@pytest.mark.parametrize("case", [
1,
]) # lower (1) vs. higher (2) density ratio
@pytest.mark.parametrize("matching_p", [
False,
])
@pytest.mark.parametrize("scheme",
["SemiDecoupled", "FullyDecoupled"]) # "Monolithic"
def test_bubble(scheme, matching_p, case, postprocessor):
set_log_level(WARNING)
# Read parameters
scriptdir = os.path.dirname(os.path.realpath(__file__))
prm_file = os.path.join(scriptdir, "bubble-parameters.xml")
mpset.read(prm_file)
# Adjust parameters
if case == 2:
mpset["model"]["nu"]["2"] = 0.1
mpset["model"]["rho"]["2"] = 1.0
mpset["model"]["sigma"]["12"] = 1.96
# Fixed parameters
t_end = postprocessor.t_end
OTD = postprocessor.OTD
# Names and directories
basename = postprocessor.basename
outdir = postprocessor.outdir
def test_shear(scheme, nu_interp, postprocessor):
#set_log_level(WARNING)
assert scheme == "SemiDecoupled"
dt = 0.0 # solve as the stationary problem
# Read parameters
scriptdir = os.path.dirname(os.path.realpath(__file__))
prm_file = os.path.join(scriptdir, "interface-parameters.xml")
mpset.read(prm_file)
# Adjust parameters
c = postprocessor.get_coefficients()
mpset["model"]["eps"] = c[r"\eps"]
mpset["model"]["rho"]["1"] = c[r"\rho_1"]
mpset["model"]["rho"]["2"] = c[r"\rho_2"]
mpset["model"]["nu"]["1"] = c[r"\nu_1"]
mpset["model"]["nu"]["2"] = c[r"\nu_2"]
mpset["model"]["chq"]["L"] = c[r"L_0"]
mpset["model"]["chq"]["V"] = c[r"V_0"]
mpset["model"]["chq"]["rho"] = c[r"\rho_0"]
mpset["model"]["mobility"]["M0"] = 1.0e+0
mpset["model"]["sigma"]["12"] = 1.0e-0
#mpset.show()
cc = wrap_coeffs_as_constants(c)
# Names and directories
basename = postprocessor.basename
label = "{}_{}".format(basename, nu_interp)
outdir = postprocessor.outdir
for level in range(2, 3):
# Prepare domain and discretization
mesh, boundary_markers, pinpoint, periodic_bnd = create_domain(
level, "crossed")
del periodic_bnd
DS, div_v = create_discretization(scheme, mesh, div_projection=True)
DS.parameters["PTL"] = 1
DS.setup()
# Prepare initial and boundary conditions
load_initial_conditions(DS, c)
bcs = create_bcs(DS, boundary_markers, pinpoint) # for Dirichlet
p_h = create_hydrostatic_pressure(mesh, cc) # for Neumann
# Force applied on the top plate
B = 0.0 if dt == 0.0 else 1.0
applied_force = df.Expression(
("A*(1.0 - B*exp(-alpha*t))", "0.0"),
degree=DS.subspace("v", 0).ufl_element().degree(),
t=0.0,
alpha=1.0,
A=1.0,
B=B)
# Prepare model
model = ModelFactory.create("Incompressible", DS, bcs)
model.parameters["THETA2"] = 0.0
#model.parameters["rho"]["itype"] = "lin"
#model.parameters["rho"]["trunc"] = "minmax"
model.parameters["nu"]["itype"] = nu_interp
model.parameters["nu"]["trunc"] = "minmax"
#model.parameters["nu"]["trunc"] = "clamp_hard"
#model.parameters["mobility"]["cut"] = True
# Prepare external source term
g_a = c[r"g_a"]
g_a /= mpset["model"]["chq"]["V"]**2.0 * mpset["model"]["chq"]["L"]
f_src = df.Constant((0.0, -g_a), cell=mesh.ufl_cell(), name="f_src")
model.load_sources(f_src)
# Create forms
forms = model.create_forms()
# Add boundary integrals
n = DS.facet_normal()
