vivianes changes
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4
agent.py
4
agent.py
@ -17,6 +17,7 @@ import numpy.typing as npt
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from mesa.agent import Agent
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from mesa.agent import Agent
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from mesa.space import Coordinate
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from mesa.space import Coordinate
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class RandomWalkerAnt(Agent):
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class RandomWalkerAnt(Agent):
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def __init__(self, unique_id, model,
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def __init__(self, unique_id, model,
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look_for_pheromone=None,
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look_for_pheromone=None,
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@ -127,12 +128,13 @@ class RandomWalkerAnt(Agent):
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self.sensitivity = self.model.s_0
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self.sensitivity = self.model.s_0
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self.energy = self.model.e_0
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self.energy = self.model.e_0
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self.look_for_pheromone = "A" # Is this a correct interpretation?
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self.look_for_pheromone = "B"
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self.drop_pheromone = "A"
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self.drop_pheromone = "A"
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self._prev_pos = neighbor
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self._prev_pos = neighbor
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self._next_pos = self.pos
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self._next_pos = self.pos
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# recruit new ants
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# recruit new ants
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for agent_id in self.model.get_unique_ids(self.model.N_r):
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for agent_id in self.model.get_unique_ids(self.model.N_r):
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if self.model.schedule.get_agent_count() < self.model.N_m:
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if self.model.schedule.get_agent_count() < self.model.N_m:
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96
main.py
Executable file → Normal file
96
main.py
Executable file → Normal file
@ -1,3 +1,4 @@
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#!/bin/python
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#!/bin/python
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"""
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"""
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main.py - Part of ants project
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main.py - Part of ants project
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@ -14,7 +15,7 @@ import matplotlib.pyplot as plt
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from mesa.space import Coordinate
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from mesa.space import Coordinate
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from mesa.datacollection import DataCollector
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from mesa.datacollection import DataCollector
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from multihex import MultiHexGrid
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#from multihex import MultiHexGrid
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def main():
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def main():
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pass
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pass
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@ -213,3 +214,96 @@ This program is distributed in the hope that it will be useful, but WITHOUT ANY
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You should have received a copy of the GNU Affero General Public License along with this program. If not, see <https://www.gnu.org/licenses/>
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You should have received a copy of the GNU Affero General Public License along with this program. If not, see <https://www.gnu.org/licenses/>
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"""
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"""
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# |%%--%%| <Z5Ra4Us5kN|y6CRYNrY9x>
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# Access the DataCollector
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datacollector = model.datacollector
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# |%%--%%| <y6CRYNrY9x|v2PfrSWbzG>
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# Get the data from the DataCollector
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model_data = datacollector.get_model_vars_dataframe()
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# |%%--%%| <v2PfrSWbzG|74OaeOltqi>
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print(model_data.columns)
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# |%%--%%| <74OaeOltqi|WpQLCA0RuP>
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# Plot the number of alive ants over time
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plt.plot(model_data.index, model_data['alive_ants'])
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plt.xlabel('Time')
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plt.ylabel('Number of Alive Ants') #this should probably be "active" ants, since it is not considering those in the nest
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plt.title('Number of Alive Ants Over Time')
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plt.grid(True)
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plt.show()
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# |%%--%%| <WpQLCA0RuP|UufL3yaROS>
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# Plot the number of sucessful walkers over time
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plt.plot(model_data.index, model_data['sucessful_walkers'])
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plt.xlabel('Time')
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plt.ylabel('Number of Sucessful Walkers')
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plt.title('Number of Sucessful Walkers Over Time')
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plt.grid(True)
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plt.show()
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# |%%--%%| <UufL3yaROS|mgJWQ0bqG1>
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# Calculate the cumulative sum
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model_data['cumulative_sucessful_walkers'] = model_data['sucessful_walkers'].cumsum()
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# Plot the cumulative sum of sucessful walkers over time
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plt.plot(model_data.index, model_data['cumulative_sucessful_walkers'])
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plt.xlabel('Time')
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plt.ylabel('Cumulative Sucessful Walkers')
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plt.title('Cumulative Sucessful Walkers Over Time')
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plt.grid(True)
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plt.show()
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# Values over 100 are to be interpreted as walkers being sucessfull several times since the total max number of ants is 100
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# |%%--%%| <mgJWQ0bqG1|64kmoHYvCD>
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# Connectivity measure
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def check_food_source_connectivity(food_sources, paths): #food_sources = nodes.is_nest, paths=result from BFS
