def line_risk2(T_list, line):
risk = 0
# 預先算五點
points = None
for T in T_list:
T_center = T[0:2]
T_range = T[2]
line_dis = dis_p2l(T_center,line)
# 若線段中最短距離小於 range 代表有部分落於 range 內
if line_dis[1] < T_range:
if points == None:
points = cut_into_length(line)
risk += 1
for p in points:
dis = geo.distance(p, T_center)
# if dis <= T_range:
if dis !=0:
risk += (math.pow(dis,-4)*T[3])
else:
risk += 10000
risk *= geo.distance(line[0], line[1])/5
return risk
def _trim_spoke_q(shorter, longer, d):
# if length difference significant, trim
if abs(longer.length()-d)>longer.seg.network.street_scale:
return True
# if next point after shorter spoke end is better match for longer end, trim!
next_shorter = shorter.next()
if next_shorter:
delta_next = geo.distance(longer.end().point, next_shorter.end().point)
delta_this = geo.distance(longer.end().point, shorter.end().point)
return delta_next < delta_this
# no good reason to trim
return False
def getBusPath(self, line=0, via=0, start=-1, end=-1):
try:
doc = xml.dom.minidom.parse("Linha1.kml")
except:
return []
linepts = self.listLinePoints(line, via)
sp = ep = -1 # Point IDs
sd = ed = -1 # Distancias
start_pt = end_pt = None
if start != -1:
if linepts.index(start) == -1: start = -1
else:
pt = self.getStopPosition(start)
start_pt = geo.xyz(float(pt['lat']), float(pt['lon']))
if end != -1:
if linepts.index(end) == -1: end = -1
else:
pt = self.getStopPosition(end)
end_pt = geo.xyz(float(pt['lat']), float(pt['lon']))
plist = []
for node in doc.getElementsByTagName("coordinates"):
pts = node.childNodes[0].data.split()
for i in range(0, len(pts)):
#plist.append(pts[i])
#continue
p = pts[i].split(',')
pt = geo.xyz(float(p[0]), float(p[1]))
plist.append({'lat': p[0], 'lon': p[1]})
if start_pt != None:
d = geo.distance(start_pt, pt)
if sd == -1 or d < sd:
#point = {'lat': p[0], 'lon': p[1], 'dist': sd}
sd = d
sp = i
if end_pt != None:
d = geo.distance(end_pt, pt)
if ed == -1 or d < ed:
#point = {'lat': p[0], 'lon': p[1], 'dist': ed}
ed = d
ep = i
if (ep == -1 or sp == -1):
return plist
elif ep < sp:
return plist[sp:] + plist[:ep]
else:
return plist[sp:ep]
def getBusPath(self, line=0, via=0, start=-1, end=-1):
try:
doc = xml.dom.minidom.parse("Linha1.kml")
except:
return []
linepts = self.listLinePoints(line, via)
sp = ep = -1 # Point IDs
sd = ed = -1 # Distancias
start_pt = end_pt = None
if start != -1:
if linepts.index(start) == -1: start = -1
else:
pt = self.getStopPosition(start)
start_pt = geo.xyz(float(pt['lat']), float(pt['lon']))
if end != -1:
if linepts.index(end) == -1: end = -1
else:
pt = self.getStopPosition(end)
end_pt = geo.xyz(float(pt['lat']), float(pt['lon']))
plist = []
for node in doc.getElementsByTagName("coordinates"):
pts = node.childNodes[0].data.split()
for i in range(0, len(pts)):
#plist.append(pts[i])
#continue
p = pts[i].split(',')
pt = geo.xyz(float(p[0]), float(p[1]))
plist.append({'lat': p[0], 'lon': p[1]})
if start_pt != None:
d = geo.distance(start_pt, pt)
if sd == -1 or d < sd:
#point = {'lat': p[0], 'lon': p[1], 'dist': sd}
sd = d
sp = i
if end_pt != None:
d = geo.distance(end_pt, pt)
if ed == -1 or d < ed:
#point = {'lat': p[0], 'lon': p[1], 'dist': ed}
ed = d
ep = i
if (ep == -1 or sp == -1):
return plist
elif ep < sp:
return plist[sp:] + plist[:ep]
else:
return plist[sp:ep]
def closest(cls, location, count=5, with_event=False):
from operator import itemgetter
import geo
pdx_lat, pdx_lon = "45.511810", "-122.675680"
try:
# lat is +, lon is -, a bug if otherwise
lat, lon, zip_code = geo.get_geocode(location)
if not geo.is_within_radius(pdx_lat, pdx_lon, 15, lat, lon):
return list()
dist = 0.2
got_result = False
while not got_result:
hi_lat, lo_lat, hi_lon, lo_lon = \
geo.radius_to_ll_bounds(lat, lon, dist)
venues = Venue.select(AND(Venue.q.geocode_lat >= lo_lat,
Venue.q.geocode_lat <= hi_lat, Venue.q.geocode_lon >= lo_lon,
Venue.q.geocode_lon <= hi_lon))
venues = list(venues)
if with_event:
venues = [v for v in venues if v.today_events.count()]
if len(venues) >= count:
got_result = True
else:
dist *= 2
except IOError:
return list()
# sort by distance
lst = [(v, geo.distance(lat, lon, v.geocode_lat, v.geocode_lon)) for v in venues]
lst.sort(key=itemgetter(1))
return lst[:count]
def dist_in_miles(g, src, dst):
'''Given a NetworkX graph data and node names, compute mileage between.'''
src_pair = lat_long_pair(g.node[src])
src_loc = geo.xyz(src_pair[0], src_pair[1])
dst_pair = lat_long_pair(g.node[dst])
dst_loc = geo.xyz(dst_pair[0], dst_pair[1])
return geo.distance(src_loc, dst_loc) * METERS_TO_MILES
def dist_in_miles(data, src, dst):
'''Given a dict of names and location data, compute mileage between.'''
