def _get_corners(): """ Populate the Global Dictionary, all_corners, with the coordinates of all the nodes in the data set. """ if not all_corners: for tag in soup.find_all('node'): ref = tag.get('id') lat = float(tag.get('lat')) lon = float(tag.get('lon')) grid = latlong2grid(lat, lon) all_corners[ref] = grid.E, grid.N
def get_property_boundary(lat, lon, likely_boundary=None): point = latlong2grid(lat, lon) point = (point.E, point.N) # Check the likely boundary first to save time if likely_boundary and Point(point).within( shape(boundaries[likely_boundary])): return likely_boundary for boundary in boundaries: if Point(point).within(boundaries[boundary]): return boundary raise UnregognisedPropertyLocationException("{},{}".format(lat, lon))
def process_item(self, item, spider): if item['ngr'] is not None: item['ngr'] = self.pad_ngr(item['ngr']) if item['wgS84'] is None and item['ngr'] is None: raise DropItem('wgS84 and ngr not set %s' % item) if item['wgS84'] is None: latlong = grid2latlong(item['ngr'], tag='WGS84') item['wgS84'] = [latlong.latitude, latlong.longitude] if item['ngr'] is None: item['ngr'] = str( latlong2grid(item['wgS84'][0], item['wgS84'][1], tag='WGS84')) return item
def respond(s, xml): ts = datetime.datetime.now().strftime('%Y-%m-%dT%H:%M:%SZ') request = parseCoT(xml) print(ts, request) if request["cmd"] in commands: print(request["lat"], request["lon"]) if (abs(request["lat"]) + abs(request["lon"])) < 1.0: s.sendall( geochat( "Set your location (%.1f,%.1f )before requesting a conversion!" % (request["lat"], request["lon"]), request["atakuid"])) return s.sendall( geochat( "Tranforming location %.5f, %.5f..." % (request["lat"], request["lon"]), request["atakuid"])) # WHAT 3 WORDS if request["cmd"] == "w3w": res = geocoder.convert_to_3wa( what3words.Coordinates(request["lat"], request["lon"])) if "words" in res: s.sendall(geochat(res["words"], request["atakuid"])) else: print(res) s.sendall(geochat(res["error"]["message"], request["atakuid"])) # OSGB / EPSG if request["cmd"] == "os": bng = latlong2grid(request["lat"], request["lon"]) print(bng) s.sendall(geochat(str(bng), request["atakuid"])) else: s.sendall( geochat( "Available services. Ensure you have set your lat/lon either manually or with a GPS", request["atakuid"])) c = 0 while c < len(commands): s.sendall( geochat(commands[c] + ": " + helpers[c], request["atakuid"])) c += 1
def __calculate_bng(self, datum): bng = latlong2grid(self.lat, self.lon, datum) return (bng.E, bng.N)
#!/usr/bin/env python3 # -*- coding: utf-8 -*- """ Created on Thu Dec 5 16:52:58 2019 @author: thomasjhojlunddodd """ from OSGridConverter import latlong2grid import pandapower.networks as pn net = pn.case1888rte(ref_bus_idx=1246) x = range(0, ((len(net.bus_geodata.index)) - 1)) for i in x: g = latlong2grid(net.bus_geodata.x[i], net.bus_geodata.y[i]) net.bus_geodata.x[i] = g.E net.bus_geodata.y[i] = g.N #g = latlong2grid(52.657977,1.716038) #print(g.E, g.N) print(net.bus_geodata)
def convert(latitude, longitude): grid = latlong2grid(float(latitude), float(longitude)) return str(grid)[0:2] + str(grid.E)[1:-2] + str(grid.N)[1:-2]
with open('parking.csv') as csv_file: csv_reader = csv.reader(csv_file, delimiter=';') line_count = 0 for row in csv_reader: if line_count == 0: line_count += 1 else: # print(row[8] +', manchester , UK', ) responce = requests.get( 'https://maps.googleapis.com/maps/api/geocode/json?address=' + row[8] + ', manchester, uk&key=AIzaSyCAcR729aS6d0hfZGpLWsDBBuK1X0hFpB8') lattitude = responce.json( )['results'][0]['geometry']['location']['lat'] longtitude = ( responce.json()['results'][0]['geometry']['location']['lng']) line_count += 1 grid = latlong2grid(lattitude, longtitude) grifref = [(str(grid)[0:2] + str(grid.E)[1:-2] + str(grid.N)[1:-2]) ] # print(grifref) # p= csv.writer(grifref) with open("output.csv", 'a') as finalfile: wr = csv.writer(finalfile, dialect='excel') wr.writerow(grifref)
stations = { 'IDs': ['W001', 'W006', 'W018', 'W026', 'PC', 'CH'], 'Names': [ 'Sutton Park', 'Handsworth', 'Hodge Hill', 'Elms Road', 'Paradise Circus', 'Coleshill' ], 'Lat': [52.566353, 52.50451, 52.49249, 52.45638, 52.4806, 52.48015], 'Lon': [-1.83791, -1.92291, -1.80763, -1.92767, -1.90493, -1.69075] } # Transform co-ordinates for met stations gridn = [] gride = [] for i, j in zip(stations['Lat'], stations['Lon']): g = latlong2grid(i, j) gridn.append(g.N) gride.append(g.E) stations['gridn'] = gridn stations['gride'] = gride print(gridn, gride) # Now we have sufficient information for be able to plot our overview map. fig, ax = plt.subplots(figsize=(4, 4)) ax.set_aspect('equal') df_bound.plot(ax=ax, zorder=-1, alpha=1, color='white', edgecolors='grey') brum.plot(ax=ax, zorder=-1, alpha=0.7, color='lightgrey', edgecolors='grey') df_broad.plot(ax=ax, color='tan')