import numpy as np import shed import pylab from mpl_toolkits mplot3d

  • Anonymous
  • Python
  • 10 Mar 2019 
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import numpy as np

import shed

import pylab

from mpl_toolkits.mplot3d import Axes3D

import matplotlib.pyplot as plt

from scipy.spatial import Delaunay

import networkx as nx

from scipy.spatial import  distance



def builtRandomFlow (mA):

    f = []

    for i in range(len(mA)):

        f.append([0] * len(mA))

   

    for i in range(len(mA)):

        for j in range(len(mA)):

            if mA[i][j]!=np.inf and i!=j:

                f[i][j]=np.random.randint(20)+1

            if i==j:

                f[i][j]=0

    return f



def length (path):

    l = 0

    for i in range(len(path)-1):

        l+=G[path[i]][path[i+1]]['weight']

        

    return l



N = 6

p = shed.builtPoints(N,10,10)

tri = Delaunay(p)

e,f = shed.getEdgesDelaunay(tri)





G = nx.DiGraph()

for edge in e:

    G.add_edge(edge[0],edge[1],weight = round(distance.euclidean(p[edge[0]],p[edge[1]]),3), capacity = np.random.randint(10)+1)   

H = G.copy()            

positions_vertexes = [(p[i][0], p[i][1]) for i in range(N)]

edge_labels=dict([((u,v,),(d['capacity'])) for u,v,d in G.edges(data=True)])

nx.draw_networkx_edge_labels(G,positions_vertexes,edge_labels=edge_labels,label_pos=0.75)

nx.draw_networkx(G, positions_vertexes, with_labels=True, arrows=True, node_color='Red')

plt.show()



#for u,v,d in G.edges(data=True):

#    print (u,v,d)

path = nx.all_pairs_dijkstra_path(G)

print ("Изначальные пути",path)





#shed.pprint(path)

for i in range(N):   

    for j in range(N):

        for k in range(len(path[i][j])-1):

            G[path[i][j][k]][path[i][j][k+1]]['capacity'] -= 1



for u,v,d in G.edges(data=True):

    if d['capacity']==0:

        G.remove_edge(u,v)



edge_labels=dict([((u,v,),(d['capacity'])) for u,v,d in G.edges(data=True)])

nx.draw_networkx_edge_labels(G,positions_vertexes,edge_labels=edge_labels,label_pos=0.75)

nx.draw_networkx(G, positions_vertexes, with_labels=True, arrows=True, node_color='Red')

plt.show()





#print ("Потоки после дейсктры")

#shed.pprint (flow)

#

flow_edge = [[[] for j in range(N)] for i in range(N)]  

for i in range(N):

    for j in range(N):

        if len(path[i][j])!=1:

            for k in range(len(path[i][j])-1):

                flow_edge[int(path[i][j][k])][int(path[i][j][k+1])].append(path[i][j])



shed.pprint(flow_edge)



for u,v,d in G.edges(data=True):

    if d['capacity']<0:

        print (flow_edge[u][v],d['capacity'])

        d['weight'] = np.inf

        for r_flow in range(d['capacity']*(-1)):

            new_path = []

            new_k = np.inf

            for i in flow_edge[u][v]:

                

                try:

                    tmp_path = nx.shortest_path(G,i[0],i[-1],weight = 'weight')

                    tmp_k = length(tmp_path)/round(distance.euclidean(p[i[0]],p[i[-1]]))

                    if (tmp_k<new_k):

                        new_k = tmp_k

                        new_path = tmp_path

                except nx.NetworkXNoPath:

                    continue

            print ( new_path)

            

            for vertrex_new_path in range(len(new_path)-1):

                flow_edge[new_path[vertrex_new_path]][new_path[vertrex_new_path+1]].append(new_path)

                G[new_path[vertrex_new_path]][new_path[vertrex_new_path+1]]['capacity']-=1

                if G[new_path[vertrex_new_path]][new_path[vertrex_new_path+1]]['capacity']==0:

                    G.remove_edge(new_path[vertrex_new_path],new_path[vertrex_new_path+1])

                

            

            for vertrex_new_path in range(len(path[u][v])-1):

                flow_edge[path[u][v][vertrex_new_path]][path[u][v][vertrex_new_path+1]].remove(path[u][v])

                G[path[u][v][vertrex_new_path]][path[u][v][vertrex_new_path+1]]['capacity']+=1

            path[u][v] = new_path

            G.remove_edge(u,v)



#

#for i in range(N):

#    for j in range(N):

#         if flow[i][j]<=0:

#             if G.has_edge(i,j):

#                 G.remove_edge(i, j)

#

#flag = True

#

#while flag:

#    flag = False

#    for i in range(N):   

#        for j in range(N):

#            if flow[i][j]<=0:

#                

#                if G.has_edge(i,j):

#                    flag = True

#                    G.remove_edge(i, j)

#                if flow[i][j]<0:

#                    

#                    new_path = ""

#                    old_path = ""

#                    len_new_path = np.inf

#                    for p in flow_edge[i][j]:

#                        if nx.has_path(G,int(p[0]),int(p[-1])) == False:

#                            path[int(p[0])][int(p[-1])]=[] 

#                        else:

#                            tmp = nx.dijkstra_path(G,int(p[0]),int(p[-1]))

#                            len_tmp = nx.dijkstra_path_length(G,int(p[0]),int(p[-1]))

#                            if len_tmp<len_new_path:

#                                len_new_path = len_tmp

#                                new_path = tmp

#                                old_path = p

#                    if new_path!="":

#                        for old_edge in range(len(old_path)-1):

#                            flow[old_path[old_edge]][old_path[old_edge+1]]+=1

##                            print ("del",old_path[old_edge], old_path[old_edge+1], old_path)

#                            flow_edge[old_path[old_edge]][old_path[old_edge+1]].remove(old_path)

#                        flag = True

#                        path[new_path[0]][new_path[-1]]=new_path

#                                

#                        for t in range(len(new_path)-1):

#                            flow[new_path[t]][new_path[t+1]]-=1

##                            print ("add",new_path[t], new_path[t+1], new_path)

#                            flow_edge[new_path[t]][new_path[t+1]].append(new_path)

#                            path[new_path[t]][new_path[t+1]]=new_path

#                        print (old_path,"->",new_path)        

#

#edge_labels=dict([((u,v,),(flow[u][v])) for u,v,d in G.edges(data=True)])

#nx.draw_networkx_edge_labels(G,positions_vertexes,edge_labels=edge_labels,label_pos=0.75)

#nx.draw_networkx(G, positions_vertexes, with_labels=True, arrows=True, node_color='Red')

#shed.pprint(path)

#shed.pprint(flow)
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