def generate_routing_goals_for_polygon(sim,
polygon,
polygon_surface,
scoring_functions=None,
orientation_restrictions=None,
object_ids_to_ignore=None,
flush_planner=False,
sim_location_score_offset=0.0,
add_sim_location_as_goal=True,
los_reference_pt=None,
score_density=2.5,
max_points=100,
min_score_to_ignore_outer_penalty=2,
target_object=2,
target_object_id=0,
even_coverage_step=3,
single_goal_only=False,
los_routing_context=None,
all_blocking_edges_block_los=False):
yield_to_irq()
if los_routing_context is None:
los_routing_context = sim.routing_context
return _placement.generate_routing_goals_for_polygon(
sim.routing_location, polygon, polygon_surface, scoring_functions,
orientation_restrictions, object_ids_to_ignore, sim.routing_context,
flush_planner, sim_location_score_offset, add_sim_location_as_goal,
los_reference_pt, score_density, max_points,
min_score_to_ignore_outer_penalty, target_object_id,
even_coverage_step, single_goal_only, los_routing_context,
all_blocking_edges_block_los)
def generate_routing_goals_for_polygon(sim,
polygon,
polygon_surface,
scoring_functions=None,
orientation_restrictions=None,
object_ids_to_ignore=None,
flush_planner=False,
sim_location_score_offset=0.0,
add_sim_location_as_goal=True,
los_reference_pt=None,
score_density=2.5,
max_points=100,
min_score_to_ignore_outer_penalty=2,
target_object=2,
target_object_id=0,
even_coverage_step=3,
single_goal_only=False,
los_routing_context=None,
all_blocking_edges_block_los=False):
yield_to_irq()
if los_routing_context is None:
los_routing_context = sim.routing_context
return _placement.generate_routing_goals_for_polygon(
sim.routing_location, polygon, polygon_surface, scoring_functions,
orientation_restrictions, object_ids_to_ignore, sim.routing_context,
flush_planner, sim_location_score_offset, add_sim_location_as_goal,
los_reference_pt, score_density, max_points,
min_score_to_ignore_outer_penalty, target_object_id,
even_coverage_step, single_goal_only, los_routing_context,
all_blocking_edges_block_los)
def get_score(cls, resolver: Resolver) -> int:
"""get_score(resolver)
Calculate the score.
"""
try:
yield_to_irq()
cls.get_verbose_log().format_with_message('Retrieving score.',
class_name=cls.__name__)
source_sim = resolver.get_participant(ParticipantType.Actor)
if source_sim is None or not CommonTypeUtils.is_sim_or_sim_info(
source_sim):
cls.get_verbose_log().format_with_message(
'Failed, the Source was not a Sim.', source=source_sim)
return cls.get_default_score()
source_sim_info = CommonSimUtils.get_sim_info(source_sim)
interaction_instance = resolver.interaction or getattr(
resolver, 'affordance', None)
score = cls.calculate_score(resolver, source_sim_info,
interaction_instance)
cls.get_verbose_log().format_with_message(
'Retrieved score for Sim.',
source_sim=source_sim_info,
score=score)
return score
except Exception as ex:
cls.get_verbose_log().error(
'Error occurred while retrieving score.', exception=ex)
return cls.get_default_score()
def generate_routing_goals_for_polygon(sim,
polygon,
polygon_surface,
orientation_restrictions=None,
object_ids_to_ignore=None,
flush_planner=False,
sim_location_bonus=0.0,
add_sim_location_as_goal=True,
los_reference_pt=None,
max_points=100,
ignore_outer_penalty_amount=2,
target_object=2,
target_object_id=0,
even_coverage_step=2,
single_goal_only=False,
los_routing_context=None,
all_blocking_edges_block_los=False,
provided_points=(),
min_water_depth=None,
max_water_depth=None,
terrain_tags=None):
yield_to_irq()
routing_context = sim.get_routing_context()
if los_routing_context is None:
los_routing_context = routing_context
return _placement.generate_routing_goals_for_polygon(
sim.routing_location, polygon, polygon_surface, None,
orientation_restrictions, object_ids_to_ignore, routing_context,
flush_planner, -sim_location_bonus, add_sim_location_as_goal,
los_reference_pt, 2.5, max_points, ignore_outer_penalty_amount,
target_object_id, even_coverage_step, single_goal_only,
los_routing_context, all_blocking_edges_block_los, provided_points,
min_water_depth, max_water_depth, terrain_tags)
def get_score(cls, resolver):
yield_to_irq()
target = resolver.get_participant(
