def generate_speed_data(traj_dir, grid_idx, feature_path):
MIN_DISTANCE_IN_METER = 5
MAX_DISTANCE_IN_METER = 300
speed_data = np.zeros((grid_idx.row_num, grid_idx.col_num, 1), dtype=np.float)
cnt_data = np.zeros((grid_idx.row_num, grid_idx.col_num, 1), dtype=np.float)
for filename in tqdm(os.listdir(traj_dir)):
if not filename.endswith('.txt'):
continue
traj_list = parse_traj_file(os.path.join(traj_dir, filename))
for traj in traj_list:
for i in range(len(traj.pt_list) - 1):
cur_pt, next_pt = traj.pt_list[i], traj.pt_list[i + 1]
delta_time = (next_pt.time - cur_pt.time).total_seconds()
if MIN_DISTANCE_IN_METER < distance(cur_pt, next_pt) < MAX_DISTANCE_IN_METER:
try:
row_idx, col_idx = grid_idx.get_matrix_idx(cur_pt.lat, cur_pt.lng)
speed = distance(next_pt, cur_pt) / delta_time
# 120 km/h
if speed > 34:
continue
speed_data[row_idx, col_idx, 0] += speed
cnt_data[row_idx, col_idx, 0] += 1
except IndexError:
continue
speed_data = np.divide(speed_data, cnt_data, out=np.zeros_like(speed_data), where=cnt_data != 0)
np.save(os.path.join(feature_path, 'speed.npy'), speed_data)
def remove_similar_links(self, rn, edge_virtual_links):
new_edge_virtual_links = copy.copy(edge_virtual_links)
o = edge_virtual_links[0].end_node
stable = False
while not stable:
stable = True
for i in range(len(new_edge_virtual_links) - 1):
link_a = new_edge_virtual_links[i]
a = cal_loc_along_line(rn.edges[link_a.target_segment]['coords'][link_a.split_edge_idx],
rn.edges[link_a.target_segment]['coords'][link_a.split_edge_idx + 1],
link_a.split_edge_offset)
for j in range(i + 1, len(new_edge_virtual_links)):
link_b = new_edge_virtual_links[j]
b = cal_loc_along_line(rn.edges[link_b.target_segment]['coords'][link_b.split_edge_idx],
rn.edges[link_b.target_segment]['coords'][link_b.split_edge_idx + 1],
link_b.split_edge_offset)
# if small angle
if angle(o, a, o, b) < self.SIMILAR_DIRECTION_THRESHOLD:
# delete longer edge
if distance(o, a) < distance(o, b):
new_edge_virtual_links.remove(new_edge_virtual_links[j])
else:
new_edge_virtual_links.remove(new_edge_virtual_links[i])
stable = False
break
if not stable:
break
return new_edge_virtual_links
def generate_transition_view(traj_dir, grid_idx, nbhd_size, nbhd_dist, feature_path):
MIN_DISTANCE_IN_METER = 5
MAX_DISTANCE_IN_METER = 300
meters_per_grid = grid_idx.lat_interval / LAT_PER_METER
radius = int(nbhd_dist / meters_per_grid)
transit_data = np.zeros((grid_idx.row_num, grid_idx.col_num, nbhd_size, nbhd_size, 2),
dtype=np.uint8)
for filename in tqdm(os.listdir(traj_dir)):
if not filename.endswith('.txt'):
continue
traj_list = parse_traj_file(os.path.join(traj_dir, filename))
for traj in traj_list:
for idx in range(len(traj.pt_list) - 1):
cur_pt = traj.pt_list[idx]
next_pt = traj.pt_list[idx + 1]
if MIN_DISTANCE_IN_METER < distance(cur_pt, next_pt) < MAX_DISTANCE_IN_METER:
try:
global_cur_i, global_cur_j = grid_idx.get_matrix_idx(cur_pt.lat, cur_pt.lng)
local_idx = get_local_idx(global_cur_i, global_cur_j, radius, grid_idx, nbhd_dist)
local_next_i, local_next_j = local_idx.get_matrix_idx(next_pt.lat, next_pt.lng)
transit_data[global_cur_i, global_cur_j, local_next_i, local_next_j, 0] = 1
global_next_i, global_next_j = grid_idx.get_matrix_idx(next_pt.lat, next_pt.lng)
local_idx = get_local_idx(global_next_i, global_next_j, radius, grid_idx, nbhd_dist)
