def get_additional_code_nodes(self, lb_method):
"""Return a list of code nodes that will be added in the generated code before the index field loop.
Args:
lb_method: Lattice Boltzmann method. See :func:`lbmpy.creationfunctions.create_lb_method`
Returns:
list containing NeighbourOffsetArrays
"""
return [NeighbourOffsetArrays(lb_method.stencil)]
def __call__(self, f_out, f_in, dir_symbol, inv_dir, lb_method, index_field):
vel_from_idx_field = callable(self._velocity)
vel = [index_field(f'vel_{i}') for i in range(self.dim)] if vel_from_idx_field else self._velocity
assert self.dim == lb_method.dim, \
f"Dimension of UBB ({self.dim}) does not match dimension of method ({lb_method.dim})"
neighbor_offset = NeighbourOffsetArrays.neighbour_offset(dir_symbol, lb_method.stencil)
velocity = tuple(v_i.get_shifted(*neighbor_offset)
if isinstance(v_i, Field.Access) and not vel_from_idx_field
else v_i
for v_i in vel)
if self._adaptVelocityToForce:
cqc = lb_method.conserved_quantity_computation
shifted_vel_eqs = cqc.equilibrium_input_equations_from_init_values(velocity=velocity)
shifted_vel_eqs = shifted_vel_eqs.new_without_subexpressions()
velocity = [eq.rhs for eq in shifted_vel_eqs.new_filtered(cqc.first_order_moment_symbols).main_assignments]
c_s_sq = sp.Rational(1, 3)
weight_info = LbmWeightInfo(lb_method, data_type=self.data_type)
weight_of_direction = weight_info.weight_of_direction
vel_term = 2 / c_s_sq * sum([d_i * v_i for d_i, v_i in zip(neighbor_offset, velocity)]) * weight_of_direction(
dir_symbol, lb_method)
# Better alternative: in conserved value computation
# rename what is currently called density to "virtual_density"
# provide a new quantity density, which is constant in case of incompressible models
if not lb_method.conserved_quantity_computation.zero_centered_pdfs:
cqc = lb_method.conserved_quantity_computation
density_symbol = sp.Symbol("rho")
pdf_field_accesses = [f_out(i) for i in range(len(lb_method.stencil))]
density_equations = cqc.output_equations_from_pdfs(pdf_field_accesses, {'density': density_symbol})
density_symbol = lb_method.conserved_quantity_computation.defined_symbols()['density']
result = density_equations.all_assignments
result += [Assignment(f_in(inv_dir[dir_symbol]),
f_out(dir_symbol) - vel_term * density_symbol)]
return result
else:
return [Assignment(f_in(inv_dir[dir_symbol]),
f_out(dir_symbol) - vel_term)]
def __call__(self, f_out, f_in, dir_symbol, inv_dir, lb_method, index_field):
subexpressions = []
boundary_assignments = []
dtdx = sp.Rational(self.dt, self.dx)
neighbor_offset = NeighbourOffsetArrays.neighbour_offset(dir_symbol, lb_method.stencil)
tangential_offset = tuple(offset - normal for offset, normal in zip(neighbor_offset, self.normal_direction))
interpolated_pdf_sym = sp.Symbol('pdf_inter')
interpolated_pdf_asm = Assignment(interpolated_pdf_sym, (index_field[0]('pdf') * (self.c * dtdx))
+ ((sp.Number(1) - self.c * dtdx) * index_field[0]('pdf_nd')))
subexpressions.append(interpolated_pdf_asm)
asm = Assignment(f_in.center(inv_dir[dir_symbol]), interpolated_pdf_sym)
boundary_assignments.append(asm)
asm = Assignment(index_field[0]('pdf'), f_out[tangential_offset](inv_dir[dir_symbol]))
boundary_assignments.append(asm)
asm = Assignment(index_field[0]('pdf_nd'), interpolated_pdf_sym)
boundary_assignments.append(asm)
return AssignmentCollection(boundary_assignments, subexpressions=subexpressions)
def __call__(self, f_out, f_in, dir_symbol, inv_dir, lb_method, index_field):
neighbour_offset = NeighbourOffsetArrays.neighbour_offset(dir_symbol, lb_method.stencil)
return [Assignment(f_in(inv_dir[dir_symbol]), self.constant),
Assignment(f_out[neighbour_offset](dir_symbol), self.constant)]
def __call__(self, f_out, f_in, dir_symbol, inv_dir, lb_method, index_field):
neighbor_offset = NeighbourOffsetArrays.neighbour_offset(dir_symbol, lb_method.stencil)
tangential_offset = tuple(offset - normal for offset, normal in zip(neighbor_offset, self.normal_direction))
return Assignment(f_in.center(inv_dir[dir_symbol]), f_out[tangential_offset](inv_dir[dir_symbol]))