g., `-lopenblas -lpthread`):
+LIBRARIES ?=
+
+# List of library paths (e.g., `-L /foo/bar -L /beep/boop`):
+LIBPATH ?=
+
+# List of C targets:
+c_targets := example.out
+
+
+# RULES #
+
+#/
+# Compiles source files.
+#
+# @param {string} [C_COMPILER] - C compiler (e.g., `gcc`)
+# @param {string} [CFLAGS] - C compiler options
+# @param {(string|void)} [fPIC] - compiler flag determining whether to generate position independent code (e.g., `-fPIC`)
+# @param {string} [INCLUDE] - list of includes (e.g., `-I /foo/bar -I /beep/boop/include`)
+# @param {string} [SOURCE_FILES] - list of source files
+# @param {string} [LIBPATH] - list of library paths (e.g., `-L /foo/bar -L /beep/boop`)
+# @param {string} [LIBRARIES] - list of libraries (e.g., `-lopenblas -lpthread`)
+#
+# @example
+# make
+#
+# @example
+# make all
+#/
+all: $(c_targets)
+
+.PHONY: all
+
+#/
+# Compiles C source files.
+#
+# @private
+# @param {string} CC - C compiler (e.g., `gcc`)
+# @param {string} CFLAGS - C compiler options
+# @param {(string|void)} fPIC - compiler flag determining whether to generate position independent code (e.g., `-fPIC`)
+# @param {string} INCLUDE - list of includes (e.g., `-I /foo/bar`)
+# @param {string} SOURCE_FILES - list of source files
+# @param {string} LIBPATH - list of library paths (e.g., `-L /foo/bar`)
+# @param {string} LIBRARIES - list of libraries (e.g., `-lopenblas`)
+#/
+$(c_targets): %.out: %.c
+ $(QUIET) $(CC) $(CFLAGS) $(fPIC) $(INCLUDE) -o $@ $(SOURCE_FILES) $< $(LIBPATH) -lm $(LIBRARIES)
+
+#/
+# Runs compiled examples.
+#
+# @example
+# make run
+#/
+run: $(c_targets)
+ $(QUIET) ./$<
+
+.PHONY: run
+
+#/
+# Removes generated files.
+#
+# @example
+# make clean
+#/
+clean:
+ $(QUIET) -rm -f *.o *.out
+
+.PHONY: clean
diff --git a/lib/node_modules/@stdlib/stats/strided/distances/dcosine-similarity/examples/c/example.c b/lib/node_modules/@stdlib/stats/strided/distances/dcosine-similarity/examples/c/example.c
new file mode 100644
index 000000000000..4fb46668e825
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/strided/distances/dcosine-similarity/examples/c/example.c
@@ -0,0 +1,45 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+* http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+#include "stdlib/stats/strided/distances/dcosine_similarity.h"
+#include
+
+int main( void ) {
+ // Create strided arrays:
+ const double x[] = { 1.0, -2.0, 3.0, -4.0, 5.0, -6.0, 7.0, -8.0 };
+ const double y[] = { 1.0, -2.0, 3.0, -4.0, 5.0, -6.0, 7.0, -8.0 };
+
+ // Specify the number of elements:
+ const int N = 8;
+
+ // Specify strides:
+ const int strideX = 1;
+ const int strideY = -1;
+
+ // Compute the cosine similarity of `x` and `y`:
+ double sim = stdlib_strided_dcosine_similarity( N, x, strideX, y, strideY );
+
+ // Print the result:
+ printf( "cosine similarity: %lf\n", sim );
+
+ // Compute the cosine similarity of `x` and `y` with offsets:
+ sim = stdlib_strided_dcosine_similarity_ndarray( N, x, strideX, 0, y, strideY, N-1 );
+
+ // Print the result:
+ printf( "cosine similarity: %lf\n", sim );
+}
diff --git a/lib/node_modules/@stdlib/stats/strided/distances/dcosine-similarity/examples/index.js b/lib/node_modules/@stdlib/stats/strided/distances/dcosine-similarity/examples/index.js
new file mode 100644
index 000000000000..14a056e79760
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/strided/distances/dcosine-similarity/examples/index.js
@@ -0,0 +1,34 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+* http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+'use strict';
+
+var discreteUniform = require( '@stdlib/random/array/discrete-uniform' );
+var dcosineSimilarity = require( './../lib' );
+
+var opts = {
+ 'dtype': 'float64'
+};
+var x = discreteUniform( 10, 0, 100, opts );
+console.log( x );
+
+var y = discreteUniform( x.length, 0, 10, opts );
+console.log( y );
+
+var out = dcosineSimilarity.ndarray( x.length, x, 1, 0, y, -1, y.length-1 );
+console.log( out );
diff --git a/lib/node_modules/@stdlib/stats/strided/distances/dcosine-similarity/include.gypi b/lib/node_modules/@stdlib/stats/strided/distances/dcosine-similarity/include.gypi
new file mode 100644
index 000000000000..4217944b5d20
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/strided/distances/dcosine-similarity/include.gypi
@@ -0,0 +1,70 @@
+# @license Apache-2.0
+#
+# Copyright (c) 2025 The Stdlib Authors.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+# http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+# A GYP include file for building a Node.js native add-on.
+#
+# Note that nesting variables is required due to how GYP processes a configuration. Any variables defined within a nested 'variables' section is defined in the outer scope. Thus, conditions in the outer variable scope are free to use these variables without running into "variable undefined" errors.
