![]() ![]() # graph_utils_py.draw_graph3d(H, fig=2, show=True) Please find the code that is used to attack edges import networkx as nx The observation made is the change in node values after an edge is attacked and no observation of the edge value is available. From the source node b, the goods are transported to target node e. We could imagine this to be a transportation network and the values at node reflect the amount of a product that has reached the location/node. I want to see the attack on which edge has the maximum effect on the time course value observed at e. What information do you want to be able to see or identify from your #Visualize and attack how to#I would like to ask for suggestions on how to visualize the effect of these attacks on the value of node e changing over time. ![]() Let's say I perform 5 (attack = 5) attacks, I have a time x attack matrix (time=25, attack=5) that stores the time-series data of node e. So the edge that's connected to node 2 is also removed.Įach time an edge is attacked, the value of the terminal node labelled e observed over time changes. To explain a bit, when edge (a, 2) is attacked the node 2 will have a degree < 2. If I attack edge (a,2): edge (a, 2) and (2, 1) will be removed. I perform edge attacks and observe the change in values at the node of the resulting subgraph. I have a Networkx graph like the following image ( image source) ![]()
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