Merge branch 'new_spaces' of https://github.com/quaquel/mesa-examples into new_spaces

Author: quaquel

examples/hotelling_law/hotelling_law/agents.py

@@ -175,11 +175,15 @@ def determine_preferred_store(self):
         for store in stores:
             # Calculate score based on consumer preference
             if consumer_preference == "proximity":
-                score = self.euclidean_distance(self.cell.coordinate, store.cell.coordinate)
+                score = self.euclidean_distance(
+                    self.cell.coordinate, store.cell.coordinate
+                )
             elif consumer_preference == "price":
                 score = store.price
             else:  # Default case includes both proximity and price
-                score = store.price + self.euclidean_distance(self.cell.coordinate, store.cell.coordinate)
+                score = store.price + self.euclidean_distance(
+                    self.cell.coordinate, store.cell.coordinate
+                )
 
             # Update the list of best stores if a new minimum score is found
             if score < min_score:

examples/hotelling_law/hotelling_law/model.py

@@ -190,7 +190,7 @@ def _initialize_agents(self):
             # Randomly place agents on the grid for a grid environment.
             x = self.random.randrange(self.grid.dimensions[0])
             y = self.random.randrange(self.grid.dimensions[1])
-            agent.cell = self.grid[(x,y)]
+            agent.cell = self.grid[(x, y)]
 
         # Place consumer agents
         for _ in range(self.num_consumers):
@@ -200,7 +200,7 @@ def _initialize_agents(self):
             # Place consumer randomly on the grid
             x = self.random.randrange(self.grid.dimensions[0])
             y = self.random.randrange(self.grid.dimensions[1])
-            consumer.cell = self.grid[(x,y)]
+            consumer.cell = self.grid[(x, y)]
 
     # Method to advance the simulation by one step.
     def step(self):