+#
+# Main documentation:
+#
+# [1]: https://gyp.gsrc.io/docs/InputFormatReference.md
+# [2]: https://gyp.gsrc.io/docs/UserDocumentation.md
+#
+# Variable nesting hacks:
+#
+# [3]: https://chromium.googlesource.com/external/skia/gyp/+/master/common_variables.gypi
+# [4]: https://src.chromium.org/viewvc/chrome/trunk/src/build/common.gypi?revision=127004
+{
+ # Define variables to be used throughout the configuration for all targets:
+ 'variables': {
+ 'variables': {
+ # Host BLAS library (to override -Dblas=):
+ 'blas%': '',
+
+ # Path to BLAS library (to override -Dblas_dir=):
+ 'blas_dir%': '',
+ }, # end variables
+
+ # Source directory:
+ 'src_dir': './src',
+
+ # Include directories:
+ 'include_dirs': [
+ '<@(blas_dir)',
+ '=0.10.0",
+ "npm": ">2.7.0"
+ },
+ "os": [
+ "aix",
+ "darwin",
+ "freebsd",
+ "linux",
+ "macos",
+ "openbsd",
+ "sunos",
+ "win32",
+ "windows"
+ ],
+ "keywords": [
+ "stdlib",
+ "stdmath",
+ "statistics",
+ "stats",
+ "mathematics",
+ "math",
+ "cosine",
+ "similarity",
+ "distance",
+ "metric",
+ "strided",
+ "strided array",
+ "typed",
+ "array",
+ "float64",
+ "double",
+ "float64array"
+ ],
+ "__stdlib__": {}
+}
diff --git a/lib/node_modules/@stdlib/stats/strided/distances/dcosine-similarity/src/Makefile b/lib/node_modules/@stdlib/stats/strided/distances/dcosine-similarity/src/Makefile
new file mode 100644
index 000000000000..7733b6180cb4
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/strided/distances/dcosine-similarity/src/Makefile
@@ -0,0 +1,70 @@
+#/
+# @license Apache-2.0
+#
+# Copyright (c) 2025 The Stdlib Authors.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+# http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+#/
+
+# VARIABLES #
+
+ifndef VERBOSE
+ QUIET := @
+else
+ QUIET :=
+endif
+
+# Determine the OS ([1][1], [2][2]).
+#
+# [1]: https://en.wikipedia.org/wiki/Uname#Examples
+# [2]: http://stackoverflow.com/a/27776822/2225624
+OS ?= $(shell uname)
+ifneq (, $(findstring MINGW,$(OS)))
+ OS := WINNT
+else
+ifneq (, $(findstring MSYS,$(OS)))
+ OS := WINNT
+else
+ifneq (, $(findstring CYGWIN,$(OS)))
+ OS := WINNT
+else
+ifneq (, $(findstring Windows_NT,$(OS)))
+ OS := WINNT
+endif
+endif
+endif
+endif
+
+
+# RULES #
+
+#/
+# Removes generated files for building an add-on.
+#
+# @example
+# make clean-addon
+#/
+clean-addon:
+ $(QUIET) -rm -f *.o *.node
+
+.PHONY: clean-addon
+
+#/
+# Removes generated files.
+#
+# @example
+# make clean
+#/
+clean: clean-addon
+
+.PHONY: clean
diff --git a/lib/node_modules/@stdlib/stats/strided/distances/dcosine-similarity/src/addon.c b/lib/node_modules/@stdlib/stats/strided/distances/dcosine-similarity/src/addon.c
new file mode 100644
index 000000000000..c3a6b76fb761
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/strided/distances/dcosine-similarity/src/addon.c
@@ -0,0 +1,66 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+* http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+#include "stdlib/stats/strided/distances/dcosine_similarity.h"
+#include "stdlib/blas/base/shared.h"
+#include "stdlib/napi/export.h"
+#include "stdlib/napi/argv.h"
+#include "stdlib/napi/argv_int64.h"
+#include "stdlib/napi/argv_strided_float64array.h"
+#include "stdlib/napi/create_double.h"
+#include
+
+/**
+* Receives JavaScript callback invocation data.
+*
+* @param env environment under which the function is invoked
+* @param info callback data
+* @return Node-API value
+*/
+static napi_value addon( napi_env env, napi_callback_info info ) {
+ STDLIB_NAPI_ARGV( env, info, argv, argc, 5 );
+ STDLIB_NAPI_ARGV_INT64( env, N, argv, 0 );
+ STDLIB_NAPI_ARGV_INT64( env, strideX, argv, 2 );
+ STDLIB_NAPI_ARGV_INT64( env, strideY, argv, 4 );
+ STDLIB_NAPI_ARGV_STRIDED_FLOAT64ARRAY( env, X, N, strideX, argv, 1 );
+ STDLIB_NAPI_ARGV_STRIDED_FLOAT64ARRAY( env, Y, N, strideY, argv, 3 );
+ STDLIB_NAPI_CREATE_DOUBLE( env, API_SUFFIX( stdlib_strided_dcosine_similarity )( N, X, strideX, Y, strideY ), v );
+ return v;
+}
+
+/**
+* Receives JavaScript callback invocation data.
+*
+* @param env environment under which the function is invoked
+* @param info callback data
+* @return Node-API value
+*/
+static napi_value addon_method( napi_env env, napi_callback_info info ) {
+ STDLIB_NAPI_ARGV( env, info, argv, argc, 7 );
+ STDLIB_NAPI_ARGV_INT64( env, N, argv, 0 );
+ STDLIB_NAPI_ARGV_INT64( env, strideX, argv, 2 );
+ STDLIB_NAPI_ARGV_INT64( env, offsetX, argv, 3 );
+ STDLIB_NAPI_ARGV_INT64( env, strideY, argv, 5 );
+ STDLIB_NAPI_ARGV_INT64( env, offsetY, argv, 6 );
+ STDLIB_NAPI_ARGV_STRIDED_FLOAT64ARRAY( env, X, N, strideX, argv, 1 );
+ STDLIB_NAPI_ARGV_STRIDED_FLOAT64ARRAY( env, Y, N, strideY, argv, 4 );
+ STDLIB_NAPI_CREATE_DOUBLE( env, API_SUFFIX( stdlib_strided_dcosine_similarity_ndarray )( N, X, strideX, offsetX, Y, strideY, offsetY ), v );
+ return v;
+}
+
+STDLIB_NAPI_MODULE_EXPORT_FCN_WITH_METHOD( addon, "ndarray", addon_method );
diff --git a/lib/node_modules/@stdlib/stats/strided/distances/dcosine-similarity/src/main.c b/lib/node_modules/@stdlib/stats/strided/distances/dcosine-similarity/src/main.c
new file mode 100644
index 000000000000..e5587b0d7471
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/strided/distances/dcosine-similarity/src/main.c
@@ -0,0 +1,66 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+* http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+#include "stdlib/stats/strided/distances/dcosine_similarity.h"
+#include "stdlib/blas/base/ddot.h"
+#include "stdlib/blas/base/dnrm2.h"
+#include "stdlib/blas/base/shared.h"
+#include "stdlib/strided/base/stride2offset.h"
+
+/**
+* Computes the cosine similarity of two double-precision floating-point strided arrays.
