In [1]:

    

from collections import Counter
from matplotlib import pyplot as plt


class Graph(object):
    """docstring for Graph"""
    def __init__(self, nodes=[], edges=[], directed=False):
        self._graph = dict()
        self._deg_dist = {}  # Degree Distribution
        if len(nodes):
            self.make_graph(nodes, edges, directed)

    def make_complete(self, num_nodes, directed=False):
        nodes = list(range(num_nodes))
        edges = [(node_1, node_2) for node_1 in nodes for node_2 in nodes if node_1 != node_2]
        self.make_graph(nodes, edges, directed)

    def make_graph(self, nodes, edges, directed=False):
        for node in nodes:
            self._graph[node] = set()

        if not directed:
            edges = set([sorted(edge) for edge in edges])

        for edge in edges:
            self._graph[edge[0]].add(edge[1])

    def in_degrees(self):
        """
        Returns a dictionary of in-degrees of the nodes
        of the input digraph
        """
        degrees = dict.fromkeys(self._graph, 0)
        edges = []
        for value in self._graph.values():
            edges += list(value)
        for edge in edges:
            degrees[edge] += 1
        return degrees

    def in_degree_distribution(self, normalized=False):
        """Returns the degree distribution of a digraph"""
        num_nodes = float(len(self._graph))
        degrees = self.in_degrees(self._graph)
        self._deg_dist = dict(Counter(degrees.values()))
        if normalized:
            for degree in iter(self._deg_dist):
                self._deg_dist[degree] /= num_nodes
        return self._deg_dist

    def plot(self, log=True, file_name='', title='', xlabel='', ylabel='', color='#634017'):
        if log:
            plt.loglog(self._graph.keys(), self._graph.values(), 'o', color=color)
        else:
            plt.plot(self._graph.keys(), self._graph.values(), 'o', color=color)

        plt.title(title, fontsize=18, color='#ff8800')
        plt.xlabel(xlabel, fontsize=14, color='#ff8800')
        plt.ylabel(ylabel, fontsize=14, color='#ff8800')
        if file_name:
            plt.savefig(file_name, dpi=300, format='png', transparent=False, orientation='landscape', bbox_inches='tight', pad_inches=0.3)


    

In [3]:

    

NODES_0 = [0, 1, 2]
EDGES_0 = [(0, 1), (0, 2)]
EX_GRAPH0 = Graph(NODES_0, EDGES_0, True)

NODES_1 = [0, 1, 2, 3, 4, 5, 6]
EDGES_1 = [(0, 1), (0, 4), (0, 5),
           (1, 2), (1, 6), (2, 3),
           (3, 0), (4, 1), (5, 2)]
EX_GRAPH1 = Graph(NODES_1, EDGES_1, True)

NODES_2 = [0, 1, 2, 3, 4, 5, 6, 7, 8, 9]
EDGES_2 = [(0, 1), (0, 4), (0, 5),
           (1, 2), (1, 6), (2, 3),
           (2, 7), (3, 7), (4, 1),
           (5, 2), (7, 3), (8, 1),
           (8, 2), (9, 0), (9, 3),
           (9, 4), (9, 5), (9, 6),
           (9, 7)]
EX_GRAPH2 = Graph(NODES_2, EDGES_2, True)


    

In [21]:

    

def load_graph_data(file_name):
    """
    Function that loads a graph given a text
    representation of the graph

    Returns a dictionary that models a graph
    """
    graph_file = open(file_name)
    graph_text = graph_file.read()
    graph_lines = graph_text.split('\n')
    graph_lines = graph_lines[:-1]
    
    print("Loaded graph with", len(graph_lines), "nodes")
    
    nodes = []
    edges = []
    for line in graph_lines:
        neighbors = line.split(' ')
        node = int(neighbors[0])
        nodes.append(node)
        for neighbor in neighbors[1:-1]:
            edges.append((node, neighbor))
    return nodes, edges


    

In [22]:

    

citation_graph_data = load_graph_data('alg_phys-cite.txt')


    

    




Loaded graph with 27770 nodes

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