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[sumo-user] Error In SumoLib Graph traversing (Harald Schaefer)

Dear Sir,
Your solution worked. I have used self.size = len(graph.edges).

But now the issued is that this code stuck in some loop. and i am not able to identify. Would you please help? 

Code is attached here with.

This code will help others to know how to implement ant colony optimization with sumo. as currently i am not getting this kind of code anywhere. So If this would get done,would help me and others.

On Sun, Mar 17, 2019 at 4:37 PM <sumo-user-request@xxxxxxxxxxx> wrote:
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Today's Topics:

   1. Re: Error In SumoLib Graph traversing (Harald Schaefer)


----------------------------------------------------------------------

Message: 1
Date: Sun, 17 Mar 2019 09:36:53 +0100
From: Harald Schaefer <fechsaer@xxxxxxxxx>
To: sumo-user@xxxxxxxxxxx
Subject: Re: [sumo-user] Error In SumoLib Graph traversing
Message-ID: <bbfb588d-83e4-c672-ecb3-c6a82a4cdff4@xxxxxxxxx>
Content-Type: text/plain; charset="utf-8"

Hi Bijal,

as I understand your code graph is initialized like
?? graph = sumolib.net.readNet('Dijkstra1.net.xml')

you can asked either for the numbers of edges like
?? len(graph.getEdges())
or for the numbers of nodes like
? len(graph.getNodes())

See the SUMO wiki for methods of Net
https://sumo.dlr.de/daily/pydoc/sumolib.net.html

