# mars.tensor.ldexp#

mars.tensor.ldexp(x1, x2, out=None, where=None, **kwargs)[source]#

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) – Tensor of multipliers.

• x2 (array_like, int) – Tensor of twos exponents.

• out (Tensor, None, or tuple of Tensor 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 tensor 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

Returns

y – The result of `x1 * 2**x2`.

Return type

Tensor or scalar

`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

```>>> import mars.tensor as mt
```
```>>> mt.ldexp(5, mt.arange(4)).execute()
array([  5.,  10.,  20.,  40.], dtype=float32)
```
```>>> x = mt.arange(6)
>>> mt.ldexp(*mt.frexp(x)).execute()
array([ 0.,  1.,  2.,  3.,  4.,  5.])
```