diff --git a/lib/node_modules/@stdlib/blas/sasum/README.md b/lib/node_modules/@stdlib/blas/sasum/README.md
new file mode 100644
index 000000000000..daae636fabe1
--- /dev/null
+++ b/lib/node_modules/@stdlib/blas/sasum/README.md
@@ -0,0 +1,167 @@
+
+
+# sasum
+
+> Compute the sum of [absolute values][@stdlib/math/base/special/abs] ([_L1_ norm][l1norm]).
+
+
+
+The [_L1_ norm][l1norm] is defined as
+
+
+
+```math
+\|\mathbf{x}\|_1 = \sum_{i=0}^{n-1} \vert x_i \vert
+```
+
+
+
+
+
+
+
+
+
+
+
+## Usage
+
+```javascript
+var sasum = require( '@stdlib/blas/sasum' );
+```
+
+#### sasum( x\[, dim] )
+
+Computes the sum of [absolute values][@stdlib/math/base/special/abs].
+
+```javascript
+var Float32Array = require( '@stdlib/array/float32' );
+var array = require( '@stdlib/ndarray/array' );
+
+var x = array( new Float32Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] ) );
+
+var z = sasum( x );
+// returns
+
+var v = z.get();
+// returns 15.0
+```
+
+The function has the following parameters:
+
+- **x**: a non-zero-dimensional [`ndarray`][@stdlib/ndarray/ctor] whose underlying data type is `float32`.
+- **dim**: dimension for which to compute the sum. Must be a negative integer. Negative indices are resolved relative to the last array dimension, with the last dimension corresponding to `-1`. Default: `-1`.
+
+For multi-dimensional input [`ndarrays`][@stdlib/ndarray/ctor], the function performs batched computation, such that the function computes the sum for each pair of vectors in `x` according to the specified dimension index.
+
+```javascript
+var Float32Array = require( '@stdlib/array/float32' );
+var array = require( '@stdlib/ndarray/array' );
+
+var opts = {
+ 'shape': [ 2, 3 ]
+};
+var x = array( new Float32Array( [ 4.0, 2.0, -3.0, 5.0, -1.0, 3.0 ] ), opts );
+
+var z = sasum( x );
+// returns
+
+var v1 = z.get( 0 );
+// returns 9.0
+
+var v2 = z.get( 1 );
+// returns 9.0
+```
+
+
+
+
+
+
+
+## Notes
+
+- Negative indices are resolved relative to the last [`ndarray`][@stdlib/ndarray/ctor] dimension, with the last dimension corresponding to `-1`.
+- The output [`ndarray`][@stdlib/ndarray/ctor] has the same data type as the input [`ndarray`][@stdlib/ndarray/ctor] and has a shape which is determined by broadcasting and excludes the contracted dimension.
+- If provided an empty vector, the sum is `0`.
+- `sasum()` provides a higher-level interface to the [BLAS][blas] level 1 function [`sasum`][@stdlib/blas/base/sasum].
+
+
+
+
+
+
+
+## Examples
+
+
+
+```javascript
+var discreteUniform = require( '@stdlib/random/array/discrete-uniform' );
+var ndarray2array = require( '@stdlib/ndarray/to-array' );
+var array = require( '@stdlib/ndarray/array' );
+var sasum = require( '@stdlib/blas/sasum' );
+
+var opts = {
+ 'dtype': 'float32'
+};
+
+var x = array( discreteUniform( 10, 0, 100, opts ), {
+ 'shape': [ 5, 2 ]
+});
+console.log( ndarray2array( x ) );
+
+var z = sasum( x, -1 );
+console.log( ndarray2array( z ) );
+```
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+[l1norm]: https://en.wikipedia.org/wiki/Norm_%28mathematics%29
+
+[@stdlib/math/base/special/abs]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/math/base/special/abs
+
+[blas]: http://www.netlib.org/blas
+
+[@stdlib/ndarray/ctor]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/ndarray/ctor
+
+[@stdlib/blas/base/sasum]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/blas/base/sasum
+
+
+
+
diff --git a/lib/node_modules/@stdlib/blas/sasum/benchmark/benchmark.js b/lib/node_modules/@stdlib/blas/sasum/benchmark/benchmark.js
new file mode 100644
index 000000000000..44e4224e9fd9
--- /dev/null
+++ b/lib/node_modules/@stdlib/blas/sasum/benchmark/benchmark.js
@@ -0,0 +1,103 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2024 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 isnan = require( '@stdlib/math/base/assert/is-nan' );
+var pow = require( '@stdlib/math/base/special/pow' );
+var uniform = require( '@stdlib/random/array/uniform' );
+var array = require( '@stdlib/ndarray/array' );
+var pkg = require( './../package.json' ).name;
+var sasum = require( './../lib/main.js' );
+
+
+// VARIABLES //
+
+var opts = {
+ 'dtype': 'float32'
+};
+
+
+// FUNCTIONS //
+
+/**
+* Creates a benchmark function.
