def test():
probes, links = read_data()
link_points, belong = flatten_uniq(links)
print "%d probe points loaded" % len(probes)
print "%d link points loaded" % len(link_points)
probes = np.array(random.sample(probes, 100))
# print probes
link_points = np.array(link_points)
probes_rad = np.deg2rad(probes)
link_points_rad = np.deg2rad(link_points)
knns_kd = evaluate(
lambda: nearest_kdtree(
probes_rad, link_points_rad, n=30, is_filter=True), "kdtree")
knns_force = evaluate(
lambda: nearest_force(probes_rad, link_points_rad, n=30),
"brute force")
for idx, (k1, k2) in enumerate(izip(knns_kd, knns_force)):
diff = np.setdiff1d(k2, k1)
if diff.size > 0:
print diff
print probes[idx]
print link_points[diff]
print haversine_np(probes_rad[idx], link_points_rad[diff])
def probe_to_link_dist(link_points, probe):
link_points_rad = np.deg2rad(link_points)
probe_rad = np.deg2rad(probe)
#底边
base_side = haversine_np(link_points_rad[:-1,:], link_points_rad[1:,:])
#腰
tmp = haversine_np(probe_rad, link_points_rad)
side1 = tmp[:-1]
side2 = tmp[1:]
link_dis = calc_link_dis(base_side, side1, side2)
return np.min(link_dis)
def probe_to_link_dist(link_points, probe):
link_points_rad = np.deg2rad(link_points)
probe_rad = np.deg2rad(probe)
#底边
base_side = haversine_np(link_points_rad[:-1, :], link_points_rad[1:, :])
#腰
tmp = haversine_np(probe_rad, link_points_rad)
side1 = tmp[:-1]
side2 = tmp[1:]
link_dis = calc_link_dis(base_side, side1, side2)
return np.min(link_dis)
def calc_road_vec(probe, link_points):
link_points_rad = np.deg2rad(link_points)
probe_rad = np.deg2rad(probe)
base_side = haversine_np(link_points_rad[:-1,:], link_points_rad[1:,:])
tmp = haversine_np(probe_rad, link_points_rad)
side1 = tmp[:-1]
side2 = tmp[1:]
link_dis = calc_link_dis(base_side, side1, side2)
min_idx = np.argmin(link_dis)
road_vec = np.array(link_points[min_idx + 1]) - np.array(link_points[min_idx])
return road_vec
def calc_road_vec(probe, link_points):
link_points_rad = np.deg2rad(link_points)
probe_rad = np.deg2rad(probe)
base_side = haversine_np(link_points_rad[:-1, :], link_points_rad[1:, :])
tmp = haversine_np(probe_rad, link_points_rad)
side1 = tmp[:-1]
side2 = tmp[1:]
link_dis = calc_link_dis(base_side, side1, side2)
min_idx = np.argmin(link_dis)
road_vec = np.array(link_points[min_idx + 1]) - np.array(
link_points[min_idx])
return road_vec
def dis_ref_nonref(probe, link_points, nearest_dis, link_len):
link_points_rad = np.deg2rad(link_points)
probe_rad = np.deg2rad(probe)
base_side = haversine_np(link_points_rad[:-1, :], link_points_rad[1:, :])
tmp = haversine_np(probe_rad, link_points_rad)
side1 = tmp[:-1]
side2 = tmp[1:]
link_dis = calc_link_dis(base_side, side1, side2)
min_idx = np.argmin(link_dis)
proj_len = calc_proj_len(base_side[min_idx], side1[min_idx], side2[min_idx])
dis_ref = np.sum(base_side[:min_idx]) + proj_len
dis_ref = dis_ref / np.sum(base_side) * link_len
dis_nonref = link_len - dis_ref
return dis_ref, dis_nonref
def dis_ref_nonref(probe, link_points, nearest_dis, link_len):
link_points_rad = np.deg2rad(link_points)
probe_rad = np.deg2rad(probe)
base_side = haversine_np(link_points_rad[:-1,:], link_points_rad[1:,:])
tmp = haversine_np(probe_rad, link_points_rad)
side1 = tmp[:-1]
side2 = tmp[1:]
link_dis = calc_link_dis(base_side, side1, side2)
min_idx = np.argmin(link_dis)
proj_len = calc_proj_len(base_side[min_idx], side1[min_idx], side2[min_idx])
dis_ref = np.sum(base_side[:min_idx]) + proj_len
dis_ref = dis_ref / np.sum(base_side) * link_len
dis_nonref = link_len - dis_ref
return dis_ref, dis_nonref
def test():
probes, links = read_data()
link_points, belong = flatten_uniq(links)
print "%d probe points loaded" % len(probes)
print "%d link points loaded" % len(link_points)
probes = np.array(random.sample(probes, 100))
# print probes
link_points = np.array(link_points)
probes_rad = np.deg2rad(probes)
link_points_rad = np.deg2rad(link_points)
knns_kd = evaluate(lambda: nearest_kdtree(probes_rad, link_points_rad, n=30, is_filter=True), "kdtree")
knns_force = evaluate(lambda: nearest_force(probes_rad, link_points_rad, n=30), "brute force")
for idx, (k1, k2) in enumerate(izip(knns_kd, knns_force)):
diff = np.setdiff1d(k2, k1)
if diff.size > 0:
print diff
print probes[idx]
print link_points[diff]
print haversine_np(probes_rad[idx], link_points_rad[diff])
def compute_traj_diff_time_distance(traj=None):
"""Compute the sampling time and the coordinate distance."""
# Compute the time difference
time_diff_array = (traj["time"].iloc[1:].reset_index(drop=True) - traj[
"time"].iloc[:-1].reset_index(drop=True)).dt.total_seconds() / 60
# dist_array = np.sqrt(np.diff(traj[x].values)**2 + np.diff(traj[y].values)**2)
# Compute the coordinate distance
dist_diff_array = haversine_np(traj["lon"].values[1:], # lon_0
traj["lat"].values[1:], # lat_0
traj["lon"].values[:-1], # lon_1
traj["lat"].values[:-1] # lat_1
)
# Filling the fake values
time_diff_array = [0.5] + time_diff_array.tolist()
dist_diff_array = [0.5] + dist_diff_array.tolist()
traj["time_array"] = time_diff_array
traj["dist_array"] = dist_diff_array
return traj
def nearest_probe_force(probe, link_points, n):
distance = haversine_np(probe, link_points)
knns = np.argsort(distance)[:n]
# print distance[knns]
return knns
def nearest_probe_force(probe, link_points, n):
distance = haversine_np(probe, link_points)
knns = np.argsort(distance)[:n]
# print distance[knns]
return knns
