Reinstate PR #161: Replace schedulers with AgentSet functionality

This reinstates PR #161 after the previous revert.

Author: EwoutH

examples/bank_reserves/bank_reserves/agents.py

@@ -10,15 +10,18 @@
     Northwestern University, Evanston, IL.
 """
 
-import mesa
-
 from .random_walk import RandomWalker
 
 
-class Bank(mesa.Agent):
-    def __init__(self, unique_id, model, reserve_percent=50):
-        # initialize the parent class with required parameters
-        super().__init__(unique_id, model)
+class Bank:
+    """Note that the Bank class is not a Mesa Agent, but just a regular Python
+    class. This is because there is only one bank in this model, and it does not
+    use any Mesa-specific features like the scheduler or the grid, and doesn't
+    have a step method. It is just used to keep track of the bank's reserves and
+    the amount it can loan out, for Person agents to interact with."""
+
+    def __init__(self, model, reserve_percent=50):
+        self.model = model
         # for tracking total value of loans outstanding
         self.bank_loans = 0
         """percent of deposits the bank must keep in reserves - this is set via
@@ -173,7 +176,6 @@ def take_out_loan(self, amount):
         # increase the bank's outstanding loans
         self.bank.bank_loans += amount
 
-    # step is called for each agent in model.BankReservesModel.schedule.step()
     def step(self):
         # move to a cell in my Moore neighborhood
         self.random_move()

examples/bank_reserves/bank_reserves/model.py

@@ -26,40 +26,38 @@
 def get_num_rich_agents(model):
     """return number of rich agents"""
 
-    rich_agents = [a for a in model.schedule.agents if a.savings > model.rich_threshold]
+    rich_agents = [a for a in model.agents if a.savings > model.rich_threshold]
     return len(rich_agents)
 
 
 def get_num_poor_agents(model):
     """return number of poor agents"""
 
-    poor_agents = [a for a in model.schedule.agents if a.loans > 10]
+    poor_agents = [a for a in model.agents if a.loans > 10]
     return len(poor_agents)
 
 
 def get_num_mid_agents(model):
     """return number of middle class agents"""
 
     mid_agents = [
-        a
-        for a in model.schedule.agents
-        if a.loans < 10 and a.savings < model.rich_threshold
+        a for a in model.agents if a.loans < 10 and a.savings < model.rich_threshold
     ]
     return len(mid_agents)
 
 
 def get_total_savings(model):
     """sum of all agents' savings"""
 
-    agent_savings = [a.savings for a in model.schedule.agents]
+    agent_savings = [a.savings for a in model.agents]
     # return the sum of agents' savings
     return np.sum(agent_savings)
 
 
 def get_total_wallets(model):
     """sum of amounts of all agents' wallets"""
 
-    agent_wallets = [a.wallet for a in model.schedule.agents]
+    agent_wallets = [a.wallet for a in model.agents]
     # return the sum of all agents' wallets
     return np.sum(agent_wallets)
 
@@ -75,7 +73,7 @@ def get_total_money(model):
 
 def get_total_loans(model):
     # list of amounts of all agents' loans
-    agent_loans = [a.loans for a in model.schedule.agents]
+    agent_loans = [a.loans for a in model.agents]
     # return sum of all agents' loans
     return np.sum(agent_loans)
 
@@ -118,7 +116,7 @@ def __init__(
         self.height = height
         self.width = width
         self.init_people = init_people
-        self.schedule = mesa.time.RandomActivation(self)
+
         self.grid = mesa.space.MultiGrid(self.width, self.height, torus=True)
         # rich_threshold is the amount of savings a person needs to be considered "rich"
         self.rich_threshold = rich_threshold
@@ -138,7 +136,7 @@ def __init__(
         )
 
         # create a single bank for the model
-        self.bank = Bank(1, self, self.reserve_percent)
+        self.bank = Bank(self, self.reserve_percent)
 
         # create people for the model according to number of people set by user
         for i in range(self.init_people):
@@ -148,15 +146,13 @@ def __init__(
             p = Person(i, self, True, self.bank, self.rich_threshold)
             # place the Person object on the grid at coordinates (x, y)
             self.grid.place_agent(p, (x, y))
-            # add the Person object to the model schedule
-            self.schedule.add(p)
 
         self.running = True
         self.datacollector.collect(self)
 
     def step(self):
         # tell all the agents in the model to run their step function
-        self.schedule.step()
+        self.agents.shuffle().do("step")
         # collect data
         self.datacollector.collect(self)
 

examples/bank_reserves/batch_run.py

@@ -37,15 +37,15 @@
 def get_num_rich_agents(model):
     """list of rich agents"""
 
-    rich_agents = [a for a in model.schedule.agents if a.savings > model.rich_threshold]
+    rich_agents = [a for a in model.agents if a.savings > model.rich_threshold]
     # return number of rich agents
     return len(rich_agents)
 
 
 def get_num_poor_agents(model):
     """list of poor agents"""
 
