Thanks! On 04/04/2017 09:49 AM, Jaime Fernández del Río wrote:
On Tue, Apr 4, 2017 at 9:14 AM, Mads Ipsen <[email protected] <mailto:[email protected]>> wrote:Hi If I have an n x m array of bools, is there a handy way for me to perform a 'bitwise_and' or 'bitwise_or' along an axis, for example all the rows or all the columns? For example a = [[1,0,0,0], [0,0,1,0], [0,0,0,0]] (0 and 1 meaning True and False) a.bitwise_or(axis=0) giving [1,0,1,0] I think what you want is equivalent to np.all(a, axis=0) for bitwise_and and np.any(a, axis=0) for bitwise_or. You can also use the more verbose np.bitwise_and.reduce(a, axis=0) and np.bitwise_or.reduce(a, axis=0). Jaime Best regards, Mads -- +---------------------------------------------------------------------+ | Mads Ipsen | +----------------------------------+----------------------------------+ | Overgaden Oven Vandet 106, 4.tv <http://4.tv> | phone: +45-29716388 <tel:%2B45-29716388> | | DK-1415 København K | email: [email protected] <mailto:[email protected]> | | Denmark | map : https://goo.gl/maps/oQ6y6 | +----------------------------------+----------------------------------+ _______________________________________________ NumPy-Discussion mailing list [email protected] <mailto:[email protected]> https://mail.python.org/mailman/listinfo/numpy-discussion <https://mail.python.org/mailman/listinfo/numpy-discussion> -- (\__/) ( O.o) ( > <) Este es Conejo. Copia a Conejo en tu firma y ayúdale en sus planes de dominación mundial. _______________________________________________ NumPy-Discussion mailing list [email protected] https://mail.python.org/mailman/listinfo/numpy-discussion
-- +---------------------------------------------------------------------+ | Mads Ipsen | +----------------------------------+----------------------------------+ | Overgaden Oven Vandet 106, 4.tv | phone: +45-29716388 | | DK-1415 København K | email: [email protected] | | Denmark | map : https://goo.gl/maps/oQ6y6 | +----------------------------------+----------------------------------+ _______________________________________________ NumPy-Discussion mailing list [email protected] https://mail.python.org/mailman/listinfo/numpy-discussion
