def enterElevator(self, distElevator):
self.accept(self.elevatorDoneEvent, self.handleElevatorDone)
self.elevator = Elevator.Elevator(self.fsm.getStateNamed('Elevator'),
self.elevatorDoneEvent, distElevator)
self.elevator.load()
self.elevator.enter()
base.localAvatar.cantLeaveGame = 1
def enterElevator(self, distElevator):
self.accept(self.elevatorDoneEvent, self.handleElevatorDone)
self.elevator = Elevator.Elevator(self.fsm.getStateNamed('Elevator'),
self.elevatorDoneEvent, distElevator)
self.elevator.load()
self.elevator.enter()
return None
return None
def enterElevator(self, distElevator):
assert (self.notify.debug('enterElevator()'))
self.accept(self.elevatorDoneEvent, self.handleElevatorDone)
self.elevator = Elevator.Elevator(self.fsm.getStateNamed("Elevator"),
self.elevatorDoneEvent, distElevator)
self.elevator.load()
self.elevator.enter()
# Disable leave to pay / set parent password
base.localAvatar.cantLeaveGame = 1
return
def add_request(self, _from, _to):
print _to
tmp = [int(x) for x in _to.split(',')]
for __to in tmp:
req = (_from, __to)
self.info_list.append('from {} to {}'.format(_from, __to))
Elevator.REQUESTS.append(req)
self.from_entry.delete(0, END)
self.to_entry.delete(0, END)
self.text.configure(state='normal')
self.text.delete("1.0", END)
for item in self.info_list:
self.text.insert("1.0", item+"\n")
self.text.configure(state='disable')
Elevator.call(_from, _to)
def __init__(self, n_floors, n_elevators, instruction_filename):
self.elevators = []
self.requests = []
self.cleanup = False
self.instruction_filename = instruction_filename
self.tick_number = 0
self.request_id = 0
for _ in range(n_elevators):
self.elevators.append(Elevator(0))
def __init__(self, gpioController, config):
self._gpioController = gpioController
self._config = config
self._elevator = Elevator.Elevator(self._config, self._gpioController)
self._gripper = Gripper.Gripper(self._gpioController, self._config)
self._servoRotate = Servo.ServoDS3218_270(self._gpioController, self._config.servo_rotate.gpio)
self._recordPlayer = RecordPlayer.RecordPlayer(self._gpioController, self._config.record_player.gpio_start, self._config.record_player.gpio_stop, self._config.record_player.gpio_light_barrier)
self._lock = RLock()
self._ready = False
self.ROTATE_0 = self._config.servo_rotate.rotate_0
self.ROTATE_180 = self._config.servo_rotate.rotate_180
self.HOME_TO_BASE = self._config.elevator.home_to_base
self.FLIPPED_DELTA = self._config.elevator.flipped_delta
def testElevator(opMode, fileName):
""" module to load data from file and run elevator for testing
"""
if opMode.lower() != 'a' and opMode.lower() != 'b':
raise Exception('Incorrect operation node ' + opMode +
'. a and b are the only valid modes.')
