readded all consensus approaches

cami_src/cami_suite.py

@@ -357,13 +357,32 @@ class cami():
         for tool in result_sets:
             result_sets[tool] -= set(self.seed_lst)
         
-        params_tr = {'hub_penalty': [0.25],
-                     'damping_factor': [0.7], 
-                     'confidence_level': [0.5],
+        params_1 = {'consens_threshold': [consens_threshold],
+                    'function': {'cami_v1': cami_v1.run_cami}}
+        
+        params_0 = {'function': {'union':cami_v1.make_union, 
+                                 'intersection':cami_v1.make_intersection,
+                                 'first_neighbours': cami_v1.make_first_neighbor_result_set}
+                    }
+        
+        params_tr = {'hub_penalty': [0, 0.25, 0.5, 0.75, 1.0], 
+                     'damping_factor': [0.1, 0.25, 0.5, 0.75], 
+                     'confidence_level': [0.2, 0.35, 0.5, 0.75],
                      'ranking': ['trustrank'],
-                     'function': {'cami_v3':cami_v3.run_cami}}
+                     'function': {'cami_v2': cami_v2.run_cami, 
+                                  'cami_v3':cami_v3.run_cami}}
+        
+        params_b_m = {'hub_penalty': [0, 0.25, 0.5, 0.75, 1.0], 
+                     'confidence_level': [0.2, 0.35, 0.5, 0.75],
+                     'ranking': ['betweenness', 'harmonic'],
+                     'function': {'cami_v2': cami_v2.run_cami,
+                                  'cami_v3':cami_v3.run_cami}}
+        
+        cami_setting_list = generate_param_combinations(params_0)+\
+                            generate_param_combinations(params_1)+\
+                            generate_param_combinations(params_tr)+\
+                            generate_param_combinations(params_b_m)
 
-        cami_setting_list = generate_param_combinations(params_tr)
 
         camis = {}
         for setting in cami_setting_list: