def setupMeshes(cls, mesh, N, num_refine=0, randref=(1.0, 1.0)):
"""Create a set of N meshes based on provided mesh. Parameters
num_refine>=0 and randref specify refinement
adjustments. num_refine specifies the number of refinements
per mesh, randref[0] specifies the probability that a given
mesh is refined, and randref[1] specifies the probability that
an element of the mesh is refined (if it is refined at all).
"""
assert num_refine >= 0
assert 0 < randref[0] <= 1.0
assert 0 < randref[1] <= 1.0
# create set of (refined) meshes
meshes = list();
for _ in range(N):
m = Mesh(mesh)
for _ in range(num_refine):
if randref[0] == 1.0 and randref[1] == 1.0:
m = refine(m)
elif random() <= randref[0]:
cell_markers = CellFunction("bool", m)
cell_markers.set_all(False)
cell_ids = range(m.num_cells())
shuffle(cell_ids)
num_ref_cells = int(ceil(m.num_cells() * randref[1]))
for cell_id in cell_ids[0:num_ref_cells]:
cell_markers[cell_id] = True
m = refine(m, cell_markers)
meshes.append(m)
return meshes
def test_convert_diffpack(self):
from dolfin import Mesh, MPI, MeshFunction
if MPI.num_processes() != 1:
return
fname = os.path.join("data", "diffpack_tet")
dfname = fname+".xml"
# Read triangle file and convert to a dolfin xml mesh file
meshconvert.diffpack2xml(fname+".grid", dfname)
# Read in dolfin mesh and check number of cells and vertices
mesh = Mesh(dfname)
self.assertEqual(mesh.num_vertices(), 27)
self.assertEqual(mesh.num_cells(), 48)
self.assertEqual(mesh.domains().markers(3).size(), 48)
self.assertEqual(mesh.domains().markers(2).size(), 16)
mf_basename = dfname.replace(".xml", "_marker_%d.xml")
for marker, num in [(3, 9), (6, 9), (7, 3), (8, 1)]:
mf_name = mf_basename % marker
mf = MeshFunction("uint", mesh, mf_name)
self.assertEqual(sum(mf.array()==marker), num)
os.unlink(mf_name)
# Clean up
os.unlink(dfname)
def test_convert_diffpack_2d(self):
from dolfin import Mesh, MPI, MeshFunction
fname = os.path.join(os.path.dirname(__file__), "data", "diffpack_tri")
dfname = fname + ".xml"
# Read triangle file and convert to a dolfin xml mesh file
meshconvert.diffpack2xml(fname + ".grid", dfname)
# Read in dolfin mesh and check number of cells and vertices
mesh = Mesh(dfname)
self.assertEqual(mesh.num_vertices(), 41)
self.assertEqual(mesh.num_cells(), 64)
self.assertEqual(len(mesh.domains().markers(2)), 64)
mf_basename = dfname.replace(".xml", "_marker_%d.xml")
for marker, num in [(1, 10), (2, 5), (3, 5)]:
mf_name = mf_basename % marker
mf = MeshFunction("size_t", mesh, mf_name)
self.assertEqual(sum(mf.array() == marker), num)
os.unlink(mf_name)
# Clean up
os.unlink(dfname)
def test_convert_diffpack(self):
from dolfin import Mesh, MPI, MeshFunction, mpi_comm_world
if MPI.size(mpi_comm_world()) != 1:
return
fname = os.path.join("data", "diffpack_tet")
dfname = fname + ".xml"
# Read triangle file and convert to a dolfin xml mesh file
meshconvert.diffpack2xml(fname + ".grid", dfname)
# Read in dolfin mesh and check number of cells and vertices
mesh = Mesh(dfname)
self.assertEqual(mesh.num_vertices(), 27)
self.assertEqual(mesh.num_cells(), 48)
self.assertEqual(len(mesh.domains().markers(3)), 48)
self.assertEqual(len(mesh.domains().markers(2)), 16)
mf_basename = dfname.replace(".xml", "_marker_%d.xml")
for marker, num in [(3, 9), (6, 9), (7, 3), (8, 1)]:
mf_name = mf_basename % marker
mf = MeshFunction("size_t", mesh, mf_name)
self.assertEqual(sum(mf.array() == marker), num)
os.unlink(mf_name)
# Clean up
os.unlink(dfname)
def test_convert_diffpack_2d(self):
from dolfin import Mesh, MPI, MeshFunction, mpi_comm_world
fname = os.path.join(os.path.dirname(__file__), "data", "diffpack_tri")
dfname = fname+".xml"
# Read triangle file and convert to a dolfin xml mesh file
meshconvert.diffpack2xml(fname+".grid", dfname)
# Read in dolfin mesh and check number of cells and vertices
mesh = Mesh(dfname)
self.assertEqual(mesh.num_vertices(), 41)
self.assertEqual(mesh.num_cells(), 64)
self.assertEqual(len(mesh.domains().markers(2)), 64)
mf_basename = dfname.replace(".xml", "_marker_%d.xml")
for marker, num in [(1,10), (2,5), (3,5)]:
mf_name = mf_basename % marker
mf = MeshFunction("size_t", mesh, mf_name)
self.assertEqual(sum(mf.array()==marker), num)
os.unlink(mf_name)
# Clean up
os.unlink(dfname)
def convert(msh_file, h5_file):
'''Temporary version of convert from msh to h5'''
root, _ = os.path.splitext(msh_file)
assert os.path.splitext(msh_file)[1] == '.msh'
assert os.path.splitext(h5_file)[1] == '.h5'
# Get the xml mesh
xml_file = '.'.join([root, 'xml'])
subprocess.call(['dolfin-convert %s %s' % (msh_file, xml_file)], shell=True)
