import numpy as np



def power_aver(kf,scales,pot,datadir):


	keff=np.zeros((len(scales),2))

	for s in range(len(scales)):
		l=scales[s]
		lz=scales[s]

		nbx, nby, nbz= kf.shape[0]//l, kf.shape[1]//l,kf.shape[2]//l,
		if nbz==0:
			nbz=1
			lz=1

		res=np.zeros((nbx,nby,nbz))

		for i in range(nbx):
			for j in range(nby):
				for k in range(nbz):

					res[i,j,k]=np.mean(kf[i*l:(i+1)*l,j*l:(j+1)*l,k*lz:(k+1)*lz]**(1.0/pot))**(pot)

		keff[s,0]=np.exp(np.mean(np.log(res)))
		keff[s,01]=np.var(np.log(res))
		np.save(datadir+'KpostProcess/Kpo'+str(scales[s])+'.npy',res)
	return keff


rdir='./data/'



scales=np.array([4,8,16,32,64,128,256,512])

for i in range(3):

	kf=np.load(rdir+str(i)+'/k.npy')
	kpower=power_aver(kf,scales,3,rdir+str(i)+'/')