On 10/03/2014 11:24 PM, Charles R Harris wrote:
What I want is that the following script would warn three times
import numpy as np
z = np.zeros(1, dtype=np.int http://np.int)
def f(x):
return x/x
f(z)
f(z)
f(z)
But it only warns once. That is not helpful when f gets called
On Sat, Oct 4, 2014 at 2:17 AM, Nathaniel Smith n...@pobox.com wrote:
On Sat, Oct 4, 2014 at 12:40 AM, Robert Kern robert.k...@gmail.com wrote:
On Sat, Oct 4, 2014 at 12:21 AM, Nathaniel Smith n...@pobox.com wrote:
On Fri, Oct 3, 2014 at 8:12 AM, Robert Kern robert.k...@gmail.com wrote:
On
Hi everyone,
import numpy as np
np.__version__
'1.9.0'
np.gradient(np.array([[1, 2, 6], [3, 4, 5]], dtype=np.float))
[array([[ 2., 2., -1.],
[ 2., 2., -1.]]), array([[-0.5, 2.5, 5.5],
[ 1. , 1. , 1. ]])]
On the other hand:
import numpy as np
np.__version__
On 4 Oct 2014, at 08:37 pm, Ariel Rokem aro...@gmail.com wrote:
import numpy as np
np.__version__
'1.9.0'
np.gradient(np.array([[1, 2, 6], [3, 4, 5]], dtype=np.float))
[array([[ 2., 2., -1.],
[ 2., 2., -1.]]), array([[-0.5, 2.5, 5.5],
[ 1. , 1. , 1. ]])]
On the
On Sat, Oct 4, 2014 at 12:29 PM, Derek Homeier
de...@astro.physik.uni-goettingen.de wrote:
On 4 Oct 2014, at 08:37 pm, Ariel Rokem aro...@gmail.com wrote:
import numpy as np
np.__version__
'1.9.0'
np.gradient(np.array([[1, 2, 6], [3, 4, 5]], dtype=np.float))
[array([[ 2., 2.,
Hi Ariel,
I think that the docstring in 1.9 is fine (has the 1.9 result). The docs
online (for all of numpy) are still on version 1.8, though.
I think that enabling the old behavior might be useful, if only so that I can
write code that behaves consistently across these two versions of
On Oct 4, 2014 10:14 PM, Derek Homeier
de...@astro.physik.uni-goettingen.de wrote:
+1 for an order=2 or maxorder=2 flag
If you parameterize that flag, users will want to change its value (above
two). Perhaps rather use a boolean flag such as second_order or
high_order, unless it seems feasible
On Fri, Oct 3, 2014 at 11:28 AM, T J tjhn...@gmail.com wrote:
It does, but it is not portable. That's why I was hoping NumPy might think
about supporting more rounding algorithms.
On Thu, Oct 2, 2014 at 10:00 PM, John Zwinck jzwi...@gmail.com wrote:
On 3 Oct 2014 07:09, T J
