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feat: add C ndarray API and refactor
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‎lib/node_modules/@stdlib/blas/ext/base/sasumpw/README.md‎

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@@ -51,27 +51,26 @@ The [_L1_ norm][l1norm] is defined as
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var sasumpw = require( '@stdlib/blas/ext/base/sasumpw' );
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```
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#### sasumpw( N, x, stride )
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#### sasumpw( N, x, strideX )
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Computes the sum of absolute values ([_L1_ norm][l1norm]) of single-precision floating-point strided array elements using pairwise summation.
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```javascript
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var Float32Array = require( '@stdlib/array/float32' );
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var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );
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var N = x.length;
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var v = sasumpw( N, x, 1 );
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var v = sasumpw( x.length, x, 1 );
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// returns 5.0
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```
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The function has the following parameters:
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- **N**: number of indexed elements.
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- **x**: input [`Float32Array`][@stdlib/array/float32].
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- **stride**: index increment for `x`.
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- **stride**: stride length.
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The `N` and stride parameters determine which elements in the strided array are accessed at runtime. For example, to compute the sum of absolute values of every other element in `x`,
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The `N` and stride parameters determine which elements in the strided array are accessed at runtime. For example, to compute the sum of absolute values of every other element:
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```javascript
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var Float32Array = require( '@stdlib/array/float32' );
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// returns 9.0
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```
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#### sasumpw.ndarray( N, x, stride, offset )
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#### sasumpw.ndarray( N, x, strideX, offsetX )
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Computes the sum of absolute values ([_L1_ norm][l1norm]) of single-precision floating-point strided array elements using pairwise summation and alternative indexing semantics.
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```javascript
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var Float32Array = require( '@stdlib/array/float32' );
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var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );
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var N = x.length;
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var v = sasumpw.ndarray( N, x, 1, 0 );
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var v = sasumpw.ndarray( x.length, x, 1, 0 );
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// returns 5.0
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```
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The function has the following additional parameters:
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- **offset**: starting index for `x`.
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- **offsetX**: starting index.
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While [`typed array`][mdn-typed-array] views mandate a view offset based on the underlying `buffer`, the `offset` parameter supports indexing semantics based on a starting index. For example, to calculate the sum of absolute values of every other value in `x` starting from the second value
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While [`typed array`][mdn-typed-array] views mandate a view offset based on the underlying buffer, the offset parameter supports indexing semantics based on a starting index. For example, to calculate the sum of absolute values of every other element starting from the second element:
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```javascript
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var Float32Array = require( '@stdlib/array/float32' );
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<!-- eslint no-undef: "error" -->
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```javascript
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var discreteUniform = require( '@stdlib/random/base/discrete-uniform' ).factory;
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var filledarrayBy = require( '@stdlib/array/filled-by' );
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var discreteUniform = require( '@stdlib/random/array/discrete-uniform' );
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var sasumpw = require( '@stdlib/blas/ext/base/sasumpw' );
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var x = filledarrayBy( 10, 'float32', discreteUniform( 0, 100 ) );
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var x = discreteUniform( 10, -100, 100, {
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'dtype': 'float32'
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});
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console.log( x );
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var v = sasumpw( x.length, x, 1 );
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<!-- /.examples -->
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<!-- C interface documentation. -->
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* * *
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<section class="c">
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## C APIs
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<!-- Section to include introductory text. Make sure to keep an empty line after the intro `section` element and another before the `/section` close. -->
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<section class="intro">
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</section>
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<!-- /.intro -->
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<!-- C usage documentation. -->
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<section class="usage">
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### Usage
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```c
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#include "stdlib/blas/ext/base/sasumpw.h"
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```
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#### stdlib_strided_sasumpw( N, \*X, strideX )
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Computes the sum of absolute values ([_L1_ norm][l1norm]) of single-precision floating-point strided array elements using pairwise summation.
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```c
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const float x[] = { 1.0f, 2.0f, 3.0f, 4.0f }
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float v = stdlib_strided_sasumpw( 4, x, 1 );
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// returns 10.0
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```
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The function accepts the following arguments:
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- **N**: `[in] CBLAS_INT` number of indexed elements.
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- **X**: `[in] float*` input array.
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- **strideX**: `[in] CBLAS_INT` stride length.
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```c
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float stdlib_strided_sasumpw( const CBLAS_INT N, const float *X, const CBLAS_INT strideX );
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```
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#### stdlib_strided_sasumpw_ndarray( N, \*X, strideX, offsetX )
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Computes the sum of absolute values ([_L1_ norm][l1norm]) of single-precision floating-point strided array elements using pairwise summation and alternative indexing semantics.
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```c
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const float x[] = { 1.0f, 2.0f, 3.0f, 4.0f }
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float v = stdlib_strided_sasumpw_ndarray( 4, x, 1, 0 );
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// returns 10.0
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```
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The function accepts the following arguments:
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- **N**: `[in] CBLAS_INT` number of indexed elements.
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- **X**: `[in] float*` input array.
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- **strideX**: `[in] CBLAS_INT` stride length.
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- **offsetX**: `[in] CBLAS_INT` starting index.
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```c
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float stdlib_strided_sasumpw_ndarray( const CBLAS_INT N, const float *X, const CBLAS_INT strideX, const CBLAS_INT offsetX );
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```
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</section>
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<!-- /.usage -->
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<!-- C API usage notes. Make sure to keep an empty line after the `section` element and another before the `/section` close. -->
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<section class="notes">
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</section>
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<!-- /.notes -->
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<!-- C API usage examples. -->
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<section class="examples">
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### Examples
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```c
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#include "stdlib/blas/ext/base/sasumpw.h"
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#include <stdio.h>
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int main( void ) {
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// Create a strided array:
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const float x[] = { 1.0f, -2.0f, 3.0f, -4.0f, 5.0f, -6.0f, 7.0f, -8.0f };
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// Specify the number of indexed elements:
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const int N = 8;
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// Specify a stride:
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const int strideX = 1;
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// Compute the sum:
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float v = stdlib_strided_sasumpw( N, x, strideX );
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// Print the result:
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printf( "sumabs: %f\n", v );
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}
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```
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</section>
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<!-- /.examples -->
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</section>
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<!-- /.c -->
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<section class="references">
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## References

