def Frechet(R1,R2,varargin=None):
# get path point length
L1=len(R1);
L2=len(R2);
frechet1=np.zeros((L1,L2))
# print(frechet1)
# calculate frechet distance matrix
for i in range(L1):
for j in range(L2):
# frechet1[i,j]=math.sqrt(math.pow(R1[i][0]-R2[j][0],2)+math.pow(R1[i][1]-R2[j][1],2))
frechet1[i,j]=calDistance(R1[i],R2[j])
fmin=frechet1.min();
fmax=frechet1.max();
# print(fmin)
# print(fmax)
# handle resolution
if varargin==None:
varargin=1000
# print(frechet1<=3)
# print(varargin)
# compute frechet distance
# print(np.linspace(fmin,fmax,varargin))
for q3 in np.linspace(fmin,fmax,varargin):
# print(q3)
im1=np.asarray(measurements.label(frechet1<=q3))[0]
# print(im1.shape)
# print(im1[-1,-1])
# get region number of beginning and end points
if im1[0,0]!=0 and im1[0,0]==im1[-1,-1]:
f=q3
break
return f
def lcs(a, b, radiusBound):
lengths = [[0 for j in range(len(b) + 1)] for i in range(len(a) + 1)]
# row 0 and column 0 are initialized to 0 already
for i, x in enumerate(a):
for j, y in enumerate(b):
if calDistance(x, y) <= radiusBound:
lengths[i + 1][j + 1] = lengths[i][j] + 1
else:
lengths[i+1][j+1] = \
max(lengths[i+1][j], lengths[i][j+1])
# read the substring out from the matrix
# result = []
# x, y = len(a), len(b)
# while x != 0 and y != 0:
# print('aa')
# if lengths[x][y] == lengths[x-1][y]:
# x -= 1
# elif lengths[x][y] == lengths[x][y-1]:
# y -= 1
# else:
# assert calDistance(a[x-1],b[y-1])<=radiusBound
# result.append(a[x-1])
# x -= 1
# y -= 1
# print(result)
return lengths[-1][-1]
def find_near(lst, pnt, radius):
near = []
for i in range(len(lst)):
# print(calDistance(lst[i],pnt))
if calDistance(lst[i], pnt) < radius:
near.append(i)
return near
def lcs(a, b,radiusBound):
lengths = [[0 for j in range(len(b)+1)] for i in range(len(a)+1)]
# row 0 and column 0 are initialized to 0 already
for i, x in enumerate(a):
for j, y in enumerate(b):
if calDistance(x,y)<=radiusBound:
lengths[i+1][j+1] = lengths[i][j] + 1
else:
lengths[i+1][j+1] = \
max(lengths[i+1][j], lengths[i][j+1])
# read the substring out from the matrix
# result = []
# x, y = len(a), len(b)
# while x != 0 and y != 0:
# print('aa')
# if lengths[x][y] == lengths[x-1][y]:
# x -= 1
# elif lengths[x][y] == lengths[x][y-1]:
# y -= 1
# else:
# assert calDistance(a[x-1],b[y-1])<=radiusBound
# result.append(a[x-1])
# x -= 1
# y -= 1
# print(result)
return lengths[-1][-1]
def max_Distance(points):
# 'track_points':[{'track_location':{'type':'Point', 'coordinates':[point["lat"],point["lon"]]}, 'time':point["time"]}for point in seg_act_note["trackPoints"]] if "trackPoints" in seg_act_note else []}
num_pts=len(points)
max_d=0
for i in range(num_pts):
for j in range(i+1,num_pts):
max_d=max(max_d,calDistance(points[i]['track_location']['coordinates'], points[j]['track_location']['coordinates']))
return max_d
def calSpeed(trackpoint1, trackpoint2):
from dateutil import parser
distanceDelta = calDistance(trackpoint1['track_location']['coordinates'],
trackpoint2['track_location']['coordinates'])
timeDelta = parser.parse(trackpoint2['time']) - parser.parse(trackpoint1['time'])
logging.debug("while calculating speed form %s -> %s, distanceDelta = %s, timeDelta = %s" %
(trackpoint1, trackpoint2, distanceDelta, timeDelta))
if timeDelta.total_seconds() != 0:
return distanceDelta / timeDelta.total_seconds()
else:
return None
def find_nearest(lst, pnt):