ds = df.Measure("ds", subdomain_data=boundary_markers)
test = DS.test_functions()
forms["lin"]["rhs"] +=\
df.inner(applied_force, test["v"]) * ds(3) # driving force
forms["lin"]["rhs"] -=\
p_h * df.inner(n, test["v"]) * (ds(2) + ds(4)) # hydrostatic balance
# Prepare solver
solver = SolverFactory.create(model, forms, fix_p=False)
# Prepare time-stepping algorithm
comm = mesh.mpi_comm()
pv = DS.primitive_vars_ctl()
modulo_factor = 1
xfields = list(zip(pv["phi"].split(), ("phi", )))
xfields.append((pv["p"].dolfin_repr(), "p"))
if scheme == "FullyDecoupled":
xfields += list(zip(pv["v"].split(), ("v1", "v2")))
else:
xfields.append((pv["v"].dolfin_repr(), "v"))
if div_v is not None:
xfields.append((div_v, "div_v"))
functionals = {"t": [], "E_kin": [], "Psi": [], "mean_p": []}
hook = prepare_hook(model, applied_force, functionals, modulo_factor,
div_v)
logfile = "log_{}.dat".format(label)
TS = TimeSteppingFactory.create("ConstantTimeStep",
comm,
solver,
hook=hook,
logfile=logfile,
xfields=xfields,
outdir=outdir)
TS.parameters["xdmf"]["folder"] = "XDMF_{}".format(label)
TS.parameters["xdmf"]["modulo"] = modulo_factor
TS.parameters["xdmf"]["flush"] = True
TS.parameters["xdmf"]["iconds"] = True
# Time-stepping
with Timer("Time stepping") as tmr_tstepping:
result = TS.run(0.0, 2.0, dt, OTD=1)
# Pre-process results
v = pv["v"].dolfin_repr()
p = pv["p"].dolfin_repr()
phi = pv["phi"].split()[0]
w_diff = DS.solution_ctl()[0].copy(True)
w0 = DS.solution_ptl(0)[0]
w_diff.vector().axpy(-1.0, w0.vector())
phi_diff = w_diff.split(True)[0]
phi_diff.rename("phi_diff", "phi_tstep_difference")
xdmfdir = \
os.path.join(outdir, TS.parameters["xdmf"]["folder"], "phi_diff.xdmf")
with df.XDMFFile(xdmfdir) as file:
file.write(phi_diff, 0.0)
D_12 = df.project(0.5 * v.sub(0).dx(1), div_v.function_space())
if nu_interp in [
"har",
]:
deg = DS.subspace("phi", 0).ufl_element().degree()
V_nu = df.FunctionSpace(mesh, "DG", deg)
else:
V_nu = DS.subspace("phi", 0, deepcopy=True)
nu_0 = df.project(model.coeffs["nu"], V_nu)
T_12 = df.project(model.coeffs["nu"] * v.sub(0).dx(1), V_nu)
#p_ref = df.project(p_h, df.FunctionSpace(mesh, W.sub(1).ufl_element()))
# Save results
make_cut = postprocessor._make_cut
rs = dict(level=level,
r_dens=c[r"r_dens"],
r_visc=c[r"r_visc"],
nu_interp=nu_interp)
rs[r"$v_1$"] = make_cut(v.sub(0))
rs[r"$p$"] = make_cut(p)
rs[r"$\phi$"] = make_cut(phi)
rs[r"$D_{12}$"] = make_cut(D_12)
rs[r"$T_{12}$"] = make_cut(T_12)
rs[r"$\nu$"] = make_cut(nu_0)
print(label, level)
# Send to posprocessor
comm = mesh.mpi_comm()
rank = df.MPI.rank(comm)
postprocessor.add_result(rank, rs)
# Save results into a binary file
filename = "results_{}.pickle".format(label)
postprocessor.save_results(filename)
# Flush plots as we now have data for all level values
postprocessor.flush_plots()
# Cleanup
df.set_log_level(df.INFO)
gc.collect()
def test_scaling_time(scheme, matching_p, postprocessor):
"""
Compute convergence rates for fixed element order, fixed mesh and
gradually decreasing time step.
