print expected SNR reduction

scripts/tune_demixing_parameters.py

@@ -652,7 +652,7 @@ class DemixingTuner:
         for ci in range(self.Nf):
             self.RSS_iter[ci,:]/=self.RSS[ci,0]
         rss=np.mean(self.RSS_iter,axis=0)**2
-        self.AIC_iter=rss*self.N*self.N+self.N*len(self.chosen_patches)*np.array(self.maxiter)
+        self.AIC_iter=rss*self.N*self.N+self.N*len(self.chosen_patches)*np.log(np.array(self.maxiter))
         index=np.argmin(self.AIC_iter)
         self.maxiter_to_use=self.maxiter[index]
 
@@ -666,26 +666,27 @@ class DemixingTuner:
 
     def report(self):
         print('*************************')
-        print('patches')
+        print('Patches')
         print(self.ateam_names)
-        print('probabilities of being selected')
+        print('Probabilities of being selected')
         print(self.AIC_probs)
-        print('separation')
+        print('Separation')
         print(self.separation)
-        print('elevation')
+        print('Elevation')
         print(self.elevation)
-        print('direction selection')
+        print('Direction selection')
         print(self.RSS)
         print(self.AIC)
-        print('frequency resolution selection')
+        print('Frequency resolution selection')
         print(self.RSS_freq)
         print(self.AIC_freq)
-        print('robust DOF selection')
+        print('Robust DOF selection')
         print(self.RSS_dof)
         print(self.AIC_dof)
-        print('maxiter selection')
+        print('Maxiter selection')
         print(self.RSS_iter)
         print(self.AIC_iter)
+        print('Expected reduction in noise is %f %%'%((1-np.mean(self.RSS_iter[:,np.argmin(self.AIC_iter)]))*100.0))
         print('*************************')
 
     def cleanup(self):