def testInverseDistanceMean(self): print "testing inverse_distance_mean" Ms1 = cluster.inverse_distance_mean(self.distance_list1) Ms2 = cluster.inverse_distance_mean(self.distance_list2) Ms3 = cluster.inverse_distance_mean(self.distance_list3) assert Ms1 > Ms3, "no-cluster sample has larger Ms value than two-clustered sample" assert Ms2 == 0.5, "Ms of clustered sample is not correct"
def setUp(self): #kdrew: load pdb file pdb_filename = "data/1UBQ.pdb" pdb_handle = open(pdb_filename) pdb_string = pdb_handle.read() #kdrew: using list of residue ids that are near each other clustered_ids = [2,3,15,16,64] self.dist_list = cluster.structure_distance_calc(pdb_string, clustered_ids) self.Ms = cluster.inverse_distance_mean(self.dist_list) self.random_Ms_list = cluster.random_structure_distance_calc(pdb_string, len(clustered_ids)) print self.random_Ms_list