+*
+* @private
+* @param {PositiveInteger} len - array length
+* @returns {Function} benchmark function
+*/
+function createBenchmark( len ) {
+ var x = array( uniform( len, -100.0, 100.0, opts ) );
+ return benchmark;
+
+ /**
+ * Benchmark function.
+ *
+ * @private
+ * @param {Benchmark} b - benchmark instance
+ */
+ function benchmark( b ) {
+ var d;
+ var i;
+
+ b.tic();
+ for ( i = 0; i < b.iterations; i++ ) {
+ d = sasum( x );
+ if ( isnan( d.get() ) ) {
+ b.fail( 'should not return NaN' );
+ }
+ }
+ b.toc();
+ if ( isnan( d.get() ) ) {
+ 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( pkg+'::vectors:len='+len, f );
+ }
+}
+
+main();
diff --git a/lib/node_modules/@stdlib/blas/sasum/benchmark/benchmark.stack.js b/lib/node_modules/@stdlib/blas/sasum/benchmark/benchmark.stack.js
new file mode 100644
index 000000000000..939ccc3867ec
--- /dev/null
+++ b/lib/node_modules/@stdlib/blas/sasum/benchmark/benchmark.stack.js
@@ -0,0 +1,120 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2024 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 isnan = require( '@stdlib/math/base/assert/is-nan' );
+var pow = require( '@stdlib/math/base/special/pow' );
+var uniform = require( '@stdlib/random/array/uniform' );
+var numel = require( '@stdlib/ndarray/base/numel' );
+var array = require( '@stdlib/ndarray/array' );
+var pkg = require( './../package.json' ).name;
+var sasum = require( './../lib/main.js' );
+
+
+// VARIABLES //
+
+var OPTS = {
+ 'dtype': 'float32'
+};
+
+
+// FUNCTIONS //
+
+/**
+* Creates a benchmark function.
+*
+* @private
+* @param {PositiveIntegerArray} shape - array shape
+* @returns {Function} benchmark function
+*/
+function createBenchmark( shape ) {
+ var x;
+ var N;
+ var o;
+
+ N = numel( shape );
+ o = {
+ 'shape': shape
+ };
+ x = array( uniform( N, -100.0, 100.0, OPTS ), o );
+
+ return benchmark;
+
+ /**
+ * Benchmark function.
+ *
+ * @private
+ * @param {Benchmark} b - benchmark instance
+ */
+ function benchmark( b ) {
+ var d;
+ var i;
+
+ b.tic();
+ for ( i = 0; i < b.iterations; i++ ) {
+ d = sasum( x );
+ if ( isnan( d.iget( 0 ) ) ) {
+ b.fail( 'should not return NaN' );
+ }
+ }
+ b.toc();
+ if ( isnan( d.iget( 0 ) ) ) {
+ b.fail( 'should not return NaN' );
+ }
+ b.pass( 'benchmark finished' );
+ b.end();
+ }
+}
+
+
+// MAIN //
+
+/**
+* Main execution sequence.
+*
+* @private
+*/
+function main() {
+ var shape;
+ var min;
+ var max;
+ var N;
+ var f;
+ var i;
+
+ min = 1; // 10^min
+ max = 6; // 10^max
+
+ for ( i = min; i <= max; i++ ) {
+ N = pow( 10, i );
+
+ shape = [ 2, N/2 ];
+ f = createBenchmark( shape );
+ bench( pkg+'::stacks:size='+N+',ndims='+shape.length+',shape=('+shape.join( ',' )+')', f );
+
+ shape = [ N/2, 2 ];
+ f = createBenchmark( shape );
+ bench( pkg+'::stacks:size='+N+',ndims='+shape.length+',shape=('+shape.join( ',' )+')', f );
+ }
+}
+
+main();
diff --git a/lib/node_modules/@stdlib/blas/sasum/docs/img/equation_l1norm.svg b/lib/node_modules/@stdlib/blas/sasum/docs/img/equation_l1norm.svg
new file mode 100644
index 000000000000..4dbb928da546
--- /dev/null
+++ b/lib/node_modules/@stdlib/blas/sasum/docs/img/equation_l1norm.svg
@@ -0,0 +1,44 @@
+
\ No newline at end of file
diff --git a/lib/node_modules/@stdlib/blas/sasum/docs/repl.txt b/lib/node_modules/@stdlib/blas/sasum/docs/repl.txt
new file mode 100644
index 000000000000..244ce215e181
--- /dev/null
+++ b/lib/node_modules/@stdlib/blas/sasum/docs/repl.txt
@@ -0,0 +1,39 @@
+
+{{alias}}( x[, dim] )
+ Computes the sum of absolute values.