else:
try:
with open(fileName, 'r') as openFl:
for trips in openFl.read().splitlines():
elevator = Elevator.Elevator(opMode,
trips.split(':')[0],
trips.split(':')[1])
except IOError:
raise Exception('Could not read file:', openFl)
except Exception as e: # catch all errors
raise Exception(traceback.format_exc())
def initialize(people,elevators):
fileinput.close()
file=fileinput.input("data.txt") # pull file with data on it
# assign people to the array with each entry as a line in the file
for i in file:
people+=[re.split(',|\n',i)] # split each line at ',' and \n
# split at \n causes blank element
if len(people[fileinput.lineno()-1])==4:
people[fileinput.lineno()-1].pop(3) # removes blank element
fileinput.close() # closes file to allow for rerun and rethread
for i in range(len(people)):
people[i][0]=float(people[i][0]) # float time
people[i][1]=int(people[i][1]) # int floors
people[i][2]=int(people[i][2])
# if any elevators in list, remove and replace with new elevators
for i in range(2,-1,-1):
if i < len(elevators):
elevators.pop(i)
for i in range(3):
elevators += [Elevator.Elevator(4+i,0,[],(width/2-58+43*i),\
height,dt,len(people)/people[len(people)-1][0])]
def next_scenario(self):
# Decide the elevator's next direction when it is IDLE
if len(Elevator.REQUESTS) == 0 and len(Elevator.IN_ELEVATOR) == 0:
Elevator.DIRECTION = Elevator.IDLE
elif Elevator.DIRECTION == Elevator.IDLE:
time.sleep(2)
if Elevator.has_from_request_from_upper_floor():
Elevator.DIRECTION = Elevator.UP
elif Elevator.has_to_request_from_upper_floor():
Elevator.DIRECTION = Elevator.UP
elif Elevator.has_from_request_from_lower_floor():
Elevator.DIRECTION = Elevator.DOWN
elif Elevator.has_to_request_from_lower_floor():
Elevator.DIRECTION = Elevator.DOWN
Elevator.move()
# Detect if there is anyone wanna embark the elevator on current floor
if any([req for req in Elevator.REQUESTS if req[0] == Elevator.CURRENT_FLOOR]):
temp = [req for req in Elevator.REQUESTS if req[0] == Elevator.CURRENT_FLOOR]
Elevator.REQUESTS = [req for req in Elevator.REQUESTS if req not in temp]
Elevator.DIRECTION = Elevator.IDLE
if len(temp) > 0:
for req in temp:
Elevator.IN_ELEVATOR.append(req)
# Detect if there is anyone wanna disembark the elevator on current floor
if any([req for req in Elevator.IN_ELEVATOR if req[1] == Elevator.CURRENT_FLOOR]):
Elevator.DIRECTION = Elevator.IDLE
Elevator.IN_ELEVATOR = \
[req for req in Elevator.IN_ELEVATOR if req[1] != Elevator.CURRENT_FLOOR]
self.set_indicator(Elevator.DIRECTION)
self.set_right_canvas(Elevator.CURRENT_FLOOR)
self.after(Ele.REFRESH_RATE, lambda: self.next_scenario())
count = 2
# %%
ret = start(user, problem, count)
token = ret['token']
print('Token for %s is %s' % (user, token))
# %%
request = oncalls(token)
# %%
print(request)
# %%
requestList = []
elevatorList = [Elevator.Elevator(i) for i in range(2)]
callDict = {}
# %%
Update(request, elevatorList, callDict)
# %%
commandList = []
takenIds = []
for call in callDict.values():
minDist = math.inf
elevatorId = None
for elevator in elevatorList:
if len(elevator.passengers) > 0 or elevator.id in takenIds:
continue
#!/usr/bin/python
import getch
import Elevator as Elevator
print("DiskRobot")
diskElevator = Elevator.Steuerung()
diskElevator.info()
while True:
print("\ncommands are:")
print(" f = stepForward")
print(" b = stepBackward")
print(" c = calibrate")
print(" i = info")
print(" q = quit")
command = raw_input("command:")
#quit
if command == "q":
diskElevator.dispose()
break
#info
if command == "i":
diskElevator.info()
#calibrate
if command == "c":
diskElevator.calibrate()
if savestatus['stage'] == 1:
save()
print("As you walk down the hill the rocks beneath your feet collapse,\nyou fall a short distance but suffer no harm. There's just no going back")
time.sleep(2)
print("There is a small pond with water, do you want to drink?")
des = input('Y/N ')
while des not in "yYnN10" or des == '':
print("Invalid input.")
des = input('Y/N ')
if des == 'Y' or des == 'y':
print("\nThe water doesn't have any taste, but you feel refreshed.\n")
time.sleep(2)
print("You continue walking down the cave and stumble upon a bizarre elevator.\nIt is covered in vines, the chamber is illuminated by glowing mushrooms.")
time.sleep(2)
# Pending elevator implementation
Elevator.daElevaturr()
savestatus['stage'] = 2
time.sleep(1)
#Puzzle elevator handling
while (savestatus['stage'] > 9 and savestatus['stage'] < 20) or savestatus['stage'] == 2:
#Main elevator chamber
if savestatus['stage'] == 2:
lights = (savestatus['completed'] if savestatus['completed'] < 1 else savestatus['completed'] - 1)
print("There are %s button(s) glowing.\n" % (3 - lights))
#Path to Luis' puzzle
print("The 4th button is glowing." if savestatus['kpuzzle'] == 3 else "The 4th button is dark.")
