Python networkx.eulerian_circuit方法代碼示例

# 需要導入模塊: import networkx [as 別名]
# 或者: from networkx import eulerian_circuit [as 別名]
def run_diffusion_process(self, node):
        """
        Generating a diffusion tree from a given source node.
        Linearizing it with an Eulerian tour.
        :param node: Source of diffusion.
        :return euler: Eulerian linear node sequence.
        """
        infected = [node]
        sub_graph = nx.DiGraph()
        sub_graph.add_node(node)
        infected_counter = 1
        while infected_counter < self.number_of_nodes:
            end_point = random.sample(infected, 1)[0]
            nebs = [node for node in self.graph.neighbors(end_point)]
            sample = random.sample(nebs, 1)[0]
            if sample not in infected:
                infected_counter = infected_counter + 1
                infected = infected + [sample]
                sub_graph.add_edges_from([(end_point, sample), (sample, end_point)])
                if infected_counter == self.number_of_nodes:
                    break
        euler = [str(u) for u, v in nx.eulerian_circuit(sub_graph, infected[0])]
        if len(euler) == 0:
            euler = [str(u) for u, v in nx.eulerian_circuit(graph, infected[0])]
        return euler 

# 需要導入模塊: import networkx [as 別名]
# 或者: from networkx import eulerian_circuit [as 別名]
def test_eulerian_circuit_cycle(self):
        G=nx.cycle_graph(4)

        edges=list(eulerian_circuit(G,source=0))
        nodes=[u for u,v in edges]
        assert_equal(nodes,[0,3,2,1])
        assert_equal(edges,[(0,3),(3,2),(2,1),(1,0)])

        edges=list(eulerian_circuit(G,source=1))
        nodes=[u for u,v in edges]
        assert_equal(nodes,[1,2,3,0])
        assert_equal(edges,[(1,2),(2,3),(3,0),(0,1)])

        G=nx.complete_graph(3)
        
        edges=list(eulerian_circuit(G,source=0))
        nodes=[u for u,v in edges]
        assert_equal(nodes,[0,2,1])
        assert_equal(edges,[(0,2),(2,1),(1,0)])
        
        edges=list(eulerian_circuit(G,source=1))
        nodes=[u for u,v in edges]
        assert_equal(nodes,[1,2,0])
        assert_equal(edges,[(1,2),(2,0),(0,1)]) 

# 需要導入模塊: import networkx [as 別名]
# 或者: from networkx import eulerian_circuit [as 別名]
def test_eulerian_circuit_cycle(self):
        G = nx.cycle_graph(4)

        edges = list(eulerian_circuit(G, source=0))
        nodes = [u for u, v in edges]
        assert_equal(nodes, [0, 3, 2, 1])
        assert_equal(edges, [(0, 3), (3, 2), (2, 1), (1, 0)])

        edges = list(eulerian_circuit(G, source=1))
        nodes = [u for u, v in edges]
        assert_equal(nodes, [1, 2, 3, 0])
        assert_equal(edges, [(1, 2), (2, 3), (3, 0), (0, 1)])

        G = nx.complete_graph(3)

        edges = list(eulerian_circuit(G, source=0))
        nodes = [u for u, v in edges]
        assert_equal(nodes, [0, 2, 1])
        assert_equal(edges, [(0, 2), (2, 1), (1, 0)])

        edges = list(eulerian_circuit(G, source=1))
        nodes = [u for u, v in edges]
        assert_equal(nodes, [1, 2, 0])
        assert_equal(edges, [(1, 2), (2, 0), (0, 1)]) 

# 需要導入模塊: import networkx [as 別名]
# 或者: from networkx import eulerian_circuit [as 別名]
def _run_diffusion_process(self, node):
        """
        Generating a diffusion tree from a given source node and linearizing it
        with a directed Eulerian tour.

        Arg types:
            * **node** *(int)* - The source node of the diffusion.
        Return types:
            * **euler** *(list of strings)* - The list of nodes in the walk.
        """
        infected = [node]
        sub_graph = nx.DiGraph()
        sub_graph.add_node(node)
        infected_counter = 1
        while infected_counter < self.diffusion_cover:
            end_point = random.sample(infected, 1)[0]
            nebs = [node for node in self.graph.neighbors(end_point)]
            sample = random.choice(nebs)
            if sample not in infected:
                infected_counter = infected_counter + 1
                infected = infected + [sample]
                sub_graph.add_edges_from([(end_point, sample), (sample, end_point)])
                if infected_counter == self.diffusion_cover:
                    break
        euler = [str(u) for u, v in nx.eulerian_circuit(sub_graph, infected[0])]
        return euler 

# 需要導入模塊: import networkx [as 別名]
# 或者: from networkx import eulerian_circuit [as 別名]
def test_eulerian_circuit_digraph(self):
        G=nx.DiGraph()
        G.add_cycle([0,1,2,3])

        edges=list(eulerian_circuit(G,source=0))
        nodes=[u for u,v in edges]
        assert_equal(nodes,[0,1,2,3])
        assert_equal(edges,[(0,1),(1,2),(2,3),(3,0)])

        edges=list(eulerian_circuit(G,source=1))
        nodes=[u for u,v in edges]
        assert_equal(nodes,[1,2,3,0])
        assert_equal(edges,[(1,2),(2,3),(3,0),(0,1)]) 