-    poor_agents = [a for a in model.schedule.agents if a.loans > 10]
+    poor_agents = [a for a in model.agents if a.loans > 10]
     # return number of poor agents
     return len(poor_agents)
 
@@ -54,9 +54,7 @@ def get_num_mid_agents(model):
     """list of middle class agents"""
 
     mid_agents = [
-        a
-        for a in model.schedule.agents
-        if a.loans < 10 and a.savings < model.rich_threshold
+        a for a in model.agents if a.loans < 10 and a.savings < model.rich_threshold
     ]
     # return number of middle class agents
     return len(mid_agents)
@@ -65,15 +63,15 @@ def get_num_mid_agents(model):
 def get_total_savings(model):
     """list of amounts of all agents' savings"""
 
-    agent_savings = [a.savings for a in model.schedule.agents]
+    agent_savings = [a.savings for a in model.agents]
     # return the sum of agents' savings
     return np.sum(agent_savings)
 
 
 def get_total_wallets(model):
     """list of amounts of all agents' wallets"""
 
-    agent_wallets = [a.wallet for a in model.schedule.agents]
+    agent_wallets = [a.wallet for a in model.agents]
     # return the sum of all agents' wallets
     return np.sum(agent_wallets)
 
@@ -91,7 +89,7 @@ def get_total_money(model):
 def get_total_loans(model):
     """list of amounts of all agents' loans"""
 
-    agent_loans = [a.loans for a in model.schedule.agents]
+    agent_loans = [a.loans for a in model.agents]
     # return sum of all agents' loans
     return np.sum(agent_loans)
 
@@ -129,7 +127,7 @@ def __init__(
         self.height = height
         self.width = width
         self.init_people = init_people
-        self.schedule = mesa.time.RandomActivation(self)
+
         self.grid = mesa.space.MultiGrid(self.width, self.height, torus=True)
         # rich_threshold is the amount of savings a person needs to be considered "rich"
         self.rich_threshold = rich_threshold
@@ -150,8 +148,8 @@ def __init__(
             agent_reporters={"Wealth": "wealth"},
         )
 
-        # create a single bank for the model
-        self.bank = Bank(1, self, self.reserve_percent)
+        # create a single bank object for the model
+        self.bank = Bank(self, self.reserve_percent)
 
         # create people for the model according to number of people set by user
         for i in range(self.init_people):
@@ -162,16 +160,14 @@ def __init__(
             p = Person(i, (x, y), self, True, self.bank, self.rich_threshold)
             # place the Person object on the grid at coordinates (x, y)
             self.grid.place_agent(p, (x, y))
-            # add the Person object to the model schedule
-            self.schedule.add(p)
 
         self.running = True
 
     def step(self):
         # collect data
         self.datacollector.collect(self)
         # tell all the agents in the model to run their step function
-        self.schedule.step()
+        self.agents.shuffle().do("step")
 
     def run_model(self):
         for i in range(self.run_time):

examples/boid_flockers/Flocker Test.ipynb

@@ -25,7 +25,7 @@
     "def draw_boids(model):\n",
     "    x_vals = []\n",
     "    y_vals = []\n",
-    "    for boid in model.schedule.agents:\n",
+    "    for boid in model.agents:\n",
     "        x, y = boid.pos\n",
     "        x_vals.append(x)\n",
     "        y_vals.append(y)\n",

examples/boid_flockers/boid_flockers/SimpleContinuousModule.py

@@ -18,7 +18,7 @@ def __init__(self, portrayal_method=None, canvas_height=500, canvas_width=500):
 
     def render(self, model):
         space_state = []
-        for obj in model.schedule.agents:
+        for obj in model.agents:
             portrayal = self.portrayal_method(obj)
             x, y = obj.pos
             x = (x - model.space.x_min) / (model.space.x_max - model.space.x_min)

examples/boid_flockers/boid_flockers/model.py

@@ -120,7 +120,7 @@ def __init__(
         self.vision = vision
         self.speed = speed
         self.separation = separation
-        self.schedule = mesa.time.RandomActivation(self)
+
         self.space = mesa.space.ContinuousSpace(width, height, True)
         self.factors = {"cohere": cohere, "separate": separate, "match": match}
         self.make_agents()
@@ -144,7 +144,6 @@ def make_agents(self):
                 **self.factors,
             )
             self.space.place_agent(boid, pos)
-            self.schedule.add(boid)
 
     def step(self):
-        self.schedule.step()
+        self.agents.shuffle().do("step")

