def convert_meshfunctions_to_submesh(mesh, submesh, meshfunctions_on_mesh):
assert meshfunctions_on_mesh is None or (isinstance(
meshfunctions_on_mesh, list) and len(meshfunctions_on_mesh) > 0)
if meshfunctions_on_mesh is None:
return None
meshfunctions_on_submesh = list()
# Create submesh subdomains
for mesh_subdomain in meshfunctions_on_mesh:
submesh_subdomain = MeshFunction("size_t", submesh,
mesh_subdomain.dim())
submesh_subdomain.set_all(0)
assert submesh_subdomain.dim() in (submesh.topology().dim(),
submesh.topology().dim() - 1)
if submesh_subdomain.dim() == submesh.topology().dim():
for submesh_cell in cells(submesh):
submesh_subdomain.array()[
submesh_cell.index()] = mesh_subdomain.array()[
submesh.submesh_to_mesh_cell_local_indices[
submesh_cell.index()]]
elif submesh_subdomain.dim() == submesh.topology().dim() - 1:
for submesh_facet in facets(submesh):
submesh_subdomain.array()[
submesh_facet.index()] = mesh_subdomain.array()[
submesh.submesh_to_mesh_facet_local_indices[
submesh_facet.index()]]
else: # impossible to arrive here anyway, thanks to the assert
raise TypeError(
"Invalid arguments in convert_meshfunctions_to_submesh.")
meshfunctions_on_submesh.append(submesh_subdomain)
return meshfunctions_on_submesh
def boundaries(mesh):
boundaries = MeshFunction("size_t", mesh, mesh.topology().dim() - 1, 0)
for f in facets(mesh):
boundaries.array()[f.index()] = 0
for v in vertices(f):
boundaries.array()[f.index()] += v.global_index()
return boundaries
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 mplot_cellfunction(
cell_function: df.MeshFunction) -> Tuple[plt.Figure, Any]:
"""Return a pseudocolor plot of an unstructured triangular grid."""
fig, ax = plt.subplots(1)
tri = mesh2triang(cell_function.mesh())
ax.tripcolor(tri, facecolors=cell_function.array())
return fig, ax
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_mesh_function_assign_2D_cells():
mesh = UnitSquareMesh(MPI.comm_world, 3, 3)
ncells = mesh.num_cells()
f = MeshFunction("int", mesh, mesh.topology.dim, 0)
for cell in Cells(mesh):
f[cell] = ncells - cell.index()
g = MeshValueCollection("int", mesh, 2)
g.assign(f)
assert ncells == f.size()
assert ncells == g.size()
f2 = MeshFunction("int", mesh, g, 0)
for cell in Cells(mesh):
value = ncells - cell.index()
assert value == g.get_value(cell.index(), 0)
assert f2[cell] == g.get_value(cell.index(), 0)
h = MeshValueCollection("int", mesh, 2)
global_indices = mesh.topology.global_indices(2)
ncells_global = mesh.num_entities_global(2)
for cell in Cells(mesh):
if global_indices[cell.index()] in [5, 8, 10]:
continue
value = ncells_global - global_indices[cell.index()]
h.set_value(cell.index(), int(value))
f3 = MeshFunction("int", mesh, h, 0)
values = f3.array()
values[values > ncells_global] = 0.
assert MPI.sum(mesh.mpi_comm(), values.sum() * 1.0) == 140.
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 create(mesh, domain_ids, invert=False):
"""
Creates a wrapped mesh from a super mesh for a given collection
of domain IDs.
*Arguments*
mesh (:class:`dolfin.Mesh`)
The mesh.
domain_ids (:class:`[int]`)
List of domain IDs
invert (:class:`bool`)
Invert list of domain IDs
*Returns*
:class:`WrappedMesh`
The wrapped mesh
"""
if invert or isinstance(domain_ids, list) or isinstance(domain_ids, tuple):
if isinstance(domain_ids, int): domain_ids = (domain_ids,)
subdomains = MeshFunction('size_t', mesh, 3, mesh.domains())
combined_subdomains = CellFunction("size_t", mesh, 0)
for domain_id in domain_ids:
combined_subdomains.array()[subdomains.array() == domain_id] = 1
submesh = SubMesh(mesh, combined_subdomains, 0 if invert else 1)
else:
submesh = SubMesh(mesh, domain_ids)
submesh.__class__ = WrappedMesh
submesh._init(mesh)
return submesh
def dP(self, domain = "all"):
"""
Convenience wrapper for integral-point measure. If the mesh does not contain
any cell domains, the measure for the whole mesh is returned.