Best regards, Harald

Am 17.03.19 um 05:46 schrieb Bijal:
> Thanks for answer Harald & Jakob
>
> Actually I am trying to build adjecency matrix using this code.
>
> Graph class has add vertex and add edge function.
>
> I have added first edges and then vertex.
>
> Plz help me to resolve the issue.
>
> Jakob I can solve this issue by myself,But for me python is little new.?
>
> But as per your suggestion i have tried hard to solve issue by my
> self. But unfortunatly failed.
>
> Thanks for reply once again.
>
> On Sun 17 Mar, 2019, 3:48 AM , <sumo-user-request@xxxxxxxxxxx
> <mailto:sumo-user-request@xxxxxxxxxxx>> wrote:
>
>     Send sumo-user mailing list submissions to
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>
>     To subscribe or unsubscribe via the World Wide Web, visit
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>     or, via email, send a message with subject or body 'help' to
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>     <mailto:sumo-user-request@xxxxxxxxxxx>
>
>     You can reach the person managing the list at
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>     <mailto:sumo-user-owner@xxxxxxxxxxx>
>
>     When replying, please edit your Subject line so it is more specific
>     than "Re: Contents of sumo-user digest..."
>
>
>     Today's Topics:
>
>     ? ?1. Re: Problem with changing lanes (Jakob Erdmann)
>     ? ?2. Re: Error In SumoLib Graph traversing (Harald Schaefer)
>
>
>     ----------------------------------------------------------------------
>
>     Message: 1
>     Date: Sat, 16 Mar 2019 17:45:03 +0100
>     From: Jakob Erdmann <namdre.sumo@xxxxxxxxx
>     <mailto:namdre.sumo@xxxxxxxxx>>
>     To: Sumo project User discussions <sumo-user@xxxxxxxxxxx
>     <mailto:sumo-user@xxxxxxxxxxx>>
>     Subject: Re: [sumo-user] Problem with changing lanes
>     Message-ID:
>     ? ? ? ?
>     <CAMbUcbxbSgB8tGkWD6VPhW+qhP68J1HSOredi83NxeON063U2w@xxxxxxxxxxxxxx
>     <mailto:CAMbUcbxbSgB8tGkWD6VPhW%2BqhP68J1HSOredi83NxeON063U2w@xxxxxxxxxxxxxx>>
>     Content-Type: text/plain; charset="utf-8"
>
>     Hello,
>     the issue is now fixed (https://github.com/eclipse/sumo/issues/5309).
>     Thanks for reporting.
>
>     Regarding the effect of the duration:
>     The longer duration does not change the urgency of the lane change
>     attempt.
>     Rather it controls the time after which the change attempt is
>     aborted if
>     unsuccessful.
>     The urgency currently only has two levels (urgent and non-urgent)
>     which can
>     be controlled using setLaneChangeMode
>     https://sumo.dlr.de/wiki/TraCI/Change_Vehicle_State#lane_change_mode_.280xb6.29
>     (bits 8 and 9 both set to 1)
>
>     regards,
>     Jakob
>
>     Am Fr., 15. M?rz 2019 um 18:00 Uhr schrieb H?bner, Karl <
>     karl.huebner@xxxxxxxxxxxxxxxxxxx
>     <mailto:karl.huebner@xxxxxxxxxxxxxxxxxxx>>:
>
>     > Dear SUMO devs,
>     >
>     >
>     >
>     > I use changeLaneRelative(1, 3) for a vehicle for changing its
>     lane to the
>     > left. If I would do this right before an edge with more lanes
>     than my
>     > current edge, the vehicle would switch to the left as expected
>     but right
>     > after driving onto the next edge it switches back again to the
>     next right
>     > lane, since the lane index has changed. I attached an example script
>     > demonstrating this behavior.
>     >
>     >
>     >
>     > This is currently a huge problem for us, do you have any idea
>     how to solve
>     > this?
>     >
>     >
>     >
>     > Another problem I have with the changeLane-command is that with
>     short
>     > durations the lane change tends to be more aggressive and
>     distorts upstream
>     > traffic. Therefore I thought I choose longer durations in the
>     hope that the
>     > lane change model has more time to do necessary safety checks.
>     Is this even
>     > the case?
>     >
>     >
>     >
>     > Thanks in advance and kind regards,
>     >
>     > Karl
>     >
>     >
>     > _______________________________________________
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>
>     ------------------------------
>
>     Message: 2
>     Date: Sat, 16 Mar 2019 23:17:50 +0100
>     From: Harald Schaefer <fechsaer@xxxxxxxxx <mailto:fechsaer@xxxxxxxxx>>
>     To: sumo-user@xxxxxxxxxxx <mailto:sumo-user@xxxxxxxxxxx>
>     Subject: Re: [sumo-user] Error In SumoLib Graph traversing
>     Message-ID: <baebc87b-5d7d-39d8-f573-899893a621b6@xxxxxxxxx
>     <mailto:baebc87b-5d7d-39d8-f573-899893a621b6@xxxxxxxxx>>
>     Content-Type: text/plain; charset="utf-8"
>
>     Hello Bijal
>
>     you asked for the len of a graph.
>     A graph consists of edges and nodes, I think you need to specify
>     whether
>     you want to get the number of edges or nodes.
>
>     Regards? Harald
>
>     Am 16.03.19 um 15:39 schrieb Jakob Erdmann:
