Ajout demonstration final

Mesure-preliminaire
LéopoldClement 2 years ago
parent 5002bba5a2
commit 24965b27e7

@ -0,0 +1,35 @@
#! /bin/python3
import socket
import time
import numpy as np
from coapthon.client.helperclient import HelperClient
from coapthon.client.superviseur import (SuperviseurGlobal,
SuperviseurLocalFiltre)
from coapthon.utils import parse_uri
from utils_learning import RequettePeriodique
host, port, path = parse_uri("coap://polaris.kokarde.fr/basic")
try:
tmp = socket.gethostbyname(host)
host = tmp
except socket.gaierror:
pass
nombreCapteur = 25
periodeRequette = 1
periodeControl = 15
clients = [HelperClient(server=(host, port)) for _ in range(nombreCapteur)]
super_g = SuperviseurGlobal(clients, SuperviseurLocalFiltre)
requests = [RequettePeriodique(client, periodeRequette, path, name="Spamer {}".format(
n)) for n, client in enumerate(clients)]
[request.start() for request in requests]
for _ in range(10):
super_g.reset()
time.sleep(periodeControl)
print(super_g.state)

@ -7,11 +7,7 @@ import time
from typing import Any, Callable, Iterable, Mapping, Optional
import numpy as np
import tensorflow as tf
from tf_agents.environments import (py_environment, tf_environment,
tf_py_environment, utils, wrappers)
from tf_agents.specs import array_spec
from tf_agents.trajectories import time_step as ts
from coapthon.client.helperclient import HelperClient
from coapthon.client.superviseur import (SuperviseurGlobal,
@ -46,8 +42,13 @@ class RequettePeriodique(threading.Thread):
else:
raise ValueError
class MaquetteCoapEnv(py_environment.PyEnvironment):
try :
import tensorflow as tf
from tf_agents.environments import (py_environment, tf_environment,
tf_py_environment, utils, wrappers)
from tf_agents.specs import array_spec
from tf_agents.trajectories import time_step as ts
class MaquetteCoapEnv(py_environment.PyEnvironment):
def __init__(self, clients: Iterable[HelperClient], superviseur_local_type: type, superviseur_global_type: type, request_path: str, args_reward: Iterable[Any] = (),
control_period: float = 30, request_period: Iterable[float] = None) -> None:
@ -105,3 +106,6 @@ class MaquetteCoapEnv(py_environment.PyEnvironment):
return ts.termination(etat, -10000)
else:
return ts.transition(etat, reward=recompense)
except ImportError :
print("Pas de fonctionalité d'apprentissage")
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