def save_nullspaces():
# points, cells = meshzoo.rectangle_tri((0.0, 0.0), (1.0, 1.0), 20)
points, cells = meshzoo.disk(6, 20)
@fem.BilinearForm
def flux(u, v, w):
return dot(w.n, u.grad) * v
mesh = fem.MeshTri(points.T, cells.T)
basis = fem.InteriorBasis(mesh, fem.ElementTriP1())
facet_basis = fem.FacetBasis(basis.mesh, basis.elem)
lap = fem.asm(laplace, basis)
boundary_terms = fem.asm(flux, facet_basis)
A_dense = (lap - boundary_terms).toarray()
# the right null space are the affine-linear functions
rns = scipy.linalg.null_space(A_dense).T
mesh.save("nullspace-right.vtk",
point_data={
"k0": rns[0],
"k1": rns[1],
"k2": rns[2]
})
# the left null space is a bit weird; something around the boundaries
lns = scipy.linalg.null_space(A_dense.T).T
mesh.save("nullspace-left.vtk",
point_data={
"k0": lns[0],
"k1": lns[1],
"k2": lns[2]
})
def __init__(self, edges, coord_sys, tabs):
self.edges = edges
self.nodes = dict.fromkeys(["y", "z"])
for var in self.nodes.keys():
self.nodes[var] = (self.edges[var][1:] + self.edges[var][:-1]) / 2
self.npts = len(self.edges["y"]) * len(self.edges["z"])
self.coord_sys = coord_sys
# create mesh
self.fem_mesh = skfem.MeshTri.init_tensor(self.edges["y"],
self.edges["z"])
# get coordinates (returns a vector size 2*(Ny*Nz))
self.coordinates = self.fem_mesh.p
# create elements and basis
self.element = skfem.ElementTriP1()
self.basis = skfem.InteriorBasis(self.fem_mesh, self.element)
self.facet_basis = skfem.FacetBasis(self.fem_mesh, self.element)
# get degrees of freedom and facets which correspond to tabs, and
# create facet basis for sub regions
self.negative_tab_dofs = self.basis.get_dofs(
lambda x: self.on_boundary(x[0], x[1], tabs["negative"])).all()
self.positive_tab_dofs = self.basis.get_dofs(
lambda x: self.on_boundary(x[0], x[1], tabs["positive"])).all()
self.negative_tab_facets = self.fem_mesh.facets_satisfying(
lambda x: self.on_boundary(x[0], x[1], tabs["negative"]))
self.positive_tab_facets = self.fem_mesh.facets_satisfying(
lambda x: self.on_boundary(x[0], x[1], tabs["positive"]))
self.negative_tab_basis = skfem.FacetBasis(
self.fem_mesh, self.element, facets=self.negative_tab_facets)
self.positive_tab_basis = skfem.FacetBasis(
self.fem_mesh, self.element, facets=self.positive_tab_facets)
def setup(n):
x0 = rng.random((n, 2)) - 0.5
# y0 = np.ones(n)
# y0 = x0[:, 0]
# y0 = x0[:, 0]**2
# y0 = np.cos(np.pi*x0.T[0])
# y0 = np.cos(np.pi*x0.T[0]) * np.cos(np.pi*x0.T[1])
y0 = np.cos(np.pi * np.sqrt(x0.T[0]**2 + x0.T[1]**2))
points, cells = meshzoo.rectangle_tri((-1.0, -1.0), (1.0, 1.0), n)
mesh = skfem.MeshTri(points.T.copy(), cells.T.copy())
element = skfem.ElementTriP1()
@skfem.BilinearForm
def mass(u, v, _):
return u * v
@skfem.BilinearForm
def flux(u, v, w):
return dot(w.n, u.grad) * v
basis = skfem.InteriorBasis(mesh, element)
facet_basis = skfem.FacetBasis(basis.mesh, basis.elem)
lap = skfem.asm(laplace, basis)
boundary_terms = skfem.asm(flux, facet_basis)
A = lap - boundary_terms
# A *= lmbda
# get the evaluation matrix
E = basis.probes(x0.T)
# mass matrix
M = skfem.asm(mass, basis)
# x = _solve(A, M, E, y0, solver)
# # Neumann preconditioner
# An = _assemble_eigen(dot(grad(u), grad(v)) * dx).sparray()
# # Dirichlet preconditioner
# Ad = _assemble_eigen(dot(grad(u), grad(v)) * dx)
# bc = DirichletBC(V, 0.0, "on_boundary")
# bc.apply(Ad)
# # Ad = Ad.sparray()
# Aq = _assemble_eigen(
# dot(grad(u), grad(v)) * dx - dot(n, grad(u)) * v * ds - dot(n, grad(v)) * u * ds
# ).sparray()
# ml = pyamg.smoothed_aggregation_solver(A, coarse_solver="jacobi", max_coarse=100)
# mln = pyamg.smoothed_aggregation_solver(An, coarse_solver="jacobi", max_coarse=100)
# mld = pyamg.smoothed_aggregation_solver(Ad, coarse_solver="jacobi", max_coarse=100)
# mlq = pyamg.smoothed_aggregation_solver(Aq, coarse_solver="jacobi", max_coarse=100)
ml = pyamg.smoothed_aggregation_solver(A,
coarse_solver="jacobi",
symmetry="nonsymmetric",
max_coarse=100)
# mlT = pyamg.smoothed_aggregation_solver(
# A.T, coarse_solver="jacobi", symmetry="nonsymmetric", max_coarse=100
# )
P = ml.aspreconditioner()
