我有2000多个节点和900多个边缘,但当我尝试在networkx中制作图形时,我发现所有节点都挤在一起。我尝试更改属性值,例如scale,k,并发现它们没用,因为下面有数百个带有标签的节点,这意味着我无法选择小尺寸的节点。我想知道是否有一种方法来扩展canva或其他方法来增加节点距离以避免重叠,这样我就可以清楚地看到每个节点及其标签。
由于
答案 0 :(得分:1)
您可以按 ploty 使用交互式图形绘制大量节点和边。您可以更改每个属性,例如画布大小等,并通过缩放其他操作更轻松地将其可视化。
示例:
导入剧情
import plotly.graph_objects as go
import networkx as nx
在一条轨迹中将边缘添加为不连续的线,并在散布轨迹中添加节点
G = nx.random_geometric_graph(200, 0.125)
edge_x = []
edge_y = []
for edge in G.edges():
x0, y0 = G.nodes[edge[0]]['pos']
x1, y1 = G.nodes[edge[1]]['pos']
edge_x.append(x0)
edge_x.append(x1)
edge_x.append(None)
edge_y.append(y0)
edge_y.append(y1)
edge_y.append(None)
edge_trace = go.Scatter(
x=edge_x, y=edge_y,
line=dict(width=0.5, color='#888'),
hoverinfo='none',
mode='lines')
node_x = []
node_y = []
for node in G.nodes():
x, y = G.nodes[node]['pos']
node_x.append(x)
node_y.append(y)
node_trace = go.Scatter(
x=node_x, y=node_y,
mode='markers',
hoverinfo='text',
marker=dict(
showscale=True,
# colorscale options
#'Greys' | 'YlGnBu' | 'Greens' | 'YlOrRd' | 'Bluered' | 'RdBu' |
#'Reds' | 'Blues' | 'Picnic' | 'Rainbow' | 'Portland' | 'Jet' |
#'Hot' | 'Blackbody' | 'Earth' | 'Electric' | 'Viridis' |
colorscale='YlGnBu',
reversescale=True,
color=[],
size=10,
colorbar=dict(
thickness=15,
title='Node Connections',
xanchor='left',
titleside='right'
),
line_width=2))
通过连接数为节点指定颜色。
另一种选择是按连接数来确定点的大小,即node_trace.marker.size = node_adjacencies
node_adjacencies = []
node_text = []
for node, adjacencies in enumerate(G.adjacency()):
node_adjacencies.append(len(adjacencies[1]))
node_text.append('# of connections: '+str(len(adjacencies[1])))
node_trace.marker.color = node_adjacencies
node_trace.text = node_text
创建网络图
fig = go.Figure(data=[edge_trace, node_trace],
layout=go.Layout(
title='<br>Network graph made with Python',
titlefont_size=16,
showlegend=False,
hovermode='closest',
margin=dict(b=20,l=5,r=5,t=40),
annotations=[ dict(
text="Python code: <a href='https://plotly.com/ipython-notebooks/network-graphs/'> https://plotly.com/ipython-notebooks/network-graphs/</a>",
showarrow=False,
xref="paper", yref="paper",
x=0.005, y=-0.002 ) ],
xaxis=dict(showgrid=False, zeroline=False, showticklabels=False),
yaxis=dict(showgrid=False, zeroline=False, showticklabels=False))
)
fig.show()
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答案 1 :(得分:0)
当我遇到相同的问题时,我想出了我想要的节点在哪里,并将其作为从csv文件输入到networkx的输入:
f1 = csv.reader(open('nodes-C4-final.csv','r'),delimiter="\t")
for row in f1:
G.add_node(row[0], label=row[1], weight = float(row[3]), pos =(float(row[4]),float(row[5])))