*Arguments*
domain (:class:`string` / :class:`int`)
name or ID of domain
*Returns*
:class:`dolfin:Measure`
the measure
"""
if not self.mesh_has_domains(): return Measure('dP', self.mesh)
if not self._dP.has_key(domain):
v = TestFunction(self.FunctionSpace())
values = assemble(v*self.dx(domain)).array()
# TODO improve this?
markers = ((np.sign(np.ceil(values) - 0.5) + 1.0) / 2.0).astype(np.uint64)
vertex_domains = MeshFunction('size_t', self.mesh, 0)
vertex_domains.array()[:] = markers
self._dP[domain] = Measure('dP', self.mesh)[vertex_domains](1)
return self._dP[domain]
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 load_data(mesh, mesh_f, dim, data):
'''
Represent mesh_f over dim entities of mesh as collection of vertices.
Can have mesh as mesh function or (h5_file, data_set)
'''
try:
h5_file, data_set = mesh_f
mf = MeshFunction('size_t', mesh, dim, 0)
h5_file.read(mf, data_set)
except ValueError:
mf = mesh_f
data_set = '%d dim entites' % mf.dim()
# Mapf for encoding entities as vertices
mesh.init(dim, 0)
e2v = mesh.topology()(dim, 0)
tags = set(mf.array())
# Don't encode zero - we initialize to it
if 0 in tags: tags.remove(0)
info('%s evolves tags %r' % (data_set, tags))
for tag in tags:
data[(dim, tag)] = np.array([e2v(e.index()) for e in SubsetIterator(mf, tag)],
dtype='uintp')
return data
def create(mesh, domain_ids, invert=False):
"""
Creates a wrapped mesh from a super mesh for a given collection
of domain IDs.
*Arguments*
mesh (:class:`dolfin.Mesh`)
The mesh.
domain_ids (:class:`[int]`)
List of domain IDs
invert (:class:`bool`)
Invert list of domain IDs
*Returns*
:class:`WrappedMesh`
The wrapped mesh
"""
if invert or isinstance(domain_ids, list) or isinstance(
domain_ids, tuple):
if isinstance(domain_ids, int): domain_ids = (domain_ids, )
subdomains = MeshFunction('size_t', mesh, 3, mesh.domains())
combined_subdomains = CellFunction("size_t", mesh, 0)
for domain_id in domain_ids:
combined_subdomains.array()[subdomains.array() ==
domain_id] = 1
submesh = SubMesh(mesh, combined_subdomains, 0 if invert else 1)
else:
submesh = SubMesh(mesh, domain_ids)
submesh.__class__ = WrappedMesh
submesh._init(mesh)
return submesh
def transfer_markers(mesh, f, markers=None):
'''
Let mesh be a mesh embedded into mesh(f). Transfer all markers from f
to the mesh.
'''
# Check that we are embdded
parent_mesh = f.mesh()
assert parent_mesh.id() in mesh.parent_entity_map
# If we are embedded then the transfer is only possible of the lower
# dimensional entities
assert f.dim() < mesh.topology().dim()
cdim = mesh.topology().dim()
edim = f.dim() # That of entities
# All not zeros
if markers is None: markers = set(f.array()) - set((0, ))
# The idea is to look up mesh.entities in parent by vertex ids
child_parent_vertex = mesh.parent_entity_map[parent_mesh.id()][0]
child_parent_cell = mesh.parent_entity_map[parent_mesh.id()][cdim]
# child_entity -> as vertex in child -> as vertex in parent
# \- connected child cells -> parent -> cells -> parent cell entities as vertex
# Entity in terms of vertices
mesh.init(edim, 0)
ch_e2v = mesh.topology()(edim, 0)
# The connected cell; we already have child to parent for cell
mesh.init(edim, cdim)
ch_e2c = mesh.topology()(edim, cdim)
# Then parent entities
parent_mesh.init(cdim, edim)
p_c2e = parent_mesh.topology()(cdim, edim)
# In terms of vertices
parent_mesh.init(edim, 0)
p_e2v = parent_mesh.topology()(edim, 0)
child_f = MeshFunction('size_t', mesh, edim, 0)
ch_values = child_f.array()
# Assignee
p_values = f.array()
for entity in range(len(ch_values)):
# As vertices in parent
e_as_vertex = set(child_parent_vertex[v] for v in ch_e2v(entity))
ch_cells = iter(ch_e2c(entity))
# One of the cells entities should match
for ch_cell in ch_cells:
for p_entity in p_c2e(child_parent_cell[ch_cell]):
found = p_values[p_entity] in markers and set(p_e2v(p_entity)) == e_as_vertex
# Can assign color
if found: break
if found:
ch_values[entity] = p_values[p_entity]
break
return child_f
def __init__(
self,
time: df.Constant,
mesh: df.Mesh,
cell_model: CellModel,
parameters: CoupledODESolverParameters,
cell_function: df.MeshFunction,
) -> None:
"""Initialise parameters. NB! Keep I_s for compatibility"""
# Store input
self._mesh = mesh
self._time = time
self._model = cell_model # FIXME: For initial conditions and num states
# Extract some information from cell model
self._num_states = self._model.num_states()
self._parameters = parameters
_cell_function_tags = set(cell_function.array())
if not set(self._parameters.valid_cell_tags) <= _cell_function_tags:
msg = "Valid cell tag not found in cell function. Expected {}, for {}."