+*
+* @param N number of indexed elements
+* @param X first array
+* @param strideX X stride length
+* @param Y second array
+* @param strideY Y stride length
+* @return cosine similarity
+*/
+double API_SUFFIX( stdlib_strided_dcosine_similarity )( const CBLAS_INT N, const double *X, const CBLAS_INT strideX, const double *Y, const CBLAS_INT strideY ) {
+ CBLAS_INT ox = stdlib_strided_stride2offset( N, strideX );
+ CBLAS_INT oy = stdlib_strided_stride2offset( N, strideY );
+ return API_SUFFIX( stdlib_strided_dcosine_similarity_ndarray )( N, X, strideX, ox, Y, strideY, oy );
+}
+
+/**
+* Computes the cosine similarity of two double-precision floating-point strided arrays using alternative indexing semantics.
+*
+* @param N number of indexed elements
+* @param X first array
+* @param strideX X stride length
+* @param offsetX starting index for X
+* @param Y second array
+* @param strideY Y stride length
+* @param offsetY starting index for Y
+* @return cosine similarity
+*/
+double API_SUFFIX( stdlib_strided_dcosine_similarity_ndarray )( const CBLAS_INT N, const double *X, const CBLAS_INT strideX, const CBLAS_INT offsetX, const double *Y, const CBLAS_INT strideY, const CBLAS_INT offsetY ) {
+ double ynrm;
+ double xnrm;
+ double dot;
+
+ if ( N <= 0 ) {
+ return 0.0;
+ }
+
+ dot = c_ddot_ndarray( N, X, strideX, offsetX, Y, strideY, offsetY );
+ xnrm = c_dnrm2_ndarray( N, X, strideX, offsetX );
+ ynrm = c_dnrm2_ndarray( N, Y, strideY, offsetY );
+ return dot / ( xnrm*ynrm );
+}
diff --git a/lib/node_modules/@stdlib/stats/strided/distances/dcosine-similarity/test/test.dcosine_similarity.js b/lib/node_modules/@stdlib/stats/strided/distances/dcosine-similarity/test/test.dcosine_similarity.js
new file mode 100644
index 000000000000..df51115eb14e
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/strided/distances/dcosine-similarity/test/test.dcosine_similarity.js
@@ -0,0 +1,256 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+* http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+'use strict';
+
+// MODULES //
+
+var tape = require( 'tape' );
+var Float64Array = require( '@stdlib/array/float64' );
+var sqrt = require( '@stdlib/math/base/special/sqrt' );
+var dcosineSimilarity = require( './../lib/dcosine_similarity.js' );
+
+
+// TESTS //
+
+tape( 'main export is a function', function test( t ) {
+ t.ok( true, __filename );
+ t.strictEqual( typeof dcosineSimilarity, 'function', 'main export is a function' );
+ t.end();
+});
+
+tape( 'the function has an arity of 5', function test( t ) {
+ t.strictEqual( dcosineSimilarity.length, 5, 'returns expected value' );
+ t.end();
+});
+
+tape( 'the function calculates the cosine similarity of two strided arrays', function test( t ) {
+ var sim;
+ var x;
+ var y;
+
+ x = new Float64Array( [ 4.0, 2.0, -3.0, 5.0, -1.0, 2.0, -5.0, 6.0 ] );
+ y = new Float64Array( [ 2.0, 6.0, -1.0, -4.0, 8.0, 8.0, 2.0, -3.0 ] );
+
+ sim = dcosineSimilarity( x.length, x, 1, y, 1 );
+ t.strictEqual( sim, -0.11028735042288243, 'returns expected value' );
+
+ x = new Float64Array( [ 3.0, -4.0, 1.0 ] );
+ y = new Float64Array( [ 1.0, -2.0, 3.0 ] );
+
+ sim = dcosineSimilarity( x.length, x, 1, y, 1 );
+ t.strictEqual( sim, 0.7337993857053429, 'returns expected value' );
+
+ t.end();
+});
+
+tape( 'if provided an `N` parameter less than or equal to `0`, the function returns `0`', function test( t ) {
+ var sim;
+ var x;
+ var y;
+
+ x = new Float64Array( [ 3.0, -4.0, 1.0 ] );
+ y = new Float64Array( [ 1.0, -2.0, 3.0 ] );
+
+ sim = dcosineSimilarity( 0, x, 1, y, 1 );
+ t.strictEqual( sim, 0.0, 'returns expected value' );
+
+ sim = dcosineSimilarity( -4, x, 1, y, 1 );
+ t.strictEqual( sim, 0.0, 'returns expected value' );
+ t.end();
+});
+
+tape( 'the function supports an `x` stride', function test( t ) {
+ var sim;
+ var x;
+ var y;
+
+ x = new Float64Array([
+ 2.0, // 0
+ -3.0,
+ -5.0, // 1
+ 7.0,
+ 6.0 // 2
+ ]);
+ y = new Float64Array([
+ 8.0, // 0
+ 2.0, // 1
+ -3.0, // 2
+ 3.0,
+ -4.0,
+ 1.0
+ ]);
+
+ sim = dcosineSimilarity( 3, x, 2, y, 1 );
+ t.strictEqual( sim, -0.1696208382576527, 'returns expected value' );
+ t.end();
+});
+
+tape( 'the function supports a `y` stride', function test( t ) {
+ var sim;
+ var x;
+ var y;
+
+ x = new Float64Array([
+ 2.0, // 0
+ -3.0, // 1
+ -5.0, // 2
+ 7.0,
+ 6.0
+ ]);
+ y = new Float64Array([
+ 8.0, // 0
+ 2.0,
+ -3.0, // 1
+ 3.0,
+ -4.0, // 2
+ 1.0
+ ]);
+
+ sim = dcosineSimilarity( 3, x, 1, y, 2 );
+ t.strictEqual( sim, 0.7737946312060225, 'returns expected value' );
+ t.end();
+});
+
+tape( 'the function supports negative strides', function test( t ) {
+ var sim;
+ var x;
+ var y;
+
+ x = new Float64Array([
+ 1.0, // 2
+ 2.0,
+ 3.0, // 1
+ 4.0,
+ 5.0 // 0
+ ]);
+ y = new Float64Array([