>     > The error does not come from sumo but from your own classes and I
>     > cannot help you with those. I advise you to find a programmer
>     locally
>     > who can guide your efforts.
>     > regards,
>     > Jakob
>     >
>     > Am Sa., 16. M?rz 2019 um 13:30?Uhr schrieb Bijal
>     > <bijal.varia88@xxxxxxxxx <mailto:bijal.varia88@xxxxxxxxx>
>     <mailto:bijal.varia88@xxxxxxxxx <mailto:bijal.varia88@xxxxxxxxx>>>:
>     >
>     >? ? ?Dear Sir,
>     >
>     >? ? ?I am trying to set graph for Ant colony algorithm
>     implementation.
>     >? ? ?But I am getting Error says :?
>     >
>     >? ? ? ? ?Traceback (most recent call last):
>     >
>     >? ? ? ? ?? File "hay4_ACO.py", line 317, in <module>
>     >
>     >? ? ? ? ?? ? main()
>     >
>     >? ? ? ? ?? File "hay4_ACO.py", line 278, in main
>     >
>     >? ? ? ? ?? ? aco.set_graph(Objgraph_mat)
>     >
>     >? ? ? ? ?? File "hay4_ACO.py", line 111, in set_graph
>     >
>     >? ? ? ? ?? ? self.size = len(graph)
>     >
>     >? ? ? ? ?AttributeError: Graph_mat instance has no attribute
>     '__len__'
>     >
>     >
>     >
>     >? ? ?Please help me to resolve this issue. I am new bee in this &
>     Some
>     >? ? ?how i have managed to get myself up to this.
>     >
>     >? ? ?*Code Is :*
>     >? ? ?*
>     >? ? ?*
>     >
>     >
>     >? ? ? ? ?import os, sys
>     >
>     >? ? ? ? ?import optparse
>     >
>     >? ? ? ? ?import subprocess
>     >
>     >? ? ? ? ?import random
>     >
>     >? ? ? ? ?from Queue import PriorityQueue
>     >
>     >? ? ? ? ?import xml.sax
>     >
>     >? ? ? ? ?from xml.sax import saxutils, parse, make_parser, handler
>     >
>     >? ? ? ? ?from copy import copy
>     >
>     >? ? ? ? ?from itertools import *
>     >
>     >
>     >? ? ? ? ?SUMO_HOME = "/home/dhaval/sumo-1.0.0/"
>     >
>     >
>     >? ? ? ? ?try:
>     >
>     >? ? ? ? ?? ? sys.path.append(os.path.join(SUMO_HOME, "tools"))
>     >
>     >? ? ? ? ?? ? # import the library
>     >
>     >? ? ? ? ?? ? import sumolib
>     >
>     >? ? ? ? ?? ? from sumolib import checkBinary
>     >
>     >? ? ? ? ?? ? from sumolib.net <http://sumolib.net>
>     <http://sumolib.net> import Net
>     >
>     >? ? ? ? ?? ? from sumolib.net <http://sumolib.net>
>     <http://sumolib.net> import NetReader
>     >
>     >? ? ? ? ?? ? from sumolib.net <http://sumolib.net>
>     <http://sumolib.net> import Lane
>     >
>     >? ? ? ? ?? ? from sumolib.net <http://sumolib.net>
>     <http://sumolib.net> import Edge
>     >
>     >? ? ? ? ?? ? from sumolib.net <http://sumolib.net>
>     <http://sumolib.net> import Node
>     >
>     >? ? ? ? ?? ? from sumolib.net <http://sumolib.net>
>     <http://sumolib.net> import Connection
>     >
>     >? ? ? ? ?? ? from sumolib.net <http://sumolib.net>
>     <http://sumolib.net> import Roundabout
>     >
>     >? ? ? ? ?? ? ? ?
>     >
>     >? ? ? ? ?except ImportError:
>     >
>     >? ? ? ? ?? ? sys.exit("please declare environment variable
>     'SUMO_HOME'
>     >? ? ? ? ?as the root directory of your sumo installation (it should
>     >? ? ? ? ?contain folders 'bin', 'tools' and 'docs')")
>     >
>     >
>     >? ? ? ? ?import random
>     >
>     >? ? ? ? ?graph = sumolib.net.readNet('Dijkstra1.net.xml')
>     >
>     >
>     >? ? ? ? ?import traci
>     >
>     >? ? ? ? ?# the port used for communicating with your sumo instance
>     >
>     >? ? ? ? ?PORT = 8873
>     >
>     >
>     >? ? ? ? ?# implementation of an undirected graph using Adjacency
>     >? ? ? ? ?Matrix, with weighted or unweighted edges
>     >
>     >? ? ? ? ?class Vertex:
>     >
>     >? ? ? ? ?def __init__(self, n):
>     >
>     >? ? ? ? ?self.name <http://self.name> <http://self.name> = n
>     >
>     >
>     >? ? ? ? ?class Graph_mat:
>     >
>     >? ? ? ? ?vertices = {}
>     >
>     >? ? ? ? ?edges = []
>     >
>     >? ? ? ? ?edge_indices = {}
>     >
>     >
>     >? ? ? ? ?def add_vertex(self, vertex):
>     >
>     >? ? ? ? ?if isinstance(vertex, Vertex) and vertex.name
>     <http://vertex.name>
>     >? ? ? ? ?<http://vertex.name> not in self.vertices:
>     >
>     >? ? ? ? ?self.vertices[vertex.name <http://vertex.name>
>     <http://vertex.name>] = vertex
>     >
>     >? ? ? ? ?for row in self.edges:
>     >
>     >? ? ? ? ?row.append(0)
>     >
>     >? ? ? ? ?self.edges.append([0] * (len(self.edges)+1))
>     >
>     >? ? ? ? ?self.edge_indices[vertex.name <http://vertex.name>
>     <http://vertex.name>] =
>     >? ? ? ? ?len(self.edge_indices)
>     >
>     >? ? ? ? ?return True
>     >
>     >? ? ? ? ?else:
>     >
>     >? ? ? ? ?return False
>     >
>     >
>     >? ? ? ? ?def add_edge(self, u, v, weight=1):
>     >
>     >? ? ? ? ?if u in self.vertices and v in self.vertices:
>     >
>     >? ? ? ? ?self.edges[self.edge_indices[u]][self.edge_indices[v]] =
>     weight
>     >
>     >? ? ? ? ?self.edges[self.edge_indices[v]][self.edge_indices[u]] =
>     weight
