def print_min_max(u, title, color='97', cls=None):
"""
Print the minimum and maximum values of <u>, a Vector, Function, or array.
"""
#if cls is not None:
# color = cls.color()
if isinstance(u, GenericVector):
uMin = MPI.min(mpi_comm_world(), u.min())
uMax = MPI.max(mpi_comm_world(), u.max())
s = title + ' <min, max> : <%.3e, %.3e>' % (uMin, uMax)
print_text(s, color)
elif isinstance(u, ndarray):
if u.dtype != float64:
u = u.astype(float64)
uMin = MPI.min(mpi_comm_world(), u.min())
uMax = MPI.max(mpi_comm_world(), u.max())
s = title + ' <min, max> : <%.3e, %.3e>' % (uMin, uMax)
print_text(s, color)
elif isinstance(u, Function):# \
# or isinstance(u, dolfin.functions.function.Function):
uMin = MPI.min(mpi_comm_world(), u.vector().min())
uMax = MPI.max(mpi_comm_world(), u.vector().max())
s = title + ' <min, max> : <%.3e, %.3e>' % (uMin, uMax)
print_text(s, color)
elif isinstance(u, int) or isinstance(u, float):
s = title + ' : %.3e' % u
print_text(s, color)
elif isinstance(u, Constant):
s = title + ' : %.3e' % u(0)
print_text(s, color)
else:
er = title + ": print_min_max function requires a Vector, Function" \
+ ", array, int or float, not %s." % type(u)
print_text(er, 'red', 1)
t0 = timer.time()
#try:
if r["space"] == "mixedspace":
problem_mix(**vars())
elif r["space"] == "singlespace":
problem_single()
else:
print("Problem type %s is not implemented, only mixedspace " +
"and singlespace are valid options") % r["space"]
sys.exit(0)
#except Exception as e:
# print "Problems for solver", r["name"]
# print "Unexpected error:", sys.exc_info()[0]
# print e
# print "Move on the the next solver"
r["number_of_cores"] = MPI.max(mpi_comm_world(), MPI.rank(
mpi_comm_world())) + 1
r["solution_time"] = MPI.sum(mpi_comm_world(),
timer.time() - t0) / (r["number_of_cores"])
displacement = probe.array()
probe.clear()
# Store results
if MPI.rank(mpi_comm_world()) == 0 and not load:
results.append(
(displacement[0, :], displacement[1, :], np.array(time)))
if not path.exists(r["case_path"]):
makedirs(r["case_path"])
results[-1][0].dump(path.join(r["case_path"], "dis_x.np"))
results[-1][1].dump(path.join(r["case_path"], "dis_y.np"))
results[-1][2].dump(path.join(r["case_path"], "time.np"))