def length(self):
if self._length is None:
length = 0
for i in range(0, len(self.object) - 1, 1):
p1 = self.point_n(i)
p2 = self.point_n(i + 1)
dist = spherical_distance(p1, p2)
length += dist
self._length = length
return self._length
def get_sub_trajectory_keep_end(traj, length):
"""
Cut initial part of traj such that the length is respected.
"""
if length >= traj.length():
return traj
id_sub = traj.id
object_sub = [traj.end_point()]
vehicle_sub = traj.vehicle
tmp_length = 0
for i in range(len(traj) - 1, 0, -1):
p = traj.point_n(i)
q = object_sub[len(object_sub) - 1]
tmp_length += spherical_distance(q, p)
if tmp_length >= length:
break
object_sub.insert(0, p)
sub_trajectory = Trajectory(id=id_sub,
object=object_sub,
vehicle=vehicle_sub)
return sub_trajectory
def calculate_traj_approximation(traj1,
traj2,
pred_thr,
last_prop,
time_mod=86400):
"""
Calculate the approximation between the traejctory and the routine.
"""
res = {
'id_t1': traj1.id,
'id_t2': traj2.id,
'head': None,
'tail': None,
'dist': float('infinity')
}
# lool for the closest point on routine to the last point of traj
t_last = traj1.end_point()
min_dist = float('infinity')
id_min = None
for i in range(0, len(traj2) - 1):
p = traj2.point_n(i)
dist = spherical_distance(p, t_last)
if dist < min_dist:
min_dist = dist
id_min = i
cp = closest_point_on_segment(traj2.point_n(id_min),
traj2.point_n(id_min + 1), t_last)
# calcualte the distance between the two closest points
dist = spherical_distance(cp, t_last)
if last_prop == 0.0 and dist >= pred_thr:
return res
# cut the routine temporally from the beginning of traj to the time of the closest point
t2 = cp[2] / 1000 % time_mod
t1 = traj2.start_point()[2] / 1000 % time_mod
traj2_cut = get_sub_trajectory(traj2, t1, t2)
if traj2_cut is None or len(traj2_cut) < 3:
return res
# if the trajectory is shorter than the routine cut remove the initial part of the routine_cut
if traj1.length() < traj2_cut.length():
traj2_cut = get_sub_trajectory_keep_end(traj2_cut, traj1.length())
# calculate the tail
traj2_head = traj2_cut
traj2_tail = get_sub_trajectory(traj2, t2,
traj2.end_point()[2] / 1000 % time_mod)
if traj2_tail is None:
traj2_tail = Trajectory(id=traj2.id,
object=[traj2.end_point()],
vehicle=traj2.vehicle)
traj2_tail.object.insert(0, traj2_cut.end_point())
if last_prop > 0.0:
last_traj = get_sub_trajectory_keep_end(traj1,
traj1.length() * last_prop)
last_routine_head = get_sub_trajectory_keep_end(
traj2_head,
traj2_head.length() * last_prop)
if len(last_traj) >= 2 and len(last_routine_head) >= 2:
dist = trajectory_distance(last_traj, last_routine_head)
if dist >= pred_thr:
return res
res['head'] = traj2_head
res['tail'] = traj2_tail
res['dist'] = dist
return res
def segment_trajectories(alltraj,
uid,
temporal_thr=120,
spatial_thr=50,
max_speed=0.07):
# temporal_thr = 120 # seconds
# spatial_thr = 50 # meters
# max_speed = 0.07 # km/s
spatial_thr = spatial_thr / 1000
#traj_list = list()
traj_list = dict()
tid = 0
traj = list()
is_a_new_traj = True
p = None
length = 0.0
ref_p = None # for stop detection
first_iteration = True
p_index = 0
next_p_index = 0
ref_p_index = 0
for i in range(0, len(alltraj)):
next_p = alltraj[i]
next_p_index = i
if first_iteration: # first iteration
p = next_p
p_index = next_p_index
