Package Exports

@stdlib/stats-strided-smskmaxabs
@stdlib/stats-strided-smskmaxabs/lib/index.js
@stdlib/stats-strided-smskmaxabs/lib/main.js

This package does not declare an exports field, so the exports above have been automatically detected and optimized by JSPM instead. If any package subpath is missing, it is recommended to post an issue to the original package (@stdlib/stats-strided-smskmaxabs) to support the "exports" field. If that is not possible, create a JSPM override to customize the exports field for this package.

Readme

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!

smskmaxabs

Calculate the maximum absolute value of a single-precision floating-point strided array according to a mask.

Installation

npm install @stdlib/stats-strided-smskmaxabs

Usage

var smskmaxabs = require( '@stdlib/stats-strided-smskmaxabs' );

smskmaxabs( N, x, strideX, mask, strideMask )

Computes the maximum absolute value of a single-precision floating-point strided array according to a mask.

var Float32Array = require( '@stdlib/array-float32' );
var Uint8Array = require( '@stdlib/array-uint8' );

var x = new Float32Array( [ 1.0, -2.0, 4.0, 2.0 ] );
var mask = new Uint8Array( [ 0, 0, 1, 0 ] );

var v = smskmaxabs( x.length, x, 1, mask, 1 );
// returns 2.0

The function has the following parameters:

N: number of indexed elements.
x: input Float32Array.
strideX: stride length for x.
mask: mask Uint8Array. If a mask array element is 0, the corresponding element in x is considered valid and included in computation. If a mask array element is 1, the corresponding element in x is considered invalid/missing and excluded from computation.
strideMask: stride length for mask.

The N and stride parameters determine which elements in the strided arrays are accessed at runtime. For example, to compute the maximum absolute value of every other element in x,

var Float32Array = require( '@stdlib/array-float32' );
var Uint8Array = require( '@stdlib/array-uint8' );

var x = new Float32Array( [ 1.0, 2.0, -7.0, -2.0, 4.0, 3.0, 5.0, 6.0 ] );
var mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1, 1 ] );

var v = smskmaxabs( 4, x, 2, mask, 2 );
// returns 7.0

Note that indexing is relative to the first index. To introduce offsets, use typed array views.

var Float32Array = require( '@stdlib/array-float32' );
var Uint8Array = require( '@stdlib/array-uint8' );

var x0 = new Float32Array( [ 2.0, 1.0, -2.0, -2.0, 3.0, 4.0, 5.0, 6.0 ] );
var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element

var mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1, 1 ] );
var mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 ); // start at 2nd element

var v = smskmaxabs( 4, x1, 2, mask1, 2 );
// returns 4.0

smskmaxabs.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )

Computes the maximum absolute value of a single-precision floating-point strided array according to a mask and using alternative indexing semantics.

var Float32Array = require( '@stdlib/array-float32' );
var Uint8Array = require( '@stdlib/array-uint8' );

var x = new Float32Array( [ 1.0, -2.0, 4.0, 2.0 ] );
var mask = new Uint8Array( [ 0, 0, 1, 0 ] );

var v = smskmaxabs.ndarray( x.length, x, 1, 0, mask, 1, 0 );
// returns 2.0

The function has the following additional parameters:

offsetX: starting index for x.
offsetMask: starting index for mask.

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 calculate the maximum absolute value for every other element in x starting from the second element

var Float32Array = require( '@stdlib/array-float32' );
var Uint8Array = require( '@stdlib/array-uint8' );

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

var v = smskmaxabs.ndarray( 4, x, 2, 1, mask, 2, 1 );
// returns 4.0

Notes

If N <= 0, both functions return NaN.

Examples

var uniform = require( '@stdlib/random-array-uniform' );
var bernoulli = require( '@stdlib/random-array-bernoulli' );
var smskmaxabs = require( '@stdlib/stats-strided-smskmaxabs' );

var x = uniform( 10, -50.0, 50.0, {
    'dtype': 'float32'
});
console.log( x );

var mask = bernoulli( x.length, 0.2, {
    'dtype': 'uint8'
});
console.log( mask );

var v = smskmaxabs( x.length, x, 1, mask, 1 );
console.log( v );

C APIs

Usage

#include "stdlib/stats/strided/smskmaxabs.h"

stdlib_strided_smskmaxabs( N, X, strideX, Mask, strideMask )

Computes the maximum absolute value of a single-precision floating-point strided array according to a mask.

