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feat: add C ndarray interface and refactor implementation for `stat…
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…s/base/dsmeanpw`

PR-URL: #4338
Reviewed-by: Athan Reines <[email protected]>
Co-authored-by: stdlib-bot <[email protected]>
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Neerajpathak07 and stdlib-bot authored Jan 19, 2025
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144 changes: 115 additions & 29 deletions lib/node_modules/@stdlib/stats/base/dsmeanpw/README.md
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Expand Up @@ -51,36 +51,33 @@ The [arithmetic mean][arithmetic-mean] is defined as
var dsmeanpw = require( '@stdlib/stats/base/dsmeanpw' );
```

#### dsmeanpw( N, x, stride )
#### dsmeanpw( N, x, strideX )

Computes the [arithmetic mean][arithmetic-mean] of a single-precision floating-point strided array `x` using pairwise summation with extended accumulation and returning an extended precision result.

```javascript
var Float32Array = require( '@stdlib/array/float32' );

var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );
var N = x.length;

var v = dsmeanpw( N, x, 1 );
var v = dsmeanpw( x.length, x, 1 );
// returns ~0.3333
```

The function has the following parameters:

- **N**: number of indexed elements.
- **x**: input [`Float32Array`][@stdlib/array/float32].
- **stride**: index increment for `x`.
- **strideX**: stride length for `x`.

The `N` and `stride` parameters determine which elements in `x` are accessed at runtime. For example, to compute the [arithmetic mean][arithmetic-mean] of every other element in `x`,

```javascript
var Float32Array = require( '@stdlib/array/float32' );
var floor = require( '@stdlib/math/base/special/floor' );

var x = new Float32Array( [ 1.0, 2.0, 2.0, -7.0, -2.0, 3.0, 4.0, 2.0 ] );
var N = floor( x.length / 2 );

var v = dsmeanpw( N, x, 2 );
var v = dsmeanpw( 4, x, 2 );
// returns 1.25
```

Expand All @@ -90,45 +87,39 @@ Note that indexing is relative to the first index. To introduce an offset, use [

```javascript
var Float32Array = require( '@stdlib/array/float32' );
var floor = require( '@stdlib/math/base/special/floor' );

var x0 = new Float32Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] );
var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element

var N = floor( x0.length / 2 );

var v = dsmeanpw( N, x1, 2 );
var v = dsmeanpw( 4, x1, 2 );
// returns 1.25
```

#### dsmeanpw.ndarray( N, x, stride, offset )
#### dsmeanpw.ndarray( N, x, strideX, offsetX )

Computes the [arithmetic mean][arithmetic-mean] of a single-precision floating-point strided array using pairwise summation with extended accumulation and alternative indexing semantics and returning an extended precision result.

```javascript
var Float32Array = require( '@stdlib/array/float32' );

var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );
var N = x.length;

var v = dsmeanpw.ndarray( N, x, 1, 0 );
var v = dsmeanpw.ndarray( x.length, x, 1, 0 );
// returns ~0.33333
```

The function has the following additional parameters:

- **offset**: starting index for `x`.
- **offsetX**: starting index for `x`.

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 [arithmetic mean][arithmetic-mean] for every other value in `x` starting from the second value
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 [arithmetic mean][arithmetic-mean] for every other element in `x` starting from the second element

```javascript
var Float32Array = require( '@stdlib/array/float32' );
var floor = require( '@stdlib/math/base/special/floor' );

var x = new Float32Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] );
var N = floor( x.length / 2 );

var v = dsmeanpw.ndarray( N, x, 2, 1 );
var v = dsmeanpw.ndarray( 4, x, 2, 1 );
// returns 1.25
```

Expand All @@ -155,18 +146,12 @@ var v = dsmeanpw.ndarray( N, x, 2, 1 );
<!-- eslint no-undef: "error" -->