+
+ For multi-dimensional input array, the function performs batched
+ computation, such that the function computes the sum for each pair
+ of vectors in `x` according to the specified dimension index.
+
+ If provided an empty vector, the sum is `0`.
+
+ Parameters
+ ----------
+ x: ndarray
+ First input array. Must have a 'float32' data type. Must have at least
+ one dimension.
+
+ dim: integer (optional)
+ Dimension index for which to compute the dot product. Must be a negative
+ integer. Negative indices are resolved relative to the last array
+ dimension, with the last dimension corresponding to `-1`. Default: -1.
+
+ Returns
+ -------
+ out: ndarray
+ The dot product. The output array has the same data type and shape as
+ the input array.
+
+ Examples
+ --------
+ > var xbuf = new {{alias:@stdlib/array/float32}}( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] );
+ > var x = {{alias:@stdlib/ndarray/array}}( xbuf );
+ > var z = {{alias}}( x )
+
+ > z.get()
+ 15.0
+
+ See Also
+ --------
+
diff --git a/lib/node_modules/@stdlib/blas/sasum/docs/types/index.d.ts b/lib/node_modules/@stdlib/blas/sasum/docs/types/index.d.ts
new file mode 100644
index 000000000000..8605a0380f4e
--- /dev/null
+++ b/lib/node_modules/@stdlib/blas/sasum/docs/types/index.d.ts
@@ -0,0 +1,60 @@
+/*
+* @license Apache-2.0
+*
+* Copyright (c) 2024 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+* http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+// TypeScript Version: 4.1
+
+///
+
+import { float32ndarray } from '@stdlib/types/ndarray';
+
+/**
+* Computes the sum of absolute values.
+*
+* ## Notes
+*
+* - If provided at least one input array having more than one dimension, the input arrays are broadcasted to a common shape.
+* - For multi-dimensional input arrays, the function performs batched computation, such that the function computes the dot product for each pair of vectors in `x` and `y` according to the specified dimension index.
+* - The size of the contracted dimension must be the same for both input arrays.
+* - The function resolves the dimension index for which to compute the dot product **before** broadcasting.
+* - If provided empty vectors, the dot product is `0`.
+* - Negative indices are resolved relative to the last array dimension, with the last dimension corresponding to `-1`.
+* - The output array has the same data type as the input arrays and has a shape which is determined by broadcasting and excludes the contracted dimension.
+*
+* @param x - input array
+* @param dim - dimension for which to compute the sum (default: -1)
+* @throws first argument must be a non-zero-dimensional ndarray containing single-precision floating-point numbers
+* @returns sum
+*
+* @example
+* var Float32Array = require( '@stdlib/array/float32' );
+* var array = require( '@stdlib/ndarray/array' );
+*
+* var x = array( new Float32Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] ) );
+*
+* var z = sasum( x );
+* returns
+*
+* var v = z.get();
+* // returns 15.0
+*/
+declare function sasum( x: float32ndarray, dim?: number ): float32ndarray;
+
+
+// EXPORTS //
+
+export = sasum;
diff --git a/lib/node_modules/@stdlib/blas/sasum/docs/types/test.ts b/lib/node_modules/@stdlib/blas/sasum/docs/types/test.ts
new file mode 100644
index 000000000000..79868d446475
--- /dev/null
+++ b/lib/node_modules/@stdlib/blas/sasum/docs/types/test.ts
@@ -0,0 +1,102 @@
+/*
+* @license Apache-2.0
+*
+* Copyright (c) 2024 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+* http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+import zeros = require( '@stdlib/ndarray/zeros' );
+import sasum = require( './index' );
+
+
+// TESTS //
+
+// The function returns a number...
+{
+ sasum( zeros( [ 10 ] ), zeros( [ 10 ] ) ); // $ExpectType float32ndarray
+}
+
+// The compiler throws an error if the function is provided a first argument which is not an ndarray...
