On Mon, Dec 27, 2010 at 6:20 AM, Enzo Michelangeli enzom...@gmail.com 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
2010/12/7 Rajat Banerjee rban...@fas.harvard.edu:
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
On Tue, Dec 28, 2010 at 11:22 PM, Robert Bradshaw
rober...@math.washington.edu wrote:
On Tue, Dec 28, 2010 at 8:10 PM, John Salvatier
jsalv...@u.washington.edu wrote:
Wouldn't that be a cast? You do casts in Cython with double(expression)
and that should be the equivalent of float64 I think.
On Wed, Dec 29, 2010 at 9:05 AM, Keith Goodman kwgood...@gmail.com wrote:
On Tue, Dec 28, 2010 at 11:22 PM, Robert Bradshaw
rober...@math.washington.edu wrote:
On Tue, Dec 28, 2010 at 8:10 PM, John Salvatier
jsalv...@u.washington.edu wrote:
Wouldn't that be a cast? You do casts in Cython with
On Wed, Dec 29, 2010 at 9:37 AM, Robert Bradshaw
rober...@math.washington.edu wrote:
On Wed, Dec 29, 2010 at 9:05 AM, Keith Goodman kwgood...@gmail.com wrote:
On Tue, Dec 28, 2010 at 11:22 PM, Robert Bradshaw
rober...@math.washington.edu wrote:
On Tue, Dec 28, 2010 at 8:10 PM, John Salvatier
Hi,
On Wed, Dec 29, 2010 at 5:37 PM, Robert Bradshaw
rober...@math.washington.edu wrote:
On Wed, Dec 29, 2010 at 9:05 AM, Keith Goodman kwgood...@gmail.com wrote:
On Tue, Dec 28, 2010 at 11:22 PM, Robert Bradshaw
rober...@math.washington.edu wrote:
On Tue, Dec 28, 2010 at 8:10 PM, John
On Wed, Dec 29, 2010 at 9:48 AM, Matthew Brett matthew.br...@gmail.com wrote:
Hi,
On Wed, Dec 29, 2010 at 5:37 PM, Robert Bradshaw
rober...@math.washington.edu wrote:
On Wed, Dec 29, 2010 at 9:05 AM, Keith Goodman kwgood...@gmail.com wrote:
On Tue, Dec 28, 2010 at 11:22 PM, Robert Bradshaw
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 dtype
On Wed, Dec 29, 2010 at 10:13 AM, Matthew Brett matthew.br...@gmail.com 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
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
computer and my
On Wed, Dec 29, 2010 at 11:43 AM, Matthew Brett matthew.br...@gmail.com 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
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
On Wed, Dec 29, 2010 at 11:54 AM, Pauli Virtanen p...@iki.fi 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
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