pytbc¶
pytbc contains Python bindings to the tree-based clustering algorithm by Vitalis and Caflisch [Vitalis2012] implemented in Campari. The algorithm is written in Fortran90 and the Python bindings allow for more flexibility and possibility of integration with other packages avoiding file-based I/O. The binding interface is generated with f90wrap to have access to derived types and then compiled with f2py.
Purpose of Module¶
The clustering algorithm published in [Vitalis2012] is a hierarchical multi-resolution clustering algorithm built on an efficient tree data structure. It is based on the Birch clustering algorithm [CIT]. pytbc wraps the basic functionality of the algorithm which can be used with the most common clustering distances.
Background Information¶
See the project page for full details.
Building and Testing¶
Installation
Up to date installation instructions can be found at https://gitlab.com/clangi/pytbc#installation
Testing and Examples
Example notebooks that leverage the package can be found at https://gitlab.com/clangi/pytbc/-/tree/master/docs/source/notebooks
Source Code¶
The source code of ``pytbc` is available on GitLab.com <https://gitlab.com/clangi/pytbc>`_.
| [Vitalis2012] | (1, 2) A. Vitalis and A. Caflisch. Efficient Construction of Mesostate Networks from Molecular Dynamics Trajectories. J. Chem. Theory Comput. 8 (3), 1108-1120 (2012) DOI |