dissmodel-ca

Cellular Automata (CA) extension for dissmodel.

This library provides a collection of cellular automata models implemented using the dissmodel engine. It showcases the power of the framework's dual-substrate architecture, offering both vector (GeoDataFrame) and raster (NumPy) versions of classic and research models.

🌟 Features

• Classic & Research Models: Game of Life, Forest Fire (Probabilistic), Anneal, Snow, and more.
• Dual Substrate: Seamlessly switch between vector precision and raster performance.
• Interactive Dashboards: Built-in Streamlit apps for real-time parameter exploration.
• Experiment Tracking: Professional-grade executors with built-in telemetry and JSON reporting.

⚙️ Installation

pip install .

🚀 Usage

1. Simple Script (Quick Start)

For a quick run with default parameters and visual output:

python -m dissmodel_ca.cli.ca_game_of_life

2. Model Executor (Production/Research)

Use the Executor for automated runs, cloud integration, and full experiment tracking (generates SHA256 checksums and profiling reports):

python src/dissmodel_ca/executor/ca_gol_vector_executor.py run \
  --input "synthetic" \
  --param grid_size=30 \
  --param end_time=50

3. Interactive Streamlit App

Explore all models via a reactive web interface:

streamlit run src/dissmodel_ca/streamlit/ca_all.py

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📂 Repository Structure

• dissmodel_ca/models/: Core CA implementations (the "Science" layer).
• dissmodel_ca/executor/: Standardized executors for experiment tracking and reproducibility.
• dissmodel_ca/cli/: Simplified, self-contained scripts for quick testing.
• dissmodel_ca/streamlit/: Reactive UI components and apps.

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🛠️ Included Models

Model	Substrate	Description
GameOfLife	Vector / Raster	Classic Conway's simulation.
FireModel	Vector / Raster	Forest fire spread with probabilistic regrowth.
Snow	Vector	Snowfall accumulation and gravity dynamics.
Growth	Vector	Stochastic radial growth.
Anneal	Vector	Binary system relaxation via majority-vote rule.

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⚖️ License

MIT © 2026 LambdaGeo — UFMA