classomfier 0.1

ClasSOMfier: A neural network for cluster analysis and detection of lattice defects

ClasSOMfier: A neural network for cluster analysis and detection of lattice defects

Class that classifies atoms according to their environment. Unsupervised training using a 1-dimensional Self Organizing Map (SOM) in Fortran.

Created by Javier F. Troncoso, October 2020. Contact: [e-mail]

USE:

The network and its parameters can be initialized using the following commans:
    >>nn=ClasSOMfier(6.43718,2,"dump1000.file")
Only 3 parameters are necessary: characteristic length, number of clusters and input file.
The format of the input file is that provided by the dump command in LAMMPS:
    #compute         peratom all pe/atom
    #dump            dumpid2 all custom 1000 dump*.file id mass x y z c_peratom
The first command calculates and stores the potential energy per atom.

The network is trained using the following command:
    >>nn.execute()
The final condigurations are written in ./data (default value) and can be easily read by Ovito.

The final configuration can be postprocessed so that it can be used again to find subcategories
inside a specific category:
    >>nn.postprocess_output()