Module ensemble_selection

Classes for representing receptor ensembles and for choosing the best
ensembles of a specified size from a cross-docking experiment.

Example:

    from schrodinger.application.glide import ensemble_selection
    es = ensemble_selection.EnsembleSelection(fname='xdock.csv', 
                                              exp_dg_fname='exp.txt')

    # get the 10 best 3-member ensembles

    print "Best by count"
    for ens in es.best_ensembles_by_count(3, 10):
        print "%d\t%.3f\t%s" % (ens.count, ens.rmsd, ens)

    print "\nBest by rmsd"
    for ens in es.best_ensembles_by_rmsd(3, 10):
        print "%d\t%.3f\t%s" % (ens.count, ens.rmsd, ens)

For more details, see the documentation for the EnsembleSelection class.