def create_agents():
global sheep_slider
global wolf_slider
global num_sheep
global num_wolves
# get agent parameters from sliders
num_sheep = sheep_slider.get()
num_wolves = wolf_slider.get()
# download y and x data from web
# extract for use in positioning agents
mydata = requests.get(
'https://www.geog.leeds.ac.uk/courses/computing/practicals/python/agent-framework/part9/data.html'
)
content = mydata.text
soup = bs4.BeautifulSoup(content, 'html.parser')
mydata_y = soup.find_all(attrs={"class": "y"})
mydata_x = soup.find_all(attrs={"class": "x"})
# print(mydata_y) # Test download of y
# print(mydata_x) # Test download of x
# Create sheep within environment, using y and x classes
for i in range(num_sheep):
y = int(mydata_y[i].text)
x = int(mydata_x[i].text)
sheep.append(agentframework.Sheep(current_environment, sheep, y, x))
# print(y, x) # Test print sheep coordinates
# print()
# create wolves within environment, using y and x classes
for i in range(num_wolves):
y = int(mydata_y[num_sheep + i].text)
x = int(mydata_x[num_sheep + i].text)
wolves.append(agentframework.Wolves(sheep, y, x))
content = mydata.text
soup = bs4.BeautifulSoup(content, 'html.parser')
mydata_y = soup.find_all(attrs={"class": "y"})
mydata_x = soup.find_all(attrs={"class": "x"})
# print(mydata_y) # Test download of y
# print(mydata_x) # Test download of x
# create an environment for the agents
# NB update filename to use a different csv dataset
current_environment = Environment.create_environment('in.txt')
# Create sheep within environment, using y and x classes
for i in range(num_sheep):
y = int(mydata_y[i].text)
x = int(mydata_x[i].text)
sheep.append(agentframework.Sheep(current_environment, sheep, y, x))
# print(y, x) # Test print sheep coordinates
# print()
# create wolves within environment, using y and x classes
for i in range(num_wolves):
y = int(mydata_y[num_sheep + i].text)
x = int(mydata_x[num_sheep + i].text)
wolves.append(agentframework.Wolves(sheep, y, x))
# print(y, x) # Test print wolf coordinates
carry_on = True
# print descriptive text for user
print("Sheep are white, wolves are red")
print()
#print(td_xs)
r.close
# create fig and ax the animation function based on
fig = matplotlib.pyplot.figure(figsize=(7, 7))
ax = fig.add_axes([0, 0, 1, 1])
carry_on = True
# Make the agents fro object Sheep.
for i in range(
num_of_agents): #use the for-loop to create agents in each iterations
y = int(td_ys[i].text) #assign x,y coordinates values to agents
x = int(td_xs[i].text)
agents.append(
agentframework.Sheep(x, y, environment, agents, neighbourhood))
#Make the wolf agents.
for j in range(num_of_wolves):
wolves.append(w.wolf(x, y, wolves))
#the function animation based on
def update(frame_number):
fig.clear()
global carry_on
for j in range(num_of_wolves):
wolves[j].random_move()
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 """
"""Add raster to the environment list."""
file.close()
for i in range(num_of_sheep):
"""Generate sheep herd.
Loop through the number of sheep to be generated and add each sheep
to the herd list. Use the Sheep class from the agentframework to
create the x/y coordinates for each sheep.
The __str__ class has been overridden to print the original location
of each sheep.
"""
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))