Apply a unary function to a single-precision floating-point strided input array and assign results to a single-precision floating-point strided output array.
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> Apply a unary function to a single-precision floating-point strided input array and assign results to a single-precision floating-point strided output array.
``bash`
npm install @stdlib/strided-base-smap
`javascript`
var smap = require( '@stdlib/strided-base-smap' );
#### smap( N, x, strideX, y, strideY, fcn )
Applies a unary function to a single-precision floating-point strided input array and assigns results to a single-precision floating-point strided output array.
`javascript
var Float32Array = require( '@stdlib/array-float32' );
var absf = require( '@stdlib/math-base-special-absf' );
var x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, 0.0, -1.0, -3.0 ] );
// Compute the absolute values in-place:
smap( x.length, x, 1, x, 1, absf );
// x =>
`
The function accepts the following arguments:
- N: number of indexed elements.
- x: input [Float32Array][@stdlib/array/float32].x
- strideX: index increment for .Float32Array
- y: output [][@stdlib/array/float32].y
- strideY: index increment for .
- fcn: function to apply.
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 absf = require( '@stdlib/math-base-special-absf' );
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 ] );
smap( 3, x, 2, y, -1, absf );
// y =>
`
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' );
var absf = require( '@stdlib/math-base-special-absf' );
// 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
smap( 3, x1, -2, y1, 1, absf );
// y0 =>
`
#### smap.ndarray( N, x, strideX, offsetX, y, strideY, offsetY, fcn )
Applies a unary function to a single-precision floating-point strided input array and assigns results to a single-precision floating-point strided output array using alternative indexing semantics.
`javascript
var Float32Array = require( '@stdlib/array-float32' );
var absf = require( '@stdlib/math-base-special-absf' );
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 ] );
smap.ndarray( x.length, x, 1, 0, y, 1, 0, absf );
// y =>
`
The function accepts the following additional arguments:
- offsetX: starting index for x.y
- offsetY: starting index for .
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 in reverse order,
`javascript
var Float32Array = require( '@stdlib/array-float32' );
var absf = require( '@stdlib/math-base-special-absf' );
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 ] );
smap.ndarray( 3, x, 2, 1, y, -1, y.length-1, absf );
// y =>
`
`javascript
var round = require( '@stdlib/math-base-special-round' );
var randu = require( '@stdlib/random-base-randu' );
var Float32Array = require( '@stdlib/array-float32' );
var smap = require( '@stdlib/strided-base-smap' );
function scale( x ) {
return x * 10.0;
}
var x = new Float32Array( 10 );
var y = new Float32Array( 10 );
var i;
for ( i = 0; i < x.length; i++ ) {
x[ i ] = round( (randu()*200.0) - 100.0 );
}
console.log( x );
console.log( y );
smap.ndarray( x.length, x, 1, 0, y, -1, y.length-1, scale );
console.log( y );
`
*
`c`
#include "stdlib/strided/base/smap.h"
#### stdlib_strided_smap( N, \X, strideX, \Y, strideY, fcn )
Applies a unary function to a single-precision floating-point strided input array and assigns results to a single-precision floating-point strided output array.
`c
#include
static float scale( const float x ) {
return x * 10.0f;
}
float X[] = { 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 };
float Y[] = { 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 };
int64_t N = 6;
stdlib_strided_smap( N, X, 1, Y, 1, scale );
`
The function accepts the following arguments:
- N: [in] int64_t number of indexed elements.[in] float*
- X: input array.[in] int64_t
- strideX index increment for X.[out] float*
- Y: output array.[in] int64_t
- strideY: index increment for Y.[in] float (*fcn)( float )
- fcn: unary function to apply.
`c`
void stdlib_strided_smap( const int64_t N, const float X, const int64_t strideX, float Y, const int64_t strideY, float (*fcn)( float ) );
`c
#include "stdlib/strided/base/smap.h"
#include
#include
#include
// Define a callback:
static float scale( const float x ) {
return x * 10.0;
}
int main( void ) {
// Create an input strided array:
float X[] = { 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 };
// Create an output strided array:
float Y[] = { 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 };
// Specify the number of elements:
int64_t N = 6;
// Define the strides:
int64_t strideX = 1;
int64_t strideY = -1;
// Apply the callback:
stdlib_strided_smap( N, X, strideX, Y, strideY, scale );
// Print the results:
for ( int64_t i = 0; i < N; i++ ) {
printf( "Y[ %"PRId64" ] = %f\n", i, Y[ i ] );
}
}
`
*
- [@stdlib/strided-base/dmap][@stdlib/strided/base/dmap]: apply a unary function to a double-precision floating-point strided input array and assign results to a double-precision floating-point strided output array.
- [@stdlib/strided-base/unary][@stdlib/strided/base/unary]: apply a unary callback to elements in a strided input array and assign results to elements in a strided output array.
*
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].
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---
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[@stdlib/array/float32]: https://www.npmjs.com/package/@stdlib/array-float32
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[@stdlib/strided/base/unary]: https://www.npmjs.com/package/@stdlib/strided-base-unary