Thank you Olsen,
My objective was to find out, how many values
are falling under different ranges. ie, find RMS < ,5 and then rms between .5
and .8 etc. If there is a speficic python way of handling mask and making
boolean operation with out any doubt, I was look
On Fri, Mar 14, 2014 at 1:43 AM, alex wrote:
>
> I think everyone who wants fast numpy linalg already connects to
> something like OpenBLAS or MKL. When these are not available, numpy
> uses its own "lapack-lite" which is way slower. I don't think you are
> going to beat OpenBLAS, so are you sug
The difference appears to be that the boolean selection pulls out all data
values <= 0.5 whether or not they are masked, and then carries over the
appropriate masks to the new array. So r2010 and bt contain identical
unmasked values but different numbers of masked values. Because the
initial fill
Sorry,
The below solution I thoght working was not working but was just
giving array size.
On Fri, 14/3/14, Sudheer Joseph wrote:
Subject: Re: [Numpy-discussion] python array
To: "Discussion of Numerical Python"
Date: Friday, 14 March,
Thank you very much Nicolas and Chris,
The hint was helpful and from that I treid below
steps ( a crude way I would say) and getting same result now
I have been using abs available by default and it is the same with
numpy.absolute( i checked).
nr= ((r2010>r2010.min(
On Mar 13, 2014, at 9:39 AM, Nicolas Rougier wrote:
>
> Seems to be related to the masked values:
Good hint -- a masked array keeps the "junk" values in the main array.
What "abs" are you using -- it may not be mask-aware. ( you want a
numpy abs anyway)
Also -- I'm not sure I know what happens
On Thu, Mar 13, 2014 at 1:35 PM, Leo Mao wrote:
>>
> And I found that maybe I can also make some functions related to linalg
> (like dot, svd or something else) faster by integrating a proper library
> into numpy.
I think everyone who wants fast numpy linalg already connects to
something like Ope
Hi,
Thanks a lot for your advice, Chuck.
Following your advice, I have modified my draft of proposal. (attachment)
I think it still needs more comments so that I can make it better.
And I found that maybe I can also make some functions related to linalg
(like dot, svd or something else) faster by
On Thu, Mar 13, 2014 at 5:18 PM, Charles R Harris
wrote:
>
> On Thu, Mar 13, 2014 at 11:08 AM, Robert Kern wrote:
>>
>> On Thu, Mar 13, 2014 at 5:02 PM, Charles R Harris
>> wrote:
>> > Hi All,
>> >
>> > In a note on a PR, Ralf has suggested the removal of doc/numpybook. I
>> > believe most of th
On Thu, Mar 13, 2014 at 11:08 AM, Robert Kern wrote:
> On Thu, Mar 13, 2014 at 5:02 PM, Charles R Harris
> wrote:
> > Hi All,
> >
> > In a note on a PR, Ralf has suggested the removal of doc/numpybook. I
> > believe most of the content is now part of the numpy documentation, and
> the
> > book i
On Thu, Mar 13, 2014 at 5:02 PM, Charles R Harris
wrote:
> Hi All,
>
> In a note on a PR, Ralf has suggested the removal of doc/numpybook. I
> believe most of the content is now part of the numpy documentation, and the
> book itself is outdated in some parts.
Sounds reasonable. It would be good t
Hi All,
In a note on a PR, Ralf has suggested the removal of doc/numpybook. I
believe most of the content is now part of the numpy documentation, and the
book itself is outdated in some parts.
Thoughts?
Chuck
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Seems to be related to the masked values:
print r2010[:3,:3]
[[-- -- --]
[-- -- --]
[-- -- --]]
print abs(r2010)[:3,:3]
[[-- -- --]
[-- -- --]
[-- -- --]]
print r2010[ r2010[:3,:3] <0 ]
[-- -- -- -- -- -- -- -- --]
print r2010[ abs(r2010)[:3,:3] < 0]
[]
Nicolas
On 13 Mar 2014, at 16:5
Hello All!
I am pleased to announce that *SciPy 2014*, the thirteenth annual *Scientific
Computing with Python conference*, will be held this July 6th-12th in
Austin, Texas. SciPy is a community dedicated to the advancement of
scientific computing through open source Python software for mathematic
I have been working on a general function caching mechanism, and in doing
so I stumbled upon the following quirck:
@cached
def foo(a,b):
b[0] = 1
return a[0]
a = np.zeros(1)
b = a[:]
print foo(a, b)#computes and returns 1
print foo(a, b)#gets 1 fro
On Mon, Mar 10, 2014 at 10:45 PM, Ralf Gommers wrote:
> Hi GSoC students,
>
> The PSF just made their application template for this year available:
> https://wiki.python.org/moin/SummerOfCode/ApplicationTemplate2014. There
> are a few things in there that are required (for one, submit a patch to
>
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