def create_graph():
parser = FileReader.SemEvalParser()
sent_ids = parser.get_sentences_ids_by(doc_id)
root = GraphManager.Node(doc_id)
graph = GraphManager.Graph(root=root)
# sent_ids = sent_ids[:2]
for sent_id in sent_ids:
sent_node = GraphManager.Node(sent_id)
graph.add_node(sent_node, root)
words = parser.get_instances_by(sentence=sent_id)
for node_id, word in words:
word_node = GraphManager.WordNode(identifier=node_id, word=word)
graph.add_word_node(word_node, sent_node)
senses = utils.get_sences(word)
for sense in senses:
extended_def = utils.get_extended_def(sense)
odour = convert_extended_def_to_odour(extended_def)
nest = GraphManager.NestNode(identifier=sense,
lemma=sense.lemmas()[0].key(),
odour=odour)
graph.add_nest(nest, word_node)
global vocabulary
global index
del vocabulary
del index
return graph
def DEPARTURE(self, GM, pk, index, DDMM, packetsize):
#current time
now = time.time()
pnow = time.ctime(now)
sourceID = pk.getsourceID()
destinationID = pk.getdestinationID()
# print('time in departure:', time.ctime(now))
# print("Id packet leaving")
pkID = pk.getpacketID()
# print(pk.getpacketID())
# print("generated by node ")
# print(pk.getsourceID())
#update current node
pk.updateCurrentNode(pk.getnextnodeID())
# print("leaving from node ")
# print(pk.getCurrentNode())
#update info about the packet in GM
# GM.dellstPackets(pk.getCurrentNode(), pk)
# #update size of the current node: the packet is leaving
# GM.updateSizeQueue(pk.getCurrentNode(), -1)
# print("queue size of ")
# print(pk.getCurrentNode())
## print(" is ")
# print(GM.showSizeQueue(pk.getCurrentNode()))
flowID = pk.getflowID()
print("{}-{}\t {} -> {}\t [{}] \t time DEPARTURE: {}".format(
pk.getflowID(), pk.getpacketID(), pk.getsourceID(),
pk.getdestinationID(), pk.getpath(), pnow))
alivepath = pk.getpath()
alivepk = GM.getalivepk()
# print('alive packets', alivepk)
GM.delalivepk(pk.getflowID(), pk.getpacketID())
alivepk = GM.getalivepk()
# print('alive packets', alivepk)
countpk = 0
# print('alivepath', alivepath[:-2])
for id in alivepk:
if (id[0] == flowID):
countpk += 1
if (countpk == 0):
GM.delaliveflow(flowID)
GM.delalivePaths(alivepath[:-2])
# print('countpk', countpk)
DM = DDMM.updateDemandMatrix(sourceID, destinationID, packetsize, -1)
odour1 = np.array([1, 2, 3, 4, 5])
odour2 = np.array([3, 5, 7, 8, 9, 1])
print("SIZE", odour2.size)
print(utils.lesk_similarity(odour1, odour2))
# syn = wn.synsets('monkey')[0]
#
# print(syn.lemmas()[0].key())
d = {("a", "b"): "da"}
print(d[('a', 'b')])
a = GraphManager.Node()
b = GraphManager.Node()
l = [a, b]
for node in l:
if isinstance(node, GraphManager.NestNode):
print(node.lemma)
print(set([a, b]) == set([b, a]))
print(str(None))
parser = FileReader.SemEvalParser()
sent_ids = parser.get_sentences_ids_by('d001')
sent = parser.get_instances_by(sentence=sent_ids[0])
def main(argv):
input_graph_file = None
graph_save_file = None
input_params_file = None
airport_q = 10
only_generate = False
verbosity = 5
data = None
graph = None
# Parameters
params = {
'graph' : graph,
'start_idx' : 1,
'end_idx' : 4,
'max_flights' : 150,
'cost_weight' : 2,
'time_weight' : 1,
'pop_size' : 20,
'generations' : 10,
'mutation_rate' : 0.2,
'tournament_size' : 2,
'elitism' : False,
'dest_min' : 2,
'dest_max' : 5
}
# Parse command line options
try:
opts, args = getopt.getopt(argv, "hi:s:p:a:gv:",
["ifile=", "save=", "params=", "airports=", "verbose=",
"start_idx=" ,
"end_idx=" ,
"max_flights=",
"cost_weight=",
"time_weight=",
"pop_size=" ,
"generations=",
"mutation_rate=",
"tournament_size=",
"elitism=",
"dest_min=",
"dest_max="
])
except getopt.GetoptError:
print_help()
sys.exit(2)
for opt, arg in opts:
if opt == '-h':
print_help()
sys.exit()
elif opt in ("-i", "--ifile"):
input_graph_file = arg
print('Will read data from: {}'.format(input_graph_file))
elif opt in ("-s", "--save"):
graph_save_file = arg
print('Will save graph to: {}'.format(graph_save_file))
elif opt in ("-p", "--params"):
input_params_file = arg
print('Will read params from: {}'.format(input_params_file))
elif opt in ("-a", "--airports"):
airport_q = int(arg)
print('Number of airports = {}'.format(airport_q))
elif opt in ("-g", "--generate"):
only_generate = True
print('Will just generate data')
elif opt in ("-v", "--verbose"):
verbosity = int(arg)
print('Verbosity level = {} ({})'.format(verbosity, get_verbosity_info(verbosity)))
elif opt in list("--" + x for x in params.keys()):
if opt[2:] == 'mutation_rate':
params[opt[2:]] = float(arg)
elif opt[2:] == 'elitism':
params[opt[2:]] = arg.lower() in ['true', 't', 'tak', 'yes', 'y', '1']
else:
params[opt[2:]] = int(arg)
print('Params are: \n{} \n'.format('\n'.join(' {:{}}: {}'.format(k, len(max(params.keys()))+1, v) for k,v in sorted(params.items()))))
# DataGenerator
data = DataGenerator()
DataGenerator.DESTINATIONS_MIN = params['dest_min']
DataGenerator.DESTINATIONS_MAX = params['dest_max']
if input_graph_file is not None:
data.load_saved_graph(input_graph_file)
else:
data.load_new_data(airport_q)
data.create_graph()
if graph_save_file is not None:
data.save_graph(graph_save_file)
testsuite_airports = data.get_airports()
testsuite_graph = data.get_graph()
graph = GraphManager(params['max_flights'])
graph.set_graph(testsuite_graph, testsuite_airports)
if verbosity > 1:
graph.print_airports()
graph.print_flights()
graph.print_graph()
if not only_generate:
print(' === GeneticAlgorithm tests ===')
params['graph'] = graph
GA.run_with_params(params)
mRefreshDelay = int(mConfig.get('SETTINGS', 'refreshperiod'))
mTypeGRF = int(mConfig.get('SETTINGS', 'typegrf'))
mScale = int(mConfig.get('SETTINGS', 'scale'))
mRecDir = mConfig.get('RECORDS', 'recordsdirectory')
mRecRatio = int(mConfig.get('RECORDS', 'recordratio'))
sockData = 0
sockConfig = 0
sockConfig2 = 0
mDisplayConnected = False
mIpAddr = ""
mScreen = Afficheur()
mDataManager = DataManager()
mGraphManager = GraphManager()
def dessineGraph():
mDuree = mScreen.getDuree(mScreen.getScale())
mGraphManager.setDuree(mDuree)
mGraphManager.fillGraph(mDataManager.getDataList(mDuree))
mScreen.majTendance(mDataManager.getTendance())
coordList = mGraphManager.getCoords()
th_dessineGrf = threading.Thread(target=mScreen.traceGraphe,
args=(coordList, ))
th_dessineGrf.start()
#mScreen.traceGraphe(coordList)
mRecord = 0
def GENERATE(self, GM, newpk, DDMM, packetsize):
"""
event called when a new packet is generated. It triggers
- a migration event if the next node is not the destination
- a departure event if the next node is the destination