src_pair = lat_long_pair(data[src])
src_loc = geo.xyz(src_pair[0], src_pair[1])
dst_pair = lat_long_pair(data[dst])
dst_loc = geo.xyz(dst_pair[0], dst_pair[1])
return geo.distance(src_loc, dst_loc) * METERS_TO_MILES
def put_sign(self, sign_id, latitude, longitude):
nearest_cluster = None
nearest_distance = float('inf')
for cluster in self.clusters:
if latitude > cluster.latitude + self.gridsize_lat or \
latitude < cluster.latitude - self.gridsize_lat or \
longitude > cluster.longitude + self.gridsize_lon or \
longitude < cluster.longitude - self.gridsize_lon:
continue
distance = geo.distance(cluster.latitude, cluster.longitude,
latitude, longitude)
if distance < nearest_distance:
nearest_cluster = cluster
nearest_distance = distance
if nearest_cluster:
# Check duplicate
if sign_id in nearest_cluster.signs:
return
if len(nearest_cluster.signs) < self.n_signs:
nearest_cluster.signs.add(sign_id)
nearest_cluster.size += 1
elif len(self.clusters) < self.n_max:
cluster = Cluster()
cluster.latitude = latitude
cluster.longitude = longitude
cluster.size = 1
cluster.signs.add(sign_id)
self.clusters.append(cluster)
def genArc2(self, branch, point, ref, u, radius, son):
ipr = self.points[branch.initialPoint]
fpr = self.points[branch.finalPoint]
lenght = geo.distance(ipr, fpr)
if son == 1:
off = 40
else:
off = -40
off = 0
t=(lenght-branch.radius*0.6)/lenght
ref2 = [(1-t)*ipr[0]+t*fpr[0],((1-t)*ipr[1]+t*fpr[1]),((1-t)*ipr[2]+t*fpr[2])]
ipr = self.points[point-1]
coords = geo2.rotateByAxis(geo2.getVector4_3(ref2), geo2.getVector4_3(ipr), u, -90+off)
vAux1 = geo.createVertex(coords[0],coords[1],coords[2])
ipr = self.points[point-1]
coords = geo2.rotateByAxis(geo2.getVector4_3(ref), geo2.getVector4_3(ipr), u, -90+off)
vAux2 = geo.createVertex(coords[0],coords[1],coords[2])
circleI = geo.createCircleNormal2(point,vAux2,vAux2,radius,branch.index)
vAux3 = geo.createVertexOnCurveFraction(circleI, 0.25)
eliFullAux = geo.createEllipseFull(vAux3, vAux1, point)
eliFull = geo.createEllipseFull(vAux3, vAux1, point)
geo.deleteCurve2(circleI)
geo.deleteVertex(vAux1)
geo.deleteVertex(vAux2)
v1 = geo.createVertexOnCurveFraction(eliFullAux, 0)
v2 = geo.createVertexOnCurveFraction(eliFullAux, 0.5)
eli1 = geo.splitCurve2(eliFullAux, v1, v2)
eli2 = eli1-1
arcs = [eli1,eli2,eliFull]
return arcs
def dist_in_miles(g, src, dst):
'''Given a NetworkX graph data and node names, compute mileage between.'''
src_pair = lat_long_pair(g.node[src])
src_loc = geo.xyz(src_pair[0], src_pair[1])
dst_pair = lat_long_pair(g.node[dst])
dst_loc = geo.xyz(dst_pair[0], dst_pair[1])
return geo.distance(src_loc, dst_loc) * METERS_TO_MILES
def getDistanceRaw(self):
if self.distanceRaw==None:
this=geo.xyz(self.lat,self.lon)
distance=int(geo.distance(this,home))
self.distanceRaw=distance
return self.distanceRaw
def dist_in_miles(data, src, dst):
'''Given a dict of names and location data, compute mileage between.'''
src_pair = lat_long_pair(data[src])
src_loc = geo.xyz(src_pair[0], src_pair[1])
dst_pair = lat_long_pair(data[dst])
dst_loc = geo.xyz(dst_pair[0], dst_pair[1])
return geo.distance(src_loc, dst_loc) * METERS_TO_MILES
def match(self, spokes):
match_set = []
if self.seg.match: return match_set
len1 = self.length()
street_scale = self.seg.network.street_scale
for spoke in spokes:
if spoke.seg.match: continue
len2 = spoke.length()
if len1<=len2:
length = len1
d1=length
d2=spoke.project(self.end().point)
else:
length = len2
d1 = self.project(spoke.end().point)
d2 = length
# to match, segments must be approximately same length
if abs(d1-d2) > max(street_scale, 0.1*length): continue
# to match, segment end points must be near each other
if geo.distance(self.interpolate(d1),spoke.interpolate(d2)) > street_scale: continue
match_set.append((self, d1, spoke, d2))
return match_set
def process_answer(self, guess, player):
if player not in self.players:
raise KeyError(f"Unknown player: '{player}'")
(main_name, hint), ref = self.place
delta = time.time() - self.start
dist = geo.distance(ref, guess)
sd = self.dist_score(dist)
st = sd * self.time_score(delta)
score = round(st + sd)
msg = MSG_TEMPLATE.format(dist=dist, delta=delta, st=st, sd=sd, score=score)
self.distances[player] = dist
self.durations[player] = delta
self.scores[player] = score
self.messages[player] = msg
res = dict(dist=dist, delta=delta, score=score, msg=msg,
guess=dict(lon=guess[0], lat=guess[1]),
answer=dict(lon=ref[0], lat=ref[1], name=main_name),
player=player, st=st, sd=sd,
)
self.records.append(res)
self.dones[player] = True
game_done = all(self.dones[p] for p in self.players)
if game_done:
self.on_run_end()
return res, game_done
def genArcFull(self, branch, point, ref):
radius = branch.getRadius()
u = branch.getU(self.points)
ipr = self.points[branch.initialPoint]
fpr = self.points[branch.finalPoint]
lenght = geo.distance(ipr, fpr)
t=(lenght-radius[0]*radius[1])/lenght
ref2 = [(1-t)*ipr[0]+t*fpr[0],((1-t)*ipr[1]+t*fpr[1]),((1-t)*ipr[2]+t*fpr[2])]
ipr = self.points[point-1]
coords = geo2.rotateByAxis(geo2.getVector4_3(ref2), geo2.getVector4_3(ipr), u, -90)
vAux1 = geo.createVertex(coords[0],coords[1],coords[2])
coords = geo2.rotateByAxis(geo2.getVector4_3(ref), geo2.getVector4_3(ipr), u, -90)
vAux2 = geo.createVertex(coords[0],coords[1],coords[2])
circleI = geo.createCircleNormal2(point,vAux2,vAux2,radius[1],branch.index)
vAux3 = geo.createVertexOnCurveFraction(circleI, 0.25)
eliFull = geo.createEllipseFull(vAux3, vAux1, point)
geo.deleteCurve(circleI)
#geo.deleteVertex(vAux2)
geo.deleteVertex(vAux1)
#geo.deleteVertex(vAux3)
if eliFull == circleI:
tube.eprint("Erro Ellipse")
return -1
else:
return eliFull
def simulatePulseOld(self):
self.checkQueues()
if self.vehicle.homePositionSet:
if self.vehicle.homePosition == self.vehicle.position:
self.pulseQueue.put(0)
else:
angleToCollar = geo.great_circle_angle(
self.vehicle.homePosition, self.vehicle.position,
geo.geographic_northpole)
distanceToCollar = geo.distance(self.vehicle.position,
self.vehicle.homePosition)
vehicleHeadingToCollar = self.vehicle.heading - angleToCollar
print("simulateBeep", angleToCollar, distanceToCollar,
self.vehicle.heading, vehicleHeadingToCollar)
# Start at full strength
beepStrength = 600.0
# Adjust for distance
maxDistance = 500.0
distanceToCollar = min(distanceToCollar, maxDistance)
beepStrength *= (maxDistance - distanceToCollar) / maxDistance
# Adjust for vehicle heading in relationship to direction to collar
vehicleHeadingToCollar = abs(vehicleHeadingToCollar)
if vehicleHeadingToCollar > 180.0:
vehicleHeadingToCollar = 180.0 - (vehicleHeadingToCollar -
180.0)
vehicleHeadingToCollar = 180.0 - vehicleHeadingToCollar
beepMultiplier = vehicleHeadingToCollar / 180.0
print("beepMultiplier", beepMultiplier, vehicleHeadingToCollar)
beepStrength *= beepMultiplier
self.pulseQueue.put(beepStrength)
else:
print("simulateBeep - home position not set")
self.simulationTimer = threading.Timer(60.0 / BPM, self.simulatePulse)
self.simulationTimer.start()
