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from functools import partial
import random
import mesa
import seaborn as sns
import numpy as np
import pandas as pd
from matplotlib.colors import ListedColormap
import matplotlib.pyplot as plt
import pprint
# List of parties. Negative ones are left-wing, positive ones are
# right-wing. Radical parties have higher weight.
left = [-9, -7, -5, -3, -1]
right = [1, 3, 5, 7, 9]
preferences = left + [0] + right
preferences_p = left + right
# Keep also names.
names = ["E", "D", "C", "B", "A", "O", "A'", "B'", "C'", "D'", "E'"]
weights = [1, 3, 5, 7, 9]
colors = [(250, 187, 187), (250, 135, 135), (252, 101, 101), (250, 52, 52), (250, 15, 15), (0, 0, 0),
(15, 39, 250), (77, 95, 250), (130, 142, 250), (174, 182, 252), (214, 218, 255)]
colors = [(e[0] / 255.0, e[1] / 255.0, e[2] / 255.0) for e in colors]
cmap = ListedColormap(colors)
def portions(n):
a = random.sample(range(1, n), 4) + [0, n]
list.sort(a)
return sorted([a[i + 1] - a[i] for i in range(len(a) - 1)])
class Voter(mesa.Agent):
"""A voter with fixed initial preference."""
def __init__(self, unique_id, model):
super().__init__(unique_id, model)
self.preference = random.choice(preferences)
#self.preference = model.voters.pop()
#self.preference = random.choices(preferences, left_portions + [4]
# + right_portions)[0]
self.next_preference = None
def step(self):
neighbors = self.model.grid.get_neighbors(
self.pos,
moore=False,
include_center=False,
radius=1)
#print(neighbors)
neighbors_prefs = [neighbor.preference for neighbor in neighbors]
#print(sum(neighbors_prefs))
neighbors_sum = sum(neighbors_prefs)
if neighbors_sum == 0: # It's a tie, then I vote sincerely.
self.next_preference = self.preference
self.model.outcomes["tie"] += 1
elif neighbors_sum > 0:
# Right-wing is winning. If I am a rightist, then I vote
# sincerely, otherwise I vote strategically.
if self.preference < 0:
for weight in weights:
if neighbors_sum + (-weight) <= self.preference:
self.next_preference = -weight
self.model.outcomes["left_suc_strategic"] += 1
#print(f"{str(self.pos)}, {str(neighbors_sum)}, {str(-weight)}")
break
else:
toss = random.choice([-1, 0, 1])
if toss == -1:
self.next_preference = -9 # Left-wing will not win, but I will try my best.
self.model.outcomes["left_unsuc_best_try"] += 1
elif toss == 0:
self.next_preference = self.preference
self.model.outcomes["left_unsuc_sincere"] += 1
elif toss == 1:
self.next_preference = random.choice(preferences_p)
self.model.outcomes["left_unsuc_random"] += 1
else:
self.next_preference = self.preference
self.model.outcomes["right_winning_sincere"] += 1
elif neighbors_sum < 0:
# Left-wing is winning. If I am a leftist, then I vote
# sincerely, otherwise I vote strategically.
if self.preference > 0:
for weight in weights:
if neighbors_sum + weight >= self.preference:
self.next_preference = weight
self.model.outcomes["right_suc_strategic"] += 1
#print(f"{str(self.pos)}, {str(neighbors_sum)}, {str(weight)}")
break
else:
toss = random.choice([-1, 0, 1])
if toss == -1:
self.next_preference = 9 # Left-wing will not win, but I will try my best.
self.model.outcomes["right_unsuc_best_try"] += 1
elif toss == 0:
self.next_preference = self.preference
self.model.outcomes["right_unsuc_sincere"] += 1
elif toss == 1:
self.next_preference = random.choice(preferences_p)
self.model.outcomes["right_unsuc_random"] += 1
else:
self.next_preference = self.preference
self.model.outcomes["left_winning_sincere"] += 1
def advance(self):
self.preference = self.next_preference
# Construct the reporter dictionary.
def count_preferences(model, preference):
prefs_list = [agent.preference for agent in model.schedule.agents]
prefs_set = set(preferences)
prefs_dict = dict([(preference, prefs_list.count(preference))
for preference in prefs_set])
return prefs_dict[preference]
model_reporters = {str(names[i]): partial(count_preferences,
preference=preference) for
i, preference in enumerate(preferences)}
# Add the outcomes reporter.
model_reporters["outcomes"] = lambda m : dict(m.outcomes)
class VotingModel(mesa.Model):
"""Model with some voters possibly voting strategically."""
def __init__(self, width):
super().__init__()
self.num_voters = width * width
self.grid = mesa.space.SingleGrid(width, width, True)
self.schedule = mesa.time.SimultaneousActivation(self)
# Keep count of sincere and strategic votes.
self.outcomes = {
"tie" : 0,
"left_suc_strategic" : 0,
"left_unsuc_best_try" : 0,
"left_unsuc_sincere" : 0,
"left_unsuc_random" : 0,
"left_winning_sincere" : 0,
"right_suc_strategic" : 0,
"right_unsuc_best_try" : 0,
"right_unsuc_sincere" : 0,
"right_unsuc_random" : 0,
"right_winning_sincere" : 0,
}
# Initiate portions of the parties
#left_portions = sorted(portions(48), reverse=True)
#right_portions = portions(48)
#print(left_portions, right_portions)
#self.voter_portions = left_portions + [4] + right_portions
#self.voters = []
#for index, i in enumerate(self.voter_portions):
# # Assume width is a multiple of 10.
# for _ in range(i * self.num_voters // 100):
# self.voters.append(preferences[index])
# Create voters.
for i in range(self.num_voters):
voter = Voter(i, self)
self.schedule.add(voter)
# Place the agent to a random grid cell
self.grid.place_agent(voter, random.choice(list(self.grid.empties)))
self.datacollector = mesa.DataCollector(model_reporters=model_reporters)
def step(self):
self.datacollector.collect(self)
# Reset outcomes counters.
for key in self.outcomes:
self.outcomes[key] = 0
self.schedule.step()Editor is loading...
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