def main():
if SERVER:
server.port = SERVER_PORT
server.launch()
elif NUM_STEPS >= 0:
model = bacModel(WIDTH, HEIGHT, RADIUS_INITIALIZATION)
quit = graph(model, 0)
for i in range(NUM_STEPS):
model.step()
quit = graph(model, i + 1)
if quit:
break
else: #-1 indicates infinite loop
model = bacModel(WIDTH, HEIGHT, RADIUS_INITIALIZATION)
i = 0
quit = graph(model, i)
while True:
model.step()
i += 1
quit = graph(model, i)
if quit:
break
def main():
# constants specific to statistic collection of simulations
NUM_SIMULATIONS = 2
parser = argparse.ArgumentParser(description="Visualization controls")
parser.add_argument("--visualize",
action="store_true",
help="whether to visualize on browser")
args = parser.parse_args()
if args.visualize:
server.launch()
else:
coops = np.arange(0.0, 1.1, 0.1)
## TESTING ##
# coops = [0.5]
#############
e_prob = 0.5
for coop in coops:
print("Simulating with cooperation level %.2f" % (coop))
f_name = "logs/log_%d" % (coop * 100)
with open(f_name, 'w+') as f:
for _ in range(NUM_SIMULATIONS):
model = World(100, coop, e_prob)
while model.schedule.time < 3000 and len(
model.schedule.agents) != 0:
# simulate till there are agents in the world
model.step()
# explorer mean age
mean_explorer_age = np.mean(
[model.ages[i] for i in model.ages if "explorer" in i])
# exploiter mean age
mean_exploiter_age = np.mean([
model.ages[i] for i in model.ages if "exploiter" in i
])
# entire population mean age
mean_age = np.mean([model.ages[i] for i in model.ages])
# mean expected age based on initial values
expected_age = np.mean(model.expected_ages)
ages = ', '.join([str(model.ages[i]) for i in model.ages])
memoryLens = ', '.join(
[str(model.memoryLens[i]) for i in model.memoryLens])
total_energy = ', '.join(
[str(i) for i in model.energy_tracker])
num_explorers = ', '.join(
[str(i[0]) for i in model.member_tracker])
num_exploiters = ', '.join(
[str(i[1]) for i in model.member_tracker])
f.write("ages, " + ages + "\n")
f.write("memoryLens, " + memoryLens + "\n")
f.write("total_energy, " + total_energy + "\n")
f.write("num_explorers, " + num_explorers + "\n")
f.write("num_exploiters, " + num_exploiters + "\n")
f.write("%.5f, %.5f, %.5f, %.5f\n" %
(mean_explorer_age, mean_exploiter_age, mean_age,
expected_age))
import argparse
from server import server
from model import *
# constants specific to statistic collection of simulations
NUM_SIMULATIONS = 10
parser = argparse.ArgumentParser(description="Visualization controls")
parser.add_argument("--visualize",
action="store_true",
help="whether to visualize on browser")
args = parser.parse_args()
if args.visualize:
server.launch()
else:
coops = np.arange(0.0, 1.1, 0.1)
## TESTING ##
# coops = [0.5]
#############
e_prob = 0.5
for coop in coops:
print("Simulating with cooperation level %.2f" % (coop))
f_name = "logs/log_%d" % (coop * 100)
with open(f_name, 'w+') as f:
for _ in range(NUM_SIMULATIONS):
model = World(100, coop, e_prob)
from server import server
import os
port = int(os.getenv("PORT", 4200))
server.launch(port=port, open_browser=False)
from server import server import profile profile.run(server.launch())
from server import server server.launch()
# -*- coding: utf-8 -*- #runServer.py: starts the server (visualisation in the web-browser) from server import server #Imports the setup of the server server.port = 8521 # Sets the port on which the server will listen server.launch() # launches the server
from server import server server.launch(open_browser=False)
from server import server server.launch() # Default port: 8521
from server.server import launch launch()