def _drawPoint(self, crPosUnitsProj, point, colors, distance=True, action="", highlight=False):
(cr, pos, units, proj) = crPosUnitsProj
(lat,lon) = point.getLL() #TODO use getLLE for 3D distance
(lat1,lon1) = pos # current position coordinates
kiloMetricDistance = geo.distance(lat,lon,lat1,lon1)
unitString = units.km2CurrentUnitString(kiloMetricDistance, 0, True)
if distance and pos and units:
distanceString = " (%s)" % unitString
else:
distanceString=""
text = "%s%s" % (point.getName(), distanceString)
(x,y) = proj.ll2xy(lat, lon)
# get colors
(bgColor,textColor) = colors
if highlight:
# draw the highlighting circle
cr.set_line_width(8)
cr.set_source_rgba(*bgColor.getCairoColor()) # highlight circle color
cr.arc(x, y, 15, 0, 2.0 * math.pi)
cr.stroke()
cr.fill()
# draw the point
cr.set_source_rgb(0.0, 0.0, 0.0)
cr.set_line_width(10)
cr.arc(x, y, 3, 0, 2.0 * math.pi)
cr.stroke()
cr.set_source_rgb(0.0, 0.0, 1.0)
cr.set_line_width(8)
cr.arc(x, y, 2, 0, 2.0 * math.pi)
cr.stroke()
# draw a caption with transparent background
cr.set_font_size(25)
extents = cr.text_extents(text) # get the text extents
(w,h) = (extents[2], extents[3])
border = 2
cr.set_line_width(2)
cr.set_source_rgba(*bgColor.getCairoColor()) # trasparent blue
(rx,ry,rw,rh) = (x - border+12, y + border+h*0.2 + 6, w + 4*border, -(h*1.4))
cr.rectangle(rx,ry,rw,rh) # create the transparent background rectangle
cr.fill()
# register clickable area
click = self.m.get('clickHandler', None)
if click:
""" make the POI caption clickable"""
click.registerXYWH(rx,ry-(-rh),rw,-rh, action)
cr.fill()
# draw the actual text
cr.set_source_rgba(*textColor.getCairoColor()) # slightly transparent white
cr.move_to(x+15,y+7)
cr.show_text(text) # show the transparent result caption
cr.stroke()
def get_member_info(self, member):
info = {'nickname': re.sub('[<>&]', '', member.nickname),
'lat': member.location.lat,
'lon': member.location.lon}
if self.member:
info['distance'] = geo.distance(
self.member.location, member.location)
return info
def dist_between_crimes(self, crime1, crime2):
coord1 = crime1.get_coordinates()
coord2 = crime2.get_coordinates()
#splat operator * turns fnctn(['p','p']) into fnctn('p1','p2')
dist = geo.distance(geo.xyz(*coord1), geo.xyz(*coord2))
#avoid 1/r^2 singularities with 100 m min dist
return dist if dist > 100 else 100
def move_to(start, goal,velocity):
# 如果在一步內，則不經計算直接到點（同時避免超過)
if (geo.distance(start,goal) <= velocity):
return goal
# move direction
move = geo.normalize(geo.Vector(start,goal))
# mul by v
move = geo.constance_multi(velocity, move)
return geo.vector_add(start, move)
def compute_sensor_movement(last_position, current_position):
# Calculate how the sensor moved.
course = geo.course(last_position.lat, last_position.lon,
current_position.lat, current_position.lon)
displacement = geo.distance(last_position.lat, last_position.lon,
current_position.lat, current_position.lon)
dx = displacement * trig.sind(course)
dy = displacement * trig.cosd(course)
return dx, dy
def updateItemDistance(self):
position = self.get("pos", None) # our lat lon coordinates
if position is not None:
(lat1,lon1) = position
(lat2,lon2) = (float(item['lat']), float(item['lng']))
distance = geo.distance(lat1,lon1,lat2,lon2)
else:
distance = 0 # in this case, we don't know our position, so we say the distance is 0
return distance
def dist_between_crimes(self,crime1,crime2):
coord1 = crime1.get_coordinates()
coord2 = crime2.get_coordinates()
#splat operator * turns fnctn(['p','p']) into fnctn('p1','p2')
dist = geo.distance(geo.xyz(*coord1),geo.xyz(*coord2))
#avoid 1/r^2 singularities with 100 m min dist
return dist if dist > 100 else 100
def genWaypoints(x,y):
bbox = [min(y),min(x),max(y),max(x)]
response = urllib2.urlopen("http://overpass.osm.rambler.ru/cgi/interpreter?data=[out:json];node[natural~'peak'][name](%(X)s);node[place~'town|city|village|hamlet'](%(X)s);out;" % {'X':','.join(map(str,bbox))})
places = json.loads(response.read())
minplaces = {}
for i in range(len(x)):
lon,lat = x[i],y[i]
pt1 = geo.xyz(lon,lat)
mindist = False
minplace = False
for place in places['elements']:
pt2 = geo.xyz(place['lon'],place['lat'])
dist = geo.distance(pt1,pt2)
if False == mindist or dist < mindist:
if (dist < 100 and 'natural' in place['tags'] and place['tags']['natural'] == 'peak') or \
(dist < 150 and 'place' in place['tags'] and place['tags']['place'] == 'hamlet') or \
(dist < 500 and 'place' in place['tags'] and place['tags']['place'] == 'village') or \
(dist < 1500 and 'place' in place['tags'] and place['tags']['place'] == 'place') or \
(dist < 5000 and 'place' in place['tags'] and place['tags']['place'] == 'city'):
mindist = dist
minplace = place
if minplace:
minplaces[minplace['tags']['name']] = minplace
waypoints = {}
for place in minplaces.values():
pt2 = geo.xyz(place['lon'],place['lat'])
mindist = False;
for i in range(len(x)):
lon,lat = x[i],y[i]
pt1 = geo.xyz(lon,lat)
dist = geo.distance(pt1,pt2)
if False == mindist or dist < mindist:
mindist = dist
mini = i
if (mindist < 100 and 'natural' in place['tags'] and place['tags']['natural'] == 'peak') or \
(mindist < 150 and 'place' in place['tags'] and place['tags']['place'] == 'hamlet') or \
(mindist < 500 and 'place' in place['tags'] and place['tags']['place'] == 'village') or \
(mindist < 1500 and 'place' in place['tags'] and place['tags']['place'] == 'place') or \
(mindist < 5000 and 'place' in place['tags'] and place['tags']['place'] == 'city'):
waypoints[mini] = (mindist,place['tags']['name'])
return waypoints;
def get_distance(self):
corner1, corner2 = self.bounding_box()
p1 = Point.from_latlon(*corner1)
p2 = Point.from_latlon(*corner2)
dist = geo.distance(p1, p2)
dist_param = round(dist**self.distance_harshness)
print(self.name, dist_param)
return dist_param
def jct_filter_max_d(self, setJct, parms):
(max_d,d) = parms
dist = geo.distance(setJct.point,self.jct.point)
jcts_near_point = self.set_nwk.get_jcts_near_point(self.jct.point, d)
log.debug('DEBUG jct_filter_max_d (dist <= max_d) = (%s <= %s) (%s), d = %s, len(jcts_near_point)=%s',
dist, max_d, dist <= max_d, d, len(jcts_near_point))
return (dist <= max_d and
len(jcts_near_point) == 1)
def localAddPointsToLine(lat1, lon1, lat2, lon2, maxDistance):
distance = geo.distance(lat1, lon1, lat2, lon2)
if distance <= maxDistance: # the termination criterion
return
else:
middleLat = (lat1 + lat2) / 2.0 # fin the midpoint between the two points
middleLon = (lon1 + lon2) / 2.0
pointsBetween.append((middleLat, middleLon))
# process the 2 new line segments
localAddPointsToLine(lat1, lon1, middleLat, middleLon, maxDistance)
localAddPointsToLine(middleLat, middleLon, lat2, lon2, maxDistance)
def rand_map(self):
index = -1
coord_table = []
while True:
x = (random.randint(0, self.map_size[0] - 1),
random.randint(0, self.map_size[0] - 1))
if x not in coord_table and self.in_area(
x) is False and geo.distance(x,
start_pos) >= map_size[1] / 3:
coord_table.append(x)
yield x
def compute_sensor_movement(last_position, current_position):
