Xdas: a Python Framework for Distributed Acoustic Sensing

Xdas is an python library for managing, processing and visualizing Distributed Acoustic Sensing (DAS) data. It reads any DAS format into self-described python abstractions that encapsulates both the data and the metadata (coordinates and attributes). Xdas reuses concepts of labeled N-dimensional arrays developped by the Xarray library. It takes inspiration from Dask in term of lazy computing.

Key Features

• Seamless manipulation of large multi-file datasets in their native DAS-specific format.
• Signal Processing: Multi-threaded implementations of common routines.
• Extensibility: build your pipeline with a mix of Xdas, NumPy/SciPy, and/or your own custom routines.
• Larger-than-memory processing: apply your piplines with optimized I/O latencies.

Xdas can also be used in other context than DAS, for example in the context of other dense and heavy N-dimenional arrays such as large-N seismic arrays.

Installation

Xdas can be fetched from PyPI:

pip install xdas

Documentation

The documentation is available at: https://xdas.readthedocs.io.

Tutorials

A comprehensive series of tutorials can be found at: https://github.com/xdas-dev/tutorials.

Contributing

You can find information about contributing to Xdas in our Contributing Guide.

Get in touch

• Ask usage questions and discuss any ideas on GitHub Discussions.
• Report bugs, suggest features or view the source code on GitHub.
• To follow the main announcements such as online trainning sessions please register to our Newsletter.

Citing

If you use Xdas for your DAS data processing, please consider citing the project.