raise ValueError(
msg.format(set(self._parameters.valid_cell_tags),
_cell_function_tags))
valid_cell_tags = self._parameters.valid_cell_tags
# Create (vector) function space for potential + states
self._function_space_VS = df.VectorFunctionSpace(self._mesh,
"CG",
1,
dim=self._num_states +
1)
# Initialize solution field
self.vs_prev = df.Function(self._function_space_VS, name="vs_prev")
self.vs = df.Function(self._function_space_VS, name="vs")
self.ode_module = load_module(
"LatticeODESolver",
recompile=self._parameters.reload_extension_modules,
verbose=self._parameters.reload_extension_modules)
self.ode_solver = self.ode_module.LatticeODESolver(
self._function_space_VS._cpp_object,
VectorSizet(cell_function.array()), self._parameters.parameter_map)
def refineMesh(m, l, u):
cell_markers = MeshFunction('bool', m, 1)
cell_markers.set_all(False)
coords = m.coordinates()
midpoints = 0.5 * (coords[:-1] + coords[1:])
ref_idx = np.where((midpoints > l) & (midpoints < u))[0]
cell_markers.array()[ref_idx] = True
m = refine(m, cell_markers)
return m
def test_ale():
# Create some mesh
mesh = UnitSquareMesh(4, 5)
# Make some cell function
# FIXME: Initialization by array indexing is probably
# not a good way for parallel test
cellfunc = MeshFunction('size_t', mesh, mesh.topology().dim())
cellfunc.array()[0:4] = 0
cellfunc.array()[4:] = 1
# Create submeshes - this does not work in parallel
submesh0 = SubMesh(mesh, cellfunc, 0)
submesh1 = SubMesh(mesh, cellfunc, 1)
# Move submesh0
disp = Constant(("0.1", "-0.1"))
ALE.move(submesh0, disp)
# Move and smooth submesh1 accordignly
ALE.move(submesh1, submesh0)
# Move mesh accordingly
parent_vertex_indices_0 = \
submesh0.data().array('parent_vertex_indices', 0)
parent_vertex_indices_1 = \
submesh1.data().array('parent_vertex_indices', 0)
mesh.coordinates()[parent_vertex_indices_0[:]] = \
submesh0.coordinates()[:]
mesh.coordinates()[parent_vertex_indices_1[:]] = \
submesh1.coordinates()[:]
# If test passes here then it is probably working
# Check for cell quality for sure
magic_number = 0.28
rmin = MeshQuality.radius_ratio_min_max(mesh)[0]
assert rmin > magic_number
def check_boundaries_are_marked(
mesh: df.Mesh,
ffun: df.MeshFunction,
markers: Dict[str, int],
boundaries: List[str],
) -> None:
# Check that all boundary faces are marked
num_boundary_facets = df.BoundaryMesh(mesh, "exterior").num_cells()
if num_boundary_facets != sum(
[np.sum(ffun.array() == markers[boundary])
for boundary in boundaries], ):
raise RuntimeError(
("Not all boundary faces are marked correctly. Make sure all "
"boundary facets are marked as: {}"
"").format(", ".join(
["{} = {}".format(k, v) for k, v in markers.items()])), )
def _init_for_append_if_needed(self):
# Initialize dof to cells map only the first time
if len(self.dof_to_cells) == 0:
self.dof_to_cells = list() # of size len(V)
for (component, V_component) in enumerate(self.V):
dof_to_cells = self._compute_dof_to_cells(V_component)
# Debugging
log(DEBUG, "DOFs to cells map (component " + str(component) + ") on processor " + str(self.mpi_comm.rank) + ":")
for (global_dof, cells_) in dof_to_cells.items():
log(DEBUG, "\t" + str(global_dof) + ": " + str([cell.global_index() for cell in cells_]))
# Add to storage
self.dof_to_cells.append(dof_to_cells)
self.dof_to_cells = tuple(self.dof_to_cells)
# Initialize cells marker
N = self._get_next_index()
reduced_mesh_markers = MeshFunction("bool", self.mesh, self.mesh.topology().dim())
reduced_mesh_markers.set_all(False)
if N > 0:
reduced_mesh_markers.array()[:] = self.reduced_mesh_markers[N - 1].array()
assert N not in self.reduced_mesh_markers
self.reduced_mesh_markers[N] = reduced_mesh_markers
def derived_bcs(V, original_bcs, u_):
new_bcs = []
# Check first if user has declared subdomains
subdomain = original_bcs[0].user_sub_domain()
if subdomain is None:
mesh = V.mesh()
ff = MeshFunction("size_t", mesh, mesh.topology().dim() - 1, 0)
for i, bc in enumerate(original_bcs):
bc.apply(u_[0].vector()) # Need to initialize bc
m = bc.markers() # Get facet indices of boundary
ff.array()[m] = i + 1
new_bcs.append(DirichletBC(V, Constant(0), ff, i + 1))
else:
for i, bc in enumerate(original_bcs):
subdomain = bc.user_sub_domain()
new_bcs.append(DirichletBC(V, Constant(0), subdomain))
return new_bcs
def load_data(mesh, h5_file, data_set, dim, data):
'''
Fill the data dictionary with data_set representing mesh function with
dim over mesh read from h5_file according to key spec expected by tiling
algorithm.