"""
# Additional test configuration w.r.t. chosen scheme
if scheme == "SemiDecoupled":
OTD = 1
method = "it"
elif scheme == "FullyDecoupled":
OTD = 2
method = "lu" # iterative solvers not yet supported
else:
assert False
# Run test
set_log_level(WARNING)
degrise = 3 # degree rise for computation of errornorm
# Read parameters
scriptdir = os.path.dirname(os.path.realpath(__file__))
prm_file = os.path.join(scriptdir, "mms-parameters.xml")
mpset.read(prm_file)
# Fixed parameters
level = postprocessor.level
k = postprocessor.OPA
t_end = postprocessor.t_end
# Names and directories
basename = postprocessor.basename
outdir = postprocessor.outdir
# Mesh independent predefined quantities
msol = create_manufactured_solution()
ic = create_initial_conditions(msol)
# Prepare space discretization, exact solution and bcs
mesh, boundary_markers = create_domain(level)
DS = create_discretization(scheme, mesh, k)
DS.parameters["PTL"] = OTD
DS.setup()
esol = create_exact_solution(msol, DS.finite_elements(), degrise)
bcs = create_bcs(DS, boundary_markers, esol, method)
# Iterate over time step
for m in range(6): # CHANGE #1: set "m in range(7)"
dt = 0.1*0.5**m
label = "{}_dt_{}_{}".format(scheme, dt, basename)
with Timer("Prepare") as tmr_prepare:
# Reset sol_ptl[0] back to initial conditions
DS.load_ic_from_simple_cpp(ic)
# Prepare model
model = ModelFactory.create("Incompressible", DS, bcs)
cell = DS.mesh().ufl_cell()
t_src_ctl = Constant(0.0, cell=cell, name="t_src_ctl")
t_src_ptl = Constant(0.0, cell=cell, name="t_src_ptl")
f_src_ctl, g_src_ctl = \
create_source_terms(t_src_ctl, mesh, model, msol, matching_p)
f_src_ptl, g_src_ptl = \
create_source_terms(t_src_ptl, mesh, model, msol, matching_p)
t_src = [t_src_ctl,]
f_src = [f_src_ctl,]
g_src = [g_src_ctl,]
if OTD == 2 and scheme in ["Monolithic", "SemiDecoupled"]:
t_src.append(t_src_ptl)
g_src.append(g_src_ptl)
if scheme == "Monolithic":
f_src.append(f_src_ptl)
model.load_sources(f_src, g_src)
forms = model.create_forms(matching_p)
# Prepare solver
comm = mesh.mpi_comm()
solver = SolverFactory.create(model, forms, fix_p=(method == "it"))
if method == "it":
solver.data["solver"]["CH"]["lin"] = \
create_ch_solver(comm, "bjacobi")
solver.data["solver"]["NS"] = \
create_pcd_solver(comm, "BRM1", "iterative")
# prefix_ch = solver.data["solver"]["CH"]["lin"].get_options_prefix()
# PETScOptions.set(prefix_ch+"ksp_monitor_true_residual")
# solver.data["solver"]["CH"]["lin"].set_from_options()
# prefix_ns = solver.data["solver"]["NS"].get_options_prefix()
# PETScOptions.set(prefix_ns+"ksp_monitor")
# solver.data["solver"]["NS"].set_from_options()
# Prepare time-stepping algorithm
xfields = None
# NOTE: Uncomment the following block of code to get XDMF output
# pv = DS.primitive_vars_ctl()
# phi, chi, v, p = pv["phi"], pv["chi"], pv["v"], pv["p"]
# phi_, chi_, v_ = phi.split(), chi.split(), v.split()
# xfields = list(zip(phi_, len(phi_)*[None,])) \
# + list(zip(v_, len(v_)*[None,])) \
# + [(p.dolfin_repr(), None),]
hook = prepare_hook(t_src, model, esol, degrise, {})
logfile = "log_{}.dat".format(label)
TS = TimeSteppingFactory.create("ConstantTimeStep", comm, solver,
hook=hook, logfile=logfile, xfields=xfields, outdir=outdir)
