class VertexBasedLimiter(Limiter):
"""
A vertex based limiter for P1DG fields.
This limiter implements the vertex-based limiting scheme described in
Dmitri Kuzmin, "A vertex-based hierarchical slope limiter for p-adaptive
discontinuous Galerkin methods". J. Comp. Appl. Maths (2010)
http://dx.doi.org/10.1016/j.cam.2009.05.028
"""
def __init__(self, space):
"""
Initialise limiter
:param space : FunctionSpace instance
"""
self.P1DG = space
self.P1CG = FunctionSpace(self.P1DG.mesh(), 'CG', 1) # for min/max limits
self.P0 = FunctionSpace(self.P1DG.mesh(), 'DG', 0) # for centroids
# Storage containers for cell means, max and mins
self.centroids = Function(self.P0)
self.centroids_rhs = Function(self.P0)
self.max_field = Function(self.P1CG)
self.min_field = Function(self.P1CG)
self.centroid_solver = self._construct_centroid_solver()
# Update min and max loop
domain = "{[i]: 0 <= i < maxq.dofs}"
instructions = """
for i
maxq[i] = fmax(maxq[i], q[0])
minq[i] = fmin(minq[i], q[0])
end
"""
self._min_max_loop = (domain, instructions)
# Perform limiting loop
domain = "{[i, ii]: 0 <= i < q.dofs and 0 <= ii < q.dofs}"
instructions = """
<float64> alpha = 1
<float64> qavg = qbar[0, 0]
for i
<float64> _alpha1 = fmin(alpha, fmin(1, (qmax[i] - qavg)/(q[i] - qavg)))
<float64> _alpha2 = fmin(alpha, fmin(1, (qavg - qmin[i])/(qavg - q[i])))
alpha = if(q[i] > qavg, _alpha1, if(q[i] < qavg, _alpha2, alpha))
end
for ii
q[ii] = qavg + alpha * (q[ii] - qavg)
end
"""
self._limit_kernel = (domain, instructions)
def _construct_centroid_solver(self):
"""
Constructs a linear problem for computing the centroids
:return: LinearSolver instance
"""
u = TrialFunction(self.P0)
v = TestFunction(self.P0)
a = assemble(u * v * dx)
return LinearSolver(a, solver_parameters={'ksp_type': 'preonly',
'pc_type': 'bjacobi',
'sub_pc_type': 'ilu'})
def _update_centroids(self, field):
"""
Update centroid values
"""
assemble(TestFunction(self.P0) * field * dx, tensor=self.centroids_rhs)
self.centroid_solver.solve(self.centroids, self.centroids_rhs)
def compute_bounds(self, field):
"""
Only computes min and max bounds of neighbouring cells
"""
self._update_centroids(field)
self.max_field.assign(-1.0e10) # small number
self.min_field.assign(1.0e10) # big number
par_loop(self._min_max_loop,
dx,
{"maxq": (self.max_field, MAX),
"minq": (self.min_field, MIN),
"q": (self.centroids, READ)},
is_loopy_kernel=True)
def apply_limiter(self, field):
"""
Only applies limiting loop on the given field
"""
par_loop(self._limit_kernel, dx,
{"qbar": (self.centroids, READ),
"q": (field, RW),
"qmax": (self.max_field, READ),
"qmin": (self.min_field, READ)},
is_loopy_kernel=True)
def apply(self, field):
"""
Re-computes centroids and applies limiter to given field
"""
assert field.function_space() == self.P1DG, \
'Given field does not belong to this objects function space'
self.compute_bounds(field)
self.apply_limiter(field)
class VertexBasedLimiter(Limiter):
"""
A vertex based limiter for P1DG fields.
