Thesis » QuynhNguyen-MS

import json

import os

import networkx as nx

import matplotlib.pyplot as plt

import betweenness_centrality as centrality

MAIN_CODE_DIR = os.environ.get('MAIN_CODE_DIR', '')

def initialize():

    """

    Create all necessary folder

    """

    output_dir = os.path.join(MAIN_CODE_DIR, 'output')

    if not os.path.isdir(output_dir):

        os.makedirs(output_dir)

    visualization_dir = os.path.join(output_dir, 'visualization')

    if not os.path.isdir(visualization_dir):

        os.makedirs(visualization_dir)

def weight_betweenness_centrality(graph, file_suffix):

    score = centrality.weight_betweenness_centrality(graph, rescale=True)

    filepath = '/output/weight_basic_%s.csv'  % file_suffix

    with open(MAIN_CODE_DIR + filepath, 'w') as output:

        for node, bc in score.iteritems():

            output.write('%s, %s\n' % (node, bc))

def brandes_betweenness_centrality(graph, file_suffix):

    score = nx.betweenness_centrality(graph, endpoints=False, normalized=False)

    # score = nx.betweenness_centrality(graph, endpoints=True)

    filepath = '/output/networkx_%s.csv'  % file_suffix

    with open(MAIN_CODE_DIR + filepath, 'w') as output:

        for node, bc in score.iteritems():

            output.write('%s, %s\n' % (node, bc))

def brandes_betweenness_centrality_endpoints(graph, file_suffix):

    score = nx.betweenness_centrality(graph, endpoints=True, normalized=True)

    filepath = '/output/networkx_%s.csv'  % file_suffix

    with open(MAIN_CODE_DIR + filepath, 'w') as output:

        for node, bc in score.iteritems():

            output.write('%s, %s\n' % (node, bc))

def read_complex_json(filepath):

    """Returns a graph object

    """

    edges = []

    with open(filepath) as f:

        doc = json.loads(f.read())

        topologies = doc["topology"]

        for connection in topologies:

            source = connection['lastHopIP']

            target = connection['destinationIP']

            cost = connection['neighborLinkQuality']

            edges.append((source, target, {'weight': cost}))

    graph = nx.Graph()

    print "Edges = %i\n" % len(edges)

    graph.add_edges_from(edges)

    return graph

def plot_graph(output_filepath, graph, title=""):

    plt.figure(1, figsize=(15, 10))

    plt.title(title)

    pos=nx.spring_layout(graph)

    colors=range(30)

    nx.draw(graph, pos, node_size=1000, with_label=True)

    nx.draw_networkx_labels(graph,pos,font_size=20,font_family='sans-serif')

    plt.savefig(output_filepath)

    plt.close()

    # plt.show()