File size: 3,596 Bytes
a93d680 c86f6cb a93d680 45af18b |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 |
# import gradio as gr
# import igraph as ig
# import plotly.graph_objects as go
# def create_plotly_tree():
# # Create an igraph tree
# g = ig.Graph.Tree(7, 2) # Example tree
# lay = g.layout('rt') # Reingold-Tilford layout
# # Plotly setup
# edge_x = []
# edge_y = []
# for edge in g.get_edgelist():
# x0, y0 = lay[edge[0]]
# x1, y1 = lay[edge[1]]
# edge_x.extend([x0, x1, None])
# edge_y.extend([y0, y1, None])
# edge_trace = go.Scatter(
# x=edge_x, y=edge_y,
# line=dict(width=0.5, color='#888'),
# hoverinfo='none',
# mode='lines')
# node_x = [lay[k][0] for k in range(len(lay))]
# node_y = [lay[k][1] for k in range(len(lay))]
# node_trace = go.Scatter(
# x=node_x, y=node_y,
# mode='markers',
# hoverinfo='text',
# marker=dict(showscale=False, size=10, color='#850', line_width=2))
# fig = go.Figure(data=[edge_trace, node_trace],
# layout=go.Layout(
# showlegend=False,
# hovermode='closest',
# margin=dict(b=0, l=0, t=0, r=0),
# xaxis=dict(showgrid=False, zeroline=False, showticklabels=False),
# yaxis=dict(showgrid=False, zeroline=False, showticklabels=False))
# )
# return fig
# def setup_interface():
# iface = gr.Interface(
# fn=create_plotly_tree,
# inputs=[],
# outputs=gr.Plot(),
# title="Interactive Tree Visualization"
# )
# return iface
# # Launch the interface
# if __name__ == "__main__":
# iface = setup_interface()
# iface.launch()
# Import necessary libraries
import dash
from dash import html, dcc, Input, Output
import plotly.graph_objects as go
import igraph as ig
# Initialize the Dash app
app = dash.Dash(__name__)
# Create an igraph tree
g = ig.Graph.Tree(7, 2) # A binary tree with 7 nodes
lay = g.layout('rt') # Reingold-Tilford layout
# Prepare node and edge traces for Plotly
edge_trace = go.Scatter(
x=[lay[edge[0]][0], lay[edge[1]][0], None],
y=[lay[edge[0]][1], lay[edge[1]][1], None],
line=dict(width=0.5, color='#888'),
hoverinfo='none',
mode='lines',
line_shape='spline',
showlegend=False
) for edge in g.get_edgelist()]
node_trace = go.Scatter(
x=[lay[k][0] for k in range(len(lay))],
y=[lay[k][1] for k in range(len(lay))],
text=[str(k) for k in range(len(lay))],
mode='markers+text',
hoverinfo='text',
marker=dict(
showscale=False,
color='blue',
size=10,
line_width=2))
# Create a figure containing the traces
fig = go.Figure(data=edge_trace + [node_trace])
# Define layout properties
fig.update_layout(
showlegend=False,
hovermode='closest',
margin=dict(b=0, l=0, r=0, t=0),
xaxis=dict(showgrid=False, zeroline=False, showticklabels=False),
yaxis=dict(showgrid=False, zeroline=False, showticklabels=False)
)
# Define the app layout
app.layout = html.Div([
dcc.Graph(id='tree-graph', figure=fig),
html.Pre(id='click-data', style={'paddingTop': 35})
])
# Define callback to update the output on click
@app.callback(
Output('click-data', 'children'),
[Input('tree-graph', 'clickData')]
)
def display_click_data(clickData):
if clickData is not None:
node_id = clickData['points'][0]['text']
return f"You clicked on node {node_id}"
return "Click on a node"
# Run the app
if __name__ == '__main__':
app.run_server(debug=True)
|