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  • License Apache-2.0

Compute the Fresnel integrals S(x) and C(x).

Package Exports

  • @stdlib/math-base-special-fresnel

This package does not declare an exports field, so the exports above have been automatically detected and optimized by JSPM instead. If any package subpath is missing, it is recommended to post an issue to the original package (@stdlib/math-base-special-fresnel) to support the "exports" field. If that is not possible, create a JSPM override to customize the exports field for this package.

Readme

fresnel

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Compute the Fresnel integrals S(x) and C(x).

The Fresnel integrals are defined as

Fresnel integral

Some sources define the Fresnel integrals using t2 for the argument of the sine and cosine. To get these functions, multiply the computed integrals by √(π/2) and multiply the argument x by √(2/π).

Installation

npm install @stdlib/math-base-special-fresnel

Usage

var fresnel = require( '@stdlib/math-base-special-fresnel' );

fresnel( [out,] x )

Simultaneously computes the Fresnel integrals S(x) and C(x).

var v = fresnel( 0.0 );
// returns [ ~0.0, ~0.0 ]

v = fresnel( 1.0 );
// returns [ ~0.438, ~0.780 ]

v = fresnel( Infinity );
// returns [ ~0.5, ~0.5 ]

v = fresnel( -Infinity );
// returns [ ~-0.5, ~-0.5 ]

v = fresnel( NaN );
// returns [ NaN, NaN ]

By default, the function returns the S(x) and C(x) as a two-element array. To avoid extra memory allocation, the function supports providing an output (destination) object.

var Float64Array = require( '@stdlib/array-float64' );

var out = new Float64Array( 2 );

var v = fresnel( out, 0.0 );
// returns <Float64Array>[ ~0.0, ~0.0 ]

var bool = ( v === out );
// returns true

Examples

var linspace = require( '@stdlib/array-linspace' );
var fresnel = require( '@stdlib/math-base-special-fresnel' );

var x = linspace( 0.0, 10.0, 100 );
var i;

for ( i = 0; i < x.length; i++ ) {
    console.log( fresnel( x[ i ] ) );
}

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.

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License

See LICENSE.

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