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90 lines
1.4 KiB
Python
90 lines
1.4 KiB
Python
import numpy as np
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import petsc4py
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import math
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import time
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#from mpi4py import MPI
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from computeFlows import *
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from petsc4py import PETSc
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petsc4py.init('-ksp_max_it 9999999999')
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from flow import getKeff
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def PetscP(datadir,ref,k,saveres):
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ref=1
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rank=0
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pn=1
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t0=time.time()
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pcomm=PETSc.COMM_SELF
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if k.shape[2]==1:
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refz=1
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else:
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refz=ref
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nz, ny, nx=k.shape[0]*ref,k.shape[1]*ref,k.shape[2]*refz
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n=nx*ny*nz
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K = PETSc.Mat().create(comm=pcomm)
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K.setType('seqaij')
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K.setSizes(((n,None),(n,None))) # Aca igual que lo que usas arriba
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K.setPreallocationNNZ(nnz=(7,4)) # Idem anterior
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K.setUp()
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R = PETSc.Vec().createSeq((n,None),comm=pcomm) #PETSc.COMM_WORLD
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R.setUp()
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k2, Nz, nnz2=getKref(k,1,2,ref)
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k, Nz, nnz=getKref(k,0,2,ref)
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pbc=float(Nz)
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K,R = firstL(K,R,k,pbc)
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r=(k.shape[1]-2)*(k.shape[2]-2)*nnz2 #start row
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K,R =lastL(K,R,k2,r)
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k2=0
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K.assemble()
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R.assemble()
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ksp = PETSc.KSP()
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ksp.create(comm=pcomm)
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ksp.setFromOptions()
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P = R.copy()
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ksp.setType(PETSc.KSP.Type.CG)
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pc = PETSc.PC()
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pc.create(comm=pcomm)
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pc.setType(PETSc.PC.Type.JACOBI)
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ksp.setPC(pc)
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ksp.setOperators(K)
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ksp.setUp()
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t1=time.time()
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ksp.solve(R, P)
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t2=time.time()
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p=P.getArray().reshape(nz,ny,nx)
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if rank==0:
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keff,Q=getKeff(p,k[1:-1,1:-1,1:-1],pbc,Nz)
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print(keff,ref,nx,ny,nz)
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return keff
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return
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#Ver: A posteriori error estimates and adaptive solvers for porous media flows (Martin Vohralik)
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