def initialize(self, method):
Depositor.initialize(self, method)
discr = method.discretization
eg, = discr.element_groups
fg, = discr.face_groups
ldis = eg.local_discretization
from hedge.mesh import TAG_ALL
bdry = discr.get_boundary(TAG_ALL)
bdry_fg, = bdry.face_groups
if self.filter_response:
from hedge.discretization import Filter
filter = Filter(discr, self.filter_response)
filter_mat, = filter.filter_matrices
else:
filter_mat = numpy.zeros((0, 0))
backend_class = getattr(
_internal,
"AdvectiveDepositor" + method.get_dimensionality_suffix())
self.backend = backend_class(method.mesh_data,
len(ldis.face_indices()),
ldis.node_count(), ldis.mass_matrix(),
ldis.inverse_mass_matrix(), filter_mat,
ldis.face_mass_matrix(), fg, bdry_fg,
self.activation_threshold,
self.kill_threshold, self.upwind_alpha)
for i, diffmat in enumerate(ldis.differentiation_matrices()):
self.backend.add_local_diff_matrix(i, diffmat)
def set_shape_function(self, state, sf):
Depositor.set_shape_function(self, state, sf)
state.depositor_state.clear()
for pn in xrange(len(state)):
self.backend.add_advective_particle(state.depositor_state,
state.particle_state, sf, pn)
def __init__(
self,
activation_threshold=1e-5,
kill_threshold=1e-3,
filter_amp=None,
filter_order=None,
upwind_alpha=1,
):
Depositor.__init__(self)
self.activation_threshold = activation_threshold
self.kill_threshold = kill_threshold
self.upwind_alpha = upwind_alpha
self.shape_function = None
self.filter_amp = filter_amp
self.filter_order = filter_order
if filter_amp is not None:
from hedge.discretization import ExponentialFilterResponseFunction
self.filter_response = ExponentialFilterResponseFunction(
filter_amp, filter_order)
else:
self.filter_response = None
def add_instrumentation(self, mgr, observer):
Depositor.add_instrumentation(self, mgr, observer)
# instrumentation
from pytools.log import IntervalTimer, EventCounter
self.element_activation_counter = EventCounter(
"n_el_activations",
"#Advective rec. elements activated this timestep")
self.element_kill_counter = EventCounter(
"n_el_kills", "#Advective rec. elements retired this timestep")
self.advective_rhs_timer = IntervalTimer(
"t_advective_rhs", "Time spent evaluating advective RHS")
self.active_elements_log = ActiveAdvectiveElements(observer)
mgr.add_quantity(self.element_activation_counter)
mgr.add_quantity(self.element_kill_counter)
mgr.add_quantity(self.advective_rhs_timer)
mgr.add_quantity(self.active_elements_log)
mgr.set_constant("el_activation_threshold", self.activation_threshold)
mgr.set_constant("el_kill_threshold", self.kill_threshold)
mgr.set_constant("adv_upwind_alpha", self.upwind_alpha)
mgr.set_constant("filter_amp", self.filter_amp)
mgr.set_constant("filter_amp", self.filter_order)
def initialize(self, method):
Depositor.initialize(self, method)
backend_class = getattr(
_internal,
"InterpolatingDepositor" + method.get_dimensionality_suffix())
self.backend = backend_class(method.mesh_data)
def add_instrumentation(self, mgr, observer):
Depositor.add_instrumentation(self, mgr, observer)
# instrumentation
from pytools.log import IntervalTimer, EventCounter
self.element_activation_counter = EventCounter(
"n_el_activations",
"#Advective rec. elements activated this timestep")
self.element_kill_counter = EventCounter(
"n_el_kills",
"#Advective rec. elements retired this timestep")
self.advective_rhs_timer = IntervalTimer(
"t_advective_rhs",
"Time spent evaluating advective RHS")
self.active_elements_log = ActiveAdvectiveElements(observer)
mgr.add_quantity(self.element_activation_counter)
mgr.add_quantity(self.element_kill_counter)