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connected_food_sources = set()
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for source in food_sources:
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if source in paths:
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connected_food_sources.add(source)
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connectivity = len(connected_food_sources)
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return connectivity
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# Calculate connectivity through BFS
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current_paths = bfs(self.grid, self.grid.fields["nests"], 0.000001)
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# |%%--%%| <64kmoHYvCD|JEzmDy4wuX>
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# |%%--%%| <JEzmDy4wuX|U9vmSFZUyD>
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# |%%--%%| <U9vmSFZUyD|r0xVXEqlAh>
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# |%%--%%| <r0xVXEqlAh|6K80EwwmVN>
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54
model.py
54
model.py
@ -15,6 +15,7 @@ from multihex import MultiHexGridScalarFields
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from mesa.time import SimultaneousActivation
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from mesa.time import SimultaneousActivation
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from mesa.datacollection import DataCollector
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from mesa.datacollection import DataCollector
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from agent import RandomWalkerAnt
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from agent import RandomWalkerAnt
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from collections import deque
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kwargs_paper_setup1 = {
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kwargs_paper_setup1 = {
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"width": 100,
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"width": 100,
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@ -62,6 +63,7 @@ kwargs_paper_setup2 = {
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"resistance_map_type" : None,
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"resistance_map_type" : None,
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}
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}
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class ActiveWalkerModel(Model):
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class ActiveWalkerModel(Model):
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def __init__(self, width : int, height : int,
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def __init__(self, width : int, height : int,
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N_0 : int, # number of initial roamers
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N_0 : int, # number of initial roamers
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@ -120,8 +122,6 @@ class ActiveWalkerModel(Model):
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raise NotImplemented(f"{resistance_map_type=} is not implemented.")
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raise NotImplemented(f"{resistance_map_type=} is not implemented.")
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self._unique_id_counter = -1
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self._unique_id_counter = -1
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self.max_steps = max_steps
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self.max_steps = max_steps
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@ -136,15 +136,65 @@ class ActiveWalkerModel(Model):
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for _ in range(N_f):
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for _ in range(N_f):
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self.grid.add_food(food_size)
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self.grid.add_food(food_size)
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# Breadth-first-search algorithm for connectivity
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#def bfs(graph, start_node, threshold): #graph=grid, start_node=nest, threshold=TBD?
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# visited = set()
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# queue = deque([(start_node, [])])
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# paths = {}
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# connected_food_sources = set()
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# while queue:
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# current_node, path = queue.popleft()
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#current_node = tuple(current_node)
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# visited.add(current_node)
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# if current_node in graph:
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# for neighbor, m.grid.fields["A"] in graph[current_node].items():
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# if neighbor not in visited and m.grid.fields["A"] >= threshold:
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# new_path = path + [neighbor]
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# queue.append((neighbor, new_path))
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# Check if the neighbor is a food source
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# if neighbor in self.grid_food:
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# if neighbor not in paths:
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# paths[neighbor] = new_path
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# connected_food_sources.add(neighbor)
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# connectivity = len(connected_food_sources)
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# return connectivity
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# Calculate connectivity through BFS
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# current_paths = bfs(self.grid, self.grid.fields["nests"], 0.000001)
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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 and agent.look_for_pheromone == "B"]
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count = float(len(subset_agents))
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return count
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self.datacollector = DataCollector(
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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={"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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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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"pheromone_b": lambda m: m.grid.fields["B"],
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"alive_ants": lambda m: self.schedule.get_agent_count(),
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"sucessful_walkers": lambda m: subset_agent_count(self),
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#"connectivity": lambda m: check_food_source_connectivity(self.grid_food,current_paths),
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},
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},
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agent_reporters={}
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agent_reporters={}
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)
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)
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self.datacollector.collect(self) # keep at end of __init___
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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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def agent_density(self):
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a = np.zeros((self.grid.width, self.grid.height))
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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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for i in range(self.grid.width):
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