我们从Python开源项目中，提取了以下6个代码示例，用于说明如何使用networkx.shell_layout()。
def draw(self, label_nodes=False): """Draw the graph using matplotlib in a color-coordinated manner.""" try: import matplotlib.pyplot as plt print 'Node colors: red=core, blue=major-building, green=distribution, yellow=minor-building, cyan=server,' \ ' magenta=host, black=floor-switch, white=rack-switch, white=cloud, green=gateway' # TODO: ignore building internals? colormap = {'c': 'r', 'b': 'b', 'd': 'g', 'm': 'y', 's': 'c', 'h': 'm', 'f': 'k', 'r': 'w', 'x': 'w', 'g': 'g'} node_colors = [colormap[node[0]] for node in self.topo.nodes()] # shell layout places nodes as a series of concentric circles positions = nx.shell_layout(self.topo, [self.core_nodes, # sort the building routers by degree in attempt to get ones connected to each other next to each other sorted(self.major_building_routers, key=lambda n: nx.degree(self.topo, n)) + self.distribution_routers + self.server_nodes, self.hosts + self.minor_building_routers]) # then do a spring layout, keeping the inner nodes fixed in positions positions = nx.spring_layout(self.topo, pos=positions, fixed=self.core_nodes + self.server_nodes + self.major_building_routers + self.distribution_routers) nx.draw(self.topo, node_color=node_colors, pos=positions, with_labels=label_nodes) plt.show() except ImportError: print "ERROR: couldn't draw graph as matplotlib.pyplot couldn't be imported!"
def save(self, path='out.png'): import networkx import matplotlib.pyplot as plt pos = networkx.spring_layout(self.graph, iterations=500) # pos = networkx.spectral_layout(self.graph) # pos = networkx.shell_layout(self.graph) # pos = networkx.fruchterman_reingold_layout(self.graph) nodelist = list(range(self.num_rooms)) networkx.draw_networkx_nodes(self.graph, pos, nodelist=nodelist) edgelist = sorted(self.edges - self.secret_edges) secret = sorted(self.secret_edges) networkx.draw_networkx_edges(self.graph, pos, edgelist=edgelist, edge_color='k') networkx.draw_networkx_edges(self.graph, pos, edgelist=secret, edge_color='r') networkx.draw_networkx_labels(self.graph, pos, self.labels) plt.savefig(path)
def plot_graph(self, file_name: str='graph.png', label_nodes: bool=True, label_edges: bool=True): import matplotlib.pyplot as plt # pos = nx.spring_layout(self.graph) pos = nx.shell_layout(self.graph, dim=1024, scale=0.5) # pos = nx.random_layout(self.graph, dim=1024, scale=0.5) if label_edges: edge_labels = { (edge[0], edge[1]): edge[2]['object'] for edge in self.graph.edges(data=True) } nx.draw_networkx_edge_labels(self.graph, pos, edge_labels, font_size=5) if label_nodes: labels = {node[0]: node[1] for node in self.graph.nodes(data=True)} nx.draw_networkx_labels(self.graph, pos, labels, font_size=5, alpha=0.8) # nx.draw(self.graph, with_labels=True, arrows=True, node_size=80) nx.draw_spectral(self.graph, with_labels=True, arrows=True, node_size=80) plt.savefig(file_name, dpi=1024)
def draw(self, layout='circular', figsize=None): """Draw all graphs that describe the DGM in a common figure Parameters ---------- layout : str possible are 'circular', 'shell', 'spring' figsize : tuple(int) tuple of two integers denoting the mpl figsize Returns ------- fig : figure """ layouts = { 'circular': nx.circular_layout, 'shell': nx.shell_layout, 'spring': nx.spring_layout } figsize = (10, 10) if figsize is None else figsize fig = plt.figure(figsize=figsize) rocls = np.ceil(np.sqrt(len(self.graphs))) for i, graph in enumerate(self.graphs): ax = fig.add_subplot(rocls, rocls, i+1) ax.set_title('Graph ' + str(i+1)) ax.axis('off') ax.set_frame_on(False) g = graph.nxGraph weights = [abs(g.edge[i][j]['weight']) * 5 for i, j in g.edges()] nx.draw_networkx(g, pos=layouts[layout](g), ax=ax, edge_cmap=plt.get_cmap('Reds'), width=2, edge_color=weights) return fig
def draw(self, layout='circular', figsize=None): """Draw graph in a matplotlib environment Parameters ---------- layout : str possible are 'circular', 'shell', 'spring' figsize : tuple(int) tuple of two integers denoting the mpl figsize Returns ------- fig : figure """ layouts = { 'circular': nx.circular_layout, 'shell': nx.shell_layout, 'spring': nx.spring_layout } figsize = (10, 10) if figsize is None else figsize fig = plt.figure(figsize=figsize) ax = fig.add_subplot(1, 1, 1) ax.axis('off') ax.set_frame_on(False) g = self.nxGraph weights = [abs(g.edge[i][j]['weight']) * 5 for i, j in g.edges()] nx.draw_networkx(g, pos=layouts[layout](g), ax=ax, edge_cmap=plt.get_cmap('Reds'), width=2, edge_color=weights) return fig
def prune_homology_graph(df, chim_dir): to_remove = [] df['brk_left_cut'] = df['name'].str.split(":").str[0:3].str.join(sep=":") df['brk_right_cut'] = df['name'].str.split(":").str[3:6].str.join(sep=":") left_nodes = set(df[df['brk_left_cut'].duplicated()]['brk_left_cut']) right_nodes = df[df['brk_right_cut'].duplicated()]['brk_right_cut'] all_nodes = list(zip(left_nodes, itertools.repeat("left"))) + list(zip(right_nodes, itertools.repeat("right"))) for node, hom_side in all_nodes: node_members = df[((df['brk_' + hom_side + '_cut'] == node))]['name'] node_graph = nx.Graph() node_graph.add_nodes_from(node_members, exprs=10) for jxn1, jxn2 in itertools.combinations(node_members, 2): pair_score = get_pairwise_hom(jxn1, jxn2, chim_dir, hom_side) if pair_score != 0: node_graph.add_edge(jxn1, jxn2, weight=pair_score) # nx.draw_networkx(node_graph, pos=nx.shell_layout(node_graph), node_size=100) # plt.show() adj_mat = nx.to_pandas_dataframe(node_graph) node_compare = adj_mat[adj_mat.sum()> 0].index.tolist() if len(node_compare) > 0: node_homdf = df[df['name'].isin(node_compare)][['name', 'TPM_Fusion', 'TPM_Left', 'TPM_Right']].set_index('name') node_homdf['max_pairs'] = node_homdf[['TPM_Left','TPM_Right']].max(axis=1) node_homdf = node_homdf.sort_values(['TPM_Fusion', 'max_pairs'] , ascending=False) node_remove = node_homdf.iloc[1:].index.tolist() to_remove.extend(node_remove) # use list of to_remove to mark homologous fusions return to_remove