print("The 6th button is glowing." if savestatus['wpuzzle'] == 3 else "The 6th button is dark.")
print("The 9th button is glowing." if savestatus['rtpuzzle'] == 3 else "The 9th button is dark.")
from GlobalConfig import GlobalConfig
if __name__ == "__main__":
config = GlobalConfig()
with GlobalGPIO.GlobalGPIO() as gpio:
gripper = Gripper.Gripper(gpio, config)
gripper.release()
# sleep(2)
# gripper.grip()
# sleep(2)
# gripper.release()
elevator = Elevator.Elevator(config, gpio)
elevator.gotoHome()
HOME_TO_BASE = 100000
FLIPPED_DELTA = 18000
servo_rotate = Servo.ServoDS3218_270(gpio, 17)
# gripper.grip()
ROTATE_0 = 185.5
ROTATE_180 = 6
# slowly
def create_graph(netlist_list, average_over_X_repeats, methods, type, standardOn=True):
salt = str(randint(0,20000000))
for net in netlist_list:
filename = "netlist_" + str(net) +"_" + str(methods) + str(type) + "repeats_is_" + str(average_over_X_repeats) + "salt_is" + salt + ".png"
textfilename = "netlist_" + str(net) +"_" + str(methods) + str(type) + "repeats_is_" + str(average_over_X_repeats) + "salt_is" + salt + ".txt"
textfile = open(textfilename, 'w')
fig, ax = plt.subplots()
if "ppa" in methods and "elev" in type:
ppa_results = [None]*average_over_X_repeats
if "hill" in methods and "elev" in type:
helev_results = [None]*average_over_X_repeats
if "decrmut" in methods:
decrmut_results = [None]*average_over_X_repeats
if "hill" in methods and "ash" in type:
ashclimber_results = [None]*average_over_X_repeats
for method in methods:
if method == "ppa" and type == "elev":
#line length plot
for k in range(average_over_X_repeats):
print("generation "+str(k))
print("repeat number", k, "of netlist", net)
ppa_results[k] = ppa.PPA_data(net)
ppa_iteration_sizes = [0]*average_over_X_repeats
for k in range(average_over_X_repeats):
ppa_iteration_sizes[k] = len(ppa_results[k][0])-1
ppa_average_lengths = [0]*min(ppa_iteration_sizes)
for k in range(average_over_X_repeats):
for i in range(len(ppa_average_lengths)):
ppa_average_lengths[i] += ppa_results[k][0][i]
ppa_iteration_sizes.sort()
for k in range(len(ppa_average_lengths)):
print("ok")
if k == ppa_iteration_sizes[0]:
del ppa_iteration_sizes[0]
print(ppa_iteration_sizes)
ppa_average_lengths[k] = ppa_average_lengths[k]/len(ppa_iteration_sizes)
ax.plot(ppa_average_lengths, 'b')
# generation point plot
ppa_generation_amount = [0]*average_over_X_repeats
for k in range(average_over_X_repeats):
ppa_generation_amount[k] = len(ppa_results[k][1])
ppa_average_generation_points = [0]*max(ppa_generation_amount)
for k in range(average_over_X_repeats):
for i in range(len(ppa_results[k][1])-1):
ppa_average_generation_points[i] += ppa_results[k][1][i]
for i in range(len(ppa_average_generation_points)-1):
ppa_average_generation_points[i] = ppa_average_generation_points[i]/average_over_X_repeats
for xc in ppa_average_generation_points:
ax.axvline(x=xc, color='g')
#earliest/average first constraint satisfaction
first_constraint_satisfaction_list = []
for k in range(average_over_X_repeats):
first_constraint_satisfaction_list.append(ppa_results[k][2])
