traffic.py

distances=[['A','B',1],['A','C',3],['B','C',1],['B','D',5],['C','B',2],['C','E',1],['D','E',7],['D','F',2],['E','D',1],['E','F',1]]
distribution={'A':[('A',0.5),('B',0.35),('C',0.15)],'B':[('B',0.4),('C',0.2),('D',0.4)],'C':[('C',0.9),('B',0.1),('E',0.1)],'D':[('D',0.3),('E',0.4),('F',0.3)],'E':[('E',0.7),('D',0.1),('F',0.2)],'F':[('F',1)]}
cars_initial={'A':10,'B':20,'C':30,'D':40,'E':50,'F':60}
number_of_cars_time={10:1,20:2,30:4,40:8,50:16,60:32,70:64,80:128,90:256}
def calc_weight(ele_dist,no_of_car):
    t=0#How to calculate weights between two points taking(A,B) and number of cars as arguments
    for i in number_of_cars_time:
        if no_of_car<i:
            t=number_of_cars_time[i]
    weight=ele_dist[2]+t
    return weight
def num_of_cars(node):
    t=0
    for i in distances:
        if i[1]==node:
            for j in distribution:
                if j==i[0]:
                    for k in distribution[j]:
                        if k[0]==node:
                            t+=(cars_initial[node])*k[1]
    t-=(distribution[node][0][1])*(cars_initial[node])
    cars_initial[node]=t
    return t
from collections import defaultdict
from heapq import *

def dijkstra(edges, f, t):
    g = defaultdict(list)
    for l,r,c in edges:
        g[l].append((c,r))

    q, seen, mins = [(0,f,())], set(), {f: 0}
    while q:
        (cost,v1,path) = heappop(q)
        if v1 not in seen:
            seen.add(v1)
            path = (v1, path)
            if v1 == t: return (cost, path)

            for c, v2 in g.get(v1, ()):
                if v2 in seen: continue
                prev = mins.get(v2, None)
                next = cost + c
                if prev is None or next < prev:
                    mins[v2] = next
                    heappush(q, (next, v2, path))
    return float("inf")
def format_dijkstra(k):
    s=''
    path_time=k[0]
    for i in str(k[1]):
        if i not in [',','(',')',"'",' ']:
            s+=i
    return (s[::-1],path_time)
        
start=raw_input('Enter start point:')
end=raw_input('Enter end point:')
def change_weights():
    for i in distances:
        for j in cars_initial:
            if i[0]==j:
                i[2]=calc_weight(i,cars_initial[j])
change_weights()
path=start
print 'The best route according to current traffic conditions.'
k=format_dijkstra(dijkstra(distances,start,end))
print 'Route:',k[0],'Time',k[1]
for i in distances:
    if start==i[0] and k[0][1]==i[1]:
        t1=i[2]
        break
clock=[]
from copy import deepcopy
temp=deepcopy(distances)
for i in temp:
    i.append(0)
for i in temp:
    clock.append(i)
clock.append([start,k[0][1],t1,1])
t=1
car_pos=start
while car_pos!=end:
    for i in clock:
        if i[2]==t and i[3]==0:
            i[2]=(calc_weight(i[:3],num_of_cars(i[1])))+t
            if i not in clock:
                clock.append(i)
        if i[3]==1 and i[2]==t:
            k=format_dijkstra(dijkstra(distances,car_pos,end))
            path+=k[0][1]
            car_pos=k[0][1]
            if len(k[0])==2:
                pass
            else:
                clock.append([car_pos,k[0][2],k[1]+t,1])
            print path,t
    for i in clock:
        if i[2]==t:
            clock.remove(i)
    t+=1
print path,t