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alternative cummulative successful ants measurement

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Alexander Bocken 2023-06-26 10:55:23 +02:00
parent 74d59ecc2e
commit 960b4b1ca0
Signed by: Alexander
GPG Key ID: 1D237BE83F9B05E8
3 changed files with 22 additions and 24 deletions
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3
agent.py
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@ -113,8 +113,8 @@ class RandomWalkerAnt(Agent):
self.energy = self.model.e_0
#now look for other pheromone
self.drop_pheromone = "B"
self.look_for_pheromone = "A"
self.drop_pheromone = "B"
self._prev_pos = neighbor
self._next_pos = self.pos
@ -133,6 +133,7 @@ class RandomWalkerAnt(Agent):
self._prev_pos = neighbor
self._next_pos = self.pos
self.model.successful_ants += 1
# recruit new ants

1
main.py
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@ -187,6 +187,7 @@ def check_ants_follow_gradient():
# main()
from model import kwargs_paper_setup1 as kwargs
# kwargs["N_m"] = 10000
model = ActiveWalkerModel(**kwargs)
from hexplot import plot_hexagon

42
model.py
View File

@ -100,6 +100,7 @@ class ActiveWalkerModel(Model):
self.q_tr : float = q_tr # threshold under which ant cannot distinguish concentrations
self.e_min : float = e_min # energy at which walker dies
self.N_f : int = N_f #num food sources
self.successful_ants = 0 # for viviane's graph
fields=["A", "B", "nests", "food", "res"]
self.schedule = SimultaneousActivation(self)
@ -135,7 +136,7 @@ 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?
@ -143,7 +144,7 @@ class ActiveWalkerModel(Model):
# queue = deque([(start_node, [])])
# paths = {}
# connected_food_sources = set()
# while queue:
# current_node, path = queue.popleft()
#current_node = tuple(current_node)
@ -154,36 +155,31 @@ class ActiveWalkerModel(Model):
# 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
# connectivity = len(connected_food_sources)
# return connectivity
# Calculate connectivity through BFS
# current_paths = bfs(self.grid, self.grid.fields["nests"], 0.000001)
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),
"alive_ants": lambda m: m.schedule.get_agent_count(),
"sucessful_walkers": lambda m: m.successful_ants,
#"connectivity": lambda m: check_food_source_connectivity(self.grid_food,current_paths),
},
agent_reporters={}
@ -194,7 +190,7 @@ class ActiveWalkerModel(Model):
# 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):
@ -230,4 +226,4 @@ 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/>
"""
"""