def callback_refinement_criterion(
q, qbc, aux, subdivision_factor_x0, subdivision_factor_x1,
subdivision_factor_x2, unknowns_per_cell, aux_fields_per_cell,
size_x, size_y, size_z, position_x, position_y, position_z):
import peanoclaw
from peanoclaw.converter import get_number_of_dimensions
from peanoclaw.converter import create_domain
from peanoclaw.converter import create_subgrid_state
number_of_dimensions = get_number_of_dimensions(q)
position = (position_x, position_y, position_z)
size = (size_x, size_y, size_z)
subdivision_factor = (subdivision_factor_x0, subdivision_factor_x1,
subdivision_factor_x2)
self.domain = create_domain(number_of_dimensions, position, size,
subdivision_factor)
subgrid_state = create_subgrid_state(self.solver.solution.state,
self.domain, q, qbc, aux,
unknowns_per_cell,
aux_fields_per_cell)
#Steer refinement
if self.refinement_criterion != None:
return self.refinement_criterion(subgrid_state)
else:
return self.initial_minimal_mesh_width
def callback_interpolation(
source_q, source_qbc, source_aux, source_subdivision_factor_x0,
source_subdivision_factor_x1, source_subdivision_factor_x2,
source_size_x0, source_size_x1, source_size_x2,
source_position_x0, source_position_x1, source_position_x2,
source_current_time, source_timestep_size, destination_q,
destination_qbc, destination_aux,
destination_subdivision_factor_x0,
destination_subdivision_factor_x1,
destination_subdivision_factor_x2, destination_size_x0,
destination_size_x1, destination_size_x2,
destination_position_x0, destination_position_x1,
destination_position_x2, destination_current_time,
destination_timestep_size, unknowns_per_cell,
aux_fields_per_cell):
# Fix aux array
if (aux_fields_per_cell == 0):
source_aux = None
destination_aux = None
number_of_dimensions = get_number_of_dimensions(source_q)
source_domain = create_domain(
number_of_dimensions,
(source_position_x0, source_position_x1, source_position_x2),
(source_size_x0, source_size_x1, source_size_x2),
(source_subdivision_factor_x0, source_subdivision_factor_x1,
source_subdivision_factor_x2))
source_subgrid_state = create_subgrid_state(
self.solver.solution.state, source_domain, source_q,
source_qbc, source_aux, unknowns_per_cell, aux_fields_per_cell)
destination_domain = create_domain(
number_of_dimensions,
(destination_position_x0, destination_position_x1,
destination_position_x2),
(destination_size_x0, destination_size_x1,
destination_size_x2), (destination_subdivision_factor_x0,
destination_subdivision_factor_x1,
destination_subdivision_factor_x2))
destination_subgrid_state = create_subgrid_state(
self.solver.solution.state, destination_domain, destination_q,
destination_qbc, destination_aux, unknowns_per_cell,
aux_fields_per_cell)
self.interpolation(source_subgrid_state, source_qbc,
destination_subgrid_state, destination_qbc)
def __init__(self, solver, global_state, q, qbc, aux, position, size,
subdivision_factor, unknowns_per_cell, aux_fields_per_cell,
current_time):
r"""
Initializes this subgrid solver. It get's all information to prepare a domain and state for a
single subgrid.
:Input:
- *solver* - (:class:`pyclaw.Solver`) The PyClaw-solver used for advancing this subgrid in time.
- *global_state* - (:class:`pyclaw.State`) The global state. This is not the state used for
for the actual solving of the timestep on the subgrid.
- *q* - The array storing the current solution.
- *qbc* - The array storing the solution of the last timestep including the ghostlayer.
- *position* - A d-dimensional tuple holding the position of the grid in the computational domain.
This measures the continuous real-world position in floats, not the integer position
in terms of cells.
- *size* - A d-dimensional tuple holding the size of the grid in the computational domain. This
measures the continuous real-world size in floats, not the size in terms of cells.
- *subdivision_factor* - The number of cells in one dimension of this subgrid. At the moment only
square subgrids are allowed, so the total number of cells in the subgrid
(excluding the ghostlayer) is subdivision_factor x subdivision_factor.
- *unknowns_per_cell* - The number of equations or unknowns that are stored per cell of the subgrid.
