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
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 tool built
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
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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;idims[0];i++)
for(j=0;jdims[1];j++)
{
*((npy_float
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 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
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]: NotImplemented
however:
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);
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'],
dtype='|S4')
In [27]:
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:
In [25]: a
Out[25]:
array(['abc',
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
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.
?xml version=1.0 encoding=UTF-8?
!DOCTYPE language
!-- Python syntax highlightning v0.9 by Per Wigren --
!-- Python
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
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