| Name | Modified | Size | Downloads / Week |
|---|---|---|---|
| README.txt | 2011-02-15 | 1.3 kB | |
| Totals: 1 Item | 1.3 kB | 0 |
Hello, This is a readme file for our project. Our Python project is about clustering trajectories obtained from a molecular dynamics simulation. The aim of the project is to use python programming language to be able to run different clustering algorithms, namely: hierarchical, single linkage (edge), average linkage (average), centroid linkage (linkage), complete linkage (complete), K-means (means), centripetal, entripetal-complete, COBWEB, Bayesian, or self-organizing maps(SOM) to evaluate free energy values from different clusters. The program will ask the user to choose one or several of the algorithms to be run and the corresponding set of parameters, such as the number of clusters and the atoms used and other options more specific depending on the algorithm chosen. One has to take into account that the performace of each algorithm strongly depend on the data set used as well as the parametres used. Moreover, it has to be considered the possibility of including an option to do a primarly clustering pass with some of the trajectories and then, use the rest of the data distributing each one on the different clusters created. This strategy could reduce the computational demand not feasible, sometimes, dealing with some complex molecular dynamics data sets.