def setup():
#this is done to allow for connection with scale bar
global num_of_agents
#global allows to be seen outside of def function, agents=sheep
num_of_agents = scale_sheep.get()
#number of agents, connecting with scale bar
global num_of_wolves
#number of wolves
num_of_wolves = scale_wolves.get()
#set number of wolves
global wolves
#make wolves global
wolves = []
#makes wolves list
global agents
#makes agents global
agents = []
# Make the agents list
for i in range(num_of_agents):
#setting x y for sheep
y = int(td_ys[i].text)
#grabing text from html
x = int(td_xs[i].text)
#grabing text from html
agents.append(agentframework.Agent(environment, agents, wolves, x, y))
#connects agents to the environment, and grabs from framework
#print(agents[i])
for i in range(num_of_wolves):
#seeting up num of wolves
x = random.randint(150, 199)
#seting wolves random starting x coordinate
y = random.randint(0, 50)
#setting agents random y starting points
wolves.append(agentframework.Wolf(environment, wolves, agents, x, y))
carry_on = True # boolean for stopping functions
fig = plt.figure(figsize=(7, 7))
ax = fig.add_axes([0, 0, 1, 1])
env_total = sum(sum(x) for x in environment) # sum of all values in environment
counter = 0 # counter for num_of_iterations
agents_pop = []
infants_pop = []
# make the agents
for i in range(num_of_agents):
agents.append(agentframework.Agent(environment,
neighbourhood))
# make the wolves
for i in range(num_of_wolves):
wolves.append(agentframework.Wolf(environment,
neighbourhood))
# update function
def update(misc):
"""
Update function to be called at each frame, actions include:
Agents and wolves will be made to interact with the environment and themselves
Stopping conditions will be assessed
Environment, wolves and agents will be plotted
"""
fig.clear()
global carry_on
global counter
"""
herd.append(af.Sheep(environment,herd))
herd[i].__str__()
"""Print original location of each sheep."""
#: Make the wolves
for j in range(num_of_wolves):
"""Generate wolves.
Loop through the number of wolves to be generated and add each wolf
to the list of wolves. Use the Wolf class from the agentframework to
create the x/y coordinates for each wolf.
"""
wolves.append(af.Wolf(wolves))
#: Generate plot layout (figure)
fig =plt.figure(figsize=(7, 7))
"""Figure: Define figure size."""
ax = fig.add_axes([0, 0, 1, 1])
"""Axes: Define figure axes."""
fig.patch.set_facecolor('#dedede')
"""Set figure background color to grey."""
def update(frame_number):
"""Update the model"""
fig.clear()
"""Clear figure before rebuilding it."""
def update(frame_number):
"""Update the model"""
fig.clear()
"""Clear figure before rebuilding it."""
for j in range(num_of_iterations):
try:
for j in range(len(wolves)):
"""Loop through the list of wolves."""
wolves[j].wolves = rnd.sample(wolves[j].wolves, k=len(wolves[j].wolves))
wolves[j].hunt_sheep()
"""Wolf moves to hunt sheep."""
wolves[j].starve()
"""If wolf is not able to catch sheep, it will starve"""
if wolves[j].alive == False:
""" remove dead wolves """
wolves.pop(j)
for i in range(len(herd)):
"""Loop through the sheep herd."""
herd[i].escape_wolves(wolves)
"""Sheep tries to escape wolf."""
if herd[i].alive == False:
"""Remove dead sheep."""
herd.pop(i)
else:
herd[i].herd = rnd.sample(herd[i].herd, k=len(herd[i].herd))
"""reorder sheep randomly."""
herd[i].move()
"""Sheep moves."""
herd[i].eat()
"""Sheep eats and sickens up with overeaten."""
herd[i].share_with_neighbours(neighbourhood)
if herd[i].mate():
"""If female sheep try to mate."""
herd.append(af.Sheep(environment,herd))
# control sheep population
if ctrl.new_wolves(): wolves.append(af.Wolf(wolves))
"""There is a 1% chance a new wolf is introduced."""
ctrl.disease_outbreak(herd)
""" If sheep herd exceeds 100, a disease outbreak occurs. Sheep have a 20% chance of surviving the disease."""
except IndexError:
pass
#: Map environment, sheep and wolves
pos = plt.imshow(environment,cmap='summer_r')
"""Plot environment raster."""
plt.colorbar(pos, orientation="horizontal")
"""Add color bar to the figure. """
for i in range(len(herd)):
"""Loop through the herd and plot sheep."""
plt.scatter(herd[i].x, herd[i].y,color ='white')
for j in range(len(wolves)):
"""Loop through the wolves and plot wolves."""
plt.scatter(wolves[j].x, wolves[j].y, color ='red')
#: Style plot
plt.scatter(102, 102,color ='white',label="Sheep #("+ str(len(herd)) +')')
plt.scatter(102, 102,color ='red',label="Wolf #("+ str(len(wolves)) +')')
"""Create two fakes points outside the plot area. These points will be used for the legend."""
plt.legend(loc=9, bbox_to_anchor=(0.5, -0.1),ncol=2,frameon=False)
""" Add plot legend."""
plt.xlim(0, 99)
plt.ylim(0, 99)
""" restrict plot area to 100px """
plt.suptitle('Sheep and Wolves', fontsize=20,color='#0d6d13')
plt.title('(Agent Based Model)', fontsize=12,loc='center',color='#4b4f4c')
""" Add plot title and subtitle """
num_of_wolves = 60
num_of_iterations = 100
neighbourhood = 20
zone = 10
# Setting Plots
fig = matplotlib.pyplot.figure(figsize=(7, 7))
ax = fig.add_axes([0, 0, 1, 1])
# Creating sheeps and wolves
for i in range(num_of_agents):
agents.append(agentframework.Agent(environment, agents, neighbourhood))
for i in range(num_of_wolves):
wolves.append(agentframework.Wolf(agents, zone))
#Moving, eating and sharing
carry_on = True
def update(frame_number):
fig.clear()
global carry_on
if len(agents) == 0:
carry_on=False
print("stopping condition")
for j in range(len(agents)):