# Time-stepping
t_beg = 0.0
with Timer("Time stepping") as tmr_tstepping:
it = 0
if OTD == 2:
if scheme == "FullyDecoupled":
dt0 = dt
result = TS.run(t_beg, dt0, dt0, OTD=1, it=it)
t_beg = dt
elif scheme == "Monolithic":
dt0 = 1.0e-4*dt
result = TS.run(t_beg, dt0, dt0, OTD=1, it=it)
if dt - dt0 > 0.0:
it = 0.5
result = TS.run(dt0, dt, dt - dt0, OTD=2, it=it)
t_beg = dt
it = 1
result = TS.run(t_beg, t_end, dt, OTD, it)
# Prepare results
name = logfile[4:-4]
result.update(
method=method,
ndofs=DS.num_dofs(),
scheme=scheme,
dt=dt,
t_end=t_end,
OTD=OTD,
err=hook.err,
level=level,
k=k,
tmr_prepare=tmr_prepare.elapsed()[0],
tmr_tstepping=tmr_tstepping.elapsed()[0]
)
print(name, result["ndofs"], result["tmr_prepare"],
result["tmr_solve"], result["it"], result["tmr_tstepping"])
# Send to posprocessor
rank = MPI.rank(comm)
postprocessor.add_result(rank, result)
# Save results into a binary file
filename = "results_{}.pickle".format(label)
postprocessor.save_results(filename)
# Pop results that we do not want to report at the moment
postprocessor.pop_items(["ndofs", "tmr_prepare", "tmr_solve", "it", "OTD"])
# Flush plots as we now have data for all level values
postprocessor.flush_plots()
# Store timings
#datafile = os.path.join(outdir, "timings.xml")
#dump_timings_to_xml(datafile, TimingClear_clear)
# Cleanup
set_log_level(INFO)
#mpset.write(comm, prm_file) # uncomment to save parameters
mpset.refresh()
gc.collect()
def test_scaling_mesh(pcd_variant, ls, matching_p, postprocessor):
"""
Compute convergence rates for fixed time step and gradually refined mesh or
increasing element order.
"""
set_log_level(WARNING)
degrise = 3 # degree rise for computation of errornorm
# Read parameters
scriptdir = os.path.dirname(os.path.realpath(__file__))
prm_file = os.path.join(scriptdir, "mms-parameters.xml")
mpset.read(prm_file)
# Fixed parameters
OTD = postprocessor.OTD
dt = postprocessor.dt
t_end = postprocessor.t_end
test_type = postprocessor.test
# Discretization
scheme = "SemiDecoupled"
# Names and directories
basename = postprocessor.basename
outdir = postprocessor.outdir
# Mesh independent predefined quantities
msol = create_manufactured_solution()
ic = create_initial_conditions(msol)
# Iterate over refinement level
for it in range(1, 6): # CHANGE #1: set "it in range(1, 8)"
# Decide which test to perform
if test_type == "ref":
level = it
k = 1
elif test_type == "ord":
level = 1
k = it
label = "{}_{}_level_{}_k_{}_{}".format(pcd_variant, ls, level, k,
basename)
with Timer("Prepare") as tmr_prepare:
# Prepare discretization
mesh, boundary_markers = create_domain(level)
DS = create_discretization(scheme, mesh, k)
DS.parameters["PTL"] = OTD
DS.setup()
DS.load_ic_from_simple_cpp(ic)
esol = create_exact_solution(msol, DS.finite_elements(), degrise)
bcs = create_bcs(DS, boundary_markers, esol)
# Prepare model
model = ModelFactory.create("Incompressible", DS, bcs)
cell = DS.mesh().ufl_cell()
t_src_ctl = Constant(0.0, cell=cell, name="t_src_ctl")
t_src_ptl = Constant(0.0, cell=cell, name="t_src_ptl")
f_src_ctl, g_src_ctl = \
create_source_terms(t_src_ctl, mesh, model, msol, matching_p)
f_src_ptl, g_src_ptl = \
create_source_terms(t_src_ptl, mesh, model, msol, matching_p)
