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Tensor0D

Create a zero-dimensional ndarray.

Installation

npm install @stdlib/ndarray-tensor0d-ctor

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 tensor0d = require( '@stdlib/ndarray-tensor0d-ctor' );

tensor0d()

Returns a zero-dimensional ndarray having a float64 data type.

var getDType = require( '@stdlib/ndarray-dtype' );

var arr = tensor0d();
// returns <ndarray>

var dt = String( getDType( arr ) );
// returns 'float64'

tensor0d( dtype[, options] )

Returns a zero-dimensional ndarray having a specified data type.

var getDType = require( '@stdlib/ndarray-dtype' );

var arr = tensor0d( 'int32' );
// returns <ndarray>

var dt = String( getDType( arr ) );
// returns 'int32'

The function accepts the following options:

• order: specifies whether an ndarray is 'row-major' (C-style) or 'column-major' (Fortran-style). Default: 'row-major'.
• readonly: boolean indicating whether an array should be read-only. Default: false.

tensor0d( buffer[, byteOffset][, dtype][, options] )

Returns a zero-dimensional ndarray view of an ArrayBuffer.

var ArrayBuffer = require( '@stdlib/array-buffer' );
var getDType = require( '@stdlib/ndarray-dtype' );

var buf = new ArrayBuffer( 32 );

var arr1 = tensor0d( buf );
// returns <ndarray>

var dt1 = String( getDType( arr1 ) );
// returns 'float64'

var arr2 = tensor0d( buf, 'float32' );
// returns <ndarray>

var dt2 = String( getDType( arr2 ) );
// returns 'float32'

var arr3 = tensor0d( buf, 16 );
// returns <ndarray>

var dt3 = String( getDType( arr3 ) );
// returns 'float64'

var arr4 = tensor0d( buf, 16, 'float32' );
// returns <ndarray>

var dt4 = String( getDType( arr4 ) );
// returns 'float32'

The function accepts the same options as above.

tensor0d( value[, dtype][, options] )

Creates a zero-dimensional ndarray from a scalar value.

var arr1 = tensor0d( 1.0 );
// returns <ndarray>

var arr2 = tensor0d( 1.0, 'float32' );
// returns <ndarray>

If a dtype argument is not provided and value

• is a number, the default data type is the default real-valued floating-point data type.
• is a boolean, the default data type is the default boolean data type.
• is a complex number object of a known data type, the data type is the same as the provided value.
• is a complex number object of an unknown data type, the default data type is the default complex-valued floating-point data type.
• is any other value type, the default data type is 'generic'.

If value is a number and dtype is a complex data type, the function returns a zero-dimensional ndarray containing a complex number whose real component equals the provided scalar value and whose imaginary component is zero.

The function does not guard against precision loss when value is a number and the dtype argument is an integer data type.

The function accepts the same options as above.

tensor0d.factory( dtype[, options] )

Returns a function for creating a zero-dimensional ndarray.

var getDType = require( '@stdlib/ndarray-dtype' );

var Float32Tensor0D = tensor0d.factory( 'float32' );

var arr = new Float32Tensor0D( 1.0 );
// returns <ndarray>

var dt = String( getDType( arr ) );
// returns 'float32'

The function supports the following parameters:

• dtype: data type.
• options: function options (optional).

The function accepts the following options:

• order: specifies whether the default memory layout for a returned ndarray should be 'row-major' (C-style) or 'column-major' (Fortran-style). Default: 'row-major'.
• readonly: boolean indicating whether to return a read-only ndarray by default. Default: false.

The function returned by the factory method supports the same arguments and options as tensor0d above, except for the dtype argument, as the returned function always returns a zero-dimensional ndarray having the same data type.

When providing options to the returned function, the provided option values override the defaults established during function creation.

Examples

var discreteUniform = require( '@stdlib/random-array-discrete-uniform' );
var cartesianProduct = require( '@stdlib/array-cartesian-product' );
var unzip = require( '@stdlib/utils-unzip' );
var dtypes = require( '@stdlib/ndarray-dtypes' );
var logEachMap = require( '@stdlib/console-log-each-map' );
var tensor0d = require( '@stdlib/ndarray-tensor0d-ctor' );

// Create an array of random values:
var values = discreteUniform( 10, 5, 15, {
    'dtype': 'int32'
});

// Resolve a list of supported ndarray integer-valued data types:
var dts = dtypes( 'integer_and_generic' );

// Create value-dtype pairs:
var pairs = cartesianProduct( values, dts );

// Split the pairs into individual arguments:
var args = unzip( pairs );

// Define a callback to create an ndarray and return the scalar:
function clbk( value, dtype ) {
    var x = tensor0d( value, dtype );
    return x.get();
}

// Apply the callback and print the results:
logEachMap( 'value: %2d. dtype: %7s. value: %d.', args[ 0 ], args[ 1 ], clbk );

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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 © 2016-2026. The Stdlib Authors.