plate-model-manager 1.3.0rc1

Plate Model Manager

plate-model-manager

Originally the plate-model-manager was designed for GPlately. Later, it was found also useful in other scenarios and contexts. The plate-model-manager downloads and manages the plate reconstruction model files. It is a dataset manager for plate tectonic reconstruction models, similar to NPM or Conda for software packages.

Have you ever wondered where to get the plate tectonic reconstruction models for your research? Are you tired of downloading files from Internet manually and specify file paths when calling PyGPlates functions? If the answer is yes, you probably want to check out this plate-model-manager Python module.

How to install

pip install plate-model-manager

or

conda install conda-forge::plate-model-manager

For more information regarding installation, visit this page

How to use the Python module

Visit this page to see how to use the plate-model-manager package in assorted scenarios.

How to use the command line

Visit this page to see how to use the plate-model-manager command lines.

Documentation

• latest
• v1.2.0

Software adoption

The plate-model-manager module is used in

• GPlately
• GPlates Web Service
• PyGPlates Tutorials
• GWS Python Wrapper

The plate-model-manager can also be used with the GPlates desktop application. To do so, use the plate-model-manager command-line tool to download the plate model files, then open them in GPlates. This provides a convenient alternative to manually downloading files from the internet.

Dependencies

• aiohttp
• requests
• nest_asyncio

Event loop RuntimeError

For Jupyter Notebook, Web Server or GUI application users, you need the following two lines to workaround the event loop RuntimeError. If you do not add these two lines, the PlateModelManager still works. But you will see a warning message. You can ignore the warning message safely. If the warning message bothers you, add the two lines before calling PlateModelManager.

https://anaconda.org/conda-forge/nest-asyncio/

import nest_asyncio
nest_asyncio.apply()