+ 6.0, // 2
+ 7.0, // 1
+ 8.0, // 0
+ 9.0,
+ 10.0
+ ]);
+
+ sim = dcosineSimilarity( 3, x, -2, y, -1 );
+ t.strictEqual( sim, 0.9277856399363485, 'returns expected value' );
+ t.end();
+});
+
+tape( 'the function supports complex access patterns', function test( t ) {
+ var sim;
+ var x;
+ var y;
+
+ x = new Float64Array([
+ 1.0, // 0
+ 2.0,
+ 3.0, // 1
+ 4.0,
+ 5.0 // 2
+ ]);
+ y = new Float64Array([
+ 6.0, // 2
+ 7.0, // 1
+ 8.0, // 0
+ 9.0,
+ 10.0
+ ]);
+
+ sim = dcosineSimilarity( 3, x, 2, y, -1 );
+ t.strictEqual( sim, 0.8170052650185755, 'returns expected value' );
+ t.end();
+});
+
+tape( 'the function supports view offsets', function test( t ) {
+ var sim;
+ var x0;
+ var y0;
+ var x1;
+ var y1;
+
+ x0 = new Float64Array([
+ 1.0,
+ 2.0, // 0
+ 3.0,
+ 4.0, // 1
+ 5.0,
+ 6.0 // 2
+ ]);
+ y0 = new Float64Array([
+ 6.0,
+ 7.0,
+ 8.0,
+ 9.0, // 0
+ 10.0, // 1
+ 11.0 // 2
+ ]);
+
+ x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );
+ y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );
+
+ sim = dcosineSimilarity( 3, x1, 2, y1, 1 );
+ t.strictEqual( sim, 0.953507690477341, 'returns expected value' );
+ t.end();
+});
+
+tape( 'if both strides are equal to `1`, the function efficiently calculates the cosine similarity', function test( t ) {
+ var expected;
+ var xnrm2;
+ var ynrm2;
+ var sim;
+ var x;
+ var y;
+ var i;
+
+ expected = 0.0;
+ xnrm2 = 0.0;
+ ynrm2 = 0.0;
+ x = new Float64Array( 100 );
+ y = new Float64Array( x.length );
+ for ( i = 0; i < x.length; i++ ) {
+ x[ i ] = i;
+ y[ i ] = x.length - i;
+ expected += x[ i ] * y[ i ];
+ xnrm2 += x[ i ] * x[ i ];
+ ynrm2 += y[ i ] * y[ i ];
+ }
+ expected /= sqrt( xnrm2 ) * sqrt( ynrm2 );
+
+ sim = dcosineSimilarity( x.length, x, 1, y, 1 );
+ t.strictEqual( sim, expected, 'returns expected value' );
+
+ expected = 0.0;
+ xnrm2 = 0.0;
+ ynrm2 = 0.0;
+ x = new Float64Array( 240 );
+ y = new Float64Array( x.length );
+ for ( i = 0; i < x.length; i++ ) {
+ x[ i ] = i;
+ y[ i ] = x.length - i;
+ expected += x[ i ] * y[ i ];
+ xnrm2 += x[ i ] * x[ i ];
+ ynrm2 += y[ i ] * y[ i ];
+ }
+ expected /= sqrt( xnrm2 ) * sqrt( ynrm2 );
+
+ sim = dcosineSimilarity( x.length, x, 1, y, 1 );
+ t.strictEqual( sim, expected, 'returns expected value' );
+
+ t.end();
+});
diff --git a/lib/node_modules/@stdlib/stats/strided/distances/dcosine-similarity/test/test.dcosine_similarity.native.js b/lib/node_modules/@stdlib/stats/strided/distances/dcosine-similarity/test/test.dcosine_similarity.native.js
new file mode 100644
index 000000000000..852d47e045ff
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/strided/distances/dcosine-similarity/test/test.dcosine_similarity.native.js
@@ -0,0 +1,265 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+* http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+'use strict';
+
+// MODULES //
+
+var resolve = require( 'path' ).resolve;
+var tape = require( 'tape' );
+var Float64Array = require( '@stdlib/array/float64' );
+var sqrt = require( '@stdlib/math/base/special/sqrt' );
+var tryRequire = require( '@stdlib/utils/try-require' );
+
+
+// VARIABLES //
+
+var dcosineSimilarity = tryRequire( resolve( __dirname, './../lib/dcosine_similarity.native.js' ) );
+var opts = {
+ 'skip': ( dcosineSimilarity instanceof Error )
+};
+
+
+// TESTS //
+
+tape( 'main export is a function', opts, function test( t ) {
+ t.ok( true, __filename );
+ t.strictEqual( typeof dcosineSimilarity, 'function', 'main export is a function' );
+ t.end();
+});
+
+tape( 'the function has an arity of 5', opts, function test( t ) {
+ t.strictEqual( dcosineSimilarity.length, 5, 'returns expected value' );
+ t.end();
+});
+
+tape( 'the function calculates the cosine similarity of two strided arrays', opts, function test( t ) {
+ var sim;
+ var x;
+ var y;
+
+ x = new Float64Array( [ 4.0, 2.0, -3.0, 5.0, -1.0, 2.0, -5.0, 6.0 ] );
+ y = new Float64Array( [ 2.0, 6.0, -1.0, -4.0, 8.0, 8.0, 2.0, -3.0 ] );
+
+ sim = dcosineSimilarity( x.length, x, 1, y, 1 );
+ t.strictEqual( sim, -0.11028735042288243, 'returns expected value' );
+
+ x = new Float64Array( [ 3.0, -4.0, 1.0 ] );
+ y = new Float64Array( [ 1.0, -2.0, 3.0 ] );
+
+ sim = dcosineSimilarity( x.length, x, 1, y, 1 );
+ t.strictEqual( sim, 0.7337993857053429, 'returns expected value' );
+
+ t.end();
+});
+
+tape( 'if provided an `N` parameter less than or equal to `0`, the function returns `0`', opts, function test( t ) {
+ var sim;
+ var x;
+ var y;
+
+ x = new Float64Array( [ 3.0, -4.0, 1.0 ] );
+ y = new Float64Array( [ 1.0, -2.0, 3.0 ] );
+
+ sim = dcosineSimilarity( 0, x, 1, y, 1 );
+ t.strictEqual( sim, 0.0, 'returns expected value' );
+
+ sim = dcosineSimilarity( -4, x, 1, y, 1 );
+ t.strictEqual( sim, 0.0, 'returns expected value' );
