Fixes #42

doc_src/manual.rst

@@ -65,7 +65,7 @@ Visualization
 To visualize the single and pairwise marginals, we have to create a visualizer object first containing the fanova object and configspace
 
     >>> import fanova.visualizer
-    >>> vis = visualizer.Visualizer(f, config_space)
+    >>> vis = fanova.visualizer.Visualizer(f, config_space)
 
 We can then plot single marginals by 
 

examples/onlineLDA_example.py

@@ -37,7 +37,7 @@
 # directory in which you can find all plots
 plot_dir = path + '/example_data/test_plots'
 # first create an instance of the visualizer with fanova object and configspace
-vis = visualizer.Visualizer(f, cs)
+vis = fanova.visualizer.Visualizer(f, cs)
 # generating plot data for col0
 mean, std, grid = vis.generate_marginal(0)
 print(mean)

fanova/fanova.py

@@ -326,13 +326,20 @@ def get_most_important_pairwise_marginals(self, n=10):
         list: 
              Contains the n most important pairwise marginals
         """
+        tot_imp_dict = OrderedDict()
         pairwise_marginals = []
         dimensions = range(self.n_dims)
         for combi in it.combinations(dimensions,2):
+
             pairwise_marginal_performance = self.quantify_importance(combi)
-            pairwise_marginals.append((pairwise_marginal_performance, combi[0], combi[1]))
+            tot_imp = pairwise_marginal_performance[combi]['total importance']
+            pairwise_marginals.append((tot_imp, combi[0], combi[1]))
 
         pairwise_marginal_performance = sorted(pairwise_marginals, reverse=True)
-        important_pairwise_marginals = [(p1, p2) for marginal, p1, p2  in pairwise_marginal_performance[:n]]
 
-        return important_pairwise_marginals
+        #important_pairwise_marginals = [((p1, p2), marginal) for marginal, p1, p2  in pairwise_marginal_performance[:n]]
+
+        for marginal, p1, p2  in pairwise_marginal_performance[:n]:
+            tot_imp_dict[(p1,p2)] = marginal
+
+        return tot_imp_dict