nearest = lst[0]
dis = 99999999
for i in range(len(lst)):
# print(calDistance(lst[i],pnt))
new_dis = calDistance(lst[i], pnt)
if new_dis < dis:
dis = new_dis
nearest = lst[i]
print(dis)
return nearest
def max_Distance(points):
# 'track_points':[{'track_location':{'type':'Point', 'coordinates':[point["lat"],point["lon"]]}, 'time':point["time"]}for point in seg_act_note["trackPoints"]] if "trackPoints" in seg_act_note else []}
num_pts = len(points)
max_d = 0
for i in range(num_pts):
for j in range(i + 1, num_pts):
max_d = max(
max_d,
calDistance(points[i]['track_location']['coordinates'],
points[j]['track_location']['coordinates']))
return max_d
def searchTrip(user, period, startpoint, endpoint, mode, option):
user_id = UUID(user)
user_home = detect_home(user_id)
gmap = pygmaps.maps(user_home[1], user_home[0], 14)
start, end = Date(period)
sectionList = []
startpoint = Geocoder.geocode(startpoint)[0].coordinates
endpoint = Geocoder.geocode(endpoint)[0].coordinates
for section in get_section_db().find({
"$and": [{
"mode": mode
}, {
"mode": {
"$ne": 'airplane'
}
}, {
"mode": {
"$ne": 7
}
}, {
"section_start_point": {
"$ne": None
}
}, {
"section_end_point": {
"$ne": None
}
}]
}):
point_start = section['section_start_point']['coordinates']
point_end = section['section_end_point']['coordinates']
if calDistance(startpoint, point_start) < 100 and calDistance(
endpoint, point_end) < 100:
sectionList.append(section['_id'])
gmap.addpoint(point_end[1], point_end[0], COLOR[1])
gmap.addpoint(point_start[1], point_start[0], COLOR[1])
drawSection(section, option, gmap)
gmap.draw('gmap_display/' + 'SearchResult' + str(start)[:10] + '-' +
str(end)[:10] + '_' + user + '.html')
print sectionList
def calSpeed(trackpoint1, trackpoint2):
from dateutil import parser
distanceDelta = calDistance(trackpoint1['track_location']['coordinates'],
trackpoint2['track_location']['coordinates'])
timeDelta = parser.parse(trackpoint2['time']) - parser.parse(
trackpoint1['time'])
logging.debug(
"while calculating speed form %s -> %s, distanceDelta = %s, timeDelta = %s"
% (trackpoint1, trackpoint2, distanceDelta, timeDelta))
if timeDelta.total_seconds() != 0:
return distanceDelta / timeDelta.total_seconds()
else:
return None
def searchTrip(user, period, startpoint, endpoint, mode, option):
user_id = UUID(user)
user_home = detect_home(user_id)
gmap = pygmaps.maps(user_home[1], user_home[0], 14)
start, end = Date(period)
sectionList = []
startpoint = Geocoder.geocode(startpoint)[0].coordinates
endpoint = Geocoder.geocode(endpoint)[0].coordinates
for section in get_section_db().find({"$and":[
{"mode": mode},
{"mode": {"$ne": 'airplane'}},
{"mode": {"$ne":7}},
{"section_start_point": {"$ne": None}},
{"section_end_point": {"$ne": None}}]}):
point_start = section['section_start_point']['coordinates']
point_end = section['section_end_point']['coordinates']
if calDistance(startpoint, point_start) < 100 and calDistance(endpoint, point_end) < 100:
sectionList.append(section['_id'])
gmap.addpoint(point_end[1], point_end[0], COLOR[1])
gmap.addpoint(point_start[1], point_start[0], COLOR[1])
drawSection(section, option, gmap)
gmap.draw('gmap_display/' + 'SearchResult' + str(start)[:10] + '-' + str(end)[:10] + '_' + user + '.html')
print sectionList
def refineRoute(lst1, step):
# print(len(lst1))
lst1_extended = []
for i in range(len(lst1) - 1):