# Calculate how the sensor moved.
course = geo.course(
last_position.lat, last_position.lon,
current_position.lat, current_position.lon)
displacement = geo.distance(
last_position.lat, last_position.lon,
current_position.lat, current_position.lon)
dx = displacement * trig.sind(course)
dy = displacement * trig.cosd(course)
return dx, dy
def screenRadius(self): """Return the centerpoint and radius of a circle encompassing the screen.""" (centreXpixel,centreYpixel) = self.screenPos(0.5,0.5) (centreX, centreY) = self.xy2ll(centreXpixel, centreYpixel) #ASUMPTION: screen is rectangular (cornerXpixel,cornerYpixel) = self.screenPos(0, 0) # we take the coordinates of one corner of the screen (cornerX,cornerY) = self.xy2ll(cornerXpixel, cornerYpixel) # we convert them to projection coordinates (anotherCornerXpixel,anotherCornerYpixel) = self.screenPos(1, 1) # we take the coordinates of another corner of the screen (anotherCornerX,anotherCornerY) = self.xy2ll(anotherCornerXpixel, anotherCornerYpixel) # we convert them to projection coordinates """radius = diagonal/2""" radius = geo.distance(anotherCornerX, anotherCornerY, cornerX , cornerY)/2.0 return centreX, centreY, radius # we return the centre coordinates and the radius
def _stations_with_distance(loc: Optional[LatLonTuple]) -> Optional[List]:
""" Return list of petrol stations w. added distance data. """
pd = _get_petrol_station_data()
if not pd:
return None
if loc:
# Calculate distance of all stations
for s in pd:
s["distance"] = distance(loc, (s["geo"]["lat"], s["geo"]["lon"]))
return pd
def getClosestStep(self):
"""get the geographically closest step"""
proj = self.m.get('projection', None) # we also need the projection module
pos = self.get('pos', None) # and current position
if pos and proj:
(lat1,lon1) = pos
tempSteps = self.route.getMessagePoints()
for step in tempSteps:
(lat2, lon2) = step.getLL()
step.setCurrentDistance = geo.distance(lat1,lon1,lat2,lon2)*1000 # km to m
closestStep = sorted(tempSteps, key=lambda x: x.getCurrentDistance())[0]
return closestStep
def collision_detect_angle(rs, v):
rsv_dot = geo.dot(rs, v)
if rsv_dot < 0 :
return None
elif rsv_dot == 0:
return math.pi/2
rs_value = geo.distance([0,0],rs)
v_value = geo.distance([0,0],v)
value = rsv_dot/(rs_value*v_value)
if value <=1 :
return_v = math.acos(value)
else:
return_v = math.acos(1)
return return_v
def _impl(record):
entry = SearchEntry()
entry.sign_id = int(record['sign_id'])
entry.rank = record.get('rank')
# Min rank threshold
if entry.rank != None and entry.rank < params.min_rank:
return
# Legacy
if entry.rank == None:
entry.rank = 0
location = record['location'].unwrap().get('coordinates')
entry.distance = geo.distance(params.latitude, params.longitude, location[1], location[0])
heap.push(entry)
def getNearestBusStops(self,
lat=None,
lon=None,
radius=1000,
limit=10,
line=None,
via=None):
#dados = list(csv.reader(open('circular1.csv')))
#__location__ = os.path.realpath(os.path.join(os.getcwd(), os.path.dirname(sys.argv[0])))
if line != None and via != None:
possible = self.listLinePoints(line, via)
else:
possible = None
if (lat == None or lon == None):
return "Missing Lat or Lon"
source = geo.xyz(float(lat), float(lon))
txt = str(limit) + " Closest Bus Stops in a " + str(
radius) + "m radius: <br/>"
ldist = []
doc = xml.dom.minidom.parse("bus_stops.kml")
for node in doc.getElementsByTagName("Placemark"):
name = node.getElementsByTagName("name")[0].childNodes[0].data
sid = node.getElementsByTagName("stopid")[0].childNodes[0].data
points = node.getElementsByTagName("Point")
coord = points[0].getElementsByTagName("coordinates")
lon = float(coord[0].childNodes[0].data.split(",")[0])
lat = float(coord[0].childNodes[0].data.split(",")[1])
point = geo.xyz(lat, lon)
dist = float('%.2f' % geo.distance(source, point))
if (float(dist) < float(radius)
and (possible == None or possible.index(sid) != -1)):
ldist.append({
'dist': float(dist),
'name': name,
'lat': lat,
'lon': lon,
'sid': sid
})
if (ldist == []):
return self.getNearestBusStops(lat, lon, radius + 100, limit)
return sorted(ldist, key=itemgetter('dist'))[0:int(limit)]
def dist_answer_for_loc(matches, query):
""" Generate response to distance query. """
locname = matches.group(1)
loc_nf = _addr2nom(locname[0].upper() + locname[1:])
res = query_geocode_api_addr(loc_nf)
# Verify sanity of API response
if (not res or not "status" in res or res["status"] != "OK"
or not res.get("results")):
return None
# Try to avoid answering bus queries here
loc_lower = locname.lower()
if any(s in loc_lower for s in (
"strætó",
"stoppistöð",
"strætisvagn",
"biðstöð",
"stoppustöð",
"stræto",
"strædo",
)):
return None
# Extract location coordinates from API result
topres = res["results"][0]
coords = topres["geometry"]["location"]
loc = (coords["lat"], coords["lng"])
# Calculate distance, round it intelligently and format num string
km_dist = distance(query.location, loc)
# Generate answer
answer = distance_desc(km_dist, abbr=True)
response = dict(answer=answer)
loc_nf = loc_nf[0].upper() + loc_nf[1:]
dist = distance_desc(km_dist, case="þf")
voice = "{0} er {1} í burtu".format(loc_nf, dist)
query.set_key(capitalize_placename(loc_nf))
# Beautify by capitalizing remote loc name
uc = capitalize_placename(locname)
bq = query.beautified_query.replace(locname, uc)
query.set_beautified_query(bq)
query.set_context(dict(subject=loc_nf))
return response, answer, voice
def update_data(self):
if self.start_pos==None or self.dest_pos==None: return
self.data_dist.set_text("Distance: %f km" % (geo.distance(self.start_pos,self.dest_pos)/1000.))
