Lisandro Dalcin skrev:
> Is there any specific naming convention for these XML files to work
> with KATE? Would it be fine to call it 'cython-mode-kate.xml' to push
> it to the repo? Will it still work (I mean, with that name) when
> placed appropriately in KATE config dirs or whatever? ... Just
>
Sturla Molden skrev:
and "Cython with NumPy" shows up under Sources. Anyway, this is the
syntax high-lighter I use to write Cython.
It seems I posted the wrong file. :-(
S.M.
as
cimport
import
from
Here is an XML for Cython syntax highlighting in katepart (e.g. KATE and
KDevelop). I made this because KATE is my faviourite text edior (feel
free to call me a heretic for not using emacs). Unfortunately, the
Python highlighting for KDE contains several bugs. And the Pyrex/Cython
version that
Travis Oliphant wrote:
> On Oct 27, 2009, at 2:31 PM, Michael Droettboom wrote:
>
>
>> Christopher Barker wrote:
>>
>>> Nadav Horesh wrote:
>>>
>>>
np.equal(a,a).sum(0)
but, for unknown reason, np.equal operates only on "normal" arrays.
>>> true:
>>>
On Oct 27, 2009, at 2:31 PM, Michael Droettboom wrote:
> Christopher Barker wrote:
>> Nadav Horesh wrote:
>>
>>> np.equal(a,a).sum(0)
>>>
>>> but, for unknown reason, np.equal operates only on "normal" arrays.
>>>
>>
>> true:
>>
>> In [25]: a
>> Out[25]:
>> array(['abc', 'def', 'abc', 'ghij'],
>>
On Oct 26, 2009, at 9:54 AM, Eli Bressert wrote:
Hi Everyone,
Is Numpy supposed to behave this like this when converting an array of
numbers to an array of strings with astype?
In general you have to tell NumPy how big the string should be (i.e.
np.str is generic).
There are a few places
On Oct 27, 2009, at 7:43 AM, Raspaud Martin wrote:
-BEGIN PGP SIGNED MESSAGE-
Hash: SHA1
Hello,
I’m using numpy v1.2.0, and I have the following codes that provide
different results :
- -
cal = (PyArrayObject *)PyArray_SimpleNew(2,dims,NPY_FLOAT);
for(i=0;iAs you
Christopher Barker wrote:
> Nadav Horesh wrote:
>
>> np.equal(a,a).sum(0)
>>
>> but, for unknown reason, np.equal operates only on "normal" arrays.
>>
>
> true:
>
> In [25]: a
> Out[25]:
> array(['abc', 'def', 'abc', 'ghij'],
>dtype='|S4')
>
> In [27]: np.equal(a,a)
> Out[27]: NotIm
On Oct 27, 2009, at 7:56 AM, Gökhan Sever wrote:
>
>
> Unfortunately, matplotlib.mlab's prctile cannot handle this division:
Actually, the division's OK, it's mlab.prctile which is borked. It
uses the length of the input array instead of its count to compute the
nb of valid data. The easiest
Nadav Horesh wrote:
> np.equal(a,a).sum(0)
>
> but, for unknown reason, np.equal operates only on "normal" arrays.
true:
In [25]: a
Out[25]:
array(['abc', 'def', 'abc', 'ghij'],
dtype='|S4')
In [27]: np.equal(a,a)
Out[27]: NotImplemented
however:
In [28]: a == a
Out[28]: array([ True,
On Tue, Oct 27, 2009 at 7:56 AM, Gökhan Sever wrote:
> Hello,
>
> Consider this sample two columns of data:
>
> 99. 99.
> 99. 99.
> 99. 99.
> 99. 1693.9069
> 99. 1676.1059
> 99. 1621.5875
> 651.8040 1542.
-BEGIN PGP SIGNED MESSAGE-
Hash: SHA1
Hello,
I’m using numpy v1.2.0, and I have the following codes that provide
different results :
- -
cal = (PyArrayObject *)PyArray_SimpleNew(2,dims,NPY_FLOAT);
for(i=0;ihttp://enigmail.mozdev.org/
iQEcBAEBAgAGBQJK5usJAAoJEBdvyODiy
Hello,
Consider this sample two columns of data:
99. 99.
99. 99.
99. 99.
99. 1693.9069
99. 1676.1059
99. 1621.5875
651.8040 1542.1373
691.0138 1650.4214
678.5558 1710.7311
621.577
On 10/27/2009 05:11 AM, Pauli Virtanen wrote:
> Mon, 26 Oct 2009 14:26:20 -0400, Michael Droettboom wrote:
>
>> I know David Cournapeau has done some work on using gcov for coverage
>> with Numpy.
>>
>> Unaware of this, (doh! -- I should have Googled first), I wrote a small
>> C code-coverage t
Mon, 26 Oct 2009 14:26:20 -0400, Michael Droettboom wrote:
> I know David Cournapeau has done some work on using gcov for coverage
> with Numpy.
>
> Unaware of this, (doh! -- I should have Googled first), I wrote a small
> C code-coverage tool built on top of valgrind's callgrind tool, so it
> bas
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