'''
mf = MeshFunction('size_t', mesh, dim, 0)
h5_file.read(mf, data_set)
# Data to evolve
mesh.init(dim, 0)
e2v = tile.topology()(dim, 0)
tags = set(mf.array())
# Don't evolve zero - we initialize to it
if 0 in tags: tags.remove(0)
info('%s evolves tags %r' % (data_set, tags))
for tag in tags:
data[(dim, tag)] = np.array([e2v(e.index()) for e in SubsetIterator(mf, tag)],
dtype='uintp')
return data
def create_boundary(self, domains, interior, exterior):
""" mark commmon facets between two domains with 1 and a return FacetFunction"""
edges = MeshFunction("size_t", domains.mesh(),
domains.mesh().topology().dim() - 1)
edges.set_all(0)
# count number of boundary facets
Nfacets = 0
for facet in facets(domains.mesh()):
cells = facet.entities(2)
if facet.exterior() == False:
cell1 = cells[0]
cell2 = cells[1]
domain1 = domains.array()[cells[0]]
domain2 = domains.array()[cells[1]]
if (sorted([domain1, domain2]) == sorted([interior,
exterior])):
idx = facet.index()
edges.array()[idx] = True
Nfacets += 1
return (edges, Nfacets)
def les_setup(u_, mesh, assemble_matrix, CG1Function, nut_krylov_solver, bcs, **NS_namespace):
"""
Set up for solving the Germano Dynamic LES model applying
Lagrangian Averaging.
"""
# Create function spaces
CG1 = FunctionSpace(mesh, "CG", 1)
p, q = TrialFunction(CG1), TestFunction(CG1)
dim = mesh.geometry().dim()
# Define delta and project delta**2 to CG1
delta = pow(CellVolume(mesh), 1. / dim)
delta_CG1_sq = project(delta, CG1)
delta_CG1_sq.vector().set_local(delta_CG1_sq.vector().array()**2)
delta_CG1_sq.vector().apply("insert")
# Define nut_
Sij = sym(grad(u_))
magS = sqrt(2 * inner(Sij, Sij))
Cs = Function(CG1)
nut_form = Cs**2 * delta**2 * magS
# Create nut_ BCs
ff = MeshFunction("size_t", mesh, mesh.topology().dim() - 1, 0)
bcs_nut = []
for i, bc in enumerate(bcs['u0']):
bc.apply(u_[0].vector()) # Need to initialize bc
m = bc.markers() # Get facet indices of boundary
ff.array()[m] = i + 1
bcs_nut.append(DirichletBC(CG1, Constant(0), ff, i + 1))
nut_ = CG1Function(nut_form, mesh, method=nut_krylov_solver,
bcs=bcs_nut, bounded=True, name="nut")
# Create functions for holding the different velocities
u_CG1 = as_vector([Function(CG1) for i in range(dim)])
u_filtered = as_vector([Function(CG1) for i in range(dim)])
dummy = Function(CG1)
ll = LagrangeInterpolator()
# Assemble required filter matrices and functions
G_under = Function(CG1, assemble(TestFunction(CG1) * dx))
G_under.vector().set_local(1. / G_under.vector().array())
G_under.vector().apply("insert")
G_matr = assemble(inner(p, q) * dx)
# Set up functions for Lij and Mij
Lij = [Function(CG1) for i in range(dim * dim)]
Mij = [Function(CG1) for i in range(dim * dim)]
# Check if case is 2D or 3D and set up uiuj product pairs and
# Sij forms, assemble required matrices
Sijcomps = [Function(CG1) for i in range(dim * dim)]
Sijfcomps = [Function(CG1) for i in range(dim * dim)]
# Assemble some required matrices for solving for rate of strain terms
Sijmats = [assemble_matrix(p.dx(i) * q * dx) for i in range(dim)]
if dim == 3:
tensdim = 6
uiuj_pairs = ((0, 0), (0, 1), (0, 2), (1, 1), (1, 2), (2, 2))
else:
tensdim = 3
uiuj_pairs = ((0, 0), (0, 1), (1, 1))
# Set up Lagrange functions
JLM = Function(CG1)
JLM.vector()[:] += 1E-32
JMM = Function(CG1)
JMM.vector()[:] += 1
return dict(Sij=Sij, nut_form=nut_form, nut_=nut_, delta=delta, bcs_nut=bcs_nut,
delta_CG1_sq=delta_CG1_sq, CG1=CG1, Cs=Cs, u_CG1=u_CG1,
u_filtered=u_filtered, ll=ll, Lij=Lij, Mij=Mij, Sijcomps=Sijcomps,
Sijfcomps=Sijfcomps, Sijmats=Sijmats, JLM=JLM, JMM=JMM, dim=dim,
tensdim=tensdim, G_matr=G_matr, G_under=G_under, dummy=dummy,
uiuj_pairs=uiuj_pairs)
def __init__(
self,
time: df.Constant,
mesh: df.Mesh,
intracellular_conductivity: Dict[int, df.Expression],
extracellular_conductivity: Dict[int, df.Expression],
cell_function: df.MeshFunction,
cell_tags: CellTags,
interface_function: df.MeshFunction,
interface_tags: InterfaceTags,
