Python networkx.draw_networkx_labels方法代碼示例

# 需要導入模塊: import networkx [as 別名]
# 或者: from networkx import draw_networkx_labels [as 別名]
def plot_alerts(_g, _bank_accts, _output_png):
    bank_ids = _bank_accts.keys()
    cmap = plt.get_cmap("tab10")
    pos = nx.nx_agraph.graphviz_layout(_g)

    plt.figure(figsize=(12.0, 8.0))
    plt.axis('off')

    for i, bank_id in enumerate(bank_ids):
        color = cmap(i)
        members = _bank_accts[bank_id]
        nx.draw_networkx_nodes(_g, pos, members, node_size=300, node_color=color, label=bank_id)
        nx.draw_networkx_labels(_g, pos, {n: n for n in members}, font_size=10)

    edge_labels = nx.get_edge_attributes(_g, "label")
    nx.draw_networkx_edges(_g, pos)
    nx.draw_networkx_edge_labels(_g, pos, edge_labels, font_size=6)

    plt.legend(numpoints=1)
    plt.subplots_adjust(left=0, right=1, bottom=0, top=1)
    plt.savefig(_output_png, dpi=120) 

# 需要導入模塊: import networkx [as 別名]
# 或者: from networkx import draw_networkx_labels [as 別名]
def graph_att_head(M, N, weight, ax, title):
    "credit: Jinjing Zhou"
    in_nodes=len(M)
    out_nodes=len(N)

    g = nx.bipartite.generators.complete_bipartite_graph(in_nodes,out_nodes)
    X, Y = bipartite.sets(g)
    height_in = 10
    height_out = height_in 
    height_in_y = np.linspace(0, height_in, in_nodes)
    height_out_y = np.linspace((height_in - height_out) / 2, height_out, out_nodes)
    pos = dict()
    pos.update((n, (1, i)) for i, n in zip(height_in_y, X))  # put nodes from X at x=1
    pos.update((n, (3, i)) for i, n in zip(height_out_y, Y))  # put nodes from Y at x=2
    ax.axis('off')
    ax.set_xlim(-1,4)
    ax.set_title(title)
    nx.draw_networkx_nodes(g, pos, nodelist=range(in_nodes), node_color='r', node_size=50, ax=ax)
    nx.draw_networkx_nodes(g, pos, nodelist=range(in_nodes, in_nodes + out_nodes), node_color='b', node_size=50, ax=ax)
    for edge in g.edges():
        nx.draw_networkx_edges(g, pos, edgelist=[edge], width=weight[edge[0], edge[1] - in_nodes] * 1.5, ax=ax)
    nx.draw_networkx_labels(g, pos, {i:label + '  ' for i,label in enumerate(M)},horizontalalignment='right', font_size=8, ax=ax)
    nx.draw_networkx_labels(g, pos, {i+in_nodes:'  ' + label for i,label in enumerate(N)},horizontalalignment='left', font_size=8, ax=ax) 

# 需要導入模塊: import networkx [as 別名]
# 或者: from networkx import draw_networkx_labels [as 別名]
def draw_wstate_tree(svm):
    import matplotlib.pyplot as plt
    import networkx as nx
    from networkx.drawing.nx_agraph import write_dot, graphviz_layout

    G = nx.DiGraph()
    pending_list = [svm.root_wstate]
    while len(pending_list):
        root = pending_list.pop()
        for trace, children in root.trace_to_children.items():
            for c in children:
                G.add_edge(repr(root), repr(c), label=trace)
                pending_list.append(c)
    # pos = nx.spring_layout(G)
    pos = graphviz_layout(G, prog='dot')
    edge_labels = nx.get_edge_attributes(G, 'label')
    nx.draw(G, pos)
    nx.draw_networkx_edge_labels(G, pos, edge_labels, font_size=8)
    nx.draw_networkx_labels(G, pos, font_size=10)
    plt.show() 

