On Fri, Jan 2, 2015 at 7:45 PM, Daniel Smith wrote:
> Hello everyone,
>
> I have been working on a chunk of code that basically sets out to provide
> a single function that can take an arbitrary einsum expression and computes
> it in the most optimal way. While np.einsum can compute arbitrary
> e
Hello everyone,
I have been working on a chunk of code that basically sets out to provide a
single function that can take an arbitrary einsum expression and computes it in
the most optimal way. While np.einsum can compute arbitrary expressions, there
are two drawbacks to using pure einsum: eins
Hi All,
The diag, diagonal, and ravel functions have recently been changed to
preserve subtypes. However, this causes lots of backward compatibility
problems for matrix users, in particular, scipy.sparse. One possibility for
fixing this is to special case matrix and so that these functions continu
Yuxiang Wang wrote:
> 1) @Strula Sorry about my stupid mistake! That piece of code totally
> gave away how green I am in coding C :)
Don't worry. C is a high-level assember. It will bite you again and again,
it happens to everyone. Those who say they have never made a stupid mistake
while coding
Yuxiang Wang wrote:
> 4) I wanted to say that it seems to me, as the project gradually
> scales up, Cython is easier to deal with, especially when I am using a
> lot of numpy arrays. If it is even higher dimensional data, it would
> be verbose while it is really succinct to use Cython.
The easie
Dear Jaime:
Thank you so much. Your codes are always great.
By the way, I have been waiting for several hours to get satisfactory
answer at:
http://codereview.stackexchange.com/questions/75457/faster-way-of-using-interp1d-in-2d-array?noredirect=1#comment137329_75457
http://stackoverflow.com/ques
Hi,
without further testing; this approach may help:
(1) create a shared library with all symbols from libnpymath.a:
$ gcc -shared -o libnpymath.dll -Wl,--whole-archive libnpymath.a
-Wl,--no-whole-archive -lm
(2) create a def file:
gendef libnpymath.dll
There are now two files created by mings
On Fri, Jan 2, 2015 at 3:06 AM, Simen Langseth wrote:
> import numpy as np
> from scipy import signal
>
> y = np.array([[2, 1, 2, 3, 2, 0, 1, 0],
> [2, 1, 2, 3, 2, 0, 1, 0]])
>
> maximas = signal.argrelmax(y, axis=1)
>
> print maximas
>
> (array([0, 0, 1, 1], dtype=int64), array([3,
import numpy as np
from scipy import signal
y = np.array([[2, 1, 2, 3, 2, 0, 1, 0],
[2, 1, 2, 3, 2, 0, 1, 0]])
maximas = signal.argrelmax(y, axis=1)
print maximas
(array([0, 0, 1, 1], dtype=int64), array([3, 6, 3, 6], dtype=int64))
I want to extract only the first maxima of both
On Fri, Jan 2, 2015 at 5:13 AM, Charles R Harris
wrote:
> Hi All,
>
> I've invited Alex Griffing onto the team to be a numpy developer. He has
> been contributing fixes and reviews for a while and it is time to give him
> more opportunity to contribute. I think he will do well.
>
+1
Ralf
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