>     >
>     >? ? ? ? ?return True
>     >
>     >? ? ? ? ?else:
>     >
>     >? ? ? ? ?return False
>     >
>     >? ? ? ? ?def print_graph(self):
>     >
>     >? ? ? ? ?for v, i in sorted(self.edge_indices.items()):
>     >
>     >? ? ? ? ?print(v + ' ')
>     >
>     >? ? ? ? ?for j in range(len(self.edges)):
>     >
>     >? ? ? ? ?print(self.edges[i][j])
>     >
>     >? ? ? ? ?print(' ')
>     >
>     >
>     >? ? ? ? ?class Ant():
>     >
>     >
>     >? ? ? ? ?? ? def __init__(self):
>     >
>     >? ? ? ? ?? ? ? ? self.cost = 0
>     >
>     >? ? ? ? ?? ? ? ? self.trace = [0]
>     >
>     >
>     >? ? ? ? ?? ? def start_travel(self):
>     >
>     >? ? ? ? ?? ? ? ? self.cost = 0
>     >
>     >? ? ? ? ?? ? ? ? self.trace = [0]
>     >
>     >
>     >? ? ? ? ?? ? def add_vertex(self, _vertex, _cost):
>     >
>     >? ? ? ? ?? ? ? ? self.trace.append(_vertex)
>     >
>     >? ? ? ? ?? ? ? ? self.cost += _cost
>     >
>     >
>     >? ? ? ? ?? ? def get_position(self):
>     >
>     >? ? ? ? ?? ? ? ? return self.trace[-1]
>     >
>     >
>     >? ? ? ? ?? ? def get_cost(self):
>     >
>     >? ? ? ? ?? ? ? ? return self.cost
>     >
>     >
>     >? ? ? ? ?? ? def get_path(self):
>     >
>     >? ? ? ? ?? ? ? ? path = []
>     >
>     >? ? ? ? ?? ? ? ? for i in range(len(self.trace) - 1):
>     >
>     >? ? ? ? ?? ? ? ? ? ? path.append((self.trace[i], self.trace[i + 1]))
>     >
>     >
>     >? ? ? ? ?? ? ? ? return path
>     >
>     >
>     >
>     >? ? ? ? ?class ACOAlgorithm():
>     >
>     >? ? ? ? ?? ? '''
>     >
>     >? ? ? ? ?? ? Ant colony optimization algorithms to find shortest path
>     >
>     >? ? ? ? ?? ? '''
>     >
>     >
>     >? ? ? ? ?? ? def __init__(self):
>     >
>     >? ? ? ? ?? ? ? ? self.evaporation_rate = 0.8
>     >
>     >? ? ? ? ?? ? ? ? self.threshhold = 0.5
>     >
>     >? ? ? ? ?? ? ? ? self.remain_path = 0
>     >
>     >
>     >? ? ? ? ?? ? def set_graph(self, graph):
>     >
>     >? ? ? ? ?? ? ? ? self.size = len(graph)
>     >
>     >
>     >? ? ? ? ?? ? ? ? self.num_ant = 20*self.size ** 2
>     >
>     >? ? ? ? ?? ? ? ? self.ant = [Ant() for _ in range(self.num_ant)]
>     >
>     >
>     >
>     >? ? ? ? ?? ? ? ? self.distance = graph
>     >
>     >? ? ? ? ?? ? ? ? self.pheromones = [[1.0]* self.size for _ in
>     >? ? ? ? ?range(self.size)]
>     >
>     >
>     >? ? ? ? ?? ? ? ? max_distance = 0
>     >
>     >? ? ? ? ?? ? ? ? for i in range(len(self.distance)):
>     >
>     >? ? ? ? ?? ? ? ? ? ? for j in range(len(self.distance[0])):
>     >
>     >? ? ? ? ?? ? ? ? ? ? ? ? if self.distance[i][j] > max_distance:
>     >
>     >? ? ? ? ?? ? ? ? ? ? ? ? ? ? max_distance = self.distance[i][j]
>     >
>     >
>     >? ? ? ? ?? ? ? ? for i in range(len(self.distance)):
>     >
>     >? ? ? ? ?? ? ? ? ? ? for j in range(len(self.distance[0])):
>     >
>     >? ? ? ? ?? ? ? ? ? ? ? ? if self.distance[i][j] > 0:
>     >
>     >? ? ? ? ?? ? ? ? ? ? ? ? ? ? self.distance[i][j] /= max_distance*1.0
>     >
>     >? ? ? ? ?? ? ? ? ? ? ? ? else:
>     >
>     >? ? ? ? ?? ? ? ? ? ? ? ? ? ? self.pheromones[i][j] = -1.0
>     >
>     >
>     >? ? ? ? ?? ? def process(self):
>     >
>     >? ? ? ? ?? ? ? ? while True:
>     >
>     >? ? ? ? ?? ? ? ? ? ? self._start_travel()
>     >
>     >? ? ? ? ?? ? ? ? ? ? self._find_edge()
>     >
>     >? ? ? ? ?? ? ? ? ? ? if self._finish_travel():
>     >
>     >? ? ? ? ?? ? ? ? ? ? ? ? break
>     >
>     >
>     >? ? ? ? ?? ? ? ? for i in range(self.num_ant):
>     >
>     >? ? ? ? ?? ? ? ? ? ? if len(self.ant[i].trace) == self.size:
>     >
>     >? ? ? ? ?? ? ? ? ? ? ? ? print 'trace %s' % (self.ant[i].trace)
>     >
>     >? ? ? ? ?? ? ? ? ? ? ? ? break
>     >
>     >
>     >? ? ? ? ?? ? def _start_travel(self):
>     >
>     >? ? ? ? ?? ? ? ? for i in range(self.num_ant):
>     >
>     >? ? ? ? ?? ? ? ? ? ? self.ant[i].start_travel()
>     >
>     >
>     >? ? ? ? ?? ? def _find_edge(self):
>     >
>     >? ? ? ? ?? ? ? ? while not self._have_ant_completed():
>     >
>     >? ? ? ? ?? ? ? ? ? ? for i in range(len(self.ant)):
>     >
>     >? ? ? ? ?? ? ? ? ? ? ? ? available_edge = 0
>     >
>     >? ? ? ? ?? ? ? ? ? ? ? ? for e in range(self.size):
>     >
>     >? ? ? ? ?? ? ? ? ? ? ? ? ? ? if e not in self.ant[i].trace and
>     >? ? ? ? ?self.pheromones[self.ant[i].get_position()][e] > 0:
>     >
>     >? ? ? ? ?? ? ? ? ? ? ? ? ? ? ? ? available_edge +=? (2.0 -
>     >? ? ? ?
>     ?self.distance[self.ant[i].get_position()][e])*self.pheromones[self.ant[i].get_position()][e]
>     >
>     >
>     >? ? ? ? ?? ? ? ? ? ? ? ? last_e = -1
>     >
>     >? ? ? ? ?? ? ? ? ? ? ? ? prob_edge = 0
>     >
>     >? ? ? ? ?? ? ? ? ? ? ? ? prob_random = random.uniform(0.0, 1.0)
>     >
>     >? ? ? ? ?? ? ? ? ? ? ? ? for e in range(self.size):
>     >
>     >? ? ? ? ?? ? ? ? ? ? ? ? ? ? if e not in self.ant[i].trace and
