Installation

Prerequisites

Nenya requires Python 3.7+ and the following main dependencies:

  • PyTorch (1.7.0+)

  • NumPy

  • Pandas

  • UMAP

  • h5py

  • Bokeh (for visualization)

  • scikit-image

  • tqdm

For working with geographic data:

  • ulmo (internal dependency)

From PyPI

Note

Coming soon. The package is not yet available on PyPI.

pip install nenya

From Source

To install Nenya from source:

git clone https://github.com/yourusername/nenya.git
cd nenya
pip install -e .

Environment Variables

Nenya requires certain environment variables to be set for proper functioning:

  • OS_SST: Base directory for satellite data

  • AWS_ACCESS_KEY_ID and AWS_SECRET_ACCESS_KEY: For accessing S3 data (if needed)

Example:

export OS_SST=/path/to/sst/data

GPU Support

For optimal performance, it’s recommended to have a CUDA-compatible GPU. Nenya uses PyTorch’s GPU acceleration when available.

To verify GPU detection:

import torch
print(torch.cuda.is_available())
print(torch.cuda.device_count())
print(torch.cuda.get_device_name(0))

Docker Installation

Note

Docker configuration coming soon.

Development Installation

For developers who want to contribute to Nenya:

git clone https://github.com/yourusername/nenya.git
cd nenya
pip install -e ".[dev]"

This will install additional development dependencies like pytest, flake8, and sphinx for documentation.