Sorry can't really help with the numpy build, but for the "can't find
libquadmath.so.0" issue, try to locate this file on your HD, and add the
directory that contains it to your LD_LIBRARY_PATH environment variable.
-=- Olivier
2011/9/13 Thomas K Gamble
> **
>
> I am trying to upgrade my numpy
On Tue, Sep 13, 2011 at 3:43 AM, Pierre GM wrote:
>
> On Sep 13, 2011, at 01:38 , Christopher Jordan-Squire wrote:
>
>> I did some timings to see what the advantage would be, in the simplest
>> case possible, of taking multiple lines from the file to process at a
>> time. Assuming the dtype is alr
Den 12.09.2011 08:52, skrev David Froger:
Hy everybody,
I'm wondering what is the (best) way to apply the same function to multiple
arrays.
I tried to experiment a bit with this. Here is from an ipython session:
Create some arrays:
In [1]: import numpy as np
In [2]: a = np.zeros(4)
In [3]
On Tue, Sep 13, 2011 at 3:34 PM, Ralf Gommers
wrote:
> Hi Jacob,
>
> On Fri, Sep 9, 2011 at 11:57 PM, Jacob Silterra wrote:
>
>> Hello all,
>>
>> I'd like to see functions for calculating the relative extrema in a set of
>> data included in numpy. I use that functionality frequently, and always s
Hi Jacob,
On Fri, Sep 9, 2011 at 11:57 PM, Jacob Silterra wrote:
> Hello all,
>
> I'd like to see functions for calculating the relative extrema in a set of
> data included in numpy. I use that functionality frequently, and always seem
> to be writing my own version. It seems like this functiona
On Tue, Sep 13, 2011 at 2:41 PM, Chris.Barker wrote:
> On 9/12/11 4:38 PM, Christopher Jordan-Squire wrote:
>> I did some timings to see what the advantage would be, in the simplest
>> case possible, of taking multiple lines from the file to process at a
>> time.
>
> Nice work, only a minor commen
On 9/12/11 4:38 PM, Christopher Jordan-Squire wrote:
> I did some timings to see what the advantage would be, in the simplest
> case possible, of taking multiple lines from the file to process at a
> time.
Nice work, only a minor comment:
> f6 and f7 use stripped down versions of Chris
> Barker's
I am trying to upgrade my numpy installation from 1.5.1 to 1.6.1 on Ubuntu
10.04. When I build, it doesn't seem to use the installed lapack libraries,
but uses lapack_lite. After installation (which seems to complete without
error), importing numpy fails with an error that it can't find
libq
Sorry if it sounds like a stupid question, but are the files listed in the
error message present in that directory?
If yes, maybe try running the command with sudo, just in case it would be
some weird permission issue.
-=- Olivier
2011/9/13 Igor Ying
> Hi,
>
> I am very new to Numpy and tryin
I agree with Robert, don't use locals(). I should have added a disclaimer
"this is very hackish and probably not a good idea", sorry ;) (interesting
read: http://stackoverflow.com/questions/1450275/modifying-locals-in-python)
>From what you said I think what you really want is f to work in-place.
On 09/13/2011 01:53 AM, David Froger wrote:
> Thank you Olivier and Robert for your replies!
>
> Some remarks about the dictionnary solution:
>
> from numpy import *
>
> def f(arr):
> return arr + 100.
>
> arrs = {}
> arrs['a'] = array( [1,1,1] )
> arrs['b'] = array( [2,2,2] )
> arrs['c'] = a
Hi,
I am very new to Numpy and trying to build Numpy 1.6.1 with Intel MKL 10.3.6
and getting the following errors.
$python setup.py config --compiler=intel build_clib --compiler=intel build_ext
--compiler=intel install
Running from numpy source directory.F2PY Version 2
blas_opt_info:
blas_mk
On Sep 13, 2011, at 01:38 , Christopher Jordan-Squire wrote:
> I did some timings to see what the advantage would be, in the simplest
> case possible, of taking multiple lines from the file to process at a
> time. Assuming the dtype is already known. The code is attached. What
> I found was I can
On Tue, Sep 13, 2011 at 01:53, David Froger wrote:
>
> Thank you Olivier and Robert for your replies!
>
> Some remarks about the dictionnary solution:
>
> from numpy import *
>
> def f(arr):
> return arr + 100.
>
> arrs = {}
> arrs['a'] = array( [1,1,1] )
> arrs['b'] = array( [2,2,2] )
> arrs[
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