On 2010-08-05, at 4:53 PM, Søren Gammelmark wrote:
> It seems to me, that you are using an libiomp5 for Intel Itanium
> (lib/intel64) or such, but an MKL for EM64T-processors (lib/em64t). In
> my case I used EM64T in all cases (I'm running AMD Opteron) . I don't
> think the two types of librar
On 2010-08-01, at 12:38 PM, Ralf Gommers wrote:
> I am pleased to announce the availability of the first beta of NumPy 1.5.0.
> This will be the first NumPy release to include support for Python 3, as well
> as for Python 2.7. Please try this beta and report any problems on the NumPy
> mailing
> I've been having a similar problem compiling NumPy with MKL on a cluster with
> a site-wide license. Dag's site.cfg fails to config if I use 'iomp5' in it,
> since (at least with this version, 11.1) libiomp5 is located in
>
> /scinet/gpc/intel/Compiler/11.1/072/lib/intel64/
>
> whereas t
choose might be slower if you weren't doing an "arange(N)" each time.
On Thu, Aug 5, 2010 at 1:51 PM, Keith Goodman wrote:
> On Thu, Aug 5, 2010 at 1:32 PM, wrote:
> > On Thu, Aug 5, 2010 at 4:07 PM, Martin Spacek
> wrote:
> >> josef.pkt wrote:
> > a = np.array([[0, 1],
> >>
On Thu, Aug 5, 2010 at 3:43 PM, Gökhan Sever wrote:
> Hello,
> There is a nice e-mailing trend tool for Gmail users
> at http://code.google.com/p/mail-trends/
> It is a command line tool producing an html output showing your e-mailing
> statistics. In my inbox, the following threads are highly ran
It seems to me, that you are using an libiomp5 for Intel Itanium
(lib/intel64) or such, but an MKL for EM64T-processors (lib/em64t). In
my case I used EM64T in all cases (I'm running AMD Opteron) . I don't
think the two types of libraries are compatible, but I might be wrong.
/Søren
On 05-08-
On Thu, Aug 5, 2010 at 1:32 PM, wrote:
> On Thu, Aug 5, 2010 at 4:07 PM, Martin Spacek wrote:
>> josef.pkt wrote:
> a = np.array([[0, 1],
>> [2, 3],
>> [4, 5],
>> [6, 7],
>> [8, 9]])
> i = np.array([0, 1, 1, 0, 1])
>
On 08/05/2010 03:07 PM, Martin Spacek wrote:
> josef.pkt wrote:
a = np.array([[0, 1],
> [2, 3],
> [4, 5],
> [6, 7],
> [8, 9]])
i = np.array([0, 1, 1, 0, 1])
a[range(a.shape[0]), i]
> array([0, 3, 5, 6,
On Thu, Aug 5, 2010 at 4:07 PM, Martin Spacek wrote:
> josef.pkt wrote:
a = np.array([[0, 1],
> [2, 3],
> [4, 5],
> [6, 7],
> [8, 9]])
i = np.array([0, 1, 1, 0, 1])
a[range(a.shape[0]), i]
> array([0, 3, 5, 6, 9
josef.pkt wrote:
>>> a = np.array([[0, 1],
[2, 3],
[4, 5],
[6, 7],
[8, 9]])
>>> i = np.array([0, 1, 1, 0, 1])
>>> a[range(a.shape[0]), i]
array([0, 3, 5, 6, 9])
>>> a[np.arange(a.shape[0]), i]
array([0, 3, 5, 6, 9])
Thank
Hello,
There is a nice e-mailing trend tool for Gmail users at
http://code.google.com/p/mail-trends/
It is a command line tool producing an html output showing your e-mailing
statistics. In my inbox, the following threads are highly ranked in the top
threads section.
[Numpy-discussion] Announcing
On 2010-08-03, at 4:09 PM, Pauli Virtanen wrote:
> Tue, 03 Aug 2010 15:52:55 -0400, David Warde-Farley wrote:
> [clip]
>> in PyErr_WarnEx (category=0x11eb6c54,
>>text=0x5f90c0 "PyOS_ascii_strtod and PyOS_ascii_atof are deprecated.
>> Use PyOS_string_to_double instead.", stack_level=0) at
>
On 2010-08-04, at 2:18 AM, Matthieu Brucher wrote:
> 2010/8/4 Søren Gammelmark :
>>
>>>
>>> I wouldn't know for sure, but could this be related to changes to the
>>> gcc compiler in Fedora 13 (with respect to implicit DSO linking) or
>>> would that only be an issue at build-time?
>>>
>>> http:
You may also use the choose function:
http://docs.scipy.org/doc/numpy/reference/generated/numpy.choose.html
choose(i, (a[:,0], a[:,1])
On Thu, Aug 5, 2010 at 10:31 AM, Keith Goodman wrote:
> On Thu, Aug 5, 2010 at 10:26 AM, wrote:
> > On Thu, Aug 5, 2010 at 1:12 PM, Martin Spacek
> wrote:
>
On Thu, Aug 5, 2010 at 10:26 AM, wrote:
> On Thu, Aug 5, 2010 at 1:12 PM, Martin Spacek wrote:
>> I want to take an n x m array "a" and index into it using an integer index
>> array
>> "i" of length n that will pull out the value at the designated column from
>> each
>> corresponding row of "a
On Thu, Aug 5, 2010 at 10:12 AM, Martin Spacek wrote:
> I want to take an n x m array "a" and index into it using an integer index
> array
> "i" of length n that will pull out the value at the designated column from
> each
> corresponding row of "a".
>
a = np.arange(10)
a.shape = 5, 2
On Thu, Aug 5, 2010 at 1:12 PM, Martin Spacek wrote:
> I want to take an n x m array "a" and index into it using an integer index
> array
> "i" of length n that will pull out the value at the designated column from
> each
> corresponding row of "a".
>
a = np.arange(10)
a.shape = 5, 2
>
I want to take an n x m array "a" and index into it using an integer index
array
"i" of length n that will pull out the value at the designated column from each
corresponding row of "a".
>>> a = np.arange(10)
>>> a.shape = 5, 2
>>> a
array([[0, 1],
[2, 3],
[4, 5],
[6, 7]
On Aug 5, 2010, at 8:45 AM, Ralf Gommers wrote:
> Hi all,
>
> I'm looking at what needs to be deprecated/removed and have a few questions:
>
> 1. ma.core has some deprecations without version info:
> make_mask: flag keyword
> MaskedArray.flag
> MaskedArray.raw_data
> allclose: fillval
Hi all,
I'm looking at what needs to be deprecated/removed and have a few questions:
1. ma.core has some deprecations without version info:
make_mask: flag keyword
MaskedArray.flag
MaskedArray.raw_data
allclose: fillvalue keyword
Should these be removed, and if not can someone provide a
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