Skip to main content

A PyQt5-based GUI for the processing and analysis of active near-surface seismic data

Project description

pyckster

pipeline status GitLab Tag PyPI - Version PyPI Downloads PyPI - Downloads

PyCKSTER is an open-source PyQt5-based GUI for processing and analysis of active near-surface seismic data, with a focus on traveltime picking and surface wave dispersion analysis.

Core Features:

  • File I/O: Read and write seismic files in SEG2, SEGY, and Seismic Unix (SU) formats
  • Data Editing: Edit headers information (source and trace coordinates, topography integration, delay, ffid) and traces (move, swap, mute, delete)
  • Traveltime Analysis: Interactive picking with multiple visualization options (source/geophone diagrams, hodochrones) and direct inversion using pyGIMLi
  • Surface Wave Analysis: Compute dispersion images using phase-shift transform, simple windowing with interactive picking capabilities, and import/export dispersion curves with SWIP MATLAB package compatibility.

Coming Soon: Advanced dispersion windowing and stacking, surface wave dispersion inversion

Picked traveltimes are saved in pyGIMLi's unified format for seamless subsurface velocity model reconstruction.

Installation

PyCKSTER has now a built-in inversion module based on pyGIMLi. So far it seems to work better if pyGIMLi is installed first:

conda create -n pyckster -c gimli -c conda-forge "pygimli>=1.5.0" "suitesparse=5"

Then you can simply download the package from PyPi:

pip install pyckster

To update PyCKSTER, run the following command:

pip install pyckster --upgrade

Troubleshooting

If numpy > 2 is installed in your environment, you might not be able to run pygimli. If so you can downgrade numpy with the following command :

pip install numpy==1.26.4 --upgrade

Running PyCKSTER

Open a terminal and run:

pyckster

How to use PyCKSTER

Detailed GUI walkthrough

Mouse Controls

  • Left click: Add a single pick at cursor position
  • Left drag: Pan the plot
  • Ctrl + Left drag: Draw freehand picks along multiple traces
  • Middle click: Remove a single pick
  • Middle drag: Pan the plot
  • Ctrl + Middle drag: Select and remove multiple picks in a rectangle
  • Right click: Context menu with plot options
  • Right drag: Zoom along axes (horizontal or vertical)
  • Ctrl + Right drag: Rectangle zoom (zoom to selected area)

Here is an example of PyCKSTER in action:

Author

PyCKSTER is currently developped by Sylvain Pasquet
sylvain.pasquet@sorbonne-universite.fr

CNRS, Sorbonne Université
UAR 3455 OMA TERRA
UMR 7619 METIS

Any feedback or help is welcome.

Licence

PyCKSTER is distributed under the terms of the GPLv3 license. Details on the license agreement can be found here.

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

pyckster-26.4.2.tar.gz (474.4 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

pyckster-26.4.2-py3-none-any.whl (488.8 kB view details)

Uploaded Python 3

File details

Details for the file pyckster-26.4.2.tar.gz.

File metadata

  • Download URL: pyckster-26.4.2.tar.gz
  • Upload date:
  • Size: 474.4 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.2.0 CPython/3.14.4

File hashes

Hashes for pyckster-26.4.2.tar.gz
Algorithm Hash digest
SHA256 96877489534eb77ae8c1419de2f7b95d330a6670d6674fdf30254d3e9bc5261d
MD5 dbecefb6ef25a1540c41511944cffca5
BLAKE2b-256 6cca2ecc20096bf490bf14d1c33e84fc072eb06fe80c0e2ac26cff933743aecb

See more details on using hashes here.

File details

Details for the file pyckster-26.4.2-py3-none-any.whl.

File metadata

  • Download URL: pyckster-26.4.2-py3-none-any.whl
  • Upload date:
  • Size: 488.8 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.2.0 CPython/3.14.4

File hashes

Hashes for pyckster-26.4.2-py3-none-any.whl
Algorithm Hash digest
SHA256 bc5a8b28141696960b40ab0e8d5f3bfc8d15058ff555e266e08844c5793faaa7
MD5 fe504ee804b51369d662930707cec589
BLAKE2b-256 f1c8d9f85f500bf9a0ec75abc0f2195186f2c4858064fba8cf1d23ee7c857ceb

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page