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


Up to date installation instructions can be found at

Testing and Examples

Example notebooks that leverage the package can be found at

Source Code

The source code of ``pytbc` is available on <>`_.

[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