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minViewBufferIndex

Compute the minimum linear index in an underlying data buffer accessible to an array view.

Installation

npm install @stdlib/ndarray-base-min-view-buffer-index

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 minViewBufferIndex = require( '@stdlib/ndarray-base-min-view-buffer-index' );

minViewBufferIndex( shape, strides, offset )

Computes the minimum linear index in an underlying data buffer accessible to an array view.

// Array shape:
var shape = [ 2, 2 ];

// Stride array:
var strides = [ -2, -1 ];

// Index offset which specifies the location of the first indexed value:
var offset = 13; // includes a view offset

var idx = minViewBufferIndex( shape, strides, offset );
// returns 10

Examples

var discreteUniform = require( '@stdlib/random-base-discrete-uniform' );
var shape2strides = require( '@stdlib/ndarray-base-shape2strides' );
var strides2offset = require( '@stdlib/ndarray-base-strides2offset' );
var randu = require( '@stdlib/random-base-randu' );
var minViewBufferIndex = require( '@stdlib/ndarray-base-min-view-buffer-index' );

var strides;
var offset;
var shape;
var idx;
var i;
var j;

shape = [ 0, 0, 0 ];

for ( i = 0; i < 100; i++ ) {
    // Generate a random array shape:
    shape[ 0 ] = discreteUniform( 1, 10 );
    shape[ 1 ] = discreteUniform( 1, 10 );
    shape[ 2 ] = discreteUniform( 1, 10 );

    // Generate strides:
    if ( randu() < 0.5 ) {
        strides = shape2strides( shape, 'row-major' );
    } else {
        strides = shape2strides( shape, 'column-major' );
    }
    j = discreteUniform( 0, shape.length-1 );
    strides[ j ] *= ( randu() < 0.5 ) ? -1 : 1;

    // Compute the index offset:
    offset = strides2offset( shape, strides ) + 25; // include view offset

    // Compute the minimum linear index:
    idx = minViewBufferIndex( shape, strides, offset );
    console.log( 'Shape: %s. Strides: %s. Offset: %d. Min idx: %d.', shape.join( 'x' ), strides.join( ',' ), offset, idx );
}

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C APIs

Usage

#include "stdlib/ndarray/base/min_view_buffer_index.h"

stdlib_ndarray_min_view_buffer_index( ndims, *shape, *strides, offset )

Computes the minimum linear index (in bytes) in an underlying data buffer accessible to an array view.

#include <stdint.h>

int64_t ndims = 2;
int64_t shape[] = { 10, 10 };
int64_t strides[] = { 10, 1 };
int64_t offset = 10;

int64_t idx = stdlib_ndarray_min_view_buffer_index( ndims, shape, strides, offset );
// returns 10

The function accepts the following arguments:

• ndims: [in] int64_t number of dimensions.
• shape: [in] int64_t* array shape (dimensions).
• strides: [in] int64_t* array strides (in bytes).
• offset: [in] int64_t index offset.

int64_t stdlib_ndarray_min_view_buffer_index( const int64_t ndims, const int64_t *shape, const int64_t *strides, const int64_t offset );

Examples

#include "stdlib/ndarray/base/min_view_buffer_index.h"
#include <stdint.h>
#include <stdio.h>
#include <inttypes.h>

int main( void ) {
    // Specify the number of dimensions:
    const int64_t ndims = 2;

    // Define an array shape:
    const int64_t shape[] = { 10, 10 };

    // Define array strides:
    const int64_t strides[] = { -2, 5 };

    // Define an offset:
    const int64_t offset = 100;

    // Compute the minimum accessible index:
    int64_t idx = stdlib_ndarray_min_view_buffer_index( ndims, shape, strides, offset );

    // Print the results:
    printf( "idx: %"PRId64"\n", idx );
}

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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

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License

See LICENSE.

Copyright

Copyright © 2016-2024. The Stdlib Authors.