# 需要導入模塊: import networkx [as 別名]
# 或者: from networkx import eulerian_circuit [as 別名]
def test_eulerian_circuit_multigraph(self):
        G=nx.MultiGraph()
        G.add_cycle([0,1,2,3])
        G.add_edge(1,2)
        G.add_edge(1,2)
        edges=list(eulerian_circuit(G,source=0))
        nodes=[u for u,v in edges]
        assert_equal(nodes,[0,3,2,1,2,1])
        assert_equal(edges,[(0,3),(3,2),(2,1),(1,2),(2,1),(1,0)]) 

# 需要導入模塊: import networkx [as 別名]
# 或者: from networkx import eulerian_circuit [as 別名]
def test_not_eulerian(self):    
        f=list(eulerian_circuit(nx.complete_graph(4))) 

# 需要導入模塊: import networkx [as 別名]
# 或者: from networkx import eulerian_circuit [as 別名]
def test_eulerian_circuit_digraph(self):
        G = nx.DiGraph()
        nx.add_cycle(G, [0, 1, 2, 3])

        edges = list(eulerian_circuit(G, source=0))
        nodes = [u for u, v in edges]
        assert_equal(nodes, [0, 1, 2, 3])
        assert_equal(edges, [(0, 1), (1, 2), (2, 3), (3, 0)])

        edges = list(eulerian_circuit(G, source=1))
        nodes = [u for u, v in edges]
        assert_equal(nodes, [1, 2, 3, 0])
        assert_equal(edges, [(1, 2), (2, 3), (3, 0), (0, 1)]) 

# 需要導入模塊: import networkx [as 別名]
# 或者: from networkx import eulerian_circuit [as 別名]
def test_multigraph(self):
        G = nx.MultiGraph()
        nx.add_cycle(G, [0, 1, 2, 3])
        G.add_edge(1, 2)
        G.add_edge(1, 2)
        edges = list(eulerian_circuit(G, source=0))
        nodes = [u for u, v in edges]
        assert_equal(nodes, [0, 3, 2, 1, 2, 1])
        assert_equal(edges, [(0, 3), (3, 2), (2, 1), (1, 2), (2, 1), (1, 0)]) 

# 需要導入模塊: import networkx [as 別名]
# 或者: from networkx import eulerian_circuit [as 別名]
def test_multigraph_with_keys(self):
        G = nx.MultiGraph()
        nx.add_cycle(G, [0, 1, 2, 3])
        G.add_edge(1, 2)
        G.add_edge(1, 2)
        edges = list(eulerian_circuit(G, source=0, keys=True))
        nodes = [u for u, v, k in edges]
        assert_equal(nodes, [0, 3, 2, 1, 2, 1])
        assert_equal(edges[:2], [(0, 3, 0), (3, 2, 0)])
        assert_count_equal(edges[2:5], [(2, 1, 0), (1, 2, 1), (2, 1, 2)])
        assert_equal(edges[5:], [(1, 0, 0)]) 

# 需要導入模塊: import networkx [as 別名]
# 或者: from networkx import eulerian_circuit [as 別名]
def test_not_eulerian(self):
        f = list(eulerian_circuit(nx.complete_graph(4))) 

# 需要導入模塊: import networkx [as 別名]
# 或者: from networkx import eulerian_circuit [as 別名]
def create_eulerian_circuit(graph_augmented, graph_original, start_node=None):
    """
    networkx.eulerian_circuit only returns the order in which we hit each node.  It does not return the attributes of the
    edges needed to complete the circuit.  This is necessary for the postman problem where we need to keep track of which
    edges have been covered already when multiple edges exist between two nodes.
    We also need to annotate the edges added to make the eulerian to follow the actual shortest path trails (not
    the direct shortest path pairings between the odd nodes for which there might not be a direct trail)

    Args:
        graph_augmented (networkx graph): graph w links between odd degree nodes created from `add_augmenting_path_to_graph`.
        graph_original (networkx graph): orginal graph created from `create_networkx_graph_from_edgelist`
        start_node (str): name of starting (and ending) node for CPP solution.

    Returns:
        networkx graph (`graph_original`) augmented with edges directly between the odd nodes
    """

    euler_circuit = list(nx.eulerian_circuit(graph_augmented, source=start_node, keys=True))
    assert len(graph_augmented.edges()) == len(euler_circuit), 'graph and euler_circuit do not have equal number of edges.'

    for edge in euler_circuit:
        aug_path = nx.shortest_path(graph_original, edge[0], edge[1], weight='distance')
        edge_attr = graph_augmented[edge[0]][edge[1]][edge[2]]
        if not edge_attr.get('augmented'):
            yield edge + (edge_attr,)
        else:
            for edge_aug in list(zip(aug_path[:-1], aug_path[1:])):
                # find edge with shortest distance (if there are two parallel edges between the same nodes)
                edge_aug_dict = graph_original[edge_aug[0]][edge_aug[1]]
                edge_key = min(edge_aug_dict.keys(), key=(lambda k: edge_aug_dict[k]['distance']))  # index with min distance
                edge_aug_shortest = edge_aug_dict[edge_key]
                edge_aug_shortest['augmented'] = True
                edge_aug_shortest['id'] = edge_aug_dict[edge_key]['id']
                yield edge_aug + (edge_key, edge_aug_shortest, )