Hi
The plain gcc (non-llvm) is no longer there, if you install Lion and directly
Xcode 4.3.
Only, if you have the old Xcode 4.2 or lower, then you may have a non-llvm gcc.
For Xcode 4.3, I recommend installing the "Command Line Tools for Xcode" from
the preferences of Xcode. Then you'll have th
On 17.02.2012, at 21:46, Ralf Gommers wrote:
> [...]
> So far no one has managed to build the numpy/scipy combo with the LLVM-based
> compilers, so if you were willing to have a go at fixing that it would be
> hugely appreciated. See http://projects.scipy.org/scipy/ticket/1500 for
> details.
>
Wow, I wasn't aware of that even if I work with numpy for years now.
NumPy is amazing.
Samuel
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Hi!
Your Machine should be able to handle at least Mac OS X10.6 and even 10.7.
If there is not a strong reason to remain on 10.5...
10.5 is so long ago, I can barely remember.
cheers,
Samuel
On 01.02.2012, at 18:03, Dustin Lang wrote:
>
> Hi,
>
> I don't really believe this is a numpy bug t
Hi Ruby,
I still do not fully understand your question but what I do in such cases is to
construct a very simple array and test the functions.
The help of numpy.histogram2d or numpy.histogramdd (for more than two dims)
might help here.
So I guess, basically you want to ignore the x,y positions
Hi Hans-Martin!
You could try my instructions recently posted to this list
http://thread.gmane.org/gmane.comp.python.scientific.devel/15956/
Basically, using llvm-gcc scipy segfaults when scipy.test() (on my system at
least).
Therefore, I created the homebrew install formula.
They work for wha
Yes, I agree 100%.
On 26.01.2012, at 10:19, Sturla Molden wrote:
> When we have nice libraries like OpenCL, OpenGL and OpenMP, I am so glad
> we have Microsoft to screw it up.
>
> Congratulations to Redmond: Another C++ API I cannot read, and a
> scientific compute library I hopefully never hav
Sorry for the late answer. But at least for the record:
If you are using eclipse, I assume you have also installed the eclipse plugin
[pydev](http://pydev.org/). Is use it myself, it's good.
Then you have to go to the preferences->pydev->PythonInterpreter and select the
python version you want
I know you wrote that you want "TEXT" files, but never-the-less, I'd like to
point to http://code.google.com/p/h5py/ .
There are viewers for hdf5 and it is stable and widely used.
Samuel
On 24.01.2012, at 00:26, Emmanuel Mayssat wrote:
> After having saved data, I need to know/remember the da
I get the same results as you, Kathy.
*surprised*
(On OS X (Lion), 64 bit, numpy 2.0.0.dev-55472ca, Python 2.7.2.
On 24.01.2012, at 16:29, Kathleen M Tacina wrote:
> I was experimenting with np.min_scalar_type to make sure it worked as
> expected, and found some unexpected results for integers
On 23.01.2012, at 11:23, David Warde-Farley wrote:
>> a = numpy.array(numpy.random.randint(256,size=(500,972)),dtype='uint8')
>> b = numpy.random.randint(500,size=(4993210,))
>> c = a[b]
>> In [14]: c[100:].sum()
>> Out[14]: 0
Same here.
Python 2.7.2, 64bit, Mac OS X (Lion), 8GB RAM,
I'd like to add
http://git.tiker.net/pyopencl.git/blob/HEAD:/examples/demo_mandelbrot.py to the
discussion, since I use pyopencl (http://mathema.tician.de/software/pyopencl)
with great success in my daily scientific computing. Install with pip.
PyOpenCL does understand numpy arrays. You write
[sorry for duplicate - I used the wrong mail address]
I am afraid, I didn't quite get the question.
What is the scenario? What is the benefit that would weight out the performance
hit of checking whether there is a callback or not. This has to be evaluated
quite a lot.
Oh well ... and 1.3.0 is
I would just use a lookup dict:
names = [ "uc_berkeley", "stanford", "uiuc", "google", "intel",
"texas_instruments", "bool"]
lookup = dict( zip( range(len(names)), names ) )
Now, given you have n entries:
S = numpy.zeros( (n, len(names)) ,dtype=numpy.int32)
for k in ["uc_berkeley", "google",
I just learned two things:
1. np.newaxis
2. Array dimension broadcasting rocks more than you think.
The x[:, np.newaxis] might not be the most intuitive solution but it's great
and powerful.
