def __init__(self, binary): GraphBuilder.__init__(self, binary) # for func in self.external_functions.values(): # func.visualize_function() self.__label_function_boundaries() self.__create_internal_functions() self.__reduce_functions() for func in self.get_all_functions(): self.__lift_function(func)
def get_local_rrt_search_space(current_position, horizon=300):
current_position = tuple((np.array(current_position) - offset[:len(current_position)]).astype(float))
print("Creating local ss", current_position)
gb = GraphBuilder(np.array(current_position[:2])-horizon, np.array(current_position[:2])+horizon, polygons, collision_tree=collision_tree)
print('Creating RRT graph')
graph = gb.create_rrt_graph(current_position, num_vertices=300, dt=5)
print('Created RRT graph')
#all_nodes = np.array(list(graph.nodes))
#min_values = np.amin(all_nodes, axis=0)
#max_values = np.amax(all_nodes, axis=0)
search_space = GraphSearchSpace(graph, offset=offset_2D)
print('Created search space')
return search_space
def __init__(self, binary):
"""
Lift初始化
:param binary:
"""
logging.info("链接器初始化")
GraphBuilder.__init__(self, binary) # 图构建器
# for func in self.external_functions.values():
# func.visualize_function()
self.__label_function_boundaries()
self.__create_internal_functions()
self.__reduce_functions()
for func in self.get_all_functions():
self.__lift_function(func)
def test_graph(self):
graphbuilder = GraphBuilder(self.ids, self.edges)
subgraphs = graphbuilder.subgraphs
#test we get back 2 subgroups
self.assertEqual(len(subgraphs), 2)
#test the subgroups are the right sizes
sortedsubgraphs = sorted(subgraphs, key=lambda x: len(x))
self.assertEqual(len(sortedsubgraphs[1]), 4)
def execute(self, params, content):
"""
Запустить команду на выполнение.
Метод возвращает текст, который будет вставлен на место команды в вики-нотации
"""
params_dict = self.parseGraphParams(params)
graph = GraphBuilder(params_dict, content, self.parser.page).graph
render = self._getRender(graph)
return render.addGraph(graph)
def create_search_space(search_space_type: SearchSpaceType, search_altitude: float, safety_distance=np.array([5, 5, 0])):
"""search_altitude: only for 2D search space"""
print('Creating search space')
# Read in obstacle map
data = np.loadtxt('colliders.csv', delimiter=',', dtype='Float64', skiprows=2)
# read lat0, lon0 from colliders into floating point values
with open('colliders.csv') as f:
origin_pos_data = f.readline().split(',')
lat0 = float(origin_pos_data[0].strip().split(' ')[1])
lon0 = float(origin_pos_data[1].strip().split(' ')[1])
home = (lon0, lat0, 0)
# Define a grid for a particular altitude and safety margin around obstacles
polygons, min_bounds = extract_polyheights(data, safety_distance=safety_distance)
north_offset, east_offset = min_bounds[:2].astype(int)
print("North offset = {0}, east offset = {1}".format(north_offset, east_offset))
offset = np.array([north_offset, east_offset, 0])
offset_2D = offset[:2] # 2D map
if search_space_type == SearchSpaceType.SKELETON:
grid_builder = GridBuilder(polygons)
prune_grid = grid_builder.create_grid_2D(altitude=search_altitude)
skel_grid = grid_builder.create_grid_skeleton(altitude=search_altitude)
search_space = GridGridSearchSpace(skel_grid, prune_grid, offset=offset_2D)
#search_space = GridSearchSpace(grid, offset=offset_2D)
elif search_space_type == SearchSpaceType.GRID_25D:
grid = GridBuilder(polygons).create_grid_25D()
search_space = GridSearchSpace(grid, offset=offset)
elif search_space_type == SearchSpaceType.GRID_2D:
grid = GridBuilder(polygons).create_grid_2D(altitude=search_altitude)
search_space = GridSearchSpace(grid, offset=offset_2D)
elif search_space_type == SearchSpaceType.RECEDING_HORIZON_RRT:
# Very very naive rough path that just goes in a straight line
get_rough_path = lambda s, g: [s, g]
collision_tree = CollisionTree(polygons)
def get_local_rrt_search_space(current_position, horizon=300):
current_position = tuple((np.array(current_position) - offset[:len(current_position)]).astype(float))
print("Creating local ss", current_position)
gb = GraphBuilder(np.array(current_position[:2])-horizon, np.array(current_position[:2])+horizon, polygons, collision_tree=collision_tree)
print('Creating RRT graph')
graph = gb.create_rrt_graph(current_position, num_vertices=300, dt=5)
print('Created RRT graph')
#all_nodes = np.array(list(graph.nodes))
#min_values = np.amin(all_nodes, axis=0)
#max_values = np.amax(all_nodes, axis=0)
search_space = GraphSearchSpace(graph, offset=offset_2D)
print('Created search space')
return search_space
search_space = RecedingHorizonSearchSpace(get_local_rrt_search_space, get_rough_path)
elif search_space_type == SearchSpaceType.VORONOI:
graph_builder = GraphBuilder(np.array([0, 0, 0]), np.array([926, 926, 220]), polygons)
graph = graph_builder.create_voronoi_graph(drone_altitude=search_altitude)
search_space = GraphSearchSpace(graph, offset=offset_2D)
elif search_space_type == SearchSpaceType.VORONOI_WITH_PRUNING:
graph_builder = GraphBuilder(np.array([0, 0, 0]), np.array([926, 926, 220]), polygons)
graph = graph_builder.create_voronoi_graph(drone_altitude=search_altitude)
grid = GridBuilder(polygons).create_grid_25D()
search_space = GraphGridSearchSpace(graph, grid, offset=offset)
elif search_space_type == SearchSpaceType.RANDOM_SAMPLING_2D:
graph_builder = GraphBuilder(np.array([0, 0, 0]), np.array([926, 926, 220]), polygons)
graph = graph_builder.create_sample_graph(n_samples=500, n_d=2, k=10)
search_space = GraphSearchSpace(graph, offset=offset_2D)
elif search_space_type == SearchSpaceType.RANDOM_SAMPLING_3D:
graph_builder = GraphBuilder(np.array([0, 0, 0]), np.array([926, 926, 220]), polygons)
graph = graph_builder.create_sample_graph(n_samples=1000, n_d=3, k=10)
search_space = GraphSearchSpace(graph, offset=offset)
else:
raise ValueError(f"Unknown search space type {search_space_type}")
print('Search space created')
return search_space, home