def divisiveClusteringPdb_justC(self, maxClusters=30):
'''gets all the models in this pdb file, does divisive clustering.
since proteins are large, just use the carbon in the backbone to represent
each residue. other options later maybe.'''
eachModelXyz = self.getEachModelJustXyz_restrictAtomNames("C ")
import divisive_clustering
clusters = divisive_clustering.divisiveClustering(eachModelXyz, maxClusters)
return clusters
def divisiveClustering(self): '''takes all conformations. bisects them along the longest dimension (in N*atoms*3 space). Repeat on the biggest remaining cluster until there are numClusters left, return the clusters as lists.''' numClusters = min(20, int(self.origXyzCount/3.)) #print numClusters #debugging, find out target # of clusters clusters = divisive_clustering.divisiveClustering(self.atomXyz, numClusters) return clusters
def divisiveClusteringPdb(self, maxClusters=30): '''gets all the models in this pdb file, does divisive clustering''' eachModelXyz = self.getEachModelJustXyz() import divisive_clustering clusters = divisive_clustering.divisiveClustering(eachModelXyz, maxClusters) return clusters