# 需要導入模塊: import networkx [as 別名]
# 或者: from networkx import draw_networkx_labels [as 別名]
def draw_graph(graph, output):
        """If matplotlib is available, draw the given graph to output file"""
        try:
            layout = nx.spring_layout(graph)
            metrics = {
                (src, dst): data['metric']
                for src, dst, data in graph.edges_iter(data=True)
            }
            nx.draw_networkx_edge_labels(graph, layout, edge_labels=metrics)
            nx.draw(graph, layout, node_size=20)
            nx.draw_networkx_labels(graph, layout,
                                    labels={n: n for n in graph})
            if os.path.exists(output):
                os.unlink(output)
            plt.savefig(output)
            plt.close()
            log.debug('Graph of %d nodes saved in %s', len(graph), output)
        except:
            pass 

# 需要導入模塊: import networkx [as 別名]
# 或者: from networkx import draw_networkx_labels [as 別名]
def build_word_ego_graph():
    import networkx as nx
    import matplotlib.pyplot as plt
    plt.rcParams['font.sans-serif'] = ['SimHei']  # 步驟一（替換sans-serif字體）
    plt.rcParams['axes.unicode_minus'] = False  # 步驟二（解決坐標軸負數的負號顯示問題）
    from harvesttext import get_sanguo, get_sanguo_entity_dict, get_baidu_stopwords

    ht0 = HarvestText()
    entity_mention_dict, entity_type_dict = get_sanguo_entity_dict()
    ht0.add_entities(entity_mention_dict, entity_type_dict)
    sanguo1 = get_sanguo()[0]
    stopwords = get_baidu_stopwords()
    docs = ht0.cut_sentences(sanguo1)
    G = ht0.build_word_ego_graph(docs,"劉備",min_freq=3,other_min_freq=2,stopwords=stopwords)
    pos = nx.kamada_kawai_layout(G)
    nx.draw(G,pos)
    nx.draw_networkx_labels(G,pos)
    plt.show()
    G = ht0.build_entity_ego_graph(docs, "劉備", min_freq=3, other_min_freq=2)
    pos = nx.spring_layout(G)
    nx.draw(G, pos)
    nx.draw_networkx_labels(G, pos)
    plt.show() 

# 需要導入模塊: import networkx [as 別名]
# 或者: from networkx import draw_networkx_labels [as 別名]
def plot_subgraph(self, region_start, region_stop, seq_name, neighbours=0):
		"""
		Return a plot of a sub-graph from a defined region with positions relative to some of the sequences.
		:param region_start: Start position (bp)
		:param region_stop: Stop position (bp)
		:param seq_name: Sequence ID that the bp positions are relative to.
		:param neighbours: Number of neighbours to be included. Currently testing, only 1 level available.
		:return: Plots a netowrkx + matplotlib figure of the region subgraph.
		"""

		sub_graph = extract_region_subgraph(self, region_start, region_stop, seq_name, neighbours=neighbours)
		pos = nx.spring_layout(sub_graph)
		nx.draw_networkx_nodes(sub_graph, pos, cmap=plt.get_cmap('jet'), node_size=300)
		nx.draw_networkx_labels(sub_graph, pos)
		nx.draw_networkx_edges(sub_graph, pos, arrows=True)
		plt.show() 

# 需要導入模塊: import networkx [as 別名]
# 或者: from networkx import draw_networkx_labels [as 別名]
def replay(self, graph):
        """Draw the given graph."""
        fig, ax = plt.subplots(frameon=False)  # pylint:disable=invalid-name
        plt.subplots_adjust(left=0, right=1, top=1, bottom=0)

        node_pos = graph.node_coordinates

        def _update(num):
            ax.clear()

            fig.canvas.set_window_title(f'{graph.name} - Iteration ({num+1}/{len(self.__edge_colors)})')

            nodes_artist = nx.draw_networkx_nodes(graph.networkx_graph, pos=node_pos, ax=ax, node_color=self.__node_color)
            labels_artist = nx.draw_networkx_labels(graph.networkx_graph, pos=node_pos, ax=ax)
            edges_artist = nx.draw_networkx_edges(graph.networkx_graph, pos=node_pos, width=self.__edge_widths[num], edge_color=self.__edge_colors[num], ax=ax)

            return nodes_artist, labels_artist, edges_artist

        _ = animation.FuncAnimation(fig, _update, frames=len(self.__edge_colors), interval=self.__interval, repeat=self.__continuous)
        plt.show() 