local_cur_i, local_cur_j = local_idx.get_matrix_idx(cur_pt.lat, cur_pt.lng)
transit_data[global_next_i, global_next_j, local_cur_i, local_cur_j, 1] = 1
except IndexError:
continue
np.save(os.path.join(feature_path, 'transition.npy'), transit_data)
def generate_line_image(traj_dir, grid_idx, feature_path):
MIN_DISTANCE_IN_METER = 5
MAX_DISTANCE_IN_METER = 300
traj_line_img = np.zeros((grid_idx.row_num, grid_idx.col_num),
dtype=np.uint8)
for filename in tqdm(os.listdir(traj_dir)):
if not filename.endswith('.txt'):
continue
traj_list = parse_traj_file(os.path.join(traj_dir, filename))
for traj in traj_list:
one_traj_line_img = np.zeros((grid_idx.row_num, grid_idx.col_num),
dtype=np.uint8)
for j in range(len(traj.pt_list) - 1):
cur_pt, next_pt = traj.pt_list[j], traj.pt_list[j + 1]
if MIN_DISTANCE_IN_METER < distance(
cur_pt, next_pt) < MAX_DISTANCE_IN_METER:
try:
y1, x1 = grid_idx.get_matrix_idx(
cur_pt.lat, cur_pt.lng)
y2, x2 = grid_idx.get_matrix_idx(
next_pt.lat, next_pt.lng)
cv2.line(one_traj_line_img, (x1, y1), (x2, y2),
16,
1,
lineType=cv2.LINE_AA)
except IndexError:
continue
traj_line_img = cv2.add(traj_line_img, one_traj_line_img)
cv2.imwrite(os.path.join(feature_path, 'line.png'), traj_line_img)
def extension_intersection(self, o, f, target_coords):
min_dist = float('inf')
split_edge_idx = float('inf')
split_edge_offset = float('inf')
# check whether internal edge has intersection (if multiple intersections, select the shortest)
for i in range(0, len(target_coords) - 1):
a = target_coords[i]
b = target_coords[i + 1]
result = line_ray_intersection_test(o, f, a, b)
if result is None or result[0] < 0 or result[0] > 1:
continue
else:
dist_tmp = distance(o, result[1])
if dist_tmp < self.radius and dist_tmp < min_dist:
nearest_node_with_offset = (target_coords[i], 0.0) if result[0] < 0.5 else \
(target_coords[i + 1], 1.0)
min_dist = dist_tmp
split_edge_idx = i
# prefer link to existing nodes if too short
if distance(nearest_node_with_offset[0], result[1]) < self.NO_NEW_VERTEX_OFFSET:
split_edge_offset = nearest_node_with_offset[1]
else:
split_edge_offset = result[0]
# doesn't have internal intersection, check whether has smooth transition
if split_edge_idx == float('inf'):
# check start node
tmp_dist = distance(target_coords[0], o)
if tmp_dist < self.radius and \
angle_between((o.lng - f.lng, o.lat - f.lat),
(target_coords[0].lng - o.lng, target_coords[0].lat - o.lat)) <= 0.5 * np.pi:
min_dist = tmp_dist
split_edge_idx = 0
split_edge_offset = 0.0
# check end node
tmp_dist = distance(target_coords[-1], o)
if tmp_dist < self.radius and \
angle_between((o.lng - f.lng, o.lat - f.lat),
(target_coords[-1].lng - o.lng, target_coords[-1].lat - o.lat)) <= 0.5 * np.pi:
if tmp_dist < min_dist:
split_edge_idx = len(target_coords) - 2
split_edge_offset = 1.0
return split_edge_idx, split_edge_offset
def perpendicular_intersection(self, o, target_coords, rn, opposite_of_o, target_segment):
split_edge_idx = float('inf')
split_edge_offset = float('inf')
o_min_dist, o_split_edge_idx, o_split_edge_offset = self.cal_projection(o, target_coords)
other_min_dist, other_split_edge_idx, other_split_edge_offset = self.cal_projection(opposite_of_o,
target_coords)
if o_min_dist < other_min_dist:
split_edge_idx = o_split_edge_idx
split_edge_offset = o_split_edge_offset
# no internal intersection
if split_edge_idx == float('inf'):