>     >? ? ? ? ?self.pheromones[self.ant[i].get_position()][e] > 0:
>     >
>     >? ? ? ? ?? ? ? ? ? ? ? ? ? ? ? ? prob_edge += (2.0 -
>     >? ? ? ?
>     ?self.distance[self.ant[i].get_position()][e])*self.pheromones[self.ant[i].get_position()][e]/available_edge
>     >
>     >? ? ? ? ?? ? ? ? ? ? ? ? ? ? ? ? last_e = e
>     >
>     >? ? ? ? ?? ? ? ? ? ? ? ? ? ? ? ? if prob_edge >= prob_random:
>     >
>     >? ? ? ? ?? ? ? ? ? ? ? ? ? ? ? ? ? ? break
>     >
>     >? ? ? ? ?? ? ? ? ? ? ? ? if last_e >= 0:
>     >
>     >? ? ? ? ?? ? ? ? ? ? ? ? ? ? self.ant[i].add_vertex(last_e,
>     >? ? ? ? ?self.distance[self.ant[i].get_position()][last_e])
>     >
>     >? ? ? ? ?? ? ? ? ? ? ? ? else:
>     >
>     >? ? ? ? ?? ? ? ? ? ? ? ? ? ? self.ant[i].start_travel()
>     >
>     >
>     >? ? ? ? ?? ? def _finish_travel(self):
>     >
>     >? ? ? ? ?? ? ? ? # find short path
>     >
>     >? ? ? ? ?? ? ? ? avg_cost = 0
>     >
>     >? ? ? ? ?? ? ? ? ant_completed = 0
>     >
>     >? ? ? ? ?? ? ? ? for i in range(len(self.ant)):
>     >
>     >? ? ? ? ?? ? ? ? ? ? if len(self.ant[i].trace) == self.size:
>     >
>     >? ? ? ? ?? ? ? ? ? ? ? ? avg_cost += self.ant[i].get_cost()
>     >
>     >? ? ? ? ?? ? ? ? ? ? ? ? ant_completed += 1
>     >
>     >? ? ? ? ?? ? ? ? avg_cost /= ant_completed
>     >
>     >
>     >? ? ? ? ?? ? ? ? # update pheromones
>     >
>     >? ? ? ? ?? ? ? ? for i in range(len(self.pheromones)):
>     >
>     >? ? ? ? ?? ? ? ? ? ? for j in range(len(self.pheromones[0])):
>     >
>     >? ? ? ? ?? ? ? ? ? ? ? ? if self.pheromones[i][j] > 0:
>     >
>     >? ? ? ? ?? ? ? ? ? ? ? ? ? ? self.pheromones[i][j] *= (1 -
>     >? ? ? ? ?self.evaporation_rate)
>     >
>     >
>     >? ? ? ? ?? ? ? ? for i in range(len(self.ant)):
>     >
>     >? ? ? ? ?? ? ? ? ? ? if self.ant[i].get_cost() < avg_cost:
>     >
>     >? ? ? ? ?? ? ? ? ? ? ? ? update_pheromones = self.ant[i].get_path()
>     >
>     >? ? ? ? ?? ? ? ? ? ? ? ? for x,y in update_pheromones:
>     >
>     >? ? ? ? ?? ? ? ? ? ? ? ? ? ? self.pheromones[x][y]? +=
>     >? ? ? ? ?avg_cost/self.ant[i].get_cost()
>     >
>     >
>     >? ? ? ? ?? ? ? ? # remove path has small pheromones
>     >
>     >? ? ? ? ?? ? ? ? if self.remain_path > 2*(self.size - 1):
>     >
>     >? ? ? ? ?? ? ? ? ? ? for i in range(len(self.pheromones)):
>     >
>     >? ? ? ? ?? ? ? ? ? ? ? ? for j in range(len(self.pheromones[0])):
>     >
>     >? ? ? ? ?? ? ? ? ? ? ? ? ? ? if self.pheromones[i][j] <=
>     self.threshhold:
>     >
>     >? ? ? ? ?? ? ? ? ? ? ? ? ? ? ? ? self.pheromones[i][j] = -1.0
>     >
>     >? ? ? ? ?? ? ? ? else:
>     >
>     >? ? ? ? ?? ? ? ? ? ? min_pheromones = 999999.99
>     >
>     >? ? ? ? ?? ? ? ? ? ? for i in range(len(self.pheromones)):
>     >
>     >? ? ? ? ?? ? ? ? ? ? ? ? for j in range(len(self.pheromones[0])):
>     >
>     >? ? ? ? ?? ? ? ? ? ? ? ? ? ? if min_pheromones >
>     self.pheromones[i][j] > 0:
>     >
>     >? ? ? ? ?? ? ? ? ? ? ? ? ? ? ? ? min_pheromones =
>     self.pheromones[i][j]
>     >
>     >
>     >? ? ? ? ?? ? ? ? ? ? for i in range(len(self.pheromones)):
>     >
>     >? ? ? ? ?? ? ? ? ? ? ? ? for j in range(len(self.pheromones[0])):
>     >
>     >? ? ? ? ?? ? ? ? ? ? ? ? ? ? if self.pheromones[i][j] <=
>     min_pheromones:
>     >
>     >? ? ? ? ?? ? ? ? ? ? ? ? ? ? ? ? self.pheromones[i][j] = -1.0
>     >
>     >
>     >? ? ? ? ?? ? ? ? # check exist only one path
>     >
>     >? ? ? ? ?? ? ? ? self.remain_path = 0
>     >
>     >? ? ? ? ?? ? ? ? for i in range(len(self.pheromones)):
>     >
>     >? ? ? ? ?? ? ? ? ? ? for j in range(len(self.pheromones[0])):
>     >
>     >? ? ? ? ?? ? ? ? ? ? ? ? if self.pheromones[i][j] > 0:
>     >
>     >? ? ? ? ?? ? ? ? ? ? ? ? ? ? self.remain_path += 1
>     >
>     >
>     >? ? ? ? ?? ? ? ? return self.remain_path < self.size
>     >
>     >
>     >? ? ? ? ?? ? def _have_ant_completed(self):
>     >
>     >? ? ? ? ?? ? ? ? for i in range(len(self.ant)):
>     >
>     >? ? ? ? ?? ? ? ? ? ? if len(self.ant[i].trace) == self.size:
>     >
>     >? ? ? ? ?? ? ? ? ? ? ? ? return True
>     >
>     >? ? ? ? ?? ? ? ? return False
>     >
>     >
>     >
>     >
>     >
>     >? ? ? ? ?def AntColony(graph, start, end=None):
>     >
>     >? ? ? ? ?? ? ? ? D = {}# dictionary of final distances
>     >
>     >? ? ? ? ?P = {}# dictionary of predecessors
>     >
>     >
>     >
>     >
>     >? ? ? ? ?return (D,P)
>     >
>     >? ? ? ? ?? ? ? ??
>     >
>     >? ? ? ? ?def shortestPath(graph, start, end):
>     >
>     >? ? ? ? ?"""
>     >
>     >? ? ? ? ?Find a single shortest path from the given start vertex
>     to the
>     >? ? ? ? ?given end vertex.
>     >
>     >? ? ? ? ?The input has the same conventions as Dijkstra().
>     >
>     >? ? ? ? ?The output is a list of the vertices in order along the
>     >? ? ? ? ?shortest path.
>     >
>     >? ? ? ? ?"""
>     >
