sys.path.append("/home/ggdhines/PycharmProjects/reduction/experimental/clusteringAlg") elif os.path.exists("/Users/greg"): sys.path.append("/Users/greg/Code/reduction/experimental/clusteringAlg") else: sys.path.append("/home/greg/github/reduction/experimental/clusteringAlg") from divisiveKmeans import DivisiveKmeans from multiClickCorrect import MultiClickCorrect clusterAlg = DivisiveKmeans().__fit__ correctionAlg = MultiClickCorrect(overlap_threshold=1,min_cluster_size=2).__fix__ condor = CondorAggregation() gold_subjects = condor.__get_gold_subjects__() gold_sample = gold_subjects[:50] for zooniverse_id in gold_sample: print zooniverse_id condor.__load_gold_standard__(zooniverse_id) condor.__readin_subject__(zooniverse_id) blankImage = condor.__cluster_subject__(zooniverse_id, clusterAlg,fix_distinct_clusters=True)#,correction_alg=correctionAlg) condor.__readin_users__() condor.__signal_ibcc__() #condor.__roc__() #condor.__display_false_positives__() for zooniverse_id in gold_sample: condor.__display_nearest_neighbours__(zooniverse_id)
else: sys.path.append("/home/greg/github/reduction/experimental/clusteringAlg") from divisiveKmeans import DivisiveKmeans from multiClickCorrect import MultiClickCorrect clusterAlg = DivisiveKmeans().__fit__ correctionAlg = MultiClickCorrect(overlap_threshold=1, min_cluster_size=2).__fix__ condor = CondorAggregation() gold_subjects = condor.__get_gold_subjects__() gold_sample = gold_subjects[:50] for zooniverse_id in gold_sample: print zooniverse_id condor.__load_gold_standard__(zooniverse_id) condor.__readin_subject__(zooniverse_id) blankImage = condor.__cluster_subject__( zooniverse_id, clusterAlg, fix_distinct_clusters=True) #,correction_alg=correctionAlg) condor.__readin_users__() condor.__signal_ibcc__() #condor.__roc__() #condor.__display_false_positives__() for zooniverse_id in gold_sample: condor.__display_nearest_neighbours__(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)
#!/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)