Hi,
This branch improves numpy import times quite significantly on slow
machines:
http://github.com/cournape/numpy/tree/noinspect
One of the main culprit is ma, because of inspect (inspect is extremely
slow to import; as a data point, python -c "import inspect" takes 67 ms
vs python -c "" ta
On Thu, Oct 8, 2009 at 9:25 PM, Travis Oliphant wrote:
>
> On Oct 8, 2009, at 7:19 AM, Travis Oliphant wrote:
>
>>
>> I just checked a fix for this into SVN (tests still need to be added
>> though...)
>>
>> I can't currently build SVN on my Mac for some reason (I don't know if
>> it has to do with
On Thu, Oct 8, 2009 at 19:32, David Warde-Farley wrote:
>
> On 8-Oct-09, at 6:47 PM, Robert Kern wrote:
>
>> On Thu, Oct 8, 2009 at 17:28, David Warde-Farley
>> wrote:
>>> I'm trying to use PyArray_FROM_OF from Cython and the generated C
>>> code
>>> keeps crashing. Dag said on the Cython list t
On 8-Oct-09, at 6:47 PM, Robert Kern wrote:
> On Thu, Oct 8, 2009 at 17:28, David Warde-Farley
> wrote:
>> I'm trying to use PyArray_FROM_OF from Cython and the generated C
>> code
>> keeps crashing. Dag said on the Cython list that he wasn't sure what
>> was going on, so maybe someone here
On Thu, Oct 8, 2009 at 17:28, David Warde-Farley wrote:
> I'm trying to use PyArray_FROM_OF from Cython and the generated C code
> keeps crashing. Dag said on the Cython list that he wasn't sure what
> was going on, so maybe someone here will have an idea.
You must call import_array() at the top
I'm trying to use PyArray_FROM_OF from Cython and the generated C code
keeps crashing. Dag said on the Cython list that he wasn't sure what
was going on, so maybe someone here will have an idea.
The line that gdb says is crashing is:
#0 0x00e48287 in __pyx_pf_3_vq_vq (__pyx_self=0x0,
__py
On Oct 8, 2009, at 12:08 PM, Michael Droettboom wrote:
Thanks! I guess I won't file a bug then ;)
Probably still should, actually: Until the tests get committed, the
bug is not really "fixed"
-Travis
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On Oct 8, 2009, at 10:01 AM, David Cournapeau wrote:
> On Thu, Oct 8, 2009 at 8:55 PM, Travis Oliphant > wrote:
>>
>> The problem I have with spending time on it though is that there is
>> still
>> more implementation work to finish on the datetime functionality to
>> complete
>> the NEP imp
Thanks! I guess I won't file a bug then ;)
Mike
Travis Oliphant wrote:
> On Oct 7, 2009, at 10:28 AM, Michael Droettboom wrote:
>
>
>> I'm noticing an inconsistency as to how complex numbers are
>> byteswapped
>> as arrays vs. scalars, and wondering if I'm doing something wrong.
>>
>>
On Thu, Oct 8, 2009 at 8:55 PM, Travis Oliphant wrote:
>
> The problem I have with spending time on it though is that there is still
> more implementation work to finish on the datetime functionality to complete
> the NEP implementation. Naturally, I'd like to see those improvements
> made fi
On Thu, Oct 8, 2009 at 8:55 PM, Travis Oliphant wrote:
>
> On Oct 7, 2009, at 9:51 PM, David Cournapeau wrote:
>
> On Thu, Oct 8, 2009 at 11:39 AM, Travis Oliphant
> wrote:
>
> I apologize for the mis communication that has occurred here.
>
> No problem
>
> I did not
>
> understand that there w
On Oct 8, 2009, at 7:19 AM, Travis Oliphant wrote:
>
> I just checked a fix for this into SVN (tests still need to be added
> though...)
>
> I can't currently build SVN on my Mac for some reason (I don't know if
> it has to do with recent changes or not, but I don't have time to
> track it down r
On Oct 7, 2009, at 10:28 AM, Michael Droettboom wrote:
> I'm noticing an inconsistency as to how complex numbers are
> byteswapped
> as arrays vs. scalars, and wondering if I'm doing something wrong.
>
x = np.array([-1j], '>>> x.tostring().encode('hex')
> '80bf'
> # This is a l
On Oct 7, 2009, at 10:28 AM, Michael Droettboom wrote:
> I'm noticing an inconsistency as to how complex numbers are
> byteswapped
> as arrays vs. scalars, and wondering if I'm doing something wrong.
>
x = np.array([-1j], '>>> x.tostring().encode('hex')
> '80bf'
> # This is a l
On Oct 7, 2009, at 9:51 PM, David Cournapeau wrote:
On Thu, Oct 8, 2009 at 11:39 AM, Travis Oliphant > wrote:
I apologize for the mis communication that has occurred here.
No problem
I did not
understand that there was a desire to keep ABI compatibility with
NumPy 1.3
when NumPy 1.4 wa
Stéfan van der Walt wrote:
> We can work on implementing that today.
>
I am working on it ATM - it is taking me longer than expected, though.
David
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