Hi everyone,
I had to draw a real-world network from a basemap in ArcGIS 10.2. After having added my shp files to a geometric network, I fixed the network build errors. Then, with the purpose of determining the degree of each node (e.g., the number of edges connected to that node), I ran the Spatial Statistics Tools->Utilities->Collect Events function. This gave me a table with the ICOUNT values, which correspond to the degree I was looking for.
My problem: the number of vertices worked out by the Collect Events function is far lower than the number of vertices my network actually has.
1) How can this be possible?
2) How could such function miss any point?
3) What do you think I could do to spare me the use of some network modeling tool?
PS: Using the Join function to see what vertices are not mapped in the ICOUNT table is out of question as the ObjectID key of the two tables does not refer to the same points.
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Thank you for your time and dedication.
Francesco, I am not that experienced with ArcGIS 10.2 and geometric networks to answer your question directly. But I am a friend of the Python module Networkx, which has a lot of functions and algorithms for network and graph analysis. And, for the sake of ArcGIS users, the module can import shape files.
With this module installed you can run the commands in Python console (or standalone importing ArcPy):
G=nx.read_shp('your_edges.shp')
print degree(G)
Export your edges as a shape file of polylines. The read_shp function will extract start and end nodes, labels them with the corresponding coordinate tuple, and construncts the network.
Since nodeIds will be derived from coordinates, you are able to reconstruct which node in the network belongs to which real world position.
Most outputs are lists and dictionaries. So your are free to process the results according your needs.
https://networkx.github.io/documentation/latest/overview.html
Hi,
I don't spare you the use of a dedicated network modelling/analysis tool but I think it could be useful.
I have recently found a software and you can have a look at it with this link: https://gephi.github.io
https://gephi.github.io
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