parameters: CoupledBidomainParameters,
neumann_boundary_condition: Dict[int, df.Expression] = None,
v_prev: df.Function = None,
surface_to_volume_factor: Union[float, df.Constant] = None,
membrane_capacitance: Union[float, df.Constant] = None,
) -> None:
self._time = time
self._mesh = mesh
self._parameters = parameters
# Strip none from cell tags
cell_tags = set(cell_tags) - {None}
if surface_to_volume_factor is None:
surface_to_volume_factor = df.constant(1)
if membrane_capacitance is None:
membrane_capacitance = df.constant(1)
# Set Chi*Cm
self._chi_cm = df.Constant(surface_to_volume_factor) * df.Constant(
membrane_capacitance)
if not set(intracellular_conductivity.keys()) == {
*tuple(extracellular_conductivity.keys())
}:
raise ValueError(
"intracellular conductivity and lambda does not havemnatching keys."
)
if not set(cell_tags) == set(intracellular_conductivity.keys()):
raise ValueError("Cell tags does not match conductivity keys")
self._intracellular_conductivity = intracellular_conductivity
self._extracellular_conductivity = extracellular_conductivity
# Check cell tags
_cell_function_tags = set(cell_function.array())
if set(cell_tags) != _cell_function_tags: # If not equal
msg = "Mismatching cell tags. Expected {}, got {}"
raise ValueError(msg.format(set(cell_tags), _cell_function_tags))
self._cell_tags = set(cell_tags)
self._cell_function = cell_function
restrict_tags = self._parameters.restrict_tags
if set(restrict_tags) >= self._cell_tags:
msg = "restrict tags ({})is not a subset of cell tags ({})"
raise ValueError(msg.format(set(restrict_tags), self._cell_tags))
self._restrict_tags = set(restrict_tags)
# Check interface tags
_interface_function_tags = {*set(interface_function.array()), None}
if not set(interface_tags
) <= _interface_function_tags: # if not subset of
msg = "Mismatching interface tags. Expected {}, got {}"
raise ValueError(
msg.format(set(interface_tags), _interface_function_tags))
self._interface_function = interface_function
self._interface_tags = interface_tags
# Set up function spaces
self._transmembrane_function_space = df.FunctionSpace(
self._mesh, "CG", 1)
transmembrane_element = df.FiniteElement("CG", self._mesh.ufl_cell(),
1)
extracellular_element = df.FiniteElement("CG", self._mesh.ufl_cell(),
1)
if neumann_boundary_condition is None:
self._neumann_bc: Dict[int, df.Expression] = dict()
else:
self._neumann_bc = neumann_boundary_condition
if self._parameters.linear_solver_type == "direct":
lagrange_element = df.FiniteElement("R", self._mesh.ufl_cell(), 0)
mixed_element = df.MixedElement(
(transmembrane_element, extracellular_element,
lagrange_element))
else:
mixed_element = df.MixedElement(
(transmembrane_element, extracellular_element))
self._VUR = df.FunctionSpace(
mesh, mixed_element) # TODO: rename to something sensible
# Set-up solution fields:
if v_prev is None:
self._merger = df.FunctionAssigner(
self._transmembrane_function_space, self._VUR.sub(0))
self._v_prev = df.Function(self._transmembrane_function_space,
name="v_prev")
else:
self._merger = None
self._v_prev = v_prev
self._vur = df.Function(self._VUR,
name="vur") # TODO: Give sensible name
# For normlising rhs_vector. TODO: Unsure about this. Check the nullspace from cbcbeat
self._extracellular_dofs = np.asarray(self._VUR.sub(1).dofmap().dofs())
# Mark first timestep
self._timestep: df.Constant = None
def model(self, parameters=None, logger=None):
def format(arr):
return np.array(arr)
# Setup parameters, logger
self.set_parameters(parameters)
self.set_logger(logger)
# Get parameters
parameters = self.get_parameters()
#SS#if not parameters.get('simulate'):
#SS# return
# Setup data
self.set_data(reset=True)
self.set_observables(reset=True)
# Show simulation settings
self.get_logger()('\n\t'.join([
'Simulating:', *[
'%s : %r' % (param, parameters[param] if not isinstance(
parameters[param], dict) else list(parameters[param]))
for param in
['fields', 'num_elem', 'N', 'dt', 'D', 'alpha', 'tol']
