Metadata-Version: 2.1
Name: classomfier
Version: 0.1
Summary: ClasSOMfier: A neural network for cluster analysis and detection of lattice defects
Home-page: https://github.com/JaviFdezT/ClasSOMfier
Author: Javier F. Troncoso
Author-email: javierfdeztroncoso@gmail.com
License: LICENSE.txt
Download-URL: https://github.com/JaviFdezT/ClasSOMfier/archive/0.1.tar.gz
Keywords: kohonen,neural,network,cluster,analysis
Platform: UNKNOWN
Description-Content-Type: text/markdown

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: javierfdeztroncoso@gmail.com


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()


