everything working; need to clean prints though

distribution_matching/commons.py

@@ -8,7 +8,7 @@ from distribution_matching.method_dirichlety import DIRy
 from sklearn.linear_model import LogisticRegression
 from method_kdey_closed_efficient import KDEyclosed_efficient
 
-METHODS  = ['KDEy-closed++', 'KDEy-closed+', 'KDEy-closed', 'ACC', 'PACC', 'HDy-OvA', 'DIR', 'DM', 'KDEy-DMhd3', 'EMQ', 'KDEy-ML'] #, 'KDEy-DMhd2'] #, 'KDEy-DMhd2', 'DM-HD'] 'KDEy-DMjs', 'KDEy-DM', 'KDEy-ML+', 'KDEy-DMhd3+',
+METHODS  = ['ACC', 'PACC', 'HDy-OvA', 'DIR', 'DM', 'KDEy-DMhd3', 'KDEy-closed++', 'EMQ', 'KDEy-ML'] #, 'KDEy-DMhd2'] #, 'KDEy-DMhd2', 'DM-HD'] 'KDEy-DMjs', 'KDEy-DM', 'KDEy-ML+', 'KDEy-DMhd3+',
 BIN_METHODS = [x.replace('-OvA', '') for x in METHODS]
 
 

distribution_matching/method_kdey_closed_efficient_correct.py

@@ -61,6 +61,8 @@ class KDEyclosed_efficient_corr(AggregativeProbabilisticQuantifier):
             data, self.classifier, val_split, probabilistic=True, fit_classifier=fit_classifier, n_jobs=self.n_jobs
         )
 
+        print('training over')
+
         assert all(sorted(np.unique(y)) == np.arange(data.n_classes)), \
             'label name gaps not allowed in current implementation'
 
@@ -94,11 +96,14 @@ class KDEyclosed_efficient_corr(AggregativeProbabilisticQuantifier):
         self.tr_tr_sums = tr_tr_sums
         self.counts_inv = counts_inv
 
+        print('fit over')
+
         return self
 
 
     def aggregate(self, posteriors: np.ndarray):
 
+        # print('aggregating')
         Ptr = self.Ptr
         Pte = posteriors
 
@@ -121,6 +126,8 @@ class KDEyclosed_efficient_corr(AggregativeProbabilisticQuantifier):
             partB = 0.5 * np.log((alpha_l[:,np.newaxis] * tr_tr_sums * alpha_l).sum())
             return partA + partB + partC
 
+        # print('starting search')
+
         # the initial point is set as the uniform distribution
         uniform_distribution = np.full(fill_value=1 / n, shape=(n,))