ParticipantType.TargetSim) or resolver.get_participant(
ParticipantType.Listeners)
if has_sim_permission_for_nudity(target)[0]:
return 100
return 0
def _on_sim_posture_event(self, change, dest_state, track, old_posture, new_posture):
if not PostureTrack.is_body(track):
return
yield_to_irq()
posture = new_posture or old_posture
sim = posture.sim
if change == PostureEvent.TRANSITION_START:
if isinstance(self._footprints.get(sim), PolygonFootprint):
sim.routing_context.remove_footprint_contour_override(self._footprints[sim].footprint_id)
self._footprints[sim] = FP_REMOVED_BY_POSTURE
elif change == PostureEvent.TRANSITION_COMPLETE and self._footprints.get(sim) == FP_REMOVED_BY_POSTURE:
self._add_user_footprint(sim)
def generate_content_set(sim, super_affordance, super_interaction, context, potential_targets=(), include_failed_aops_with_tooltip=False, push_super_on_prepare=False, check_posture_compatibility=False, aop_kwargs=frozendict()):
si_or_sa = super_interaction if super_interaction is not None else super_affordance
if not si_or_sa.has_affordances():
return ()
yield_to_irq()
phase_index = None
if super_interaction and not _mixer_name_list:
phase_index = super_interaction.phase_index
valid = collections.defaultdict(list)
if gsi_handlers.content_set_handlers.archiver.enabled:
gsi_considered = {}
else:
gsi_considered = None
if check_posture_compatibility and sim is not None and sim.posture.target is not None:
show_posture_incompatible_icon = True
else:
show_posture_incompatible_icon = False
if not si_or_sa.is_social or potential_targets:
with sims4.callback_utils.invoke_enter_exit_callbacks(sims4.callback_utils.CallbackEvent.CONTENT_SET_GENERATE_ENTER, sims4.callback_utils.CallbackEvent.CONTENT_SET_GENERATE_EXIT):
target_to_posture_icon_info = {}
for affordance in si_or_sa.all_affordances_gen(phase_index=phase_index):
if affordance.is_super:
logger.error('Content set contains a super affordance: {} has {}', si_or_sa, affordance)
targets = _test_affordance_and_get_targets(affordance, potential_targets, sim, considered=gsi_considered)
if targets is None:
pass
for target in targets:
valid_aops_gen = get_valid_aops_gen(target, affordance, super_affordance, super_interaction, context, include_failed_aops_with_tooltip, push_super_on_prepare=push_super_on_prepare, considered=gsi_considered, aop_kwargs=aop_kwargs)
for (aop, test_result) in valid_aops_gen:
if not aop.affordance.is_super:
aop_show_posture_incompatible_icon = False
if show_posture_incompatible_icon:
aop_show_posture_incompatible_icon = show_posture_incompatible_icon
if target not in target_to_posture_icon_info:
if aop.compatible_with_current_posture_state(sim):
aop_show_posture_incompatible_icon = False
target_to_posture_icon_info[target] = aop_show_posture_incompatible_icon
else:
aop_show_posture_incompatible_icon = target_to_posture_icon_info[target]
aop.show_posture_incompatible_icon = aop_show_posture_incompatible_icon
mixer_weight = aop.affordance.calculate_autonomy_weight(sim)
else:
mixer_weight = 0
valid[affordance].append((mixer_weight, aop, test_result))
if sim.posture.source_interaction is si_or_sa:
for buff in sim.Buffs:
buff_aops = get_buff_aops(sim, buff, sim.animation_interaction, context, potential_targets=potential_targets, gsi_considered=gsi_considered)
while buff_aops:
valid.update(buff_aops)
if valid:
return list(_select_affordances_gen(sim, super_affordance, valid, show_posture_incompatible_icon, gsi_considered))
return ()
def get_score(cls, resolver):
yield_to_irq()
sim = resolver.get_participant(ParticipantType.Actor)
target = resolver.get_participant(
ParticipantType.TargetSim) or resolver.get_participant(
ParticipantType.Listeners)
if sim is None or target is None:
return 0
pre_sex_handler = sim_ev(sim).active_pre_sex_handler
if pre_sex_handler is not None and pre_sex_handler.is_failure_sex():
return 0
if pre_sex_handler is not None and pre_sex_handler.is_success_sex():
return 1000
return get_test_relationship_score((sim, target))
def _on_sim_posture_event(self, change, dest_state, track, old_posture,
new_posture):
if not PostureTrack.is_body(track):
return
yield_to_irq()
posture = new_posture or old_posture
