On Jul 24, 2010, at 11:39 AM, Benjamin Root wrote:
I have to wonder why this question keeps coming up. Do we need to make the
build/installation instructions on the website clearer?
Yes. I was one who asked recently. I've not seen easy_install nor pip
mentioned on the website nor
On Jul 2, 2010, at 11:33 AM, Benjamin Root wrote:
I want to do the same for the calculation of the kinetic energy:
phi|p^2|phi/2m. There is a laplacian in the volume integral which
complicates things:
K = 0.0
for i in numpy.arange(len(dx)-1):
for j in numpy.arange(len(dy)-1):
Hi All,
Sorry if this has been documented or discussed already, but my searches have
come up short. Can someone please recommend a way to setup both Cython and
Fortran extensions in a single package with numpy.distutils (or something
else)? E.g.:
from numpy.distutils.core import setup,
Hi,
I'm getting a SEGV for boolean indices to a multi-dimensional array (numpy ver
1.4.1). Is this a known problem? Code and backtrace below.
Thanks,
Geoff
import numpy
a = numpy.ones((1,1))
a[a0]
Program received signal SIGSEGV, Segmentation fault.
[Switching to Thread 182902359776 (LWP
No, and I cannot replicate it on OS X. Can you give more details about
your platform and how you built numpy?
$ uname -a
Linux login3.ranger.tacc.utexas.edu 2.6.9-78.0.22.EL_lustre_TACC #9 SMP
Wed Nov 4 16:21:54 CST 2009 x86_64 x86_64 x86_64 GNU/Linux
Python 2.6.5 built with
./configure
make
On Jun 22, 2010, at 5:13 PM, Benjamin Root wrote:
Which distro of Linux are you using? The kernel version is fairly old, but
the installation date is less than a year old. Also, what version of python
is available through Distribute?
It is CentOS, heavily customized, I am sure, for this
On Jun 22, 2010, at 7:11 PM, David wrote:
Is it better to avoid setuptools/distribute/PyPI altogether?
Yes, unless you need their features (which in the case of numpy is
mostly egg, since installing from pypi rarely works anyway).
OK, installing from source solved the problem (and so did
This does not exactly answer your question, but you can use the dtype
string representation and positional parameter to make things nicer.
For example:
a = numpy.array( [1.0, 2.0, 3.0], 'f' )
instead of
a = numpy.array( [1.0, 2.0, 3.0], dtype=numpy.float32 )
-Geoff
On Jun 25, 2009, at
If you use LaTex and Mac OSX, I recommend BibDesk:
http://bibdesk.sourceforge.net/
Quite nice, and open-source.
-Geoff
On Jun 10, 2009, at 12:23 PM, Gökhan SEVER wrote:
Hello,
I am very off-the-topic, sorry about that first, but I know most of
the people in this list are students /
On Jun 5, 2009, at 10:18 AM, josef.p...@gmail.com wrote:
I'm only using arrays for consistency, but my econometrics code is
filled with arr[np.newaxis,:] .
arr[None,:] is a lot cleaner in my opinion, especially when using
numpy as the namespace.
-Geoff
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