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feat: add C ndarray API and refactor blas/ext/base/dapxsumkbn2
PR-URL: #2948 Reviewed-by: Athan Reines <[email protected]>
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lib/node_modules/@stdlib/blas/ext/base/dapxsumkbn2/README.md

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@@ -20,7 +20,7 @@ limitations under the License.
2020

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# dapxsumkbn2
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> Add a constant to each double-precision floating-point strided array element and compute the sum using a second-order iterative Kahan–Babuška algorithm.
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> Add a scalar constant to each double-precision floating-point strided array element and compute the sum using a second-order iterative Kahan–Babuška algorithm.
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<section class="intro">
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@@ -36,9 +36,9 @@ limitations under the License.
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var dapxsumkbn2 = require( '@stdlib/blas/ext/base/dapxsumkbn2' );
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```
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#### dapxsumkbn2( N, alpha, x, stride )
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#### dapxsumkbn2( N, alpha, x, strideX )
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Adds a constant to each double-precision floating-point strided array element and computes the sum using a second-order iterative Kahan–Babuška algorithm.
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Adds a scalar constant to each double-precision floating-point strided array element and computes the sum using a second-order iterative Kahan–Babuška algorithm.
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```javascript
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var Float64Array = require( '@stdlib/array/float64' );
@@ -53,7 +53,7 @@ The function has the following parameters:
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- **N**: number of indexed elements.
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- **x**: input [`Float64Array`][@stdlib/array/float64].
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- **stride**: index increment for `x`.
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- **strideX**: index increment for `x`.
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The `N` and stride parameters determine which elements in the strided array are accessed at runtime. For example, to access every other element in `x`,
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@@ -80,9 +80,9 @@ var v = dapxsumkbn2( 4, 5.0, x1, 2 );
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// returns 25.0
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```
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#### dapxsumkbn2.ndarray( N, alpha, x, stride, offset )
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#### dapxsumkbn2.ndarray( N, alpha, x, strideX, offsetX )
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Adds a constant to each double-precision floating-point strided array element and computes the sum using a second-order iterative Kahan–Babuška algorithm and alternative indexing semantics.
85+
Adds a scalar constant to each double-precision floating-point strided array element and computes the sum using a second-order iterative Kahan–Babuška algorithm and alternative indexing semantics.
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```javascript
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var Float64Array = require( '@stdlib/array/float64' );
@@ -95,9 +95,9 @@ var v = dapxsumkbn2.ndarray( 3, 5.0, x, 1, 0 );
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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 for `x`.
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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 access 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 access every other value in `x` starting from the second value
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```javascript
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var Float64Array = require( '@stdlib/array/float64' );
@@ -129,11 +129,12 @@ var v = dapxsumkbn2.ndarray( 4, 5.0, x, 2, 1 );
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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;
133-
var filledarrayBy = require( '@stdlib/array/filled-by' );
132+
var discreteUniform = require( '@stdlib/random/array/discrete-uniform' );
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var dapxsumkbn2 = require( '@stdlib/blas/ext/base/dapxsumkbn2' );
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var x = filledarrayBy( 10, 'float64', discreteUniform( 0, 100 ) );
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var x = discreteUniform( 10, -100, 100, {
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'dtype': 'float64'
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});
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console.log( x );
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var v = dapxsumkbn2( x.length, 5.0, x, 1 );
@@ -144,8 +145,125 @@ console.log( v );
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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/dapxsumkbn2.h"
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```
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#### stdlib_strided_dapxsumkbn2( N, alpha, \*X, strideX )
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Adds a scalar constant to each double-precision floating-point strided array element and computes the sum using a second-order iterative Kahan–Babuška algorithm.
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```c
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const double x[] = { 1.0, 2.0, 3.0, 4.0 };
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double v = stdlib_strided_dapxsumkbn2( 4, 5.0, x, 1 );
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// returns 30.0
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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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- **alpha**: `[in] double` scalar constant.
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- **X**: `[in] double*` input array.
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- **strideX**: `[in] CBLAS_INT` index increment for `X`.
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```c
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double stdlib_strided_dapxsumkbn2( const CBLAS_INT N, const double alpha, const double *X, const CBLAS_INT strideX );
194+
```
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196+
#### stdlib_strided_dapxsumkbn2_ndarray( N, alpha, \*X, strideX, offsetX )
197+
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Adds a scalar constant to each double-precision floating-point strided array element and computes the sum using a second-order iterative Kahan–Babuška algorithm and alternative indexing semantics.
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```c
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const double x[] = { 1.0, 2.0, 3.0, 4.0 };
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double v = stdlib_strided_dapxsumkbn2_ndarray( 4, 5.0, x, 1, 0 );
204+
// returns 30.0
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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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- **alpha**: `[in] double` scalar constant.
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- **X**: `[in] double*` input array.
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- **strideX**: `[in] CBLAS_INT` index increment for `X`.
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- **offsetX**: `[in] CBLAS_INT` starting index for `X`.
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```c
216+
double stdlib_strided_dapxsumkbn2_ndarray( const CBLAS_INT N, const double alpha, const double *X, const CBLAS_INT strideX, const CBLAS_INT offsetX );
217+
```
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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/dapxsumkbn2.h"
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#include <stdio.h>
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int main( void ) {
242+
// Create a strided array:
243+
const double x[] = { 1.0, -2.0, 3.0, -4.0, 5.0, -6.0, 7.0, -8.0 };
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245+
// Specify the number of indexed elements:
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const int N = 8;
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248+
// Specify a stride:
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const int strideX = 1;
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251+
// Compute the sum:
252+
double v = stdlib_strided_dapxsumkbn2( N, 5.0, x, strideX );
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// Print the result:
255+
printf( "Sum: %lf\n", sum );
256+
}
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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/dapxsumkbn2/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' );
24+
var uniform = require( '@stdlib/random/array/uniform' );
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var isnan = require( '@stdlib/math/base/assert/is-nan' );
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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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34-
var rand = uniform( -10.0, 10.0 );
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var options = {
34+
'dtype': 'float64'
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};
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// FUNCTIONS //
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* @returns {Function} benchmark function
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*/
4647
function createBenchmark( len ) {
47-
var x = filledarrayBy( len, 'float64', 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/dapxsumkbn2/benchmark/benchmark.native.js

