DASPy is an open-source Python package for Distributed Acoustic Sensing (DAS) data processing.
Project description
DASPy
DASPy is an open-source Python package for Distributed Acoustic Sensing (DAS) data processing.
The project aims to lower the barrier for DAS processing and to provide a practical toolkit for DAS seismology workflows.
Features
DASPy includes:
- Classic seismic processing: preprocessing, filtering, spectral analysis, and visualization.
- DAS-oriented algorithms: denoising, wavefield decomposition, channel analysis, and strain-velocity conversion.
- Convenient data structures:
Section,Collection, andDASDateTimefor waveform, continuous acquisition, and time handling workflows.
Documentation
- English tutorial: https://daspy-tutorial.readthedocs.io/en/latest/
- 中文教程: https://daspy-tutorial-cn.readthedocs.io/zh-cn/latest/
- Example notebook:
document/example.ipynb
Installation
DASPy supports Python 3.9+ on Linux, macOS, and Windows.
pip
Install from PyPI:
pip install daspy-toolbox
Install the latest development version:
pip install git+https://github.com/HMZ-03/DASPy.git
conda
conda install conda-forge::daspy-toolbox
If you are using Python 3.13 or later, installation through conda may fail
because segyio is not yet available for all conda-forge builds. In that case,
use pip or Python 3.12 and earlier.
Manual installation
- Install dependencies:
numpy,scipy>=1.13,matplotlib,geographiclib,pyproj,h5py,segyio,nptdms,tqdm. - Add DASPy to your Python path, or install it in editable mode:
git clone https://github.com/HMZ-03/DASPy.git
cd DASPy
pip install -e .
Quick start
from daspy import read
sec = read() # load the built-in example waveform
sec.bandpass(1, 15)
sec.plot()
Contributing
Contributions are welcome. Please see CONTRIBUTING.md.
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.
Contact
If you have questions, please contact hmz2018@mail.ustc.edu.cn.
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