Gc nodes centralization

• (import "Gc_negative.gml")
• calculate degree centralization
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In [6]:

import networkx as nx
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
%matplotlib inline
import os
from glob import glob

#Gc_files = glob('../output/network/Gc_negative.gml')
#Gc_files = glob('../output/network/Gc_positive.gml')
Gc_files = glob('../output/network/Gc_neutral.gml')

def calculate_graph_inf(graph):
graph.name = filename
info = nx.info(graph)
print info

for graph_num, gml_graph in enumerate(Gc_files):
(filepath, filename) = os.path.split(gml_graph)
print('-' * 10)
print(gml_graph)
calculate_graph_inf(graph)

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----------
../output/network/Gc_neutral.gml
Name: Gc_neutral.gml
Type: MultiGraph
Number of nodes: 171
Number of edges: 221
Average degree:   2.5848

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In [3]:

# negative

N = graph.order()
degrees = graph.degree().values()
max_in = max(degrees)
centralization = float((N*max_in - sum(degrees)))/(N-1)**2
centralization

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Out[3]:

0.11493531670265107

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In [5]:

# positive

N = graph.order()
degrees = graph.degree().values()
max_in = max(degrees)
centralization = float((N*max_in - sum(degrees)))/(N-1)**2
centralization

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Out[5]:

0.11025755301182211

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In [8]:

# neutral

N = graph.order()
degrees = graph.degree().values()
max_in = max(degrees)
centralization = float((N*max_in - sum(degrees)))/(N-1)**2
centralization

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Out[8]:

0.17996539792387542

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In [ ]:

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