"""
self.solver = solver
number_of_dimensions = get_number_of_dimensions(q)
self.domain = create_domain(number_of_dimensions, position, size,
subdivision_factor)
subgrid_state = create_subgrid_state(global_state, self.domain, q, qbc,
aux, unknowns_per_cell,
aux_fields_per_cell)
subgrid_state.problem_data = global_state.problem_data
self.solution = pyclaw.Solution(subgrid_state, self.domain)
self.solution.t = current_time
self.solver.bc_lower[:] = [pyclaw.BC.custom] * len(
self.solver.bc_lower)
self.solver.bc_upper[:] = [pyclaw.BC.custom] * len(
self.solver.bc_upper)
self.qbc = qbc
self.solver.user_bc_lower = self.user_bc_lower
self.solver.user_bc_upper = self.user_bc_upper
self.recover_ghostlayers = False
def callback_refinement_criterion(q, qbc, aux, subdivision_factor_x0, subdivision_factor_x1, subdivision_factor_x2, unknowns_per_cell, aux_fields_per_cell, size_x, size_y, size_z, position_x, position_y, position_z):
import peanoclaw
from peanoclaw.converter import get_number_of_dimensions
from peanoclaw.converter import create_domain
from peanoclaw.converter import create_subgrid_state
number_of_dimensions = get_number_of_dimensions(q)
position = (position_x, position_y, position_z)
size = (size_x, size_y, size_z)
subdivision_factor = (subdivision_factor_x0, subdivision_factor_x1, subdivision_factor_x2)
self.domain = create_domain(number_of_dimensions, position, size, subdivision_factor)
subgrid_state = create_subgrid_state(self.solver.solution.state, self.domain, q, qbc, aux, unknowns_per_cell, aux_fields_per_cell)
#Steer refinement
if self.refinement_criterion != None:
return self.refinement_criterion(subgrid_state)
else:
return self.initial_minimal_mesh_width
def __init__(self, solver, global_state, q, qbc, aux, position, size, subdivision_factor, unknowns_per_cell, aux_fields_per_cell, current_time):
r"""
Initializes this subgrid solver. It get's all information to prepare a domain and state for a
single subgrid.
:Input:
- *solver* - (:class:`pyclaw.Solver`) The PyClaw-solver used for advancing this subgrid in time.
- *global_state* - (:class:`pyclaw.State`) The global state. This is not the state used for
for the actual solving of the timestep on the subgrid.
- *q* - The array storing the current solution.
- *qbc* - The array storing the solution of the last timestep including the ghostlayer.
- *position* - A d-dimensional tuple holding the position of the grid in the computational domain.
This measures the continuous real-world position in floats, not the integer position
in terms of cells.
- *size* - A d-dimensional tuple holding the size of the grid in the computational domain. This
measures the continuous real-world size in floats, not the size in terms of cells.
- *subdivision_factor* - The number of cells in one dimension of this subgrid. At the moment only
square subgrids are allowed, so the total number of cells in the subgrid
(excluding the ghostlayer) is subdivision_factor x subdivision_factor.
- *unknowns_per_cell* - The number of equations or unknowns that are stored per cell of the subgrid.
"""
self.solver = solver
number_of_dimensions = get_number_of_dimensions(q)
self.domain = create_domain(number_of_dimensions, position, size, subdivision_factor)
subgrid_state = create_subgrid_state(global_state, self.domain, q, qbc, aux, unknowns_per_cell, aux_fields_per_cell)
subgrid_state.problem_data = global_state.problem_data
self.solution = pyclaw.Solution(subgrid_state, self.domain)
self.solution.t = current_time
self.solver.bc_lower[:] = [pyclaw.BC.custom] * len(self.solver.bc_lower)
self.solver.bc_upper[:] = [pyclaw.BC.custom] * len(self.solver.bc_upper)
self.qbc = qbc
self.solver.user_bc_lower = self.user_bc_lower
self.solver.user_bc_upper = self.user_bc_upper
self.recover_ghostlayers = False
def callback_restriction(
source_q,
source_qbc,
source_aux,
source_subdivision_factor_x0,
source_subdivision_factor_x1,
source_subdivision_factor_x2,
source_size_x0,
source_size_x1,
source_size_x2,
source_position_x0,
source_position_x1,
source_position_x2,
source_current_time,
source_timestep_size,
destination_q,
destination_qbc,
destination_aux,
destination_subdivision_factor_x0,
destination_subdivision_factor_x1,
destination_subdivision_factor_x2,
destination_size_x0,
destination_size_x1,
destination_size_x2,
destination_position_x0,
destination_position_x1,
destination_position_x2,
destination_current_time,
destination_timestep_size,
unknowns_per_cell,
aux_fields_per_cell):
# Fix aux array
if(aux_fields_per_cell == 0):
source_aux = None
destination_aux = None
number_of_dimensions = get_number_of_dimensions(source_q)
source_domain = create_domain(number_of_dimensions,
(source_position_x0, source_position_x1, source_position_x2),
(source_size_x0, source_size_x1, source_size_x2),
(source_subdivision_factor_x0, source_subdivision_factor_x1, source_subdivision_factor_x2))
source_subgrid_state = create_subgrid_state(
self.solver.solution.state,
source_domain,
source_q,
source_qbc,
source_aux,
unknowns_per_cell,
aux_fields_per_cell)
destination_domain = create_domain(number_of_dimensions,
(destination_position_x0, destination_position_x1, destination_position_x2),
(destination_size_x0, destination_size_x1, destination_size_x2),
(destination_subdivision_factor_x0, destination_subdivision_factor_x1, destination_subdivision_factor_x2))
destination_subgrid_state = create_subgrid_state(
self.solver.solution.state,
destination_domain,
destination_q,
destination_qbc,
destination_aux,
unknowns_per_cell,
aux_fields_per_cell)
self.restriction(source_subgrid_state, source_qbc, destination_subgrid_state, destination_qbc)