On Wed, Dec 29, 2010 at 11:54 AM, Pauli Virtanen wrote:
> Keith Goodman wrote:
>> np.float64 is fast, just hoping someone had a C-API inline version of
>> np.float64() that is faster.
>
> You're looking for PyArrayScalar_New and _ASSIGN.
> See
> https://github.com/numpy/numpy/blob/master/numpy/co
Keith Goodman wrote:
> np.float64 is fast, just hoping someone had a C-API inline version of
> np.float64() that is faster.
You're looking for PyArrayScalar_New and _ASSIGN.
See
https://github.com/numpy/numpy/blob/master/numpy/core/include/numpy/arrayscalars.h
Undocumented (bad), but AFAIK publi
On Wed, Dec 29, 2010 at 11:43 AM, Matthew Brett wrote:
> Hi,
>
>>> That might be because I'm not understanding you very well, but I was
>>> thinking that:
>>>
>>> cdef dtype descr = PyArray_DescrFromType(NPY_FLOAT64)
>>>
>>> would give you the float64 dtype that I thought you wanted? I'm
>>> shoo
Hi,
>> That might be because I'm not understanding you very well, but I was
>> thinking that:
>>
>> cdef dtype descr = PyArray_DescrFromType(NPY_FLOAT64)
>>
>> would give you the float64 dtype that I thought you wanted? I'm
>> shooting from the hip here, in between nieces competing for the
>> com
On Wed, Dec 29, 2010 at 10:13 AM, Matthew Brett wrote:
>>> Forgive me if I haven't understood your question, but can you use
>>> PyArray_DescrFromType with e.g NPY_FLOAT64 ?
>>
>> I'm pretty hopeless here. I don't know how to put all that together in
>> a function.
>
> That might be because I'm n
>> Forgive me if I haven't understood your question, but can you use
>> PyArray_DescrFromType with e.g NPY_FLOAT64 ?
>
> I'm pretty hopeless here. I don't know how to put all that together in
> a function.
That might be because I'm not understanding you very well, but I was
thinking that:
cdef d
On Wed, Dec 29, 2010 at 9:48 AM, Matthew Brett wrote:
> Hi,
>
> On Wed, Dec 29, 2010 at 5:37 PM, Robert Bradshaw
> wrote:
>> On Wed, Dec 29, 2010 at 9:05 AM, Keith Goodman wrote:
>>> On Tue, Dec 28, 2010 at 11:22 PM, Robert Bradshaw
>>> wrote:
On Tue, Dec 28, 2010 at 8:10 PM, John Salvatie
Hi,
On Wed, Dec 29, 2010 at 5:37 PM, Robert Bradshaw
wrote:
> On Wed, Dec 29, 2010 at 9:05 AM, Keith Goodman wrote:
>> On Tue, Dec 28, 2010 at 11:22 PM, Robert Bradshaw
>> wrote:
>>> On Tue, Dec 28, 2010 at 8:10 PM, John Salvatier
>>> wrote:
Wouldn't that be a cast? You do casts in Cython
On Wed, Dec 29, 2010 at 9:37 AM, Robert Bradshaw
wrote:
> On Wed, Dec 29, 2010 at 9:05 AM, Keith Goodman wrote:
>> On Tue, Dec 28, 2010 at 11:22 PM, Robert Bradshaw
>> wrote:
>>> On Tue, Dec 28, 2010 at 8:10 PM, John Salvatier
>>> wrote:
Wouldn't that be a cast? You do casts in Cython with
On Wed, Dec 29, 2010 at 9:05 AM, Keith Goodman wrote:
> On Tue, Dec 28, 2010 at 11:22 PM, Robert Bradshaw
> wrote:
>> On Tue, Dec 28, 2010 at 8:10 PM, John Salvatier
>> wrote:
>>> Wouldn't that be a cast? You do casts in Cython with (expression)
>>> and that should be the equivalent of float64 I
On Tue, Dec 28, 2010 at 11:22 PM, Robert Bradshaw
wrote:
> On Tue, Dec 28, 2010 at 8:10 PM, John Salvatier
> wrote:
>> Wouldn't that be a cast? You do casts in Cython with (expression)
>> and that should be the equivalent of float64 I think.
>
> Or even (expression) if you've cimported numpy
> (t
2010/12/7 Rajat Banerjee :
> Hi All,
> I have been using Numpy for a while with great success. I left my
> little project for a little while
> (http://web.mit.edu/stardev/cluster/) and now some of my code is
> broken.
>
> I have some Numpy code to create graphs of activity on a cluster with
> matpl
On Mon, Dec 27, 2010 at 6:20 AM, Enzo Michelangeli wrote:
> Many thanks to Josef and Justin for their replies.
>
> Josef's hint sounds like a good way of reducing peak memory allocation
> especially when the row size is large, which makes the "for" overhead for
> each iteration comparatively lower
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