if not self.start_pos==self.dest_pos:
if HAVE_GEOMAG:
true_north = geo.great_circle_angle(self.dest_pos,self.start_pos,geo.geographic_northpole)
angle = geomag.mag_heading(true_north,dlat=self.start_lat,dlon=self.start_lon)
else:
angle = geo.great_circle_angle(self.dest_pos,self.start_pos,geo.magnetic_northpole)
self.data_dir.set_text("Direction: %f\xc2\xb0 from north (%s)" % (angle, geo.direction_name(angle)))
else:
self.data_dir.set_text("Start point and destination is the same!")
def imprime(self):
heap = [self.root]
while not (len(heap) == 0):
atual = heap.pop()
pi = self.points[atual.initialPoint]
pf = self.points[atual.finalPoint]
lenght = geo.distance(pi, pf)
if lenght < atual.radius*3:
print "Segmento muito pequeno "
print atual.initialPoint+1
#print str(atual.initialPoint) + str(self.points[atual.initialPoint])+ " " + str(atual.finalPoint) + str(self.points[atual.finalPoint])
#print str(atual.initialPoint) + " " + str(atual.finalPoint)
if atual.son1 is not None:
heap.append(atual.son1)
if atual.son2 is not None:
heap.append(atual.son2)
def dist_answer_for_loc(locname, query):
""" Generate response to distance query """
loc_nf = _addr2nom(locname[0].upper() + locname[1:])
res = query_geocode_api_addr(loc_nf)
# Verify sanity of API response
if (not res or not "status" in res or res["status"] != "OK"
or not res.get("results")):
return None
# Extract location coordinates from API result
topres = res["results"][0]
coords = topres["geometry"]["location"]
loc = (coords["lat"], coords["lng"])
# Calculate distance, round it intelligently and format num string
km_dist = distance(query.location, loc)
# E.g. 7,3 kílómetra
if km_dist >= 1.0:
km_dist = round(km_dist, 1 if km_dist < 10 else 0)
dist = str(km_dist).replace(".", ",")
dist = re.sub(r",0$", "", dist)
unit = "kílómetra"
unit_abbr = "km"
# E.g. 940 metra
else:
dist = int(math.ceil(
(km_dist * 1000.0) / 10.0) * 10) # Round to nearest 10 m
unit = "metra"
unit_abbr = "m"
# Generate answer
answer = "{0} {1}".format(dist, unit_abbr)
response = dict(answer=answer)
loc_nf = loc_nf[0].upper() + loc_nf[1:]
voice = "{2} er {0} {1} í burtu".format(dist, unit, loc_nf)
query.set_key(loc_nf)
# Beautify by capitalizing remote loc name
uc = locname.title()
bq = query.beautified_query.replace(locname, uc)
query.set_beautified_query(bq)
return response, answer, voice
def routeClosestPoint(self, lat=None, lon=None, line=0, via=0):
try:
doc = xml.dom.minidom.parse("Linha" + (line + 1) + ".kml")
except:
return []
source = geo.xyz(float(lat), float(lon))
md = -1
point = None
for node in doc.getElementsByTagName("coordinates"):
pts = node[0].childNodes[0].data.split(" ")
for p in pts:
p = p.split(',')
pt = geo.xyz(float(p[0]), float(p[1]))
d = geo.distance(source, pt)
if md == -1 or d < md:
point = {'lat': p[0], 'lon': p[1], 'dist': d}
md = d
return point
def routeClosestPoint(self, lat=None, lon=None, line=0, via=0):
try:
doc = xml.dom.minidom.parse("Linha" + (line + 1) + ".kml")
except:
return []
source = geo.xyz(float(lat), float(lon))
md = -1
point = None
for node in doc.getElementsByTagName("coordinates"):
pts = node[0].childNodes[0].data.split(" ")
for p in pts:
p = p.split(',')
pt = geo.xyz(float(p[0]), float(p[1]))
d = geo.distance(source, pt)
if md == -1 or d < md:
point = {'lat': p[0], 'lon': p[1], 'dist': d}
md = d
return point
def getNearestBusStops(self, lat=None, lon=None, radius=1000, limit=10, line=None, via=None):
#dados = list(csv.reader(open('circular1.csv')))
#__location__ = os.path.realpath(os.path.join(os.getcwd(), os.path.dirname(sys.argv[0])))
if line != None and via != None:
possible = self.listLinePoints(line, via)
else:
possible = None
if(lat == None or lon == None):
return "Missing Lat or Lon"
source = geo.xyz(float(lat), float(lon))
txt = str(limit) + " Closest Bus Stops in a " + str(radius) + "m radius: <br/>"
ldist = []
doc = xml.dom.minidom.parse("bus_stops.kml")
for node in doc.getElementsByTagName("Placemark"):
name = node.getElementsByTagName("name")[0].childNodes[0].data
sid = node.getElementsByTagName("stopid")[0].childNodes[0].data
points = node.getElementsByTagName("Point")
coord = points[0].getElementsByTagName("coordinates")
lon = float(coord[0].childNodes[0].data.split(",")[0])
lat = float(coord[0].childNodes[0].data.split(",")[1])
point = geo.xyz(lat, lon)
dist = float('%.2f' % geo.distance(source, point))
if(float(dist) < float(radius) and (possible == None or possible.index(sid) != -1)):
ldist.append({
'dist':float(dist),
'name':name,
'lat':lat,
'lon':lon,
'sid':sid
})
if(ldist == []):
return self.getNearestBusStops(lat, lon, radius + 100, limit)
return sorted(ldist, key=itemgetter('dist'))[0:int(limit)]
def analyze(igc):
igc.min_gps_altitude = 5000
igc.max_gps_altitude = 0
igc.min_baro_altitude = 5000
igc.max_baro_altitude = 0
previous_record = igc.b_records[0]
for record in igc.b_records:
if previous_record and previous_record.validity == 'A' and record.validity == 'A':
igc.tracklog_length += distance(previous_record.point, record.point)
if igc.min_gps_altitude > record.gps_altitude:
igc.min_gps_altitude = record.gps_altitude
if igc.max_gps_altitude < record.gps_altitude:
igc.max_gps_altitude = record.gps_altitude
if igc.min_baro_altitude > record.baro_altitude:
igc.min_baro_altitude = record.baro_altitude
if igc.max_baro_altitude < record.baro_altitude:
igc.max_baro_altitude = record.baro_altitude
previous_record = record
igc.flight_duration = igc.b_records[-1].datetime - igc.b_records[0].datetime
def fixSizes(self):
heap = [self.root]
while not (len(heap) == 0):
atual = heap.pop()
ip = self.points[atual.initialPoint]
fp = self.points[atual.finalPoint]
lenght = geo.distance(ip, fp)
if lenght < atual.radius*5:
t=(atual.radius*6)/lenght
npf = [(1-t)*ip[0]+t*fp[0],((1-t)*ip[1]+t*fp[1]),((1-t)*ip[2]+t*fp[2])]
#self.points[atual.finalPoint] = npf
xyz = [npf[0]-fp[0], npf[1]-fp[1], npf[2]-fp[2]]
if atual.son1 is not None:
self.move(atual.son1,xyz)
if atual.son2 is not None:
self.move(atual.son2,xyz)
if atual.son1 is not None:
heap.append(atual.son1)
if atual.son2 is not None:
heap.append(atual.son2)
def updateDistance(self):
if self.localSearchResults:
position = self.get("pos", None) # our lat lon coordinates
list = []
index = 0
for item in self.localSearchResults['responseData']['results']: # we iterate over the local search results
if position is not None:
(lat1,lon1) = position
(lat2,lon2) = (float(item['lat']), float(item['lng']))
distance = geo.distance(lat1,lon1,lat2,lon2)
tupple = (distance, item, index)
list.append(tupple) # we pack each result into a tupple with ist distance from us
else:
tupple = (0, item, index) # in this case, we dont know our position, so we say the distance is 0
list.append(tupple)
index += 1
self.list = list
return list
else:
print "search: error -> distance update on empty results"
def parse_raw(raw):
result = {}
num_regexp = re.compile("\d+(\.\d+)?")
