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')