smskmap

Apply a unary function to a single-precision floating-point strided input array according to a strided mask array and assign results to a single-precision floating-point strided output array.

Usage

var smskmap = require( '@stdlib/strided/base/smskmap' );

smskmap( N, x, strideX, mask, strideMask, y, strideY, fcn )

Applies a unary function to a single-precision floating-point strided input array according to a strided mask array and assigns results to a single-precision floating-point strided output array.

var Float32Array = require( '@stdlib/array/float32' );
var Uint8Array = require( '@stdlib/array/uint8' );
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 ] );
var m = new Uint8Array( [ 0, 0, 1, 0, 0, 1, 1, 0 ] );

// Compute the absolute values in-place:
smskmap( x.length, x, 1, m, 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.
  • mask: mask Uint8Array.
  • strideMask: index increment for mask.
  • y: output Float32Array.
  • strideY: index increment for y.
  • fcn: function to apply.

The N and stride parameters determine which elements in the strided arrays 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 Uint8Array = require( '@stdlib/array/uint8' );
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 m = new Uint8Array( [ 0, 0, 1, 0, 0, 1 ] );
var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] );

smskmap( 3, x, 2, m, 2, y, -1, absf );
// y => <Float32Array>[ 5.0, 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 views.

var Float32Array = require( '@stdlib/array/float32' );
var Uint8Array = require( '@stdlib/array/uint8' );
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 m0 = new Uint8Array( [ 0, 0, 1, 0, 0, 1 ] );
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 m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*3 ); // start at 4th element
var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 ); // start at 4th element

smskmap( 3, x1, -2, m1, 1, y1, 1, absf );
// y0 => <Float32Array>[ 0.0, 0.0, 0.0, 6.0, 4.0, 0.0 ]

smskmap.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask, y, strideY, offsetY, fcn )

Applies a unary function to a single-precision floating-point strided input array according to a strided mask array and assigns results to a single-precision floating-point strided output array using alternative indexing semantics.

var Float32Array = require( '@stdlib/array/float32' );
var Uint8Array = require( '@stdlib/array/uint8' );
var absf = require( '@stdlib/math/base/special/absf' );

var x = new Float32Array( [ -1.0, -2.0, -3.0, -4.0, -5.0 ] );
var m = new Uint8Array( [ 0, 0, 1, 0, 0 ] );
var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0, 0.0 ] );

smskmap.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0, absf );
// y => <Float32Array>[ 1.0, 2.0, 0.0, 4.0, 5.0 ]

The function accepts the following additional arguments:

  • offsetX: starting index for x.
  • offsetMask: starting index for mask.
  • 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 Uint8Array = require( '@stdlib/array/uint8' );
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 m = new Uint8Array( [ 0, 0, 1, 0, 0, 1 ] );
var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] );

smskmap.ndarray( 3, x, 2, 1, m, 2, 1, y, -1, y.length-1, absf );
// y => <Float32Array>[ 0.0, 0.0, 0.0, 0.0, 4.0, 2.0 ]

Examples

var round = require( '@stdlib/math/base/special/round' );
var randu = require( '@stdlib/random/base/randu' );
var bernoulli = require( '@stdlib/random/base/bernoulli' );
var Float32Array = require( '@stdlib/array/float32' );
var Uint8Array = require( '@stdlib/array/uint8' );
var smskmap = require( '@stdlib/strided/base/smskmap' );

function scale( x ) {
    return x * 10.0;
}

var x = new Float32Array( 10 );
var m = new Uint8Array( x.length );
var y = new Float32Array( x.length );

var i;
for ( i = 0; i < x.length; i++ ) {
    x[ i ] = round( (randu()*200.0) - 100.0 );
    m[ i ] = bernoulli( 0.2 );
}
console.log( x );
console.log( m );
console.log( y );

smskmap.ndarray( x.length, x, 1, 0, m, 1, 0, y, -1, y.length-1, scale );
console.log( y );

C APIs

Usage

#include "stdlib/strided/base/smskmap.h"

stdlib_strided_smskmap( N, *X, strideX, *Mask, strideMask, *Y, strideY, fcn )

Applies a unary function to a single-precision floating-point strided input array according to a strided mask 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[] = { 1.0f, 2.0f, 3.0f, 4.0f, 5.0f, 6.0f };
uint8_t M[] = { 0, 0, 1, 0, 0, 1 };
float Y[] = { 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f };

int64_t N = 6;

stdlib_strided_smskmap( N, X, 1, M, 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 for X.
  • Mask: [in] uint8_t* mask array.
  • strideMask: [in] int64_t index increment for Mask.
  • Y: [out] float* output array.
  • strideY: [in] int64_t index increment for Y.
  • fcn: [in] float (*fcn)( float ) unary function to apply.
void stdlib_strided_smskmap( const int64_t N, const float *X, const int64_t strideX, const uint8_t *Mask, const int64_t strideMask, float *Y, const int64_t strideY, float (*fcn)( float ) );

Examples

#include "stdlib/strided/base/smskmap.h"
#include <stdint.h>
#include <stdio.h>
#include <inttypes.h>

// Define a callback:
static float scale( const float x ) {
    return x * 10.0f;
}

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

    // Create a mask strided array:
    uint8_t M[] = { 0, 0, 1, 0, 0, 1 };

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

    // Specify the number of elements:
    int64_t N = 6;

    // Define the strides:
    int64_t strideX = 1;
    int64_t strideM = 1;
    int64_t strideY = -1;

    // Apply the callback:
    stdlib_strided_smskmap( N, X, strideX, M, strideM, 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/dmskmap: apply a unary function to a double-precision floating-point strided input array according to a strided mask array and assign results to a double-precision floating-point strided output array.
  • @stdlib/strided/base/mskunary: apply a unary callback to elements in a strided input array according to elements in a strided mask array and assign results to elements in a strided output array.
  • @stdlib/strided/base/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.
  • @stdlib/strided/base/smskmap2: apply a binary function to single-precision floating-point strided input arrays according to a strided mask array and assign results to a single-precision floating-point strided output array.
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