je-remy22/HydroSense-Kenya

# HydroSense-Kenya: Scientific Computing Capstone HydroSense-Kenya is a Python-based scientific computing system designed for smart irrigation, water balance simulation, and climate-aware decision support. It processes daily weather and soil-sensor data to model water availability, simulate uncertainty, and recommend optimized irrigation schedules. ## Project Structure - `data/raw/`: Original sensor and weather datasets (contains deliberate anomalies). - `data/processed/`: Cleaned and unified dataset generated via Pandas. - `notebooks/`: Six Jupyter notebooks demonstrating the cumulative scientific workflow. - `src/`: Reusable Python modules for numerical methods, simulation, and optimization. - `tests/`: Automated test suite using `pytest` to verify mathematical correctness. - `reports/`: Final presentation and scientific report PDFs. ## Setup and Installation 1. Ensure Python 3.10+ is installed. 2. Clone this repository and navigate to the project root. 3. Create a virtual environment: `python -m venv venv` 4. Activate the environment: - Windows: `venv\Scripts\activate` - Mac/Linux: `source venv/bin/activate` 5. Install dependencies: `pip install -r requirements.txt` ## Running the Tests To verify the numerical engine and simulation logic, run the test suite from the root directory: ```bash pytest tests/