]
]))
# Data mesh
mesh = IntervalMesh(MPI.comm_world, parameters['num_elem'],
parameters['L_0'], parameters['L_1'])
# Fields
V = {}
W = {}
fields_n = {}
fields = {}
w = {}
fields_0 = {}
potential = {}
potential_derivative = {}
bcs = {}
R = {}
J = {}
# v2d_vector = {}
observables = {}
for field in parameters['fields']:
# Define functions
V[field] = {}
w[field] = {}
for space in parameters['spaces']:
V[field][space] = getattr(
dolfin, parameters['spaces'][space]['type'])(
mesh, parameters['spaces'][space]['family'],
parameters['spaces'][space]['degree'])
w[field][space] = TestFunction(V[field][space])
space = V[field][parameters['fields'][field]['space']]
test = w[field][parameters['fields'][field]['space']]
fields_n[field] = Function(space, name='%sn' % (field))
fields[field] = Function(space, name=field)
# Inital condition
fields_0[field] = Expression(
parameters['fields'][field]['initial'],
element=space.ufl_element())
fields_n[field] = project(fields_0[field], space)
fields[field].assign(fields_n[field])
# Define potential
if parameters['potential'].get('kwargs') is None:
parameters['potential']['kwargs'] = {}
for k in parameters['potential']['kwargs']:
if parameters['potential']['kwargs'][k] is None:
parameters['potential']['kwargs'][k] = fields[k]
potential[field] = Expression(
parameters['potential']['expression'],
degree=parameters['potential']['degree'],
**parameters['potential']['kwargs'])
potential_derivative[field] = Expression(
parameters['potential']['derivative'],
degree=parameters['potential']['degree'] - 1,
**parameters['potential']['kwargs'])
#Subdomain for defining Positive grain
sub_domains = MeshFunction('size_t', mesh,
mesh.topology().dim(), 0)
#BC condition
bcs[field] = []
if parameters['fields'][field]['bcs'] == 'dirichlet':
BC_l = CompiledSubDomain('near(x[0], side) && on_boundary',
side=parameters['L_0'])
BC_r = CompiledSubDomain('near(x[0], side) && on_boundary',
side=parameters['L_1'])
bcl = DirichletBC(V, fields_n[field], BC_l)
bcr = DirichletBC(V, fields_n[field], BC_r)
bcs[field].extend([bcl, bcr])
elif parameters['fields'][field]['bcs'] == 'neumann':
bcs[field].extend([])
# Residual and Jacobian
R[field] = (
((fields[field] - fields_n[field]) / parameters['dt'] * test *
dx) +
(inner(parameters['D'] * grad(test), grad(fields[field])) * dx)
+ (parameters['alpha'] * potential_derivative[field] * test *
dx))
J[field] = derivative(R[field], fields[field])
# Observables
observables[field] = {}
files = {
'xdmf': XDMFFile(MPI.comm_world,
self.get_paths()['xdmf']),
'hdf5': HDF5File(MPI.comm_world,
self.get_paths()['hdf5'], 'w'),
}
files['hdf5'].write(mesh, '/mesh')
eps = lambda n, key, field, observables, tol: (
n == 0) or (abs(observables[key]['total_energy'][n] - observables[
key]['total_energy'][n - 1]) /
(observables[key]['total_energy'][0]) > tol)
flag = {field: True for field in parameters['fields']}
tol = {
field: parameters['tol'][field] if isinstance(
parameters['tol'], dict) else parameters['tol']
for field in parameters['fields']
}
phases = {'p': 1, 'm': 2}
n = 0
problem = {}
solver = {}
while (n < parameters['N']
and any([flag[field] for field in parameters['fields']])):
self.get_logger()('Time: %d' % (n))
for field in parameters['fields']:
if not flag[field]:
continue
# Solve
problem[field] = NonlinearVariationalProblem(
R[field], fields[field], bcs[field], J[field])
solver[field] = NonlinearVariationalSolver(problem[field])
solver[field].solve()
# Get field array
array = assemble(
(1 / CellVolume(mesh)) *
inner(fields[field], w[field]['Z']) * dx).get_local()
# Observables
observables[field]['Time'] = parameters['dt'] * n
# observables[field]['energy_density'] = format(0.5*dot(grad(fields[field]),grad(fields[field]))*dx)
observables[field]['gradient_energy'] = format(
assemble(0.5 *
dot(grad(fields[field]), grad(fields[field])) *
dx(domain=mesh)))
observables[field]['landau_energy'] = format(