# Success?
assert os.path.exists(xml_file)
mesh = Mesh(xml_file)
out = HDF5File(mesh.mpi_comm(), h5_file, 'w')
out.write(mesh, 'mesh')
info('Mesh has %d cells' % mesh.num_cells())
info('Mesh size %g %g' % (mesh.hmin(), mesh.hmax()))
outputs = [mesh]
# Save ALL data as facet_functions
names = ('surfaces', 'volumes')
for name, region in zip(names, ('facet_region.xml', 'physical_region.xml')):
r_xml_file = '_'.join([root, region])
f = MeshFunction('size_t', mesh, r_xml_file)
out.write(f, name)
outputs.append(f)
return outputs
def CladdingR_solver(FC_mesh, FC_facets, FC_fs, FC_info, D_post, R_path):
FC_fi, FC_fo = FC_fs
h, Tfc_inner, Tb, FC_Tave = FC_info
# Reading mesh data stored in .xdmf files.
mesh = Mesh()
with XDMFFile(FC_mesh) as infile:
infile.read(mesh)
mvc = MeshValueCollection("size_t", mesh, 1)
with XDMFFile(FC_facets) as infile:
infile.read(mvc, "name_to_read")
mf = cpp.mesh.MeshFunctionSizet(mesh, mvc)
#File("Circle_facet.pvd").write(mf)
# Mesh data
print('CladdingRod_mesh data\n', 'Number of cells: ', mesh.num_cells(),
'\n Number of nodes: ', mesh.num_vertices())
# Define variational problem
V = FunctionSpace(mesh, 'P', 1)
u = Function(V)
v = TestFunction(V)
# Define boundary conditions base on pygmsh mesh mark
bc = DirichletBC(V, Constant(Tfc_inner), mf, FC_fi)
ds = Measure("ds", domain=mesh, subdomain_data=mf, subdomain_id=FC_fo)
# Variational formulation
# Klbda_ZrO2 = 18/1000 # W/(m K) --> Nuclear reactor original source
# Klbda_ZrO2 = Constant(K_ZrO2(FC_Tave))
F = K_ZrO2(u) * dot(grad(u), grad(v)) * dx + h * (u - Tb) * v * ds
# Compute solution
du = TrialFunction(V)
Gain = derivative(F, u, du)
solve(F==0, u, bc, J=Gain, \
solver_parameters={"newton_solver": {"linear_solver": "lu",
"relative_tolerance": 1e-9}}, \
form_compiler_parameters={"cpp_optimize": True,
"representation": "uflacs",
"quadrature_degree" : 2}
) # mumps
# Save solution
if D_post:
fU_out = XDMFFile(os.path.join(R_path, 'FuelCladding', 'u.xdmf'))
fU_out.write_checkpoint(u, "T", 0, XDMFFile.Encoding.HDF5, False)
fU_out.close()
def FuelR_solver(FR_mesh, FR_facets, FR_f, FRod_info, D_post, R_path):