mgr.add_quantity(self.advective_rhs_timer)
mgr.add_quantity(self.active_elements_log)
mgr.set_constant("el_activation_threshold", self.activation_threshold)
mgr.set_constant("el_kill_threshold", self.kill_threshold)
mgr.set_constant("adv_upwind_alpha", self.upwind_alpha)
mgr.set_constant("filter_amp", self.filter_amp)
mgr.set_constant("filter_amp", self.filter_order)
def set_shape_function(self, state, sf):
Depositor.set_shape_function(self, state, sf)
state.depositor_state.clear()
for pn in xrange(len(state)):
self.backend.add_advective_particle(
state.depositor_state,
state.particle_state,
sf, pn)
def add_instrumentation(self, mgr, observer):
Depositor.add_instrumentation(self, mgr, observer)
mgr.set_constant("rec_grid_el_tolerance", self.el_tolerance)
mgr.set_constant("rec_grid_enforce_continuity", self.enforce_continuity)
mgr.set_constant("rec_grid_method", self.submethod)
mgr.set_constant("rec_grid_jiggle_radius", self.jiggle_radius)
self.brick_generator.log_data(mgr)
def initialize(self, method):
Depositor.initialize(self, method)
eg, = method.discretization.element_groups
ldis = eg.local_discretization
backend_class = getattr(_internal, "NormalizingInterpolatingDepositor"
+ method.get_dimensionality_suffix())
self.backend = backend_class(method.mesh_data, ldis.mass_matrix())
def initialize(self, method):
Depositor.initialize(self, method)
eg, = method.discretization.element_groups
ldis = eg.local_discretization
backend_class = getattr(
_internal, "NormalizingInterpolatingDepositor" +
method.get_dimensionality_suffix())
self.backend = backend_class(method.mesh_data, ldis.mass_matrix())
def add_instrumentation(self, mgr, observer):
Depositor.add_instrumentation(self, mgr, observer)
mgr.set_constant("rec_grid_el_tolerance", self.el_tolerance)
mgr.set_constant("rec_grid_enforce_continuity",
self.enforce_continuity)
mgr.set_constant("rec_grid_method", self.submethod)
mgr.set_constant("rec_grid_jiggle_radius", self.jiggle_radius)
self.brick_generator.log_data(mgr)
def initialize(self, method):
Depositor.initialize(self, method)
if self.jiggle_radius:
dep_type = "Jiggly"
else:
dep_type = "Regular"
backend_class = getattr(
_internal,
dep_type + "GridDepositor" + method.get_dimensionality_suffix())
backend = self.backend = backend_class(method.mesh_data)
discr = method.discretization
if self.enforce_continuity:
self.prepare_average_groups()
else:
backend.average_group_starts.append(0)
if self.filter_min_amplification is not None:
from hedge.discretization import Filter, ExponentialFilterResponseFunction
self.filter = Filter(
discr,
ExponentialFilterResponseFunction(
self.filter_min_amplification, self.filter_order))
else:
self.filter = None
for i, (stepwidths, origin,
dims) in enumerate(self.brick_generator(discr)):
if self.jiggle_radius:
brk = _internal.JigglyBrick(
i,
backend.grid_node_count_with_extra(),
stepwidths,
origin,
dims,
jiggle_radius=self.jiggle_radius)
else:
brk = _internal.Brick(i, backend.grid_node_count_with_extra(),
stepwidths, origin, dims)
backend.bricks.append(brk)
if self.submethod == "simplex_extra":
self.prepare_with_pointwise_projection_and_extra_points()
elif self.submethod == "simplex_enlarge":
self.prepare_with_pointwise_projection_and_enlargement()
elif self.submethod == "simplex_reduce":
self.prepare_with_pointwise_projection_and_basis_reduction()
elif self.submethod == "brick":
self.prepare_with_brick_interpolation()
else:
raise RuntimeError, "invalid rec_grid submethod specified"
def initialize(self, method):
Depositor.initialize(self, method)
if self.jiggle_radius:
dep_type = "Jiggly"
else:
dep_type = "Regular"