>     >? ? ? ? ?? ? ? ? start = graph.getEdge(start)
>     >
>     >? ? ? ? ?? ? ? ? end = graph.getEdge(end)
>     >
>     >
>     >? ? ? ? ?D,P = AntColony(graph, start, end)
>     >
>     >? ? ? ? ?Path = []
>     >
>     >
>     >? ? ? ? ?#while 1:
>     >
>     >? ? ? ? ?#Path.append(end)
>     >
>     >? ? ? ? ?#if end == start: break
>     >
>     >? ? ? ? ?#end = P[end]
>     >
>     >? ? ? ? ?#Path.reverse()
>     >
>     >
>     >? ? ? ? ?return Path
>     >
>     >
>     >? ? ? ? ?def generate_routefile():
>     >
>     >? ? ? ? ?? ? with open("dijkstra_000.rou.xml", "w") as routes:
>     >
>     >? ? ? ? ?? ? ? ? print >> routes, """<routes>
>     >
>     >? ? ? ? ?? ? ? ? <vType id="vehicle1" accel="0.8" decel="4.5"
>     >? ? ? ? ?sigma="0.5" length="5" minGap="2.5" maxSpeed="16.67"
>     >? ? ? ? ?guiShape="passenger"/>
>     >
>     >
>     >? ? ? ? ?? ? ? ? <route id="1" edges="1 3 5 9" /> </routes>"""
>     >
>     >? ? ? ? ?def main():
>     >
>     >? ? ? ? ?? ? traci.init(PORT)
>     >
>     >? ? ? ? ?? ? Objgraph_mat = Graph_mat()
>     >
>     >? ? ? ? ?? ? aco = ACOAlgorithm()
>     >
>     >? ? ? ? ?? ? for edge in graph.getEdges():
>     >
>     >? ? ? ? ?? ? ? ?
>     >? ? ? ? ?Objgraph_mat.add_vertex(Vertex(edge.getFromNode().getID()))
>     >
>     >? ? ? ? ?? ? ? ?
>     Objgraph_mat.add_vertex(Vertex(edge.getToNode().getID()))
>     >
>     >
>     >
>     >? ? ? ? ?? ? for edge in graph.getEdges():
>     >
>     >? ? ? ? ?? ? ? ? Objgraph_mat.add_edge(edge.getFromNode().getID(),
>     >? ? ? ? ?edge.getToNode().getID())
>     >
>     >
>     >? ? ? ? ?? ? Objgraph_mat.print_graph()
>     >
>     >
>     >? ? ? ? ?? ? aco.set_graph(Objgraph_mat)
>     >
>     >? ? ? ? ?? ? #aco.process()
>     >
>     >? ? ? ? ?? ? #route = shortestPath(graph, '1', '18')
>     >
>     >? ? ? ? ?? ? #for x in range(len(route)):
>     >
>     >? ? ? ? ?? ? ?#? ?print route[x],
>     >
>     >
>     >? ? ? ? ?? ? #edges = [str (edge.getID()) for edge in route]
>     >
>     >? ? ? ? ?? ? #create the new route for vehicle
>     >
>     >? ? ? ? ?? ? #traci.route.add("0", edges)
>     >
>     >? ? ? ? ?? ? #assign the new route for vehicle with id vehicle1
>     >
>     >? ? ? ? ?? ? #traci.vehicle.add("vehicle0","0")
>     >
>     >? ? ? ? ?? ? for i in range(1000):? ? #? or whatever nulmber of steps
>     >? ? ? ? ?you want to simulate
>     >
>     >? ? ? ? ?? ? ? ? traci.simulationStep()
>     >
>     >? ? ? ? ?? ? traci.close()
>     >
>     >? ? ? ? ?? ? sys.stdout.flush()
>     >
>     >? ? ? ? ?? ??
>     >
>     >
>     >? ? ? ? ?def get_options():
>     >
>     >? ? ? ? ?? ? optParser = optparse.OptionParser()
>     >
>     >? ? ? ? ?? ? optParser.add_option("--nogui", action=""> >     >? ? ? ? ?default=False, help="run the commandline version of sumo")
>     >
>     >? ? ? ? ?? ? options, args = optParser.parse_args()
>     >
>     >? ? ? ? ?? ? return options
>     >
>     >
>     >
>     >? ? ? ? ?# this is the main entry point of this script
>     >
>     >? ? ? ? ?if __name__ == "__main__":
>     >
>     >? ? ? ? ?? ? options = get_options()
>     >
>     >? ? ? ? ?? ? # this script has been called from the command line. It
>     >? ? ? ? ?will start sumo as a
>     >
>     >? ? ? ? ?? ? # server, then connect and run
>     >
>     >? ? ? ? ?? ? if options.nogui:
>     >
>     >? ? ? ? ?? ? ? ?sumoBinary = checkBinary('sumo')
>     >
>     >? ? ? ? ?? ? else:
>     >
>     >? ? ? ? ?? ? ? ?sumoBinary = checkBinary('sumo-gui')
>     >
>     >
>     >? ? ? ? ?? ? generate_routefile()
>     >
>     >
>     >? ? ? ? ?? ? # this is the normal way of using traci. sumo is
>     started as a
>     >
>     >? ? ? ? ?? ? # subprocess and then the python script connects and
>     runs
>     >
>     >? ? ? ? ?? ? sumoProcess = subprocess.Popen([sumoBinary, "-c",
>     >? ? ? ? ?"dijkstra.sumo.cfg", "--tripinfo-output", "tripinfo.xml",
>     >? ? ? ? ?"--remote-port", str(PORT)], stdout=sys.stdout,
>     stderr=sys.stderr)
>     >
>     >? ? ? ? ?? ? main()
>     >
>     >? ? ? ? ?? ? sumoProcess.wait()
>     >
>     >
>     >? ? ?--
>     >? ? ?*:)*
>     >? ? ?Bijal Varia
>     >? ? ?_______________________________________________
>     >? ? ?sumo-user mailing list
>     >? ? ?sumo-user@xxxxxxxxxxx <mailto:sumo-user@xxxxxxxxxxx>
>     <mailto:sumo-user@xxxxxxxxxxx <mailto:sumo-user@xxxxxxxxxxx>>
>     >? ? ?To change your delivery options, retrieve your password, or
>     >? ? ?unsubscribe from this list, visit
>     >? ? ?https://www.eclipse.org/mailman/listinfo/sumo-user
>     >
>     >
>     > _______________________________________________
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--
:)
Bijal Varia
import os, sys
import optparse
import subprocess
import random
from Queue import PriorityQueue
import xml.sax
from xml.sax import saxutils, parse, make_parser, handler
from copy import copy
from itertools import *

