def update_sample(self, mobo_info, n_kb=5, n_cpu=1):
"""Run multi-objective optimization/update.
Args:
mobo_info (dict): KADAL-style input dictionary.
n_kb (int, optional): Requested number of Kriging Believer
samples to search for. Defaults to 5.
n_cpu (int, optional): If > 1, uses parallel processing, if
supported. Defaults to 1.
"""
# infeasiblesamp = np.where(self.cldat <= 0.15)[0]
mobo = MOBO(mobo_info, self.obj_krig, autoupdate=False,
multiupdate=n_kb, savedata=False,
expconst=self.con_krig, chpconst=self.h)
start_update = time.time()
xupdate, yupdate, supdate, metricall = mobo.run(disp=True,
infeasible=None,
n_cpu=n_cpu)
elapsed = time.time() - start_update
print(f'Total update time: {elapsed:.2f} seconds')
self.total_update_time = elapsed
self.xupdate.append(xupdate)
self.yupdate.append(yupdate)
self.supdate.append(supdate)
self.metricall.append(metricall)
return xupdate, yupdate, supdate, metricall
def optimize(kriglist, expconstlist):
moboInfo = dict()
moboInfo['nup'] = 5
moboInfo['acquifunc'] = "ehvi"
moboInfo['acquifuncopt'] = "diff_evo"
cheapconstlist = [cheap_const]
mobo = MOBO(moboInfo, kriglist, autoupdate=True, multiupdate=5, expconst=expconstlist,
chpconst = cheapconstlist)
xupdate, yupdate, supdate, metricall = mobo.run(disp=True)
return xupdate, yupdate, supdate, metricall
def runopt(krigobj1, krigobj2):
moboInfo = dict()
moboInfo["nup"] = 3
moboInfo["nrestart"] = 10
moboInfo["acquifunc"] = "ehvi"
moboInfo["acquifuncopt"] = "lbfgsb"
Optim = MOBO(moboInfo,[krigobj1,krigobj2],autoupdate=True,multiupdate=5)
xupdate,yupdate,supdate,metricall = Optim.run(disp=True)
return xupdate,yupdate,metricall