last_update = prop_raw_extract("Date et heure du dernier point ", raw, True)
# remove "(heure d'été)"
last_update = last_update[0:last_update.rfind("(")].strip()
result["last_update"] = datetime.strptime(last_update, "%d/%m/%Y %H:%M:%S")
course = prop_raw_extract("Cap", raw)
result["course"] = float(re.search(num_regexp, course).group(0))
speed = prop_raw_extract("Vitesse", raw)
result["speed"] = float(re.search(num_regexp, speed).group(0))
latitude = prop_raw_extract("Latitude", raw)
result["str_latitude"] = latitude
south = latitude[0] == "S"
split = re.findall("\d+", latitude)
# N 47 43'30''
numlatitude = float(split[0]) + float(split[1])/60 + float(split[2])/3600
if south:
numlatitude = -numlatitude
result["latitude"] = numlatitude
longitude = prop_raw_extract("Longitude", raw)
result["str_longitude"] = longitude
est = longitude[0] == "E"
split = re.findall("\d+", longitude)
# W 003 20'59''
numlongitude = float(split[0]) + float(split[1])/60 + float(split[2])/3600
if est:
numlongitude = -numlongitude
result["longitude"] = numlongitude
pos = geo.xyz(numlatitude, numlongitude)
# N 47 42,8 W 3 21,5
finish = geo.xyz(47.7133,3.3583)
result["dtf"] = '%0.1f' % (geo.distance(pos, finish) / 1852)
return result
def cut_into_length(line, length = 5):
v_add = geo.constance_multi(length, geo.normalize(geo.Vector(line[0],line[1])))
dis = geo.distance(line[0],line[1])
v_start = line[0]
points = []
for d in range(0, math.ceil(dis+length), length):
if d > dis:
v_start = line[1]
else:
v_start = geo.vector_add(v_start, v_add)
points.append(v_start[:])
return points
def testDistanceWithRealworldData(self):
""" Test the distance function using data I gathered from Google Earth."""
alcatraz = (37.825685, -122.422586)
sfo = (37.619057, -122.375483)
mono_lake = (37.998619, -119.028868)
nyc = (40.577485, -73.975278)
gibralter = (35.904513, -5.562047)
mumbai = (19.010173, 72.910176)
self.assertAlmostEqual(geo.distance(alcatraz, sfo), 12.5, .1)
self.assertAlmostEqual(geo.distance(alcatraz, mono_lake), 162, 2)
self.assertAlmostEqual(geo.distance(alcatraz, nyc), 2233, 25)
self.assertAlmostEqual(geo.distance(alcatraz, gibralter), 5163, 450)
self.assertAlmostEqual(geo.distance(nyc, gibralter), 3148, 90)
self.assertAlmostEqual(geo.distance(mumbai, gibralter), 4193, 65)
# Here's one that is wildly inaccurate, just as an example. (The algorithm
# uses an approximation that's only valid for shorter distances.)
self.assertAlmostEqual(geo.distance(alcatraz, mumbai), 7291, 3000)
def testDistanceWithRealworldData(self):
""" Test the distance function using data I gathered from Google Earth."""
alcatraz = (37.825685, -122.422586)
sfo = (37.619057, -122.375483)
mono_lake = (37.998619, -119.028868)
nyc = (40.577485, -73.975278)
gibralter = (35.904513, -5.562047)
mumbai = (19.010173, 72.910176)
self.assertAlmostEqual(geo.distance(alcatraz, sfo), 12.5, .1)
self.assertAlmostEqual(geo.distance(alcatraz, mono_lake), 162, 2)
self.assertAlmostEqual(geo.distance(alcatraz, nyc), 2233, 25)
self.assertAlmostEqual(geo.distance(alcatraz, gibralter), 5163, 450)
self.assertAlmostEqual(geo.distance(nyc, gibralter), 3148, 90)
self.assertAlmostEqual(geo.distance(mumbai, gibralter), 4193, 65)
# Here's one that is wildly inaccurate, just as an example. (The algorithm
# uses an approximation that's only valid for shorter distances.)
self.assertAlmostEqual(geo.distance(alcatraz, mumbai), 7291, 3000)
def getTilesForRoute(self, route, radius, z):
"""get tilenames for tiles around the route for given radius and zoom"""
""" now we look whats the distance between each two trackpoints,
if it is larger than the tracklog radius, we add additional interpolated points,
so we get continuous coverage for the tracklog """
first = True
interpolatedPoints = []
for point in route:
if first: # the first point has no previous point
(lastLat, lastLon) = point[0], point[1]
first = False
continue
thisLat, thisLon = point[0], point[1]
distBtwPoints = geo.distance(lastLat, lastLon, thisLat, thisLon)
"""if the distance between points was greater than the given radius for tiles,
there would be no continuous coverage for the route"""
if distBtwPoints > radius:
"""so we call this recursive function to interpolate points between
points that are too far apart"""
interpolatedPoints.extend(self.addPointsToLine(lastLat, lastLon, thisLat, thisLon, radius))
(lastLat, lastLon) = (thisLat, thisLon)
"""because we don't care about what order are the points in this case,
we just add the interpolated points to the end"""
route.extend(interpolatedPoints)
start = clock()
tilesToDownload = set()
for point in route: #now we iterate over all points of the route
lat, lon = point[0], point[1]
# be advised: the xy in this case are not screen coordinates but tile coordinates
(x, y) = latlon2xy(lat, lon, z)
# the spiral gives us tiles around coordinates for a given radius
currentPointTiles = self.spiral(x, y, z, radius)
"""now we take the resulting list and process it in such a way,
that the tiles coordinates can be stored in a set,
so we will save only unique tiles"""
outputSet = set(map(lambda x: tuple(x), currentPointTiles))
tilesToDownload.update(outputSet)
print "Listing tiles took %1.2f ms" % (1000 * (clock() - start))
print "unique tiles %d" % len(tilesToDownload)
return tilesToDownload
def _updateLogCB(self):
"""add current position at the end of the log"""
pos = self.get('pos', None)
if pos and not self.loggingPaused:
timestamp = geo.timestampUTC()
lat, lon = pos
elevation = self.get('elevation', None)
self.log1.addPointLLET(lat, lon, elevation, timestamp)
self.log2.addPointLLET(lat, lon, elevation, timestamp)
# update statistics for the current log
if self.loggingEnabled and not self.loggingPaused:
# update the current log speed statistics
currentSpeed = self.get('speed', None)
if currentSpeed:
# max speed
if currentSpeed > self.maxSpeed:
self.maxSpeed = currentSpeed
# avg speed
self.avg1 += currentSpeed
self.avg2 += (time.time() - self.lastUpdateTimestamp)
self.avgSpeed = self.avg1/self.avg2
self.lastUpdateTimestamp = time.time()