Qv, Tfr_outer, FR_Tave = FRod_info
# Reading mesh data stored in .xdmf files.
mesh = Mesh()
with XDMFFile(FR_mesh) as infile:
infile.read(mesh)
mvc = MeshValueCollection("size_t", mesh, 1)
with XDMFFile(FR_facets) as infile:
infile.read(mvc, "name_to_read")
mf = cpp.mesh.MeshFunctionSizet(mesh, mvc)
#File("Circle_facet.pvd").write(mf)
# Mesh data
print('FuelRod_mesh data\n', 'Number of cells: ', mesh.num_cells(),
'\n Number of nodes: ', mesh.num_vertices())
# Define variational problem
V = FunctionSpace(mesh, 'P', 1)
u = Function(V)
v = TestFunction(V)
f = Constant(Qv)
# Define boundary conditions base on pygmsh mesh mark
bc = DirichletBC(V, Constant(Tfr_outer), mf, FR_f)
# Variational formulation
# Klbda_UO2 = Constant(K_UO2(FR_Tave))
F = K_UO2(u) * dot(grad(u), grad(v)) * dx - f * v * dx
# Compute solution
du = TrialFunction(V)
Gain = derivative(F, u, du)
solve(F==0, u, bc, J=Gain, \
solver_parameters={"newton_solver": {"linear_solver": "lu",
"relative_tolerance": 1e-9}}, \
form_compiler_parameters={"cpp_optimize": True,
"representation": "uflacs",
"quadrature_degree" : 2}
) # mumps
# Save solution
if D_post:
fU_out = XDMFFile(os.path.join(R_path, 'FuelRod', 'u.xdmf'))
fU_out.write_checkpoint(u, "T", 0, XDMFFile.Encoding.HDF5, False)
fU_out.close()
def convert(msh_file, h5_file, save_mvc=False):
'''Temporary version of convertin from msh to h5'''
root, _ = os.path.splitext(msh_file)
assert os.path.splitext(msh_file)[1] == '.msh'
assert os.path.splitext(h5_file)[1] == '.h5'
# Get the xml mesh
xml_file = '.'.join([root, 'xml'])
subprocess.call(['dolfin-convert %s %s' % (msh_file, xml_file)], shell=True)
# Success?
assert os.path.exists(xml_file)
mesh = Mesh(xml_file)
out = HDF5File(mesh.mpi_comm(), h5_file, 'w')
out.write(mesh, 'mesh')
print('Mesh has %d cells' % mesh.num_cells())
print('Mesh size %g %g' % (mesh.hmin(), mesh.hmax()))
# Save ALL data as facet_functions
names = ('surfaces', 'volumes')
if not save_mvc:
for name, region in zip(names, ('facet_region.xml', 'physical_region.xml')):
r_xml_file = '_'.join([root, region])
f = MeshFunction('size_t', mesh, r_xml_file)
print('%d %s with 1' % (sum(1 for _ in SubsetIterator(f, 1)), name))
out.write(f, name)
return True
for name, region in zip(names, ('facet_region.xml', 'physical_region.xml')):
r_xml_file = '_'.join([root, region])
f = MeshFunction('size_t', mesh, r_xml_file)
# With mesh value collection we only store nonzero tags
mvc = MeshValueCollection('size_t', mesh, f.dim())
# Fill
fill_mvc_from_mf(f, mvc)
# And save
out.write(mvc, name)
return True
def test_convert_triangle(self): # Disabled because it fails, see FIXME below
# test no. 1
from dolfin import Mesh, MPI
if MPI.num_processes() != 1:
return
fname = os.path.join("data", "triangle")
dfname = fname+".xml"
# Read triangle file and convert to a dolfin xml mesh file
meshconvert.triangle2xml(fname, dfname)
# Read in dolfin mesh and check number of cells and vertices
mesh = Mesh(dfname)
self.assertEqual(mesh.num_vertices(), 96)
self.assertEqual(mesh.num_cells(), 159)
# Clean up
os.unlink(dfname)
# test no. 2
from dolfin import MPI, Mesh, MeshFunction, \
edges, Edge, faces, Face, \
SubsetIterator, facets, CellFunction
if MPI.num_processes() != 1:
return
fname = os.path.join("data", "test_Triangle_3")
dfname = fname+".xml"
dfname0 = fname+".attr0.xml"
# Read triangle file and convert to a dolfin xml mesh file
meshconvert.triangle2xml(fname, dfname)
# Read in dolfin mesh and check number of cells and vertices
mesh = Mesh(dfname)
mesh.init()
mfun = MeshFunction('double', mesh, dfname0)
self.assertEqual(mesh.num_vertices(), 58)
self.assertEqual(mesh.num_cells(), 58)
# Create a size_t CellFunction and assign the values based on the
# converted Meshfunction
cf = CellFunction("size_t", mesh)
cf.array()[mfun.array()==10.0] = 0
cf.array()[mfun.array()==-10.0] = 1
