def dist_to_all_nds(self, lon, lat):
## Needs optimization, write a numpy version of computeDist
return map((
lambda i: {
'id': self.node_ids[i],
'dist': computeDist(lon, lat, self.node_lons[i], self.
node_lats[i])
}), range(len(self.node_ids)))
def dist_to_all_nds(self, lon, lat):
## Needs optimization, write a numpy version of computeDist
return map((lambda i : {'id' : self.node_ids[i],
'dist' : computeDist(lon,
lat,
self.node_lons[i],
self.node_lats[i])}),
range(len(self.node_ids)))
# start = my_network.lkd_nds.keys()[0] end = 240469798 # # Get their latitudes and longitudes # lon_1 = my_network.lkd_nds[start]['lon'] lat_1 = my_network.lkd_nds[start]['lat'] lon_2 = my_network.lkd_nds[end]['lon'] lat_2 = my_network.lkd_nds[end]['lat'] # # Compute the distance between the two nodes # dist = computeDist(lon_1, lat_1, lon_2, lat_2) # # Compute all paths betwoeen start and end whose length is below dist * 1.35 # path_finding_result = my_network.find_all_paths(start, end, dist * 1.35) # # Extract the ids along the first path (the shortest) # path_points = path_finding_result['paths'][1] # # Plot the path onto the network # #===============================================================================
def l2_dist(node_1, node_2):
lat_1 = float(node_1.get('lat'))
lon_1 = float(node_1.get('lon'))
lat_2 = float(node_2.get('lat'))
lon_2 = float(node_2.get('lon'))
return computeDist(lon_1, lat_1, lon_2, lat_2)