# NOTE: Source terms are time-dependent. Updates to these terms
# are possible via 't_src.assign(Constant(t))', where 't'
# denotes the actual time value.
t_src = [
t_src_ctl,
]
f_src = [
f_src_ctl,
]
g_src = [
g_src_ctl,
]
if OTD == 2:
t_src.append(t_src_ptl)
g_src.append(g_src_ptl)
model.load_sources(f_src, g_src)
forms = model.create_forms(matching_p)
# NOTE: Here is the possibility to modify forms, e.g. by adding
# boundary integrals.
# Prepare solver
comm = mesh.mpi_comm()
solver = SolverFactory.create(model, forms, fix_p=True)
solver.data["solver"]["NS"] = \
create_pcd_solver(comm, pcd_variant, ls, mumps_debug=False)
# PETScOptions.set("ksp_monitor")
# solver.data["solver"]["NS"].set_from_options()
# Prepare time-stepping algorithm
xfields = None
# NOTE: Uncomment the following block of code to get XDMF output
# pv = DS.primitive_vars_ctl()
# phi, chi, v, p = pv["phi"], pv["chi"], pv["v"], pv["p"]
# phi_, chi_, v_ = phi.split(), chi.split(), v.split()
# xfields = list(zip(phi_, len(phi_)*[None,])) \
# + list(zip(v_, len(v_)*[None,])) \
# + [(p.dolfin_repr(), None),]
hook = prepare_hook(t_src, model, esol, degrise, {})
logfile = "log_{}.dat".format(label)
#info("BREAK POINT %ia" % level)
TS = TimeSteppingFactory.create("ConstantTimeStep",
comm,
solver,
hook=hook,
logfile=logfile,
xfields=xfields,
outdir=outdir)
#info("BREAK POINT %ib" % level) <-- not reached for level == 2
# when running in parallel
# Time-stepping
t_beg = 0.0
with Timer("Time stepping") as tmr_tstepping:
result = TS.run(t_beg, t_end, dt, OTD)
# Get number of Krylov iterations if relevant
try:
krylov_it = solver.iters["NS"][0]
except AttributeError:
krylov_it = 0
# Prepare results
name = logfile[4:-4]
x_var = k if test_type == "ord" else mesh.hmin()
result.update(scheme=scheme,
pcd_variant=pcd_variant,
ls=ls,
krylov_it=krylov_it,
ndofs=DS.num_dofs(),
dt=dt,
t_end=t_end,
OTD=OTD,
err=hook.err,
x_var=x_var,
tmr_prepare=tmr_prepare.elapsed()[0],
tmr_tstepping=tmr_tstepping.elapsed()[0])
print(name, result["ndofs"], result["it"], result["krylov_it"],
result["tmr_tstepping"])
# Send to posprocessor
rank = MPI.rank(comm)
postprocessor.add_result(rank, result)
# Save results into a binary file
filename = "results_{}.pickle".format(label)
postprocessor.save_results(filename)
# Pop results that we do not want to report at the moment
postprocessor.pop_items(["ndofs", "scheme", "tmr_prepare"])
# Flush plots as we now have data for all level values
postprocessor.flush_plots()
# Store timings
#datafile = os.path.join(outdir, "timings.xml")
#dump_timings_to_xml(datafile, TimingClear_clear)
