Rename update_probability to drop

examples/plot_connectivity.py

@@ -58,7 +58,7 @@
 # all the same cell type allowing for easy modifications.
 for conn in net.connectivity:
     if conn['src_type'] == 'L2_basket':
-        conn.update_probability(0.1)
+        conn.drop(0.1)
 
 net_remove = net.copy()
 dpl_remove = simulate_dipole(net_remove, n_trials=1)

hnn_core/network.py

@@ -1074,7 +1074,7 @@ def add_connection(self, src_gids, target_gids, loc, receptor,
             conn['nc_dict'][key] = item
 
         if probability != 1.0:
-            conn.update_probability(probability)
+            conn.drop(probability)
         conn['probability'] = probability
 
         self.connectivity.append(deepcopy(conn))
@@ -1178,7 +1178,7 @@ def __repr__(self):
 
         return entr
 
-    def update_probability(self, probability):
+    def drop(self, probability):
         """Remove/keep a random subset of connections.
 
         Parameters
@@ -1206,7 +1206,7 @@ def update_probability(self, probability):
              target_src_pair in self['gid_pairs'].values()])
         n_connections = np.round(
             len(all_connections) * probability).astype(int)
-        print(len(all_connections), n_connections)
+
         # Select a random subset of connections to retain.
         new_connections = np.random.choice(
             range(len(all_connections)), n_connections, replace=False)

hnn_core/tests/test_network.py

@@ -231,7 +231,7 @@ def test_network():
     n_connections = np.sum(
         [len(t_gids) for
          t_gids in net.connectivity[0]['gid_pairs'].values()])
-    net.connectivity[0].update_probability(0.5)
+    net.connectivity[0].drop(0.5)
     n_connections_new = np.sum(
         [len(t_gids) for
          t_gids in net.connectivity[0]['gid_pairs'].values()])