@devtea2026/nihil-iusto-possimus-consequatur NPM

Typed Arrays

Create a typed array.

Installation

npm install @devtea2026/nihil-iusto-possimus-consequatur

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 typedarray = require( '@devtea2026/nihil-iusto-possimus-consequatur' );

typedarray( [dtype] )

Creates a typed array having a specified data type dtype.

var arr = typedarray();
// returns <Float64Array>

The function recognizes the following data types:

float64: double-precision floating-point numbers (IEEE 754)
float32: single-precision floating-point numbers (IEEE 754)
complex128: double-precision complex floating-point numbers
complex64: single-precision complex floating-point numbers
int32: 32-bit two's complement signed integers
uint32: 32-bit unsigned integers
int16: 16-bit two's complement signed integers
uint16: 16-bit unsigned integers
int8: 8-bit two's complement signed integers
uint8: 8-bit unsigned integers
uint8c: 8-bit unsigned integers clamped to 0-255

By default, the output typed array data type is float64. To specify an alternative data type, provide a dtype argument.

var arr = typedarray( 'int32' );
// returns <Int32Array>

typedarray( length[, dtype] )

Returns a typed array having a specified length.

var arr1 = typedarray( 5 );
// returns <Float64Array>[ 0.0, 0.0, 0.0, 0.0, 0.0 ]

var arr2 = typedarray( 5, 'uint8' );
// returns <Uint8Array>[ 0, 0, 0, 0, 0 ]

typedarray( typedarray[, dtype] )

Creates a typed array from another typed array.

var arr1 = typedarray( [ 5.0, -3.0, 2.0 ] );
// returns <Float64Array>[ 5.0, -3.0, 2.0 ]

var arr2 = typedarray( arr1 );
// returns <Float64Array>[ 5.0, -3.0, 2.0 ]

var arr3 = typedarray( arr1, 'int32' );
// returns <Int32Array>[ 5, -3, 2 ]

typedarray( obj[, dtype] )

Creates a typed array from an array-like object or iterable.

var arr1 = typedarray( [ 0.5, 0.5, 0.5 ] );
// returns <Float64Array>[ 0.5, 0.5, 0.5 ]

var arr2 = typedarray( [ 0.5, 0.5, 0.5 ], 'float32' );
// returns <Float32Array>[ 0.5, 0.5, 0.5 ]

If dtype is complex number data type and an array-like object contains interleaved real and imaginary components, the array-like object must have a length which is a multiple of two.

typedarray( buffer[, byteOffset[, length]][, dtype] )

Returns a typed array view of an ArrayBuffer.

var ArrayBuffer = require( '@stdlib/array-buffer' );
var buf = new ArrayBuffer( 32 );

var arr1 = typedarray( buf );
// returns <Float64Array>[ 0.0, 0.0, 0.0, 0.0 ]

var arr2 = typedarray( buf, 'float32' );
// returns <Float32Array>[ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ]

var arr3 = typedarray( buf, 16 );
// returns <Float64Array>[ 0.0, 0.0 ]

var arr4 = typedarray( buf, 16, 'float32' );
// returns <Float32Array>[ 0.0, 0.0, 0.0, 0.0 ]

var arr5 = typedarray( buf, 16, 1 );
// returns <Float64Array>[ 0.0 ]

var arr6 = typedarray( buf, 10, 4, 'int16' );
// returns <Int16Array>[ 0, 0, 0, 0 ]

Notes

When providing a complex number array, if dtype is unspecified or the specified data type is not a complex number data type, the returned array contains interleaved real and imaginary components.

Examples

var randu = require( '@stdlib/random-base-randu' );
var typedarray = require( '@devtea2026/nihil-iusto-possimus-consequatur' );

var arr = typedarray( 100, 'float64' );

var i;
for ( i = 0; i < arr.length; i++ ) {
    arr[ i ] = randu() * 100.0;
}
console.log( arr );

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.