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Compute the minimum linear index in an underlying data buffer accessible to an array view.
import minViewBufferIndex from 'https://cdn.jsdelivr.net/gh/stdlib-js/ndarray-base-min-view-buffer-index@esm/index.mjs';
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
<!DOCTYPE html>
<html lang="en">
<body>
<script type="module">
import discreteUniform from 'https://cdn.jsdelivr.net/gh/stdlib-js/random-base-discrete-uniform@esm/index.mjs';
import shape2strides from 'https://cdn.jsdelivr.net/gh/stdlib-js/ndarray-base-shape2strides@esm/index.mjs';
import strides2offset from 'https://cdn.jsdelivr.net/gh/stdlib-js/ndarray-base-strides2offset@esm/index.mjs';
import randu from 'https://cdn.jsdelivr.net/gh/stdlib-js/random-base-randu@esm/index.mjs';
import minViewBufferIndex from 'https://cdn.jsdelivr.net/gh/stdlib-js/ndarray-base-min-view-buffer-index@esm/index.mjs';
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 );
}
</script>
</body>
</html>
This package is part of stdlib, a standard library 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.
See LICENSE.
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