Intuitive would be to have x.T to transform [0,1,2,4] into [[0],[1],[2],[4]].
Thanks Warren :-)
Samuel
import numpy
# Say y is
y = numpy.array([1,2,3])
Y = numpy.vstack([y,y,y,y])
# Y is array([[1, 2, 3],
# [1, 2, 3],
# [1, 2, 3],
# [1, 2, 3]])
x = numpy.array([[0],[2],[4],[6]]) # a column-vector of your scalars x0, x1...
Y - x
Hope this is what you meant.
cheers,
Sa
Hi!
On 20.09.2011, at 14:41, David Cournapeau wrote:
> On Tue, Sep 20, 2011 at 5:13 AM, Samuel John wrote:
>> Ralf, thanks for your answer.
>>
>> However, in short:
>>
>> I want `pip install numpy; pip install scipy` to work on OS X Lion without
>> extr
Ralf, thanks for your answer.
However, in short:
I want `pip install numpy; pip install scipy` to work on OS X Lion without
extra effort :-)
On 19.09.2011, at 19:05, Ralf Gommers wrote:
> Do you think it's possible to teach numpy to use different CC, CXX?
>
>> This is possible, but numpy pro
Ahoy numpy gurus :-)
Would it be possible to adapt the setup.py and/or numpy/distutils to set the
right variables on Mac OS X 10.7? (see below).
I have looked a bit into the setup.py and the distutils package of numpy but I
am a bit lost.
Do you think it's possible to teach numpy to use differe
Hi Nicolas,
that looks great.
Could you make this available such that `pip install glumpy` would work?
cheers,
Samuel
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middle is returned.
>
> If there are two adjacent elements with the same value,
> one of them is returned.
>
> x[0] and x[-1] are never returned as an index for the
> local maximum.
>
> @Author: Samuel John
> @copyright:
Hi Nils,
which version of numpy, which os?
I can infer that you use python 2.6 in 64bit, right?
Right after the beginning of the numpy.test() are some crucial information.
bests
Samuel
On 14.09.2011, at 22:09, Nils Wagner wrote:
> ERROR: test_polyfit (test_polynomial.TestDocs)
> -
On 06.09.2011, at 22:13, David Cottrell wrote:
> Thanks, I didn't realize dot was not just calling dgemm or some
> variant which I assume would be reasonably fast. I see dgemm appears
> in the numpy code in various places such as the lapack_lite module.
>
> I ran the svd test on the solaris setu
Thanks Robin,
that makes sense and explains why I could not find any reference.
Perhaps the scipy.org wiki and install instructions should be updated.
I mean how many people try to compile amd and umfpack, because they
think it's good for numpy to have them, because the site.cfg contains
those en
Ping.
How to tell, if numpy successfully build against libamd.a and libumfpack.a?
How do I know if they were successfully linked (statically)?
Is it possible from within numpy, like show_config() ?
I think show_config() has no information about these in it :-(
Anybody?
Thanks,
Samuel
__
Hi Paul,
thanks for your answer! I was not aware of numpy.show_config().
However, it does not say anything about libamd.a and libumfpack.a, right?
How do I know if they were successfully linked (statically)?
Does anybody have a clue?
greetings
Samuel
the fftw3 is no longer supported, I guess (even if it is still
mentioned in the site.cfg.example)
Bests,
Samuel
--
Dipl.-Inform. Samuel John
- - - - - - - - - - - - - - - - - - - - - - - - -
PhD student, CoR-Lab(.de) and
Neuroinformatics Group, Faculty
of Technology, D33594 Bielefeld
in cooperat
Perhaps related tickets, but no perfect match (as far as I can judge):
- http://projects.scipy.org/numpy/ticket/1399 "distutils fails to build ppc64
support on Mac OS X when requested"
This revision is older than the one I used, ergo should already be applied.
- http://projects.scipy.org
Hello!
At first, I'd like to say thanks to the numpy/scipy team and all contributors.
Great software!
On Snow Leopard, aka Mac OS X 10.6.4 (server) I managed to build numpy
2.0.0.dev8636 (and scipy 0.9.0.dev6646) for arch i386 in combined 32/64bit
against MacPorts python27 (No ppc here!).
All
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