This limiter implements the vertex-based limiting scheme described in
Dmitri Kuzmin, "A vertex-based hierarchical slope limiter for p-adaptive
discontinuous Galerkin methods". J. Comp. Appl. Maths (2010)
http://dx.doi.org/10.1016/j.cam.2009.05.028
"""
def __init__(self, space):
"""
Initialise limiter
:param space : FunctionSpace instance
"""
self.P1DG = space
self.P1CG = FunctionSpace(self.P1DG.mesh(), 'CG',
1) # for min/max limits
self.P0 = FunctionSpace(self.P1DG.mesh(), 'DG', 0) # for centroids
# Storage containers for cell means, max and mins
self.centroids = Function(self.P0)
self.centroids_rhs = Function(self.P0)
self.max_field = Function(self.P1CG)
self.min_field = Function(self.P1CG)
self.centroid_solver = self._construct_centroid_solver()
# Update min and max loop
self._min_max_loop = """
for(int i = 0; i < maxq.dofs; i++) {
maxq[i][0] = fmax(maxq[i][0],q[0][0]);
minq[i][0] = fmin(minq[i][0],q[0][0]);
}
"""
# Perform limiting loop
self._limit_kernel = """
double alpha = 1.0;
double qavg = qbar[0][0];
for (int i=0; i < q.dofs; i++) {
if (q[i][0] > qavg)
alpha = fmin(alpha, fmin(1, (qmax[i][0] - qavg)/(q[i][0] - qavg)));
else if (q[i][0] < qavg)
alpha = fmin(alpha, fmin(1, (qavg - qmin[i][0])/(qavg - q[i][0])));
}
for (int i=0; i<q.dofs; i++) {
q[i][0] = qavg + alpha*(q[i][0] - qavg);
}
"""
def _construct_centroid_solver(self):
"""
Constructs a linear problem for computing the centroids
:return: LinearSolver instance
"""
u = TrialFunction(self.P0)
v = TestFunction(self.P0)
a = assemble(u * v * dx)
return LinearSolver(a,
solver_parameters={
'ksp_type': 'preonly',
'pc_type': 'bjacobi',
'sub_pc_type': 'ilu'
})
def _update_centroids(self, field):
"""
Update centroid values
"""
assemble(TestFunction(self.P0) * field * dx, tensor=self.centroids_rhs)
self.centroid_solver.solve(self.centroids, self.centroids_rhs)
def compute_bounds(self, field):
"""
Only computes min and max bounds of neighbouring cells
"""
self._update_centroids(field)
self.max_field.assign(-1.0e10) # small number
self.min_field.assign(1.0e10) # big number
par_loop(
self._min_max_loop, dx, {
"maxq": (self.max_field, MAX),
"minq": (self.min_field, MIN),
"q": (self.centroids, READ)
})
def apply_limiter(self, field):
"""
Only applies limiting loop on the given field
"""
par_loop(
self._limit_kernel, dx, {
"qbar": (self.centroids, READ),
"q": (field, RW),
"qmax": (self.max_field, READ),
"qmin": (self.min_field, READ)
})
def apply(self, field):
"""
Re-computes centroids and applies limiter to given field
"""
assert field.function_space() == self.P1DG, \
'Given field does not belong to this objects function space'
self.compute_bounds(field)
self.apply_limiter(field)
class ThetaLimiter(object):
"""
A vertex based limiter for fields in the DG1xCG2 space,
i.e. temperature variables. This acts like the vertex-based
limiter implemented in Firedrake, but in addition corrects
the central nodes to prevent new maxima or minima forming.
"""
def __init__(self, equation):
"""
Initialise limiter
:param space : equation, as we need the broken space attached to it
"""
self.Vt = equation.space
# check this is the right space, only currently working for 2D extruded mesh
if self.Vt.extruded and self.Vt.mesh().topological_dimension() == 2:
# check that horizontal degree is 1 and vertical degree is 2
if self.Vt.ufl_element().degree()[0] is not 1 or \
self.Vt.ufl_element().degree()[1] is not 2:
raise ValueError('This is not the right limiter for this space.')
# check that continuity of the spaces is correct
# this will fail if the space does not use broken elements
if self.Vt.ufl_element()._element.sobolev_space()[0].name is not 'L2' or \
self.Vt.ufl_element()._element.sobolev_space()[1].name is not 'H1':
raise ValueError('This is not the right limiter for this space.')
else:
logger.warning('This limiter may not work for the space you are using.')
self.Q1DG = FunctionSpace(self.Vt.mesh(), 'DG', 1) # space with only vertex DOFs
self.vertex_limiter = VertexBasedLimiter(self.Q1DG)
self.theta_hat = Function(self.Q1DG) # theta function with only vertex DOFs
self.w = Function(self.Vt)
self.result = Function(self.Vt)
par_loop(_weight_kernel, dx, {"weight": (self.w, INC)})
def copy_vertex_values(self, field):
"""
Copies the vertex values from temperature space to
Q1DG space which only has vertices.
"""
par_loop(_copy_into_Q1DG_loop, dx,
{"theta": (field, READ),
"theta_hat": (self.theta_hat, RW)})
def copy_vertex_values_back(self, field):
"""
Copies the vertex values back from the Q1DG space to
the original temperature space.
"""
par_loop(_copy_from_Q1DG_loop, dx,
{"theta": (field, RW),
"theta_hat": (self.theta_hat, READ)})
def check_midpoint_values(self, field):
"""
Checks the midpoint field values are less than the maximum
and more than the minimum values. Amends them to the average
if they are not.
