ants/main.py

194 lines
6.7 KiB
Python
Executable File

#!/bin/python
"""
main.py - Part of ants project
execute via `python main.py` in terminal or only UNIX: `./main.py`
License: AGPL 3 (see end of file)
(C) Alexander Bocken, Viviane Fahrni, Grace Kagho
"""
from model import ActiveWalkerModel
from agent import RandomWalkerAnt
import numpy as np
import matplotlib.pyplot as plt
from mesa.space import Coordinate
from mesa.datacollection import DataCollector
from multihex import MultiHexGrid
def main():
check_pheromone_exponential_decay()
check_ant_sensitivity_linear_decay()
check_ant_pheromone_exponential_decay()
check_ants_follow_gradient()
def check_pheromone_exponential_decay():
"""
Check whether wanted exponential decay of pheromones on grid is done correctly
shows plot of pheromone placed on grid vs. equivalent exponential decay function
"""
width = 21
height = width
num_initial_roamers = 0
num_max_agents = 100
nest_position : Coordinate = (width //2, height //2)
max_steps = 1000
model = ActiveWalkerModel(width=width, height=height,
num_initial_roamers=num_initial_roamers,
nest_position=nest_position,
num_max_agents=num_max_agents,
max_steps=max_steps)
model.grid.fields["A"][5,5] = 10
model.datacollector = DataCollector(
model_reporters={"pheromone_a": lambda m: m.grid.fields["A"][5,5] },
agent_reporters={}
)
model.run_model()
a_test = model.datacollector.get_model_vars_dataframe()["pheromone_a"]
plt.figure()
xx = np.linspace(0,1000, 10000)
yy = a_test[0]*np.exp(-model.decay_rates["A"]*xx)
plt.plot(xx, yy, label="correct exponential function")
plt.scatter(range(len(a_test)), a_test, label="modeled decay", marker='o')
plt.title("Exponential grid pheromone decay test")
plt.legend(loc='best')
plt.show()
def check_ant_sensitivity_linear_decay():
"""
Check whether wanted linear decay of ant sensitivity is done correctly
shows plot of ant sensitivity placed on grid vs. equivalent linear decay function
not food sources are on the grid for this run to not reset sensitivities
"""
width = 50
height = width
num_initial_roamers = 1
num_max_agents = 100
nest_position : Coordinate = (width //2, height //2)
max_steps = 1000
num_food_sources = 0
model = ActiveWalkerModel(width=width, height=height,
num_initial_roamers=num_initial_roamers,
nest_position=nest_position,
num_max_agents=num_max_agents,
num_food_sources=num_food_sources,
max_steps=max_steps)
model.datacollector = DataCollector(
model_reporters={},
agent_reporters={"sensitivity": lambda a: a.sensitivity}
)
start = model.schedule.agents[0].sensitivity_decay_rate
model.run_model()
a_test = model.datacollector.get_agent_vars_dataframe().reset_index()["sensitivity"]
plt.figure()
xx = np.linspace(0,1000, 10000)
yy = a_test[0] - start*xx
plt.title("Linear Ant Sensitivity decay test")
plt.plot(xx, yy, label="correct linear function")
plt.scatter(range(len(a_test)), a_test, label="modeled decay", marker='o')
plt.legend(loc='best')
plt.show()
def check_ant_pheromone_exponential_decay():
"""
Check whether wanted exponential decay of pheromone drop rate for ants is correctly modeled
shows plot of pheromone placed on grid vs. equivalent exponential decay function
"""
width = 50
height = width
num_initial_roamers = 1
num_max_agents = 100
nest_position : Coordinate = (width //2, height //2)
max_steps = 1000
model = ActiveWalkerModel(width=width, height=height,
num_initial_roamers=num_initial_roamers,
nest_position=nest_position,
num_max_agents=num_max_agents,
max_steps=max_steps)
model.datacollector = DataCollector(
model_reporters={},
agent_reporters={"pheromone_drop_rate": lambda a: a.pheromone_drop_rate["A"]}
)
start = model.schedule.agents[0].pheromone_drop_rate["A"]
model.run_model()
a_test = model.datacollector.get_agent_vars_dataframe().reset_index()["pheromone_drop_rate"]
plt.figure()
xx = np.linspace(0,1000, 10000)
yy = a_test[0]*np.exp(-model.schedule.agents[0].betas["A"]*xx)
plt.plot(xx, yy, label="correct exponential function")
plt.scatter(range(len(a_test)), a_test, label="modeled decay", marker='o')
plt.title("Exponential pheromone drop rate decay test")
plt.legend(loc='best')
plt.show()
def check_ants_follow_gradient():
"""
Create a path of neighbours with a static gradient.
Observe whether ant correctly follows gradient once found. via matrix printouts
8 = ant
anything else: pheromone A density.
The ant does not drop any new pheromones for this test
"""
width, height = 20,20
params = {
"width": width, "height": height,
"num_max_agents": 1,
"num_food_sources": 0,
"nest_position": (10,10),
"num_initial_roamers": 1,
}
model = ActiveWalkerModel(**params)
def place_line(grid : MultiHexGrid, start_pos=None):
strength = 5
if start_pos is None:
start_pos = (9,9)
next_pos = start_pos
for _ in range(width):
grid.fields["A"][next_pos] = strength
strength += 0.01
next_pos = grid.get_neighborhood(next_pos)[0]
place_line(model.grid)
ant = model.schedule._agents[0]
ant.looking_for_pheromone = "A"
ant.drop_pheromone = None
ant.threshold["A"] = 0
ant.sensitivity_max = 100
#model.grid.fields["A"] = np.diag(np.ones(width))
model.decay_rates["A"] = 0
while model.schedule.steps < 100:
display_field = np.copy(model.grid.fields["A"])
display_field[ant.pos] = 8
print(display_field)
print(20*"#")
model.step()
if __name__ == "__main__":
main()
"""
This program is free software: you can redistribute it and/or modify it under the terms of the GNU Affero General Public License as published by the Free Software Foundation, version 3.
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/>
"""