sim = posture.sim
if change == PostureEvent.TRANSITION_START:
if isinstance(self._footprints.get(sim), PolygonFootprint):
sim.routing_context.remove_footprint_contour_override(
self._footprints[sim].footprint_id)
self._footprints[sim] = FP_REMOVED_BY_POSTURE
elif change == PostureEvent.TRANSITION_COMPLETE and self._footprints.get(
sim) == FP_REMOVED_BY_POSTURE:
self._add_user_footprint(sim)
def get_score(cls, resolver):
yield_to_irq()
sim = resolver.get_participant(ParticipantType.Actor)
if has_sim_permission_for_nudity(sim)[0]:
return 100
return 0
def _trigger_interaction_complete_test_event(self):
yield_to_irq()
super()._trigger_interaction_complete_test_event()
self._remove_target_event_auto_update()
def apply_operations(self):
for loot_action in self._loot_actions:
yield_to_irq()
loot_action.apply_to_resolver(self._resolver)
def apply_operations(self):
resolver = self._interaction.get_resolver()
for loot_action in self._loot_actions:
yield_to_irq()
loot_action.apply_to_resolver(resolver)
def _trigger_interaction_complete_test_event(self):
yield_to_irq()
super()._trigger_interaction_complete_test_event()
self._remove_target_event_auto_update()
def _create_containment_slot_data_list(self, key, actor, actor_name, to_state_name, from_state_name, posture, entry, verbose_logging):
cache_containment_slot_data_list = True
param_sequence_list = self._get_param_sequences_for_cache(actor, actor_name, to_state_name, from_state_name, posture)
boundary_to_params = {}
for param_sequence in param_sequence_list:
self.set_param_sequence(param_sequence)
yield_to_irq()
if verbose_logging:
logger.warn(' Setting parameter list on ASM:')
for (key, value) in param_sequence.items():
logger.warn(' {}:\t{}', key, value)
boundary = self.get_boundary_conditions(actor, to_state_name, from_state_name)
boundary.debug_info = None
pre_condition_reference_object_name = self.get_actor_name_from_id(boundary.pre_condition_reference_object_id)
post_condition_reference_object_name = self.get_actor_name_from_id(boundary.post_condition_reference_object_id)
if verbose_logging:
logger.warn(' Pre conditions')
logger.warn(' Object: {}', pre_condition_reference_object_name)
logger.warn(' Translation: {}', boundary.pre_condition_transform.translation)
logger.warn(' Orientation: {}', boundary.pre_condition_transform.orientation)
logger.warn(' Post conditions')
logger.warn(' Object: {}', post_condition_reference_object_name)
logger.warn(' Translation: {}', boundary.post_condition_transform.translation)
logger.warn(' Orientation: {}', boundary.post_condition_transform.orientation)
required_slots = []
currently_set_actor_names = self._get_all_set_actor_names()
if boundary.required_slots:
for required_slot in boundary.required_slots:
pre_condition_surface_child_id = required_slot[0]
pre_condition_surface_object_id = required_slot[1]
pre_condition_surface_child_name = self.get_actor_name_from_id(pre_condition_surface_child_id)
pre_condition_surface_object_name = self.get_actor_name_from_id(pre_condition_surface_object_id)
if pre_condition_surface_child_name and pre_condition_surface_object_name:
required_slots.append((pre_condition_surface_child_name, pre_condition_surface_object_name, required_slot[2]))
else:
cache_containment_slot_data_list = False
self._log_bc_error(logger.error, currently_set_actor_names, key, 'missing parent or child object', "The parent or child in Maya isn't one of the following actors:")
if not required_slots and boundary.pre_condition_reference_object_id is None:
pass
if boundary.pre_condition_reference_object_id is not None and pre_condition_reference_object_name is None:
pass
for (boundary_existing, params_list) in boundary_to_params.items():
while pre_condition_reference_object_name == boundary_existing.pre_condition_reference_object_name and (post_condition_reference_object_name == boundary_existing.post_condition_reference_object_name and (self.transform_almost_equal_2d(boundary.pre_condition_transform, boundary_existing.pre_condition_transform) and self.transform_almost_equal_2d(boundary.post_condition_transform, boundary_existing.post_condition_transform))) and required_slots == boundary_existing.required_slots:
params_list.append(param_sequence)
break
boundary_relative = self.BoundaryConditionRelative(pre_condition_reference_object_name, boundary.pre_condition_transform, post_condition_reference_object_name, boundary.post_condition_transform, required_slots, boundary.debug_info)
boundary_to_params[boundary_relative] = [param_sequence]
if verbose_logging:
logger.warn(' Boundary -> Param Sequences')
for (key, value) in boundary_to_params.items():
logger.warn(' {}', key)
for param_sequence in value:
logger.warn(' {}', param_sequence)
boundary_list = []
if len(boundary_to_params) > 0:
if len(boundary_to_params) == 1:
boundary_list.append((boundary_to_params.popitem()[0], [{}]))
else:
boundary_param_sets = partition_boundary_on_params(boundary_to_params)
for (boundary, param_set) in boundary_param_sets.items():
boundary_params_list_minimal = {frozendict({k: v for (k, v) in boundary_params.items() if k in param_set}) for boundary_params in boundary_to_params[boundary]}
boundary_list.append((boundary, boundary_params_list_minimal))
relative_object_name = None
containment_slot_data_list = []
for (boundary_condition, slot_params_list) in boundary_list:
relative_object_name_key = boundary_condition.pre_condition_reference_object_name or boundary_condition.post_condition_reference_object_name
if entry:
if boundary_condition.post_condition_reference_object_name is not None:
containment_transform = boundary_condition.post_condition_transform
else:
containment_transform = boundary_condition.pre_condition_transform
else:
containment_transform = boundary_condition.pre_condition_transform
for (containment_transform_existing, slots_to_params) in containment_slot_data_list:
while self.transform_almost_equal_2d(containment_transform, containment_transform_existing):
slots_to_params.append((boundary_condition, slot_params_list))
break
containment_slot_data_list.append((containment_transform, [(boundary_condition, slot_params_list)]))
if cache_containment_slot_data_list:
self._bc_cache[key] = tuple(containment_slot_data_list)
return containment_slot_data_list
def get_score(cls, resolver):
yield_to_irq()
return sum(test_pair.score for test_pair in cls._scores if resolver(test_pair.test))
def generate_content_set(sim,
super_affordance,
super_interaction,
context,
potential_targets=(),
include_failed_aops_with_tooltip=False,
push_super_on_prepare=False,
check_posture_compatibility=False,
aop_kwargs=frozendict()):
si_or_sa = super_interaction if super_interaction is not None else super_affordance
if not si_or_sa.has_affordances():
return ()
yield_to_irq()
phase_index = None
if super_interaction and not _mixer_name_list:
phase_index = super_interaction.phase_index
valid = collections.defaultdict(list)
if gsi_handlers.content_set_handlers.archiver.enabled:
gsi_considered = {}
else:
gsi_considered = None
if check_posture_compatibility and sim is not None and sim.posture.target is not None:
show_posture_incompatible_icon = True
else:
show_posture_incompatible_icon = False
if not si_or_sa.is_social or potential_targets:
with sims4.callback_utils.invoke_enter_exit_callbacks(
sims4.callback_utils.CallbackEvent.CONTENT_SET_GENERATE_ENTER,
sims4.callback_utils.CallbackEvent.CONTENT_SET_GENERATE_EXIT):
target_to_posture_icon_info = {}
for affordance in si_or_sa.all_affordances_gen(
phase_index=phase_index):
if affordance.is_super:
logger.error(
'Content set contains a super affordance: {} has {}',
si_or_sa, affordance)
targets = _test_affordance_and_get_targets(
affordance,
potential_targets,
sim,
considered=gsi_considered)
if targets is None:
pass
for target in targets:
valid_aops_gen = get_valid_aops_gen(
target,
affordance,
super_affordance,
super_interaction,
context,
include_failed_aops_with_tooltip,
push_super_on_prepare=push_super_on_prepare,
considered=gsi_considered,
aop_kwargs=aop_kwargs)
for (aop, test_result) in valid_aops_gen:
if not aop.affordance.is_super:
aop_show_posture_incompatible_icon = False
if show_posture_incompatible_icon:
aop_show_posture_incompatible_icon = show_posture_incompatible_icon
if target not in target_to_posture_icon_info:
if aop.compatible_with_current_posture_state(
sim):