# for earliest use min(...), for average use sum(...)/average_over..
# ax.axhline(sum(first_constraint_satisfaction_list)/average_over_X_repeats, color='y')
#data
best_heights = []
for k in range(average_over_X_repeats):
best_heights.append(ppa_results[k][4])
best_lengths = []
for k in range(average_over_X_repeats):
best_lengths.append(ppa_results[k][5])
best_orders = []
for k in range(average_over_X_repeats):
best_orders.append(ppa_results[k][3])
combined_height_order = []
for k in range(average_over_X_repeats):
combined_height_order.append([best_heights[k], best_orders[k]])
#sort
best_lengths, combined_height_order = (list(x) for x in zip(
*sorted(zip(best_lengths, combined_height_order),
key=lambda pair: pair[0])))
ppa_first_csa = min(first_constraint_satisfaction_list)
best_height = combined_height_order[0][0]
best_order = combined_height_order[0][1]
best_length = best_lengths[0]
ppa_text = "for netlist " + str(net) + ", using the plant propagation algorithm + elevator, the constraint was first satisfied at " + str(ppa_first_csa) +"\n" + \
"the best order is: " + str(best_order) + "\n" + \
"the best height is: " + str(best_height) + "\n" + \
"the best length is: " + str(best_length) + "\n"
textfile.write(ppa_text)
if method == "ppa" and type == "ash":
#line length plot
for k in range(average_over_X_repeats):
print("repeat number", k, "of netlist", net)
ppa_results[k] = ash.PPA_data(net)
ppa_iteration_sizes = [0]*average_over_X_repeats
for k in range(average_over_X_repeats):
ppa_iteration_sizes[k] = len(ppa_results[k][0])-1
ppa_average_lengths = [0]*min(ppa_iteration_sizes)
for k in range(average_over_X_repeats):
for i in range(len(ppa_average_lengths)):
ppa_average_lengths[i] += ppa_results[k][0][i]
ppa_iteration_sizes.sort()
for k in range(len(ppa_average_lengths)):
print("ok")
if k == ppa_iteration_sizes[0]:
del ppa_iteration_sizes[0]
print(ppa_iteration_sizes)
ppa_average_lengths[k] = ppa_average_lengths[k]/len(ppa_iteration_sizes)
ax.plot(ppa_average_lengths, 'b')
# generation point plot
ppa_generation_amount = [0]*average_over_X_repeats
for k in range(average_over_X_repeats):
ppa_generation_amount[k] = len(ppa_results[k][1])
ppa_average_generation_points = [0]*max(ppa_generation_amount)
for k in range(average_over_X_repeats):
for i in range(len(ppa_results[k][1])-1):
ppa_average_generation_points[i] += ppa_results[k][1][i]
for i in range(len(ppa_average_generation_points)-1):
ppa_average_generation_points[i] = ppa_average_generation_points[i]/average_over_X_repeats
for xc in ppa_average_generation_points:
ax.axvline(x=xc, color='g')
#data
best_lengths = []
for k in range(average_over_X_repeats):
best_lengths.append(ppa_results[k][4])
best_orders = []
for k in range(average_over_X_repeats):
best_orders.append(ppa_results[k][3])
#sort
best_lengths, best_orders = (list(x) for x in zip(
*sorted(zip(best_lengths, best_orders),
key=lambda pair: pair[0])))
best_order = best_orders[0]
best_length = best_lengths[0]
ppa_text = "for netlist " + str(net) + ", using the A star heatmap + plant propagation algorithm, \n" + \
"the best order is: " + str(best_order) + "\n" + \
"the best length is: " + str(best_length) + "\n"
textfile.write(ppa_text)
if method == "hill" and type == "elev":
for k in range(average_over_X_repeats):
helev_results[k] = eh.hill_climber_data(net)
# line length plot
iteration_amount = len(helev_results[0][0])-1
helev_average_lengths = [0]*iteration_amount
for k in range(average_over_X_repeats):
for i in range(len(helev_results[k][0]) - 1):
helev_average_lengths[i] += helev_results[k][0][i]
for k in range(len(helev_average_lengths)):
helev_average_lengths[k] = helev_average_lengths[k] / average_over_X_repeats
ax.plot(helev_average_lengths)
# earliest/average first constraint satisfaction
first_constraint_satisfaction_list = []
for k in range(average_over_X_repeats):
first_constraint_satisfaction_list.append(
helev_results[k][1])