# update traveled distance
if self.lastCoords:
lLat, lLon = self.lastCoords
self.distance+=geo.distance(lLat, lLon, lat, lon)
self.lastCoords = lat, lon
# update the on-map trace
if self.lastTracePoint:
lat1, lon1 = self.lastTracePoint
# check if the point is distant enough from the last added point
# (which was either the first point or also passed the test)
if geo.distanceApprox(lat, lon, lat1, lon1)*1000 >= DONT_ADD_TO_TRACE_THRESHOLD:
self._addLL2Trace(lat, lon)
else: # this is the first known log point, just add it
self._addLL2Trace(lat, lon)
def get_variables(data):
"""
выдает основные переменные
"""
x, y = data['x'], data['y']
s, d = data['s'], data['d']
end_path_s, end_path_d = data['end_path_s'], data['end_path_d']
prev_x, prev_y = data['previous_path_x'], data['previous_path_y']
if len(prev_x) == 0:
end_path_s, end_path_d = s, d
ref_yaw = deg2rad(data['yaw'])
other_cars = np.array([[a[-2], a[-1],
sqrt(a[-3]**2 + a[-4]**2)]
for a in data['sensor_fusion']])
#добавляем к s скорость * время
for i in range(len(other_cars)):
other_cars[i][0] += other_cars[i][2] * len(prev_x) * 0.02
#last_s,last_d=data['end_path_s'], data['end_path_d']
while len(last_coords) > len(prev_x):
last_coords.pop(0)
if len(last_coords) == 0:
last_coords.append((s, d))
#todo - здесь должен быть cos/sin
if len(prev_x) == 0:
prev_x, prev_y = [x - 0.001, x], [y, y]
if len(prev_x) == 1:
prev_x, prev_y = [prev_x[0] - 0.001, prev_x[0]], [prev_y[0], prev_y[0]]
car_speed = distance(prev_x[-1], prev_y[-1], prev_x[-2], prev_y[-2]) / 0.02
return prev_x, prev_y, end_path_s, end_path_d, car_speed, ref_yaw, other_cars
def finish_game(game_id, latitude, longitude):
if not game_id in games:
return bottle.HTTPResponse(status=404, body='game not found')
game = games[game_id]
answer_coordinates = (float(latitude), float(longitude))
d = distance(game.current_coordinates, answer_coordinates)
if not game.is_finished:
game.is_finished = True
game.answer_coordinates = answer_coordinates
game.distance = d
game.score = count_score(game)
return {
"right_coordinates": game.current_coordinates,
"distance": d,
"address": get_text_by_coordinates(game.current_coordinates),
"route": game.route,
"score": game.score
}
def count_score(game):
dist = distance(game.current_coordinates, game.answer_coordinates)
return 100_000 / (1 + dist)
def check_circle_fence(lat, lng, clat, clng, radius):
distance = geo.distance(lat, lng, clat, clng)
if distance < radius:
return 1
return 0
pass
def dist_answer_for_loc(matches, query: Query):
"""Generate response to distance query, e.g.
"Hvað er ég langt frá X?" """
locname = matches.group(1)
loc_nf = _addr2nom(locname) or locname
# Try to avoid answering certain queries here
loc_lower = locname.lower()
# TODO: Solve this by configuring qmodule priority
if any(s in loc_lower for s in (
"strætó",
"stoppistöð",
"strætisvagn",
"biðstöð",
"stoppustöð",
"stræto",
"strædo",
"jólin",
"jól",
"páska",
)):
return None
# Check if user is asking about distance from home address
is_home = False
loc: Tuple[float, float]
if loc_lower in _HOME_LOC:
ad = query.client_data("address")
if not ad:
return gen_answer(
"Ég veit ekki hvar þú átt heima, en þú getur sagt mér það.")
elif "lat" not in ad or "lon" not in ad:
return gen_answer("Ég veit ekki hvar heimili þitt er.")
else:
is_home = True
loc = (cast(float, ad["lat"]), cast(float, ad["lon"]))
loc_nf = "{0} {1}".format(ad["street"], ad["number"])
else:
# Talk to geocode API
res = query_geocode_api_addr(loc_nf)
# Verify sanity of API response
if (not res or "status" not in res or res["status"] != "OK"
or not res.get("results")):
return None
# Extract location coordinates from result
coords = res["results"][0]["geometry"]["location"]
loc = (coords["lat"], coords["lng"])
# Calculate distance, round it intelligently and format num string
if query.location is None:
km_dist = 0.0
else:
km_dist = distance(query.location, loc)
# Generate answer
answer = distance_desc(km_dist, abbr=True)
response = dict(answer=answer, distance=km_dist)
loc_nf = capitalize_placename(loc_nf)
dist = distance_desc(km_dist, case="þf")
voice = "{0} er {1} í burtu".format(numbers_to_neutral(loc_nf), dist)
query.set_key(loc_nf)
# Beautify by capitalizing remote loc name
uc = locname if is_home else capitalize_placename(locname)
bq = query.beautified_query.replace(locname, uc)
# Hack to fix the fact that the voice recognition often misses "ég"
prefix_fix = "Hvað er langt frá"
if bq.startswith(prefix_fix):
bq = bq.replace(prefix_fix, "Hvað er ég langt frá")
query.set_beautified_query(bq)
query.set_context(dict(subject=loc_nf))
return response, answer, voice
def getCPA(rs,angle):
return geo.distance([0,0],rs) * math.sin(angle)
def in_range(node, city, radius):
node_geo = geo.xyz(float(node[0]), float(node[1]))
city_geo = geo.xyz(float(city[0]), float(city[1]))
dist = geo.distance(node_geo, city_geo) * METERS_TO_MILES
return dist < radius
def on_friend(client, dev, command, params, message):
logging.info("on_friend %s"%(dev.devid()))
data = decode.decode_ul(message)
rtime = data[0][5]
rtime = time.time()
cells = ['%d_%d_%d_%d'%(x[0], x[1], x[2], x[3]) for x in data[2][0][2]]
logging.info("friend cells:%s"%(cells))
gps = (data[2][0][0][0],data[2][0][0][1])
mode = 1
if not gps[0] or not gps[1]:
mode = 0
gps = cell_location.calc_location(data[2][0][2])
friend_match_cache = db.cacheobj_get_friend_match_cache()
removed = []
matched = None
logging.info("friend cache:%s"%(friend_match_cache))
if dev.imei in friend_match_cache.keys():
friend_match_cache[dev.imei] = MatchCache(rtime,cells,gps, mode).__dict__
for imei in friend_match_cache:
match_cache = friend_match_cache[imei]
diff_time = abs(rtime - match_cache['time'])
logging.info("diff_time=%f",diff_time)
if( time.time() - match_cache['time'] > config.friend_match.timeout ):
removed.append(imei)
continue
if imei != dev.imei:
match_mode = mode
if mode != match_cache['mode'] and mode == 1:
match_mode = 0
match_cells = 0
for c1 in cells:
if c1 in match_cache['cells']:
match_cells = match_cells + 1