aop_show_posture_incompatible_icon = False
target_to_posture_icon_info[
target] = aop_show_posture_incompatible_icon
else:
aop_show_posture_incompatible_icon = target_to_posture_icon_info[
target]
aop.show_posture_incompatible_icon = aop_show_posture_incompatible_icon
mixer_weight = aop.affordance.calculate_autonomy_weight(
sim)
else:
mixer_weight = 0
valid[affordance].append(
(mixer_weight, aop, test_result))
if sim.posture.source_interaction is si_or_sa:
for buff in sim.Buffs:
buff_aops = get_buff_aops(sim,
buff,
sim.animation_interaction,
context,
potential_targets=potential_targets,
gsi_considered=gsi_considered)
while buff_aops:
valid.update(buff_aops)
if valid:
return list(
_select_affordances_gen(sim, super_affordance, valid,
show_posture_incompatible_icon,
gsi_considered))
return ()
def get_score(cls, resolver):
yield_to_irq()
return sum(test_pair.score for test_pair in cls._scores
if resolver(test_pair.test))
def generate_content_set(sim,
super_affordance,
super_interaction,
context,
potential_targets=(),
scoring_gsi_handler=None,
include_failed_aops_with_tooltip=False,
push_super_on_prepare=False,
mixer_interaction_group=DEFAULT,
check_posture_compatibility=False,
aop_kwargs=frozendict()):
si_or_sa = super_interaction if super_interaction is not None else super_affordance
if not si_or_sa.has_affordances():
return ()
else:
yield_to_irq()
phase_index = None
if super_interaction:
if not _mixer_name_list:
phase_index = super_interaction.phase_index
valid = collections.defaultdict(list)
if gsi_handlers.content_set_handlers.archiver.enabled:
gsi_considered = {}
else:
gsi_considered = None
if check_posture_compatibility and sim is not None and sim.posture.posture_type != postures.stand.StandSuperInteraction.STAND_POSTURE_TYPE:
show_posture_incompatible_icon = True
else:
show_posture_incompatible_icon = False
if not si_or_sa.is_social or potential_targets:
for_pie_menu = context.source == InteractionContext.SOURCE_PIE_MENU
with sims4.callback_utils.invoke_enter_exit_callbacks(
sims4.callback_utils.CallbackEvent.
CONTENT_SET_GENERATE_ENTER, sims4.callback_utils.
CallbackEvent.CONTENT_SET_GENERATE_EXIT):
target_to_posture_icon_info = {}
for affordance in si_or_sa.all_affordances_gen(
context=context, phase_index=phase_index):
if affordance.is_super:
logger.error(
'Content set contains a super affordance: {} has {}',
si_or_sa, affordance)
if for_pie_menu and not affordance.allow_user_directed:
if gsi_considered is not None:
gsi_considered[affordance] = {
'affordance': str(affordance),
'target': 'Skipped look up',
'test': 'Not allowed user directed'
}
if mixer_interaction_group is not DEFAULT and affordance.sub_action.mixer_group != mixer_interaction_group:
continue
targets = _test_affordance_and_get_targets(
affordance,
super_interaction,
potential_targets,
sim,
considered=gsi_considered)
if targets is None:
continue
if not include_failed_aops_with_tooltip and len(
targets
) >= MINIMUM_TARGETS_TO_TEST_AFFORDANCE_EARLY:
resolver = AffordanceResolver(affordance, sim)
if affordance.test_globals.run_tests(
resolver,
skip_safe_tests=False,
search_for_tooltip=False):
if not affordance.tests.run_tests(
resolver,
skip_safe_tests=False,
search_for_tooltip=False):
continue
if context.source == InteractionContext.SOURCE_AUTONOMY and not affordance.test_autonomous.run_tests(
resolver,
skip_safe_tests=False,
search_for_tooltip=False):
continue
for target in targets:
valid_aops_gen = get_valid_aops_gen(
target,
affordance,
super_affordance,
super_interaction,
context,
include_failed_aops_with_tooltip,
push_super_on_prepare=
push_super_on_prepare,
considered=gsi_considered,
aop_kwargs=aop_kwargs)
for (aop,
test_result) in valid_aops_gen:
if not aop.affordance.is_super:
aop_show_posture_incompatible_icon = False
if show_posture_incompatible_icon:
aop_show_posture_incompatible_icon = show_posture_incompatible_icon
if target not in target_to_posture_icon_info:
if aop.compatible_with_current_posture_state(
sim):
aop_show_posture_incompatible_icon = False
target_to_posture_icon_info[
target] = aop_show_posture_incompatible_icon
else:
aop_show_posture_incompatible_icon = target_to_posture_icon_info[
target]
