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.
- 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.
Xdas can be fetched from PyPI:
pip install xdas
The documentation is available at: https://xdas.readthedocs.io.
A comprehensive series of tutorials can be found at: https://github.com/xdas-dev/tutorials.
You can find information about contributing to Xdas in our Contributing Guide.
- 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.
If you use Xdas for your DAS data processing, please consider citing the project.