#include <stdint.h>

const float x[] = { 1.0f, -2.0f, 2.0f };
const uint8_t mask[] = { 0, 1, 0 };

float v = stdlib_strided_smskmaxabs( 3, x, 1, mask, 1 );
// returns 2.0f

The function accepts the following arguments:

N: [in] CBLAS_INT number of indexed elements.
X: [in] float* input array.
strideX: [in] CBLAS_INT stride length for X.
Mask: [in] uint8_t* mask array. If a Mask array element is 0, the corresponding element in X is considered valid and included in computation. If a Mask array element is 1, the corresponding element in X is considered invalid/missing and excluded from computation.
strideMask: [in] CBLAS_INT stride length for Mask.

float stdlib_strided_smskmaxabs( const CBLAS_INT N, const float *X, const CBLAS_INT strideX, const uint8_t *Mask, const CBLAS_INT strideMask );

stdlib_strided_smskmaxabs_ndarray( N, X, strideX, offsetX, Mask, strideMask, offsetMask )

Computes the maximum absolute value of a single-precision floating-point strided array according to a mask and using alternative indexing semantics.

#include <stdint.h>

const float x[] = { 1.0f, -2.0f, 2.0f };
const uint8_t mask[] = { 0, 1, 0 };

float v = stdlib_strided_smskmaxabs_ndarray( 3, x, 1, 0, mask, 1, 0 );
// returns 2.0f

The function accepts the following arguments:

N: [in] CBLAS_INT number of indexed elements.
X: [in] float* input array.
strideX: [in] CBLAS_INT stride length for X.
offsetX: [in] CBLAS_INT starting index for X.
Mask: [in] uint8_t* mask array. If a Mask array element is 0, the corresponding element in X is considered valid and included in computation. If a Mask array element is 1, the corresponding element in X is considered invalid/missing and excluded from computation.
strideMask: [in] CBLAS_INT stride length for Mask.
offsetMask: [in] CBLAS_INT starting index for Mask.

float stdlib_strided_smskmaxabs_ndarray( const CBLAS_INT N, const float *X, const CBLAS_INT strideX, const CBLAS_INT offsetX, const uint8_t *Mask, const CBLAS_INT strideMask, const CBLAS_INT offsetMask );

Examples

#include "stdlib/stats/strided/smskmaxabs.h"
#include <stdint.h>
#include <stdio.h>

int main( void ) {
    // Create a strided array:
    const float x[] = { 1.0f, 2.0f, 3.0f, 4.0f, 5.0f, 6.0f, 7.0f, 8.0f, 9.0f, 10.0f };

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

    // Specify the number of elements:
    const int N = 5;

    // Specify the stride lengths:
    const int strideX = 2;
    const int strideMask = 2;

    // Compute the maximum absolute value:
    float v = stdlib_strided_smskmaxabs( N, x, strideX, mask, strideMask );

    // Print the result:
    printf( "max: %f\n", v );
}

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.

@stdlib/stats-strided-smskmaxabs

Package Exports

Readme

smskmaxabs

Installation

Usage

smskmaxabs( N, x, strideX, mask, strideMask )

smskmaxabs.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )

Notes

Examples

C APIs

Usage

stdlib_strided_smskmaxabs( N, *X, strideX, *Mask, strideMask )

stdlib_strided_smskmaxabs_ndarray( N, *X, strideX, offsetX, *Mask, strideMask, offsetMask )

Examples

Notice

Community

License

Copyright

stdlib_strided_smskmaxabs( N, X, strideX, Mask, strideMask )

stdlib_strided_smskmaxabs_ndarray( N, X, strideX, offsetX, Mask, strideMask, offsetMask )