On 9/1/2013 9:54 AM, Charles R Harris wrote:
> Hi all,
>
> I'm happy to announce the first beta release of Numpy 1.8.0. Please try
> this beta and report any issues on the numpy-dev mailing list.
>
> Source tarballs and release notes can be found at
> https://sourceforge.net/projects/numpy/files/Nu
On Wed, Sep 4, 2013 at 5:05 PM, Orion Poplawski wrote:
> On 09/01/2013 10:54 AM, Charles R Harris wrote:
> > Hi all,
> >
> > I'm happy to announce the first beta release of Numpy 1.8.0. Please try
> this
> > beta and report any issues on the numpy-dev mailing list.
> >
> > Source tarballs and rel
On 09/01/2013 10:54 AM, Charles R Harris wrote:
> Hi all,
>
> I'm happy to announce the first beta release of Numpy 1.8.0. Please try this
> beta and report any issues on the numpy-dev mailing list.
>
> Source tarballs and release notes can be found at
> https://sourceforge.net/projects/numpy/files
On Wed, Sep 4, 2013 at 3:17 PM, Josè Luis Mietta <
joseluismie...@yahoo.com.ar> wrote:
>
> Hi experts!
>
> If I do:
>
> G = Graph(M)
>
> That is: to use the associated intersection graph, where the vertices are
the sticks and there is an edge between the two vertices if they intersect.
Two sticks a
On Tue, Sep 3, 2013 at 6:24 PM, Christoph Gohlke wrote:
>
> The 32 bit build fails two tests (unrelated to the above 64 bit issue):
>
> ==
> FAIL: test_invalid (test_errstate.TestErrstate)
> --
There do exist numpy c functions that call .py file routines. I don't know
how likely you are to find them in practice, but it definitely happens.
You don't need .py files if you have .pyc files, and those can be
compressed (python can import directly from .zip files).
-n
On 4 Sep 2013 18:52, "Fr
Hi,
I have done some exploratory work with Theano to generate a shared library
from a Theano function. This link with numpy c api. If we want to
distribute this library and call it from C and/or python, what is the
minimal installed part of NumPy needed? I suppose that only the c api is
needed. Do
On 04.09.2013 12:05, Graeme B. Bell wrote:
> In my current GIS raster work I often have a situation where I generate code
> something like this:
>
> np.any([A>4, A==2, B==5, ...])
>
> However, np.any() is quite slow.
>
> It's possible to use np.logical_or to solve the problem, but the
Announcing HDF5 for Python (h5py) 2.2.0
===
We are proud to announce that HDF5 for Python 2.2.0 is now available.
Thanks to everyone who helped put together this release!
The h5py package is a Pythonic interface to the HDF5 binary data format.
It lets you stor
On Wed, Sep 4, 2013 at 1:14 PM, Graeme B. Bell
wrote:
>
> Sorry, I should have been more clear.
>
> As shown in the benchmark/example, the method is replacing the behaviour
of
>
>np.any(inputs, 0)
>
> not the behaviour of
>
>np.any(inputs)
reduce(np.logical_or, inputs, False)
reduce(np.lo
For the record, I started a discussion about 6 months ago about a
"find_first" type function which avoided running the logic over the whole
array (using lambdas instead). This spilled into a discussion about
implementing a short-cutted "any" or "all" function:
http://numpy-discussion.10968.n7.nabbl
Hi All,
I'd like to make a 1.8.0b2 this weekend to take care of the error cascade
on 64 bit windows. If you have any fixes/bugs you would like to see in that
beta now is the time to get the PRs in.
Chuck
___
NumPy-Discussion mailing list
NumPy-Discussio
Hi experts!
If I do:
G =Graph(M)
That is: to use the associated intersection graph, where the vertices are the
sticks and there is an edge between the two
vertices if they intersect. Two sticks are "connected by a
'intersected-stick' path" if they are in the same connected component of this
David Cournapeau wrote:
> On Wed, Sep 4, 2013 at 1:00 PM, Neal Becker wrote:
>
>> Failed building on fedora 19 x86_64 using atlas:
>>
>> creating build/temp.linux-x86_64-2.7/numpy/linalg
>> creating build/temp.linux-x86_64-2.7/numpy/linalg/lapack_lite
>> compile options: '-DATLAS_INFO="\"3.8.4\"
On Wed, Sep 4, 2013 at 1:00 PM, Neal Becker wrote:
> Failed building on fedora 19 x86_64 using atlas:
>
> creating build/temp.linux-x86_64-2.7/numpy/linalg
> creating build/temp.linux-x86_64-2.7/numpy/linalg/lapack_lite
> compile options: '-DATLAS_INFO="\"3.8.4\"" -I/usr/include
> -Inumpy/core/in
Sorry, I should have been more clear.
As shown in the benchmark/example, the method is replacing the behaviour of
np.any(inputs, 0)
not the behaviour of
np.any(inputs)
Here, where I'm making decisions based on overlaying layers of raster data in
the same shape, I don't want to map the
Built on fedora linux 19 x86_64 using mkl:
build OK using:
env ATLAS=/usr/lib64 FFTW=/usr/lib64 BLAS=/usr/lib64 LAPACK=/usr/lib64
CFLAGS="-mtune=native -march=native -O3" LDFLAGS="-Wl,-
rpath=/opt/intel/mkl/lib/intel64" python setup.py build
and attached site.cfg:
==
Failed building on fedora 19 x86_64 using atlas:
creating build/temp.linux-x86_64-2.7/numpy/linalg
creating build/temp.linux-x86_64-2.7/numpy/linalg/lapack_lite
compile options: '-DATLAS_INFO="\"3.8.4\"" -I/usr/include -Inumpy/core/include -
Ibuild/src.linux-x86_64-2.7/numpy/core/include/numpy -In
On Wed, Sep 4, 2013 at 11:05 AM, Graeme B. Bell
wrote:
>
> In my current GIS raster work I often have a situation where I generate
code something like this:
>
> np.any([A>4, A==2, B==5, ...])
>
> However, np.any() is quite slow.
>
> It's possible to use np.logical_or to solve the problem,
In my current GIS raster work I often have a situation where I generate code
something like this:
np.any([A>4, A==2, B==5, ...])
However, np.any() is quite slow.
It's possible to use np.logical_or to solve the problem, but then you get
nested logical_or's, since logical_or combines o
@Stéfan: the 'np.all' calls are now unnecessary on line 26
@Stéfan, Robert: Is it worth to bring this solution into numpy? I mean
it's probably not a rare problem, and now users have to bring this
snippet into their codebase.
Gregorio
2013/9/3 Stéfan van der Walt :
> On Tue, Sep 3, 2013 at 2:47
21 matches
Mail list logo
