I had no issue running the code after remove your two MPI.rank if tests (and saving for every process), using:
Bootstrap: docker
From: quay.io/fenicsproject/stable:current
%files
output
%post
apt-get -y update
apt-get -y install python3 python3-pip
python3 -m pip install --force-reinstall numpy
mkdir -p output
sudo singularity build dolfin.simg dolfin_singularity
mpirun -n 4 singularity exec dolfin.simg python3 demo.py
where demo.py is:
import random
from dolfin import *
# Class representing the intial conditions
class InitialConditions(UserExpression):
def __init__(self, **kwargs):
random.seed(2 + MPI.rank(MPI.comm_world))
super().__init__(**kwargs)
def eval(self, values, x):
values[0] = 0.63 + 0.02*(0.5 - random.random())
values[1] = 0.0
def value_shape(self):
return (2,)
# Class for interfacing with the Newton solver
class CahnHilliardEquation(NonlinearProblem):
def __init__(self, a, L):
NonlinearProblem.__init__(self)
self.L = L
self.a = a
def F(self, b, x):
assemble(self.L, tensor=b)
def J(self, A, x):
assemble(self.a, tensor=A)
# Model parameters
lmbda = 1.0e-02 # surface parameter
dt = 5.0e-06 # time step
theta = 0.5 # time stepping family, e.g. theta=1 -> backward Euler, theta=0.5 -> Crank-Nicolson
# Form compiler options
parameters["form_compiler"]["optimize"] = True
parameters["form_compiler"]["cpp_optimize"] = True
# Create mesh and build function space
mesh = UnitSquareMesh.create(96, 96, CellType.Type.quadrilateral)
P1 = FiniteElement("Lagrange", mesh.ufl_cell(), 1)
ME = FunctionSpace(mesh, P1*P1)
# Define trial and test functions
du = TrialFunction(ME)
q, v = TestFunctions(ME)
# Define functions
u = Function(ME) # current solution
u0 = Function(ME) # solution from previous converged step
# Split mixed functions
dc, dmu = split(du)
c, mu = split(u)
c0, mu0 = split(u0)
# Create intial conditions and interpolate
u_init = InitialConditions(degree=1)
u.interpolate(u_init)
u0.interpolate(u_init)
# Compute the chemical potential df/dc
c = variable(c)
f = 100*c**2*(1-c)**2
dfdc = diff(f, c)
# mu_(n+theta)
mu_mid = (1.0-theta)*mu0 + theta*mu
# Weak statement of the equations
L0 = c*q*dx - c0*q*dx + dt*dot(grad(mu_mid), grad(q))*dx
L1 = mu*v*dx - dfdc*v*dx - lmbda*dot(grad(c), grad(v))*dx
L = L0 + L1
# Compute directional derivative about u in the direction of du (Jacobian)
a = derivative(L, u, du)
# Create nonlinear problem and Newton solver
problem = CahnHilliardEquation(a, L)
solver = NewtonSolver()
solver.parameters["linear_solver"] = "lu"
solver.parameters["convergence_criterion"] = "incremental"
solver.parameters["relative_tolerance"] = 1e-6
# Output file
file = File("output/output.pvd", "compressed")
HDF5 = HDF5File(MPI.comm_world,"output/output.hdf5",'w')
vtkfile_phi = File("output/output.pvd", "compressed")
# Step in time
t = 0.0
T = 5*dt
while (t < T):
t += dt
u0.vector()[:] = u.vector()
solver.solve(problem, u.vector())
file << (u.split()[0], t)
HDF5.write(u.split()[0], "fun",t)
file << (u.split()[0], t)