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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