```javascript
var randu = require( '@stdlib/random/base/randu' );
var round = require( '@stdlib/math/base/special/round' );
var Float32Array = require( '@stdlib/array/float32' );
var discreteUniform = require( '@stdlib/random/array/discrete-uniform' );
var dsmeanpw = require( '@stdlib/stats/base/dsmeanpw' );

var x;
var i;

x = new Float32Array( 10 );
for ( i = 0; i < x.length; i++ ) {
x[ i ] = round( (randu()*100.0) - 50.0 );
}
var x = discreteUniform( 10, -50, 50, {
'dtype': 'float32'
});
console.log( x );

var v = dsmeanpw( x.length, x, 1 );
Expand All @@ -177,6 +162,107 @@ console.log( v );

<!-- /.examples -->

<!-- C usage documentation. -->

<section class="usage">

### Usage

```c
#include "stdlib/stats/base/dsmeanpw.h"
```

#### stdlib_strided_dsmeanpw( N, \*X, strideX )

Computes the arithmetic mean of a single-precision floating-point strided array using pairwise summation with extended accumulation and returning an extended precision result.

```c
const float x[] = { 1.0f, 2.0f, 3.0f, 4.0f, 5.0f, 6.0f, 7.0f, 8.0f };

double v = stdlib_strided_dsmeanpw( 4, x, 2 );
// returns 4.0
```
The function accepts the following arguments:
- **N**: `[in] CBLAS_INT` number of indexed elements.
- **X**: `[in] float*` input array.
- **strideX**: `[in] CBLAS_INT` stride length for `X`.
```c
double stdlib_strided_dsmeanpw( const CBLAS_INT N, const float *X, const CBLAS_INT strideX );
```

#### stdlib_strided_dsmeanpw_ndarray( N, \*X, strideX, offsetX )

Computes the arithmetic mean of a single-precision floating-point strided array using pairwise summation with extended accumulation and alternative indexing semantics and returning an extended precision result.

```c
const float x[] = { 1.0f, 2.0f, 3.0f, 4.0f, 5.0f, 6.0f, 7.0f, 8.0f };

double v = stdlib_strided_dsmeanpw_ndarray( 4, x, 2, 0 );
// returns 4.0
```
The function accepts the following arguments:
- **N**: `[in] CBLAS_INT` number of indexed elements.
- **X**: `[in] float*` input array.
- **strideX**: `[in] CBLAS_INT` stride length for `X`.
- **offsetX**: `[in] CBLAS_INT` starting index for `X`.
```c
double stdlib_strided_dsmeanpw_ndarray( const CBLAS_INT N, const float *X, const CBLAS_INT strideX, const CBLAS_INT offsetX );
```

</section>

<!-- /.usage -->

<!-- C API usage notes. Make sure to keep an empty line after the `section` element and another before the `/section` close. -->

<section class="notes">

</section>

<!-- /.notes -->

<!-- C API usage examples. -->

<section class="examples">

### Examples

```c
#include "stdlib/stats/base/dsmeanpw.h"
#include <stdio.h>

int main( void ) {
// Create a strided array:
const float x[] = { 1.0f, 2.0f, 3.0f, 4.0f, 5.0f, 6.0f, 7.0f, 8.0f };

// Specify the number of elements:
const int N = 4;

// Specify the stride length:
const int strideX = 2;

// Compute the arithmetic mean:
double v = stdlib_strided_dsmeanpw( N, x, strideX );

// Print the result:
printf( "mean: %lf\n", v );
}
```
</section>
<!-- /.examples -->
</section>
<!-- /.c -->
* * *
<section class="references">
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18 changes: 9 additions & 9 deletions lib/node_modules/@stdlib/stats/base/dsmeanpw/benchmark/benchmark.js
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Expand Up @@ -21,14 +21,20 @@
// MODULES //

var bench = require( '@stdlib/bench' );
var randu = require( '@stdlib/random/base/randu' );
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 Float32Array = require( '@stdlib/array/float32' );
var pkg = require( './../package.json' ).name;
var dsmeanpw = require( './../lib/dsmeanpw.js' );


// VARIABLES //

var options = {
'dtype': 'float32'
};


