On Jul 24, 2010, at 4:04 PM, Keith Goodman wrote:
On Sat, Jul 24, 2010 at 12:58 PM, David Cournapeau
wrote: On Sun, Jul 25, 2010 at 4:50 AM, Jonathan Tu
wrote: I am unable to find the files lapack_lite.so or _dotblas.so. I used the locate command to look for them.
If you just installed numpy, locate won't find them as locate uses a database which is usually updated once in a while.
Depending on how you installed numpy, you will find lapack_lite.so in /usr, $HOME/.local or somewhere else (and also in the build directory in the numpy source tree).
Here's one way to find where numpy is installed:
$ python
import numpy numpy
So on my computer numpy is installed in /usr/local/lib/python2.6/site-packages
_dotblas.so may not be present, but numpy cannot work without a lapack_lite.so.
Thanks for the tip! This worked, and much faster than the manual hunting through directories I'd been trying. Upon running ldd on lapack_lite.so and on _dotblas.so, I got the following (first for lapack_lite, then for _dotblas): libpthread.so.0 => /lib64/tls/libpthread.so.0 (0x0000002a95792000) libc.so.6 => /lib64/tls/libc.so.6 (0x0000002a958a7000) /lib64/ld-linux-x86-64.so.2 (0x000000552aaaa000) libpthread.so.0 => /lib64/tls/libpthread.so.0 (0x0000002a95d36000) libc.so.6 => /lib64/tls/libc.so.6 (0x0000002a95e4c000) /lib64/ld-linux-x86-64.so.2 (0x000000552aaaa000) I am interested in whether my Numpy installation is in fact taking advantage of the LAPACK libraries that are installed on the cluster where I'm running. I know that Numpy can function without such an installation, but I think it is probably faster when taking advantage of optimized libraries. In any case, I know ldd shows library dependencies, but I'm not sure how to make sense of its output, and whether or not it answers my question. Jonathan Tu