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The three main features of pyicon are:\n\n* a number of functions to facilitate the every-day script-based plotting of ICON data\n* an interactive (ncview-like) plotting GUI for Jupyter notebook\n* a monitoring suite for ICON ocean simulations which combines dedicated diagnostic plots of an ICON simulation on a website\n\nPyicon is developed within the DFG-project TRR181 - Energy Transfers in Atmosphere and Ocean.\n\nThe pyicon documentation can be found here: [documentation](https://m300602.gitlab-pages.dkrz.de/pyicon/)\n\nPyicon is hosted at: (https://gitlab.dkrz.de/m300602/pyicon/)\n\n## Quick start for pyicon \n\nYou can install pyicon via pip:\n\n```bash\npip install pyicon-diagnostics\n```\n\nHowever, if you want to use the most recent development version, it is advisable to\ndownload pyicon with git:\n\n```bash\ngit clone git@gitlab.dkrz.de:m300602/pyicon.git\n```\n\nInstall pyicon by:\n\n```bash\ncd pyicon\npip install -e ./\n```\n\nIf you notice that some requirements were not met by the installation, you can \nalso use conda to install the requirements:\n\n```bash\nconda env create -f ci/requirements_latest.yml\n```\n\nor on DKRZ's super computer Levante use\n\n``` bash\nmodule load python3/2023.01-gcc-11.2.0\npip install healpy\n```\n\nTo update pyicon, you only need to enter the pyicon directory update the git repository via\n\n```bash\ngit pull\n```\n\n## Quick start for pyicon @DWD (Confluence, only intern)\nhttps://ninjoservices.dwd.de/wiki/display/KUQ/pyICON+for+ICON+with+NWP+physics\n\n## Installing locally\n\nYou can also install `pyicon` locally via `pip`. However, due to dependencies of `cartopy` it is advised to install `cartopy` first via `conda`.\n\n```bash\nconda install xarray cartopy dask -c conda-forge\n```\n\nOnce, `cartopy` is installed in your environment:\n\n```bash\npip install git+https://gitlab.dkrz.de/m300602/pyicon.git\n```\n\n## Developing\nWhen adding new functions, make sure to document them with a docstring. This should detail what the function does, the arguments and what type of objects it returns. Examples are encouraged. We use so-called \"numpy\" style docstrings which are then automatically rendered into the sphinx documentation. 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