backend_class = getattr(_internal,
dep_type + "GridDepositor" + method.get_dimensionality_suffix())
backend = self.backend = backend_class(method.mesh_data)
discr = method.discretization
if self.enforce_continuity:
self.prepare_average_groups()
else:
backend.average_group_starts.append(0)
if self.filter_min_amplification is not None:
from hedge.discretization import Filter, ExponentialFilterResponseFunction
self.filter = Filter(discr, ExponentialFilterResponseFunction(
self.filter_min_amplification, self.filter_order))
else:
self.filter = None
for i, (stepwidths, origin, dims) in enumerate(
self.brick_generator(discr)):
if self.jiggle_radius:
brk = _internal.JigglyBrick(i, backend.grid_node_count_with_extra(),
stepwidths, origin, dims,
jiggle_radius=self.jiggle_radius)
else:
brk = _internal.Brick(i, backend.grid_node_count_with_extra(),
stepwidths, origin, dims)
backend.bricks.append(brk)
if self.submethod == "simplex_extra":
self.prepare_with_pointwise_projection_and_extra_points()
elif self.submethod == "simplex_enlarge":
self.prepare_with_pointwise_projection_and_enlargement()
elif self.submethod == "simplex_reduce":
self.prepare_with_pointwise_projection_and_basis_reduction()
elif self.submethod == "brick":
self.prepare_with_brick_interpolation()
else:
raise RuntimeError, "invalid rec_grid submethod specified"
def add_instrumentation(self, mgr, observer):
Depositor.add_instrumentation(self, mgr, observer)
from pyrticle.log import StatsGathererLogQuantity
mgr.add_quantity(StatsGathererLogQuantity(
lambda : observer.state.depositor_state.stats.normalization_stats,
"normshape_norm", "1",
"normalization constants applied during deposition"))
mgr.add_quantity(StatsGathererLogQuantity(
lambda : observer.state.depositor_state.stats.centroid_distance_stats,
"normshape_centroid_dist", "m",
"distance of shape center from element centroid"))
mgr.add_quantity(StatsGathererLogQuantity(
lambda : observer.state.depositor_state.stats.el_per_particle_stats,
"normshape_el_per_particle", "1",
"number of elements per particle"))
def __init__(self, brick_generator=SingleBrickGenerator(),
el_tolerance=0.12,
max_extra_points=20,
enforce_continuity=False,
submethod="simplex_reduce",
filter_min_amplification=None,
filter_order=None,
jiggle_radius=0.0,
):
Depositor.__init__(self)
self.brick_generator = brick_generator
self.el_tolerance = el_tolerance
self.max_extra_points = max_extra_points
self.enforce_continuity = enforce_continuity
self.submethod = submethod
self.filter_min_amplification = filter_min_amplification
self.filter_order = filter_order
self.jiggle_radius = jiggle_radius
def __init__(self, activation_threshold=1e-5, kill_threshold=1e-3,
filter_amp=None, filter_order=None,
upwind_alpha=1,
):
Depositor.__init__(self)
self.activation_threshold = activation_threshold
self.kill_threshold = kill_threshold
self.upwind_alpha = upwind_alpha
self.shape_function = None
self.filter_amp = filter_amp
self.filter_order = filter_order
if filter_amp is not None:
from hedge.discretization import ExponentialFilterResponseFunction
self.filter_response = ExponentialFilterResponseFunction(
filter_amp, filter_order)
else:
self.filter_response = None
def add_instrumentation(self, mgr, observer):
Depositor.add_instrumentation(self, mgr, observer)
from pyrticle.log import StatsGathererLogQuantity
mgr.add_quantity(
StatsGathererLogQuantity(
lambda: observer.state.depositor_state.stats.
normalization_stats, "normshape_norm", "1",
"normalization constants applied during deposition"))
mgr.add_quantity(
StatsGathererLogQuantity(
lambda: observer.state.depositor_state.stats.