+{
+ const y = zeros( [ 10 ] );
+
+ sasum( 10, y ); // $ExpectError
+ sasum( '10', y ); // $ExpectError
+ sasum( true, y ); // $ExpectError
+ sasum( false, y ); // $ExpectError
+ sasum( null, y ); // $ExpectError
+ sasum( undefined, y ); // $ExpectError
+ sasum( {}, y ); // $ExpectError
+ sasum( [], y ); // $ExpectError
+ sasum( ( x: number ): number => x, y ); // $ExpectError
+
+ sasum( 10, y, -1 ); // $ExpectError
+ sasum( '10', y, -1 ); // $ExpectError
+ sasum( true, y, -1 ); // $ExpectError
+ sasum( false, y, -1 ); // $ExpectError
+ sasum( null, y, -1 ); // $ExpectError
+ sasum( undefined, y, -1 ); // $ExpectError
+ sasum( {}, y, -1 ); // $ExpectError
+ sasum( [], y, -1 ); // $ExpectError
+ sasum( ( x: number ): number => x, y, -1 ); // $ExpectError
+}
+
+// The compiler throws an error if the function is provided a second argument which is not an ndarray...
+{
+ const x = zeros( [ 10 ] );
+
+ sasum( x, 10 ); // $ExpectError
+ sasum( x, '10' ); // $ExpectError
+ sasum( x, true ); // $ExpectError
+ sasum( x, false ); // $ExpectError
+ sasum( x, null ); // $ExpectError
+ sasum( x, undefined ); // $ExpectError
+ sasum( x, {} ); // $ExpectError
+ sasum( x, [] ); // $ExpectError
+ sasum( x, ( x: number ): number => x ); // $ExpectError
+
+ sasum( x, 10, -1 ); // $ExpectError
+ sasum( x, '10', -1 ); // $ExpectError
+ sasum( x, true, -1 ); // $ExpectError
+ sasum( x, false, -1 ); // $ExpectError
+ sasum( x, null, -1 ); // $ExpectError
+ sasum( x, undefined, -1 ); // $ExpectError
+ sasum( x, {}, -1 ); // $ExpectError
+ sasum( x, [], -1 ); // $ExpectError
+ sasum( x, ( x: number ): number => x, -1 ); // $ExpectError
+}
+
+// The compiler throws an error if the function is provided a third argument which is not a number...
+{
+ const x = zeros( [ 10 ] );
+ const y = zeros( [ 10 ] );
+
+ sasum( x, y, '10' ); // $ExpectError
+ sasum( x, y, true ); // $ExpectError
+ sasum( x, y, false ); // $ExpectError
+ sasum( x, y, null ); // $ExpectError
+ sasum( x, y, {} ); // $ExpectError
+ sasum( x, y, [] ); // $ExpectError
+ sasum( x, y, ( x: number ): number => x ); // $ExpectError
+}
+
+// The compiler throws an error if the function is provided an unsupported number of arguments...
+{
+ const x = zeros( [ 10 ] );
+ const y = zeros( [ 10 ] );
+
+ sasum(); // $ExpectError
+ sasum( x ); // $ExpectError
+ sasum( x, y, -1, {} ); // $ExpectError
+}
diff --git a/lib/node_modules/@stdlib/blas/sasum/examples/index.js b/lib/node_modules/@stdlib/blas/sasum/examples/index.js
new file mode 100644
index 000000000000..8edafc778c63
--- /dev/null
+++ b/lib/node_modules/@stdlib/blas/sasum/examples/index.js
@@ -0,0 +1,36 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2024 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 ndarray2array = require( '@stdlib/ndarray/to-array' );
+var array = require( '@stdlib/ndarray/array' );
+var sasum = require( './../lib' );
+
+var opts = {
+ 'dtype': 'float32'
+};
+
+var x = array( discreteUniform( 10, 0, 100, opts ), {
+ 'shape': [ 5, 2 ]
+});
+console.log( ndarray2array( x ) );
+
+var z = sasum( x, -1 );
+console.log( ndarray2array( z ) );
diff --git a/lib/node_modules/@stdlib/blas/sasum/lib/index.js b/lib/node_modules/@stdlib/blas/sasum/lib/index.js
new file mode 100644
index 000000000000..d95875fb6921
--- /dev/null
+++ b/lib/node_modules/@stdlib/blas/sasum/lib/index.js
@@ -0,0 +1,47 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2024 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';
+
+/**
+* BLAS level 1 routine to compute the sum of absolute values.