# Meassure total area of cells with 1 and 2 marker
add = lambda x, y : x+y
area0 = reduce(add, (Face(mesh, cell.index()).area() \
for cell in SubsetIterator(cf, 0)), 0.0)
area1 = reduce(add, (Face(mesh, cell.index()).area() \
for cell in SubsetIterator(cf, 1)), 0.0)
total_area = reduce(add, (face.area() for face in faces(mesh)), 0.0)
# Check that all cells in the two domains are either above or below y=0
self.assertTrue(all(cell.midpoint().y()<0 for cell in SubsetIterator(cf, 0)))
self.assertTrue(all(cell.midpoint().y()>0 for cell in SubsetIterator(cf, 1)))
# Check that the areas add up
self.assertAlmostEqual(area0+area1, total_area)
# Measure the edge length of the two edge domains
edge_markers = mesh.domains().facet_domains()
self.assertTrue(edge_markers is not None)
length0 = reduce(add, (Edge(mesh, e.index()).length() \
for e in SubsetIterator(edge_markers, 0)), 0.0)
length1 = reduce(add, (Edge(mesh, e.index()).length() \
for e in SubsetIterator(edge_markers, 1)), 0.0)
# Total length of all edges and total length of boundary edges
total_length = reduce(add, (e.length() for e in edges(mesh)), 0.0)
boundary_length = reduce(add, (Edge(mesh, f.index()).length() \
for f in facets(mesh) if f.exterior()), 0.0)
# Check that the edges add up
self.assertAlmostEqual(length0+length1, total_length)
self.assertAlmostEqual(length1, boundary_length)
# Clean up
os.unlink(dfname)
os.unlink(dfname0)
def test_convert_triangle(
self): # Disabled because it fails, see FIXME below
# test no. 1
from dolfin import Mesh, MPI
fname = os.path.join(os.path.dirname(__file__), "data", "triangle")
dfname = fname + ".xml"
# Read triangle file and convert to a dolfin xml mesh file
meshconvert.triangle2xml(fname, dfname)
# Read in dolfin mesh and check number of cells and vertices
mesh = Mesh(dfname)
self.assertEqual(mesh.num_vertices(), 96)
self.assertEqual(mesh.num_cells(), 159)
# Clean up
os.unlink(dfname)
# test no. 2
from dolfin import MPI, Mesh, MeshFunction, \
edges, Edge, faces, Face, \
SubsetIterator, facets
fname = os.path.join(os.path.dirname(__file__), "data",
"test_Triangle_3")
dfname = fname + ".xml"
dfname0 = fname + ".attr0.xml"
# Read triangle file and convert to a dolfin xml mesh file
meshconvert.triangle2xml(fname, dfname)
# Read in dolfin mesh and check number of cells and vertices
mesh = Mesh(dfname)
mesh.init()
mfun = MeshFunction('double', mesh, dfname0)
self.assertEqual(mesh.num_vertices(), 58)
self.assertEqual(mesh.num_cells(), 58)
# Create a size_t MeshFunction and assign the values based on the
# converted Meshfunction
cf = MeshFunction("size_t", mesh, mesh.topology().dim())
cf.array()[mfun.array() == 10.0] = 0
cf.array()[mfun.array() == -10.0] = 1
# Meassure total area of cells with 1 and 2 marker
add = lambda x, y: x + y
area0 = reduce(add, (Face(mesh, cell.index()).area() \
for cell in SubsetIterator(cf, 0)), 0.0)
area1 = reduce(add, (Face(mesh, cell.index()).area() \
for cell in SubsetIterator(cf, 1)), 0.0)
total_area = reduce(add, (face.area() for face in faces(mesh)), 0.0)
# Check that all cells in the two domains are either above or below y=0
self.assertTrue(
all(cell.midpoint().y() < 0 for cell in SubsetIterator(cf, 0)))
self.assertTrue(
all(cell.midpoint().y() > 0 for cell in SubsetIterator(cf, 1)))
# Check that the areas add up
self.assertAlmostEqual(area0 + area1, total_area)
# Measure the edge length of the two edge domains
#edge_markers = mesh.domains().facet_domains()
edge_markers = mesh.domains().markers(mesh.topology().dim() - 1)
self.assertTrue(edge_markers is not None)
#length0 = reduce(add, (Edge(mesh, e.index()).length() \
# for e in SubsetIterator(edge_markers, 0)), 0.0)
length0, length1 = 0.0, 0.0
for item in list(edge_markers.items()):
if item[1] == 0:
e = Edge(mesh, int(item[0]))
length0 += Edge(mesh, int(item[0])).length()
