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Create an array filled with NaNs and having the same length and data type as a provided array.
npm install @stdlib/array-nans-likeAlternatively,
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var nansLike = require( '@stdlib/array-nans-like' );Creates an array filled with NaNs and having the same length and data type as a provided array x.
var x = [ 1, 2, 3, 4, 5 ];
var arr = nansLike( x );
// returns [ NaN, NaN, NaN, NaN, NaN ]The function supports 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 numberscomplex64: single-precision complex floating-point numbersgeneric: generic JavaScript values
By default, the output array data type is inferred from the provided array x. To return an array having a different data type, provide a dtype argument.
var x = [ 0, 0 ];
var arr = nansLike( x, 'float32' );
// returns <Float32Array>[ NaN, NaN ]- If the output array has a complex number data type, each element of the returned array has a real component equal to
NaNand an imaginary component equal toNaN.
var dtypes = require( '@stdlib/array-typed-float-dtypes' );
var zeros = require( '@stdlib/array-zeros' );
var nansLike = require( '@stdlib/array-nans-like' );
// Create a zero-filled array:
var x = zeros( 4, 'complex128' );
// Get a list of array data types:
var dt = dtypes();
// Generate filled arrays...
var y;
var i;
for ( i = 0; i < dt.length; i++ ) {
y = nansLike( x, dt[ i ] );
console.log( y );
}@stdlib/array-full-like: create a filled array having the same length and data type as a provided array.@stdlib/array-nans: create an array filled with NaNs and having a specified length.@stdlib/array-ones-like: create an array filled with ones and having the same length and data type as a provided array.@stdlib/array-zeros-like: create a zero-filled array having the same length and data type as a provided array.
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.
See LICENSE.
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