def get_cover_position(squad, member_id):
_member = entities.get_entity(member_id)
_best_coverage = {'position': None, 'score': 0}
_inside = zones.get_active_inside_positions()
if _member['movement']['path']['destination']:
_hide_pos = _member['movement']['path']['destination']
else:
_hide_pos = movement.get_position(_member)
if _hide_pos in squad['position_map_scores']:
_scores = squad['position_map_scores'][_hide_pos]
_score = _scores['coverage'] + _scores['member_coverage']
if not _scores['targets'] and _score > 0:
return _hide_pos
for pos in squad['position_map_scores']:
_scores = squad['position_map_scores'][pos]
#TODO: Add or subtract here? Subtraction will make some NPCs run away from teammates
_score = _scores['coverage'] + _scores['member_coverage']
if not pos in _inside:
continue
if _scores['targets'] or _score <= 0:
continue
if _score > _best_coverage['score']:
_best_coverage['score'] = _score
_best_coverage['position'] = pos[:]
if not _best_coverage['position']:
#print 'no good coverage position'
return
_x, _y = movement.get_position(_member)
for coverage_pos in shapes.circle(_best_coverage['position'][0],
_best_coverage['position'][1], 6):
if not coverage_pos in squad['position_map_scores']:
continue
_c_dist = 10 * (1 - (numbers.distance(coverage_pos, (_x, _y)) / 3.0))
squad['position_map_scores'][coverage_pos][
'member_coverage'] += _c_dist
squad['position_map_scores'][
_best_coverage['position']]['member_coverage'] += 15
return _best_coverage['position']
def get_cover_position(squad, member_id):
_member = entities.get_entity(member_id)
_best_coverage = {'position': None, 'score': 0}
_inside = zones.get_active_inside_positions()
if _member['movement']['path']['destination']:
_hide_pos = _member['movement']['path']['destination']
else:
_hide_pos = movement.get_position(_member)
if _hide_pos in squad['position_map_scores']:
_scores = squad['position_map_scores'][_hide_pos]
_score = _scores['coverage'] + _scores['member_coverage']
if not _scores['targets'] and _score > 0:
return _hide_pos
for pos in squad['position_map_scores']:
_scores = squad['position_map_scores'][pos]
#TODO: Add or subtract here? Subtraction will make some NPCs run away from teammates
_score = _scores['coverage'] + _scores['member_coverage']
if not pos in _inside:
continue
if _scores['targets'] or _score <= 0:
continue
if _score > _best_coverage['score']:
_best_coverage['score'] = _score
_best_coverage['position'] = pos[:]
if not _best_coverage['position']:
#print 'no good coverage position'
return
_x, _y = movement.get_position(_member)
for coverage_pos in shapes.circle(_best_coverage['position'][0], _best_coverage['position'][1], 6):
if not coverage_pos in squad['position_map_scores']:
continue
_c_dist = 10 * (1 - (numbers.distance(coverage_pos, (_x, _y)) / 3.0))
squad['position_map_scores'][coverage_pos]['member_coverage'] += _c_dist
squad['position_map_scores'][_best_coverage['position']]['member_coverage'] += 15
return _best_coverage['position']
def search_for_target(entity):
_lost_targets = entity['ai']['targets_to_search']
_inside = zones.get_active_inside_positions()
if not _lost_targets:
print 'Trying to search with no lost targets'
return
_closest_target = {'distance': 0, 'target_id': None}
for target_id in _lost_targets:
_memory = entity['ai']['life_memory'][target_id]
_distance = numbers.distance(movement.get_position(entity), _memory['last_seen_at'])
if not _closest_target['target_id'] or _distance < _closest_target['distance']:
_closest_target['target_id'] = target_id
_closest_target['distance'] = _distance
_target = entities.get_entity(_closest_target['target_id'])
_solids = zones.get_active_solids(entity)
if flags.has_flag(entity, 'search_nodes'):
_search_for_target(entity, _target['_id'])
return
_x, _y = movement.get_position(entity)
_tx, _ty = entity['ai']['life_memory'][_target['_id']]['last_seen_at']
_nodes_to_search = {}
if entity['ai']['life_memory'][_target['_id']]['last_seen_velocity']:
_vx, _vy = entity['ai']['life_memory'][_target['_id']]['last_seen_velocity']
_tx + _vx*6
_ty + _vy*6
entities.trigger_event(entity, 'set_flag', flag='search_nodes', value=_nodes_to_search)
for node_x, node_y in zones.get_active_node_grid():
_distance = numbers.distance((_tx, _ty), (node_x, node_y))
if _distance >= 30:
continue
if not (node_x, node_y) in _inside:
continue
_continue = False
for pos in shapes.line((_tx, _ty), (node_x, node_y)):
if pos in _solids:
_continue = True
break
if _continue:
continue
if _distance in _nodes_to_search:
if not (node_x, node_y) in _nodes_to_search[_distance]:
_nodes_to_search[_distance].append((node_x, node_y))
else:
_nodes_to_search[_distance] = [(node_x, node_y)]
def search_for_target(entity):
_lost_targets = entity['ai']['targets_to_search']
_inside = zones.get_active_inside_positions()
if not _lost_targets:
print 'Trying to search with no lost targets'
return
_closest_target = {'distance': 0, 'target_id': None}
for target_id in _lost_targets:
_memory = entity['ai']['life_memory'][target_id]
_distance = numbers.distance(movement.get_position(entity),
_memory['last_seen_at'])
if not _closest_target[
'target_id'] or _distance < _closest_target['distance']:
_closest_target['target_id'] = target_id
_closest_target['distance'] = _distance
_target = entities.get_entity(_closest_target['target_id'])
_solids = zones.get_active_solids(entity)
if flags.has_flag(entity, 'search_nodes'):
_search_for_target(entity, _target['_id'])
return
_x, _y = movement.get_position(entity)
_tx, _ty = entity['ai']['life_memory'][_target['_id']]['last_seen_at']
_nodes_to_search = {}
if entity['ai']['life_memory'][_target['_id']]['last_seen_velocity']:
_vx, _vy = entity['ai']['life_memory'][
_target['_id']]['last_seen_velocity']
_tx + _vx * 6
_ty + _vy * 6
entities.trigger_event(entity,
'set_flag',
flag='search_nodes',
value=_nodes_to_search)
for node_x, node_y in zones.get_active_node_grid():
_distance = numbers.distance((_tx, _ty), (node_x, node_y))
if _distance >= 30:
continue
if not (node_x, node_y) in _inside:
continue
_continue = False
for pos in shapes.line((_tx, _ty), (node_x, node_y)):
if pos in _solids:
_continue = True
break
if _continue:
continue
if _distance in _nodes_to_search:
if not (node_x, node_y) in _nodes_to_search[_distance]:
_nodes_to_search[_distance].append((node_x, node_y))
else:
_nodes_to_search[_distance] = [(node_x, node_y)]
