def __init__(self, scenario_file, perturb=False, gravity_dir=(-1,-1)):
self.perturb = perturb
self.gravity_dir = gravity_dir
# create scenario
self.width, self.height, self.immobile_objs, self.mobile_objs, self.manipulatable_obj, self.target_obj = loadScenario(
scenario_file)
self.scenario_file = scenario_file
print 'solving scenario: ', scenario_file
print 'gravity internal sim: ', gravity_dir
self.evalReal = EvaluateQualiSol(scenario_file, gravity_dir)
#self.evalReal = EvaluateQualiSol('./scenarios/mini2.json')
#self.evalReal = EvaluateQualiSol('./scenarios/s2.json')
self.objs_map = {}
self.obj_min_angle_difference = {}
self.first_real_sol = -1
for obj in self.immobile_objs:
if perturb:
perturb_obj(obj)
self.objs_map[obj['id']] = obj
#self.obj_min_angle_difference[obj['id']] = [100,100]
self.obj_min_angle_difference[obj['id']] = [100, 0]
if perturb:
sps(scenario_file, 5, self.immobile_objs)
self.target_obj_id = self.target_obj['id']
self.maxd = 3
self.scenario = None
self.qualitative_paths = {}
self.qualitative_paths_actions = {}
self.zones = []
self.simulation_counter = 0
self.round = 0
quali_sim = qualitative_simulation(scenario_file)
self.estimated_qualitative_paths = quali_sim.run()
self.initial_zone = quali_sim.initial_zone
self.graph = quali_sim.graph
self.zones = quali_sim.zones
self.zone_dic = {}
self.zone_distance = {}
for x in xrange(self.width):
for y in xrange(self.height):
self.zone_dic[(x, y)] = self.__find_zones(x, y)
for i in xrange(len(self.zones) - 1):
self.zone_distance[(i, i)] = 0
for j in xrange(i + 1, len(self.zones)):
distance = self.zones[i].distance(self.zones[j])
self.zone_distance[(i, j)] = distance
self.zone_distance[(j, i)] = distance
self.zone_distance[(len(self.zones) - 1, len(self.zones) - 1)] = 0
def __init__(self, scenario_file, gravity_dir=(-1, -1)):
# self.evalPath = EVAL(scenario_file)
self.gravity_dir = gravity_dir
self.evalPath = EVAL(scenario_file, gravity_dir=gravity_dir)
# create scenario
self.sigma = -0.0001
self.width, self.height, self.immobile_objs, self.mobile_objs, self.manipulatable_obj, self.target_obj = loadScenario(
scenario_file
)
self.target_obj_id = self.target_obj["id"]
self.maxd = 3
self.qualitative_paths = {}
self.qualitative_paths_actions = {}
self.zones = []
self.simulation_counter = 0
quali_sim = qualitative_simulation(scenario_file)
self.estimated_qualitative_paths = quali_sim.run()
self.initial_zone = quali_sim.initial_zone
self.graph = quali_sim.graph
self.zones = quali_sim.zones
self.zone_dic = {}
self.zone_distance = {}
for x in xrange(self.width):
for y in xrange(self.height):
self.zone_dic[(x, y)] = self.__find_zones(x, y)
for i in xrange(len(self.zones) - 1):
self.zone_distance[(i, i)] = 0
for j in xrange(i + 1, len(self.zones)):
distance = self.zones[i].distance(self.zones[j])
self.zone_distance[(i, j)] = distance
self.zone_distance[(j, i)] = distance
self.zone_distance[(len(self.zones) - 1, len(self.zones) - 1)] = 0
