def visualize(batteries, houses):
# Show the route in a grid
mng = plt.get_current_fig_manager()
mng.full_screen_toggle()
plt.grid()
for house in houses:
plt.plot(house.get_x(), house.get_y(),
'o', color='black', markersize=2)
# Iterate over the batteries to find the route with the corresponding house
for battery in batteries:
plt.plot(battery.get_x(), battery.get_y(),
'X', color='black', markersize=12)
for route in battery.get_routes():
# Check if the route selected is optimal, or if the house has
# a battery closer by
length = route.get_length()
optimal = True
for battery in batteries:
test = Route(route.get_house(), battery)
if test.get_length() < length:
optimal = False
if optimal:
routes = [(tup1, tup2) for tup1,
tup2 in route.get_coordinates()]
plt.plot(*zip(*routes), linewidth=1, linestyle='solid',
marker='o', markersize=1, color='blue')
plt.pause(0.1)
else:
routes = [(tup1, tup2) for tup1,
tup2 in route.get_coordinates()]
plt.plot(*zip(*routes), linewidth=1, linestyle='solid',
marker='o', markersize=1, color='red')
plt.pause(0.1)
def constraint_relaxation(batteries, houses):
"""
Keeps connecting the closest house and battery, then switches routes until
constraints are satisfied
"""
houses_local = houses
batteries_local = batteries
# distances contains a number of lists, one for each battery,
# containing tuples of houses and distances to the corresponding battery
distances = []
for battery in batteries_local:
unsorted = []
for house in houses_local:
route = Route(house, battery)
unsorted.append((route.get_length(), house))
sorted_houses = countSort2(unsorted)
distances.append(sorted_houses)
while len(houses_local) > 0:
closest = distances[0][0]
id = 0
for i in range(len(distances)):
# check the first element of eacht list if it is closer than the
# previous one
if len(distances[i]) > 0:
if distances[i][0][0] < closest[0]:
closest = distances[i][0]
id = i
# connect the closest house
batteries_local[id].connect_house(closest[1])
houses_local.remove(closest[1])
for d in distances:
for tuple in d:
if tuple[1] == closest[1]:
d.remove(tuple)
return apply_constraints(batteries_local)
def check_switch(route1, route2):
battery1 = route1.get_battery()
battery2 = route2.get_battery()
house1 = route1.get_house()
house2 = route2.get_house()
length1 = route1.get_length()
length2 = route2.get_length()
total_length1 = length1 + length2
route3 = Route(house2, battery1)
route4 = Route(house1, battery2)
length3 = route3.get_length()
length4 = route4.get_length()
total_length2 = length3 + length4
change = total_length1 - total_length2
cap_left1 = battery1.get_capacity() - battery1.get_used_cap() \
+ house1.get_output()
cap_left2 = battery2.get_capacity() - battery2.get_used_cap() \
+ house2.get_output()
if total_length2 < total_length1 and house2.get_output() \
< cap_left1 and house1.get_output() < cap_left2:
return True, change
else:
return False
def connect_greedy(batteries, houses):
"""
Goes through each battery, adding the most nearby houses if possible
"""
random.shuffle(houses)
batteries = batteries
for house in houses:
sorted_batteries = []
for battery in batteries:
route = Route(house, battery)
cap_left = battery.get_capacity() - battery.get_used_cap()
if house.get_output() < cap_left:
sorted_batteries.append((route.get_length(), battery))
if len(sorted_batteries) != 0:
sorted_batteries = countSort2(sorted_batteries)
sorted_batteries[0][1].connect_house(house)
return len(houses) == 150
def save(batteries, houses):
plt.rcParams['animation.ffmpeg_path'] = r'C:\Users\Joost Bankras\Anaconda3\Lib\site-packages\ffmpeg-20190527-3da8d04-win64-static\bin\ffmpeg.exe'
Writer = animation.writers['ffmpeg']
writer = Writer(fps=15, metadata=dict(artist='Me'), bitrate=1800)
fig2 = plt.figure()
ims = []
ims1 = []
for house in houses:
plt.plot(house.get_x(), house.get_y(),
'o', color='black', markersize=2)
# Iterate over the batteries to find the route with the corresponding house
for battery in batteries:
plt.plot(battery.get_x(), battery.get_y(),
'X', color='black', markersize=12)
for route in battery.get_routes():
# Check if the route selected is optimal, or if the house has
# a battery closer by
length = route.get_length()
optimal = True
for battery in batteries:
test = Route(route.get_house(), battery)
if test.get_length() < length:
optimal = False
if optimal:
routes = [(tup1, tup2) for tup1,
tup2 in route.get_coordinates()]
ims.append(plt.plot(*zip(*routes), linewidth=1, linestyle='solid',
marker='o', markersize=1, color='blue'))
else:
routes = [(tup1, tup2) for tup1,
tup2 in route.get_coordinates()]
ims.append(plt.plot(*zip(*routes), linewidth=1, linestyle='solid',
marker='o', markersize=1, color='red'))
ims1.append(ims)
im_ani = animation.ArtistAnimation(fig2, ims, interval=300, frames=1)
im_ani.save('im1.mp4', writer=writer)
