def __init__(self, settings_file):
Simple.__init__(self, settings_file)
self.on_string = "on"
self.off_string = "off"
self.get_status()
def __init__(self,settings_file):
Simple.__init__(self,settings_file)
self.on_string = "on"
self.off_string = "off"
self.get_status()
def _import_other_to_create_simple(self):
other_mod = self._import( 'enthought.traits.tests.other', object_name='Other')
other_klass = other_mod.__getattribute__('Other')
simple = Simple(name='simon')
other = other_klass(name='other')
simple.other = other
self.failUnless( simple.other is other )
simple2 = Simple(name='simon')
other2 = other_klass(name='other')
simple2.other = other2
self.failUnless( simple2.other is other2 )
return simple
def solve(file):
start = datetime.now()
# Rows, Columns, Vehicles, Rides, Bonus, Max Time
R, C, F, N, B, T, rides = read_file('./input/' + file + '.in')
vehicles = [Vehicle() for i in range(F)]
# Start solution here:
vehicles = [Vehicle() for i in range(F)]
simple = Simple(rides, vehicles)
vehicles = simple.simple3(B, T)
now = datetime.now()
write_file(
"./output/" + file + " - " + str(now.hour) + 'h' + str(now.minute) +
'm' + str(now.second) + "s.out", vehicles)
print 'runtime: ' + str(datetime.now() - start)
def _import_other_to_create_simple(self):
other_mod = self._import('enthought.traits.tests.other',
object_name='Other')
other_klass = other_mod.__getattribute__('Other')
simple = Simple(name='simon')
other = other_klass(name='other')
simple.other = other
self.failUnless(simple.other is other)
simple2 = Simple(name='simon')
other2 = other_klass(name='other')
simple2.other = other2
self.failUnless(simple2.other is other2)
return simple
def test_simple_add(self):
s = Simple()
assert s.add(1, 1) == 2
from simple import Simple
from os import environ as env
from posixpath import join as pathjoin
import shlex
import os
if __name__ == '__main__':
env['RABBITMQ_BASE'] = env['VIP_PROJECT_ROOT']
env['RABBITMQ_LOG_BASE'] = env['VIP_RABBITMQ_LOG_DIR']
env['RABBITMQ_MNESIA_BASE'] = env['VIP_RABBITMQ_MNESIA_BASE']
env['HOMEDRIVE'] = env['VIP_RABBITMQ_BASE_DRIVE']
env['HOMEPATH'] = env['VIP_RABBITMQ_BASE_PATH']
env['RABBITMQ_PID_FILE'] = env['VIP_RABBITMQ_PID_FILE']
env['ERLANG_HOME'] = env['VIP_RABBITMQ_ERLANG_HOME']
if not os.path.exists(env['VIP_RABBITMQ_LOG_DIR']):
os.mkdir(env['VIP_RABBITMQ_LOG_DIR'])
Simple().run([
'-o',
pathjoin(env['VIP_RABBITMQ_LOG_DIR'], 'rabbitmq_out.log'), '-e',
pathjoin(env['VIP_RABBITMQ_LOG_DIR'], 'rabbitmq_err.log'), '-p',
pathjoin(env['VIP_INIT_DIR'], 'rabbitmq.pid'), 'rabbitmq-server.bat'
])
import pickle
#from document import Document
from simple import Simple
from simple import Complex
newDoc = Simple("somedoc")
print newDoc.__dict__
newDoc2 = Complex("someotherdoc")
newDoc2.setSimple(newDoc)
fo = open("newdoc.txt", "wb")
fo.write(pickle.dumps(newDoc2))
fo.close()
print pickle.dumps(newDoc2)
def main():
#Read config.ini file
config_object = ConfigParser()
init_file = os.path.join(os.path.dirname(os.path.abspath(__file__)),
'config.ini')
config_object.read(init_file)
# The file in which the data will be written into
output_file_name = config_object.get("SETTINGS", "output_file_name")
# Number of different scenarios to run
num_of_iter = int(config_object.get("SETTINGS", "num_of_iter"))
# Simulation time factor which is set in the settings.json file of AirSim
sim_time_factor = int(config_object.get("SETTINGS", "sim_time_factor"))
# The malicious behaviour type
anomaly_type = config_object.get("SETTINGS", "anomaly_type")
# If True, after getting the data it will get tested and updated by 'test.py' script
active_data_test = config_object.get("SETTINGS", "active_data_test")
# Time until next_action() and has_ended() is called again
update_cycle_time = 0.1 / sim_time_factor
# headers for csv file
data_keys = [
'drone', 'update_step', 'iter', 'script_time', 'sim_time', 'latitude',
'longitude', 'altitude', 'angular_acceleration_x',
'angular_acceleration_y', 'angular_acceleration_z',
'angular_velocity_x', 'angular_velocity_y', 'angular_velocity_z',
'linear_acceleration_x', 'linear_acceleration_y',