+*
+* @module @stdlib/blas/sasum
+*
+* @example
+* var Float32Array = require( '@stdlib/array/float32' );
+* var array = require( '@stdlib/ndarray/array' );
+* var sasum = require( '@stdlib/blas/sasum' );
+*
+* var x = array( new Float32Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] ) );
+*
+* var z = sasum( x );
+* // returns
+*
+* var v = z.get();
+* // returns 15.0
+*/
+
+// MODULES //
+
+var main = require( './main.js' );
+
+
+// EXPORTS //
+
+module.exports = main;
diff --git a/lib/node_modules/@stdlib/blas/sasum/lib/main.js b/lib/node_modules/@stdlib/blas/sasum/lib/main.js
new file mode 100644
index 000000000000..e7c3e976a5b8
--- /dev/null
+++ b/lib/node_modules/@stdlib/blas/sasum/lib/main.js
@@ -0,0 +1,133 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2020 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 isFloat32ndarrayLike = require( '@stdlib/assert/is-float32ndarray-like' );
+var isNegativeInteger = require( '@stdlib/assert/is-negative-integer' ).isPrimitive;
+var without = require( '@stdlib/array/base/without' );
+var numel = require( '@stdlib/ndarray/base/numel' );
+var normalizeIndex = require( '@stdlib/ndarray/base/normalize-index' );
+var ndarraylike2ndarray = require( '@stdlib/ndarray/base/ndarraylike2ndarray' );
+var nditerStacks = require( '@stdlib/ndarray/iter/stacks' );
+var empty = require( '@stdlib/ndarray/empty' );
+var base = require( '@stdlib/blas/base/sasum' ).ndarray;
+var format = require( '@stdlib/string/format' );
+
+
+// MAIN //
+
+/**
+* Computes the sum of absolute values.
+*
+* @param {ndarrayLike} x - first input array
+* @param {NegativeInteger} [dim=-1] - dimension for which to compute the sum
+* @throws {TypeError} first argument must be a ndarray containing single-precision floating-point numbers
+* @throws {TypeError} first argument must have at least one dimension
+* @throws {TypeError} second argument must be a negative integer
+* @throws {RangeError} second argument is out-of-bounds
+* @returns {ndarray} ndarray containing the sum values
+*
+* @example
+* var Float32Array = require( '@stdlib/array/float32' );
+* var array = require( '@stdlib/ndarray/array' );
+*
+* var x = array( new Float32Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] ) );
+*
+* var z = sasum( x );
+* // returns
+*
+* var v = z.get();
+* // returns 15.0
+*/
+function sasum( x ) {
+ var dim;
+ var xsh;
+ var osh;
+ var xit;
+ var out;
+ var dm;
+ var xc;
+ var vx;
+ var S;
+ var v;
+ var i;
+
+ if ( !isFloat32ndarrayLike( x ) ) {
+ throw new TypeError( format( 'invalid argument. First argument must be an ndarray containing single-precision floating-point numbers. Value: `%s`.', x ) );
+ }
+ // Convert the input array to "base" ndarrays:
+ xc = ndarraylike2ndarray( x );
+
+ // Resolve the input array shape:
+ xsh = xc.shape;
+
+ // Validate that we've been provided non-zero-dimensional array...
+ if ( xsh.length < 1 ) {
+ throw new TypeError( format( 'invalid argument. First argument must have at least one dimension.' ) );
+ }
+ // Validate that the dimension argument is a negative integer...
+ if ( arguments.length > 1 ) {
+ dim = arguments[ 1 ];
+ if ( !isNegativeInteger( dim ) ) {
+ throw new TypeError( format( 'invalid argument. Second argument must be a negative integer. Value: `%s`.', dim ) );
+ }
+ } else {
+ dim = -1;
+ }
+ // Validate that a provided dimension index is within bounds...
+ dm = xsh.length - 1;
+ dim = normalizeIndex( dim, dm );
+ if ( dim === -1 ) {
+ throw new RangeError( format( 'invalid argument. Second argument must be a value on the interval: [%d,%d]. Value: `%d`.', -dm, -1, arguments[ 2 ] ) );
+ }
+ S = xsh[ dim ];
+
+ // Resolve the output array shape by excluding the contracted dimension:
+ osh = without( xc.shape, dim );
+
+ // Allocate an empty output array:
+ out = empty( osh, {
+ 'dtype': xc.dtype,
+ 'order': xc.order
+ });
+
+ // If we are only provided one-dimensional input arrays, we can skip iterating over stacks...
