def handle(self, *args, **options):
event = get_event_from_options(options)
rpqs = RacePoint.objects.filter(event=event)
i = 0
n = rpqs.count()
if not n:
print "No race points for this event. You may import a course using import_race_course"
return
meanlat = rpqs.aggregate(Avg("latitude"))["latitude__avg"]
osmdataradius = int(options["data_radius"])
osmlongdelta = calculate_easting_delta(meanlat, osmdataradius)
osmlatdelta = osmdataradius * 90./10000000.
osmendpoint = options["endpoint_url"]
if options["use_ssl"]:
osmendpoint = osmendpoint.replace("http://","https://")
for rp in rpqs:
i += 1
print "Fetching data for point %d/%d"%(i,n)
try:
query = '[out:json];way(%.6f,%.6f,%.6f,%.6f)["name"];out meta;'%(
rp.latitude-osmlatdelta,
rp.longitude-osmlongdelta,
rp.latitude+osmlatdelta,
rp.longitude+osmlongdelta)
result = urllib2.urlopen(osmendpoint, query)
jsondata = json.loads(result.read())
elements = []
for element in jsondata["elements"]:
tags = element["tags"]
elementtype = tags.get("amenity", "unknown")
for key in [
("building","building"),
("highway","road"),
("shop","shop"),
("leisure","leisure"),
("tourism","tourism"),
("waterway","waterway")]:
if key[0] in tags:
elementtype = key[1]
if ([tags["name"], elementtype] not in elements):
elements.append([tags["name"], elementtype])
postcode = tags.get("postal_code", tags.get("addr:postcode","")).split(" ")[0]
if postcode and ([postcode,"postcode"] not in elements):
elements.append([postcode,"postcode"])
print ", ".join([e[0] for e in elements])
LocationDistance.objects.filter(reference_point=rp).exclude(location_name__type="race marker").delete()
for element in elements:
locname, created = LocationName.objects.get_or_create(
name = element[0],
type = element[1])
LocationDistance.objects.create(
location_name = locname,
accuracy = osmdataradius,
reference_point = rp)
except Exception, e:
print "Error", e
def handle(self, *args, **options):
event = get_event_from_options(options)
rpqs = RacePoint.objects.filter(event=event)
i = 0
n = rpqs.count()
if not n:
print "No race points for this event. You may import a course using import_race_course"
return
meanlat = rpqs.aggregate(Avg("latitude"))["latitude__avg"]
osmdataradius = int(options["data_radius"])
osmlongdelta = calculate_easting_delta(meanlat, osmdataradius)
osmlatdelta = osmdataradius * 90. / 10000000.
osmendpoint = options["endpoint_url"]
if options["use_ssl"]:
osmendpoint = osmendpoint.replace("http://", "https://")
for rp in rpqs:
i += 1
print "Fetching data for point %d/%d" % (i, n)
try:
query = '[out:json];way(%.6f,%.6f,%.6f,%.6f)["name"];out meta;' % (
rp.latitude - osmlatdelta, rp.longitude - osmlongdelta,
rp.latitude + osmlatdelta, rp.longitude + osmlongdelta)
result = urllib2.urlopen(osmendpoint, query)
jsondata = json.loads(result.read())
elements = []
for element in jsondata["elements"]:
tags = element["tags"]
elementtype = tags.get("amenity", "unknown")
for key in [("building", "building"), ("highway", "road"),
("shop", "shop"), ("leisure", "leisure"),
("tourism", "tourism"),
("waterway", "waterway")]:
if key[0] in tags:
elementtype = key[1]
if ([tags["name"], elementtype] not in elements):
elements.append([tags["name"], elementtype])
postcode = tags.get("postal_code",
tags.get("addr:postcode",
"")).split(" ")[0]
if postcode and ([postcode, "postcode"] not in elements):
elements.append([postcode, "postcode"])
print ", ".join([e[0] for e in elements])
LocationDistance.objects.filter(reference_point=rp).exclude(
location_name__type="race marker").delete()
for element in elements:
locname, created = LocationName.objects.get_or_create(
name=element[0], type=element[1])
LocationDistance.objects.create(location_name=locname,
accuracy=osmdataradius,
reference_point=rp)
except Exception, e:
print "Error", e
def handle(self, *args, **options):
event = get_event_from_options(options)
print "Clearing Distance points for %s"%event.name
VideoDistance.objects.filter(video__event=event).delete()
rpqs = RacePoint.objects.filter(event=event)
if not rpqs.exists():
print "No race points for this event. You may import a course using import_race_course"
return
meanlat = rpqs.aggregate(Avg("latitude"))["latitude__avg"]
maxtolerance = 500.
longtolerance = calculate_easting_delta(meanlat, maxtolerance)
lattolerance = maxtolerance * 90./10000000.
otherleg = maxtolerance * 2
pointcache = {}
vqs = Video.objects.filter(event=event)
for v in vqs:
print "Finding location for video %s"%v.id
locobj = None
for delta in [0,10,30,60,120,300,600]:
rtqs = RunnerTag.objects.filter(
time__gte=v.start_time - datetime.timedelta(0,delta),
time__lte=v.end_time + datetime.timedelta(0,delta),
video__spectator=v.spectator,
)
if rtqs.exists():
locobj = rtqs.order_by("-time").first()
print "Used RunnerTag from a timespan of %d seconds around Video"%delta
break
puqs = PositionUpdate.objects.filter(
time__gte=v.start_time - datetime.timedelta(0,delta),
time__lte=v.end_time + datetime.timedelta(0,delta),
spectator=v.spectator,
)
if puqs.exists():
locobj = puqs.order_by("-time").first()
print "Used PositionUpdate from a timespan of %d seconds around Video"%delta
break
if locobj and locobj.latitude != 0:
point = (locobj.latitude, locobj.longitude)
gppoint = Point(point)
cachekey = "%.5f|%.5f"%point
if cachekey in pointcache:
bestpoints = pointcache[cachekey]
else:
candidateqs = rpqs.filter(
latitude__gt = point[0] - lattolerance,
latitude__lt = point[0] + lattolerance,
longitude__gt = point[1] - longtolerance,
longitude__lt = point[1] + longtolerance)
candidatepoints = [
{ "delta": distance.distance(Point(p.latitude,p.longitude),gppoint).m, "point": p}
for p in candidateqs]
candidatepoints = [p for p in candidatepoints if p["delta"] < maxtolerance]
candidatepoints.sort(key=lambda p: p["delta"])
bestpoints = []
if not candidatepoints:
print "Video is too far from the race"
while candidatepoints:
lastdist = candidatepoints[0]["point"].distance
bestpoints.append(candidatepoints[0])
candidatepoints = [p for p in candidatepoints if p["delta"] < locobj.accuracy and abs(p["point"].distance-lastdist) > otherleg]
pointcache[cachekey] = bestpoints
if (len(bestpoints) > 1):
print "Ambiguous location: %s"%(",".join(["%dm"%p["point"].distance for p in bestpoints]))
pointcache[cachekey] = bestpoints
for pt in bestpoints:
VideoDistance.objects.create(
video = v,
reference_point = pt["point"],
accuracy = max(10, locobj.accuracy, pt["delta"])
)
else:
print "No location found for Video"
print "%d video distances inserted"%VideoDistance.objects.filter(video__event=event).count()