dis = calDistance(lst1[i], lst1[i + 1])
num_inter = int(round(dis / step))
if num_inter == 0:
lst1_extended.append(lst1[i])
else:
lat_list = np.linspace(lst1[i][0], lst1[i + 1][0], num_inter,
False)
lon_list = np.linspace(lst1[i][1], lst1[i + 1][1], num_inter,
False)
for j in range(len(lat_list)):
lst1_extended.append([lat_list[j], lon_list[j]])
lst1_extended.append(lst1[-1])
# print(len(lst1))
# print(len(lst1_extended))
return lst1_extended
def route_matching(lst1, lst2, step, radius, len_match, min_score):
# input 2 lists of tracking points, each tracking points is geojson format
# the two lists must have at least two tracking points
if len(lst1) < 2 or len(lst2) < 2:
return False
start_pnt1 = lst1[0]
end_pnt1 = lst1[-1]
start_pnt2 = lst2[0]
end_pnt2 = lst2[-1]
# Case 1, lst2 is part of lst1:
lst1_extended = []
for i in range(len(lst1) - 1):
dis = calDistance(lst1[i]['track_location']['coordinates'],
lst1[i + 1]['track_location']['coordinates'])
num_inter = int(round(dis / step))
if num_inter == 0:
lst1_extended.append(lst1[i]['track_location']['coordinates'])
else:
lat_list = np.linspace(
lst1[i]['track_location']['coordinates'][0],
lst1[i + 1]['track_location']['coordinates'][0], num_inter,
False)
lon_list = np.linspace(
lst1[i]['track_location']['coordinates'][1],
lst1[i + 1]['track_location']['coordinates'][1], num_inter,
False)
for j in range(len(lat_list)):
lst1_extended.append([lat_list[j], lon_list[j]])
lst1_extended.append(end_pnt1['track_location']['coordinates'])
lst2_extended = []
for i in range(len(lst2) - 1):
dis = calDistance(lst2[i]['track_location']['coordinates'],
lst2[i + 1]['track_location']['coordinates'])
num_inter = int(round(dis / step))
if num_inter == 0:
lst2_extended.append(lst2[i]['track_location']['coordinates'])
else:
lat_list = np.linspace(
lst2[i]['track_location']['coordinates'][0],
lst2[i + 1]['track_location']['coordinates'][0], num_inter,
False)
lon_list = np.linspace(
lst2[i]['track_location']['coordinates'][1],
lst2[i + 1]['track_location']['coordinates'][1], num_inter,
False)
for j in range(len(lat_list)):
lst2_extended.append([lat_list[j], lon_list[j]])
lst2_extended.append(end_pnt2['track_location']['coordinates'])
# print(len(lst1_extended))
# print(len(lst2_extended))
near_start2 = find_near(lst1_extended,
start_pnt2['track_location']['coordinates'],
radius)
near_end2 = find_near(lst1_extended,
end_pnt2['track_location']['coordinates'], radius)
near_start1 = find_near(lst2_extended,
start_pnt1['track_location']['coordinates'],
radius)
near_end1 = find_near(lst2_extended,
end_pnt1['track_location']['coordinates'], radius)
# print(near_start2)
# print(near_end2)
# print(near_start1)
# print(near_end1)
best_score = []
if len(near_start2) > 0 and len(near_end2) > 0:
print("start of case 1")
for near_s in near_start2:
for near_e in near_end2:
if min(abs(near_e - near_s) + 1, len(lst2_extended)) / max(
abs(near_e - near_s) + 1,
len(lst2_extended)) >= len_match:
print("possible near_s is %s" % near_s)
print("possible near_e is %s" % near_e)
if near_e > near_s:
print("start index is %d" % near_s)
print("end index is %d" % near_e)
route1 = lst1_extended[near_s:near_e + 1:1]
route2 = lst2_extended
print("route1 is %s" % route1)
print("route2 is %s" % route2)
else:
print("start index is %d" % near_s)
print("end index is %d" % near_e)
