===== Libs and Tips =====

==== Speeding up Numpy and Scipy ====

[[http://software.intel.com/en-us/articles/numpyscipy-with-intel-mkl|with Intel MKL and OpenMP]]

=== Test numpy and scipy ===
<code python>
>>> import Numpy
>>> numpy.show_config()
>>> numpy.test()
>>>
>>> import scipy
>>> scipy.test()
</code>

== Which module is used? ==
To determine which python module is used, the preinstalled, the owne (user lib) or something else.
<code python>
>>> import a_module
>>> print a_module.__file__
</code>


== Installed Libs/Packages ==

!!!!Pizza.py (v. 0.1.0)
http://pizza.sandia.gov/
Pre- and post-processing capability for the LAMMPS molecular dynamics, ChemCell cell modeling, and SPPARKS kinetic Monte Carlo packages.
<code bash>
pip install Pizza.py
</code>

==== Way to Check the Way to install Python Packages ====


1. **''aptitude''**
> Check if there is a System-Package available/installed (if there is one installed you can't install/update this package. Ask your System Administrator).
> In Aptitude call the search with ''**/**''

2. **''pip''**
> Check if there is a Python-package in the pip-system available **''pip search name''** (find the fitting name in the Internet, be creative)
> Install the Package to your home directory (see above: Install Libs in a user environment)

3. Nothing in pip :(
> Find and download the python-package, uncompress it and run (hopefully) **''python setup.py install --user''**