one of this two events will occur after a specific time interval. This time interval = elaboration time + transmission time from the current node to the next node
Args:
GM =
newpk =
Returns:
"""
# print("generate")
# if(Topology[n].getSizeQueue() == 1) serve that packet in the queue
now = time.time()
pnow = time.ctime(now)
# print("Id packet arriving")
# print(pk.getpacketID())
pkID = newpk.getpacketID()
sourceID = newpk.getsourceID()
destinationID = newpk.getdestinationID()
path = newpk.getpath()
nextnodeID = path[1]
newpk.updateNextNode(pkID, nextnodeID)
print("{}-{}\t {} -> {}\t [{}] -> {} \t time GENERATION: {}".format(
newpk.getflowID(), pkID, sourceID, destinationID, path,
newpk.getnextnodeID(), pnow))
# newpk = packet(pkID, sourceID , destinationID)
GM.updatelstPackets(sourceID, newpk)
index = 1
GM.updateSizeQueue(sourceID, 1)
nodeA = sourceID
if (nextnodeID < sourceID):
nodeA = nextnodeID
nodeB = sourceID
else:
nodeB = nextnodeID
transmissionTime = random.uniform(
1, 3) #GM.getDelayEdges(nodeA, nodeB)#30#evaluateDelay()
# print('size', GM.showSizeQueue(newpk.getCurrentNode()))
# #when the packet arrive to the first desitation nodenode
# self.scheduler.enter(transmissionTime, 1, self.ARRIVAL, (GM, newpk, destinationID))
if (GM.showSizeQueue(newpk.getCurrentNode()) >=
1): #serve that packet in the queue
# print('len path', len(path))
if (index < len(path) - 3):
# print("migrate from gen")
serviceTime = 60 #exponential(1)
tempo = transmissionTime + pkID
print('migrazione dopo ', tempo)
Timer(tempo, self.MIGRATE,
(GM, newpk, index, DDMM, packetsize)).start()
else:
tempo = transmissionTime + pkID
Timer(tempo, self.DEPARTURE,
(GM, newpk, index, DDMM, packetsize)).start()
#devo considerare ogni volta il nodo successivo
#per trovare il percorso del pacchetto successivo devo considerare i percorsi dei pacchetti ancora nel sistema
generationTime = 1 #exponential(1)
def MIGRATE(self, GM, newpk, index, DDMM, packetsize):
#current time
now = time.time()
pnow = time.ctime(now)
# print('time MIGRATION:', time.ctime(now))
#when the migration occurs, the packet moves from currentNode to nextNode
#therefore, the queue size of currentNode decreases
GM.updateSizeQueue(newpk.getCurrentNode(), -1)
#update packet and oldnode information in GM
GM.dellstPackets(newpk.getCurrentNode(), newpk)
# print("previous node")
# print(newpk.getCurrentNode())
#nextNode is the new current node
currentNode = newpk.getnextnodeID()
# print("current node")
# print(currentNode)
#the queue size of the new currentNode increase
GM.updateSizeQueue(currentNode, 1)
#update packet and currentnode information in GM
GM.updatelstPackets(currentNode, newpk)
#update new current node of the packet
newpk.updateCurrentNode(newpk.getnextnodeID())
#update new nextnode
path = newpk.getpath()
# print("path")
# print(path)
# print('index', index)
newindex = index + 1
newNextNode = path[newindex]
newpk.updateNextNode(newpk.getpacketID(), newNextNode)
# print("sourceID")
# print(newpk.getsourceID())
# print("destination")
# print(newpk.getdestinationID())
# print("pkID")
# print(newpk.getpacketID())
# print('next node', newNextNode)
# print("current node queue size", GM.showSizeQueue(currentNode))
print("{}-{}\t {} -> {}\t [{}] -> {} \t time MIGRATION: {}".format(
newpk.getflowID(), newpk.getpacketID(), newpk.getsourceID(),
