如何将标签名称添加到线标签？
How can I add label names to the line labels?
我正在研究可视化，基本上，我已经能够创建我想要的东西，但是，我在标记边缘或（线）时遇到了问题。
我想做的是在节点上添加节点名，在线上添加标签名。
任何帮助都会非常好，即使花了很长时间搜索也找不到解决方案。
A = list(result["antecedents"])
B = list(result["consequent"])
Edges= list(result["edges"])
node_list = list(set(A+B))
G = nx.Graph()
for i in node_list:
G.add_node(i)
pos = nx.spring_layout(G, k=0.5, iterations=50)
for n, p in pos.items():
G.nodes[n]['pos'] = p
edge_trace = go.Scatter(
x=[],
y=[],
line=dict(width=0.5,color='#888'),
hoverinfo='none',
mode='lines')
for edge in G.edges():
x0, y0 = G.nodes[edge[0]]['pos']
x1, y1 = G.nodes[edge[1]]['pos']
edge_trace['x'] += tuple([x0, x1, None])
edge_trace['y'] += tuple([y0, y1, None])
node_trace = go.Scatter(
x=[],
y=[],
text=[],
mode='markers',
hoverinfo='text',
marker=dict(
showscale=True,
colorscale='RdBu',
reversescale=True,
color=[],
size=15,
colorbar=dict(
thickness=10,
title='Node Connections',
xanchor='left',
titleside='right'
),
line=dict(width=0)))
for node in G.nodes():
x, y = G.nodes[node]['pos']
node_trace['x'] += tuple([x])
node_trace['y'] += tuple([y])
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_text.append(adjacencies[0])
node_trace.marker.color = node_adjacencies
node_trace.text = node_text
for node, adjacencies in enumerate(G.adjacency()):
node_info = (adjacencies[0] ,' # of connections: ' ,str(len(adjacencies[1])))
node_trace['text']+=tuple([node_info])
fig = go.Figure(data=[edge_trace, node_trace],
layout=go.Layout(
title='<br>Association Rules connections',
titlefont=dict(size=16),
showlegend=False,
hovermode='closest',
margin=dict(b=20,l=5,r=5,t=40),
annotations=[ dict(
text="",
showarrow=True,
xref="paper", yref="paper") ],
xaxis=dict(showgrid=False, zeroline=False, showticklabels=False),
yaxis=dict(showgrid=False, zeroline=False, showticklabels=False)))
iplot(fig)```
This is what I currently have:
[enter image description here][1]
But I want to see something like:
[enter image description here][2]
[1]: https://i.stack.imgur.com/tleyG.png
[2]: https://i.stack.imgur.com/iKlah.png
Basically, I would like to see node names and and label on lines. this is what I want to visualize:
antecedents edges consequent
0 ?c parent ?a
1 ?c <isMarriedTo> ?b
2 ?b parent ?a
smth: ?c ----- parent -----> ?a
Thank you in advance.
您没有提供数据集，而且您的问题格式有点混乱。然而 fig.add_annotation 应该是去这里的方式。无论您使用什么网络图，您都应该能够通过 fig.data[0].x 和 fig.data[0].x 检索 x 和 y 坐标。然后你可以为你的节点 and/or 行构建一个伴随的注释列表，如下所示：
nodeText = ['This', 'is', 'what', 'I', 'would', 'like', 'to', 'say.']*100
然后用这个注释你喜欢的任何东西：
# zipped list of x and y coordinates
z = list(zip(fig.data[0].x, fig.data[0].y))
# some labels
nodeText = ['This', 'is', 'what', 'I', 'would', 'like', 'to', 'say.']*100
# annotate your figure
for i, e in enumerate(z):
if e[0] is not None:
fig.add_annotation(x=e[0],
y=e[1],
text = nodeText[i],
showarrow = False,
xshift = -25
)
剧情：
完整代码：
import plotly.graph_objects as go
import random
import networkx as nx
import numpy as np
random.seed(123)
np.random.seed(123)
G = nx.random_geometric_graph(16, 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))
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
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))
)
# zipped list of x and y coordinates
z = list(zip(fig.data[0].x, fig.data[0].y))
# some labels
nodeText = ['This', 'is', 'what', 'I', 'would', 'like', 'to', 'say.']*100
# annotate your figure
for i, e in enumerate(z):
if e[0] is not None:
fig.add_annotation(x=e[0],
y=e[1],
text = nodeText[i],
showarrow = False,