centroid_distance_stats, "normshape_centroid_dist", "m",
"distance of shape center from element centroid"))
mgr.add_quantity(
StatsGathererLogQuantity(
lambda: observer.state.depositor_state.stats.
el_per_particle_stats, "normshape_el_per_particle", "1",
"number of elements per particle"))
def __init__(
self,
brick_generator=SingleBrickGenerator(),
el_tolerance=0.12,
max_extra_points=20,
enforce_continuity=False,
submethod="simplex_reduce",
filter_min_amplification=None,
filter_order=None,
jiggle_radius=0.0,
):
Depositor.__init__(self)
self.brick_generator = brick_generator
self.el_tolerance = el_tolerance
self.max_extra_points = max_extra_points
self.enforce_continuity = enforce_continuity
self.submethod = submethod
self.filter_min_amplification = filter_min_amplification
self.filter_order = filter_order
self.jiggle_radius = jiggle_radius
def initialize(self, method):
Depositor.initialize(self, method)
discr = method.discretization
eg, = discr.element_groups
fg, = discr.face_groups
ldis = eg.local_discretization
from hedge.mesh import TAG_ALL
bdry = discr.get_boundary(TAG_ALL)
bdry_fg, = bdry.face_groups
if self.filter_response:
from hedge.discretization import Filter
filter = Filter(discr, self.filter_response)
filter_mat, = filter.filter_matrices
else:
filter_mat = numpy.zeros((0,0))
backend_class = getattr(_internal, "AdvectiveDepositor"
+ method.get_dimensionality_suffix())
self.backend = backend_class(method.mesh_data,
len(ldis.face_indices()),
ldis.node_count(),
ldis.mass_matrix(),
ldis.inverse_mass_matrix(),
filter_mat,
ldis.face_mass_matrix(),
fg,
bdry_fg,
self.activation_threshold,
self.kill_threshold,
self.upwind_alpha)
for i, diffmat in enumerate(ldis.differentiation_matrices()):
self.backend.add_local_diff_matrix(i, diffmat)
def clear_particles(self):
Depositor.clear_particles(self)
self.cloud.pic_algorithm.clear_advective_particles()
def clear_particles(self):
Depositor.clear_particles(self)
self.cloud.pic_algorithm.clear_advective_particles()
def set_shape_function(self, state, sf):
Depositor.set_shape_function(self, state, sf)
self.backend.shape_function = sf
def set_shape_function(self, state, sf):
Depositor.set_shape_function(self, state, sf)
self.backend.shape_function = sf
def initialize(self, method):
Depositor.initialize(self, method)
backend_class = getattr(_internal, "InterpolatingDepositor"
+ method.get_dimensionality_suffix())
self.backend = backend_class(method.mesh_data)
def __init__(self, brick_generator=None):
Depositor.__init__(self)
self.brick_generator = brick_generator
def initialize(self, method):
Depositor.initialize(self, method)
backend_class = getattr(_internal, "GridFindDepositor"
+ method.get_dimensionality_suffix())
backend = self.backend = backend_class(method.mesh_data)
discr = method.discretization
grid_node_num_to_nodes = {}
if self.brick_generator is None:
bbox_min, bbox_max = discr.mesh.bounding_box()
max_bbox_size = max(bbox_max-bbox_min)
self.brick_generator = SingleBrickGenerator(
mesh_margin=1e-3*max_bbox_size,
overresolve=0.2)
from pyrticle._internal import Brick
for i, (stepwidths, origin, dims) in enumerate(
self.brick_generator(discr)):
backend.bricks.append(
Brick(i, backend.grid_node_count(), stepwidths, origin, dims))
from pyrticle._internal import BoxFloat
for eg in discr.element_groups:
ldis = eg.local_discretization
for el in eg.members:
el_bbox = BoxFloat(*el.bounding_box(discr.mesh.points))
el_slice = discr.find_el_range(el.id)
for brk in backend.bricks:
if brk.bounding_box().intersect(el_bbox).is_empty():
continue
