def _get_seird_counts(
self, env: Environment
) -> Tuple[int, int, int, int, int]:
""" env の s, e, i, r, d のカウント結果を取得 """
s = env.count_agent(Status.SUSCEPTABLE)
e = env.count_agent(Status.EXPOSED)
i = env.count_agent(Status.INFECTED)
r = env.count_agent(Status.RECOVERED)
d = env.count_agent(Status.DEATH)
return s, e, i, r, d
def init_world(self):
""" World の初期化 """
# 各ノードの Environment を初期化
self.all_agents = []
for node in self.world_graph.nodes(data=True):
idx, data = node
env_setting = self.env_settings[idx]
data["env"] = Environment(
infection_model=self.infection_model,
agent_setting=self.agent_setting,
**env_setting
)
agents = data["env"].get_agents()
self.all_agents.extend(agents)
logger.info(
"Worldクラスを初期化しました。ノード数:{}, 総人口:{}".format(
self.node_num, len(self.all_agents)
)
)
def run(index):
EnvironmentParameters.playround_with = 600
EnvironmentParameters.playround_height = 600
EnvironmentParameters.food_count = index // 4
EnvironmentParameters.landmark_count = index
SimulationParameters.ant_count = 25
SimulationParameters.move_speed = 1
SimulationParameters.move_angle = 15 / 180 * np.pi
SimulationParameters.traceback_angle = 5 / 180 * np.pi
SimulationParameters.vision_range = 25
e = Environment().generate_environment(
[],
[(250, 0)],
[(100, 0), (-100, 0), (0, 100), (0, -100), (200, 200), (200, -200), (-200, -200), (-200, 200)])
s = Simulation(e)
return s.simulateAll()
def _simulate(args=None):
# Read control panel values
SimulationParameters.ant_count = count_scale.get()
SimulationParameters.move_speed = speed_scale.get() / 100
SimulationParameters.move_angle = angle_scale.get() / 180 * np.pi
SimulationParameters.traceback_angle = traceback_angle_scale.get() / 180 * np.pi
SimulationParameters.vision_range = vision_scale.get()
plt.clf() # clears previous graph
plt.axis("off")
plt.tight_layout(0)
e = Environment().generate_random_environment()
s = Simulation(e)
result = s.simulateAll()
if result is None:
return
drawPaths(canvas, result.getAll())
drawEnvironment(canvas, e)
canvas.draw()
def setUpClass(cls):
envi = Environment()
cls.driver = envi.create_browser_instance()
envi.navigate_to_home()
cls.username = envi.username
cls.password = envi.password
import numpy as np
import random
import sys
sys.path.append("..")
from matplotlib import pyplot as plt
from matplotlib import animation
from pylab import *
from Animat import Animat
from Environment.Environment import Environment
# Initialize an Animat
xMax = 20
yMax = 20
env = Environment(xMax, yMax, 10, 10)
animat = Animat(10, 10, xMax, yMax, env)
env.initializeWeb()
env.generateFood(5, 3, 12, 7, 17)
env.generateFood(5, 13, 3, 18, 7)
foodList = []
for e in env.foodList:
foodList.append((e.x, e.y))
#print 'Food list : {}'.format(foodList)
foodList = zip(*foodList)
#print 'Modified : {}'.format(foodList)
# First set up the figure, the axis, and the plot element we want to animate
fig = plt.figure()
ax = plt.axes(xlim=(0, xMax), ylim=(0, yMax))
#---
def runSimulation() -> None:
camera = Camera(CAMERA_SLACK)
environment = Environment()
environment.buildWalls()
robot = Robot(ROBOSIZE, HALF_WINWIDTH, HALF_WINHEIGHT)
##Init Renderers
environmentRenderer = EnvironmentRenderer(environment, camera, DISPLAY)
randomRenderer = RandomRenderer(environment, camera, robot, DISPLAY)
robotViewRenderer = RobotViewRenderer(robot, camera, DISPLAY)
##
##Add sensors to the robot
ultrasonic = Ultrasonic(350)
robot.attachUltrasonic(ultrasonic)
hall = Hall()
robot.attachHall(hall)
magnetometer = Magnetometer()
robot.attachMagnetometer(magnetometer)
##
##Add robot to the environment
environment.addRobot(robot)
##
while True:
camera.adjustCamera(DISPLAY, robot)
## Render Stuff
environmentRenderer.render(getColor('white'), getColor('white'),
getColor('red'))
randomRenderer.render()
robotViewRenderer.render(getColor('blue'), getColor('white'),
getColor('black'), True)
##
##Handle key presses
for event in pygame.event.get():
robot.moveDown, robot.moveUp, robot.rotateRight, robot.rotateLeft, robot.rotate, doScan, robot.servoLeft, robot.servoRight = RobotActionHandler(
event, robot)
doTerminate = TerminateHandler(event)
if doTerminate:
terminate()
if doScan:
robot.scan(environment)
##
##handle robot movement
robot.handleMovementCommands()
environment.triggerRobotRotation()
environment.triggerRobotMovement()
##
pygame.display.update()
FPSCLOCK.tick(FPS)
import numpy as np
import random
import sys
sys.path.append("..")