+ t.end();
+});
+
+tape( 'the function supports an `x` stride', opts, function test( t ) {
+ var sim;
+ var x;
+ var y;
+
+ x = new Float64Array([
+ 2.0, // 0
+ -3.0,
+ -5.0, // 1
+ 7.0,
+ 6.0 // 2
+ ]);
+ y = new Float64Array([
+ 8.0, // 0
+ 2.0, // 1
+ -3.0, // 2
+ 3.0,
+ -4.0,
+ 1.0
+ ]);
+
+ sim = dcosineSimilarity( 3, x, 2, y, 1 );
+ t.strictEqual( sim, -0.1696208382576527, 'returns expected value' );
+ t.end();
+});
+
+tape( 'the function supports a `y` stride', opts, function test( t ) {
+ var sim;
+ var x;
+ var y;
+
+ x = new Float64Array([
+ 2.0, // 0
+ -3.0, // 1
+ -5.0, // 2
+ 7.0,
+ 6.0
+ ]);
+ y = new Float64Array([
+ 8.0, // 0
+ 2.0,
+ -3.0, // 1
+ 3.0,
+ -4.0, // 2
+ 1.0
+ ]);
+
+ sim = dcosineSimilarity( 3, x, 1, y, 2 );
+ t.strictEqual( sim, 0.7737946312060225, 'returns expected value' );
+ t.end();
+});
+
+tape( 'the function supports negative strides', opts, function test( t ) {
+ var sim;
+ var x;
+ var y;
+
+ x = new Float64Array([
+ 1.0, // 2
+ 2.0,
+ 3.0, // 1
+ 4.0,
+ 5.0 // 0
+ ]);
+ y = new Float64Array([
+ 6.0, // 2
+ 7.0, // 1
+ 8.0, // 0
+ 9.0,
+ 10.0
+ ]);
+
+ sim = dcosineSimilarity( 3, x, -2, y, -1 );
+ t.strictEqual( sim, 0.9277856399363485, 'returns expected value' );
+ t.end();
+});
+
+tape( 'the function supports complex access patterns', opts, function test( t ) {
+ var sim;
+ var x;
+ var y;
+
+ x = new Float64Array([
+ 1.0, // 0
+ 2.0,
+ 3.0, // 1
+ 4.0,
+ 5.0 // 2
+ ]);
+ y = new Float64Array([
+ 6.0, // 2
+ 7.0, // 1
+ 8.0, // 0
+ 9.0,
+ 10.0
+ ]);
+
+ sim = dcosineSimilarity( 3, x, 2, y, -1 );
+ t.strictEqual( sim, 0.8170052650185755, 'returns expected value' );
+ t.end();
+});
+
+tape( 'the function supports view offsets', opts, function test( t ) {
+ var sim;
+ var x0;
+ var y0;
+ var x1;
+ var y1;
+
+ x0 = new Float64Array([
+ 1.0,
+ 2.0, // 0
+ 3.0,
+ 4.0, // 1
+ 5.0,
+ 6.0 // 2
+ ]);
+ y0 = new Float64Array([
+ 6.0,
+ 7.0,
+ 8.0,
+ 9.0, // 0
+ 10.0, // 1
+ 11.0 // 2
+ ]);
+
+ x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );
+ y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );
+
+ sim = dcosineSimilarity( 3, x1, 2, y1, 1 );
+ t.strictEqual( sim, 0.953507690477341, 'returns expected value' );
+ t.end();
+});
+
+tape( 'if both strides are equal to `1`, the function efficiently calculates the cosine similarity', opts, function test( t ) {
+ var expected;
+ var xnrm2;
+ var ynrm2;
+ var sim;
+ var x;
+ var y;
+ var i;
+
+ expected = 0.0;
+ xnrm2 = 0.0;
+ ynrm2 = 0.0;
+ x = new Float64Array( 100 );
+ y = new Float64Array( x.length );
+ for ( i = 0; i < x.length; i++ ) {
+ x[ i ] = i;
+ y[ i ] = x.length - i;
+ expected += x[ i ] * y[ i ];
+ xnrm2 += x[ i ] * x[ i ];
+ ynrm2 += y[ i ] * y[ i ];
+ }
+ expected /= sqrt( xnrm2 ) * sqrt( ynrm2 );
+
+ sim = dcosineSimilarity( x.length, x, 1, y, 1 );
+ t.strictEqual( sim, expected, 'returns expected value' );
+
+ expected = 0.0;
+ xnrm2 = 0.0;
+ ynrm2 = 0.0;
+ x = new Float64Array( 240 );
+ y = new Float64Array( x.length );
+ for ( i = 0; i < x.length; i++ ) {
+ x[ i ] = i;
+ y[ i ] = x.length - i;
+ expected += x[ i ] * y[ i ];
+ xnrm2 += x[ i ] * x[ i ];
+ ynrm2 += y[ i ] * y[ i ];
+ }
+ expected /= sqrt( xnrm2 ) * sqrt( ynrm2 );
+
+ sim = dcosineSimilarity( x.length, x, 1, y, 1 );
+ t.strictEqual( sim, expected, 'returns expected value' );
+
+ t.end();
+});
diff --git a/lib/node_modules/@stdlib/stats/strided/distances/dcosine-similarity/test/test.js b/lib/node_modules/@stdlib/stats/strided/distances/dcosine-similarity/test/test.js
new file mode 100644
index 000000000000..54233e9eeec9
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/strided/distances/dcosine-similarity/test/test.js
@@ -0,0 +1,82 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+* http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+'use strict';
+
+// MODULES //
+
+var tape = require( 'tape' );
+var proxyquire = require( 'proxyquire' );
+var IS_BROWSER = require( '@stdlib/assert/is-browser' );
+var dcosineSimilarity = require( './../lib' );
+
+
+// VARIABLES //
+
+var opts = {
+ 'skip': IS_BROWSER
+};
+
+
+// TESTS //
+
+tape( 'main export is a function', function test( t ) {
+ t.ok( true, __filename );
+ t.strictEqual( typeof dcosineSimilarity, '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 dcosineSimilarity.ndarray, 'function', 'method is a function' );
+ t.end();
+});
+
+tape( 'if a native implementation is available, the main export is the native implementation', opts, function test( t ) {
+ var dcosineSimilarity = proxyquire( './../lib', {
+ '@stdlib/utils/try-require': tryRequire
+ });
+
+ t.strictEqual( dcosineSimilarity, mock, 'returns expected value' );
+ t.end();
+
+ function tryRequire() {
+ return mock;
+ }
+
+ function mock() {
+ // Mock...
