Skip to main content

A web-based plot tool to visualize Earth core flows

Project description

webgeodyn is a web-based plot tool to visualize Earth core flows and scalar fields at the Core Mantle Boundary (CMB). It consists in a Tornado web server, that can be started locally, that provides a set of visualisation tools on a variety of data formats.



The installation of webgeodyn requires Python 3 to be installed.

The other dependencies will be automatically installed by the next step but are listed here for the sake of completeness:

  • numpy

  • scipy (version > 1.1)

  • h5py

  • tornado

  • cdflib

  • astropy

Installing the package

webgeodyn can be installed

  • from pip:

pip3 install webgeodyn [--user]

Put the --user flag if you are not installing in a virtual environment.

  • from the git repository :

Clone first the webgeodyn repository

git clone

Then install the package:

cd webgeodyn
python3 install [--user]

Again, put the --user flag if needed.

Whatever the method used, you can test if the install succeed by importing webgeodyn in Python3:

python3 -c "import webgeodyn; print(webgeodyn.__version__)"

This command should return the installed version.

Running the example

You can give a first try at starting the web server by running the example:

python3 webgeodyn/

or in the Python console:

>>> import webgeodyn.example

This starts the server locally and should open your browser and display a page resembling the one at If not, try to type http://localhost:8080 in your browser.

You can try the different visualisations tools provided on the loaded example model (CHAOS-7).

Note that this example will also try to load the result from the latest pygeodyn (geomagnetic data assimilation Python package also developed in our group) computation (if present in ~/pygeodyn_results/Current_computation/).

Running the server with your data

The server can be used to visualise any data of supported format. For that, it is necessary to follow the template of

  • First, load the data under the form of Model objects, of a given name and format, in a Models dictionary.

  • Then, the server must be started with the loaded Models.

This is shown in details below:

# 0.Import the necessary submodules
import webgeodyn.server
import webgeodyn.models

# 1.Initialising the Models dictionary
models = webgeodyn.models.Models()

# 2.Loading your data in the Models dictionary
# Syntax: models.loadModel('/path/to/the/model/directory', "Name of the model", "Format of the model")
# Example for pygeodyn:
models.loadModel('pygeodyn_results/Current_computation', 'Current pygeodyn computation', 'pygeodyn_hdf5')
# Several models can be loaded at once. Example for CHAOS:
models.loadModel('webgeodyn/webgeodyn/example_data/CHAOS-7', 'CHAOS-7.13', 'CHAOS')

# 3.Start the server with the loaded Models

By copying this code in a Python file of your own, you should be able to use the visualisation tools on data of supported formats.

The format of the models, that define the format of the files to read, are the modules of webgeodyn.inout. Here are some dataFormat examples:

  • archomag: to read COVARCH et COVLAKE files

  • chaos: to read CHAOS splines files

  • covobs: to read COVOBS realisations files in the spherical harmonics basis

  • covobs_splines: to read COVOBS realisations files filled with splines coefficients

  • enscore: to read files generated using [GBF15]-

  • pygeodyn_asc: for files in the old ASCII format used in pygeodyn

  • pygeodyn_hdf5: to read HDF5 files generated by pygeodyn

  • ZForecast: to read files generated by [BHF18] or [BGA17]

A list of the formats can be displayed by running:

>>> import webgeodyn.inout
>>> print(webgeodyn.inout._formats)

If you need the support of a new format of file, you can follow the templates given in the documentation of webgeodyn.inout to implement your own loading function. Otherwise, you can contact us using the information given below.

Developer documentation

Documentation of the submodules of the package are available on line.

If Sphinx is installed and the files were cloned from the repository, it is possible to generate the documentation locally using:

cd doc && ./

The documentation will then be available in HTML format at doc/html/index.html.

Conditions of use

The work is licensed under the GNU GPLv3.

Git repository

The source code is stored on a Git repository ( which can also be used to give feedbacks through Issues.



Gillet, N., Barrois, O. & Finlay, C. C. Stochastic forecasting of the geomagnetic field from the COV-OBS.x1 geomagnetic field model, and candidate models for IGRF-12. Earth, Planets and Space 67, (2015). doi:10.1186/s40623-015-0225-z


Barrois, O., N. Gillet, and J. Aubert. “Contributions to the geomagnetic secular variation from a reanalysis of core surface dynamics.” Geophysical Journal International 211.1 (2017): 50-68.


Barrois, O., Hammer, M. D., Finlay, C. C., Martin, Y. & Gillet, N. Assimilation of ground and satellite magnetic measurements: inference of core surface magnetic and velocity field changes. Geophysical Journal International (2018). doi:10.1093/gji/ggy297

Contact information

For scientific inquiries, contact Nicolas Gillet. For technical problems, contact Francois Dallasta and/or Franck Thollard.

Download files

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

Source Distribution

webgeodyn-0.10.3.tar.gz (18.0 MB view hashes)

Uploaded source

Built Distribution

webgeodyn-0.10.3-py3-none-any.whl (18.3 MB view hashes)

Uploaded py3

Supported by

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