コード例 #1
0
ファイル: menu.py プロジェクト: Nyaatan/GraphAlgoExperiments
 def load_graph(path, mode, directed):
     f = open(path, 'r+')
     for line in f.readlines():
         vals = [int(val) for val in line.split(' ')]
         if len(vals) == 2:
             if mode == 'matrix':
                 graph = Matrix(vals[1])
             else:
                 graph = ListGraph(vals[1])
         else:
             if mode == 'matrix':
                 graph.set(vals[0], vals[1], vals[2])
                 if directed and graph.get(vals[1], vals[0]) == 0:
                     graph.set(vals[1], vals[0], -1)
                 else:
                     graph.set(vals[1], vals[0], vals[2])
             else:
                 graph.add_connection(vals[0], vals[1], vals[2])
                 if not directed:
                     graph.add_connection(vals[1], vals[0], vals[2])
     return graph
コード例 #2
0
ファイル: menu.py プロジェクト: Nyaatan/GraphAlgoExperiments
    def generate_graph_nx(
            nodes: int,
            density,
            mode,
            directed,
            force=settings.force):  # graph generation using networkx
        bar = ProgBar(20, title='Generating graph', stream=sys.stdout)
        if directed:  # calculate edge count based on node count and density
            edges = nodes * (nodes - 1) * density
            if edges < nodes - 1 and not force:
                print(
                    "Minimum graph density for this problem is {:2.0%}. "
                    "To generate less dense graph anyway, set argument force to True."
                    .format(float(1 / nodes)),
                    file=sys.stderr)
                edges = nodes - 1
        else:
            edges = nodes * (nodes - 1) * density / 2
            if edges < nodes - 1 and not force:
                print(
                    "Minimum graph density for this problem is {:2.0%}. "
                    "To generate less dense graph anyway, set argument force to True."
                    .format(float(2 / nodes)),
                    file=sys.stderr)
                edges = nodes - 1
        bar.update()
        G = nx.generators.random_graphs.gnm_random_graph(
            nodes, edges, directed=directed)  # generate random graph
        bar.update()
        if not directed:  # check connectivity and generate new graph if failed
            while not nx.is_connected(G):
                G = nx.generators.random_graphs.gnm_random_graph(
                    nodes, edges, directed=directed)
        else:
            cont = False

            while not cont:
                cont = True
                for node in G.nodes:
                    if len([x for x in G.neighbors(node)]) == 0:
                        cont = False
                        G = nx.generators.random_graphs.gnm_random_graph(
                            nodes, edges, directed=directed)
                        break
        bar.update()
        if mode == 'matrix':  # convert generated networkx graph to own structure
            ret = Matrix(nodes)
            for x, y in G.edges:
                w = randint(1, nodes)
                ret.set(x, y, w)
                if directed and ret.get(y, x) == 0:
                    ret.set(y, x, 0)
                else:
                    ret.set(y, x, w)
                bar.update()
            return ret
        else:
            ret = ListGraph(nodes)
            for x, y in G.edges:
                w = randint(1, nodes)
                ret.add_connection(x, y, w)
                if not directed:
                    ret.add_connection(y, x, w)
                bar.update()
            return ret