On 12/08/2015 07:40 PM, Stephan Hoyer wrote:
On Sun, Dec 6, 2015 at 3:55 PM, Allan Haldane <email@example.com mailto:firstname.lastname@example.org> 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
Just to note, the line I pasted doesn't copy either, according to the OWNDATA flag.