https://github.com/hpc-maths/GenEO
Tip revision: 47b05ef7165f6cee92daa3002503259f0ec84695 authored by gouarin on 28 May 2018, 11:31:32 UTC
fix binder
fix binder
Tip revision: 47b05ef
demo_elasticity_3d.py
from __future__ import print_function, division
import sys, petsc4py
petsc4py.init(sys.argv)
import mpi4py.MPI as mpi
from petsc4py import PETSc
import numpy as np
from elasticity import *
def rhs(coords, rhs):
rhs[..., 1] = -9.81# + rand
OptDB = PETSc.Options()
Lx = OptDB.getInt('Lx', 10)
Ly = OptDB.getInt('Ly', 1)
Lz = OptDB.getInt('Lz', 1)
n = OptDB.getInt('n', 16)
nx = OptDB.getInt('nx', Lx*n)
ny = OptDB.getInt('ny', Ly*n)
nz = OptDB.getInt('nz', Lz*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)
hz = Lz/(nz - 1)
h = [hx, hy, hz]
da = PETSc.DMDA().create([nx, ny, nz], dof=3, stencil_width=1)
da.setUniformCoordinates(xmax=Lx, ymax=Ly, zmax=Lz)
da.setMatType(PETSc.Mat.Type.IS)
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
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('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
def lame_coeff(x, y, z, v1, v2):
output = np.empty(x.shape)
mask = np.logical_or(np.logical_and(.2<=z, z<=.4),np.logical_and(.6<=z, z<=.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)
x = da.createGlobalVec()
b = buildRHS(da, h, rhs)
A = buildElasticityMatrix(da, h, lamb, mu)
A.assemble()
bcApplyWest(da, A, b)
bcopy = b.copy()
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.setInitialGuessNonzero(True)
ksp.setFromOptions()
ksp.solve(b, x)
viewer = PETSc.Viewer().createVTK('solution_3d_asm.vts', 'w', comm = PETSc.COMM_WORLD)
x.view(viewer)