Skip to content
/ obspy Public
forked from obspy/obspy

ObsPy: A Python Toolbox for seismology/seismological observatories.

License

Notifications You must be signed in to change notification settings

lynlyf/obspy

 
 

Repository files navigation

ObsPy: A Python Toolbox for seismology/seismological observatories.

NumFOCUS affiliated project

Github Action Status Coverage Status Supported Python versions

License LGPLv3

PyPI Version DOI Conda

Discourse status Gitter Announcements Mailing List Twitter Follow Liberapay patrons

ObsPy is an open-source project dedicated to provide a Python framework for processing seismological data. It provides parsers for common file formats, clients to access data centers and seismological signal processing routines which allow the manipulation of seismological time series (see Beyreuther et al. 2010, Megies et al. 2011, Krischer et al. 2015).

The goal of the ObsPy project is to facilitate rapid application development for seismology.

ObsPy is licensed under the GNU Lesser General Public License (LGPL) v3.0.

A one-hour introduction to ObsPy is available at YouTube.

Installation

Installation instructions can be found in the wiki.

Getting started

Read about how to get started in the wiki and in our Tutorial section in the documentation.

ObsPy Tutorial notebooks -- and much more on specific seismology topics -- can also be found on Seismo-Live, both as a static preview and as interactively runnable version.

Link to Seismo-Live

from obspy import read
st = read()  # load example seismogram
st.filter(type='highpass', freq=3.0)
st = st.select(component='Z')
st.plot()

Example waveform Plot

Documentation and Changelog

The detailed changelog is available here, our docs can be found at docs.obspy.org.

Contributing

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

References

Impact

ObsPy impact statistics

About

ObsPy: A Python Toolbox for seismology/seismological observatories.

Resources

License

Code of conduct

Stars

Watchers

Forks

Packages

No packages published

Languages

  • Python 77.4%
  • C 11.1%
  • Roff 3.3%
  • Shell 3.3%
  • XSLT 2.0%
  • E 1.0%
  • Other 1.9%