On Sun, Dec 6, 2015 at 3:55 PM, Allan Haldane <allanhald...@gmail.com>
 wrote:

>
> I've also often wanted to generate large datasets of random uint8 and
> uint16. As a workaround, this is something I have used:
>
> np.ndarray(100, 'u1', np.random.bytes(100))
>
> It has also crossed my mind that np.random.randint and np.random.rand
> could use an extra 'dtype' keyword. It didn't look easy to implement though.
>

Another workaround that avoids creating a copy is to use the view method,
e.g.,
np.random.randint(np.iinfo(int).min, np.iinfo(int).max,
size=(1,)).view(np.uint8)  # creates 8 random bytes

Cheers,
Stephan
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