newpk.getdestinationID(), path, newNextNode, pnow))
nodeA = currentNode
if (newNextNode < currentNode):
nodeA = newNextNode
nodeB = currentNode
else:
nodeB = newNextNode
transmissionTime = random.uniform(
1, 3) #GM.getDelayEdges(nodeA, nodeB)#30#evaluateDelay()
# pk.removePacket(packetID)
if (GM.showSizeQueue(currentNode) >=
1): #serve the next packet in the queue
if (newNextNode == newpk.getdestinationID()):
Timer(transmissionTime, self.DEPARTURE,
(GM, newpk, newindex, DDMM, packetsize)).start()
else:
Timer(transmissionTime, self.MIGRATE,
(GM, newpk, newindex, DDMM, packetsize)).start()
def main():
parser = argparse.ArgumentParser(
description=
'Simulate run of routing strategies\n\n python RL.py <EPISODES> <GAMMA> <EPOCH> <BATCHSIZE> <BUFFER> <TOPOLOGY> <TSIM> <ROUTING> \n \n === topologies options === \n [3cycle] \n [4cycle] \n [4diag] \n [6s4hMultiSwitch] \n [Aarnet] \n [Abilene] \n \n === routing options ===\n[-rl] \t\t run reinforcement learning \n[-so] \t\t run semi-oblivious \n[-ecmp] \t run ecmp \n[-ospf] \t run ospf',
formatter_class=RawTextHelpFormatter)
parser.add_argument(
'episodes',
type=int,
help='Number of episodes to train the Reinforcement Learning algorith')
parser.add_argument('gamma', type=float, help='Discount factor')
parser.add_argument('epochs', type=int, help='Number of epochs')
parser.add_argument('batchSize',
type=int,
help='batch size of the Experience Replay buffer')
parser.add_argument(
'buffer',
type=int,
help='size of the replay buffer (for the Experience Replay)')
parser.add_argument('topology', type=str, help='Simulation topology')
parser.add_argument('simTime', type=int, help='Simulation Time')
parser.add_argument('routing', type=str, help='Routing protocol')
args = parser.parse_args()
if args.gamma > 1 or args.gamma < 0:
parser.error("gamma cannot be larger than 1 and smaller than 0")
parameters = [
args.episodes, args.gamma, args.epochs, args.batchSize, args.buffer,
args.routing, args.simTime
]
print('parameters', parameters)
initialnFlow = 3 #10 #maximum number of flows that can coexist in the system (for the training)
# RL1 = ReinforcementLearning(initialnFlow, 0)
# model, nNode, points_list, bandwidth_list, delay_list = RL1.training(parameters)
dotFormat = './topologies/' + args.topology + '.dot'
G = nx_agraph.from_agraph(pygraphviz.AGraph(dotFormat))
# pos = nx.spring_layout(G)
# nx.draw_networkx_nodes(G,pos)
# nx.draw_networkx_edges(G,pos)
# nx.draw_networkx_labels(G,pos)
labels = nx.get_edge_attributes(G, 'weight')
#topology parameters
node_name = nx.get_node_attributes(G, 'type')
print('lables', node_name)
nNode = nx.number_of_nodes(G)
print('nnode', nNode)
nHost = 0
print('nodi: ', nNode)
for attr in node_name:
# print('attr', attr)
if (attr[0] == 'h'):
nHost += 1
nSwitch = nNode - nHost
# print('nhost, nswitch', nHost, nSwitch)
#newgraph with nodes' name from 0 to nNode-1
myG = G
mapping = {}
cuonter_h = 1
cuonter_s = 1
num_h = 0
num_s = num_h + nHost
index = 0
while index < nNode:
for n in G.nodes():
if (n[0] == 's' and n[1:] == str(cuonter_s)):
mapping[n] = num_s
cuonter_s += 1
num_s += 1
index += 1
elif (n[0] == 'h' and n[1:] == str(cuonter_h)):
mapping[n] = num_h
cuonter_h += 1
num_h += 1
index += 1
myG = nx.relabel_nodes(G, mapping)
model = None
RL1 = None
if args.routing == 'rl':
#trainig RL!!