# for earliest use min(...), for average use sum(...)/average_over..
#ax.axhline(sum(
# first_constraint_satisfaction_list) / average_over_X_repeats,
# color='g')
# data possibilities
best_heights = []
for k in range(average_over_X_repeats):
best_heights.append(helev_results[k][3])
best_lengths = []
for k in range(average_over_X_repeats):
best_lengths.append(helev_results[k][4])
best_orders = []
for k in range(average_over_X_repeats):
best_orders.append(helev_results[k][2])
combined_height_order = []
for k in range(average_over_X_repeats):
combined_height_order.append(
[best_heights[k], best_orders[k]])
# sort
best_lengths, combined_height_order = (list(x) for x in zip(
*sorted(zip(best_lengths, combined_height_order),
key=lambda pair: pair[0])))
helev_first_csa = min(first_constraint_satisfaction_list)
best_height = combined_height_order[0][0]
best_order = combined_height_order[0][1]
best_length = best_lengths[0]
helev_text = "for netlist " + str(
net) + ", using the hillclimber + elevator algorithm, the constraint was first satisfied at " + str(
helev_first_csa) + "\n" + \
"the best order is: " + str(best_order) + "\n" + \
"the best height is: " + str(best_height) + "\n" + \
"the best length is: " + str(best_length) + "\n"
textfile.write(helev_text)
if method == "hill" and type == "ash":
for k in range(average_over_X_repeats):
ashclimber_results[k] = ash.hill_climber_data(net)
print("ok")
# line length plot
iteration_amount = len(ashclimber_results[0][0])-1
ashclimber_average_lengths = [0]*iteration_amount
for k in range(average_over_X_repeats):
for i in range(len(ashclimber_results[k][0]) - 1):
ashclimber_average_lengths[i] += ashclimber_results[k][0][i]
for k in range(len(ashclimber_average_lengths)):
ashclimber_average_lengths[k] = ashclimber_average_lengths[k] / average_over_X_repeats
ax.plot(ashclimber_average_lengths)
# earliest/average first constraint satisfaction
first_constraint_satisfaction_list = []
for k in range(average_over_X_repeats):
first_constraint_satisfaction_list.append(
ashclimber_results[k][1])
# for earliest use min(...), for average use sum(...)/average_over..
#ax.axhline(sum(
# first_constraint_satisfaction_list) / average_over_X_repeats,
# color='g')
# data possibilities
best_lengths = []
for k in range(average_over_X_repeats):
best_lengths.append(ashclimber_results[k][2])
best_orders = []
for k in range(average_over_X_repeats):
best_orders.append(ashclimber_results[k][1])
# sort
best_lengths, combined_height_order = (list(x) for x in zip(
*sorted(zip(best_lengths, best_orders),
key=lambda pair: pair[0])))
best_order = best_orders[0]
best_length = best_lengths[0]
helev_text = "for netlist " + str(
net) + ", using the A star heatmap + hillclimber algorithm," + "\n" + \
"the best order is: " + str(best_order) + "\n" + \
"the best length is: " + str(best_length) + "\n"
textfile.write(helev_text)
if method == "decrmut":
for k in range(average_over_X_repeats):
decrmut_results[k] = eh.decreasing_mutations(net)
#line length plot
decrmut_iteration_sizes = [0]*average_over_X_repeats
for k in range(average_over_X_repeats):
decrmut_iteration_sizes[k] = len(decrmut_results[k][0])-1
decrmut_average_lengths = [0]*min(decrmut_iteration_sizes)
for k in range(average_over_X_repeats):
for i in range(len(decrmut_average_lengths)):
decrmut_average_lengths[i] += decrmut_results[k][0][i]
decrmut_iteration_sizes.sort()
for k in range(len(decrmut_average_lengths)-0):
while k > decrmut_iteration_sizes[0]:
del decrmut_iteration_sizes[0]
decrmut_average_lengths[k] = decrmut_average_lengths[k]/len(decrmut_iteration_sizes)
ax.plot(decrmut_average_lengths)
# generation point plot
decrmut_generation_amount = [0]*average_over_X_repeats
for k in range(average_over_X_repeats):
decrmut_generation_amount[k] = len(decrmut_results[k][1])
decrmut_average_generation_points = [0]*max(decrmut_generation_amount)
for k in range(average_over_X_repeats):
for i in range(len(decrmut_results[k][1])-1):
decrmut_average_generation_points[i] += decrmut_results[k][1][i]
for i in range(len(decrmut_average_generation_points)-1):
decrmut_average_generation_points[i] = decrmut_average_generation_points[i]/average_over_X_repeats
#for xc in decrmut_average_generation_points:
# ax.axvline(x=xc, color='c')
#earliest/average first constraint satisfaction
first_constraint_satisfaction_list = []
for k in range(average_over_X_repeats):
first_constraint_satisfaction_list.append(decrmut_results[k][2])
