ConflictColor

A graph coloring-based helper tool for planning timetables at university.

Features

• Create and name nodes: Represent events, courses, or resources as nodes.
• Create and name edges: Add edges between nodes with a comment describing the relationship or conflict (e.g., "overlap", "conflict").
• Automatic graph coloring: The tool assigns colors to nodes so that no two connected nodes share the same color, minimizing the total number of colors used.
• Visualization: Visualize the graph with colored nodes and labeled edges using matplotlib and networkx.
• JSON input: Define your graph structure in a JSON file for easy editing and sharing.

Usage

1. Install dependencies

   pip install -r requirements.txt
   

2. Prepare your graph data
   Create a graph.json file in the project directory.
   Example:

   {
     "nodes": ["A", "B", "C"],
     "edges": [
       {"from": "A", "to": "B", "name": "A and B overlap"},
       {"from": "B", "to": "C", "name": "B and C conflict"},
       {"from": "A", "to": "C", "name": "A and C are related"}
     ]
   }

   You can also use the provided graph.json.example as a template.

3. Run the program

   python app.py
   

4. Example output
   The script prints the color assignment for each node and the number of colors used, and displays a visualization of the graph.

Example (programmatic usage)

g = Graph()
g.add_node("A")
g.add_node("B")
g.add_node("C")
g.add_edge("A", "B", "A and B overlap")
g.add_edge("B", "C", "B and C conflict")
g.add_edge("A", "C", "A and C are related")

coloring, num_colors = g.color_graph()
print("Coloring:", coloring)
print("Number of colors used:", num_colors)
g.visualize(coloring)

Requirements

• Python 3.7+
• matplotlib
• networkx

License

MIT License