I'm in a situation where I have the exact same need - exporting the connectivity table from a geometric network. I'm curious how you ended up solving your problem. Did you go with the VB Code, or a similar python script? Or perhaps there's a newer solution that's come up in the last three years.
Also , I have the same problem . Please if you have some solutions , share it with me . I used the schematic tool , but I got some tables , regarding your images there is only a connectivity table.
Thanks in advance
Thanks for your answers. In the end I've built a python solution to export adjacency matrix and node list of a network to text files.
It requires the installation of networkX and shapely python packages. Your network has to be a shapefile, and the script was not tested on big graphs.
I have uploaded a zip file containing script, data sample and results hereHope this helps and feel free to comment !
# Extract adjacency matrix and nodelist from Shapefile with python networkX #Packages import import os import networkx as nx import shapely import numpy as np import re # Setting the working directory (the network .shp file has to be in this path) path = r'Q:\gis\NetworkSample' # Now change the directory os.chdir( path ) # Check current working directory. retval = os.getcwd() print "Directory changed successfully %s" % retval # Name of the network shapefile shpFileName = 'SampleNetworkData.shp' shpFileNameStr=shpFileName.replace(".","_") # Adjacency matrix export name AdjMatName="Adj_matrix_dist_"+shpFileNameStr+".txt" # node list export name NodeListName="Nodes_of_"+shpFileNameStr+".txt" #Reading the shp and creating the corresponding graph G G=nx.read_shp(shpFileName) #Converting G to an unoriented graph G=G.to_undirected() # Print the number of nodes and edges n=G.number_of_nodes() e=G.number_of_edges() print str(G.number_of_nodes()) +" nodes" + " and " +str(G.number_of_edges()) + " edges" #Change nodes labels by an integer that range from 0 --> n and save the old labels (XY coordinates). G=nx.convert_node_labels_to_integers(G,label_attribute='XYcoordinates') # Adjacency Matrix # Computing adjacency matrix using length as weight adjMatrix=nx.adjacency_matrix(G,nodelist=None,weight='Shape_Leng') # Converting CSR matrix format to dense format DenseAdjMatrix=adjMatrix.todense() # Exporting adjacency matrix as .txt file np.savetxt("dense_adjacency_matrix_SampleNetworkData.txt", DenseAdjMatrix, delimiter=',', newline="\n", fmt='%d') # Nodes attributes # Exporting the nodes key and coordinates has a file ("nodelist.txt") with open('nodeslist.txt','w') as file: for node in G.nodes_iter(data=True): #Identify the node key (integer) and X,Y coordinates (float) and return them in the list 'towrite' towrite=re.findall(r"[-+]?\d*\.\d+|[-+]?\d+", str(node)) #Setting file format (node key,X,Y) and export towrite= ','.join(map(str, towrite)) print>>file, towrite #End of script