fv3fit is a library for machine learning workflows.
loaders provides unified APIs for accessing model output datasets.
fv3viz contains visualization tools.
vcm is a collection of various routines.
:doc:`synth <readme_links/synth_readme>` is a package which allows you to define data schemas and create synthetic datasets for testing.
:doc:`report <readme_links/report_readme>` handles the generation of workflow reports.
:doc:`fv3kube <readme_links/fv3kube_readme>` contains utilities to handle submitting and monitoring fv3gfs jobs on kubernetes.
Packages in other repositories:
fv3gfs-fortran is our fork of the FV3GFS fortran model, which we run using its included Python wrapper
pace-util (docs, which are no longer maintained) is a library of general-purpose Python code to use in a model script.
fv3config (docs) provides routines to configure and write a FV3GFS run directory using a yaml configuration file and data stored on the cloud.
.. toctree::
:caption: List of packages:
:maxdepth: 1
:glob:
readme_links/fv3fit_readme
readme_links/loaders_readme
readme_links/fv3viz_readme
readme_links/vcm_readme
readme_links/synth_readme
readme_links/report_readme
readme_links/fv3kube_readme
readme_links/radiation_readme