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Xdas is a Python library designed to manipulate Distributed Acoustic Sensing (DAS) data. It is capable of handling any dataset consisting of dense N-dimensional arrays. The software has the ability to read any DAS file format into a unified Python object abstraction, and to aggregate multi-file datasets produced by any number and kind of instruments, with any different acquisition parametrization into a unique virtual continuous object. It greatly facilitates the temporal and spatial selection and processing of the data while ensuring minimal overhead costs. Xdas utilizes a labeled N-dimensional arrays structure to provide a flexible, self-contained data model that encapsulates both data values and coordinate metadata. This data model adheres to the established formats provided by the NetCDF4/HDF5 file format and the Climate and Forecast (CF) conventions. Xdas has been designed to mirror the application programming interface (API) of the widely used NumPy/Scipy/Xarray Python libraries, with the objective of simplifying the learning process. Xdas is a flexible, extendible solution. The addition of a new file format support or the wrapping of a processing function typically requires less than ten lines of code. By default, Xdas functions are multithreaded, thereby leveraging the computational capacity of multicore machines. Xdas provides online processing routines, enabling continuous processing of long time series and real-time data streams.
Trabattoni et al. (Wed,) studied this question.