‎lib/node_modules/@stdlib/blas/ext/base/sasumpw/benchmark/benchmark.js‎

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// MODULES //
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var bench = require( '@stdlib/bench' );
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var uniform = require( '@stdlib/random/base/uniform' ).factory;
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var filledarrayBy = require( '@stdlib/array/filled-by' );
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var uniform = require( '@stdlib/random/array/uniform' );
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var isnanf = require( '@stdlib/math/base/assert/is-nanf' );
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var pow = require( '@stdlib/math/base/special/pow' );
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var pkg = require( './../package.json' ).name;
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// VARIABLES //
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var rand = uniform( -100.0, 100.0 );
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var options = {
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'dtype': 'float32'
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};
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// FUNCTIONS //
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* @returns {Function} benchmark function
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*/
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function createBenchmark( len ) {
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var x = filledarrayBy( len, 'float32', rand );
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var x = uniform( len, -100, 100, options );
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return benchmark;
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function benchmark( b ) {

‎lib/node_modules/@stdlib/blas/ext/base/sasumpw/benchmark/benchmark.native.js‎

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var resolve = require( 'path' ).resolve;
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var bench = require( '@stdlib/bench' );
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var uniform = require( '@stdlib/random/base/uniform' ).factory;
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var filledarrayBy = require( '@stdlib/array/filled-by' );
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var uniform = require( '@stdlib/random/array/uniform' );
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var isnanf = require( '@stdlib/math/base/assert/is-nanf' );
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var pow = require( '@stdlib/math/base/special/pow' );
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var tryRequire = require( '@stdlib/utils/try-require' );
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var pkg = require( './../package.json' ).name;
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var opts = {
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'skip': ( sasumpw instanceof Error )
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};
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var rand = uniform( -100.0, 100.0 );
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var options = {
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'dtype': 'float32'
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};
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// FUNCTIONS //
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* @returns {Function} benchmark function
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*/
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function createBenchmark( len ) {
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var x = filledarrayBy( len, 'float32', rand );
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var x = uniform( len, -100, 100, options );
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return benchmark;
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function benchmark( b ) {

‎lib/node_modules/@stdlib/blas/ext/base/sasumpw/benchmark/benchmark.ndarray.js‎

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// MODULES //
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var bench = require( '@stdlib/bench' );
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var uniform = require( '@stdlib/random/base/uniform' ).factory;
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var filledarrayBy = require( '@stdlib/array/filled-by' );
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var uniform = require( '@stdlib/random/array/uniform' );
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var isnanf = require( '@stdlib/math/base/assert/is-nanf' );
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var pow = require( '@stdlib/math/base/special/pow' );
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var pkg = require( './../package.json' ).name;
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// VARIABLES //
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var rand = uniform( -100.0, 100.0 );
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var options = {
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'dtype': 'float32'
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};
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// FUNCTIONS //
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* @returns {Function} benchmark function
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*/
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function createBenchmark( len ) {
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var x = filledarrayBy( len, 'float32', rand );
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var x = uniform( len, -100, 100, options );
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return benchmark;
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function benchmark( b ) {

‎lib/node_modules/@stdlib/blas/ext/base/sasumpw/benchmark/benchmark.ndarray.native.js‎

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var resolve = require( 'path' ).resolve;
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var bench = require( '@stdlib/bench' );
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var uniform = require( '@stdlib/random/base/uniform' ).factory;
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var filledarrayBy = require( '@stdlib/array/filled-by' );
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var uniform = require( '@stdlib/random/array/uniform' );
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var isnanf = require( '@stdlib/math/base/assert/is-nanf' );
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var pow = require( '@stdlib/math/base/special/pow' );
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var tryRequire = require( '@stdlib/utils/try-require' );
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var opts = {
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'skip': ( sasumpw instanceof Error )
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};
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var rand = uniform( -100.0, 100.0 );
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var options = {
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'dtype': 'float32'
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};
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// FUNCTIONS //
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* @returns {Function} benchmark function
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*/
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function createBenchmark( len ) {
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var x = filledarrayBy( len, 'float32', rand );
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var x = uniform( len, -100, 100, options );
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return benchmark;
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function benchmark( b ) {

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