About stdlib...

We believe in a future in which the web is a preferred environment for numerical computation. To help realize this future, we've built stdlib. stdlib is a standard library, with an emphasis on numerical and scientific computation, written in JavaScript (and C) for execution in browsers and in Node.js.

The library is fully decomposable, being architected in such a way that you can swap out and mix and match APIs and functionality to cater to your exact preferences and use cases.

When you use stdlib, you can be absolutely certain that you are using the most thorough, rigorous, well-written, studied, documented, tested, measured, and high-quality code out there.

To join us in bringing numerical computing to the web, get started by checking us out on GitHub, and please consider financially supporting stdlib. We greatly appreciate your continued support!

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.

Installation

npm install @stdlib/strided-base-smskmap2

Alternatively,

• To load the package in a website via a script tag without installation and bundlers, use the ES Module available on the esm branch (see README).
• If you are using Deno, visit the deno branch (see README for usage intructions).
• For use in Observable, or in browser/node environments, use the Universal Module Definition (UMD) build available on the umd branch (see README).

The branches.md file summarizes the available branches and displays a diagram illustrating their relationships.

To view installation and usage instructions specific to each branch build, be sure to explicitly navigate to the respective README files on each branch, as linked to above.

Usage

var smskmap2 = require( '@stdlib/strided-base-smskmap2' );

smskmap2( N, x, strideX, y, strideY, mask, strideMask, z, strideZ, fcn )

Applies a binary function to single-precision floating-point strided input arrays 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 addf = require( '@stdlib/math-base-ops-addf' );

var x = new Float32Array( [ -2.0, 1.0, -3.0, -5.0, 4.0, 0.0, -1.0, -3.0 ] );
var y = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] );
var z = new Float32Array( x.length );
var m = new Uint8Array( [ 0, 0, 1, 0, 0, 1, 1, 0 ] );

smskmap2( x.length, x, 1, y, 1, m, 1, z, 1, addf );
// z => <Float32Array>[ -1.0, 3.0, 0.0, -1.0, 9.0, 0.0, 0.0, 5.0 ]

The function accepts the following arguments:

• N: number of indexed elements.
• x: input Float32Array.
• strideX: index increment for x.
• y: input Float32Array.
• strideY: index increment for y.
• mask: mask Uint8Array.
• strideMask: index increment for mask.
• z: output Float32Array.
• strideZ: index increment for z.
• 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 addf = require( '@stdlib/math-base-ops-addf' );

var x = new Float32Array( [ -1.0, -2.0, -3.0, -4.0, -5.0, -6.0 ] );
var y = new Float32Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, 3.0 ] );
var z = new Float32Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] );
var m = new Uint8Array( [ 0, 0, 1, 0, 0, 1 ] );

smskmap2( 3, x, 2, y, -1, m, 2, z, 1, addf );
// z => <Float32Array>[ 1.0, 0.0, -4.0, 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 addf = require( '@stdlib/math-base-ops-addf' );

// Initial arrays...
var x0 = new Float32Array( [ -1.0, -2.0, -3.0, -4.0, -5.0, -6.0 ] );
var y0 = new Float32Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, 3.0 ] );
var z0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] );
var m0 = new Uint8Array( [ 0, 0, 1, 0, 0, 1 ] );

// 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
var z1 = new Float32Array( z0.buffer, z0.BYTES_PER_ELEMENT*2 ); // start at 3rd element
var m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*3 ); // start at 4th element

smskmap2( 3, x1, -2, y1, 1, m1, 1, z1, 1, addf );
// z0 => <Float32Array>[ 0.0, 0.0, -4.0, -1.0, 0.0, 0.0 ]

smskmap2.ndarray( N, x, strideX, offsetX, y, strideY, offsetY, mask, strideMask, offsetMask, z, strideZ, offsetZ, fcn )

Applies a binary function to single-precision floating-point strided input arrays 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 addf = require( '@stdlib/math-base-ops-addf' );

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

smskmap2.ndarray( x.length, x, 1, 0, y, 1, 0, m, 1, 0, z, 1, 0, addf );
// z => <Float32Array>[ 0.0, -1.0, 0.0, -2.0, -2.0 ]

The function accepts the following addfitional arguments:

• offsetX: starting index for x.
• offsetY: starting index for y.
• offsetMask: starting index for mask.
• offsetZ: starting index for z.