+ }
+});
+
+tape( 'if a native implementation is not available, the main export is a JavaScript implementation', opts, function test( t ) {
+ var dcosineSimilarity;
+ var main;
+
+ main = require( './../lib/dcosine_similarity.js' );
+
+ dcosineSimilarity = proxyquire( './../lib', {
+ '@stdlib/utils/try-require': tryRequire
+ });
+
+ t.strictEqual( dcosineSimilarity, main, 'returns expected value' );
+ t.end();
+
+ function tryRequire() {
+ return new Error( 'Cannot find module' );
+ }
+});
diff --git a/lib/node_modules/@stdlib/stats/strided/distances/dcosine-similarity/test/test.ndarray.js b/lib/node_modules/@stdlib/stats/strided/distances/dcosine-similarity/test/test.ndarray.js
new file mode 100644
index 000000000000..a6b8fdab2b12
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/strided/distances/dcosine-similarity/test/test.ndarray.js
@@ -0,0 +1,279 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+* http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+'use strict';
+
+// MODULES //
+
+var tape = require( 'tape' );
+var Float64Array = require( '@stdlib/array/float64' );
+var sqrt = require( '@stdlib/math/base/special/sqrt' );
+var dcosineSimilarity = require( './../lib/ndarray.js' );
+
+
+// TESTS //
+
+tape( 'main export is a function', function test( t ) {
+ t.ok( true, __filename );
+ t.strictEqual( typeof dcosineSimilarity, 'function', 'main export is a function' );
+ t.end();
+});
+
+tape( 'the function has an arity of 7', function test( t ) {
+ t.strictEqual( dcosineSimilarity.length, 7, 'returns expected value' );
+ t.end();
+});
+
+tape( 'the function calculates the cosine similarity of two strided arrays', function test( t ) {
+ var sim;
+ var x;
+ var y;
+
+ x = new Float64Array( [ 4.0, 2.0, -3.0, 5.0, -1.0, 2.0, -5.0, 6.0 ] );
+ y = new Float64Array( [ 2.0, 6.0, -1.0, -4.0, 8.0, 8.0, 2.0, -3.0 ] );
+
+ sim = dcosineSimilarity( x.length, x, 1, 0, y, 1, 0 );
+ t.strictEqual( sim, -0.11028735042288243, 'returns expected value' );
+
+ x = new Float64Array( [ 3.0, -4.0, 1.0 ] );
+ y = new Float64Array( [ 1.0, -2.0, 3.0 ] );
+
+ sim = dcosineSimilarity( x.length, x, 1, 0, y, 1, 0 );
+ t.strictEqual( sim, 0.7337993857053429, 'returns expected value' );
+
+ t.end();
+});
+
+tape( 'if provided an `N` parameter less than or equal to `0`, the function returns `0`', function test( t ) {
+ var sim;
+ var x;
+ var y;
+
+ x = new Float64Array( [ 3.0, -4.0, 1.0 ] );
+ y = new Float64Array( [ 1.0, -2.0, 3.0 ] );
+
+ sim = dcosineSimilarity( 0, x, 1, 0, y, 1, 0 );
+ t.strictEqual( sim, 0.0, 'returns expected value' );
+
+ sim = dcosineSimilarity( -4, x, 1, 0, y, 1, 0 );
+ t.strictEqual( sim, 0.0, 'returns expected value' );
+ t.end();
+});
+
+tape( 'the function supports an `x` stride', function test( t ) {
+ var sim;
+ var x;
+ var y;
+
+ x = new Float64Array([
+ 2.0, // 0
+ -3.0,
+ -5.0, // 1
+ 7.0,
+ 6.0 // 2
+ ]);
+ y = new Float64Array([
+ 8.0, // 0
+ 2.0, // 1
+ -3.0, // 2
+ 3.0,
+ -4.0,
+ 1.0
+ ]);
+
+ sim = dcosineSimilarity( 3, x, 2, 0, y, 1, 0 );
+ t.strictEqual( sim, -0.1696208382576527, 'returns expected value' );
+ t.end();
+});
+
+tape( 'the function supports an `x` offset', function test( t ) {
+ var sim;
+ var x;
+ var y;
+
+ x = new Float64Array([
+ 1.0,
+ 2.0, // 0
+ 3.0,
+ 4.0, // 1
+ 5.0,
+ 6.0 // 2
+ ]);
+ y = new Float64Array([
+ 6.0, // 0
+ 7.0, // 1
+ 8.0, // 2
+ 9.0,
+ 10.0,
+ 11.0
+ ]);
+
+ sim = dcosineSimilarity( 3, x, 2, 1, y, 1, 0 );
+ t.strictEqual( sim, 0.9633753381657649, 'returns expected value' );
+ t.end();
+});
+
+tape( 'the function supports a `y` stride', function test( t ) {
+ var sim;
+ var x;
+ var y;
+
+ x = new Float64Array([
+ 2.0, // 0
+ -3.0, // 1
+ -5.0, // 2
+ 7.0,
+ 6.0
+ ]);
+ y = new Float64Array([
+ 8.0, // 0
+ 2.0,
+ -3.0, // 1
+ 3.0,
+ -4.0, // 2
+ 1.0
+ ]);
+
+ sim = dcosineSimilarity( 3, x, 1, 0, y, 2, 0 );
+ t.strictEqual( sim, 0.7737946312060225, 'returns expected value' );
+ t.end();
+});
+
+tape( 'the function supports a `y` offset', function test( t ) {
+ var sim;
+ var x;
+ var y;
+
+ x = new Float64Array([
+ 1.0, // 0
+ 2.0,
+ 3.0, // 1
+ 4.0,
+ 5.0, // 2
+ 6.0
+ ]);
+ y = new Float64Array([
