1- ## Predator-Prey Cellular Automaton: Model Documentation
1+ ## Predator-Prey Cellular Automaton
22
33### Overview
44
@@ -25,7 +25,7 @@ The repository is organized to separate model logic, high-performance execution
2525├── tests/ # Pytest suite for model validation
2626├── data/ # Local storage for simulation outputs (JSONL)
2727└── requirements.txt # Project dependencies
28-
28+ ```
2929---
3030
3131### Background
@@ -328,7 +328,7 @@ pytest tests/ -x --tb=short
328328
329329### Documentation
330330
331- Full API documentation is available at: ** [ https://codegithubka.github.io/CSS_Project/ ] ( https://yourusername .github.io/CSS_Project/ ) **
331+ Full API documentation is available at: ** [ https://codegithubka.github.io/CSS_Project/ ] ( https://codegithubka .github.io/CSS_Project/ ) **
332332
333333
334334#### Generating Docs Locally
@@ -346,28 +346,28 @@ Documentation is auto-generated from NumPy-style docstrings using [pdoc](https:/
346346
347347### Getting Started
348348
349- #### Dependencies
349+ #### 1. Dependencies
350350
351- ** Required:**
351+ Required:
352352- Python 3.8+
353353- NumPy
354354- Numba (for JIT compilation)
355355- tqdm (progress bars)
356356- joblib (parallelization)
357357
358- ** Optional:**
358+ Optional:
359359- matplotlib (visualization)
360360- scipy (additional analysis)
361361
362- #### Installation
362+ #### 2. Installation
363363Clone the repository and install the dependencies. It is recommended to use a virtual environment.
364364
365365``` bash
366366# Install dependencies
367367pip install -r requirements.txt
368368```
369369
370- #### Running simulations
370+ #### 3. Running simulations
371371
372372The experiments are automated via bash-scripts in the ``` scripts ``` directory. These are configured for high-performance computing environments:
373373
@@ -378,12 +378,3 @@ chmod +x scripts/*.sh
378378# Execute a specific phase (e.g., Phase 1)
379379./scripts/run_phase1.sh
380380```
381-
382- #### Analysis and Visualization
383-
384- Once simulations complete, raw data is stored in the ``` data/ ``` folder. Use the provided Jupyter notebook for analysis.
385-
386- ``` bash
387- jupyter notebook notebooks/plots.ipynb
388- ```
389-
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