diff_gps = geo.distance(gps[0], gps[1], match_cache['gps'][0], match_cache['gps'][1])
logging.info("friend %f %f %f"%(diff_time, match_cells, diff_gps))
if( diff_time < 10 and (match_cells > 2 or (mode==1 and diff_gps < 20.0) or (mode==0 and diff_gps < 300.0)) ):
matched = imei
removed.append(imei)
break
for imei in removed:
del friend_match_cache[imei]
if matched:
#db.make_friends(dev, matched)
friend = db.get_device_record_by_imei(matched)
dev.new_friend(matched, friend.device_phone, friend.device_name)
data = db.cacheobj_get_device_host(matched)
url = 'http://%s:%s/device/%s/newfriend/%s'%(data[2], data[3], matched, dev.imei)
logging.info("friend url:%s"%(url))
try:
res = urllib2.urlopen(url, '{}')
ret = res.read()
logging.info("%s"%(ret))
except Exception as e:
logging.info("%s"%(e))
pass
else:
friend_match_cache[dev.imei] = MatchCache(rtime, cells, gps, mode).__dict__
db.cacheobj_set_friend_match_cache(friend_match_cache)
pass
def test_geo():
""" Test geography and location-related functions in geo.py """
from geo import (
icelandic_city_name,
continent_for_country,
coords_for_country,
coords_for_street_name,
country_name_for_isocode,
isocode_for_country_name,
icelandic_addr_info,
lookup_city_info,
parse_address_string,
iceprep_for_street,
iceprep_for_placename,
iceprep_for_country,
iceprep_for_cc,
capitalize_placename,
distance,
in_iceland,
code_for_us_state,
coords_for_us_state_code,
location_info,
)
assert icelandic_city_name("London") == "Lundúnir"
assert icelandic_city_name("Rome") == "Róm"
assert continent_for_country("IS") == "EU"
assert continent_for_country("no") == "EU"
assert continent_for_country("MX") == "NA"
assert coords_for_country("DE") is not None
assert coords_for_country("it") is not None
assert coords_for_street_name("Austurstræti") is not None
assert coords_for_street_name("Háaleitisbraut") is not None
assert country_name_for_isocode("DE", lang="is") == "Þýskaland"
assert country_name_for_isocode("DE") == "Þýskaland"
assert isocode_for_country_name("Danmörk", lang="is") == "DK"
assert isocode_for_country_name("Danmörk", lang="IS") == "DK"
assert isocode_for_country_name("Noregur") == "NO"
addr_info = icelandic_addr_info("Fiskislóð 31")
assert addr_info and addr_info["stadur_tgf"] == "Reykjavík"
# Test city info lookup
city_info = lookup_city_info("Kænugarður")
assert city_info and len(
city_info) == 1 and city_info[0]["country"] == "UA"
city_info = lookup_city_info("Kaupmannahöfn")
assert city_info and len(
city_info) == 1 and city_info[0]["country"] == "DK"
city_info = lookup_city_info("Pjongjang")
assert city_info and len(
city_info) == 1 and city_info[0]["country"] == "KP"
city_info = lookup_city_info("Pyongyang")
assert city_info and len(
city_info) == 1 and city_info[0]["country"] == "KP"
# Test address string parsing
assert parse_address_string(" Fiskislóð 31") == {
"street": "Fiskislóð",
"number": 31,
"letter": "",
}
assert parse_address_string("Öldugata 19c ") == {
"street": "Öldugata",
"number": 19,
"letter": "c",
}
assert parse_address_string(" Dúfnahólar 10 ") == {
"street": "Dúfnahólar",
"number": 10,
"letter": "",
}
# Test prepositions for street names
assert iceprep_for_street("Öldugata") == "á"
assert iceprep_for_street("Fiskislóð") == "á"
assert iceprep_for_street("Austurstræti") == "í"
assert iceprep_for_street("Hamrahlíð") == "í"
# Test prepositions for placenames
assert iceprep_for_placename("Dalvík") == "á"
assert iceprep_for_placename("Akureyri") == "á"
assert iceprep_for_placename("Ísafjörður") == "á"
assert iceprep_for_placename("Reykjavík") == "í"
assert iceprep_for_placename("Hafnarfjörður") == "í"
assert iceprep_for_placename("London") == "í"
assert iceprep_for_placename("Dyflinni") == "í"
# Test prepositions for countries
assert iceprep_for_country("Ítalía") == "á"
assert iceprep_for_country("Ísland") == "á"
assert iceprep_for_country("Þýskaland") == "í"
assert iceprep_for_country("Japan") == "í"
assert iceprep_for_country("spánn") == "á"
# Test prepositions for countries, queried by CC
assert iceprep_for_cc("IS") == "á"
assert iceprep_for_cc("US") == "í"
assert iceprep_for_cc("ES") == "á"
assert iceprep_for_cc("es") == "á"
# Test placename capitalization
assert capitalize_placename("ríó de janeiro") == "Ríó de Janeiro"
assert capitalize_placename("vík í mýrdal") == "Vík í Mýrdal"
assert capitalize_placename("Vík í mýrdal") == "Vík í Mýrdal"
assert capitalize_placename("frankfúrt am main") == "Frankfúrt am Main"
assert capitalize_placename("mið-afríkulýðveldið") == "Mið-Afríkulýðveldið"
assert capitalize_placename("Norður-kórea") == "Norður-Kórea"
assert capitalize_placename("norður-Kórea") == "Norður-Kórea"
assert capitalize_placename(
"bosnía og hersegóvína") == "Bosnía og Hersegóvína"
assert capitalize_placename("Norður-Makedónía") == "Norður-Makedónía"
# Distance
assert int(distance((64.141439, -21.943944),
(65.688131, -18.102528))) == 249
assert in_iceland((66.462205, -15.968417))
assert not in_iceland((62.010846, -6.776709))
assert not in_iceland((62.031342, -18.539553))
# US States
assert code_for_us_state("Flórída") == "FL"
assert code_for_us_state("Norður-Karólína") == "NC"
assert code_for_us_state("Kalifornía") == "CA"
assert coords_for_us_state_code("CA") == [36.778261, -119.417932]
# Generic location info lookup functions
assert "country" in location_info("Reykjavík", "placename")
assert "continent" in location_info("Minsk", "placename")
assert location_info("Japan", "country")["continent"] == "AS"
assert location_info("Danmörk", "country")["continent"] == "EU"
assert location_info("Mexíkó", "country")["continent"] == "NA"
assert location_info("ísafjörður", "placename")["continent"] == "EU"
assert location_info("Meðalfellsvatn", "placename")["country"] == "IS"
assert location_info("Georgía", "country")["country"] != "US"
assert location_info("Virginía", "placename")["country"] == "US"
assert location_info("Norður-Dakóta", "country")["country"] == "US"
assert location_info("Kænugarður", "placename")["continent"] == "EU"
assert location_info("Fiskislóð 31", "address")["country"] == "IS"