'linear_acceleration_z', 'linear_velocity_x', 'linear_velocity_y',
'linear_velocity_z', 'orientation_x', 'orientation_y', 'orientation_z',
'position_x', 'position_y', 'position_z', 'collision', 'label'
]
data = {data: [] for data in data_keys}
drones = ["Drone1", "Drone2", "Drone3", "Drone4", "Drone5"]
# Connect to the regular client
client = airsim.MultirotorClient()
client.confirmConnection()
# Connect to the Monitor's client which is used by the monitor function
client_monitor = airsim.MultirotorClient()
client_monitor.confirmConnection()
[client_monitor.enableApiControl(True, drone) for drone in drones]
[client_monitor.armDisarm(True, drone) for drone in drones]
# Dictionary of values that describe the current iteration state
# It is used by the monitor function
values = {
"i": 0,
"update_step": 0,
"start": 0,
"is_anomaly": False,
"malicious": None,
"collision": None
}
# Start the scenarios - each iteration is a new scenario
for i in range(num_of_iter):
[client.enableApiControl(True, drone) for drone in drones]
[client.armDisarm(True, drone) for drone in drones]
print(f'Iteration: {i}')
values["i"] = i
# On the first iteration, the drones need to take off first
if i == 0:
[client.takeoffAsync(vehicle_name=drone) for drone in drones]
time.sleep(6)
# Randomly choose a malicious drone
malicious = random.sample(drones, 1)[0]
values["malicious"] = malicious
# After time_till_anoamly passes, the malicious drone starts acting maliciously
time_till_anomaly = np.random.uniform(10, 15) / sim_time_factor
print(f'starting new scenario with malicious: {malicious}')
# Drones' initial positions which are also set in the settings.json file of AirSim
initial_positions = ([[2, 0, -2], [4, 0, -2], [6, 0, -2], [8, 0, -2],
[10, 0, -2]])
# Optional : use trace line to see the routes of the drones
[client.simSetTraceLine([0.0], 20.0, drone) for drone in drones]
# Creating the avoidance scenario class
scenario = Simple(client, drones, initial_positions, malicious,
anomaly_type, sim_time_factor)
# Get the beginning time for later measures
start = time.perf_counter()
values["start"] = start
values["update_step"] = 0
time_from_beginning = 0
# When has_ended is True, the scenario will end
has_ended = False
# When is_anomaly is True, the malicious behaviour will start
is_anomaly = False
values["is_anomaly"] = False
time.sleep(0.5)
# Create the RepeatedTimer class with the monitor function, which monitors the scenario data
# By creating the object, the function starts running and repeats itself every 0.05 seconds
rt = RepeatedTimer(0.05, monitor, data, drones, client_monitor, values)
while not has_ended:
record_time = time.perf_counter()
# Call the next action of the drones, which gets them to recalculate their movement
scenario.next_action()
# Check if the scenario has ended
has_ended = scenario.has_ended()
# Check if a collision has occured
values["collision"] = scenario.get_collision()
# If enough time has passed, the anomaly begins
if time_from_beginning > time_till_anomaly and anomaly_type != "none" and not is_anomaly:
print("starts anomaly")
is_anomaly = True
values["is_anomaly"] = True
# Optional - set the malicious drone's path to have another color
client.simSetTraceLine([1.0], 20.0, malicious)
# If the anomaly has started, call the malicious behavior function
if is_anomaly:
scenario.next_action_anomaly()
# calculating the time that passed since the beginning of the scenario
current = time.perf_counter()
time_from_beginning = current - start
values["update_step"] += 1
# If not enough time has passed until the next action should happen, sleep
try:
time.sleep(update_cycle_time - (current - record_time))
except:
print("passing")
# When the scenario ends, the RepeatedTimer stops recording and the client resets
rt.stop()
client.reset()
# Disconnect from the client
[client.armDisarm(False, drone) for drone in drones]
[client.enableApiControl(False, drone) for drone in drones]
print('finished mission')
# Write the data to the output file
data_df = pd.DataFrame.from_dict(data)
data_df.to_csv(output_file_name, index=False)
if active_data_test == "True":
test_data(output_file_name)