+ 6.0,
+ 7.0,
+ 8.0,
+ 9.0, // 0
+ 10.0, // 1
+ 11.0 // 2
+ ]);
+
+ sim = dcosineSimilarity( 3, x, 2, 0, y, 1, 3 );
+ t.strictEqual( sim, 0.9143034529972666, 'returns expected value' );
+ t.end();
+});
+
+tape( 'the function supports negative strides', function test( t ) {
+ var sim;
+ var x;
+ var y;
+
+ x = new Float64Array([
+ 1.0, // 2
+ 2.0,
+ 3.0, // 1
+ 4.0,
+ 5.0 // 0
+ ]);
+ y = new Float64Array([
+ 6.0, // 2
+ 7.0, // 1
+ 8.0, // 0
+ 9.0,
+ 10.0
+ ]);
+
+ sim = dcosineSimilarity( 3, x, -2, x.length-1, y, -1, 2 );
+ t.strictEqual( sim, 0.9277856399363485, 'returns expected value' );
+ t.end();
+});
+
+tape( 'the function supports complex access patterns', function test( t ) {
+ var sim;
+ var x;
+ var y;
+
+ x = new Float64Array([
+ 1.0, // 0
+ 2.0,
+ 3.0, // 1
+ 4.0,
+ 5.0 // 2
+ ]);
+ y = new Float64Array([
+ 6.0,
+ 7.0, // 2
+ 8.0, // 1
+ 9.0, // 0
+ 10.0
+ ]);
+
+ sim = dcosineSimilarity( 3, x, 2, 0, y, -1, y.length-2 );
+ t.strictEqual( sim, 0.8252281337630523, 'returns expected value' );
+ t.end();
+});
+
+tape( 'if both strides are equal to `1`, the function efficiently calculates the cosine similarity', function test( t ) {
+ var expected;
+ var xnrm2;
+ var ynrm2;
+ var sim;
+ var x;
+ var y;
+ var i;
+
+ expected = 0.0;
+ xnrm2 = 0.0;
+ ynrm2 = 0.0;
+ x = new Float64Array( 100 );
+ y = new Float64Array( x.length );
+ for ( i = 0; i < x.length; i++ ) {
+ x[ i ] = i;
+ y[ i ] = x.length - i;
+ expected += x[ i ] * y[ i ];
+ xnrm2 += x[ i ] * x[ i ];
+ ynrm2 += y[ i ] * y[ i ];
+ }
+ expected /= sqrt( xnrm2 ) * sqrt( ynrm2 );
+
+ sim = dcosineSimilarity( x.length, x, 1, 0, y, 1, 0 );
+
+ t.strictEqual( sim, expected, 'returns expected value' );
+
+ expected = 0.0;
+ xnrm2 = 0.0;
+ ynrm2 = 0.0;
+ x = new Float64Array( 240 );
+ y = new Float64Array( x.length );
+ for ( i = 0; i < x.length; i++ ) {
+ x[ i ] = i;
+ y[ i ] = x.length - i;
+ expected += x[ i ] * y[ i ];
+ xnrm2 += x[ i ] * x[ i ];
+ ynrm2 += y[ i ] * y[ i ];
+ }
+ expected /= sqrt( xnrm2 ) * sqrt( ynrm2 );
+
+ sim = dcosineSimilarity( x.length, x, 1, 0, y, 1, 0 );
+
+ t.strictEqual( sim, expected, 'returns expected value' );
+ t.end();
+});
diff --git a/lib/node_modules/@stdlib/stats/strided/distances/dcosine-similarity/test/test.ndarray.native.js b/lib/node_modules/@stdlib/stats/strided/distances/dcosine-similarity/test/test.ndarray.native.js
new file mode 100644
index 000000000000..482d1966b558
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/strided/distances/dcosine-similarity/test/test.ndarray.native.js
@@ -0,0 +1,288 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+* http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+'use strict';
+
+// MODULES //
+
+var resolve = require( 'path' ).resolve;
+var tape = require( 'tape' );
+var Float64Array = require( '@stdlib/array/float64' );
+var sqrt = require( '@stdlib/math/base/special/sqrt' );
+var tryRequire = require( '@stdlib/utils/try-require' );
+
+
+// VARIABLES //
+
+var dcosineSimilarity = tryRequire( resolve( __dirname, './../lib/ndarray.native.js' ) );
+var opts = {
+ 'skip': ( dcosineSimilarity instanceof Error )
+};
+
+
+// TESTS //
+
+tape( 'main export is a function', opts, function test( t ) {
+ t.ok( true, __filename );
+ t.strictEqual( typeof dcosineSimilarity, 'function', 'main export is a function' );
+ t.end();
+});
+
+tape( 'the function has an arity of 7', opts, function test( t ) {
+ t.strictEqual( dcosineSimilarity.length, 7, 'returns expected value' );
+ t.end();
+});
+
+tape( 'the function calculates the cosine similarity of two strided arrays', opts, function test( t ) {
+ var sim;
+ var x;
+ var y;
+
+ x = new Float64Array( [ 4.0, 2.0, -3.0, 5.0, -1.0, 2.0, -5.0, 6.0 ] );
+ y = new Float64Array( [ 2.0, 6.0, -1.0, -4.0, 8.0, 8.0, 2.0, -3.0 ] );
+
+ sim = dcosineSimilarity( x.length, x, 1, 0, y, 1, 0 );
+ t.strictEqual( sim, -0.11028735042288243, 'returns expected value' );
+
+ x = new Float64Array( [ 3.0, -4.0, 1.0 ] );
+ y = new Float64Array( [ 1.0, -2.0, 3.0 ] );
+
+ sim = dcosineSimilarity( x.length, x, 1, 0, y, 1, 0 );
+ t.strictEqual( sim, 0.7337993857053429, 'returns expected value' );
