fix merge

Author: smejak

.gitignore

@@ -1 +1,4 @@
 __pycache__*
+*.ini
+*.xml
+*.iml

blockference/gridference.py

@@ -1,20 +1,21 @@
-import enum
+import enum  # not currently used? Is enum used in another script? or can remove. 
 import sys
-
-from matplotlib.pyplot import grid
-
-# adding tools to the system path
-sys.path.insert(0, '../tools/')
-
 from tools.model import ActiveGridference
 from tools.control import construct_policies
 import tools.utils as u
 import random as rand
 import itertools
 
+from matplotlib.pyplot import grid
+
+# adding tools to the system path
+sys.path.insert(0, '../tools/')
+
 
 def actinf_planning_single(agent, env_state, A, B, C, prior):
-    policies = construct_policies([agent.n_states], [len(agent.E)], policy_len = agent.policy_len)
+    policies = construct_policies([agent.n_states],
+                                  [len(agent.E)],
+                                  policy_len=agent.policy_len)
     # get obs_idx
     obs_idx = grid.index(env_state)
 
@@ -34,7 +35,7 @@ def actinf_planning_single(agent, env_state, A, B, C, prior):
     chosen_action = u.sample(P_u)
 
     # calc next prior
-    prior = B[:,:,chosen_action].dot(qs_current) 
+    prior = B[:, :, chosen_action].dot(qs_current)
 
     # update env state
     # action_label = params['actions'][chosen_action]
@@ -43,42 +44,43 @@ def actinf_planning_single(agent, env_state, A, B, C, prior):
     Y_new = Y
     X_new = X
 
-    if chosen_action == 0: # UP
-          
+    if chosen_action == 0:  # UP
+
         Y_new = Y - 1 if Y > 0 else Y
         X_new = X
 
-    elif chosen_action == 1: # DOWN
+    elif chosen_action == 1:  # DOWN
 
         Y_new = Y + 1 if Y < agent.border else Y
         X_new = X
 
-    elif chosen_action == 2: # LEFT
+    elif chosen_action == 2:  # LEFT
         Y_new = Y
         X_new = X - 1 if X > 0 else X
 
-    elif chosen_action == 3: # RIGHT
+    elif chosen_action == 3:  # RIGHT
         Y_new = Y
-        X_new = X +1 if X < agent.border else X
+        X_new = X + 1 if X < agent.border else X
 
-    elif chosen_action == 4: # STAY
-        Y_new, X_new = Y, X 
-        
-    current_state = (Y_new, X_new) # store the new grid location
+    elif chosen_action == 4:  # STAY
+        Y_new, X_new = Y, X
+
+    current_state = (Y_new, X_new)  # store the new grid location
 
     return {'update_prior': prior,
             'update_env': current_state,
             'update_action': chosen_action,
             'update_inference': qs_current}
 
+
 def actinf_graph(agent_network):
 
     # list of all updates to the agents in the network
     agent_updates = []
 
     for agent in agent_network.nodes:
 
-        policies = construct_policies([agent_network.nodes[agent]['agent'].n_states], [len(agent_network.nodes[agent]['agent'].E)], policy_len = agent_network.nodes[agent]['agent'].policy_len)
+        policies = construct_policies([agent_network.nodes[agent]['agent'].n_states], [len(agent_network.nodes[agent]['agent'].E)], policy_len=agent_network.nodes[agent]['agent'].policy_len)
         # get obs_idx
         obs_idx = grid.index(agent_network.nodes[agent]['env_state'])
 
@@ -92,12 +94,12 @@ def actinf_graph(agent_network):
         Q_pi = u.softmax(-_G)
         # compute the probability of each action
         P_u = u.compute_prob_actions(agent_network.nodes[agent]['agent'].E, policies, Q_pi)
-        
+
         # sample action
         chosen_action = u.sample(P_u)
 
         # calc next prior
-        prior = agent_network.nodes[agent]['prior_B'][:,:,chosen_action].dot(qs_current) 
+        prior = agent_network.nodes[agent]['prior_B'][:, :, chosen_action].dot(qs_current)
 
         # update env state
         # action_label = params['actions'][chosen_action]
@@ -107,28 +109,28 @@ def actinf_graph(agent_network):
         X_new = X
         # here
 
-        if chosen_action == 0: # UP
-            
+        if chosen_action == 0:  # UP
+
             Y_new = Y - 1 if Y > 0 else Y
             X_new = X
 
-        elif chosen_action == 1: # DOWN
+        elif chosen_action == 1:  # DOWN
 
             Y_new = Y + 1 if Y < agent_network.nodes[agent]['agent'].border else Y
             X_new = X
 
-        elif chosen_action == 2: # LEFT
+        elif chosen_action == 2:  # LEFT
             Y_new = Y
             X_new = X - 1 if X > 0 else X
 
-        elif chosen_action == 3: # RIGHT
+        elif chosen_action == 3:  # RIGHT
             Y_new = Y
-            X_new = X +1 if X < agent_network.nodes[agent]['agent'].border else X
+            X_new = X + 1 if X < agent_network.nodes[agent]['agent'].border else X
+
+        elif chosen_action == 4:  # STAY
+            Y_new, X_new = Y, X
 