# the target segment is also a short isolated one
if rn.edges[target_segment]['length'] < self.NO_NEW_VERTEX_OFFSET and \
rn.degree(target_segment[0]) == 1 and rn.degree(target_segment[1]) == 1:
a = SPoint(target_segment[0][1], target_segment[0][0])
b = SPoint(target_segment[1][1], target_segment[1][0])
dead_end_to_target_dist = min(distance(o, a), distance(o, b))
opposite_to_target_dist = min(distance(opposite_of_o, a), distance(opposite_of_o, b))
# current dead end is shorter to the target than opposite, link with the nearest vertex
if dead_end_to_target_dist < opposite_to_target_dist and dead_end_to_target_dist < self.radius:
target = a if distance(o, a) < distance(o, b) else b
if target == target_coords[0]:
split_edge_idx = 0
split_edge_offset = 0.0
else:
split_edge_idx = len(target_coords) - 2
split_edge_offset = 1.0
return split_edge_idx, split_edge_offset
def generate_dir_dist_data(traj_dir, grid_idx, feature_path):
MIN_DISTANCE_IN_METER = 5
MAX_DISTANCE_IN_METER = 300
dir_data = np.zeros((grid_idx.row_num, grid_idx.col_num, 8), dtype=np.uint8)
for filename in tqdm(os.listdir(traj_dir)):
if not filename.endswith('.txt'):
continue
traj_list = parse_traj_file(os.path.join(traj_dir, filename))
for traj in traj_list:
for i in range(len(traj.pt_list) - 1):
cur_pt, next_pt = traj.pt_list[i], traj.pt_list[i + 1]
if MIN_DISTANCE_IN_METER < distance(cur_pt, next_pt) < MAX_DISTANCE_IN_METER:
try:
row_idx, col_idx = grid_idx.get_matrix_idx(cur_pt.lat, cur_pt.lng)
direction = int(((bearing(cur_pt, next_pt) + 22.5) % 360) // 45)
dir_data[row_idx, col_idx, direction] += 1
except IndexError:
continue
np.save(os.path.join(feature_path, 'direction.npy'), dir_data)
def update_link(self, linked_rn, from_pt, to_pt, coords, avail_eid):
"""
make sure two link will not have too similar direction
"""
is_valid = True
link_dist = distance(from_pt, to_pt)
# if the new edge is shorter, add new edge and delete old edge
# check from pt
links_with_from = [edge for edge in list(linked_rn.edges((from_pt.lng, from_pt.lat))) if
linked_rn.edges[edge]['type'] == 'virtual']
edges_to_delete = []
for u, v in links_with_from:
other_node = v if u[0] == from_pt.lng and u[1] == from_pt.lat else u
ang = angle(from_pt, to_pt, from_pt, SPoint(other_node[1], other_node[0]))
if ang < self.SIMILAR_DIRECTION_THRESHOLD:
if link_dist >= linked_rn[u][v]['length']:
is_valid = False
break
else:
edges_to_delete.append((u, v))
# check to pt
links_with_to = [edge for edge in list(linked_rn.edges((to_pt.lng, to_pt.lat))) if
linked_rn.edges[edge]['type'] == 'virtual']
for u, v in links_with_to:
other_node = v if u[0] == to_pt.lng and u[1] == to_pt.lat else u
ang = angle(to_pt, from_pt, to_pt, SPoint(other_node[1], other_node[0]))
if ang < self.SIMILAR_DIRECTION_THRESHOLD:
if link_dist >= linked_rn[u][v]['length']:
is_valid = False
break
else:
edges_to_delete.append((u, v))
if is_valid:
linked_rn.add_edge((from_pt.lng, from_pt.lat), (to_pt.lng, to_pt.lat), coords=coords, eid=avail_eid,
type='virtual')
for u, v in edges_to_delete:
if linked_rn.has_edge(u, v):
# didn't destroy the connectivity
if linked_rn.degree(u) == 2 or linked_rn.degree(v) == 2:
continue
linked_rn.remove_edge(u, v)
def is_valid(self, coords):
dist = 0.0
for i in range(len(coords) - 1):
dist += distance(coords[i], coords[i + 1])
return dist > self.min_road_dist