# PT = mlT.aspreconditioner()
# construct transpose -- dense, super expensive!
I = np.eye(P.shape[0])
PT = (P @ I).T
PT = scipy.sparse.csr_matrix(PT)
# # make sure it's really the transpose
# x = rng.random(A.shape[1])
# y = rng.random(A.shape[1])
# print(np.dot(x, P @ y))
# print(np.dot(PT @ x, y))
def matvec(x):
return P @ x
def rmatvec(y):
return PT @ y
precs = [
scipy.sparse.linalg.LinearOperator(A.shape,
matvec=matvec,
rmatvec=rmatvec)
# not working well:
# (ml.aspreconditioner(), mlT.aspreconditioner())
]
return A, E, M, precs, y0
height = 0.41
geom = Geometry()
cylinder = geom.add_circle([0.2, 0.2, 0.0], radius, lcar=radius / 2)
channel = geom.add_rectangle(
0.0, 2.2, 0.0, height, 0, holes=[cylinder], lcar=radius / 2
)
geom.add_physical(channel.surface, "domain")
geom.add_physical(channel.lines[1], "outlet")
geom.add_physical(channel.lines[3], "inlet")
mesh = from_meshio(generate_mesh(geom, dim=2))
element = {"u": skfem.ElementVectorH1(skfem.ElementTriP2()), "p": skfem.ElementTriP1()}
basis = {
**{v: skfem.InteriorBasis(mesh, e, intorder=4) for v, e in element.items()},
"inlet": skfem.FacetBasis(mesh, element["u"], facets=mesh.boundaries["inlet"]),
}
M = skfem.asm(vector_mass, basis["u"])
L = {"u": skfem.asm(vector_laplace, basis["u"]), "p": skfem.asm(laplace, basis["p"])}
B = -skfem.asm(divergence, basis["u"], basis["p"])
P = B.T + skfem.asm(
port_pressure,
*(
skfem.FacetBasis(mesh, element[v], intorder=3, facets=mesh.boundaries["outlet"])
for v in ["p", "u"]
),
)
t_final = 5.0
dt = 0.001
tol = 1.0e-8
for n in range(5, 41, 5):
# points, cells = meshzoo.rectangle_tri((0.0, 0.0), (1.0, 1.0), n)
points, cells = meshzoo.disk(6, n)
print(f"{n = }, {len(points) = }")
@fem.BilinearForm
def flux(u, v, w):
return dot(w.n, u.grad) * v
# copy to avoid warnings; better would be to get the transposed arrays from meshzoo
# directly
mesh = fem.MeshTri(points.T.copy(), cells.T.copy())
basis = fem.InteriorBasis(mesh, fem.ElementTriP1())
facet_basis = fem.FacetBasis(basis.mesh, basis.elem)
lap = fem.asm(laplace, basis)
boundary_terms = fem.asm(flux, facet_basis)
A = lap - boundary_terms
b = rng.random(A.shape[1])
# make the system consistent by removing A's left nullspace components from the
# right-hand side
lns = scipy.linalg.null_space(A.T.toarray()).T
for n in lns:
b -= np.dot(b, n) / np.dot(n, n) * n
ml = pyamg.smoothed_aggregation_solver(
mesh = from_file(Path("cylinder.json"))
except Exception as e:
from cylinder_dmsh import CylinderDmsh
print("Couldn't find cylinder.json; generating in dmsh.")
mesher = CylinderDmsh()
mesh = mesher.mesh
mesher.save()
element = {
"u": skfem.ElementVectorH1(skfem.ElementTriP2()),
"p": skfem.ElementTriP1()
}
basis = {
**{
v: skfem.InteriorBasis(mesh, e, intorder=4)
for v, e in element.items()
},
"inlet": skfem.FacetBasis(mesh,
element["u"],
facets=mesh.boundaries["inlet"]),
}
pressure_probe = probe(basis["p"], np.array([(0.15, 0.2), (0.25, 0.2)]).T)
M = skfem.asm(vector_mass, basis["u"])
L = {
"u": skfem.asm(vector_laplace, basis["u"]),
"p": skfem.asm(laplace, basis["p"])
}
B = -skfem.asm(divergence, basis["u"], basis["p"])
P = B.T + skfem.asm(