On 30 October 2011 21:01, Pauli Virtanen p...@iki.fi wrote:
30.10.2011 21:48, mark florisson kirjoitti:
First, I'd like to report a bug. It seems ndarray does not implement
tp_traverse or tp_clear, so if you have a reference cycle in an
ndarray with dtype object none of those objects will ever
31.10.2011 09:44, mark florisson kirjoitti:
[clip]
Ah, that's too bad. Is it anywhere near ready, or was it abandoned for
ironclad? Could you point me to the code?
It's quite ready and working, and as far as I understand, Enthought is
shipping it. I haven't used it, though.
The code is here:
Mark: I'm just wondering what you wanted to do with NumPy from Cython -- a
stopgap solution for SIMD, iterator support, or something else?
SIMD using NumPy really isn't the best idea long-term because of all the
temporaries needed in compound expressions, which is really bad on the memory
bus
This comes out of a long discussion on the Cython list. Following Mark's
success with the shared memory parallelism, the question is: Where to
take Cython's capabilities for parallelism further?
One thing that's been up now and then is that we could basically use
something like:
-
On 31 October 2011 10:03, Dag Sverre Seljebotn
d.s.seljeb...@astro.uio.no wrote:
Mark: I'm just wondering what you wanted to do with NumPy from Cython -- a
stopgap solution for SIMD, iterator support, or something else?
SIMD using NumPy really isn't the best idea long-term because of all the
On 31 October 2011 09:50, Pauli Virtanen p...@iki.fi wrote:
31.10.2011 09:44, mark florisson kirjoitti:
[clip]
Ah, that's too bad. Is it anywhere near ready, or was it abandoned for
ironclad? Could you point me to the code?
It's quite ready and working, and as far as I understand, Enthought
On 10/31/2011 11:48 AM, mark florisson wrote:
On 31 October 2011 10:03, Dag Sverre Seljebotn
d.s.seljeb...@astro.uio.no wrote:
Mark: I'm just wondering what you wanted to do with NumPy from Cython -- a
stopgap solution for SIMD, iterator support, or something else?
SIMD using NumPy really
On 10/31/2011 12:01 PM, Dag Sverre Seljebotn wrote:
On 10/31/2011 11:48 AM, mark florisson wrote:
On 31 October 2011 10:03, Dag Sverre Seljebotn
d.s.seljeb...@astro.uio.no wrote:
Mark: I'm just wondering what you wanted to do with NumPy from Cython -- a
stopgap solution for SIMD, iterator
If you google around einsum hang, it looks like this is a problem with
Intel compiler with the -O3 flag.
See this thread in particular:
http://comments.gmane.org/gmane.comp.python.numeric.general/43168
It looks like there may be more issues too...
-=- Olivier
2011/10/30 akshar bhosale
On 10/31/2011 08:31 AM, Olivier Delalleau wrote:
If you google around einsum hang, it looks like this is a problem
with Intel compiler with the -O3 flag.
See this thread in particular:
http://comments.gmane.org/gmane.comp.python.numeric.general/43168
It looks like there may be more issues
Pauli Virtanen pav at iki.fi writes:
The problem here seems to be that argsort (or only the mergesort?) for
datetime datatypes is not implemented.
There's a faster code path that is triggered for small selection arrays,
and that does not require argsort, and that's why the error occurs in
Hi,
I just ran into this confusing difference between np.float and np.float64:
In [8]: np.float(2**63) == 2**63
Out[8]: True
In [9]: np.float(2**63) 2**63-1
Out[9]: True
In [10]: np.float64(2**63) == 2**63
Out[10]: True
In [11]: np.float64(2**63) 2**63-1
Out[11]: False
In [16]:
As an example, it'd be nice to have scipy.ndimage available without the GIL:
http://docs.scipy.org/doc/scipy/reference/ndimage.html
Now, this *can* easily be done as the core is written in C++. I'm just
pointing out that some people may wish more for calling scipy.ndimage
inside their
Hello,
in Debian we're trying to define a way to handle numpy transitions
more smoothly (you can read the proposal, if interested, at
http://bugs.debian.org/643873).
In order to do that, we'd like to use the C_API_VERSION and
C_ABI_VERSION values; while for C_API_VERSION we can see it's a quite
On Mon, Oct 31, 2011 at 11:28 AM, Zachary Pincus
zachary.pin...@yale.edu wrote:
As an example, it'd be nice to have scipy.ndimage available without the GIL:
http://docs.scipy.org/doc/scipy/reference/ndimage.html
Now, this *can* easily be done as the core is written in C++. I'm just
pointing
On Mon, Oct 31, 2011 at 11:23 AM, Matthew Brett matthew.br...@gmail.com wrote:
In [8]: np.float(2**63) == 2**63
Out[8]: True
In [9]: np.float(2**63) 2**63-1
Out[9]: True
In [10]: np.float64(2**63) == 2**63
Out[10]: True
In [11]: np.float64(2**63) 2**63-1
Out[11]: False
In [16]:
Hi Sandro
On Mon, Oct 31, 2011 at 12:02 PM, Sandro Tosi mo...@debian.org wrote:
In order to do that, we'd like to use the C_API_VERSION and
C_ABI_VERSION values; while for C_API_VERSION we can see it's a quite
small value, with a clear history at
./numpy/core/code_generators/cversions.txt ,
Hi,
2011/10/31 Stéfan van der Walt ste...@sun.ac.za:
On Mon, Oct 31, 2011 at 11:23 AM, Matthew Brett matthew.br...@gmail.com
wrote:
In [8]: np.float(2**63) == 2**63
Out[8]: True
In [9]: np.float(2**63) 2**63-1
Out[9]: True
In [10]: np.float64(2**63) == 2**63
Out[10]: True
In [11]:
On Mon, Oct 31, 2011 at 6:25 PM, Matthew Brett matthew.br...@gmail.com wrote:
Oh, dear, I'm suffering now:
In [11]: res = np.array((2**31,), dtype=np.float32)
In [12]: res 2**31-1
Out[12]: array([False], dtype=bool)
OK - that's what I was expecting from the above, but now:
In [13]:
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