-        elif chosen_action == 4: # STAY
-            Y_new, X_new = Y, X 
-            
-        current_state = (Y_new, X_new) # store the new grid location
+        current_state = (Y_new, X_new)  # store the new grid location
         agent_update = {'source': agent,
                         'update_prior': prior,
                         'update_env': current_state,
@@ -138,6 +140,7 @@ def actinf_graph(agent_network):
 
     return {'agent_updates': agent_updates}
 
+
 class GridAgent():
     def __init__(self, grid_len, num_agents, grid_dim=2) -> None:
         self.grid = self.get_grid(grid_len, grid_dim)
@@ -157,24 +160,24 @@ def init_agents(self, no_agents):
             # create new agent
             agent = ActiveGridference(self.grid)
             # generate target state
-            target = (rand.randint(0,9), rand.randint(0,9))
+            target = (rand.randint(0, 9), rand.randint(0, 9))
             # add target state
             agent.get_C(target + (0,))
             # all agents start in the same position
-            start = (rand.randint(0,9), rand.randint(0,9))
+            start = (rand.randint(0, 9), rand.randint(0, 9))
             agent.get_D(start + (1,))
 
             agents[a] = agent
 
         return agents
-    
+
     def actinf_dict(self, agents_dict, g_agent):
         # list of all updates to the agents in the network
         agent_updates = []
 
         for source, agent in agents_dict.items():
 
-            policies = construct_policies([agent.n_states], [len(agent.E)], policy_len = agent.policy_len)
+            policies = construct_policies([agent.n_states], [len(agent.E)], policy_len=agent.policy_len)
             # get obs_idx
             obs_idx = g_agent.grid.index(agent.env_state)
 
@@ -193,12 +196,12 @@ def actinf_dict(self, agents_dict, g_agent):
             chosen_action = u.sample(P_u)
 
             # calc next prior
-            prior = agent.B[:,:,chosen_action].dot(qs_current) 
+            prior = agent.B[:, :, chosen_action].dot(qs_current)
 
             # update env state
             # action_label = params['actions'][chosen_action]
-                
-            current_state = self.move_2d(agent, chosen_action) # store the new grid location
+
+            current_state = self.move_2d(agent, chosen_action)  # store the new grid location
             agent_update = {'source': source,
                             'update_prior': prior,
                             'update_env': current_state,
@@ -214,25 +217,25 @@ def move_2d(self, agent, chosen_action):
         X_new = X
         # here
 
-        if chosen_action == 0: # UP
-                
+        if chosen_action == 0:  # UP
+
             Y_new = Y - 1 if Y > 0 else Y
             X_new = X
 
-        elif chosen_action == 1: # DOWN
+        elif chosen_action == 1:  # DOWN
 
             Y_new = Y + 1 if Y < agent.border else Y
             X_new = X
 
-        elif chosen_action == 2: # LEFT
+        elif chosen_action == 2:  # LEFT
             Y_new = Y
             X_new = X - 1 if X > 0 else X
 
-        elif chosen_action == 3: # RIGHT
+        elif chosen_action == 3:  # RIGHT
             Y_new = Y
-            X_new = X +1 if X < agent.border else X
+            X_new = X + 1 if X < agent.border else X
 
-        elif chosen_action == 4: # STAY
+        elif chosen_action == 4:  # STAY
             Y_new, X_new = Y, X
 
         return (X_new, Y_new)
@@ -244,39 +247,39 @@ def move_3d(self, agent, chosen_action):
         Z_new = Z
         # here
 
-        if chosen_action == 0: # UP
-                
+        if chosen_action == 0:  # UP
+
             Y_new = Y - 1 if Y > 0 else Y
             X_new = X
             Z_new = Z
 
-        elif chosen_action == 1: # DOWN
+        elif chosen_action == 1:  # DOWN
 
             Y_new = Y + 1 if Y < agent.border else Y
             X_new = X
             Z_new = Z
 
-        elif chosen_action == 2: # LEFT
+        elif chosen_action == 2:  # LEFT
             Y_new = Y
             X_new = X - 1 if X > 0 else X
             Z_new = Z
 
-        elif chosen_action == 3: # RIGHT
+        elif chosen_action == 3:  # RIGHT
             Y_new = Y
-            X_new = X +1 if X < agent.border else X
+            X_new = X + 1 if X < agent.border else X
             Z_new = Z
 
-        elif chosen_action == 4: # IN
+        elif chosen_action == 4:  # IN
             X_new = X
             Y_new = Y
             Z_new = Z + 1 if Z < agent.border else Z
 
-        elif chosen_action == 5: # OUT
+        elif chosen_action == 5:  # OUT
             X_new = X
             Y_new = Y
-            Z_new = Z -1 if Z > agent.border else Z
+            Z_new = Z - 1 if Z > agent.border else Z
 
-        elif chosen_action == 6: # STAY
+        elif chosen_action == 6:  # STAY
             Y_new, X_new, Z_new = Y, X, Z
 
         return (X_new, Y_new, Z_new)