On Fr, 2014-08-29 at 22:10 -0400, Benjamin Root wrote:
Consider the following:
a = np.array([(1, 'a'), (2, 'b'), (3, 'c')], dtype=[('foo', 'i'),
('bar', 'a1')])
b = np.append(a, (4, 'd'))
Traceback (most recent call last):
File stdin, line 1, in module
File
On Sa, 2014-08-30 at 09:04 +0100, Sebastian Berg wrote:
On Fr, 2014-08-29 at 22:10 -0400, Benjamin Root wrote:
Consider the following:
a = np.array([(1, 'a'), (2, 'b'), (3, 'c')], dtype=[('foo', 'i'),
('bar', 'a1')])
b = np.append(a, (4, 'd'))
Traceback (most recent call last):
On Sat, Aug 30, 2014 at 6:43 PM, josef.p...@gmail.com wrote:
Is there a way to negate a boolean, or to change the sign of a float inplace
?
np.logical_not(arr, out=arr)
np.negative(arr, out=arr)
-n
--
Nathaniel J. Smith
Postdoctoral researcher - Informatics - University of Edinburgh
Random thoughts are the best kinds of thoughts! I didn't even know there
was a np.negative() function! I will keep this card up my sleeve at work
for one of those save-the-day moments in optimization.
Cheers!
Ben Root
On Sat, Aug 30, 2014 at 1:45 PM, Nathaniel Smith n...@pobox.com wrote:
On
On Sat, Aug 30, 2014 at 7:39 PM, Benjamin Root ben.r...@ou.edu wrote:
Random thoughts are the best kinds of thoughts! I didn't even know there was
a np.negative() function!
Me neither, I had to look it up :-)
-n
--
Nathaniel J. Smith
Postdoctoral researcher - Informatics - University of
