This project is an attempt to visualize all possible Tic-Tac-Toe states on a scalable canvas using Python and Graphviz. The current layout does not really utilize the output canvas space effectively, and routing "moves" between game states is a core challenge yet to be solved. Expect incomplete functionality and rudimentary visuals.
- Python: Core logic for generating game states and images.
- Graphviz: Used for creating visual representations of the Tic-Tac-Toe game states.
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tictactoe2png.py:- Generates PNG visualizations of Tic-Tac-Toe layouts.
- Primarily responsible for converting game data into PNG format.
- Minimal error handling and assumes valid game data.
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tictactoegen.py:- Main script to generate Tic-Tac-Toe game state sequences.
- Logic for determining and storing moves in the game.
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tictactoe2gv.py:- Produces Graphviz-compatible files, facilitating a node-based visualization of game states.
- The generated Graphviz files visualize game transitions, but routing between moves remains an unresolved issue.
- The script does not handle dynamic scaling effectively, which limits the clarity of node connections.
The following images demonstrate the project's current output:
- Layout Complexity: The current layout implementation is overly simplistic and fails to effectively utilize the output canvas, especially at larger scales.
- Move Routing: The logic for routing moves between game states is rudimentary and lacks sophistication, making the output unclear in complex scenarios.
This is a minimal, experimental project intended for prototyping. Significant work is needed to refine the layout and game state transition logic.
License is MIT. Use as you wish with your own risk etc.