ref_p = p # for stop detection
traj = [p]
length = 0.0
is_a_new_traj = True
first_iteration = False
else: # all the others
spatial_dist = spherical_distance(p, next_p)
temporal_dist = next_p[2] - p[2]
ref_distance = spherical_distance(ref_p,
next_p) # for stop detection
ref_time_diff = next_p[2] - ref_p[2] # for stop detection
# Ignore extreme jump (with speed > 250km/h = 0.07km/s)
if ref_distance > max_speed * ref_time_diff:
continue
if temporal_dist > temporal_thr or (ref_time_diff > temporal_thr
and
ref_distance < spatial_thr):
# ended trajectory (includes case with long time gap)
if len(traj) > 1 and not is_a_new_traj:
start_time = traj[0][2]
end_time = traj[-1][2]
duration = end_time - start_time
trajToInsert = Trajectory(id=tid,
object=traj,
vehicle=uid,
length=length,
duration=duration,
start_time=start_time,
end_time=end_time)
#traj_list.append(trajToInsert)
traj_list[tid] = trajToInsert
# Create a new trajectory
traj = [
p[:2] + [next_p[2]]
] # 1st fake point with last position previous traj and new timestamp
p = next_p
p_index = next_p_index
ref_p = p # for stop detection
ref_p_index = p_index
traj.append(p)
length = 0.0
tid += 1
is_a_new_traj = True
else:
if is_a_new_traj and len(traj) > 1:
traj[1] = [
traj[1][0], traj[1][1], traj[0][2] + int(
(next_p[2] - traj[0][2]) / 2)
]
is_a_new_traj = False
p = next_p
p_index = next_p_index
if ref_distance > spatial_thr:
ref_p = p # for stop detection
ref_p_index = p_index
traj.append(p)
length += spatial_dist
if len(traj) > 1 and not is_a_new_traj:
start_time = traj[0][2]
end_time = traj[-1][2]
duration = end_time - start_time
trajToInsert = Trajectory(id=tid,
object=traj,
vehicle=uid,
length=length,
duration=duration,
start_time=start_time,
end_time=end_time)
#traj_list.append(trajToInsert)
traj_list[tid] = trajToInsert
return traj_list
def segment_trajectories_random(alltraj,
uid,
nbr_traj_min=None,
nbr_traj_max=None,
nbr_traj=None):
nbr_traj_min = 2 if nbr_traj_min is None else nbr_traj_min
nbr_traj_max = int(len(alltraj) /
2) if nbr_traj_max is None else nbr_traj_max
nbr_traj = np.random.randint(nbr_traj_min, nbr_traj_max +
1) if nbr_traj is None else nbr_traj
new_traj_marker = int(len(alltraj) / nbr_traj)
traj_list = list()
tid = 0
traj = list()
is_a_new_traj = True
p = None
first_iteration = True
length = 0.0
for i in range(0, len(alltraj)):
next_p = alltraj[i]
if first_iteration: # first iteration
p = next_p
traj = [p]
length = 0.0
is_a_new_traj = True
first_iteration = False
else: # all the others
spatial_dist = spherical_distance(p, next_p)
if i % new_traj_marker == 0:
if len(traj) > 1 and not is_a_new_traj:
start_time = traj[0][2]
end_time = traj[-1][2]
duration = end_time - start_time
traj_list.append(
Trajectory(id=tid,
object=traj,
vehicle=uid,
length=length,
duration=duration,
start_time=start_time,
end_time=end_time))
# Create a new trajectory
p = next_p
traj = [p]
length = 0.0
tid += 1
is_a_new_traj = True
else:
is_a_new_traj = False
p = next_p
traj.append(p)
length += spatial_dist
if len(traj) > 1 and not is_a_new_traj:
start_time = traj[0][2]
end_time = traj[-1][2]
duration = end_time - start_time
traj_list.append(
Trajectory(id=tid,
object=traj,
vehicle=uid,
length=length,
duration=duration,
start_time=start_time,
end_time=end_time))
return traj_list