from matplotlib import pyplot as plt
from matplotlib import animation
from pylab import *
from Animat import Animat
from Environment.Environment import Environment
# Initialize an Animat
xMax = 20
yMax = 20
env = Environment(xMax, yMax, 10, 10)
animat = Animat(10, 10, xMax, yMax, env)
env.initializeWeb()
env.generateFood(15, 10, 4, 16, 16)
foodList = []
for e in env.foodList:
foodList.append((e.x, e.y))
#print 'Food list : {}'.format(foodList)
foodList = zip(*foodList)
#print 'Modified : {}'.format(foodList)
# First set up the figure, the axis, and the plot element we want to animate
fig = plt.figure()
ax = plt.axes(xlim=(0, xMax), ylim=(0, yMax))
import numpy as np
import random
import sys
sys.path.append("..")
from matplotlib import pyplot as plt
from matplotlib import animation
from pylab import *
from Animat import Animat
from Environment.Environment import Environment
# Initialize an Animat
xMax = 20
yMax = 20
env = Environment(xMax, yMax, 10, 10)
animat = Animat(10, 10, xMax, yMax,env)
env.initializeWeb()
env.generateFood(15, 0 ,0,20 ,20)
foodList =[]
for e in env.foodList:
foodList.append((e.x,e.y))
#print 'Food list : {}'.format(foodList)
foodList = zip(*foodList)
#print 'Modified : {}'.format(foodList)
# First set up the figure, the axis, and the plot element we want to animate
fig = plt.figure()
ax = plt.axes(xlim=(0, xMax), ylim=(0, yMax))
def _get_average_income(self, env: Environment) -> float:
""" 平均所得を取得 """
return env.get_average_income()
def _get_tax_revenue(self, env: Environment) -> float:
""" Environment の税収を取得 """
return env.get_tax_revenue()
def _get_finance(self, env: Environment) -> float:
""" Environment の経済力を取得 """
return env.get_finance()
def _get_average_mental_strength(self, env: Environment) -> float:
""" 平均メンタル値を取得 """
return env.get_average_mental_strength()
import numpy as np
import random
import sys
sys.path.append("..")
from matplotlib import pyplot as plt
from matplotlib import animation
from pylab import *
from Animat import Animat
from Environment.Environment import Environment
# Initialize an Animat
xMax = 20
yMax = 20
env = Environment(xMax, yMax, 10, 10)
animat = Animat(10, 10, xMax, yMax,env)
env.initializeWeb()
env.generateFood(15, 10,4,16,16)
foodList =[]
for e in env.foodList:
foodList.append((e.x,e.y))
#print 'Food list : {}'.format(foodList)
foodList = zip(*foodList)
#print 'Modified : {}'.format(foodList)
# First set up the figure, the axis, and the plot element we want to animate
fig = plt.figure()
ax = plt.axes(xlim=(0, xMax), ylim=(0, yMax))
import numpy as np
import random
import sys
sys.path.append("..")
from matplotlib import pyplot as plt
from matplotlib import animation
from pylab import *
from Animat import Animat
from Environment.Environment import Environment
# Initialize an Animat
xMax = 20
yMax = 20
env = Environment(xMax, yMax, 10, 10)
animat = Animat(10, 10, xMax, yMax,env)
env.initializeWeb()
env.generateFood(5, 3,12,7,17)
env.generateFood(5,13,3,18,7)
foodList =[]
for e in env.foodList:
foodList.append((e.x,e.y))
#print 'Food list : {}'.format(foodList)
foodList = zip(*foodList)
#print 'Modified : {}'.format(foodList)
# First set up the figure, the axis, and the plot element we want to animate
fig = plt.figure()
ax = plt.axes(xlim=(0, xMax), ylim=(0, yMax))