# Cleanup
set_log_level(INFO)
#mpset.write(comm, prm_file) # uncomment to save parameters
mpset.refresh()
gc.collect()
def test_scaling_mesh(nu, pcd_variant, ls, postprocessor):
#set_log_level(WARNING)
# Read parameters
scriptdir = os.path.dirname(os.path.realpath(__file__))
prm_file = os.path.join(scriptdir, "step-parameters.xml")
mpset.read(prm_file)
# Adjust parameters
mpset["model"]["nu"]["1"] = nu
mpset["model"]["nu"]["2"] = nu
# Parameters for setting up MUFLON components
dt = postprocessor.dt
t_end = postprocessor.t_end # final time of the simulation
scheme = "SemiDecoupled"
OTD = 1
k = 1
modulo_factor = 2
# Names and directories
outdir = postprocessor.outdir
# Mesh independent predefined quantities
ic = SimpleCppIC()
ic.add("phi", "1.0")
# Prepare figure for plotting the vorticity
fig_curl = pyplot.figure()
gs = gridspec.GridSpec(2, 2, height_ratios=[3, 1], width_ratios=[0.01, 1], hspace=0.05)
ax_curl = fig_curl.add_subplot(gs[0, 1])
ax_curl.set_xlabel(r"time $t$")
ax_curl.set_ylabel(r"$\omega_\Omega = \int_\Omega \nabla \times \mathbf{v}$")
del gs
for level in range(4):
with Timer("Prepare") as tmr_prepare:
# Prepare space discretization
mesh, boundary_markers = create_domain(level)
#pyplot.figure(); plot(mesh)
#pyplot.savefig(os.path.join(outdir, "mesh.pdf"))
if dt is None:
hh = mesh.hmin()/(2.0**0.5) # mesh size in the direction of inflow
umax = 1.0 # max velocity at the inlet
dt = 0.8*hh/umax # automatically computed time step
del hh, umax
label = "level_{}_nu_{}_{}_{}_dt_{}_{}".format(
level, nu, pcd_variant, ls, dt, postprocessor.basename)
DS = create_discretization(scheme, mesh, k)
DS.setup()
DS.load_ic_from_simple_cpp(ic)
# Prepare boundary conditions
bcs, inflow = create_bcs(DS, boundary_markers, pcd_variant) #, t0=10*dt
# Prepare model
model = ModelFactory.create("Incompressible", DS, bcs)
#model.parameters["THETA2"] = 0.0
# Create forms
forms = model.create_forms()
if ls == "direct":
forms["pcd"]["a_pc"] = None
# Add boundary integrals
n = DS.facet_normal()
ds_marked = Measure("ds", subdomain_data=boundary_markers)
test = DS.test_functions()
trial = DS.trial_functions()
pv = DS.primitive_vars_ctl(indexed=True)
pv0 = DS.primitive_vars_ptl(0, indexed=True)
cc = model.coeffs
w = cc["rho"]*pv0["v"] + cc["THETA2"]*cc["J"]
a_surf = (
0.5*inner(w, n)*inner(trial["v"], test["v"])
- cc["nu"]*inner(dot(grad(trial["v"]).T, n), test["v"])
)*ds_marked(2)
forms["lin"]["lhs"] += a_surf
if forms["pcd"]["a_pc"] is not None:
forms["pcd"]["a_pc"] += a_surf
if pcd_variant == "BRM2":
forms["pcd"]["kp"] -= \
(1.0/cc["nu"])*inner(w, n)*test["p"]*trial["p"]*ds_marked(1)
