vivianes changes

This commit is contained in:
Alexander Bocken 2023-06-26 10:23:19 +02:00
parent 8f2771463d
commit 15efd64c3e
Signed by: Alexander
GPG Key ID: 1D237BE83F9B05E8
3 changed files with 151 additions and 5 deletions

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@ -17,6 +17,7 @@ import numpy.typing as npt
from mesa.agent import Agent
from mesa.space import Coordinate
class RandomWalkerAnt(Agent):
def __init__(self, unique_id, model,
look_for_pheromone=None,
@ -127,12 +128,13 @@ class RandomWalkerAnt(Agent):
self.sensitivity = self.model.s_0
self.energy = self.model.e_0
self.look_for_pheromone = "A" # Is this a correct interpretation?
self.look_for_pheromone = "B"
self.drop_pheromone = "A"
self._prev_pos = neighbor
self._next_pos = self.pos
# recruit new ants
for agent_id in self.model.get_unique_ids(self.model.N_r):
if self.model.schedule.get_agent_count() < self.model.N_m:

96
main.py Executable file → Normal file
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@ -1,3 +1,4 @@
#!/bin/python
"""
main.py - Part of ants project
@ -14,7 +15,7 @@ import matplotlib.pyplot as plt
from mesa.space import Coordinate
from mesa.datacollection import DataCollector
from multihex import MultiHexGrid
#from multihex import MultiHexGrid
def main():
pass
@ -213,3 +214,96 @@ This program is distributed in the hope that it will be useful, but WITHOUT ANY
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/>
"""
# |%%--%%| <Z5Ra4Us5kN|y6CRYNrY9x>
# Access the DataCollector
datacollector = model.datacollector
# |%%--%%| <y6CRYNrY9x|v2PfrSWbzG>
# Get the data from the DataCollector
model_data = datacollector.get_model_vars_dataframe()
# |%%--%%| <v2PfrSWbzG|74OaeOltqi>
print(model_data.columns)
# |%%--%%| <74OaeOltqi|WpQLCA0RuP>
# Plot the number of alive ants over time
plt.plot(model_data.index, model_data['alive_ants'])
plt.xlabel('Time')
plt.ylabel('Number of Alive Ants') #this should probably be "active" ants, since it is not considering those in the nest
plt.title('Number of Alive Ants Over Time')
plt.grid(True)
plt.show()
# |%%--%%| <WpQLCA0RuP|UufL3yaROS>
# Plot the number of sucessful walkers over time
plt.plot(model_data.index, model_data['sucessful_walkers'])
plt.xlabel('Time')
plt.ylabel('Number of Sucessful Walkers')
plt.title('Number of Sucessful Walkers Over Time')
plt.grid(True)
plt.show()
# |%%--%%| <UufL3yaROS|mgJWQ0bqG1>
# Calculate the cumulative sum
model_data['cumulative_sucessful_walkers'] = model_data['sucessful_walkers'].cumsum()
# Plot the cumulative sum of sucessful walkers over time
plt.plot(model_data.index, model_data['cumulative_sucessful_walkers'])
plt.xlabel('Time')
plt.ylabel('Cumulative Sucessful Walkers')
plt.title('Cumulative Sucessful Walkers Over Time')
plt.grid(True)
plt.show()
# Values over 100 are to be interpreted as walkers being sucessfull several times since the total max number of ants is 100
# |%%--%%| <mgJWQ0bqG1|64kmoHYvCD>
# Connectivity measure
def check_food_source_connectivity(food_sources, paths): #food_sources = nodes.is_nest, paths=result from BFS
connected_food_sources = set()
for source in food_sources:
if source in paths:
connected_food_sources.add(source)
connectivity = len(connected_food_sources)
return connectivity
# Calculate connectivity through BFS
current_paths = bfs(self.grid, self.grid.fields["nests"], 0.000001)
# |%%--%%| <64kmoHYvCD|JEzmDy4wuX>
# |%%--%%| <JEzmDy4wuX|U9vmSFZUyD>
# |%%--%%| <U9vmSFZUyD|r0xVXEqlAh>
# |%%--%%| <r0xVXEqlAh|6K80EwwmVN>

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@ -15,6 +15,7 @@ from multihex import MultiHexGridScalarFields
from mesa.time import SimultaneousActivation
from mesa.datacollection import DataCollector
from agent import RandomWalkerAnt
from collections import deque
kwargs_paper_setup1 = {
"width": 100,
@ -62,6 +63,7 @@ kwargs_paper_setup2 = {
"resistance_map_type" : None,
}
class ActiveWalkerModel(Model):
def __init__(self, width : int, height : int,
N_0 : int, # number of initial roamers
@ -120,8 +122,6 @@ class ActiveWalkerModel(Model):
raise NotImplemented(f"{resistance_map_type=} is not implemented.")
self._unique_id_counter = -1
self.max_steps = max_steps
@ -135,16 +135,66 @@ class ActiveWalkerModel(Model):
for _ in range(N_f):
self.grid.add_food(food_size)
# Breadth-first-search algorithm for connectivity
#def bfs(graph, start_node, threshold): #graph=grid, start_node=nest, threshold=TBD?
# visited = set()
# queue = deque([(start_node, [])])
# paths = {}
# connected_food_sources = set()
# while queue:
# current_node, path = queue.popleft()
#current_node = tuple(current_node)
# visited.add(current_node)
# if current_node in graph:
# for neighbor, m.grid.fields["A"] in graph[current_node].items():
# if neighbor not in visited and m.grid.fields["A"] >= threshold:
# new_path = path + [neighbor]
# queue.append((neighbor, new_path))
# Check if the neighbor is a food source
# if neighbor in self.grid_food:
# if neighbor not in paths:
# paths[neighbor] = new_path
# connected_food_sources.add(neighbor)
# connectivity = len(connected_food_sources)
# return connectivity
# Calculate connectivity through BFS
# current_paths = bfs(self.grid, self.grid.fields["nests"], 0.000001)
def subset_agent_count(self):
subset_agents = [agent for agent in self.schedule.agents if agent.sensitivity == self.s_0 and agent.look_for_pheromone == "B"]
count = float(len(subset_agents))
return count
self.datacollector = DataCollector(
# model_reporters={"agent_dens": lambda m: m.agent_density()},
model_reporters = {"pheromone_a": lambda m: m.grid.fields["A"],
"pheromone_b": lambda m: m.grid.fields["B"],
"alive_ants": lambda m: self.schedule.get_agent_count(),
"sucessful_walkers": lambda m: subset_agent_count(self),
#"connectivity": lambda m: check_food_source_connectivity(self.grid_food,current_paths),
},
agent_reporters={}
)
self.datacollector.collect(self) # keep at end of __init___
#def subset_agent_count(self):
# subset_agents = [agent for agent in self.schedule.agents if agent.sensitivity == self.s_0]
# count = float(len(subset_agents))
# return count
def agent_density(self):
a = np.zeros((self.grid.width, self.grid.height))
for i in range(self.grid.width):
@ -180,4 +230,4 @@ This program is free software: you can redistribute it and/or modify it under th
This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU Affero General Public License for more details.
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/>
"""
"""