@stdlib/strided-base-smap
v0.2.2
Published
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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smap
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.
Installation
npm install @stdlib/strided-base-smap
Usage
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.
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 => <Float32Array>[ 2.0, 1.0, 3.0, 5.0, 4.0, 0.0, 1.0, 3.0 ]
The function accepts the following arguments:
- N: number of indexed elements.
- x: input
Float32Array
. - strideX: index increment for
x
. - y: output
Float32Array
. - strideY: index increment for
y
. - 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,
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 => <Float32Array>[ 5.0, 3.0, 1.0, 0.0, 0.0, 0.0 ]
Note that indexing is relative to the first index. To introduce an offset, use typed array
views.
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 => <Float32Array>[ 0.0, 0.0, 0.0, 6.0, 4.0, 2.0 ]
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.
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 => <Float32Array>[ 1.0, 2.0, 3.0, 4.0, 5.0 ]
The function accepts the following additional arguments:
- offsetX: starting index for
x
. - offsetY: starting index for
y
.
While typed array
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,
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 => <Float32Array>[ 0.0, 0.0, 0.0, 6.0, 4.0, 2.0 ]
Examples
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 APIs
Usage
#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.
#include <stdint.h>
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. - X:
[in] float*
input array. - strideX
[in] int64_t
index increment forX
. - Y:
[out] float*
output array. - strideY:
[in] int64_t
index increment forY
. - fcn:
[in] float (*fcn)( float )
unary function to apply.
void stdlib_strided_smap( const int64_t N, const float *X, const int64_t strideX, float *Y, const int64_t strideY, float (*fcn)( float ) );
Examples
#include "stdlib/strided/base/smap.h"
#include <stdint.h>
#include <stdio.h>
#include <inttypes.h>
// 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 ] );
}
}
See Also
@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
: apply a unary callback to elements in a strided input array and assign results to elements in a strided output array.
Notice
This package is part of 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, see the main project repository.
Community
License
See LICENSE.
Copyright
Copyright © 2016-2024. The Stdlib Authors.