# numpy.ldexp¶

`numpy.``ldexp`(x1, x2, /, out=None, *, where=True, casting='same_kind', order='K', dtype=None, subok=True[, signature, extobj]) = <ufunc 'ldexp'>

Returns x1 * 2**x2, element-wise.

The mantissas x1 and twos exponents x2 are used to construct floating point numbers `x1 * 2**x2`.

Parameters: x1 : array_like Array of multipliers. x2 : array_like, int Array of twos exponents. out : ndarray, None, or tuple of ndarray and None, optional A location into which the result is stored. If provided, it must have a shape that the inputs broadcast to. If not provided or None, a freshly-allocated array is returned. A tuple (possible only as a keyword argument) must have length equal to the number of outputs. where : array_like, optional Values of True indicate to calculate the ufunc at that position, values of False indicate to leave the value in the output alone. **kwargs For other keyword-only arguments, see the ufunc docs. y : ndarray or scalar The result of `x1 * 2**x2`. This is a scalar if both x1 and x2 are scalars.

`frexp`
Return (y1, y2) from `x = y1 * 2**y2`, inverse to `ldexp`.

Notes

Complex dtypes are not supported, they will raise a TypeError.

`ldexp` is useful as the inverse of `frexp`, if used by itself it is more clear to simply use the expression `x1 * 2**x2`.

Examples

```>>> np.ldexp(5, np.arange(4))
array([  5.,  10.,  20.,  40.], dtype=float32)
```
```>>> x = np.arange(6)
>>> np.ldexp(*np.frexp(x))
array([ 0.,  1.,  2.,  3.,  4.,  5.])
```

numpy.frexp

numpy.nextafter