Need help for resolving error in implementing incremental_closeness centrality

Python Help
1

I have a data file in .txt format: The data is shown as

a_8358:b_5207, 0.3333333333333333
a_8357:b_5207, 0.3333333333333333
a_8358:b_5209, 0.5
a_8357:b_5209, 0.5
a_8358:b_5208, 0.0
a_8357:b_5208, 0.0
b_5207:c_1954, 0.1111111111111111
b_5207:c_1961, 0.2
b_5207:c_1957, 0.14285714285714285
b_5207:c_14167, 0.125
b_5207:c_37159, 0.14285714285714285
b_5209:c_1954, 0.125
b_5209:c_1961, 0.25
b_5209:c_1957, 0.16666666666666666
b_5209:c_14167, 0.14285714285714285
b_5209:c_37159, 0.16666666666666666
b_5208:c_1954, 0.0
b_5208:c_1961, 0.0
b_5208:c_1957, 0.0
b_5208:c_14167, 0.0
b_5208:c_37159, 0.0
d_3389:b_5207, 0.14285714285714285
d_22862:b_5207, 0.2
d_3389:b_5209, 0.16666666666666666
d_22862:b_5209, 0.25
d_3389:b_5208, 0.0
d_22862:b_5208, 0.0
e_1961:b_5207, 0.2
e_1961:b_5209, 0.25
e_1961:b_5208, 0.0
a_8358:c_1954, 0.1
a_8358:c_1961, 0.16666666666666666
a_8358:c_1957, 0.1111111111111111
a_8358:c_14167, 0.1
a_8358:c_37159, 0.1
a_8357:c_1954, 0.14285714285714285
a_8357:c_1961, 0.16666666666666666
a_8357:c_1957, 0.2
a_8357:c_14167, 0.16666666666666666
a_8357:c_37159, 0.25
d_3389:a_8358, 0.1
d_22862:a_8358, 0.125
d_3389:a_8357, 0.25
d_22862:a_8357, 0.5
e_1961:a_8358, 0.16666666666666666
e_1961:a_8357, 0.16666666666666666
d_3389:c_1954, 0.14285714285714285
d_22862:c_1954, 0.14285714285714285
d_3389:c_1961, 0.16666666666666666
d_22862:c_1961, 0.25
d_3389:c_1957, 0.2
d_22862:c_1957, 0.2
d_3389:c_14167, 0.16666666666666666
d_22862:c_14167, 0.16666666666666666
d_3389:c_37159, 0.125
d_22862:c_37159, 0.25
e_1961:c_1954, 0.16666666666666666
e_1961:c_1961, 0.5
e_1961:c_1957, 0.2
e_1961:c_14167, 0.16666666666666666
e_1961:c_37159, 0.16666666666666666
d_3389:e_1961, 0.16666666666666666
d_22862:e_1961, 0.25

I tried to implement incremental_closeness centrality as

import networkx as nx
# Calculate initial closeness centrality for each node
initial_closeness = nx.closeness_centrality(G)

# Print initial closeness centrality values
print("Initial closeness centrality:")
for node, value in initial_closeness.items():
    print(f"{node}: {value}")

# Make changes to the graph (e.g. add/remove edges or nodes)

# Calculate incremental closeness centrality for each node
incremental_closeness = {}
for node in G.nodes:
    # Create a copy of the graph with the current node removed
    H = G.copy()
    H.remove_node(node)
    # Calculate the closeness centrality of the remaining nodes in the new graph
    remaining_closeness = nx.closeness_centrality(H)
    # Calculate the difference in closeness centrality for the current node
    delta = initial_closeness[node] - remaining_closeness[node]
    incremental_closeness[node] = delta

# Print incremental closeness centrality values
print("Incremental closeness centrality:")
for node, value in incremental_closeness.items():
    print(f"{node}: {value}")

However, I am getting the following error:

KeyError                                  Traceback (most recent call last)
<ipython-input-28-5ac9eb6debea> in <module>
     20     remaining_closeness = nx.closeness_centrality(H)
     21     # Calculate the difference in closeness centrality for the current node
---> 22     delta = initial_closeness[node] - remaining_closeness[node]
     23     incremental_closeness[node] = delta
     24 

KeyError: 'a_8358'

Please help to resolve the error

2

You’re deleting the node here:

And then you try to access the (deleted) node a few lines later:

Remove H.remove_node(node) and it should work.

3

This is the output that I am getting after removing H.remove_node(node):

Incremental closeness centrality:
a_8358: 0.0
b_5207: 0.0
a_8357: 0.0
b_5209: 0.0
b_5208: 0.0
c_1954: 0.0
c_1961: 0.0
c_1957: 0.0
c_14167: 0.0
c_37159: 0.0
d_3389: 0.0
d_22862: 0.0
e_1961: 0.0

Please help

4

I’m not familiar with graph theory. What output do you expect?

5

According to incremental closeness centrality, there should be non-negative, non-zero numbers for each vertex in graph

6

OK. Again, not familiar with graph theory so you will have to provide the mathematical context for what you want to do. What is “incremental closeness” and how is it calculated?