assemble(potential[field] * dx(domain=mesh)))
observables[field]['diffusion_energy'] = format(
assemble(
project(
div(project(grad(fields[field]), V[field]['W'])),
V[field]['Z']) * dx(domain=mesh))
) #Diffusion part of chemical potential
observables[field]['spinodal_energy'] = format(
assemble(
potential_derivative[field] *
dx(domain=mesh))) #Spinodal part of chemical potential
observables[field]['total_energy'] = parameters[
'D'] * observables[field]['gradient_energy'] + parameters[
'alpha'] * observables[field]['landau_energy']
observables[field]['chi'] = parameters['alpha'] * observables[
field]['diffusion_energy'] - parameters['D'] * observables[
field]['spinodal_energy']
# Phase observables
sub_domains.set_all(0)
sub_domains.array()[:] = np.where(array > 0.0, phases['p'],
phases['m'])
phases_dxp = Measure('dx',
domain=mesh,
subdomain_data=sub_domains)
for phase in phases:
dxp = phases_dxp(phases[phase])
observables[field]['Phi_0%s' % (phase)] = format(
assemble(1 * dxp))
observables[field]['Phi_1%s' % (phase)] = format(
assemble(fields[field] * dxp))
observables[field]['Phi_2%s' % (phase)] = format(
assemble(fields[field] * fields[field] * dxp))
observables[field]['Phi_3%s' % (phase)] = format(
assemble(fields[field] * fields[field] *
fields[field] * dxp))
observables[field]['Phi_4%s' % (phase)] = format(
assemble(fields[field] * fields[field] *
fields[field] * fields[field] * dxp))
observables[field]['Phi_5%s' % (phase)] = format(
assemble(fields[field] * fields[field] *
fields[field] * fields[field] *
fields[field] * dxp))
observables[field]['gradient_energy_%s' %
(phase)] = format(
assemble(
0.5 *
dot(grad(fields[field]),
grad(fields[field])) * dxp))
observables[field]['landau_energy_%s' % (phase)] = format(
assemble(potential[field] * dxp))
observables[field][
'total_energy_%s' %
(phase)] = parameters['D'] * observables[field][
'gradient_energy_%s' %
(phase)] + parameters['alpha'] * observables[
field]['landau_energy_%s' % (phase)]
observables[field][
'diffusion_energy_%s' % (phase)] = format(
assemble(
project(
div(
project(grad(fields[field]),
V[field]['W'])), V[field]['Z'])
* dxp)) #Diffusion part of chemical potential
observables[field][
'spinodal_energy_%s' % (phase)] = format(
assemble(
potential_derivative[field] *
dxp)) #Spinodal part of chemical potential
observables[field][
'chi_%s' %
(phase)] = parameters['alpha'] * observables[field][
'spinodal_energy_%s' %
(phase)] - parameters['D'] * observables[field][
'diffusion_energy_%s' % (phase)]
files['hdf5'].write(fields[field], '/%s' % (field), n)
files['xdmf'].write(fields[field], n)
fields_n[field].assign(fields[field])
self.set_data({field: array})
self.set_observables({field: observables[field]})
flag[field] = eps(n, field, fields[field],
self.get_observables(), tol[field])
n += 1
for file in files:
files[file].close()
return
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_creation_and_marking():
class Left(SubDomain):
def inside(self, x, on_boundary):
return x[:, 0] < np.finfo(float).eps
class LeftOnBoundary(SubDomain):
def inside(self, x, on_boundary):
return np.logical_and(x[:, 0] < np.finfo(float).eps, on_boundary)
class Right(SubDomain):
def inside(self, x, on_boundary):
return x[:, 0] > 1.0 - np.finfo(float).eps
class RightOnBoundary(SubDomain):
def inside(self, x, on_boundary):
return np.logical_and(x[:, 0] > 1.0 - np.finfo(float).eps,
on_boundary)
subdomain_pairs = [(Left(), Right()),
(LeftOnBoundary(), RightOnBoundary())]
for ind, MeshClass in enumerate(
[UnitIntervalMesh, UnitSquareMesh, UnitCubeMesh]):
dim = ind + 1
args = [10] * dim
mesh = MeshClass(MPI.comm_world, *args)
mesh.create_connectivity_all()
for left, right in subdomain_pairs:
for t_dim, f_dim in [(0, 0), (mesh.topology.dim - 1, dim - 1),
(mesh.topology.dim, dim)]:
f = MeshFunction("size_t", mesh, t_dim, 0)
left.mark(f, 1)
right.mark(f, 2)
correct = {
(1, 0): 1,
(1, 0): 1,
(1, 1): 0,
(2, 0): 11,
(2, 1): 10,
(2, 2): 0,