+ if ( osh.length === 0 ) {
+ v = base( S, xc.data, xc.strides[0], xc.offset );
+ out.iset( v );
+ return out;
+ }
+ // Create iterators for iterating over stacks of vectors:
+ xit = nditerStacks( xc, [ dim ] );
+
+ // Compute the sum for each vector:
+ for ( i = 0; i < numel( osh ); i++ ) {
+ vx = xit.next().value;
+ v = base( S, vx.data, vx.strides[0], vx.offset );
+ out.iset( i, v );
+ }
+ return out;
+}
+
+
+// EXPORTS //
+
+module.exports = sasum;
diff --git a/lib/node_modules/@stdlib/blas/sasum/package.json b/lib/node_modules/@stdlib/blas/sasum/package.json
new file mode 100644
index 000000000000..34b0744e77f5
--- /dev/null
+++ b/lib/node_modules/@stdlib/blas/sasum/package.json
@@ -0,0 +1,73 @@
+{
+ "name": "@stdlib/blas/sasum",
+ "version": "0.0.0",
+ "description": "Compte the sum of absolute values.",
+ "license": "Apache-2.0",
+ "author": {
+ "name": "The Stdlib Authors",
+ "url": "https://github.com/stdlib-js/stdlib/graphs/contributors"
+ },
+ "contributors": [
+ {
+ "name": "The Stdlib Authors",
+ "url": "https://github.com/stdlib-js/stdlib/graphs/contributors"
+ }
+ ],
+ "main": "./lib",
+ "directories": {
+ "benchmark": "./benchmark",
+ "doc": "./docs",
+ "example": "./examples",
+ "lib": "./lib",
+ "test": "./test"
+ },
+ "types": "./docs/types",
+ "scripts": {},
+ "homepage": "https://github.com/stdlib-js/stdlib",
+ "repository": {
+ "type": "git",
+ "url": "git://github.com/stdlib-js/stdlib.git"
+ },
+ "bugs": {
+ "url": "https://github.com/stdlib-js/stdlib/issues"
+ },
+ "dependencies": {},
+ "devDependencies": {},
+ "engines": {
+ "node": ">=0.10.0",
+ "npm": ">2.7.0"
+ },
+ "os": [
+ "aix",
+ "darwin",
+ "freebsd",
+ "linux",
+ "macos",
+ "openbsd",
+ "sunos",
+ "win32",
+ "windows"
+ ],
+ "keywords": [
+ "stdlib",
+ "stdmath",
+ "mathematics",
+ "math",
+ "blas",
+ "level 1",
+ "sasum",
+ "sum",
+ "absolute",
+ "abs",
+ "linear",
+ "algebra",
+ "subroutines",
+ "vector",
+ "array",
+ "ndarray",
+ "float32",
+ "single",
+ "float",
+ "float32array"
+ ]
+}
diff --git a/lib/node_modules/@stdlib/blas/sasum/test/test.js b/lib/node_modules/@stdlib/blas/sasum/test/test.js
new file mode 100644
index 000000000000..c8e0df9bc6fc
--- /dev/null
+++ b/lib/node_modules/@stdlib/blas/sasum/test/test.js
@@ -0,0 +1,390 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2020 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 Float32Array = require( '@stdlib/array/float32' );
+var array = require( '@stdlib/ndarray/array' );
+var zeros = require( '@stdlib/ndarray/zeros' );
+var ndarray = require( '@stdlib/ndarray/ctor' );
+var ndims = require( '@stdlib/ndarray/ndims' );
+var shape = require( '@stdlib/ndarray/shape' );
+var sasum = require( './../lib' );
+
+
+// TESTS //
+
+tape( 'main export is a function', function test( t ) {
+ t.ok( true, __filename );
+ t.strictEqual( typeof sasum, 'function', 'main export is a function' );
+ t.end();
+});
+
+tape( 'the function has an arity of 1', function test( t ) {
+ t.strictEqual( sasum.length, 1, 'has expected arity' );
+ t.end();
+});
+
+tape( 'the function throws an error if provided a first argument which is not a non-zero-dimensional ndarray containing single-precision floating-point numbers', function test( t ) {
+ var values;
+ var i;
+
+ values = [
+ 5,
+ '5',
+ true,
+ false,
+ null,
+ void 0,
+ {},
+ [],
+ function noop() {},
+ zeros( [], {
+ 'dtype': 'float32'
+ }),
+ array( new Float64Array( 10 ) )
+ ];
+
+ for ( i = 0; i < values.length; i++ ) {
+ t.throws( badValue( values[ i ] ), TypeError, 'throws an error when provided ' + values[ i ] );
+ }
+ t.end();
+
+ function badValue( value ) {
+ return function badValue() {
+ sasum( value );
+ };
+ }
+});
+
