@stdlib/math-iter-special-coversin NPM

iterCoversin

$NPM version$ $Build Status$ $Coverage Status$

Create an iterator which computes the coversed sine for each iterated value.

Installation

npm install @stdlib/math-iter-special-coversin

Usage

var iterCoversin = require( '@stdlib/math-iter-special-coversin' );

iterCoversin( iterator )

Returns an iterator which iteratively computes the coversed sine.

var array2iterator = require( '@stdlib/array-to-iterator' );

var it = iterCoversin( array2iterator( [ 0.0, 1.57 ] ) );
// returns <Object>

var v = it.next().value;
// returns 1.0

v = it.next().value;
// returns ~0.0

// ...

The returned iterator protocol-compliant object has the following properties:

next: function which returns an iterator protocol-compliant object containing the next iterated value (if one exists) assigned to a value property and a done property having a boolean value indicating whether the iterator is finished.
return: function which closes an iterator and returns a single (optional) argument in an iterator protocol-compliant object.

Notes

If an iterated value is non-numeric (including NaN), the returned iterator returns NaN. If non-numeric iterated values are possible, you are advised to provide an iterator which type checks and handles non-numeric values accordingly.
If an environment supports Symbol.iterator and a provided iterator is iterable, the returned iterator is iterable.

Examples

var uniform = require( '@stdlib/random-iter-uniform' );
var iterCoversin = require( '@stdlib/math-iter-special-coversin' );

// Create a seeded iterator for generating pseudorandom numbers:
var rand = uniform( 0.0, 6.28, {
    'seed': 1234,
    'iter': 10
});

// Create an iterator which consumes the pseudorandom number iterator:
var it = iterCoversin( rand );

// Perform manual iteration...
var v;
while ( true ) {
    v = it.next();
    if ( v.done ) {
        break;
    }
    console.log( v.value );
}

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.