Kvazar is computational package for molecular modeling.
* There are different methods in it, such as Tight-Binding (TB), Brenner's method (Reactive empirical bond-order(REBO)), coarse-grained modeling (MARTINI force field).
* Package is written on Python2.7 and C++.
* There is a molecular dynamic method. There are different types of integrators: Leapfrog, Verlet, Velocity Verlet, Berendsen Leapfrog, Nose-Hoover Leapfrog.
* Kvazar - Free Software.
1. Kvazar can be installed on linux. Kvazar uses easy_install build system. To install package type in terminal:
python setup.py install
To build package:
python setup.py build
python setup.py test
It will run modules for testing of principal classes and raise exception, if something has broken down.
2. setup.py sets up only computational part of package. To calculate something, .cfg file must be changed accordingly. Examples of filled .cfg files are in path_to_kvazar/examples/. To start calculation:
Kvazar uses MPI interface for parallel computations. To start computing in N threads you should type something like this:
mpirun -np N kvazar config.cfg
3. Dependencies: numpy, scipy, Boost.Python, mpi4py, PyYaml.
In file boost_lib_name in Kvazar directory you must write actual name of boost.python library that depends on linux distribution you have. In Debian, for example, there should be one string in this file: boost_python-py27.
4. Documentation is made on Sphinx. To create html file of documentation, you should install Kvazar and then type:
python setup.py build_sphinx
It will build documentation in Kvazar/doc/. File to run: Kvazar/doc/build/index.html.
Package named kvazar probably will be installed in /usr/local/lib/python2.7/dist-packages/Kvazar_s_libs-0.0.1-py2.7-linux-x86_64.egg/. To delete, type:
sudo rm -r /usr/local/lib/python2.7/dist-packages/Kvazar_s_libs-0.0.1-py2.7-linux-x86_64.egg/
Or you can use:
python setup.py install --record kvazar_files.txt
And in this file you will find all names of kvazar's installed files to directly delete them.