wasp-ocean 1.0.2

Wave Spectra Partitioning - Watershed algorithm for ocean wave spectra

WASP - WAve Spectra Partitioning

Watershed Algorithm for partitioning ocean wave spectra from model and observation

📋 What is WASP?

WASP focuses exclusively on spectral partitioning - the process of separating ocean wave spectra into individual wave systems (partitions) via watershed algorithm. Each partition represents a distinct wave system characterized by significant wave height (Hs), peak period (Tp), and direction (Dp).

WASP handles:

• ✅ Spectral partitioning using watershed algorithm
• ✅ Processing SAR (Sentinel-1 and CFOSAT), NDBC and WW3 model spectra
• ✅ Extracting wave parameters (Hs, Tp, Dp) for each partition

🚀 Installation

⚠️ IMPORTANT: Python 3.10 or higher is required.

Install from PyPI (Recommended)

pip install wasp-ocean

Verify Installation

# Test the import
python -c "import wasp; print(f'WASP version: {wasp.__version__}')"

# Test main functions
python -c "from wasp import partition_spectrum, calculate_wave_parameters; print('✓ Installation successful!')"

Development Installation

For development or local modifications:

# Clone the repository
git clone https://github.with/jtcarvalho/wasp.git
cd wasp

# Install in editable mode
pip install -e .

📦 Key Dependencies

• Python >= 3.10 (required)
• NumPy >= 2.1.0 (required for np.trapezoid)
• pandas >= 2.2.0
• xarray >= 2024.11.0
• matplotlib >= 3.8.0
• scipy >= 1.14.0
• scikit-image >= 0.22.0
• netCDF4 >= 1.5.4

⚠️ Note: NumPy < 2.1.0 will cause errors as np.trapezoid is not available.

🏗️ Project Structure

wasp/
├── src/
│   └── wasp/              # Main package
│       ├── partition.py   # Watershed partitioning algorithm
│       ├── wave_params.py # Wave parameter calculations
│       ├── io_sar.py      # SAR Sentinel data I/O
│       ├── io_cfosat.py   # SAR CFOSAT data I/O
│       ├── io_ww3.py      # WW3 data I/O
│       ├── io_ndbc.py     # NDBC data I/O
│       └── utils.py       # Utility functions
└── examples/              # Usage examples

📄 License

This project is licensed under the MIT License.

🤝 Contributing

Contributions are welcome! Please feel free to submit a Pull Request.

📧 Contact

For questions or issues, please open an issue on GitHub.