aop.show_posture_incompatible_icon = aop_show_posture_incompatible_icon
mixer_weight = aop.affordance.calculate_autonomy_weight(
sim)
else:
mixer_weight = 0
valid[affordance].append(
(mixer_weight, aop,
test_result))
else:
for target in targets:
valid_aops_gen = get_valid_aops_gen(
target,
affordance,
super_affordance,
super_interaction,
context,
include_failed_aops_with_tooltip,
push_super_on_prepare=
push_super_on_prepare,
considered=gsi_considered,
aop_kwargs=aop_kwargs)
for (aop, test_result) in valid_aops_gen:
if not aop.affordance.is_super:
aop_show_posture_incompatible_icon = False
if show_posture_incompatible_icon:
aop_show_posture_incompatible_icon = show_posture_incompatible_icon
if target not in target_to_posture_icon_info:
if aop.compatible_with_current_posture_state(
sim):
aop_show_posture_incompatible_icon = False
target_to_posture_icon_info[
target] = aop_show_posture_incompatible_icon
else:
aop_show_posture_incompatible_icon = target_to_posture_icon_info[
target]
aop.show_posture_incompatible_icon = aop_show_posture_incompatible_icon
mixer_weight = aop.affordance.calculate_autonomy_weight(
sim)
else:
mixer_weight = 0
valid[affordance].append(
(mixer_weight, aop, test_result))
else:
if mixer_interaction_group is not DEFAULT and affordance.sub_action.mixer_group != mixer_interaction_group:
continue
targets = _test_affordance_and_get_targets(
affordance,
super_interaction,
potential_targets,
sim,
considered=gsi_considered)
if targets is None:
continue
if not include_failed_aops_with_tooltip and len(
targets
) >= MINIMUM_TARGETS_TO_TEST_AFFORDANCE_EARLY:
resolver = AffordanceResolver(affordance, sim)
if affordance.test_globals.run_tests(
resolver,
skip_safe_tests=False,
search_for_tooltip=False):
if not affordance.tests.run_tests(
resolver,
skip_safe_tests=False,
search_for_tooltip=False):
continue
if context.source == InteractionContext.SOURCE_AUTONOMY and not affordance.test_autonomous.run_tests(
resolver,
skip_safe_tests=False,
search_for_tooltip=False):
continue
for target in targets:
valid_aops_gen = get_valid_aops_gen(
target,
affordance,
super_affordance,
super_interaction,
context,
include_failed_aops_with_tooltip,
push_super_on_prepare=
push_super_on_prepare,
considered=gsi_considered,
aop_kwargs=aop_kwargs)
for (aop, test_result) in valid_aops_gen:
if not aop.affordance.is_super:
aop_show_posture_incompatible_icon = False
if show_posture_incompatible_icon:
aop_show_posture_incompatible_icon = show_posture_incompatible_icon
if target not in target_to_posture_icon_info:
if aop.compatible_with_current_posture_state(
sim):
aop_show_posture_incompatible_icon = False
target_to_posture_icon_info[
target] = aop_show_posture_incompatible_icon
else:
aop_show_posture_incompatible_icon = target_to_posture_icon_info[
target]
aop.show_posture_incompatible_icon = aop_show_posture_incompatible_icon
mixer_weight = aop.affordance.calculate_autonomy_weight(
sim)
else:
mixer_weight = 0
valid[affordance].append(
(mixer_weight, aop, test_result))
else:
for target in targets:
valid_aops_gen = get_valid_aops_gen(
target,
affordance,
super_affordance,
super_interaction,
context,
include_failed_aops_with_tooltip,
push_super_on_prepare=push_super_on_prepare,
considered=gsi_considered,
aop_kwargs=aop_kwargs)
for (aop, test_result) in valid_aops_gen:
if not aop.affordance.is_super:
aop_show_posture_incompatible_icon = False
if show_posture_incompatible_icon:
aop_show_posture_incompatible_icon = show_posture_incompatible_icon
if target not in target_to_posture_icon_info:
if aop.compatible_with_current_posture_state(
sim):
aop_show_posture_incompatible_icon = False
target_to_posture_icon_info[
target] = aop_show_posture_incompatible_icon
else:
aop_show_posture_incompatible_icon = target_to_posture_icon_info[
target]
aop.show_posture_incompatible_icon = aop_show_posture_incompatible_icon
mixer_weight = aop.affordance.calculate_autonomy_weight(
sim)
else:
mixer_weight = 0
valid[affordance].append(
(mixer_weight, aop, test_result))
if valid:
return list(
_select_affordances_gen(sim, super_interaction, valid,
show_posture_incompatible_icon,
gsi_considered, scoring_gsi_handler,
**aop_kwargs))
return ()
