npm package: @stdlib/math-strided-special-sramp
Description: Evaluate the ramp function for each element in a single-precision floating-point strided array.
Author: The Stdlib Authors
Latest version: 0.2.3

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# sramp

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> Evaluate the [ramp function][@stdlib/math/base/special/rampf] for each element in a single-precision floating-point strided array.

<section class="intro">

</section>

<!-- /.intro -->

<section class="installation">

## Installation

```bash
npm install @stdlib/math-strided-special-sramp
```

</section>

<section class="usage">

## Usage

```javascript
var sramp = require( '@stdlib/math-strided-special-sramp' );
```

#### sramp( N, x, strideX, y, strideY )

Evaluates the [ramp function][@stdlib/math/base/special/rampf] for each element in a single-precision floating-point strided array `x` and assigns the results to elements in a single-precision floating-point strided array `y`.

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

var x = new Float32Array( [ 1.0, 2.0, -3.0, 4.0, -5.0 ] );

// Perform operation in-place:
sramp( x.length, x, 1, x, 1 );
// x => <Float32Array>[ 1.0, 2.0, 0.0, 4.0, 0.0 ]
```

The function accepts the following arguments:

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

The `N` and `stride` parameters determine which elements in `x` and `y` are accessed at runtime. For example, to index every other value in `x` and to index the first `N` elements of `y` in reverse order,

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

var x = new Float32Array( [ 1.0, 2.0, -3.0, 4.0, -5.0, 6.0 ] );
var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] );

sramp( 3, x, 2, y, -1 );
// y => <Float32Array>[ 0.0, 0.0, 1.0, 0.0, 0.0, 0.0 ]
```

Note that indexing is relative to the first index. To introduce an offset, use [`typed array`][@stdlib/array/float32] views.

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

// Initial arrays...
var x0 = new Float32Array( [ 1.0, 2.0, -3.0, 4.0, -5.0, 6.0 ] );
var y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] );

// Create offset views...
var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element
var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 ); // start at 4th element

sramp( 3, x1, -2, y1, 1 );
// y0 => <Float32Array>[ 0.0, 0.0, 0.0, 6.0, 4.0, 2.0 ]
```

#### sramp.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )

Evaluates the [ramp function][@stdlib/math/base/special/rampf] for each element in a single-precision floating-point strided array `x` and assigns the results to elements in a single-precision floating-point strided array `y` using alternative indexing semantics.

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

var x = new Float32Array( [ 1.0, 2.0, -3.0, 4.0, -5.0 ] );
var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0, 0.0 ] );

sramp.ndarray( x.length, x, 1, 0, y, 1, 0 );
// y => <Float32Array>[ 1.0, 2.0, 0.0, 4.0, 0.0 ]
```

The function accepts the following additional arguments:

-   **offsetX**: starting index for `x`.
-   **offsetY**: starting index for `y`.

While [`typed array`][@stdlib/array/float32] views mandate a view offset based on the underlying `buffer`, the `offsetX` and `offsetY` parameters support indexing semantics based on starting indices. For example, to index every other value in `x` starting from the second value and to index the last `N` elements in `y`,

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

var x = new Float32Array( [ 1.0, 2.0, -3.0, 4.0, -5.0, 6.0 ] );
var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] );

sramp.ndarray( 3, x, 2, 1, y, -1, y.length-1 );
// y => <Float32Array>[ 0.0, 0.0, 0.0, 6.0, 4.0, 2.0 ]
```

</section>

<!-- /.usage -->

<section class="notes">

</section>

<!-- /.notes -->

<section class="examples">

## Examples

<!-- eslint no-undef: "error" -->

```javascript
var uniform = require( '@stdlib/random-base-uniform' );
var Float32Array = require( '@stdlib/array-float32' );
var sramp = require( '@stdlib/math-strided-special-sramp' );

var x = new Float32Array( 10 );
var y = new Float32Array( 10 );

var i;
for ( i = 0; i < x.length; i++ ) {
    x[ i ] = uniform( -10.0, 10.0 );
}
console.log( x );
console.log( y );

sramp.ndarray( x.length, x, 1, 0, y, -1, y.length-1 );
console.log( y );
```

</section>

<!-- /.examples -->

<!-- C interface documentation. -->

* * *

<section class="c">

## C APIs

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<section class="intro">

</section>

<!-- /.intro -->

<!-- C usage documentation. -->

<section class="usage">

### Usage

```c
#include "stdlib/math/strided/special/sramp.h"
```

#### stdlib_strided_sramp( N, \*X, strideX, \*Y, strideY )

Evaluates the ramp function for each element in a single-precision floating-point strided array `X` and assigns the results to elements in a single-precision floating-point strided array `Y`.

```c
#include <stdint.h>

const float X[] = { 1.0, 2.0, -3.0, 4.0, -5.0, 6.0, -7.0, 8.0 };
float Y[] = { 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 };

const int64_t N = 4;

stdlib_strided_sramp( N, X, 2, Y, 2 );
```

The function accepts the following arguments:

-   **N**: `[in] int64_t` number of indexed elements.
-   **X**: `[in] float*` input array.
-   **strideX**: `[in] int64_t` index increment for `X`.
-   **Y**: `[out] float*` output array.
-   **strideY**: `[in] int64_t` index increment for `Y`.

```c
void stdlib_strided_sramp( const int64_t N, const float *X, const int64_t strideX, float *Y, const int64_t strideY );
```

</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/math/strided/special/sramp.h"
#include <stdint.h>
#include <stdio.h>

int main( void ) {
    // Create an input strided array:
    const float X[] = { 1.0, 2.0, -3.0, 4.0, -5.0, 6.0, -7.0, 8.0 };

    // Create an output strided array:
    float Y[] = { 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 };

    // Specify the number of elements:
    const int64_t N = 4;

    // Specify the stride lengths:
    const int64_t strideX = 2;
    const int64_t strideY = 2;

    // Compute the results:
    stdlib_strided_sramp( N, X, strideX, Y, strideY );

    // Print the results:
    for ( int i = 0; i < 8; i++ ) {
        printf( "Y[ %i ] = %f\n", i, Y[ i ] );
    }
}
```

</section>

<!-- /.examples -->

</section>

<!-- /.c -->

<!-- Section for related `stdlib` packages. Do not manually edit this section, as it is automatically populated. -->

<section class="related">

* * *

## See Also

-   <span class="package-name">[`@stdlib/math-strided/special/dramp`][@stdlib/math/strided/special/dramp]</span><span class="delimiter">: </span><span class="description">evaluate the ramp function for each element in a double-precision floating-point strided array.</span>
-   <span class="package-name">[`@stdlib/math-strided/special/ramp`][@stdlib/math/strided/special/ramp]</span><span class="delimiter">: </span><span class="description">evaluate the ramp function for each element in a strided array.</span>

</section>

<!-- /.related -->

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<section class="main-repo" >

* * *

## Notice

This package is part of [stdlib][stdlib], a standard library for JavaScript and Node.js, with an emphasis on numerical and scientific computing. The library provides a collection of robust, high performance libraries for mathematics, statistics, streams, utilities, and more.

For more information on the project, filing bug reports and feature requests, and guidance on how to develop [stdlib][stdlib], see the main project [repository][stdlib].

#### Community

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---

## License

See [LICENSE][stdlib-license].


## Copyright

Copyright &copy; 2016-2026. The Stdlib [Authors][stdlib-authors].

</section>

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