+
+ t.end();
+});
+
+tape( 'if provided an `N` parameter less than or equal to `0`, the function returns `0`', opts, function test( t ) {
+ var sim;
+ var x;
+ var y;
+
+ x = new Float64Array( [ 3.0, -4.0, 1.0 ] );
+ y = new Float64Array( [ 1.0, -2.0, 3.0 ] );
+
+ sim = dcosineSimilarity( 0, x, 1, 0, y, 1, 0 );
+ t.strictEqual( sim, 0.0, 'returns expected value' );
+
+ sim = dcosineSimilarity( -4, x, 1, 0, y, 1, 0 );
+ t.strictEqual( sim, 0.0, 'returns expected value' );
+ t.end();
+});
+
+tape( 'the function supports an `x` stride', opts, function test( t ) {
+ var sim;
+ var x;
+ var y;
+
+ x = new Float64Array([
+ 2.0, // 0
+ -3.0,
+ -5.0, // 1
+ 7.0,
+ 6.0 // 2
+ ]);
+ y = new Float64Array([
+ 8.0, // 0
+ 2.0, // 1
+ -3.0, // 2
+ 3.0,
+ -4.0,
+ 1.0
+ ]);
+
+ sim = dcosineSimilarity( 3, x, 2, 0, y, 1, 0 );
+ t.strictEqual( sim, -0.1696208382576527, 'returns expected value' );
+ t.end();
+});
+
+tape( 'the function supports an `x` offset', opts, function test( t ) {
+ var sim;
+ var x;
+ var y;
+
+ x = new Float64Array([
+ 1.0,
+ 2.0, // 0
+ 3.0,
+ 4.0, // 1
+ 5.0,
+ 6.0 // 2
+ ]);
+ y = new Float64Array([
+ 6.0, // 0
+ 7.0, // 1
+ 8.0, // 2
+ 9.0,
+ 10.0,
+ 11.0
+ ]);
+
+ sim = dcosineSimilarity( 3, x, 2, 1, y, 1, 0 );
+ t.strictEqual( sim, 0.9633753381657649, 'returns expected value' );
+ t.end();
+});
+
+tape( 'the function supports a `y` stride', opts, function test( t ) {
+ var sim;
+ var x;
+ var y;
+
+ x = new Float64Array([
+ 2.0, // 0
+ -3.0, // 1
+ -5.0, // 2
+ 7.0,
+ 6.0
+ ]);
+ y = new Float64Array([
+ 8.0, // 0
+ 2.0,
+ -3.0, // 1
+ 3.0,
+ -4.0, // 2
+ 1.0
+ ]);
+
+ sim = dcosineSimilarity( 3, x, 1, 0, y, 2, 0 );
+ t.strictEqual( sim, 0.7737946312060225, 'returns expected value' );
+ t.end();
+});
+
+tape( 'the function supports a `y` offset', opts, function test( t ) {
+ var sim;
+ var x;
+ var y;
+
+ x = new Float64Array([
+ 1.0, // 0
+ 2.0,
+ 3.0, // 1
+ 4.0,
+ 5.0, // 2
+ 6.0
+ ]);
+ y = new Float64Array([
+ 6.0,
+ 7.0,
+ 8.0,
+ 9.0, // 0
+ 10.0, // 1
+ 11.0 // 2
+ ]);
+
+ sim = dcosineSimilarity( 3, x, 2, 0, y, 1, 3 );
+ t.strictEqual( sim, 0.9143034529972666, 'returns expected value' );
+ t.end();
+});
+
+tape( 'the function supports negative strides', opts, function test( t ) {
+ var sim;
+ var x;
+ var y;
+
+ x = new Float64Array([
+ 1.0, // 2
+ 2.0,
+ 3.0, // 1
+ 4.0,
+ 5.0 // 0
+ ]);
+ y = new Float64Array([
+ 6.0, // 2
+ 7.0, // 1
+ 8.0, // 0
+ 9.0,
+ 10.0
+ ]);
+
+ sim = dcosineSimilarity( 3, x, -2, x.length-1, y, -1, 2 );
+ t.strictEqual( sim, 0.9277856399363485, 'returns expected value' );
+ t.end();
+});
+
+tape( 'the function supports complex access patterns', opts, function test( t ) {
+ var sim;
+ var x;
+ var y;
+
+ x = new Float64Array([
+ 1.0, // 0
+ 2.0,
+ 3.0, // 1
+ 4.0,
+ 5.0 // 2
+ ]);
+ y = new Float64Array([
+ 6.0,
+ 7.0, // 2
+ 8.0, // 1
+ 9.0, // 0
+ 10.0
+ ]);
+
+ sim = dcosineSimilarity( 3, x, 2, 0, y, -1, y.length-2 );
+ t.strictEqual( sim, 0.8252281337630523, 'returns expected value' );
+ t.end();
+});
+
+tape( 'if both strides are equal to `1`, the function efficiently calculates the cosine similarity', opts, function test( t ) {
+ var expected;
+ var xnrm2;
+ var ynrm2;
+ var sim;
+ var x;
+ var y;
+ var i;
+
+ expected = 0.0;
+ xnrm2 = 0.0;
+ ynrm2 = 0.0;
+ x = new Float64Array( 100 );
+ y = new Float64Array( x.length );
+ for ( i = 0; i < x.length; i++ ) {
+ x[ i ] = i;
+ y[ i ] = x.length - i;
+ expected += x[ i ] * y[ i ];
+ xnrm2 += x[ i ] * x[ i ];
+ ynrm2 += y[ i ] * y[ i ];
+ }
+ expected /= sqrt( xnrm2 ) * sqrt( ynrm2 );
+
+ sim = dcosineSimilarity( x.length, x, 1, 0, y, 1, 0 );
+
+ t.strictEqual( sim, expected, 'returns expected value' );
+
+ expected = 0.0;
+ xnrm2 = 0.0;
+ ynrm2 = 0.0;
+ x = new Float64Array( 240 );
+ y = new Float64Array( x.length );
+ for ( i = 0; i < x.length; i++ ) {
+ x[ i ] = i;
+ y[ i ] = x.length - i;
+ expected += x[ i ] * y[ i ];
+ xnrm2 += x[ i ] * x[ i ];
+ ynrm2 += y[ i ] * y[ i ];
+ }
+ expected /= sqrt( xnrm2 ) * sqrt( ynrm2 );
+
+ sim = dcosineSimilarity( x.length, x, 1, 0, y, 1, 0 );
+
+ t.strictEqual( sim, expected, 'returns expected value' );
+ t.end();
+});