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simulacion-permeabilidad/tools/solver/Ndar.py

168 lines
4.6 KiB
Python

import numpy as np
import petsc4py
import math
import time
# from mpi4py import MPI
from tools.postprocessK.kperm.computeFlows import *
from tools.postprocessK.flow import getKeff
from petsc4py import PETSc
import sys
def PetscP(datadir, ref, k, saveres, Rtol, comm):
if comm == 0:
pcomm = PETSc.COMM_SELF
rank = 0
pn = 1
else:
pcomm = PETSc.COMM_WORLD
rank = pcomm.rank
pn = pcomm.size
t0 = time.time()
if pn == 1:
if not isinstance(k, np.ndarray):
k = np.load(datadir + "k.npy")
if k.shape[2] == 1:
refz = 1
else:
refz = ref
nz, ny, nx = k.shape[0] * ref, k.shape[1] * ref, k.shape[2] * refz
n = nx * ny * nz
K = PETSc.Mat().create(comm=pcomm)
K.setType("seqaij")
K.setSizes(((n, None), (n, None))) # Aca igual que lo que usas arriba
K.setPreallocationNNZ(nnz=(7, 4)) # Idem anterior
K.setUp()
R = PETSc.Vec().createSeq((n, None), comm=pcomm) # PETSc.COMM_WORLD
R.setUp()
k2, Nz, nnz2 = getKref(k, 1, 2, ref)
k, Nz, nnz = getKref(k, 0, 2, ref)
pbc = float(Nz)
K, R = firstL(K, R, k, pbc)
r = (k.shape[1] - 2) * (k.shape[2] - 2) * nnz2 # start row
K, R = lastL(K, R, k2, r)
k2 = 0
else:
if not isinstance(k, np.ndarray):
k = np.load(datadir + "k.npy")
k, Nz, nnz = getKref(k, rank, pn, ref)
pbc = float(Nz)
nz, ny, nx = (k.shape[0] - 2), (k.shape[1] - 2), (k.shape[2] - 2)
n = nx * ny * nz
K = PETSc.Mat().createAIJ(((n, None), (n, None)), nnz=(7, 4), comm=pcomm)
K.setUp()
R = PETSc.Vec().createMPI((n, None), comm=pcomm)
R.setUp()
r = nx * ny * nnz * rank # start row
if rank == 0:
K, R = firstL(K, R, k, pbc)
if (rank > 0) and (rank < pn - 1):
K, R = centL(K, R, k, r)
k = 0
if rank == (pn - 1):
K, R = lastL(K, R, k, r)
k = 0
K.assemble()
R.assemble()
ksp = PETSc.KSP()
ksp.create(comm=pcomm)
ksp.setTolerances(rtol=Rtol, atol=1.0e-100, max_it=999999999)
ksp.setFromOptions()
P = R.copy()
ksp.setType(PETSc.KSP.Type.CG)
pc = PETSc.PC()
pc.create(comm=pcomm)
pc.setType(PETSc.PC.Type.JACOBI)
ksp.setPC(pc)
ksp.setOperators(K)
ksp.setUp()
t1 = time.time()
ksp.solve(R, P)
t2 = time.time()
p = P.getArray().reshape(nz, ny, nx)
if rank == 0:
keff, Q = getKeff(p, k[1:-1, 1:-1, 1:-1], pbc, Nz)
if saveres == True:
for i in range(1, pn):
from mpi4py import MPI
comm = MPI.COMM_WORLD
pi = comm.recv(source=i)
p = np.append(p, pi, axis=0)
np.save(datadir + "P", p)
f = open(datadir + "RunTimes.out", "a")
f.write("ref: " + str(ref) + "\n")
f.write("Matrix creation: " + str(t1 - t0) + "\n")
f.write("Solver: " + str(t2 - t1) + "\n")
f.write("Keff: " + str(keff) + "\n")
f.write("N_cores: " + str(pn) + "\n")
f.close()
try:
res = np.loadtxt(datadir + "SolverRes.txt")
res = np.append(res, np.array([keff, ref, t2 - t0, pn]))
except:
res = np.array([keff, ref, t2 - t0, pn])
np.savetxt(
datadir + "SolverRes.txt", res, header="Keff, ref, Runtime, N_cores"
)
print(datadir[-3:], " keff= " + str(keff), " rtime= " + str(t2 - t0))
return keff
else:
if saveres == True:
from mpi4py import MPI
comm = MPI.COMM_WORLD
comm.send(p, dest=0)
return
# Ver: A posteriori error estimates and adaptive solvers for porous media flows (Martin Vohralik)
try:
if sys.argv[5] == "1":
from mpi4py import MPI
icomm = MPI.Comm.Get_parent()
PetscP(
sys.argv[1], int(sys.argv[2]), "0", True, float(sys.argv[4]), 1
) # multip cores not Tupac
# icomm = MPI.Comm.Get_parent()
icomm.Disconnect()
else:
PetscP(
sys.argv[1], int(sys.argv[2]), "0", True, float(sys.argv[4]), 0
) # 1 core read k map
except IndexError:
try:
PetscP(
sys.argv[1], int(sys.argv[2]), "0", True, 1e-4, 1
) # multip core as executable
except IndexError:
nada = 0
# PetscP(sys.argv[1],int(sys.argv[2]),sys.argv[3],False,1e-4,0) #1 core, k field as argument