Python Program Project

""" Read graphs in Open Street Maps osm format Based on osm.py from brianw's osmgeocode http://github.com/brianw/osmgeocode, which is based on osm.py from comes from Graphserver: http://github.com/bmander/graphserver/tree/master and is copyright (c) 2007, Brandon Martin-Anderson under the BSD License """ import sys sys.path.append('./lib') sys.path.append('./workspace/lib') import xml.sax import copy import networkx def download_osm(left,bottom,right,top): """ Return a filehandle to the downloaded data.""" from urllib import urlopen fp = urlopen( "http://api.openstreetmap.org/api/0.5/map?bbox=%f,%f,%f,%f"%(left,bottom,right,top) ) return fp def read_osm(filename_or_stream, only_roads=True): """Read graph in OSM format from file specified by name or by stream object. Parameters ---------- filename_or_stream : filename or stream object Returns ------- G : Graph Examples -------- >>> G=nx.read_osm(nx.download_osm(-122.33,47.60,-122.31,47.61)) >>> plot([G.node[n]['data'].lat for n in G], [G.node[n]['data'].lon for n in G], ',') """ osm = OSM(filename_or_stream) G = networkx.Graph() for w in osm.ways.itervalues(): if only_roads and 'highway' not in w.tags: continue G.add_path(w.nds, id=w.id, data=w) for n_id in G.nodes_iter(): n = osm.nodes[n_id] G.node[n_id] = dict(data=n) return G class Node: def __init__(self, id, lon, lat): self.id = id self.lon = lon self.lat = lat self.pos = (lat, lon) self.tags = {} def __str__(self): return str(self.id) def __getitem__(self, key): if key == 'id': return self.id if key == 'pos': return (self.lon, self.lat) if key == 'tags': return self.tags def __eq__(self, other): if isinstance(other, Node): return self.id == other.id return False def __hash__(self): return hash(self.id) def __str__(self): return str(self.id) class Way: def __init__(self, id, osm): self.osm = osm self.id = id self.nds = [] self.tags = {} def split(self, dividers): # slice the node-array using this nifty recursive function def slice_array(ar, dividers): for i in range(1,len(ar)-1): if dividers[ar[i]]>1: #print "slice at %s"%ar[i] left = ar[:i+1] right = ar[i:] rightsliced = slice_array(right, dividers) return [left]+rightsliced return [ar] slices = slice_array(self.nds, dividers) # create a way object for each node-array slice ret = [] i=0 for slice in slices: littleway = copy.copy( self ) littleway.id += "-%d"%i littleway.nds = slice ret.append( littleway ) i += 1 return ret class OSM: def __init__(self, filename_or_stream): """ File can be either a filename or stream/file object.""" nodes = {} ways = {} superself = self class OSMHandler(xml.sax.ContentHandler): @classmethod def setDocumentLocator(self,loc): pass @classmethod def startDocument(self): pass @classmethod def endDocument(self): pass @classmethod def startElement(self, name, attrs): if name=='node': self.currElem = Node(attrs['id'], float(attrs['lon']), float(attrs['lat'])) elif name=='way': self.currElem = Way(attrs['id'], superself) elif name=='tag': self.currElem.tags[attrs['k']] = attrs['v'] elif name=='nd': self.currElem.nds.append( attrs['ref'] ) @classmethod def endElement(self,name): if name=='node': nodes[self.currElem.id] = self.currElem elif name=='way': ways[self.currElem.id] = self.currElem @classmethod def characters(self, chars): pass xml.sax.parse(filename_or_stream, OSMHandler) self.nodes = nodes self.ways = ways #count times each node is used node_histogram = dict.fromkeys( self.nodes.keys(), 0 ) for way in self.ways.values(): if len(way.nds) < 2: #if a way has only one node, delete it out of the osm collection del self.ways[way.id] else: for node in way.nds: node_histogram[node] += 1 #use that histogram to split all ways, replacing the member set of ways new_ways = {} for id, way in self.ways.iteritems(): split_ways = way.split(node_histogram) for split_way in split_ways: new_ways[split_way.id] = split_way self.ways = new_ways if __name__ == '__main__': """Converting Atlanta OSM to pickle.""" import math import random import pickle graph = read_osm('atlanta.osm') #graph = read_osm('romania_graph.pickle') new_nodes = {node:graph.nodes[node]['data'] for node in graph.nodes()} euclidean = lambda p1, p2: math.sqrt((p1[0]-p2[0])**2 + (p1[1] - p2[1])**2) * (1 + random.random()) rads = lambda p1, p2: map(math.radians, [p1[0], p1[1], p2[0], p2[1]]) haversine = lambda lat1, long1, lat2, long2: 6371.0 * 2*math.asin(math.sqrt(math.sin(lat2-lat1)**2 + math.cos(lat1) * math.cos(lat2) * math.sin(long2-long1)**2)) new_edges = [(new_nodes[node1], new_nodes[node2], haversine(*rads(new_nodes[node1]['pos'], new_nodes[node2]['pos']))) for node1, node2 in graph.edges()] new_graph = networkx.Graph() [new_graph.add_node(node, data.__dict__) for node, data in new_nodes.items()] [new_graph.add_edge(s.id,t.id,weight=w) for s,t,w in new_edges] for key in new_graph.nodes.keys(): #new_graph.nodes[node]['pos'] = (new_graph.nodes[node]['lat'], new_graph.nodes[node]['lon']) #new_graph.nodes[node]['position'] = (new_graph.nodes[node]['lat'], new_graph.nodes[node]['lon']) new_graph.nodes[key]['pos'] = (new_graph.nodes[key]['lat'], new_graph.nodes[key]['lon']) new_graph.nodes[key]['position'] = (new_graph.nodes[key]['lat'], new_graph.nodes[key]['lon']) pickle.dump( new_graph , open( 'atlanta_osm.pickle' ,'wb') ) print('Done')