DASPy-toolbox

DASPy is an open-source project dedicated to provide a python package for DAS (Distributed Acoustic Sensing) data processing.

The goal of the DASPy project is to lower the bar of DAS data processing. DASPy includes:

• Classic seismic data processing techniques, including preprocessing, filter, spectrum analysis, and visualization
• Specialized algorithms for DAS applications, including denoising, waveform decomposition, channel attribute analysis, and strain-velocity conversion.

DASPy is licensed under the MIT License. An English version of DASPy tutorial, a Chinese version of DASPy tutorial and an example of Jupyter notebook is available. If you have any questions, please contact me via [e-mail].

Installation

DASPy runs on Linux, Windows and Mac OS and on Python 3.9 and up.

Pip

pip install daspy-toolbox

Install the latest version from GitHub:

pip install git+https://github.com/HMZ-03/DASPy.git

Conda

conda install daspy-toolbox

or

conda install conda-forge::daspy-toolbox

Manual installation

• Install dependent packages: numpy, scipy >=1.13, matplotlib, geographiclib, pyproj, h5py, segyio, nptdms, tqdm

• Add DASPy into your Python path.

Getting started

from daspy import read
sec = read()  # load example waveform
sec.bandpass(1, 15)
sec.plot()

Contributing

Please see details on how to contribute to the project here and here.

Reference

• Minzhe Hu and Zefeng Li (2024), DASPy: A Python Toolbox for DAS Seismology, Seismological Research Letters, 95(5), 3055–3066, doi: https://doi.org/10.1785/0220240124.