def improve(self,design,improvement_steps):
# from multiprocessing import Pool
j=0
# threads=8
while j<improvement_steps:
# need to add a condition to be already initiated
totals=np.zeros((design.n_test,3))
self.condition()
# multicore processing, does not work, try PATHOS instead of MULTIP
# def emulated(index):
# self.emulate(design.test_pars[index])
# return(cf.rmse(self.result,design.test_data[index]))
# magazine=np.zeros(threads)
# mag_idx=0
# i=0
# while i<design.n_test:
# if mag_idx<threads:
# magazine[mag_idx]=i
# mag_idx+=1
# else:
# p=Pool(threads)
# output_parallel_session=p.map(emulated,magazine.tolist())
# totals[magazine.tolist()]=output_parallel_session
# mag_idx=0
# p.close()
# i+=1
i=0
while i<design.n_test:
self.emulate(design.test_pars[i])
totals[i,0]=cf.rmse(self.result,design.test_data[i])
totals[i,1]=cf.sharpness(self.result,design.test_data[i])
i+=1
max_0=max(totals[:,0])
max_1=max(totals[:,1])
print(max_0)
print(max_1)
totals[:,0]=totals[:,0]/max_0
totals[:,1]=totals[:,1]/max_1
totals[:,2]=totals[:,1]+totals[:,0]
worst=np.argmax(totals[:,2])
current0=np.mean(totals[:,0])
current1=np.mean(totals[:,1])
current2=np.mean(totals[:,2])
print(max(totals[:,2]))
print(current0)
print(current1)
print(current2)
print("--------")
j+=1
design.extend(design.test_data[worst],design.test_pars[worst])
design.remove_test_set(worst)
self.dp=design.pars
self.dd=design.data
def objective_rmse(self,new_cor_len,design,n_test_sample):
totals=np.zeros(n_test_sample)
self.cor_len=new_cor_len
self.condition()
i=0
while i<n_test_sample:
self.emulate(design.test_pars[i])
totals[i]=cf.rmse(self.result,design.test_data[i])
i+=1
current=np.mean(totals)
# print(current)
# print(self.cor_len)
return(current)