elif item[1] == 1:
length1 += Edge(mesh, int(item[0])).length()
# Total length of all edges and total length of boundary edges
total_length = reduce(add, (e.length() for e in edges(mesh)), 0.0)
boundary_length = reduce(add, (Edge(mesh, f.index()).length() \
for f in facets(mesh) if f.exterior()), 0.0)
# Check that the edges add up
self.assertAlmostEqual(length0 + length1, total_length)
self.assertAlmostEqual(length1, boundary_length)
# Clean up
os.unlink(dfname)
os.unlink(dfname0)
if __name__ == "__main__":
xlim = 0.0, 3.0
ylim = 0.0, 0.0127
WAid = 12
INid = 13
BND_ids = WAid, INid
meszf = 0.001 # mesh element size factor
Domain, Facets = Generate_PBRpygmsh(xlim,
ylim,
BND_ids,
meszf,
folder='pygmeshio_test')
mesh_D = Mesh()
with XDMFFile(Domain) as infile:
infile.read(mesh_D)
mesh_F = Mesh()
with XDMFFile(Facets) as infile:
infile.read(mesh_F)
print('num_cells :', mesh_D.num_cells())
print('num_vertices:', mesh_D.num_vertices())
print('cell_type :', mesh_D.ufl_cell())
#print('num_facets:', mesh_F.num_facets())
#print('num_edges:', mesh_F.num_edges())
def mesh_around_1d(mesh, size=1, scale=10, padding=0.05):
'''
From a 1d in xd (X > 1) mesh (in XML format) produce a Xd mesh where
the 1d structure is embedded. Mesh size close to strucure should
be size(given as multiple of hmin(), elsewhere scale * size. Padding
controls size of the bounding box.
'''
dot = mesh.find('.')
root, ext = mesh[:dot], mesh[dot:]
assert ext == '.xml' or ext == '.xml.gz', ext
mesh = Mesh(mesh)
gdim = mesh.geometry().dim()
assert gdim > 1 and mesh.topology().dim() == 1
x = mesh.coordinates()
mesh.init(1, 0)
# Compute fall back mesh size:
assert size > 0
size = mesh.hmin() * size
# Don't allow zero padding - collision of lines with bdry segfaults
# too ofter so we prevent it
assert padding > 0
# Finally scale better be positive
assert scale > 0
point = (lambda xi: tuple(xi) + (0, ))\
if gdim == 2 else (lambda xi: tuple(xi))
geo = '.'.join([root, 'geo'])
with open(geo, 'w') as outfile:
# Setup
outfile.write('SetFactory("OpenCASCADE");\n')
outfile.write('size = %g;\n' % size)
outfile.write('SIZE = %g;\n' % (size * scale))
# Points
fmt = 'Point(%d) = {%.16f, %.16f, %.16f, size};\n'
for i, xi in enumerate(x, 1):
outfile.write(fmt % ((i, ) + point(xi)))
# Lines
fmt = 'Line(%d) = {%d, %d};\n'
for i, cell in enumerate(cells(mesh), 1):
outfile.write(fmt % ((i, ) + tuple(cell.entities(0) + 1)))
# BBox
xmin, xmax = x.min(0), x.max(0)
padding = (xmax - xmin) * padding / 2.
xmin -= padding
xmax += padding
dx = xmax - xmin
if gdim == 2 or dx[-1] < 1E-14: # All points are on a plane
rect = 'Rectangle(1) = {%g, %g, %g, %g, %g};\n' % (
xmin[0], xmin[1], 0 if gdim == 2 else xmin[2], dx[0], dx[1])
outfile.write(rect)
bbox = 'Surface'
else:
box = 'Box(1) = {%g, %g, %g, %g, %g, %g};\n' % (
xmin[0], xmin[1], xmin[2], dx[0], dx[1], dx[2])
outfile.write(box)
bbox = 'Volume'
# Crack
for line in xrange(1, mesh.num_cells() + 1):
outfile.write('Line{%d} In %s{1};\n' % (line, bbox))
# Add Physical volume/surface
outfile.write('Physical %s(1) = {1};\n' % bbox)
# Add Physical surface/line
lines = ', '.join(
map(lambda v: '%d' % v, xrange(1,
mesh.num_cells() + 1)))
outfile.write('Physical Line(1) = {%s};\n' % lines)
return geo, gdim
def scalar_laplacians(
mesh: df.Mesh,
markers: Optional[Dict[str, int]] = None,
ffun: Optional[MeshFunction] = None,
use_krylov_solver: bool = False,
krylov_solver_atol: Optional[float] = None,
krylov_solver_rtol: Optional[float] = None,
krylov_solver_max_its: Optional[int] = None,
verbose: bool = False,
strict: bool = False,
) -> Dict[str, df.Function]:
"""
Calculate the laplacians
Arguments
---------
mesh : dolfin.Mesh
A dolfin mesh
markers : dict (optional)
A dictionary with the markers for the
different bondaries defined in the facet function
or within the mesh itself.