activeFlows = initialnFlow - 1
RL1 = ReinforcementLearning(initialnFlow, myG, 0)
model = RL1.training(parameters, nNode, myG, nHost, activeFlows)
# nx.draw_networkx_edge_labels(G,pos,edge_labels=labels)
# plt.show()
#save name
#save_path = 'C:/example/'
#name_of_file = raw_input("What is the name of the file: ")
#completeName = os.path.join(save_path, name_of_file+".txt")
#file1 = open(completeName, "w")
# toFile = raw_input(model)
# file1.write(toFile)
GM = GraphManager(nNode)
#start generation packet and normal simulation
packetsGen = packetsGeneration(initialnFlow)
failedRL = packetsGen.generation(GM, nNode, nHost, nSwitch, myG, model,
parameters, RL1, dotFormat)
def __init__(self, row, column, inputData = []):
self.connector = GraphManager()
self.inputData = inputData
self.outputData = []
self.row = row
self.col = column
class DataManager:
def __init__(self, row, column, inputData = []):
self.connector = GraphManager()
self.inputData = inputData
self.outputData = []
self.row = row
self.col = column
def generateZeroMatrix(self):
newMatrix = [[0 for x in range(self.row*self.col)] for y in range(self.col*self.row)]
return newMatrix
def setup(self):
adjcencyMatrix = self.generateZeroMatrix()
freeNode = []
parkingNode = []
exitNode = []
newMatrixRow = -1
for i in range(0,self.row):
for j in range(0,self.col):
newMatrixRow+=1
#check for restricted block
if(self.inputData[i][j] > 5 or self.inputData[i][j] < 0):
raise InvalidDataFormat()
if(self.inputData[i][j] == 2):
parkingNode.append(newMatrixRow)
elif(self.inputData[i][j] == 5):
exitNode.append(newMatrixRow)
if(self.inputData[i][j] == 0 or self.inputData[i][j] == 2 or self.inputData[i][j] == 3):
#check-left
if(j-1 >= 0):
if(self.inputData[i][j-1] == 0 or self.inputData[i][j-1] == 2 or self.inputData[i][j-1] == 3 or self.inputData[i][j-1] == 5):
adjcencyMatrix[newMatrixRow][newMatrixRow-1] = 1
#check-right
if(j+1 <= col-1):
if(self.inputData[i][j+1] == 0 or self.inputData[i][j+1] == 2 or self.inputData[i][j+1] == 3 or self.inputData[i][j+1] == 5):
adjcencyMatrix[newMatrixRow][newMatrixRow+1] = 1
#check-up
if(i-1 >= 0):
if(self.inputData[i-1][j] == 0 or self.inputData[i-1][j] == 2 or self.inputData[i-1][j] == 3 or self.inputData[i-1][j] == 5):
adjcencyMatrix[newMatrixRow][newMatrixRow-col] = 1
#check-down
if(i+1 <= row-1):
if(self.inputData[i+1][j] == 0 or self.inputData[i+1][j] == 2 or self.inputData[i+1][j] == 3 or self.inputData[i+1][j] == 5):
adjcencyMatrix[newMatrixRow][newMatrixRow+col] = 1
self.connector.setGraph(adjcencyMatrix, parkingNode, exitNode)
def findFastestParkingRoute(self, row, col):
#print((row * self.row) + col)
self.outputData = self.connector.park(((row * self.row) + col))
if self.outputData == []:
return []
return self.returnTuple()
def findFastestExitRoute(self, row, col):
#print((row * self.row) + col)
self.outputData = self.connector.autoexit(((row * self.row) + col))
if self.outputData == []:
return []
return self.returnTuple()
def returnTuple(self):
listTuple = []
for i in self.outputData:
x = i//self.row
y = i%self.col
listTuple.append((x,y))
return listTuple
def getLenPark(self):
return self.connector.getLenPark()
def main(argv):
input_graph_file = None
graph_save_file = None
input_params_file = None
airport_q = 10
only_generate = False
verbosity = 5
data = None
graph = None
# Parameters
params = {
'graph': graph,
'start_idx': 1,
'end_idx': 4,
'max_flights': 150,
'cost_weight': 2,
'time_weight': 1,
'pop_size': 20,
'generations': 10,
'mutation_rate': 0.2,
'tournament_size': 2,
'elitism': False,
'dest_min': 2,
'dest_max': 5
}
# Parse command line options
try:
opts, args = getopt.getopt(argv, "hi:s:p:a:gv:", [
"ifile=", "save=", "params=", "airports=", "verbose=",
"start_idx=", "end_idx=", "max_flights=", "cost_weight=",
"time_weight=", "pop_size=", "generations=", "mutation_rate=",
"tournament_size=", "elitism=", "dest_min=", "dest_max="
])