# 需要導入模塊: import networkx [as 別名]
# 或者: from networkx import draw_networkx_labels [as 別名]
def draw_graph(self):
        nx.draw_shell(self.G, with_labels=True, font_weight='bold')

        # pos = graphviz_layout(self.G)
        # plt.axis('off')
        # nx.draw_networkx_nodes(self.G,pos,node_color='g',alpha = 0.8)
        # nx.draw_networkx_edges(self.G,pos,edge_color='b',alpha = 0.6)
        # nx.draw_networkx_edge_labels(self.G,pos,edge_labels = \
        # nx.get_edge_attributes(self.G,'weight'))
        # nx.draw_networkx_labels(self.G,pos) # node lables

        plt.savefig('graph.png') 

# 需要導入模塊: import networkx [as 別名]
# 或者: from networkx import draw_networkx_labels [as 別名]
def malt_demo(nx=False):
    """
    A demonstration of the result of reading a dependency
    version of the first sentence of the Penn Treebank.
    """
    dg = DependencyGraph("""Pierre  NNP     2       NMOD
Vinken  NNP     8       SUB
,       ,       2       P
61      CD      5       NMOD
years   NNS     6       AMOD
old     JJ      2       NMOD
,       ,       2       P
will    MD      0       ROOT
join    VB      8       VC
the     DT      11      NMOD
board   NN      9       OBJ
as      IN      9       VMOD
a       DT      15      NMOD
nonexecutive    JJ      15      NMOD
director        NN      12      PMOD
Nov.    NNP     9       VMOD
29      CD      16      NMOD
.       .       9       VMOD
""")
    tree = dg.tree()
    tree.pprint()
    if nx:
        # currently doesn't work
        import networkx
        from matplotlib import pylab

        g = dg.nx_graph()
        g.info()
        pos = networkx.spring_layout(g, dim=1)
        networkx.draw_networkx_nodes(g, pos, node_size=50)
        # networkx.draw_networkx_edges(g, pos, edge_color='k', width=8)
        networkx.draw_networkx_labels(g, pos, dg.nx_labels)
        pylab.xticks([])
        pylab.yticks([])
        pylab.savefig('tree.png')
        pylab.show() 

# 需要導入模塊: import networkx [as 別名]
# 或者: from networkx import draw_networkx_labels [as 別名]
def plot(cg):
    """
    Plot the call graph using matplotlib
    For larger graphs, this should not be used, as it is very slow
    and probably you can not see anything on it.

    :param cg: A networkx call graph to plot
    """
    from androguard.core.analysis.analysis import ExternalMethod
    import matplotlib.pyplot as plt
    import networkx as nx
    pos = nx.spring_layout(cg)

    internal = []
    external = []

    for n in cg.node:
        if isinstance(n, ExternalMethod):
            external.append(n)
        else:
            internal.append(n)

    nx.draw_networkx_nodes(cg, pos=pos, node_color='r', nodelist=internal)
    nx.draw_networkx_nodes(cg, pos=pos, node_color='b', nodelist=external)
    nx.draw_networkx_edges(cg, pos, arrow=True)
    nx.draw_networkx_labels(cg, pos=pos,
                            labels={x: "{} {}".format(x.get_class_name(),
                                                      x.get_name())
                                    for x in cg.edge})
    plt.draw()
    plt.show() 

# 需要導入模塊: import networkx [as 別名]
# 或者: from networkx import draw_networkx_labels [as 別名]
def _draw_node_labels(self, labels, **kwargs):
        pos = kwargs.pop('pos', self._pos)
        return nx.draw_networkx_labels(self._G, pos, labels=labels, **kwargs) 

# 需要導入模塊: import networkx [as 別名]
# 或者: from networkx import draw_networkx_labels [as 別名]
def plot_graph(self):
    import matplotlib.pyplot as plt

    pos=networkx.spring_layout(self.G,iterations=2000)
    #pos=networkx.spectral_layout(G)
    #pos = networkx.random_layout(G)
    networkx.draw_networkx_nodes(self.G, pos)
    networkx.draw_networkx_edges(self.G, pos, arrows=True)
    networkx.draw_networkx_labels(self.G, pos)
    plt.show() 