route1 = lst1_extended[near_e:near_s + 1:1][::-1]
route2 = lst2_extended
print("route1 is %s" % route1)
print("route2 is %s" % route2)
best_score.append(
cal_matching_score(route1, route2, radius))
if len(near_start1) > 0 and len(near_end1) > 0:
print("start of case 2")
for near_s in near_start1:
for near_e in near_end1:
if min(abs(near_e - near_s) + 1, len(lst1_extended)) / max(
abs(near_e - near_s) + 1,
len(lst1_extended)) >= len_match:
if near_e > near_s:
print("start index is %d" % near_s)
print("end index is %d" % near_e)
route1 = lst1_extended
route2 = lst2_extended[near_s:near_e + 1:1]
print("route1 is %s" % route1)
print("route2 is %s" % route2)
else:
route1 = lst1_extended
route2 = lst2_extended[near_e:near_s + 1:1][::-1]
best_score.append(
cal_matching_score(route1, route2, radius))
print(best_score)
if len(best_score) > 0 and max(best_score) > min_score:
return True
else:
return False
def route_matching_2(lst1, lst2, step, radius, min_score):
# input 2 lists of tracking points, each tracking points is geojson format
# the two lists must have at least two tracking points
if len(lst1) < 2 or len(lst2) < 2:
return False
start_pnt1 = lst1[0]
end_pnt1 = lst1[-1]
start_pnt2 = lst2[0]
end_pnt2 = lst2[-1]
# Case 1, lst2 is part of lst1:
lst1_extended = []
for i in range(len(lst1) - 1):
dis = calDistance(lst1[i]['track_location']['coordinates'],
lst1[i + 1]['track_location']['coordinates'])
num_inter = int(round(dis / step))
if num_inter == 0:
lst1_extended.append(lst1[i]['track_location']['coordinates'])
else:
lat_list = np.linspace(
lst1[i]['track_location']['coordinates'][0],
lst1[i + 1]['track_location']['coordinates'][0], num_inter,
False)
lon_list = np.linspace(
lst1[i]['track_location']['coordinates'][1],
lst1[i + 1]['track_location']['coordinates'][1], num_inter,
False)
for j in range(len(lat_list)):
lst1_extended.append([lat_list[j], lon_list[j]])
lst1_extended.append(end_pnt1['track_location']['coordinates'])
lst2_extended = []
for i in range(len(lst2) - 1):
dis = calDistance(lst2[i]['track_location']['coordinates'],
lst2[i + 1]['track_location']['coordinates'])
num_inter = int(round(dis / step))
if num_inter == 0:
lst2_extended.append(lst2[i]['track_location']['coordinates'])
else:
lat_list = np.linspace(
lst2[i]['track_location']['coordinates'][0],
lst2[i + 1]['track_location']['coordinates'][0], num_inter,
False)
lon_list = np.linspace(
lst2[i]['track_location']['coordinates'][1],
lst2[i + 1]['track_location']['coordinates'][1], num_inter,
False)
for j in range(len(lat_list)):
lst2_extended.append([lat_list[j], lon_list[j]])
lst2_extended.append(end_pnt2['track_location']['coordinates'])
# print(len(lst1_extended))
# print(len(lst2_extended))
best_score = []
score_2_in_1 = 0
for point2 in lst2:
if Include_place_2(lst1_extended,
point2['track_location']['coordinates'], radius):
score_2_in_1 += 1
best_score.append(score_2_in_1 / len(lst2))
score_1_in_2 = 0
for point1 in lst1:
if Include_place_2(lst2_extended,
point1['track_location']['coordinates'], radius):
score_1_in_2 += 1
best_score.append(score_1_in_2 / len(lst1))
print(best_score)
if max(best_score) > min_score:
return True
else:
return False
def _check_zip_validity(user_home, user):
if user_home != "N/A" and detect_home_from_db(
user) != "N/A" and calDistance(
user_home, detect_home_from_db(user)) < TOLERANCE:
return True
return False