for node_num in range(el_slice.start, el_slice.stop):
try:
cell_number = brk.which_cell(
discr.nodes[node_num])
except ValueError:
pass
else:
grid_node_num_to_nodes.setdefault(
brk.index(cell_number), []).append(node_num)
from pytools import flatten
unassigned_nodes = (set(xrange(len(discr)))
- set(flatten(grid_node_num_to_nodes.itervalues())))
if unassigned_nodes:
raise RuntimeError("dep_grid_find: unassigned mesh nodes found. "
"you should specify a mesh_margin when generating "
"bricks")
usecounts = numpy.zeros(
(backend.grid_node_count(),))
for gnn in xrange(backend.grid_node_count()):
grid_nodes = grid_node_num_to_nodes.get(gnn, [])
usecounts[gnn] = len(grid_nodes)
backend.node_number_list_starts.append(len(backend.node_number_lists))
backend.node_number_lists.extend(grid_nodes)
backend.node_number_list_starts.append(len(backend.node_number_lists))
if "depositor" in method.debug:
from hedge.visualization import SiloVisualizer
vis = SiloVisualizer(discr)
visf = vis.make_file("grid-find-debug")
vis.add_data(visf, [])
self.visualize_grid_quantities(visf, [
("usecounts", usecounts)
])
visf.close()
if "interactive" in cloud.debug:
from matplotlib.pylab import hist, show
hist(usecounts, bins=20)
show()
def __init__(self, brick_generator=None):
Depositor.__init__(self)
self.brick_generator = brick_generator
def initialize(self, method):
Depositor.initialize(self, method)
backend_class = getattr(
_internal,
"GridFindDepositor" + method.get_dimensionality_suffix())
backend = self.backend = backend_class(method.mesh_data)
discr = method.discretization
grid_node_num_to_nodes = {}
if self.brick_generator is None:
bbox_min, bbox_max = discr.mesh.bounding_box()
max_bbox_size = max(bbox_max - bbox_min)
self.brick_generator = SingleBrickGenerator(mesh_margin=1e-3 *
max_bbox_size,
overresolve=0.2)
from pyrticle._internal import Brick
for i, (stepwidths, origin,
dims) in enumerate(self.brick_generator(discr)):
backend.bricks.append(
Brick(i, backend.grid_node_count(), stepwidths, origin, dims))
from pyrticle._internal import BoxFloat
for eg in discr.element_groups:
ldis = eg.local_discretization
for el in eg.members:
el_bbox = BoxFloat(*el.bounding_box(discr.mesh.points))
el_slice = discr.find_el_range(el.id)
for brk in backend.bricks:
if brk.bounding_box().intersect(el_bbox).is_empty():
continue
for node_num in range(el_slice.start, el_slice.stop):
try:
cell_number = brk.which_cell(discr.nodes[node_num])
except ValueError:
pass
else:
grid_node_num_to_nodes.setdefault(
brk.index(cell_number), []).append(node_num)
from pytools import flatten
unassigned_nodes = (set(xrange(len(discr))) -
set(flatten(grid_node_num_to_nodes.itervalues())))
if unassigned_nodes:
raise RuntimeError(
"dep_grid_find: unassigned mesh nodes found. "
"you should specify a mesh_margin when generating "
"bricks")
usecounts = numpy.zeros((backend.grid_node_count(), ))
for gnn in xrange(backend.grid_node_count()):
grid_nodes = grid_node_num_to_nodes.get(gnn, [])
usecounts[gnn] = len(grid_nodes)
backend.node_number_list_starts.append(
len(backend.node_number_lists))
backend.node_number_lists.extend(grid_nodes)
backend.node_number_list_starts.append(len(backend.node_number_lists))
if "depositor" in method.debug:
from hedge.visualization import SiloVisualizer
vis = SiloVisualizer(discr)
visf = vis.make_file("grid-find-debug")
vis.add_data(visf, [])
self.visualize_grid_quantities(visf, [("usecounts", usecounts)])
visf.close()
if "interactive" in cloud.debug:
from matplotlib.pylab import hist, show
hist(usecounts, bins=20)
show()