+tape( 'the function throws an error if provided a first argument which is not a non-zero-dimensional ndarray containing single-precision floating-point numbers (dimension)', function test( t ) {
+ var values;
+ var i;
+
+ values = [
+ 5,
+ '5',
+ true,
+ false,
+ null,
+ void 0,
+ {},
+ [],
+ function noop() {},
+ zeros( [], {
+ 'dtype': 'float32'
+ }),
+ array( new Float64Array( 10 ) )
+ ];
+
+ for ( i = 0; i < values.length; i++ ) {
+ t.throws( badValue( values[ i ] ), TypeError, 'throws an error when provided ' + values[ i ] );
+ }
+ t.end();
+
+ function badValue( value ) {
+ return function badValue() {
+ sasum( value, -1 );
+ };
+ }
+});
+
+tape( 'the function throws an error if provided a second argument which is not a negative integer (vectors)', function test( t ) {
+ var values;
+ var i;
+
+ values = [
+ '5',
+ 0,
+ 5,
+ NaN,
+ -3.14,
+ true,
+ false,
+ null,
+ void 0,
+ {},
+ [],
+ function noop() {}
+ ];
+
+ for ( i = 0; i < values.length; i++ ) {
+ t.throws( badValue( values[ i ] ), TypeError, 'throws an error when provided ' + values[ i ] );
+ }
+ t.end();
+
+ function badValue( value ) {
+ var x = array( new Float32Array( 10 ) );
+
+ return function badValue() {
+ sasum( x, value );
+ };
+ }
+});
+
+tape( 'the function throws an error if provided a second argument which is not a negative integer (multi-dimensional arrays)', function test( t ) {
+ var values;
+ var i;
+
+ values = [
+ '5',
+ 0,
+ 5,
+ NaN,
+ -3.14,
+ true,
+ false,
+ null,
+ void 0,
+ {},
+ [],
+ function noop() {}
+ ];
+
+ for ( i = 0; i < values.length; i++ ) {
+ t.throws( badValue( values[ i ] ), TypeError, 'throws an error when provided ' + values[ i ] );
+ }
+ t.end();
+
+ function badValue( value ) {
+ var opts = {
+ 'shape': [ 2, 5 ]
+ };
+ var x = array( new Float32Array( 10 ), opts );
+
+ return function badValue() {
+ sasum( x, value );
+ };
+ }
+});
+
+tape( 'the function calculates the sum of absolute values', function test( t ) {
+ var sum;
+ var x;
+
+ x = new Float32Array( [ 4.0, 2.0, -3.0, 5.0, -1.0, 2.0, -5.0, 6.0 ] );
+
+ x = array( x );
+
+ sum = sasum( x );
+
+ t.strictEqual( sum instanceof ndarray, true, 'returns expected value' );
+ t.strictEqual( ndims( sum ), ndims( x )-1, 'returns expected value' );
+ t.deepEqual( shape( sum ), [], 'returns expected value' );
+ t.strictEqual( sum.get(), 28.0, 'returns expected value' );
+
+ t.end();
+});
+
+tape( 'the function supports operating on stacks of vectors (default)', function test( t ) {
+ var opts;
+ var sum;
+ var x;
+
+ x = new Float32Array( [ 4.0, 2.0, -3.0, 5.0, -1.0, 2.0, -5.0, 6.0 ] );
+
+ opts = {
+ 'shape': [ 4, 2 ]
+ };
+ x = array( x, opts );
+
+ sum = sasum( x );
+
+ t.strictEqual( sum instanceof ndarray, true, 'returns expected value' );
+ t.strictEqual( ndims( sum ), ndims( x )-1, 'returns expected value' );
+ t.deepEqual( shape( sum ), [ 4 ], 'returns expected value' );
+ t.strictEqual( sum.get( 0 ), 6.0, 'returns expected value' );
+ t.strictEqual( sum.get( 1 ), 8.0, 'returns expected value' );
+ t.strictEqual( sum.get( 2 ), 3.0, 'returns expected value' );
+ t.strictEqual( sum.get( 3 ), 11.0, 'returns expected value' );
+
+ t.end();
+});
+
+tape( 'the function supports operating on stacks of vectors (dim=-1)', function test( t ) {
+ var opts;
+ var sum;
+ var x;
+
+ x = new Float32Array( [ 4.0, 2.0, -3.0, 5.0, -1.0, 2.0, -5.0, 6.0 ] );
+
+ opts = {
+ 'shape': [ 4, 2 ]
+ };
+ x = array( x, opts );
+
+ sum = sasum( x, -1 );
+
+ t.strictEqual( sum instanceof ndarray, true, 'returns expected value' );
+ t.strictEqual( ndims( sum ), ndims( x )-1, 'returns expected value' );
+ t.deepEqual( shape( sum ), [ 4 ], 'returns expected value' );
+ t.strictEqual( sum.get( 0 ), 6.0, 'returns expected value' );
+ t.strictEqual( sum.get( 1 ), 8.0, 'returns expected value' );