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var resolve = require( 'path' ).resolve;
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var bench = require( '@stdlib/bench' );
25-
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 isnan = require( '@stdlib/math/base/assert/is-nan' );
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var pow = require( '@stdlib/math/base/special/pow' );
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var tryRequire = require( '@stdlib/utils/try-require' );
@@ -36,7 +35,9 @@ var dapxsumkbn2 = tryRequire( resolve( __dirname, './../lib/dapxsumkbn2.native.j
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var opts = {
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'skip': ( dapxsumkbn2 instanceof Error )
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};
39-
var rand = uniform( -10.0, 10.0 );
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var options = {
39+
'dtype': 'float64'
40+
};
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// FUNCTIONS //
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* @returns {Function} benchmark function
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*/
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function createBenchmark( len ) {
52-
var x = filledarrayBy( len, 'float64', 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/dapxsumkbn2/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' );
24+
var uniform = require( '@stdlib/random/array/uniform' );
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var isnan = require( '@stdlib/math/base/assert/is-nan' );
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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( -10.0, 10.0 );
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var options = {
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'dtype': 'float64'
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};
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// FUNCTIONS //
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4445
* @returns {Function} benchmark function
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*/
4647
function createBenchmark( len ) {
47-
var x = filledarrayBy( len, 'float64', rand );
48+
var x = uniform( len, -100, 100, options );
4849
return benchmark;
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5051
function benchmark( b ) {

lib/node_modules/@stdlib/blas/ext/base/dapxsumkbn2/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 isnan = require( '@stdlib/math/base/assert/is-nan' );
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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': ( dapxsumkbn2 instanceof Error )
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};
39-
var rand = uniform( -10.0, 10.0 );
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var options = {
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'dtype': 'float64'
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};
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// FUNCTIONS //
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* @returns {Function} benchmark function
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*/
5152
function createBenchmark( len ) {
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var x = filledarrayBy( len, 'float64', 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/dapxsumkbn2/benchmark/c/benchmark.length.c

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9494
* @param len array length
9595
* @return elapsed time in seconds
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*/
97-
static double benchmark( int iterations, int len ) {
97+
static double benchmark1( int iterations, int len ) {
9898
double elapsed;
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double x[ len ];
100100
double v;
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120120
return elapsed;
121121
}
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/**
124+
* Runs a benchmark.
125+
*
126+
* @param iterations number of iterations
127+
* @param len array length
128+
* @return elapsed time in seconds
129+
*/
130+
static double benchmark2( int iterations, int len ) {
131+
double elapsed;
132+
double x[ len ];
133+
double v;
134+
double t;
135+
int i;
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137+
for ( i = 0; i < len; i++ ) {
138+
x[ i ] = ( rand_double() * 20000.0 ) - 10000.0;
139+
}
140+
v = 0.0;
141+
t = tic();
142+
for ( i = 0; i < iterations; i++ ) {
143+
v = stdlib_strided_dapxsumkbn2_ndarray( len, 5.0, x, 1, 0 );
144+
if ( v != v ) {
145+
printf( "should not return NaN\n" );
146+
break;
147+
}
148+
}
149+
elapsed = tic() - t;
150+
if ( v != v ) {
151+
printf( "should not return NaN\n" );
152+
}
153+
return elapsed;
154+
}
155+
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/**
124157
* Main execution sequence.
125158
*/
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142175
for ( j = 0; j < REPEATS; j++ ) {
143176
count += 1;
144177
printf( "# c::%s:len=%d\n", NAME, len );
145-
elapsed = benchmark( iter, len );
178+
elapsed = benchmark1( iter, len );
179+
print_results( iter, elapsed );
180+
printf( "ok %d benchmark finished\n", count );
181+
}
182+
}
183+
for ( i = MIN; i <= MAX; i++ ) {
184+
len = pow( 10, i );
185+
iter = ITERATIONS / pow( 10, i-1 );
186+
for ( j = 0; j < REPEATS; j++ ) {
187+
count += 1;
188+
printf( "# c::%s:ndarray:len=%d\n", NAME, len );
189+
elapsed = benchmark2( iter, len );
146190
print_results( iter, elapsed );
147191
printf( "ok %d benchmark finished\n", count );
148192
}

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