# TODO: Is this beneficial?
# forms["pcd"]["kp"] -= \
# (1.0/cc["nu"])*inner(w, n)*test["p"]*trial["p"]*ds_marked(0)
# TODO: Alternatively try:
# forms["pcd"]["kp"] -= \
# (1.0/cc["nu"])*inner(w, n)*test["p"]*trial["p"]*ds
# Prepare solver
comm = mesh.mpi_comm()
solver = SolverFactory.create(model, forms)
prefix = "LU"
solver.data["solver"]["NS"] = \
create_pcd_solver(comm, pcd_variant, ls, mumps_debug=False)
prefix = solver.data["solver"]["NS"].get_options_prefix()
#PETScOptions.set(prefix+"ksp_monitor")
#solver.data["solver"]["NS"].set_from_options()
# Prepare time-stepping algorithm
pv = DS.primitive_vars_ctl()
xfields = list(zip(pv["phi"].split(), ("phi",)))
xfields.append((pv["p"].dolfin_repr(), "p"))
xfields.append((pv["v"].dolfin_repr(), "v"))
functionals = {"t": [], "vorticity": []}
hook = prepare_hook(DS, functionals, modulo_factor, inflow)
logfile = "log_{}.dat".format(label)
TS = TimeSteppingFactory.create("ConstantTimeStep", comm, solver,
hook=hook, logfile=logfile, xfields=xfields, outdir=outdir)
TS.parameters["xdmf"]["folder"] = "XDMF_{}".format(label)
TS.parameters["xdmf"]["modulo"] = modulo_factor
TS.parameters["xdmf"]["flush"] = True
TS.parameters["xdmf"]["iconds"] = True
# Time-stepping
t_beg = 0.0
with Timer("Time stepping") as tmr_tstepping:
result = TS.run(t_beg, t_end, dt, OTD)
# Get number of Krylov iterations if relevant
try:
krylov_it = solver.iters["NS"][0]
except AttributeError:
krylov_it = 0
# Prepare results (already contains dt, it, t_end, tmr_solve)
result.update(
nu=nu,
pcd_variant=pcd_variant,
ls=ls,
krylov_it=krylov_it,
ndofs=DS.num_dofs(),
level=level,
h_min=mesh.hmin(),
tmr_prepare=tmr_prepare.elapsed()[0],
tmr_tstepping=tmr_tstepping.elapsed()[0],
scheme=scheme,
OTD=OTD,
k=k,
t=functionals["t"],
vorticity=functionals["vorticity"]
)
print(label, prefix, result["ndofs"], result["it"],
result["tmr_tstepping"], result["krylov_it"])
# Send to posprocessor
rank = MPI.rank(comm)
postprocessor.add_result(rank, result)
# Add vorticity plot
ax_curl.plot(functionals["t"], functionals["vorticity"], label=label)
ax_curl.legend(bbox_to_anchor=(0, -0.2), loc=2, borderaxespad=0,
fontsize='x-small', ncol=1)
# Save results into a binary file
filename = "results_{}.pickle".format(label)
postprocessor.save_results(filename)
# Pop results that we do not want to report at the moment
postprocessor.pop_items([
"level", "h_min", "tmr_prepare", "tmr_tstepping",
"scheme", "OTD", "k", "t", "vorticity"])
# Flush plots as we now have data for all level values
postprocessor.flush_plots()
fig_curl.savefig(os.path.join(outdir, "fig_vorticity_{}.pdf".format(label)))
# # Plot last obtained solution
# pv = DS.primitive_vars_ctl()
# v = as_vector(pv["v"].split())
# p = pv["p"].dolfin_repr()
# #phi = pv["phi"].split()
# size = MPI.size(mesh.mpi_comm())
# rank = MPI.rank(mesh.mpi_comm())
# pyplot.figure()
# pyplot.subplot(2, 1, 1)
# plot(v, title="velocity")
# pyplot.subplot(2, 1, 2)
# plot(p, title="pressure")
# pyplot.savefig(os.path.join(outdir, "fig_v_p_size{}_rank{}.pdf".format(size, rank)))
# pyplot.figure()
# plot(p, title="pressure", mode="warp")
# pyplot.savefig(os.path.join(outdir, "fig_warp_size{}_rank{}.pdf".format(size, rank)))
# Store timings
#datafile = os.path.join(outdir, "timings.xml")
#dump_timings_to_xml(datafile, TimingClear_clear)
# Cleanup
set_log_level(INFO)
#mpset.write(comm, prm_file) # uncomment to save parameters
mpset.refresh()
gc.collect()