# for earliest use min(...), for average use sum(...)/average_over..
#ax.axhline(sum(first_constraint_satisfaction_list)/average_over_X_repeats, color='m')
#data possibilities
best_heights = []
for k in range(average_over_X_repeats):
best_heights.append(decrmut_results[k][4])
best_lengths = []
for k in range(average_over_X_repeats):
best_lengths.append(decrmut_results[k][5])
best_orders = []
for k in range(average_over_X_repeats):
best_orders.append(decrmut_results[k][3])
combined_height_order = []
for k in range(average_over_X_repeats):
combined_height_order.append([best_heights[k], best_orders[k]])
#sort
best_lengths, combined_height_order = (list(x) for x in zip(
*sorted(zip(best_lengths, combined_height_order),
key=lambda pair: pair[0])))
decrmut_first_csa = min(first_constraint_satisfaction_list)
best_height = combined_height_order[0][0]
best_order = combined_height_order[0][1]
best_length = best_lengths[0]
decrmut_text = "for netlist " + str(
net) + ", using the decreasing_mutations algorithm, the constraint was first satisfied at " + str(
decrmut_first_csa) + "\n" + \
"the best order is: " + str(best_order) + "\n" + \
"the best height is: " + str(best_height) + "\n" + \
"the best length is: " + str(best_length) + "\n"
textfile.write(decrmut_text)
if standardOn:
standard_elevator_solution = el.return_value_elevator(net)
ax.axhline(standard_elevator_solution[1], color='r')
standard_solution = standard_elevator_solution[2]
standard_solution_height = standard_elevator_solution[0]
repAstarOrder_text = "for netlist " + str(
net) + ", using the decreasing a* order algorithm" + "\n" + \
"the resulting length is: " + str(
standard_elevator_solution[1]) + "\n" + \
"the resulting height is: " + str(
standard_solution_height) + "\n" + \
"the resulting wire order is: " + str(
standard_solution) + "\n"
textfile.write(repAstarOrder_text)
plt.ylabel('length')
plt.xlabel('iterations')
fig.savefig(filename)
from Elevator import *
from Floor import *
#The requests are at the same time.
p1 = {'orig': 1, 'dest': 5 }
p2 = {'orig': 2, 'dest': 3 }
p3 = {'orig': 2, 'dest': 4 }
p4 = {'orig': 3, 'dest': 4 }
p5 = {'orig': 3, 'dest': 1 }
p6 = {'orig': 5, 'dest': 1 }
number_of_floors = 5
requests = [p1, p2, p3, p4, p5, p6]
groupings = {}
floors = []
elevator = Elevator(number_of_floors)
#Let us create arbitrary floors
#Assume we have 5 floors
for i in range(1, number_of_floors+1):
floors.append(Floor(i))
#Register origin requests
for i in requests:
floors[i['orig']-1].status = True
#Group destination requests
for i in requests:
for key, value in i.items():
groupings.setdefault(key, []).append(value)
import sys, os
path = os.path.abspath(os.path.join(os.path.dirname(__file__)))
sys.path.append(path + "/elevator")
sys.path.append(path)
import Elevator, States
elevator = Elevator.Elevator(States.Open())
elevator.close()
elevator.move()
elevator.stop()
elevator.open()
try:
elevator.move()
except Elevator.IllegalStateTransition as err:
print("can't change to state " + str(err) + " from state",
elevator.get_state())
elevator.close()
elevator.move()