time-to-botec/squiggle/node_modules/@stdlib/math/strided/special/dmsksqrt/README.md
NunoSempere b6addc7f05 feat: add the node modules
Necessary in order to clearly see the squiggle hotwiring.
2022-12-03 12:44:49 +00:00

8.8 KiB

dmsksqrt

Compute the principal square root for each element in a double-precision floating-point strided array according to a strided mask array.

Usage

var dmsksqrt = require( '@stdlib/math/strided/special/dmsksqrt' );

dmsksqrt( N, x, sx, m, sm, y, sy )

Computes the principal square root for each element in a double-precision floating-point strided array x according to a strided mask array and assigns the results to elements in a double-precision floating-point strided array y.

var Float64Array = require( '@stdlib/array/float64' );
var Uint8Array = require( '@stdlib/array/uint8' );

var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0, 24.0 ] );
var m = new Uint8Array( [ 0, 0, 1, 0, 1 ] );
var y = new Float64Array( x.length );

dmsksqrt( x.length, x, 1, m, 1, y, 1 );
// y => <Float64Array>[ 0.0, 2.0, 0.0, ~3.464, 0.0 ]

The function accepts the following arguments:

  • N: number of indexed elements.
  • x: input Float64Array.
  • sx: index increment for x.
  • m: mask Uint8Array.
  • sm: index increment for m.
  • y: output Float64Array.
  • sy: index increment for y.

The N and stride parameters determine which strided array elements 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 x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0, 24.0, 64.0 ] );
var m = new Uint8Array( [ 0, 0, 1, 0, 1, 1 ] );
var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] );

dmsksqrt( 3, x, 2, m, 2, y, -1 );
// y => <Float64Array>[ 0.0, 0.0, 0.0, 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' );

// Initial arrays...
var x0 = new Float64Array( [ 0.0, 4.0, 9.0, 12.0, 24.0, 64.0 ] );
var m0 = new Uint8Array( [ 0, 0, 1, 0, 1, 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*1 ); // start at 2nd element
var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 ); // start at 4th element

dmsksqrt( 3, x1, -2, m1, -2, y1, 1 );
// y0 => <Float64Array>[ 0.0, 0.0, 0.0, 0.0, ~3.464, 2.0 ]

dmsksqrt.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )

Computes the principal square root for each element in a double-precision floating-point strided array x according to a strided mask array and assigns the results to elements in a double-precision floating-point strided array y using alternative indexing semantics.

var Float64Array = require( '@stdlib/array/float64' );
var Uint8Array = require( '@stdlib/array/uint8' );

var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0, 24.0 ] );
var m = new Uint8Array( [ 0, 0, 1, 0, 1 ] );
var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0 ] );

dmsksqrt.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 );
// y => <Float64Array>[ 0.0, 2.0, 0.0, ~3.464, 0.0 ]

The function accepts the following additional arguments:

  • ox: starting index for x.
  • om: starting index for m.
  • oy: starting index for y.

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,

var Float64Array = require( '@stdlib/array/float64' );
var Uint8Array = require( '@stdlib/array/uint8' );

var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0, 24.0, 64.0 ] );
var m = new Uint8Array( [ 0, 0, 1, 0, 1, 1 ] );
var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] );

dmsksqrt.ndarray( 3, x, 2, 1, m, 2, 1, y, -1, y.length-1 );
// y => <Float64Array>[ 0.0, 0.0, 0.0, 0.0, ~3.464, 2.0 ]

Examples

var uniform = require( '@stdlib/random/base/uniform' );
var Float64Array = require( '@stdlib/array/float64' );
var Uint8Array = require( '@stdlib/array/uint8' );
var dmsksqrt = require( '@stdlib/math/strided/special/dmsksqrt' );

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

var i;
for ( i = 0; i < x.length; i++ ) {
    x[ i ] = uniform( 0.0, 200.0 );
    if ( uniform( 0.0, 1.0 ) < 0.5 ) {
        m[ i ] = 1;
    }
}
console.log( x );
console.log( m );
console.log( y );

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

C APIs

Usage

#include "stdlib/math/strided/special/dmsksqrt.h"

stdlib_strided_dmsksqrt( N, *X, strideX, *Mask, strideMask, *Y, strideY )

Computes the principal square root for each element in a double-precision floating-point strided array X according to a strided mask array and assigns the results to elements in a double-precision floating-point strided array Y.

#include <stdint.h>

double X[] = { 0.0, 4.0, 9.0, 12.0, 24.0, 64.0, 81.0, 101.0 };
uint8_t Mask[] = { 0, 0, 1, 0, 1, 1, 0, 0 };
double Y[] = { 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 };

int64_t N = 4;

stdlib_strided_dmsksqrt( N, X, 2, Mask, 2, Y, 2 );

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.
void stdlib_strided_dmsksqrt( 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 );

Examples

#include "stdlib/math/strided/special/dmsksqrt.h"
#include <stdint.h>
#include <stdio.h>

int main() {
    // Create an input strided array:
    double X[] = { 0.0, 4.0, 9.0, 12.0, 24.0, 64.0, 81.0, 101.0 };

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

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

    // Specify the number of elements:
    int64_t N = 4;

    // Specify the stride lengths:
    int64_t strideX = 2;
    int64_t strideM = 2;
    int64_t strideY = 2;

    // Compute the results:
    stdlib_strided_dmsksqrt( N, X, strideX, M, strideM, Y, strideY );

    // Print the results:
    for ( int i = 0; i < 8; i++ ) {
        printf( "Y[ %i ] = %lf\n", i, Y[ i ] );
    }
}