@stdlib/ndarray-base-assert-is-allowed-data-type-c

isAllowedCast

Determine whether an ndarray data type can be cast to another ndarray data type according to a specified casting mode.

Installation

npm install @stdlib/ndarray-base-assert-is-allowed-data-type-cast

Usage

var isAllowedCast = require( '@stdlib/ndarray-base-assert-is-allowed-data-type-cast' );

isAllowedCast( from, to, casting )

Returns a boolean indicating whether an ndarray data type can be cast to another ndarray data type according to a specified casting mode.

var bool = isAllowedCast( 'float32', 'float64', 'safe' );
// returns true

bool = isAllowedCast( 'float64', 'int32', 'safe' );
// returns false

The following casting modes are supported:

none: only allow casting between identical types.
equiv: allow casting between identical and byte swapped types.
safe: only allow "safe" casts.
mostly-safe: allow "safe" casts and, for floating-point data types, downcasts.
same-kind: allow "safe" casts and casts within the same kind (e.g., between signed integers or between floats).
unsafe: allow casting between all types (including between integers and floats).

Examples

var dtypes = require( '@stdlib/ndarray-dtypes' );
var modes = require( '@stdlib/ndarray-casting-modes' );
var isAllowedCast = require( '@stdlib/ndarray-base-assert-is-allowed-data-type-cast' );

var DTYPES;
var MODES;
var bool;
var dt1;
var dt2;
var i;
var j;
var k;

// Get a list of supported ndarray data types and casting modes:
DTYPES = dtypes();
MODES = modes();

// For each data type and mode, determine whether one can cast to another data type...
for ( i = 0; i < DTYPES.length; i++ ) {
    dt1 = DTYPES[ i ];
    for ( j = 0; j < DTYPES.length; j++ ) {
        dt2 = DTYPES[ j ];
        for ( k = 0; k < MODES.length; k++ ) {
            bool = isAllowedCast( dt1, dt2, MODES[ k ] );
            console.log( '%s => %s. %s: %s.', dt1, dt2, MODES[ k ], bool );
        }
    }
}

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.