SUMO_HOME = "/home/dhaval/sumo-1.0.0/"
sys.path.append(os.path.join(SUMO_HOME, "tools"))

try:
    # import the library
    import sumolib
    from sumolib import checkBinary
    from sumolib.net import Net
    from sumolib.net import NetReader
    from sumolib.net import Lane
    from sumolib.net import Edge
    from sumolib.net import Node
    from sumolib.net import Connection
    from sumolib.net import Roundabout
       
except ImportError:
    sys.exit("please declare environment variable 'SUMO_HOME' as the root directory of your sumo installation (it should contain folders 'bin', 'tools' and 'docs')")

import random
graph = sumolib.net.readNet('Dijkstra1.net.xml')


import traci
# the port used for communicating with your sumo instance
PORT = 8873

# implementation of an undirected graph using Adjacency Matrix, with weighted or unweighted edges
class Vertex:
	def __init__(self, n):
		self.name = n

class Graph_mat:
	vertices = {}
	edges = []
	edge_indices = {}

	def add_vertex(self, vertex):
		if isinstance(vertex, Vertex) and vertex.name not in self.vertices:
			self.vertices[vertex.name] = vertex
			for row in self.edges:
				row.append(0)
			self.edges.append([0] * (len(self.edges)+1))
			self.edge_indices[vertex.name] = len(self.edge_indices)
			return True
		else:
			return False

	def add_edge(self, u, v, weight=1):
		if u in self.vertices and v in self.vertices:
			self.edges[self.edge_indices[u]][self.edge_indices[v]] = weight
			self.edges[self.edge_indices[v]][self.edge_indices[u]] = weight
			return True
		else:
			return False
	def print_graph(self):
		for v, i in sorted(self.edge_indices.items()):
			print(v + ' ')
			for j in range(len(self.edges)):
				print(self.edges[i][j])
			print(' ')

class Ant():

    def __init__(self):
        self.cost = 0
        self.trace = [0]

    def start_travel(self):
        self.cost = 0
        self.trace = [0]

    def add_vertex(self, _vertex, _cost):
        self.trace.append(_vertex)
        self.cost += _cost

    def get_position(self):
        return self.trace[-1]

    def get_cost(self):
        return self.cost

    def get_path(self):
        path = []
        for i in range(len(self.trace) - 1):
            path.append((self.trace[i], self.trace[i + 1]))

        return path


class ACOAlgorithm():
    '''
    Ant colony optimization algorithms to find shortest path
    '''

    def __init__(self):
        self.evaporation_rate = 0.8
        self.threshhold = 0.5
        self.remain_path = 0

    def set_graph(self, graph):
        self.size = len(graph.edges)

        self.num_ant = 20*self.size ** 2
        self.ant = [Ant() for _ in range(self.num_ant)]


        self.distance = graph.edges
        self.pheromones = [[1.0]* self.size for _ in range(self.size)]

        max_distance = 0
        for i in range(len(self.distance)):
            for j in range(len(self.distance[0])):
                if self.distance[i][j] > max_distance:
                    max_distance = self.distance[i][j]

        for i in range(len(self.distance)):
            for j in range(len(self.distance[0])):
                if self.distance[i][j] > 0:
                    self.distance[i][j] /= max_distance*1.0
                else:
                    self.pheromones[i][j] = -1.0

    def process(self):
        while True:
            self._start_travel()
            print 'Start Travel...'
            self._find_edge()
            print 'Find Edge...'
            if self._finish_travel():
                break

        for i in range(self.num_ant):
            if len(self.ant[i].trace) == self.size:
                print 'trace %s' % (self.ant[i].trace)
                break

    def _start_travel(self):
        for i in range(self.num_ant):
            self.ant[i].start_travel()

    def _find_edge(self):
        while not self._have_ant_completed():
            for i in range(len(self.ant)):
                available_edge = 0
                for e in range(self.size):
                    if e not in self.ant[i].trace and self.pheromones[self.ant[i].get_position()][e] > 0:
                        available_edge +=  (2.0 - self.distance[self.ant[i].get_position()][e])*self.pheromones[self.ant[i].get_position()][e]