+ t.strictEqual( sum.get( 2 ), 3.0, 'returns expected value' );
+ t.strictEqual( sum.get( 3 ), 11.0, 'returns expected value' );
+
+ t.end();
+});
+
+tape( 'the function supports operating on stacks of vectors (dim=-2)', function test( t ) {
+ var opts;
+ var sum;
+ var x;
+
+ x = new Float32Array( [ 4.0, 2.0, -3.0, 5.0, -1.0, 2.0, -5.0, 6.0 ] );
+
+ opts = {
+ 'shape': [ 2, 4 ]
+ };
+ x = array( x, opts );
+
+ sum = sasum( x, -2 );
+
+ t.strictEqual( sum instanceof ndarray, true, 'returns expected value' );
+ t.strictEqual( ndims( sum ), ndims( x )-1, 'returns expected value' );
+ t.deepEqual( shape( sum ), [ 4 ], 'returns expected value' );
+ t.strictEqual( sum.get( 0 ), 5.0, 'returns expected value' );
+ t.strictEqual( sum.get( 1 ), 4.0, 'returns expected value' );
+ t.strictEqual( sum.get( 2 ), 8.0, 'returns expected value' );
+ t.strictEqual( sum.get( 3 ), 11.0, 'returns expected value' );
+
+ t.end();
+});
+
+tape( 'if provided an empty vector, the sum is `0`', function test( t ) {
+ var sum;
+ var x;
+
+ x = new Float32Array();
+
+ x = array( x );
+
+ sum = sasum( x );
+
+ t.strictEqual( sum instanceof ndarray, true, 'returns expected value' );
+ t.strictEqual( ndims( sum ), ndims( x )-1, 'returns expected value' );
+ t.deepEqual( shape( sum ), [], 'returns expected value' );
+ t.strictEqual( sum.get(), 0.0, 'returns expected value' );
+
+ t.end();
+});
+
+tape( 'the function supports a strided vector for `x`', function test( t ) {
+ var sum;
+ var x;
+
+ x = new Float32Array([
+ 2.0, // 0
+ -3.0,
+ -5.0, // 1
+ 7.0,
+ 6.0 // 2
+ ]);
+
+ x = ndarray( 'float32', x, [ 3 ], [ 2 ], 0, 'row-major' );
+
+ sum = sasum( x );
+
+ t.strictEqual( sum instanceof ndarray, true, 'returns expected value' );
+ t.strictEqual( ndims( sum ), ndims( x )-1, 'returns expected value' );
+ t.deepEqual( shape( sum ), [], 'returns expected value' );
+ t.strictEqual( sum.get(), 13.0, 'returns expected value' );
+
+ t.end();
+});
+
+tape( 'the function supports a negative stride', function test( t ) {
+ var sum;
+ var x;
+
+ x = new Float32Array([
+ 1.0, // 2
+ 2.0,
+ 3.0, // 1
+ 4.0,
+ 5.0 // 0
+ ]);
+
+ x = ndarray( 'float32', x, [ 3 ], [ -2 ], x.length-1, 'row-major' );
+
+ sum = sasum( x );
+
+ t.strictEqual( sum instanceof ndarray, true, 'returns expected value' );
+ t.strictEqual( ndims( sum ), ndims( x )-1, 'returns expected value' );
+ t.deepEqual( shape( sum ), [], 'returns expected value' );
+ t.strictEqual( sum.get(), 9.0, 'returns expected value' );
+
+ t.end();
+});
+
+tape( 'the function supports an `x` offset', function test( t ) {
+ var sum;
+ var x;
+
+ x = new Float32Array([
+ 0.0,
+ 2.0, // 0
+ -3.0,
+ -5.0, // 1
+ 7.0,
+ 6.0 // 2
+ ]);
+
+ x = ndarray( 'float32', x, [ 3 ], [ 2 ], 1, 'row-major' );
+
+ sum = sasum( x );
+
+ t.strictEqual( sum instanceof ndarray, true, 'returns expected value' );
+ t.strictEqual( ndims( sum ), ndims( x )-1, 'returns expected value' );
+ t.deepEqual( shape( sum ), [], 'returns expected value' );
+ t.strictEqual( sum.get(), 13.0, 'returns expected value' );
+
+ t.end();
+});
+
+tape( 'the function supports underlying data buffers with view offsets', function test( t ) {
+ var sum;
+ var x0;
+ var x1;
+
+ x0 = new Float32Array([
+ 1.0,
+ 2.0, // 0
+ 3.0,
+ 4.0, // 1
+ 5.0,
+ 6.0 // 2
+ ]);
+
+ x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );
+
+ x1 = ndarray( 'float32', x1, [ 3 ], [ 2 ], 0, 'row-major' );
+
+ sum = sasum( x1 );
+
+ t.strictEqual( sum instanceof ndarray, true, 'returns expected value' );
+ t.strictEqual( ndims( sum ), ndims( x1 )-1, 'returns expected value' );
+ t.deepEqual( shape( sum ), [], 'returns expected value' );
+ t.strictEqual( sum.get(), 12.0, 'returns expected value' );
+
+ t.end();
+});