# 需要導入模塊: import networkx [as 別名]
# 或者: from networkx import draw_networkx_labels [as 別名]
def draw_transmat_graph(G, edge_threshold=0, lw=1, ec='0.2', node_size=15):

    num_states = G.number_of_nodes()

    edgewidth = [ d['weight'] for (u,v,d) in G.edges(data=True)]
    edgewidth = np.array(edgewidth)
    edgewidth[edgewidth<edge_threshold] = 0

    labels = {}
    labels[0] = '1'
    labels[1]= '2'
    labels[2]= '3'
    labels[num_states-1] = str(num_states)

    npos=circular_layout(G, scale=1, direction='CW')
    lpos=circular_layout(G, scale=1.15, direction='CW')

    nx.draw_networkx_edges(G, npos, alpha=0.8, width=edgewidth*lw, edge_color=ec)

    nx.draw_networkx_nodes(G, npos, node_size=node_size, node_color='k',alpha=0.8)
    ax = plt.gca()
    nx.draw_networkx_labels(G, lpos, labels, fontsize=18, ax=ax); # fontsize does not seem to work :/

    ax.set_aspect('equal')

    return ax 

# 需要導入模塊: import networkx [as 別名]
# 或者: from networkx import draw_networkx_labels [as 別名]
def make_snap(self, step, output_file="None",draw_connection_line=False,G=None):
        self.track_code_last_position = self.get_all_points_from_videoframe(step)

        self.axarr.texts = []
        self.clear_frequency()
        self.update_coverage_regions()
        self.show_frequency(draw_connection_line=draw_connection_line)

        # showing the STEP in the upper left corner of the figure
        size = self.fig.get_size_inches() * self.fig.dpi
        plt.text(size[0]*0.02, size[1]*0.05,"Step: %i"%step, dict(size=10, color='b'))

        # showing the GRAPH
        if G !=None:
            pos = nx.spring_layout(G,seed=1)
            # pos = map_endpoints
            pos = [[pos[x][0], pos[x][1]] for x in G.nodes()]
            pos = np.array(pos)
            pos[:, 0] = (pos[:, 0] - pos[:, 0].min()) / (pos[:, 0].max() - pos[:, 0].min())
            pos[:, 1] = (pos[:, 1] - pos[:, 1].min()) / (pos[:, 1].max() - pos[:, 1].min())
            size = self.fig.get_size_inches() * self.fig.dpi * 1.5
            pos = [self.point_network_map(x, size) for x in pos]
            pos = dict(zip(G.nodes(),pos))

            nx.draw(G, pos,with_labels=False,node_size=100,nodelist=self.sim.name_endpoints.values(),node_color="#1260A0",node_shape="o")
            # rest_nodes = [e for e in G.nodes() if e not in self.sim.name_endpoints.values()]
            nodes_level_mobile = self.get_nodes_by_level(G,-1)
            nobes_upper_level = self.get_nodes_by_upper_level(G,1)
            nx.draw(G, pos,with_labels=False,node_size=100,nodelist=nodes_level_mobile,node_shape="^",node_color="orange")
            nx.draw(G, pos,with_labels=True,node_size=100,nodelist=nobes_upper_level,node_shape="s",node_color="red",font_size=8)
            # labels = nx.draw_networkx_labels(G, pos)



        canvas = plt.get_current_fig_manager().canvas
        canvas.draw()
        pil_image = Image.frombytes('RGB', canvas.get_width_height(), canvas.tostring_rgb())
        pil_image.save(output_file+".png")
        plt.close('all') 

# 需要導入模塊: import networkx [as 別名]
# 或者: from networkx import draw_networkx_labels [as 別名]
def draw_png(self,path_file):
        fig, ax = plt.subplots(nrows=1, ncols=1)
        pos = nx.spring_layout(self.G)
        nx.draw(self.G, pos)
        labels = nx.draw_networkx_labels(self.G, pos)
        fig.savefig(path_file)  # save the figure to file
        plt.close(fig)  # close the figure