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NOTICE + requirements angepasst

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Bla Bla 2024-05-03 10:56:13 +02:00
parent 0591dc9dde
commit 24548f5621
2 changed files with 10 additions and 7 deletions
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14
modules/class_optimize.py
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@ -38,7 +38,7 @@ class optimization_problem:
self.strafe = strafe
self.opti_param = None
def setup_deap_environment(self,opti_param):
def setup_deap_environment(self,opti_param, start_hour):
self.opti_param = opti_param
if "FitnessMin" in creator.__dict__:
del creator.FitnessMin
@ -50,14 +50,12 @@ class optimization_problem:
# PARAMETER
self.toolbox = base.Toolbox()
self.toolbox.register("attr_bool", random.randint, 0, 1)
self.toolbox.register("attr_int", random.randint, 0, 23)
self.toolbox.register("attr_int", random.randint, start_hour, 23)
###################
# Haushaltsgeraete
print("Haushalt:",opti_param["haushaltsgeraete"])
#print("Haushalt:",opti_param["haushaltsgeraete"])
if opti_param["haushaltsgeraete"]>0:
def create_individual():
attrs = [self.toolbox.attr_bool() for _ in range(2*self.prediction_hours)] + [self.toolbox.attr_int()]
@ -78,6 +76,7 @@ class optimization_problem:
def evaluate_inner(self,individual, ems,start_hour):
ems.reset()
#print("Spuel:",self.opti_param)
# Haushaltsgeraete
if self.opti_param["haushaltsgeraete"]>0:
@ -193,6 +192,7 @@ class optimization_problem:
###############
# spuelmaschine
##############
print(parameter)
if parameter["haushaltsgeraet_dauer"] >0:
spuelmaschine = Haushaltsgeraet(hours=self.prediction_hours, verbrauch_kwh=parameter["haushaltsgeraet_wh"], dauer_h=parameter["haushaltsgeraet_dauer"])
spuelmaschine.set_startzeitpunkt(start_hour) # Startet jetzt
@ -251,14 +251,14 @@ class optimization_problem:
if spuelmaschine != None:
opti_param["haushaltsgeraete"] = 1
self.setup_deap_environment(opti_param)
self.setup_deap_environment(opti_param, start_hour)
def evaluate_wrapper(individual):
return self.evaluate(individual, ems, parameter,start_hour,worst_case)
self.toolbox.register("evaluate", evaluate_wrapper)
start_solution, extra_data = self.optimize(start_params)
best_solution = start_params
best_solution = start_solution
o = self.evaluate_inner(best_solution, ems,start_hour)
eauto = ems.eauto.to_dict()
spuelstart_int = None

3
requirements.txt
View File

@ -4,3 +4,6 @@ requests
pytz
matplotlib
deap
scipy
sklearn
pandas