                last_e = -1
                prob_edge = 0
                prob_random = random.uniform(0.0, 1.0)
                for e in range(self.size):
                    if e not in self.ant[i].trace and self.pheromones[self.ant[i].get_position()][e] > 0:
                        prob_edge += (2.0 - self.distance[self.ant[i].get_position()][e])*self.pheromones[self.ant[i].get_position()][e]/available_edge
                        last_e = e
                        if prob_edge >= prob_random:
                            break
                if last_e >= 0:
                    self.ant[i].add_vertex(last_e, self.distance[self.ant[i].get_position()][last_e])
                else:
                    self.ant[i].start_travel()

    def _finish_travel(self):
        # find short path
        avg_cost = 0
        ant_completed = 0
        for i in range(len(self.ant)):
            if len(self.ant[i].trace) == self.size:
                avg_cost += self.ant[i].get_cost()
                ant_completed += 1
        avg_cost /= ant_completed
        print 'finish travel'

        # update pheromones
        for i in range(len(self.pheromones)):
            for j in range(len(self.pheromones[0])):
                if self.pheromones[i][j] > 0:
                    self.pheromones[i][j] *= (1 - self.evaporation_rate)

        for i in range(len(self.ant)):
            if self.ant[i].get_cost() < avg_cost:
                update_pheromones = self.ant[i].get_path()
                for x,y in update_pheromones:
                    self.pheromones[x][y]  += avg_cost/self.ant[i].get_cost()

        # remove path has small pheromones
        if self.remain_path > 2*(self.size - 1):
            for i in range(len(self.pheromones)):
                for j in range(len(self.pheromones[0])):
                    if self.pheromones[i][j] <= self.threshhold:
                        self.pheromones[i][j] = -1.0
        else:
            min_pheromones = 999999.99
            for i in range(len(self.pheromones)):
                for j in range(len(self.pheromones[0])):
                    if min_pheromones > self.pheromones[i][j] > 0:
                        min_pheromones = self.pheromones[i][j]

            for i in range(len(self.pheromones)):
                for j in range(len(self.pheromones[0])):
                    if self.pheromones[i][j] <= min_pheromones:
                        self.pheromones[i][j] = -1.0

        # check exist only one path
        self.remain_path = 0
        for i in range(len(self.pheromones)):
            for j in range(len(self.pheromones[0])):
                if self.pheromones[i][j] > 0:
                    self.remain_path += 1

        return self.remain_path < self.size

    def _have_ant_completed(self):
        for i in range(len(self.ant)):
            if len(self.ant[i].trace) == self.size:
                return True
        return False




def AntColony(graph, start, end=None):
        D = {}	# dictionary of final distances
	P = {}	# dictionary of predecessors



	return (D,P)
        
			
def shortestPath(graph, start, end):
	"""
	Find a single shortest path from the given start vertex to the given end vertex.
	The input has the same conventions as Dijkstra().
	The output is a list of the vertices in order along the shortest path.
	"""
        start = graph.getEdge(start)
        end = graph.getEdge(end)

	D,P = AntColony(graph, start, end)
	Path = []

	#while 1:
	#	Path.append(end)
	#	if end == start: break
	#	end = P[end]
	#Path.reverse()

	return Path

def generate_routefile():
    with open("dijkstra_000.rou.xml", "w") as routes:
        print >> routes, """<routes>
        <vType id="vehicle1" accel="0.8" decel="4.5" sigma="0.5" length="5" minGap="2.5" maxSpeed="16.67" guiShape="passenger"/>

        <route id="1" edges="1 3 5 9" /> </routes>"""
def main():
    traci.init(PORT)
    Objgraph_mat = Graph_mat()
    aco = ACOAlgorithm()
    for edge in graph.getEdges():
        Objgraph_mat.add_vertex(Vertex(edge.getFromNode().getID()))
        Objgraph_mat.add_vertex(Vertex(edge.getToNode().getID()))


    for edge in graph.getEdges():
        Objgraph_mat.add_edge(edge.getFromNode().getID(), edge.getToNode().getID())

    Objgraph_mat.print_graph()

    aco.set_graph(Objgraph_mat)
    aco.process()
    #route = shortestPath(graph, '1', '18')
    #for x in range(len(route)):
     #   print route[x],

    #edges = [str (edge.getID()) for edge in route]
    #create the new route for vehicle
    #traci.route.add("0", edges)
    #assign the new route for vehicle with id vehicle1
    #traci.vehicle.add("vehicle0","0")
    for i in range(1000):    #  or whatever nulmber of steps you want to simulate
        traci.simulationStep()
    traci.close()
    sys.stdout.flush()
    

def get_options():
    optParser = optparse.OptionParser()
    optParser.add_option("--nogui", action="store_true", default=False, help="run the commandline version of sumo")
    options, args = optParser.parse_args()
    return options


# this is the main entry point of this script
if __name__ == "__main__":
    options = get_options()
    # this script has been called from the command line. It will start sumo as a
    # server, then connect and run
    if options.nogui:
       sumoBinary = checkBinary('sumo')
    else:
       sumoBinary = checkBinary('sumo-gui')

    generate_routefile()

    # this is the normal way of using traci. sumo is started as a
    # subprocess and then the python script connects and runs
    sumoProcess = subprocess.Popen([sumoBinary, "-c", "dijkstra.sumo.cfg", "--tripinfo-output", "tripinfo.xml", "--remote-port", str(PORT)], stdout=sys.stdout, stderr=sys.stderr)
    main()
    sumoProcess.wait()

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