from __future__ import print_function, division
import os
import sys, petsc4py
petsc4py.init(sys.argv)
import mpi4py.MPI as mpi
from petsc4py import PETSc
import numpy as np
from GenEO import *
def rhs(coords, rhs):
n = rhs.shape
rhs[..., 1] = -9.81
OptDB = PETSc.Options()
Lx = OptDB.getInt('Lx', 10)
Ly = OptDB.getInt('Ly', 1)
n = OptDB.getInt('n', 16)
nx = OptDB.getInt('nx', Lx*n)
ny = OptDB.getInt('ny', Ly*n)
E1 = OptDB.getReal('E1', 10**6)
E2 = OptDB.getReal('E2', 1)
nu1 = OptDB.getReal('nu1', 0.4)
nu2 = OptDB.getReal('nu2', 0.4)
hx = Lx/(nx - 1)
hy = Ly/(ny - 1)
da = PETSc.DMDA().create([nx, ny], dof=2, stencil_width=1)
da.setUniformCoordinates(xmax=Lx, ymax=Ly)
da.setMatType(PETSc.Mat.Type.IS)
da.setFieldName(0, 'u')
da.setFieldName(1, 'v')
path = './output_2d/'
if mpi.COMM_WORLD.rank == 0:
if not os.path.exists(path):
os.mkdir(path)
else:
os.system('rm {}/*.vts'.format(path))
def lame_coeff(x, y, v1, v2):
output = np.empty(x.shape)
mask = np.logical_or(np.logical_and(.2<=y, y<=.4),np.logical_and(.6<=y, y<=.8))
output[mask] = v1
output[np.logical_not(mask)] = v2
return output
# non constant Young's modulus and Poisson's ratio
E = buildCellArrayWithFunction(da, lame_coeff, (E1,E2))
nu = buildCellArrayWithFunction(da, lame_coeff, (nu1,nu2))
lamb = (nu*E)/((1+nu)*(1-2*nu))
mu = .5*E/(1+nu)
class callback:
def __init__(self, da):
self.da = da
ranges = da.getRanges()
ghost_ranges = da.getGhostRanges()
self.slices = []
for r, gr in zip(ranges, ghost_ranges):
self.slices.append(slice(gr[0], r[1]))
self.slices = tuple(self.slices)
self.it = 0
def __call__(self, locals):
pyKSP = locals['self']
proj = pyKSP.mpc.proj
viewer_x = PETSc.Viewer().createVTK(path + 'cg_ite_{}.vts'.format(self.it), 'w', comm = PETSc.COMM_WORLD)
locals['x'].view(viewer_x)
viewer_x.destroy()
if self.it == 0:
work, _ = proj.A.getVecs()
for i, vec in enumerate(proj.coarse_vecs):
if vec:
proj.workl = vec.copy()
else:
proj.workl.set(0.)
work.set(0)
proj.scatter_l2g(proj.workl, work, PETSc.InsertMode.ADD_VALUES)
viewer = PETSc.Viewer().createVTK(path + 'coarse_vec_{}.vts'.format(i), 'w', comm = PETSc.COMM_WORLD)
tmp = self.da.createGlobalVec()
tmpl_a = self.da.getVecArray(tmp)
work_a = self.da.getVecArray(work)
tmpl_a[:] = work_a[:]
tmp.view(viewer)
viewer.destroy()
self.it += 1
x = da.createGlobalVec()
b = buildRHS(da, [hx, hy], rhs)
A = buildElasticityMatrix(da, [hx, hy], lamb, mu)
A.assemble()
bcApplyWest(da, A, b)
#Setup the preconditioner (or multipreconditioner) and the coarse space
pcbnn = PCBNN(A)
# Set initial guess
x.setRandom()
xnorm = b.dot(x)/x.dot(A*x)
x *= xnorm
ksp = PETSc.KSP().create()
ksp.setOperators(A)
ksp.setType(ksp.Type.PYTHON)
pyKSP = KSP_AMPCG(pcbnn)
pyKSP.callback = callback(da)
ksp.setPythonContext(pyKSP)
ksp.setFromOptions()
ksp.setInitialGuessNonzero(True)
ksp.solve(b, x)
def write_simu_info(da, viewer):
lamb_petsc = da.createGlobalVec()
lamb_a = da.getVecArray(lamb_petsc)
coords = da.getCoordinates()
coords_a = da.getVecArray(coords)
E = lame_coeff(coords_a[:, :, 0], coords_a[:, :, 1], E1, E2)
nu = lame_coeff(coords_a[:, :, 0], coords_a[:, :, 1], nu1, nu2)
lamb_a[:, :, 0] = (nu*E)/((1+nu)*(1-2*nu))
lamb_a[:, :, 1] = mpi.COMM_WORLD.rank
lamb_petsc.view(viewer)
viewer = PETSc.Viewer().createVTK(path + 'solution_2d.vts', 'w', comm = PETSc.COMM_WORLD)
x.view(viewer)
write_simu_info(da, viewer)
viewer.destroy()