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A ready-to-go Python toolbox for seismic data analysis

Project description


A ready-to-go Python toolbox for seismic data analysis

Author: Xiaotao Yang


This package is currently dependent on obspy ( to basic handling of seismic data (download, read, and write, etc). Users are referred to obspy toolbox for related functions.

Available modules

This package is under active development. The currently available modules are listed here.

  1. utils: This module contains frequently used utility functions not readily available in obspy.

  2. downloaders: This module contains functions used to download earthquake waveforms, earthquake catalogs, station information, continous waveforms, and read data from local files.

  3. obsmaster: This module contains functions to get and processing Ocean Bottom Seismometer (OBS) data. The functions and main processing modules for removing the tilt and compliance noises are inspired and modified from OBStools ( developed by Pascal Audet & Helen Janiszewski. The main tilt and compliance removal method is based on Janiszewski et al. (2019).

  4. noise: This module contains functions used in ambient noise processing, including cross-correlations and monitoring. The key functions were converted from NoisePy ( with heavy modifications. Inspired by SeisNoise.jl (, We modified the cross-correlation workflow with FFTData and CorrData (defined in types module) objects. The original NoisePy script for cross-correlations have been disassembled and wrapped in functions, primarily in this module. We also changed the way NoisePy handles timestamps when cross-correlating. This change results in more data, even with gaps. The xcorr functionality in SeisGo also has the minimum requirement on knowledge about the downloading step. We try to optimize and minimize inputs from the user. We added functionality to better manipulate the temporal resolution of xcorr results.

  5. plotting: This module contains major plotting functions for raw waveforms, cross-correlation results, and station maps.

  6. monitoring: This module contains functions for ambient noise seismic monitoring, adapted from functions by Yuan et al. (2021).

  7. clustering: Clustering functions for seismic data and velocity models.

  8. stacking: stacking of seismic data.

  9. types: This module contains the definition of major data types and classes.


  1. Create and activate the conda seisgo environment

Make sure you have a working Anaconda installed. This step is required to have all dependencies installed for the package. You can also manually install the listed packages without creating the seisgo environment OR if you already have these packages installed. The order of the following commands MATTERS.

$ conda create -n seisgo -c conda-forge jupyter numpy scipy pandas numba pycwt python obspy mpi4py
$ conda activate seisgo

The jupyter package is currently not required, unless you plan to run the accompanied Jupyter notebooks in <notebooks> directory. mip4py is required to run parallel scripts stored in scripts directory. The modules have been fully tested on python 3.7.x but versions >= 3.6 also seem to work from a few tests.

Install PyGMT plotting funcitons

Map views with geographical projections are plotted using PyGMT ( The following are steps to install PyGMT package (please refer to PyGMT webpage for trouble shooting and testing):

Install GMT through conda first into the SeisGo environment:

conda activate seisgo
conda config --prepend channels conda-forge
conda install  python pip numpy pandas xarray netcdf4 packaging gmt

You may need to specify the python version available on your environment. In ~/.bash_profile, add this line: export GMT_LIBRARY_PATH=$SEISGOROOT/lib, where $SEISGOROOT is the root directory of the seisgo environment. Then, run:

conda install pygmt

Test your installation by running:

> import pygmt
  1. Install seisgo package functions using pip

cd to the directory you want to save the package files. Then,

$ conda activate seisgo
$ pip install seisgo

This step will install the SeisGo modules under seisgo environment. The modules would then be imported under any working directory. Remember to rerun this command if you modified the functions/modules.

  1. Test the installation

Run the following commands to test your installation.

$ python
>>> from seisgo import obsmaster as obs
>>> tflist=obs.gettflist(help=True)
| Key    | Default  | Note                                       |
| ZP     | True     | Vertical and pressure                      |
| Z1     | True     | Vertical and horizontal-1                  |
| Z2-1   | True     | Vertical and horizontals (1 and 2)         |
| ZP-21  | True     | Vertical, pressure, and two horizontals    |
| ZH     | True     | Vertical and rotated horizontal            |
| ZP-H   | True     | Vertical, pressure, and rotated horizontal |

Tutorials on key functionalities

See for tutorials and more detailed descriptions.


Any bugs and ideas are welcome. Please file an issue through GitHub


  • Bell, S. W., D. W. Forsyth, & Y. Ruan (2015), Removing Noise from the Vertical Component Records of Ocean-Bottom Seismometers: Results from Year One of the Cascadia Initiative, Bull. Seismol. Soc. Am., 105(1), 300-313, doi:10.1785/0120140054.
  • Clements, T., & Denolle, M. A. (2020). SeisNoise.jl: Ambient Seismic Noise Cross Correlation on the CPU and GPU in Julia. Seismological Research Letters.
  • Janiszewski, H A, J B Gaherty, G A Abers, H Gao, Z C Eilon, Amphibious surface-wave phase-velocity measurements of the Cascadia subduction zone, Geophysical Journal International, Volume 217, Issue 3, June 2019, Pages 1929-1948,
  • Jiang, C., & Denolle, M. A. (2020). NoisePy: A New High-Performance Python Tool for Ambient-Noise Seismology. Seismological Research Letters.
  • Tian, Y., & M. H. Ritzwoller (2017), Improving ambient noise cross-correlations in the noisy ocean bottom environment of the Juan de Fuca plate, Geophys. J. Int., 210(3), 1787-1805, doi:10.1093/gji/ggx281.
  • Yuan, C., Bryan, J., & Denolle, M. (2021). Numerical comparison of time-, frequency-, and wavelet-domain methods for coda wave interferometry. Geophysical Journal International, 828–846.

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