(3, 0): 121,
(3, 2): 200,
(3, 3): 0
}
# Check that the number of marked entities are at least the
# correct number (it can be larger in parallel)
assert all(value >= correct[dim, f_dim] for value in [
MPI.sum(mesh.mpi_comm(), float((f.array() == 2).sum())),
MPI.sum(mesh.mpi_comm(), float((f.array() == 1).sum())),
])
for t_dim, f_dim in [(0, 0), (mesh.topology.dim - 1, dim - 1),
(mesh.topology.dim, dim)]:
f = MeshFunction("size_t", mesh, t_dim, 0)
class AllTrue(SubDomain):
def inside(self, x, on_boundary):
return np.full(x.shape[0], True)
class AllFalse(SubDomain):
def inside(self, x, on_boundary):
return np.full(x.shape[0], False)
empty = AllFalse()
every = AllTrue()
empty.mark(f, 1)
every.mark(f, 2)
# Check that the number of marked entities is correct
assert sum(f.array() == 1) == 0
assert sum(f.array() == 2) == mesh.num_entities(f_dim)
c2v = dual_mesh.topology()(2, 0)
for idx_old, (f, l) in enumerate(zip(mapping[:-1], mapping[1:])):
# f:l are cells of the patch
idx_new, = reduce(operator.and_, map(set,
(c2v(c) for c in range(f, l))))
patch_vertices.append(idx_new)
assert np.linalg.norm(x_old[idx_old] - x_new[idx_new]) < 1E-13
# The patch overlap vertices are unqiue
assert len(set(patch_vertices)) == len(patch_vertices)
File('old_mesh.pvd') << mesh
# Show how to build the patch mapping from the data of the dual mesh
cell_f = MeshFunction('size_t', dual_mesh, 2, 0)
values = cell_f.array()
for idx, (f, l) in enumerate(zip(mapping[:-1], mapping[1:])):
values[f:l] = idx
File('dual_mesh.pvd') << cell_f
# Scaling
nvertices, times = [], []
for n in (4, 8, 16, 32, 64, 128, 256, 512):
mesh = UnitSquareMesh(n, n)
nvertices.append(mesh.num_vertices())
timer = df.Timer('f')
dual_mesh = DualMesh(mesh)
time = timer.stop()
# -------------------------------------------------------------------
if __name__ == '__main__':
from dolfin import (CompiledSubDomain, DomainBoundary, SubsetIterator,
UnitSquareMesh, Facet)
from xii import EmbeddedMesh
mesh = UnitSquareMesh(4, 4)
surfaces = MeshFunction('size_t', mesh, 2, 0)
CompiledSubDomain('x[0] > 0.5-DOLFIN_EPS').mark(surfaces, 1)
# What should be trasfered
f = MeshFunction('size_t', mesh, 1, 0)
DomainBoundary().mark(f, 1)
CompiledSubDomain('near(x[0], 0.5)').mark(f, 1)
# Assign funky colors
for i, e in enumerate(SubsetIterator(f, 1), 1): f[e] = i
ch_mesh = EmbeddedMesh(surfaces, 1)
ch_f = transfer_markers(ch_mesh, f)
# Every color in child is found in parent and we get the midpoint right
p_values, ch_values = list(f.array()), list(ch_f.array())
for ch_value in set(ch_f.array()) - set((0, )):
assert ch_value in p_values
x = Facet(mesh, p_values.index(ch_value)).midpoint()
y = Facet(ch_mesh, ch_values.index(ch_value)).midpoint()
assert x.distance(y) < 1E-13
P1 = FiniteElement('P', 'triangle', 2)
element = MixedElement([P1, P1, P1])
ME = FunctionSpace(mesh, element)
subdomain = CompiledSubDomain(
'(pow((x[0] - 7.5E-3), 2) + pow((x[1] - 7.5E-3), 2)) <= pow(2.5E-3, 2)')
subdomains = MeshFunction("size_t", mesh, 2)
subdomains.set_all(0)
subdomain.mark(subdomains, 1)
fc = Constant(2.0) # FCD
V0_r = FunctionSpace(mesh, 'DG', 0)
fc_function = Function(V0_r)
fc_val = [0.0, fc]
help = np.asarray(subdomains.array(), dtype=np.int32)
fc_function.vector()[:] = np.choose(help, fc_val)
zeroth = plot(fc_function, title="Fixed charge density, $c^f$")
plt.colorbar(zeroth)
plot(fc_function)
plt.xlim(0.0, 0.015)
plt.xticks([0.0, 0.005, 0.01, 0.015])
plt.ylim(0.0, 0.015)
plt.yticks([0.0, 0.005, 0.01, 0.015])
plt.show()
Sol_c = Constant(1.0)
Poten = 50.0E-3
l_bc_an = DirichletBC(ME.sub(0), Sol_c, left_boundary)
r_bc_an = DirichletBC(ME.sub(0), Sol_c, right_boundary)
l_bc_ca = DirichletBC(ME.sub(1), Sol_c, left_boundary)
def subdomains(mesh):
subdomains = MeshFunction("size_t", mesh, mesh.topology().dim(), 0)
for c in cells(mesh):
subdomains.array()[c.index()] = c.global_index()
return subdomains
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)
