Thank you very much Robert !
For really big matrices, "where" is 4 times faster ! For small matrices, it's
slower than my old solution, but it really doesn't matter, it's fast enough. :)
I will think about "put" too. I used it before, but i must adapt all functions
to obtain the necessary indexe
Please excuse me for incorrect information in my announcement:
On Fri, Jun 19, 2009 at 04:01:58PM +0200, Gael Varoquaux wrote:
> We are very happy to announce that this year registration to the
> conference will be only $150, sprints $100, and students get half price!
This should read that the tu
On 2009-06-19, Nils Wagner wrote:
> Is this a known failure ?
> I am using 1.4.0.dev7069
Check the tickets:
http://projects.scipy.org/numpy/ticket/1108
Cause is not known yet, but that bug most likely has been around for a long
time.
--
Pauli Virtanen
___
Hi all,
Is this a known failure ?
I am using 1.4.0.dev7069
==
FAIL: Test bug in reduceat with structured arrays copied
for speed.
--
Traceback (most recent call
We are finally opening the registration for the SciPy 2009 conference. It
took us time, but the reason is that we made careful budget estimations
to bring the registration cost down.
We are very happy to announce that this year registration to the
conference will be only $150, sprints $100, and st
or if your mask is thin and constant, then consider np.put
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well its not really slow.
yet with np.where it seems to be 2x faster for large arrays :
a[1:4,1:4] = np.where(mask,b,a[1:4,1:4])
otherwise consider Cython:
http://docs.cython.org/docs/numpy_tutorial.html#tuning-indexing-further
Robert
Cristi Constantin wrote:
>
> Thank you so much for your