xshift = -25
)
fig.show()
我正在研究可视化，基本上，我已经能够创建我想要的东西，但是，我在标记边缘或（线）时遇到了问题。 我想做的是在节点上添加节点名，在线上添加标签名。 任何帮助都会非常好，即使花了很长时间搜索也找不到解决方案。
A = list(result["antecedents"])
B = list(result["consequent"])
Edges= list(result["edges"])
node_list = list(set(A+B))
G = nx.Graph()
for i in node_list:
G.add_node(i)
pos = nx.spring_layout(G, k=0.5, iterations=50)
for n, p in pos.items():
G.nodes[n]['pos'] = p
edge_trace = go.Scatter(
x=[],
y=[],
line=dict(width=0.5,color='#888'),
hoverinfo='none',
mode='lines')
for edge in G.edges():
x0, y0 = G.nodes[edge[0]]['pos']
x1, y1 = G.nodes[edge[1]]['pos']
edge_trace['x'] += tuple([x0, x1, None])
edge_trace['y'] += tuple([y0, y1, None])
node_trace = go.Scatter(
x=[],
y=[],
text=[],
mode='markers',
hoverinfo='text',
marker=dict(
showscale=True,
colorscale='RdBu',
reversescale=True,
color=[],
size=15,
colorbar=dict(
thickness=10,
title='Node Connections',
xanchor='left',
titleside='right'
),
line=dict(width=0)))
for node in G.nodes():
x, y = G.nodes[node]['pos']
node_trace['x'] += tuple([x])
node_trace['y'] += tuple([y])
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_text.append(adjacencies[0])
node_trace.marker.color = node_adjacencies
node_trace.text = node_text
for node, adjacencies in enumerate(G.adjacency()):
node_info = (adjacencies[0] ,' # of connections: ' ,str(len(adjacencies[1])))
node_trace['text']+=tuple([node_info])
fig = go.Figure(data=[edge_trace, node_trace],
layout=go.Layout(
title='<br>Association Rules connections',
titlefont=dict(size=16),
showlegend=False,
hovermode='closest',
margin=dict(b=20,l=5,r=5,t=40),
annotations=[ dict(
text="",
showarrow=True,
xref="paper", yref="paper") ],
xaxis=dict(showgrid=False, zeroline=False, showticklabels=False),
yaxis=dict(showgrid=False, zeroline=False, showticklabels=False)))
iplot(fig)```
This is what I currently have:
[enter image description here][1]
But I want to see something like:
[enter image description here][2]
[1]: https://i.stack.imgur.com/tleyG.png
[2]: https://i.stack.imgur.com/iKlah.png
Basically, I would like to see node names and and label on lines. this is what I want to visualize:
antecedents edges consequent
0 ?c parent ?a
1 ?c <isMarriedTo> ?b
2 ?b parent ?a
smth: ?c ----- parent -----> ?a
Thank you in advance.
您没有提供数据集，而且您的问题格式有点混乱。然而 fig.add_annotation 应该是去这里的方式。无论您使用什么网络图，您都应该能够通过 fig.data[0].x 和 fig.data[0].x 检索 x 和 y 坐标。然后你可以为你的节点 and/or 行构建一个伴随的注释列表，如下所示：
nodeText = ['This', 'is', 'what', 'I', 'would', 'like', 'to', 'say.']*100
然后用这个注释你喜欢的任何东西：
# zipped list of x and y coordinates
z = list(zip(fig.data[0].x, fig.data[0].y))
# some labels
nodeText = ['This', 'is', 'what', 'I', 'would', 'like', 'to', 'say.']*100
# annotate your figure
for i, e in enumerate(z):
if e[0] is not None:
fig.add_annotation(x=e[0],
y=e[1],
text = nodeText[i],
showarrow = False,
xshift = -25
)
剧情：
完整代码：
import plotly.graph_objects as go
import random
import networkx as nx
import numpy as np
random.seed(123)
np.random.seed(123)
G = nx.random_geometric_graph(16, 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))
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
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))
)
# zipped list of x and y coordinates
z = list(zip(fig.data[0].x, fig.data[0].y))
# some labels
nodeText = ['This', 'is', 'what', 'I', 'would', 'like', 'to', 'say.']*100
# annotate your figure
for i, e in enumerate(z):
if e[0] is not None:
fig.add_annotation(x=e[0],
y=e[1],
text = nodeText[i],
showarrow = False,
xshift = -25
)
fig.show()