Schelling: Use new API and simplify

Author: rht

examples/schelling_experimental/model.py

@@ -12,7 +12,7 @@ def __init__(self, pos, model, agent_type):
 
         Args:
            unique_id: Unique identifier for the agent.
-           x, y: Agent initial location.
+           pos: Agent initial location.
            agent_type: Indicator for the agent's type (minority=1, majority=0)
         """
         super().__init__(pos, model)
@@ -38,48 +38,38 @@ class Schelling(mesa.Model):
     """
 
     def __init__(self, width=20, height=20, density=0.8, minority_pc=0.2, homophily=3):
-        """ """
-
+        super().__init__()
         self.width = width
         self.height = height
-        self.density = density
-        self.minority_pc = minority_pc
         self.homophily = homophily
 
-        self.schedule = mesa.time.RandomActivation(self)
         self.grid = mesa.space.SingleGrid(width, height, torus=True)
 
         self.happy = 0
         self.datacollector = mesa.DataCollector(
             {"happy": "happy"},  # Model-level count of happy agents
-            # For testing purposes, agent's individual x and y
-            {"x": lambda a: a.pos[0], "y": lambda a: a.pos[1]},
         )
 
         # Set up agents
         # We use a grid iterator that returns
         # the coordinates of a cell as well as
         # its contents. (coord_iter)
-        for cell in self.grid.coord_iter():
-            x, y = cell[1]
-            if self.random.random() < self.density:
-                agent_type = 1 if self.random.random() < self.minority_pc else 0
-
-                agent = SchellingAgent((x, y), self, agent_type)
-                self.grid.place_agent(agent, (x, y))
-                self.schedule.add(agent)
+        for _, pos in self.grid.coord_iter():
+            if self.random.random() < density:
+                agent_type = 1 if self.random.random() < minority_pc else 0
+                agent = SchellingAgent(pos, self, agent_type)
+                self.grid.place_agent(agent, pos)
 
-        self.running = True
         self.datacollector.collect(self)
 
     def step(self):
         """
         Run one step of the model. If All agents are happy, halt the model.
         """
         self.happy = 0  # Reset counter of happy agents
-        self.schedule.step()
+        self.agents.shuffle().do("step")
         # collect data
         self.datacollector.collect(self)
 
-        if self.happy == self.schedule.get_agent_count():
+        if self.happy == len(self.agents):
             self.running = False