examples/boltzmann_wealth_model/boltzmann_wealth_model/model.py

@@ -2,7 +2,7 @@
 
 
 def compute_gini(model):
-    agent_wealths = [agent.wealth for agent in model.schedule.agents]
+    agent_wealths = [agent.wealth for agent in model.agents]
     x = sorted(agent_wealths)
     N = model.num_agents
     B = sum(xi * (N - i) for i, xi in enumerate(x)) / (N * sum(x))
@@ -21,14 +21,14 @@ def __init__(self, N=100, width=10, height=10):
         super().__init__()
         self.num_agents = N
         self.grid = mesa.space.MultiGrid(width, height, True)
-        self.schedule = mesa.time.RandomActivation(self)
+
         self.datacollector = mesa.DataCollector(
             model_reporters={"Gini": compute_gini}, agent_reporters={"Wealth": "wealth"}
         )
         # Create agents
         for i in range(self.num_agents):
             a = MoneyAgent(i, self)
-            self.schedule.add(a)
+
             # Add the agent to a random grid cell
             x = self.random.randrange(self.grid.width)
             y = self.random.randrange(self.grid.height)
@@ -38,7 +38,7 @@ def __init__(self, N=100, width=10, height=10):
         self.datacollector.collect(self)
 
     def step(self):
-        self.schedule.step()
+        self.agents.shuffle().do("step")
         # collect data
         self.datacollector.collect(self)
 

examples/boltzmann_wealth_model_experimental/model.py

@@ -2,7 +2,7 @@
 
 
 def compute_gini(model):
-    agent_wealths = [agent.wealth for agent in model.schedule.agents]
+    agent_wealths = [agent.wealth for agent in model.agents]
     x = sorted(agent_wealths)
     N = model.num_agents
     B = sum(xi * (N - i) for i, xi in enumerate(x)) / (N * sum(x))
@@ -21,14 +21,14 @@ def __init__(self, N=100, width=10, height=10):
         super().__init__()
         self.num_agents = N
         self.grid = mesa.space.MultiGrid(width, height, True)
-        self.schedule = mesa.time.RandomActivation(self)
+
         self.datacollector = mesa.DataCollector(
             model_reporters={"Gini": compute_gini}, agent_reporters={"Wealth": "wealth"}
         )
         # Create agents
         for i in range(self.num_agents):
             a = MoneyAgent(i, self)
-            self.schedule.add(a)
+
             # Add the agent to a random grid cell
             x = self.random.randrange(self.grid.width)
             y = self.random.randrange(self.grid.height)
@@ -38,7 +38,7 @@ def __init__(self, N=100, width=10, height=10):
         self.datacollector.collect(self)
 
     def step(self):
-        self.schedule.step()
+        self.agents.shuffle().do("step")
         # collect data
         self.datacollector.collect(self)
 

examples/boltzmann_wealth_model_network/boltzmann_wealth_model_network/model.py

@@ -3,7 +3,7 @@
 
 
 def compute_gini(model):
-    agent_wealths = [agent.wealth for agent in model.schedule.agents]
+    agent_wealths = [agent.wealth for agent in model.agents]
     x = sorted(agent_wealths)
     N = model.num_agents
     B = sum(xi * (N - i) for i, xi in enumerate(x)) / (N * sum(x))
@@ -19,7 +19,7 @@ def __init__(self, num_agents=7, num_nodes=10):
         self.num_nodes = num_nodes if num_nodes >= self.num_agents else self.num_agents
         self.G = nx.erdos_renyi_graph(n=self.num_nodes, p=0.5)
         self.grid = mesa.space.NetworkGrid(self.G)
-        self.schedule = mesa.time.RandomActivation(self)
+
         self.datacollector = mesa.DataCollector(
             model_reporters={"Gini": compute_gini},
             agent_reporters={"Wealth": lambda _: _.wealth},
@@ -30,15 +30,15 @@ def __init__(self, num_agents=7, num_nodes=10):
         # Create agents
         for i in range(self.num_agents):
             a = MoneyAgent(i, self)
-            self.schedule.add(a)
+
             # Add the agent to a random node
             self.grid.place_agent(a, list_of_random_nodes[i])
 
         self.running = True
         self.datacollector.collect(self)
 
     def step(self):
-        self.schedule.step()
+        self.agents.shuffle().do("step")
         # collect data
         self.datacollector.collect(self)
 

examples/caching_and_replay/model.py

@@ -70,7 +70,6 @@ def __init__(
         self.homophily = homophily
         self.radius = radius
 
-        self.schedule = mesa.time.RandomActivation(self)
         self.grid = mesa.space.SingleGrid(width, height, torus=True)
 
         self.happy = 0
@@ -87,7 +86,6 @@ def __init__(
                 agent_type = 1 if self.random.random() < self.minority_pc else 0
                 agent = SchellingAgent(self.next_id(), self, agent_type)
                 self.grid.place_agent(agent, pos)
-                self.schedule.add(agent)
 
         self.datacollector.collect(self)
 
@@ -96,9 +94,9 @@ def step(self):
         Run one step of the model.
         """
         self.happy = 0  # Reset counter of happy agents
-        self.schedule.step()
+        self.agents.shuffle().do("step")
 
         self.datacollector.collect(self)
 
-        if self.happy == self.schedule.get_agent_count():
+        if self.happy == len(self.agents):
             self.running = False