The follwing markers must be provided:
'base', 'lv', 'epi, 'rv' (optional).
If the markers are not provided the following default
vales will be used: base = 10, rv = 20, lv = 30, epi = 40.
fiber_space : str
A string on the form {familiy}_{degree} which
determines for what space the fibers should be calculated for.
use_krylov_solver: bool
If True use Krylov solver, by default False
krylov_solver_atol: float (optional)
If a Krylov solver is used, this option specifies a
convergence criterion in terms of the absolute
residual. Default: 1e-15.
krylov_solver_rtol: float (optional)
If a Krylov solver is used, this option specifies a
convergence criterion in terms of the relative
residual. Default: 1e-10.
krylov_solver_max_its: int (optional)
If a Krylov solver is used, this option specifies the
maximum number of iterations to perform. Default: 10000.
verbose: bool
If true, print more info, by default False
strict: bool
If true raise RuntimeError if solutions does not sum to 1.0
"""
if not isinstance(mesh, df.Mesh):
raise TypeError("Expected a dolfin.Mesh as the mesh argument.")
# Init connectivities
mesh.init(2)
if ffun is None:
ffun = df.MeshFunction("size_t", mesh, 2, mesh.domains())
# Boundary markers, solutions and cases
cases, boundaries, markers = find_cases_and_boundaries(ffun, markers)
markers_str = "\n".join(
["{}: {}".format(k, v) for k, v in markers.items()])
df.info(("Compute scalar laplacian solutions with the markers: \n"
"{}").format(markers_str, ), )
check_boundaries_are_marked(
mesh=mesh,
ffun=ffun,
markers=markers,
boundaries=boundaries,
)
# Compte the apex to base solutons
num_vertices = mesh.num_vertices()
num_cells = mesh.num_cells()
if mesh.mpi_comm().size > 1:
num_vertices = mesh.mpi_comm().allreduce(num_vertices)
num_cells = mesh.mpi_comm().allreduce(num_cells)
df.info(" Num vertices: {0}".format(num_vertices))
df.info(" Num cells: {0}".format(num_cells))
if "mv" in cases and "av" in cases:
# Use Doste approach
pass
# Else use the Bayer approach
return bayer(
cases=cases,
mesh=mesh,
markers=markers,
ffun=ffun,
verbose=verbose,
use_krylov_solver=use_krylov_solver,
strict=strict,
krylov_solver_atol=krylov_solver_atol,
krylov_solver_rtol=krylov_solver_rtol,
krylov_solver_max_its=krylov_solver_max_its,
)
mesh_size_parser.add_argument('--no_mesh_size',
dest='mesh_size',
action='store_false')
parser.set_defaults(mesh_size=False)
args = parser.parse_args()
h5_file = convert(args.input)
# VTK visualize tags
if args.save_pvd or args.mesh_size:
h5 = HDF5File(mpi_comm_world(), h5_file, 'r')
mesh = Mesh()
h5.read(mesh, 'mesh', False)
info('Mesh has %d cells' % mesh.num_cells())
info('Mesh has %d vertices' % mesh.num_vertices())
info('Box size %s' %
(mesh.coordinates().max(axis=0) - mesh.coordinates().min(axis=0)))
hmin, hmax = mesh.hmin(), mesh.hmax()
info('Mesh has sizes %g %g' % (hmin, hmax))
root = os.path.splitext(args.input)[0]
tdim = mesh.topology().dim()
data_sets = ('curves', 'surfaces', 'volumes')
dims = (1, tdim - 1, tdim)
for ds, dim in zip(data_sets, dims):
if h5.has_dataset(ds):
f = MeshFunction('size_t', mesh, dim, 0)
