time-to-botec/js/node_modules/@stdlib/strided/base/dmskmap

dmskmap

Apply a unary function accepting and returning double-precision floating-point numbers to each element in a double-precision floating-point strided input array according to a corresponding element in a strided mask array and assign each result to an element in a double-precision floating-point strided output array.

Usage

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

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

Applies a unary function accepting and returning double-precision floating-point numbers to each element in a double-precision floating-point strided input array according to a corresponding element in a strided mask array and assigns each result to an element in a double-precision floating-point strided output array.

var Float64Array = require( '@stdlib/array/float64' );
var Uint8Array = require( '@stdlib/array/uint8' );
var abs = require( '@stdlib/math/base/special/abs' );

var x = new Float64Array( [ -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:
dmskmap( x.length, x, 1, m, 1, x, 1, abs );
// x => <Float64Array>[ 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 Float64Array.
• strideX: index increment for x.
• mask: mask Uint8Array.
• strideMask: index increment for mask.
• y: output Float64Array.
• 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 Float64Array = require( '@stdlib/array/float64' );
var Uint8Array = require( '@stdlib/array/uint8' );
var floor = require( '@stdlib/math/base/special/floor' );
var abs = require( '@stdlib/math/base/special/abs' );

var x = new Float64Array( [ -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 Float64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] );

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

dmskmap( N, x, 2, m, 2, y, -1, abs );
// y => <Float64Array>[ 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 Float64Array = require( '@stdlib/array/float64' );
var Uint8Array = require( '@stdlib/array/uint8' );
var floor = require( '@stdlib/math/base/special/floor' );
var abs = require( '@stdlib/math/base/special/abs' );

// Initial arrays...
var x0 = new Float64Array( [ -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 Float64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] );

// Create offset views...
var x1 = new Float64Array( 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 Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 ); // start at 4th element

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

dmskmap( N, x1, -2, m1, 1, y1, 1, abs );
// y0 => <Float64Array>[ 0.0, 0.0, 0.0, 6.0, 4.0, 0.0 ]

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

Applies a unary function accepting and returning double-precision floating-point numbers to each element in a double-precision floating-point strided input array according to a corresponding element in a strided mask array and assigns each result to an element in a double-precision floating-point strided output array using alternative indexing semantics.

var Float64Array = require( '@stdlib/array/float64' );
var Uint8Array = require( '@stdlib/array/uint8' );
var abs = require( '@stdlib/math/base/special/abs' );

var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0, -5.0 ] );
var m = new Uint8Array( [ 0, 0, 1, 0, 0 ] );
var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0 ] );

dmskmap.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0, abs );
// y => <Float64Array>[ 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,

var Float64Array = require( '@stdlib/array/float64' );
var Uint8Array = require( '@stdlib/array/uint8' );
var floor = require( '@stdlib/math/base/special/floor' );
var abs = require( '@stdlib/math/base/special/abs' );

var x = new Float64Array( [ -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 Float64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] );

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

dmskmap.ndarray( N, x, 2, 1, m, 2, 1, y, -1, y.length-1, abs );
// y => <Float64Array>[ 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 Float64Array = require( '@stdlib/array/float64' );
var Uint8Array = require( '@stdlib/array/uint8' );
var dmskmap = require( '@stdlib/strided/base/dmskmap' );

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

var x = new Float64Array( 10 );
var m = new Uint8Array( x.length );
var y = new Float64Array( 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 );

dmskmap.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/dmskmap.h"

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

Applies a unary function accepting and returning double-precision floating-point numbers to each element in a double-precision floating-point strided input array according to a corresponding element in a strided mask array and assigns each result to an element in a double-precision floating-point strided output array.

#include <stdint.h>

static double scale( const double x ) {
    return x * 10.0;
}

double X[] = { 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 };
uint8_t M[] = { 0, 0, 1, 0, 0, 1 };
double Y[] = { 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 };

int64_t N = 6;

stdlib_strided_dmskmap( N, X, 1, M, 1, Y, 1, scale );

The function accepts the following arguments:

• N: [in] int64_t number of indexed elements.
• X: [in] double* 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] double* output array.
• strideY: [in] int64_t index increment for Y.
• fcn: [in] double (*fcn)( double ) unary function to apply.

void stdlib_strided_dmskmap( const int64_t N, const double *X, const int64_t strideX, const uint8_t *Mask, const int64_t strideMask, double *Y, const int64_t strideY, double (*fcn)( double ) );

Examples

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

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

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

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

    // Create an output strided array:
    double 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 strideM = 1;
    int64_t strideY = -1;

    // Apply the callback:
    stdlib_strided_dmskmap( N, X, strideX, M, strideM, Y, strideY, scale );

    // Print the results:
    for ( int64_t i = 0; i < N; i++ ) {
        printf( "Y[ %"PRId64" ] = %lf\n", i, Y[ i ] );
    }
}