#!/usr/bin/env python __author__ = 'greg' from condorAggregation import CondorAggregation import os import sys import random # add the paths necessary for clustering algorithm and ibcc - currently only works on Greg's computer if os.path.exists("/home/ggdhines"): sys.path.append( "/home/ggdhines/PycharmProjects/reduction/experimental/clusteringAlg") else: sys.path.append("/home/greg/github/reduction/experimental/clusteringAlg") from divisiveKmeans import DivisiveKmeans clusterAlg = DivisiveKmeans().__fit__ condor = CondorAggregation() zooniverse_id_list = random.sample( condor.__get_subjects_per_site__("ACW000177g"), 40) for i, zooniverse_id in enumerate(zooniverse_id_list): print i condor.__readin_subject__(zooniverse_id) blankImage = condor.__cluster_subject__(zooniverse_id, clusterAlg) if not blankImage: condor.__find_closest_neighbour__(zooniverse_id)
#!/usr/bin/env python __author__ = 'greg' from condorAggregation import CondorAggregation import os import sys import random # add the paths necessary for clustering algorithm and ibcc - currently only works on Greg's computer if os.path.exists("/home/ggdhines"): sys.path.append("/home/ggdhines/PycharmProjects/reduction/experimental/clusteringAlg") else: sys.path.append("/home/greg/github/reduction/experimental/clusteringAlg") from divisiveKmeans import DivisiveKmeans clusterAlg = DivisiveKmeans().__fit__ condor = CondorAggregation() zooniverse_id_list = random.sample(condor.__get_subjects_per_site__("ACW000177g"),40) for i,zooniverse_id in enumerate(zooniverse_id_list): print i condor.__readin_subject__(zooniverse_id) blankImage = condor.__cluster_subject__(zooniverse_id, clusterAlg) if not blankImage: condor.__find_closest_neighbour__(zooniverse_id)