Project Structure

The RTnn package is organized as follows:

rtnn/
├── src/rtnn/                 # Main package
│   ├── __init__.py
│   ├── __main__.py
│   ├── version.py
│   ├── dataset.py            # DataPreprocessor class
│   ├── evaluater.py          # Metrics and loss functions
│   ├── diagnostics.py        # Visualization tools
│   ├── logger.py             # Rich logging
│   ├── main.py               # Main training script
│   ├── model_loader.py       # Model factory
│   ├── model_utils.py        # Model utilities
│   ├── utils.py              # File and general utilities
│   ├── stats.py              # Statistical computations
│   └── models/               # Model architectures
│       ├── __init__.py
│       ├── rnn.py            # LSTM and GRU
│       ├── fcn.py            # Fully Connected Network
│       ├── Transformer.py    # Transformer encoder
│       ├── UNet1D.py         # 1D U-Net
│       └── DimChangeModule.py
├── tests/                    # Unit tests
│   ├── test_rnn.py
│   ├── test_fcn.py
│   ├── test_transformer.py
│   ├── test_dataset.py
│   ├── test_evaluater.py
│   ├── test_model_loader.py
│   └── test_runner.py
├── docs/                     # Documentation
│   ├── source/
│   └── build/
├── .github/workflows/        # CI/CD pipelines
│   ├── ci.yaml
│   └── docs.yml
├── pyproject.toml            # Package configuration
├── README.rst                # Project README
└── LICENSE                   # CC BY-NC-SA 4.0

Module Descriptions

Module	Description
dataset.py	DataPreprocessor for loading and preprocessing NetCDF files
evaluater.py	Loss functions and evaluation metrics
diagnostics.py	Plotting and visualization utilities
logger.py	Rich console and file logging
main.py	Main training pipeline entry point
model_loader.py	Factory function for model instantiation
model_utils.py	Model inspection and checkpoint management
utils.py	File utilities and EasyDict class
stats.py	Statistical computation for normalization
models/	Neural network architectures