Hmm,I just tried this and it took so long on my machine (Athlon64, fc5_x86_64), that I ctrl-c'd out of it. Running ldd on lapack_lite.so shows libpthread.so.0
=> /lib64/libpthread.so.0 (0x2ace2000) libc.so.6 => /lib64/libc.so.6 (0x2adfa000)
/lib64/ld-linux-x86
JJ wrote:
> Any ideas on where to look for a speedup? If the
> problem is that it could not locate the atlas
> ibraries, how might I assure that numpy finds the
> atlas libraries. I can recompile and send along the
> results if it would help.
Run ldd(1) on the file lapack_lite.so . It should s
David M. Cooke wrote:
>On Sat, Jun 10, 2006 at 01:18:05PM -0700, Tim Hochberg wrote:
>
>
>>I finally got around to cleaning up and checking in fromiter. As Travis
>>suggested, this version does not require that you specify count. From
>>the docstring:
>>
>>fromiter(...)
>>fromiter(
Hello. I am a new user to scipy, thinking about
crossing over from Matlab. I have a new AMD 64
machine and just installed fedora 5 and scipy. It is
a dual boot machine with windows XP. I did a small
test to compare the speed of matlab (in 32 bit
windows, Matlab student v14) to the speed of scip
David M. Cooke wrote:
> Can this be integrated into array() so that array(iterable, dtype=dtype)
> does the expected thing?
That was rejected early on because array() is so incredibly overloaded as it is.
http://article.gmane.org/gmane.comp.python.numeric.general/5756
--
Robert Kern
"I have c
On Sat, Jun 10, 2006 at 01:18:05PM -0700, Tim Hochberg wrote:
>
> I finally got around to cleaning up and checking in fromiter. As Travis
> suggested, this version does not require that you specify count. From
> the docstring:
>
> fromiter(...)
> fromiter(iterable, dtype, count=-1)
OK, here's another (semi-crazy) idea:
__array_struct__ is the interface. ctypes lets us use it in "pure"
Python. We provide a "reference implementation" so that newbies don't
get segfaults.
___
Numpy-discussion mailing list
Numpy-discussion@lists.sou
I finally got around to cleaning up and checking in fromiter. As Travis
suggested, this version does not require that you specify count. From
the docstring:
fromiter(...)
fromiter(iterable, dtype, count=-1) returns a new 1d array
initialized from iterable. If count is nonegative
Thanks for all the help!Convolving looks like a great way to do this, and I think that mean will be just fine for my purposes.That iterator also looks fantastic and is actually the sort of thing that I was looking for at first. I havn't tried it yet though. Any idea how fast it would be?
StephenOn
Not sure, but my Google desktop search of "medfilt" (the name of
Matlab function) brought me to:
info_signal.py - N-dimensional order filter. medfilt -N-dimensional
median filter
If it's true, then it is the 2D median filter.
Regarding the neighbouring cells, I found the iterator on 2D ranges on
On Sat, 10 Jun 2006, stephen emslie apparently wrote:
> I'm just starting with numpy (via scipy) and I'm wanting to perform
> adaptive thresholding
> (http://www.cee.hw.ac.uk/hipr/html/adpthrsh.html) on an image.
The ability to define a function on a neighborhood,
where the neighborhood is def
We believe ordering medication should be as simple as ordering anything else on
the Internet: Private, secure, and easy.
Everything is done on-line and Safe..
Click The Link Below
mediente.com
Best Regards,
Randee Erdman
mediente.com customer service
oetewlcsqv ECrHgeggQKrYdOArPhPdegiINJLCEn
Hi,
> I'm just starting with numpy (via scipy) and I'm wanting to perform
> adaptive thresholding
> (http://www.cee.hw.ac.uk/hipr/html/adpthrsh.html) on an image.
> Basically that means that I need to get a threshold for each pixel by
> examining the pixels around it. In numpy this translates to f
Hi,
> I'm just starting with numpy (via scipy) and I'm wanting to perform
> adaptive thresholding
> (http://www.cee.hw.ac.uk/hipr/html/adpthrsh.html) on an image.
> Basically that means that I need to get a threshold for each pixel by
> examining the pixels around it. In numpy this translates to f
14 matches
Mail list logo
