Ahhh I see this is due to the ABI change, sorry for the noise.
Cheers
Adam
On Mon, Feb 15, 2010 at 21:00, Adam Mercer ramer...@gmail.com wrote:
Hi
According to the NumPy download page
http://sourceforge.net/projects/numpy/files/ the latest available
version is 1.3.0, what happened to 1.4.0
On Wed, Jun 10, 2009 at 12:44, Samir Unnisru...@gmail.com wrote:
I'm trying to use F2PY on Mac OS 10.5 with G95, but I'm getting the
error g95: unrecognized option '-shared'. I tried modifying the
NumPy code to use the correct -dynamic flag, rather than the
-shared flag. While that does allow
On Wed, Jun 10, 2009 at 15:04, Samir Unnisru...@gmail.com wrote:
Are you sure? When I run f2py -c --help-fcompiler, I get:
List of available Fortran compilers:
--fcompiler=g95 G95 Fortran Compiler (0.91)
G95 is the only compiler listed as available. If it can't be used,
then what can? I
On Wed, Jun 10, 2009 at 15:19, Samir Unnisru...@gmail.com wrote:
That's odd. You're running Mac OS 10.5.7? Did you install NumPy
manually or via Fink?
Yep Intel 10.5.7, installed from MacPorts.
Cheers
Adam
___
Numpy-discussion mailing list
On Fri, Jun 5, 2009 at 06:09, David Cournapeaucourn...@gmail.com wrote:
Please test it ! I am particularly interested in results for scipy
binaries on mac os x (do they work on ppc).
Test suite passes on Intel Mac OS X (10.5.7) built from source:
OK (KNOWNFAIL=6, SKIP=21)
On Sun, Dec 7, 2008 at 23:42, David Cournapeau
[EMAIL PROTECTED] wrote:
I am strongly against dropping 2.4 support anytime soon. I haven't seen
a strong rationale for using = 2.5 features in numpy, supporting 2.4 is
not so hard, and 2.4 is still the default python version on many OS (mac
os X
Hi
If I specify a fortran compiler when building numpy, does that have
any effect on what is installed? In other words, must I build numpy
against a fortran compiler in order to successfully build and use
extension written in fortran - such as scipy?
Cheers
Adam
On Fri, Jun 20, 2008 at 4:38 PM, Robert Kern [EMAIL PROTECTED] wrote:
No. It just affects the Fortran compiler (if any) used to build numpy.
The only place this might affect you is if you use a LAPACK or BLAS
that needs to be linked with a Fortran compiler. Generally, you don't
have to
On Dec 31, 2007 10:43 PM, Jarrod Millman [EMAIL PROTECTED] wrote:
Hey,
I just wanted to announce that we now have a NumPy/SciPy blog
aggregator thanks to Gaël Varoquaux: http://planet.scipy.org/
When I try to load http://planet.scipy.org I get an error saying that
the page doesn't exist,
On 11/10/2007, Robert Kern [EMAIL PROTECTED] wrote:
Appending to a list then converting the list to an array is the most
straightforward way to do it. If the performance of this isn't a problem, I
recommend leaving it alone.
Thanks, I'll leave it as is - I was just wondering if there was a
On 11/10/2007, Mark Janikas [EMAIL PROTECTED] wrote:
If you do not know the size of your array before you finalize it, then
you should use lists whenever you can. I just cooked up a short
example:
snip
# Result #
Total Time with array: 2.12951189331
Total Time with list:
Hi
In some code I have, I need to append some extra data to a given
array. At the moment I construct the data in a list, append the extra
information I need and then convert the final list to an array. Is
there a way that I can append extra information to an existing array
thereby negating the
On 08/10/2007, Ryan May [EMAIL PROTECTED] wrote:
Why not use numpy.fromstring?
because that results in the array being filled with gibberish
values = numpy.fromstring(wavearray, dtype=float, count=-1, sep='')
print values
gives:
[ 1.39804329e-076 1.30354290e-076 1.18295070e-076 ...,
On 08/10/2007, Robert Kern [EMAIL PROTECTED] wrote:
Use sep=' '. As the docstring says, if sep is empty, then the string is
interpreted as binary data. If it is not empty, then the string is interpreted
as ASCII.
Thanks, got it the wrong way round. That works now.
Cheers
Adam
Hi
I am fairly new to using numpy and am running into a problem regarding
the type of an array. The array in question is created using the
following code:
values = array(wavearray.split())
where wavearray is a string containing a series of floats separated by
white space, it appears that the
On 07/10/2007, Gary Ruben [EMAIL PROTECTED] wrote:
Try using astype. This works:
values = array(wavearray.split()).astype(float)
Thanks Gary, that does the trick.
Cheers
Adam
___
Numpy-discussion mailing list
Numpy-discussion@scipy.org
16 matches
Mail list logo
