On Tue, Nov 6, 2012 at 8:27 PM, Phillip Feldman wrote:
> numpy.unique behaves as I would expect for small inputs like the following:
>
> In [12]: x= [0, 0, 1, 0, 1, 2, 0, 1, 2, 3]
>
> In [13]: unique(x, return_index=True)
> Out[13]: (array([0, 1, 2, 3]), array([0, 2, 5, 9], dtype=int64))
>
> But,
numpy.unique behaves as I would expect for small inputs like the following:
In [12]: x= [0, 0, 1, 0, 1, 2, 0, 1, 2, 3]
In [13]: unique(x, return_index=True)
Out[13]: (array([0, 1, 2, 3]), array([0, 2, 5, 9], dtype=int64))
But, when I give it something larger, the return index values do not alway
Hi,
I made a PR with my fix:
https://github.com/numpy/numpy/pull/2709
Frédéric
On Tue, Oct 2, 2012 at 6:18 PM, Charles R Harris
wrote:
>
>
> On Tue, Oct 2, 2012 at 1:44 PM, Frédéric Bastien wrote:
>
>> With numpy 1.6.2, it is working. So this is an interface change. Are
>> you sure you want
Hi,
I updated the numpy master and recompiled it. I still have the compilation
error I got from Theano. I'll pop up that email thread again to have the
history and I made a PR for this.
Also, I think I said that numpy.ndindex changed its interface, in the past
numpy.ndindex() was valid, not this
Dear all,
Since the NumPy 1.7.0b2 release didn't include a Windows
(32 bit) installer for Python 3.3, I am considering compiling it
myself for local testing. What compiler is recommended?
Thanks,
Peter
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Hi,
I would like to package pyhdf for Ubuntu and make the package publicly
available. Since the license is not totally clear to me (I cannot find any
information in the sources, and the cheeseshop says "public", which
doesn't mean anything to me), I tried to contact the maintainer, Andre
Gosselin,
