Dear all,
I'd like to know if there is a pythonic / numpy way of retrieving unique
lines of a 2d numpy array.
In a way I have this :
[[409 152]
[409 152]
[409 152]
[409 152]
[409 152]
[409 152]
[409 152]
[409 152]
[409 152]
[409 152]
[409 152]
[426 193]
[431 129]]
And I'd like to ge
hi,
I'm trying to install numpy-1.5.0 in our Itanium (IA-64) supercomputer
[http://www.cesga.es/content/view/917/115/lang,en/ ].
This is my site.cfg (I have to install umfpack but I think this is not the
problem):
$ cat site.cfg
[DEFAULT]
library_dirs =
/opt/cesga/fftw-3.2.2/lib:/opt/cesga/i
>> X_{ijk} = \sum_{l} A_{il}*B_{jl}*C_{kl}
>
> (A[:,newaxis,newaxis]*B[newaxis,:,newaxis]*C[newaxis,newaxis,:]).sum(axis=-1)
Thanks for the quick solution and practical exercise in broadcasting!
:-) However, this creates a temporary 4-array, right? Is there a way of
avoiding this memory requireme
Mon, 20 Sep 2010 23:34:58 +0200, Hagen Fürstenau wrote:
> I don't know if I'm overlooking something obvious, but is there a
> compact way of computing the 3-array
>
> X_{ijk} = \sum_{l} A_{il}*B_{jl}*C_{kl}
>
> out of the 2-arrays A, B, and C?
(A[:,newaxis,newaxis]*B[newaxis,:,newaxis]*C[newaxis
Hi,
I don't know if I'm overlooking something obvious, but is there a
compact way of computing the 3-array
X_{ijk} = \sum_{l} A_{il}*B_{jl}*C_{kl}
out of the 2-arrays A, B, and C?
- Hagen
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On Sep 20, 2010, at 11:09 PM, Benjamin Root wrote:
>
> And also if the inner execution could be clarified by asanyarray assertion
> why there is ma equivalent array operation functions?
>
> That is a design question for the numpy gods...
Well, asanyarray is not always a panacea, and can le
On Mon, Sep 20, 2010 at 4:03 PM, Gökhan Sever wrote:
> On Mon, Sep 20, 2010 at 3:34 PM, Benjamin Root wrote:
>
>> I have been using masked arrays quite extensively. My take on them is
>> that if a masked array makes sense in that operation, then they should still
>> work with the regular functi
On Mon, Sep 20, 2010 at 3:34 PM, Benjamin Root wrote:
> I have been using masked arrays quite extensively. My take on them is that
> if a masked array makes sense in that operation, then they should still work
> with the regular functions. However, there have been many cases where a
> developer
On Mon, Sep 20, 2010 at 3:23 PM, Gökhan Sever wrote:
> On Mon, Sep 20, 2010 at 1:05 PM, Robert Kern wrote:
>
>> Are you asking about when masked arrays are casted to ndarrays (and
>> thus losing the mask information)? Most times when a function uses
>> asarray() or array() to explicitly cast the
On Mon, Sep 20, 2010 at 3:23 PM, Gökhan Sever wrote:
> On Mon, Sep 20, 2010 at 1:05 PM, Robert Kern wrote:
>>
>> Are you asking about when masked arrays are casted to ndarrays (and
>> thus losing the mask information)? Most times when a function uses
>> asarray() or array() to explicitly cast the
On Mon, Sep 20, 2010 at 1:05 PM, Robert Kern wrote:
> Are you asking about when masked arrays are casted to ndarrays (and
> thus losing the mask information)? Most times when a function uses
> asarray() or array() to explicitly cast the inputs to an ndarray. The
> reason that np.mean() gives the
On Sun, Sep 19, 2010 at 12:19, Gökhan Sever wrote:
> Hello,
> Consider these two sets of container arrays --one defined as usual np array
> the others as ma arrays:
> all_measured = np.ma.zeros((16, 18))
> all_predicted = np.ma.zeros((16, 18))
> all_measured2 = np.zeros((16, 18))
>
On Fri, Sep 17, 2010 at 8:53 AM, Mayank P Jain wrote:
> I thought about these options but what I need is excel like interface that
> displays the values for each cell and one can modify and save the files.
>
> This would be convenient way of saving large files in less space and at the
> same time,
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