except getopt.GetoptError:
print_help()
sys.exit(2)
for opt, arg in opts:
if opt == '-h':
print_help()
sys.exit()
elif opt in ("-i", "--ifile"):
input_graph_file = arg
print('Will read data from: {}'.format(input_graph_file))
elif opt in ("-s", "--save"):
graph_save_file = arg
print('Will save graph to: {}'.format(graph_save_file))
elif opt in ("-p", "--params"):
input_params_file = arg
print('Will read params from: {}'.format(input_params_file))
elif opt in ("-a", "--airports"):
airport_q = int(arg)
print('Number of airports = {}'.format(airport_q))
elif opt in ("-g", "--generate"):
only_generate = True
print('Will just generate data')
elif opt in ("-v", "--verbose"):
verbosity = int(arg)
print('Verbosity level = {} ({})'.format(
verbosity, get_verbosity_info(verbosity)))
elif opt in list("--" + x for x in params.keys()):
if opt[2:] == 'mutation_rate':
params[opt[2:]] = float(arg)
elif opt[2:] == 'elitism':
params[opt[2:]] = arg.lower() in [
'true', 't', 'tak', 'yes', 'y', '1'
]
else:
params[opt[2:]] = int(arg)
print('Params are: \n{} \n'.format('\n'.join(
' {:{}}: {}'.format(k,
len(max(params.keys())) + 1, v)
for k, v in sorted(params.items()))))
# DataGenerator
data = DataGenerator()
DataGenerator.DESTINATIONS_MIN = params['dest_min']
DataGenerator.DESTINATIONS_MAX = params['dest_max']
if input_graph_file is not None:
data.load_saved_graph(input_graph_file)
else:
data.load_new_data(airport_q)
data.create_graph()
if graph_save_file is not None:
data.save_graph(graph_save_file)
testsuite_airports = data.get_airports()
testsuite_graph = data.get_graph()
graph = GraphManager(params['max_flights'])
graph.set_graph(testsuite_graph, testsuite_airports)
if verbosity > 1:
graph.print_airports()
graph.print_flights()
graph.print_graph()
if not only_generate:
print(' === GeneticAlgorithm tests ===')
params['graph'] = graph
GA.run_with_params(params)
class DataManager:
def __init__(self, row, column, inputData=[]):
self.connector = GraphManager()
self.inputData = inputData
self.outputData = []
self.row = row
self.col = column
def generateZeroMatrix(self):
newMatrix = [[0 for x in range(self.row * self.col)]
for y in range(self.col * self.row)]
return newMatrix
def setup(self):
adjcencyMatrix = self.generateZeroMatrix()
freeNode = []
exitNode = []
newMatrixRow = -1
for i in range(0, self.row):
for j in range(0, self.col):
newMatrixRow += 1
#check for restricted block
if (self.inputData[i][j] == 2 or self.inputData[i][j] == 3):
freeNode.append(newMatrixRow)
## if(self.inputData[i][j] == 2):
## freeNode.append(newMatrixRow)
## elif(self.inputData[i][j] == 3):
## exitNode.append(newMatrixRow)
if (self.inputData[i][j] == 0 or self.inputData[i][j] == 2
or self.inputData[i][j] == 3):
#check-left
if (j - 1 >= 0):
if (self.inputData[i][j - 1] == 0
or self.inputData[i][j - 1] == 2
or self.inputData[i][j - 1] == 3):
adjcencyMatrix[newMatrixRow][newMatrixRow - 1] = 1
#check-right
if (j + 1 <= col - 1):
if (self.inputData[i][j + 1] == 0
or self.inputData[i][j + 1] == 2
or self.inputData[i][j + 1] == 3):
adjcencyMatrix[newMatrixRow][newMatrixRow + 1] = 1
#check-up
if (i - 1 >= 0):
if (self.inputData[i - 1][j] == 0
or self.inputData[i - 1][j] == 2
or self.inputData[i - 1][j] == 3):
adjcencyMatrix[newMatrixRow][newMatrixRow -
col] = 1
#check-down
if (i + 1 <= row - 1):
if (self.inputData[i + 1][j] == 0
or self.inputData[i + 1][j] == 2
or self.inputData[i + 1][j] == 3):
adjcencyMatrix[newMatrixRow][newMatrixRow +
col] = 1
print(freeNode)
#self.connector.setGraph(adjcencyMatrix, freeNode ,exitNode)
self.connector.setGraph(adjcencyMatrix, freeNode)
def findFastestRoute(self, a=601, b=623, status='enter'):
self.outputData = self.connector.getPath(a, b, status)
#print(self.outputData)
return self.returnTuple()
def returnTuple(self):
listTuple = []
for i in self.outputData:
x = i // self.row
y = i % self.col
listTuple.append((x, y))
return listTuple