While typed array views mandate a view offset based on the underlying buffer, the offset 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 addf = require( '@stdlib/math-base-ops-addf' );

var x = new Float32Array( [ -1.0, -2.0, -3.0, -4.0, -5.0, -6.0 ] );
var y = new Float32Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, 3.0 ] );
var z = new Float32Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] );
var m = new Uint8Array( [ 0, 0, 1, 0, 0, 1 ] );

smskmap2.ndarray( 3, x, 2, 1, y, -1, y.length-1, m, 2, 1, z, 1, 0, addf );
// z => <Float32Array>[ 1.0, -1.0, 0.0, 0.0, 0.0, 0.0 ]

Examples

var discreteUniform = require( '@stdlib/random-base-discrete-uniform' ).factory;
var bernoulli = require( '@stdlib/random-base-bernoulli' ).factory;
var Float32Array = require( '@stdlib/array-float32' );
var filledarrayBy = require( '@stdlib/array-filled-by' );
var addf = require( '@stdlib/math-base-ops-addf' );
var smskmap2 = require( '@stdlib/strided-base-smskmap2' );

var x = filledarrayBy( 10, 'float32', discreteUniform( -100, 100 ) );
console.log( x );

var y = filledarrayBy( x.length, 'float32', discreteUniform( -100, 100 ) );
console.log( y );

var m = filledarrayBy( x.length, 'uint8', bernoulli( 0.2 ) );
console.log( m );

var z = new Float32Array( x.length );
console.log( z );

smskmap2.ndarray( x.length, x, 1, 0, y, -1, y.length-1, m, 1, 0, z, 1, 0, addf );
console.log( z );

---

C APIs

Usage

#include "stdlib/strided/base/smskmap2.h"

stdlib_strided_smskmap2( N, *X, strideX, *Y, strideY, *Mask, strideMask, *Z, strideZ, fcn )

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

#include <stdint.h>

static float addf( const float x, const float y ) {
    return x + y;
}

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

int64_t N = 6;

stdlib_strided_smskmap2( N, X, 1, Y, 1, M, 1, Z, 1, addf );

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: [int] float* input array.
• strideY: [in] int64_t index increment for Y.
• Mask: [in] uint8_t* mask array.
• strideMask: [in] int64_t index increment for Mask.
• Z: [out] float* output array.
• strideZ: [in] int64_t index increment for Z.
• fcn: [in] float (*fcn)( float, float ) binary function to apply.

void stdlib_strided_smskmap2( const int64_t N, const float *X, const int64_t strideX, const float *Y, const int64_t strideY, const uint8_t *Mask, const int64_t strideMask, float *Z, const int64_t strideZ, float (*fcn)( float, float ) );

Examples

#include "stdlib/strided/base/smskmap2.h"
#include <stdint.h>
#include <stdio.h>
#include <inttypes.h>

// Define a callback:
static float addf( const float x, const float y ) {
    return x + y;
}

int main( void ) {
    // Create input strided arrays:
    float X[] = { 1.0f, 2.0f, 3.0f, 4.0f, 5.0f, 6.0f };
    float Y[] = { 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 Z[] = { 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 strideY = -1;
    int64_t strideZ = 1;
    int64_t strideM = 1;

    // Apply the callback:
    stdlib_strided_smskmap2( N, X, strideX, Y, strideY, M, strideM, Z, strideZ, addf );

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

---

See Also

• @stdlib/strided-base/dmskmap2: apply a binary function to double-precision floating-point strided input arrays according to a strided mask array and assign results to a double-precision floating-point strided output array.
• @stdlib/strided-base/smap2: apply a binary function to single-precision floating-point strided input arrays and assign results to a single-precision floating-point strided output array.
• @stdlib/strided-base/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.

---

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.