def save_tstep_solution_h5(tstep, q_, u_, newfolder, tstepfiles, constrained_domain,
output_timeseries_as_vector, u_components,
scalar_components, NS_parameters):
"""Store solution on current timestep to XDMF file."""
timefolder = path.join(newfolder, 'Timeseries')
if output_timeseries_as_vector:
# project or store velocity to vector function space
for comp, tstepfile in tstepfiles.iteritems():
if comp == "u":
if not hasattr(tstepfile, 'uv'): # First time around only
V = q_['u0'].function_space()
Vv = VectorFunctionSpace(V.mesh(), V.ufl_element().family(), V.ufl_element().degree(),
constrained_domain=constrained_domain)
tstepfile.uv = Function(Vv)
tstepfile.d = dict((ui, Vv.sub(i).dofmap().collapse(Vv.mesh())[1])
for i, ui in enumerate(u_components))
# The short but timeconsuming way:
#tstepfile.uv.assign(project(u_, Vv))
# Or the faster, but more comprehensive way:
for ui in u_components:
q_[ui].update()
vals = tstepfile.d[ui].values()
keys = tstepfile.d[ui].keys()
tstepfile.uv.vector()[vals] = q_[ui].vector()[keys]
tstepfile << (tstepfile.uv, float(tstep))
elif comp in q_:
tstepfile << (q_[comp], float(tstep))
else:
tstepfile << (tstepfile.function, float(tstep))
else:
for comp, tstepfile in tstepfiles.iteritems():
tstepfile << (q_[comp], float(tstep))
if MPI.rank(mpi_comm_world()) == 0:
if not path.exists(path.join(timefolder, "params.dat")):
f = open(path.join(timefolder, 'params.dat'), 'w')
cPickle.dump(NS_parameters, f)