// FUNCTIONS //

/**
Expand All @@ -39,13 +45,7 @@ var dsmeanpw = require( './../lib/dsmeanpw.js' );
* @returns {Function} benchmark function
*/
function createBenchmark( len ) {
var x;
var i;

x = new Float32Array( len );
for ( i = 0; i < x.length; i++ ) {
x[ i ] = ( randu()*20.0 ) - 10.0;
}
var x = uniform( len, -10.0, 10.0, options );
return benchmark;

function benchmark( b ) {
Expand Down
14 changes: 5 additions & 9 deletions lib/node_modules/@stdlib/stats/base/dsmeanpw/benchmark/benchmark.native.js
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Expand Up @@ -22,10 +22,9 @@

var resolve = require( 'path' ).resolve;
var bench = require( '@stdlib/bench' );
var randu = require( '@stdlib/random/base/randu' );
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 Float32Array = require( '@stdlib/array/float32' );
var tryRequire = require( '@stdlib/utils/try-require' );
var pkg = require( './../package.json' ).name;

Expand All @@ -36,6 +35,9 @@ var dsmeanpw = tryRequire( resolve( __dirname, './../lib/dsmeanpw.native.js' ) )
var opts = {
'skip': ( dsmeanpw instanceof Error )
};
var options = {
'dtype': 'float32'
};


// FUNCTIONS //
Expand All @@ -48,13 +50,7 @@ var opts = {
* @returns {Function} benchmark function
*/
function createBenchmark( len ) {
var x;
var i;

x = new Float32Array( len );
for ( i = 0; i < x.length; i++ ) {
x[ i ] = ( randu()*20.0 ) - 10.0;
}
var x = uniform( len, -10.0, 10.0, options );
return benchmark;

function benchmark( b ) {
Expand Down
18 changes: 9 additions & 9 deletions lib/node_modules/@stdlib/stats/base/dsmeanpw/benchmark/benchmark.ndarray.js
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Expand Up @@ -21,14 +21,20 @@
// MODULES //

var bench = require( '@stdlib/bench' );
var randu = require( '@stdlib/random/base/randu' );
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 Float32Array = require( '@stdlib/array/float32' );
var pkg = require( './../package.json' ).name;
var dsmeanpw = require( './../lib/ndarray.js' );


// VARIABLES //

var options = {
'dtype': 'float32'
};


// FUNCTIONS //

/**
Expand All @@ -39,13 +45,7 @@ var dsmeanpw = require( './../lib/ndarray.js' );
* @returns {Function} benchmark function
*/
function createBenchmark( len ) {
var x;
var i;

x = new Float32Array( len );
for ( i = 0; i < x.length; i++ ) {
x[ i ] = ( randu()*20.0 ) - 10.0;
}
var x = uniform( len, -10.0, 10.0, options );
return benchmark;

function benchmark( b ) {
Expand Down
14 changes: 5 additions & 9 deletions lib/node_modules/@stdlib/stats/base/dsmeanpw/benchmark/benchmark.ndarray.native.js
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Original file line number Diff line number Diff line change
Expand Up @@ -22,10 +22,9 @@

var resolve = require( 'path' ).resolve;
var bench = require( '@stdlib/bench' );
var randu = require( '@stdlib/random/base/randu' );
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 Float32Array = require( '@stdlib/array/float32' );
var tryRequire = require( '@stdlib/utils/try-require' );
var pkg = require( './../package.json' ).name;

Expand All @@ -36,6 +35,9 @@ var dsmeanpw = tryRequire( resolve( __dirname, './../lib/ndarray.native.js' ) );
var opts = {
'skip': ( dsmeanpw instanceof Error )
};
var options = {
'dtype': 'float32'
};


// FUNCTIONS //
Expand All @@ -48,13 +50,7 @@ var opts = {
* @returns {Function} benchmark function
*/
function createBenchmark( len ) {
var x;
var i;

x = new Float32Array( len );
for ( i = 0; i < x.length; i++ ) {
x[ i ] = ( randu()*20.0 ) - 10.0;
}
var x = uniform( len, -10.0, 10.0, options );
return benchmark;

function benchmark( b ) {
Expand Down
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Coverage Report

Package Statements Branches Functions Lines
stats/base/dsmeanpw $\color{green}351/351$
$\color{green}+100.00\%$ 		$\color{green}18/18$
$\color{green}+100.00\%$ 		$\color{green}4/4$
$\color{green}+100.00\%$ 		$\color{green}351/351$
$\color{green}+100.00\%$

The above coverage report was generated for the changes in this push.

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