"""
Mindmap Generator using PyVis for interactive radial visualizations
Creates beautiful, explorable mindmaps with custom styling
"""
from pyvis.network import Network
import networkx as nx
from typing import Dict, Any, Optional
import streamlit.components.v1 as components
import tempfile
import os
class MindmapGenerator:
"""
Generate interactive radial mindmaps using PyVis
Features:
- Radial layout with ForceAtlas2 physics
- Color-coded hierarchy levels
- Interactive zoom, pan, and hover
- Customizable styling and dimensions
"""
def __init__(
self,
height: str = "650px",
width: str = "100%",
bgcolor: str = "#1e1e1e",
font_color: str = "#ffffff"
):
"""
Initialize mindmap generator with display settings
Args:
height: Height of visualization (CSS format)
width: Width of visualization (CSS format)
bgcolor: Background color (hex)
font_color: Font color (hex)
"""
self.height = height
self.width = width
self.bgcolor = bgcolor
self.font_color = font_color
# Color scheme for node levels
self.level_colors = {
0: "#ff6b6b", # Center - red/coral
1: "#4ecdc4", # Primary - teal
2: "#95e1d3", # Secondary - light teal
3: "#f9ca24", # Tertiary - yellow
4: "#a29bfe" # Quaternary - purple
}
def create_radial_mindmap(self, mindmap_data: Dict[str, Any]) -> Network:
"""
Create interactive radial mindmap from structured data
Args:
mindmap_data: Dictionary with center, nodes, and edges
Returns:
Configured PyVis Network object
"""
# Initialize PyVis network
net = Network(
height=self.height,
width=self.width,
bgcolor=self.bgcolor,
font_color=self.font_color,
notebook=False,
directed=False
)
# Configure physics for radial layout
net.set_options("""
{
"physics": {
"enabled": true,
"forceAtlas2Based": {
"gravitationalConstant": -50,
"centralGravity": 0.005,
"springLength": 150,
"springConstant": 0.08,
"damping": 0.4,
"avoidOverlap": 0.5
},
"maxVelocity": 50,
"solver": "forceAtlas2Based",
"timestep": 0.35,
"stabilization": {
"enabled": true,
"iterations": 1000,
"updateInterval": 25
}
},
"interaction": {
"hover": true,
"hoverConnectedEdges": true,
"tooltipDelay": 100,
"navigationButtons": true,
"keyboard": {
"enabled": true,
"speed": {"x": 10, "y": 10, "zoom": 0.02}
},
"zoomView": true,
"dragView": true
},
"edges": {
"smooth": {
"enabled": true,
"type": "continuous",
"roundness": 0.5
}
}
}
""")
# Add center node
center = mindmap_data.get('center', 'Unknown Topic')
net.add_node(
'center',
label=center,
title=f"{center}
Central Topic
",
size=45,
color=self.level_colors[0],
font={'size': 24, 'color': self.font_color, 'face': 'Arial', 'bold': True},
borderWidth=3,
borderWidthSelected=5
)
# Add nodes with level-based styling
for node in mindmap_data.get('nodes', []):
node_id = node.get('id', '')
label = node.get('label', node_id)
level = node.get('level', 1)
description = node.get('description', '')
# Size decreases with level
size = max(35 - (level * 7), 15)
# Font size decreases with level
font_size = max(18 - (level * 2), 12)
# Get color for this level
color = self.level_colors.get(level, self.level_colors[2])
# Create rich tooltip
tooltip = f"""
{label}
Level {level}
{description}
"""
net.add_node(
node_id,
label=label,
title=tooltip,
size=size,
color=color,
font={
'size': font_size,
'color': self.font_color,
'face': 'Arial'
},
borderWidth=2,
borderWidthSelected=4,
shape='dot'
)
# Add edges with relationship labels
for edge in mindmap_data.get('edges', []):
from_node = edge.get('from', '')
to_node = edge.get('to', '')
label = edge.get('label', '')
# Edge styling
net.add_edge(
from_node,
to_node,
title=label if label else 'related to',
label=label if len(label) < 15 else '', # Only show short labels
color={'color': '#666666', 'opacity': 0.6},
width=2,
smooth={'type': 'continuous'}
)
return net
def generate_html(self, mindmap_data: Dict[str, Any]) -> str:
"""
Generate HTML string for the mindmap
Args:
mindmap_data: Mindmap structure
Returns:
Complete HTML as string
"""
net = self.create_radial_mindmap(mindmap_data)
# Generate HTML
html_content = net.generate_html()
return html_content
def save_to_file(self, mindmap_data: Dict[str, Any], filename: str = "mindmap.html"):
"""
Save mindmap to HTML file
Args:
mindmap_data: Mindmap structure
filename: Output filename
"""
net = self.create_radial_mindmap(mindmap_data)
net.save_graph(filename)
print(f"✅ Mindmap saved to {filename}")
def render_in_streamlit(self, mindmap_data: Dict[str, Any]):
"""
Render mindmap directly in Streamlit application
Args:
mindmap_data: Mindmap structure
"""
html_content = self.generate_html(mindmap_data)
# Display using Streamlit components
components.html(
html_content,
height=int(self.height.replace('px', '')),
scrolling=False
)
# Convenience functions for direct usage
def generate_mindmap_html(mindmap_data: Dict[str, Any]) -> str:
"""
Quick function to generate mindmap HTML
Args:
mindmap_data: Mindmap structure
Returns:
HTML string
"""
generator = MindmapGenerator()
return generator.generate_html(mindmap_data)
def create_sample_mindmap() -> Dict[str, Any]:
"""
Create a sample mindmap for testing
Returns:
Sample mindmap data structure
"""
return {
'center': 'Machine Learning',
'nodes': [
{
'id': 'supervised',
'label': 'Supervised Learning',
'level': 1,
'description': 'Learning with labeled data'
},
{
'id': 'unsupervised',
'label': 'Unsupervised Learning',
'level': 1,
'description': 'Learning from unlabeled data'
},
{
'id': 'classification',
'label': 'Classification',
'level': 2,
'description': 'Categorizing data into classes'
},
{
'id': 'regression',
'label': 'Regression',
'level': 2,
'description': 'Predicting continuous values'
}
],
'edges': [
{'from': 'center', 'to': 'supervised', 'label': 'includes'},
{'from': 'center', 'to': 'unsupervised', 'label': 'includes'},
{'from': 'supervised', 'to': 'classification', 'label': 'type'},
{'from': 'supervised', 'to': 'regression', 'label': 'type'}
]
}
if __name__ == "__main__":
# Test the generator
print("Mindmap Generator Module - Ready for import")
print("Use MindmapGenerator class to create visualizations")
# Create sample
sample = create_sample_mindmap()
generator = MindmapGenerator()
generator.save_to_file(sample, "test_mindmap.html")