fix indents, add bfs to scheduler
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35
model.py
35
model.py
@ -107,7 +107,6 @@ class ActiveWalkerModel(Model):
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self.grid = MultiHexGridScalarFields(width=width, height=height, torus=True, fields=fields)
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if resistance_map_type is None:
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print("No resistance field")
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self.grid.fields["res"] = np.ones((width, height)).astype(float)
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elif resistance_map_type == "perlin":
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# perlin generates anisotropic noise which may or may not be a good choice
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@ -139,6 +138,17 @@ class ActiveWalkerModel(Model):
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for _ in range(N_f):
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self.grid.add_food(food_size)
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self.datacollector = DataCollector(
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# model_reporters={"agent_dens": lambda m: m.agent_density()},
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model_reporters = {"pheromone_a": lambda m: m.grid.fields["A"],
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"pheromone_b": lambda m: m.grid.fields["B"],
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"alive_ants": lambda m: m.schedule.get_agent_count(),
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"sucessful_walkers": lambda m: m.successful_ants,
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"connectivity": lambda m: m.connectivity,
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},
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agent_reporters={}
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)
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self.datacollector.collect(self) # keep at end of __init___
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# Breadth-first-search algorithm for connectivity
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# TODO: Implement pheromone B (take max of the two or sum?)
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@ -174,28 +184,9 @@ class ActiveWalkerModel(Model):
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connectivity += 1 #then we have found a connected path to a food source
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connected_food_sources = connected_food_sources + list([current_node]) #and it is added to the list of connected food sources
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# why not normalize to 0-1 ?
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return connectivity #we want the connectivity (0-5)
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self.connectivity = bfs(self)
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self.datacollector = DataCollector(
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# model_reporters={"agent_dens": lambda m: m.agent_density()},
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model_reporters = {"pheromone_a": lambda m: m.grid.fields["A"],
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"pheromone_b": lambda m: m.grid.fields["B"],
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"alive_ants": lambda m: m.schedule.get_agent_count(),
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"sucessful_walkers": lambda m: m.successful_ants,
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"connectivity": lambda m: m.connectivity,
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},
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agent_reporters={}
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)
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self.datacollector.collect(self) # keep at end of __init___
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#def subset_agent_count(self):
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# subset_agents = [agent for agent in self.schedule.agents if agent.sensitivity == self.s_0]
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# count = float(len(subset_agents))
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# return count
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def agent_density(self):
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a = np.zeros((self.grid.width, self.grid.height))
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for i in range(self.grid.width):
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@ -206,12 +197,14 @@ class ActiveWalkerModel(Model):
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def step(self):
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self.schedule.step() # step() and advance() all agents
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self.connectivity = self.bfs(self)
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# apply decay rate on pheromone levels
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for key in ("A", "B"):
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field = self.grid.fields[key]
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self.grid.fields[key] = field - self.gamma*field
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self.datacollector.collect(self)
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if self.schedule.steps >= self.max_steps:
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