"""
par_loop(_check_midpoint_values_loop, dx,
{"theta": (field, RW)})
def remap_to_embedded_space(self, field):
"""
Remap from DG space to embedded DG space.
"""
self.result.assign(0.)
par_loop(_average_kernel, dx, {"vrec": (self.result, INC),
"v_b": (field, READ),
"weight": (self.w, READ)})
field.assign(self.result)
def apply(self, field):
"""
The application of the limiter to the theta-space field.
"""
assert field.function_space() == self.Vt, \
'Given field does not belong to this objects function space'
self.copy_vertex_values(field)
self.vertex_limiter.apply(self.theta_hat)
self.copy_vertex_values_back(field)
self.check_midpoint_values(field)
self.remap_to_embedded_space(field)
class VertexBasedLimiter(Limiter):
"""
A vertex based limiter for P1DG fields.
This limiter implements the vertex-based limiting scheme described in
Dmitri Kuzmin, "A vertex-based hierarchical slope limiter for p-adaptive
discontinuous Galerkin methods". J. Comp. Appl. Maths (2010)
http://dx.doi.org/10.1016/j.cam.2009.05.028
"""
def __init__(self, space):
"""
Initialise limiter
:param space : FunctionSpace instance
"""
if utils.complex_mode:
raise ValueError(
"We haven't decided what limiting complex valued fields means. Please get in touch if you have need."
)
self.P1DG = space
self.P1CG = FunctionSpace(self.P1DG.mesh(), 'CG',
1) # for min/max limits
self.P0 = FunctionSpace(self.P1DG.mesh(), 'DG', 0) # for centroids
# Storage containers for cell means, max and mins
self.centroids = Function(self.P0)
self.centroids_rhs = Function(self.P0)
self.max_field = Function(self.P1CG)
self.min_field = Function(self.P1CG)
self.centroid_solver = self._construct_centroid_solver()
# Update min and max loop
domain = "{[i]: 0 <= i < maxq.dofs}"
instructions = """
for i
maxq[i] = fmax(maxq[i], q[0])
minq[i] = fmin(minq[i], q[0])
end
"""
self._min_max_loop = (domain, instructions)
# Perform limiting loop
domain = "{[i, ii]: 0 <= i < q.dofs and 0 <= ii < q.dofs}"
instructions = """
<float64> alpha = 1
<float64> qavg = qbar[0, 0]
for i
<float64> _alpha1 = fmin(alpha, fmin(1, (qmax[i] - qavg)/(q[i] - qavg)))
<float64> _alpha2 = fmin(alpha, fmin(1, (qavg - qmin[i])/(qavg - q[i])))
alpha = _alpha1 if q[i] > qavg else (_alpha2 if q[i] < qavg else alpha)
end
for ii
q[ii] = qavg + alpha * (q[ii] - qavg)
end
"""
self._limit_kernel = (domain, instructions)
def _construct_centroid_solver(self):
"""
Constructs a linear problem for computing the centroids
:return: LinearSolver instance
"""
u = TrialFunction(self.P0)
v = TestFunction(self.P0)
a = assemble(inner(u, v) * dx)
return LinearSolver(a,
solver_parameters={
'ksp_type': 'preonly',
'pc_type': 'bjacobi',
'sub_pc_type': 'ilu'
})
def _update_centroids(self, field):
"""
Update centroid values
"""
assemble(inner(field, TestFunction(self.P0)) * dx,
tensor=self.centroids_rhs)
self.centroid_solver.solve(self.centroids, self.centroids_rhs)
def compute_bounds(self, field):
"""
Only computes min and max bounds of neighbouring cells
"""
self._update_centroids(field)
self.max_field.assign(-1.0e10) # small number
self.min_field.assign(1.0e10) # big number
par_loop(self._min_max_loop,
dx, {
"maxq": (self.max_field, MAX),
"minq": (self.min_field, MIN),
"q": (self.centroids, READ)
},
is_loopy_kernel=True)
def apply_limiter(self, field):
"""
Only applies limiting loop on the given field
"""
par_loop(self._limit_kernel,
dx, {
"qbar": (self.centroids, READ),
"q": (field, RW),
"qmax": (self.max_field, READ),
"qmin": (self.min_field, READ)
},
is_loopy_kernel=True)
def apply(self, field):
"""
Re-computes centroids and applies limiter to given field
"""
assert field.function_space() == self.P1DG, \
'Given field does not belong to this objects function space'
self.compute_bounds(field)
self.apply_limiter(field)
