cf-view is a Graphical User Interface (GUI) for earth science and aligned research which supports the exploration, analysis and plotting of netCDF and Met Office format (PP or fields) data.

It is intended to be an updated replacement and improvement on the xconv+ tool, using the power of:

• Python (PyQt) for the GUI;
• cf-plot (building on top of matplotlib and Cartopy) for the plotting;
• cf-python for the data reading, processing and analysis; and
• cfdm for the underlying data model.

It is designed to be a useful tool for environmental, earth and aligned sciences, for example to facilitate climate and meteorological research. cf-view is developed and maintained by the NCAS-CMS group, part of NCAS.

With cf-view you can, in a self-contained specialised GUI environment:

• Inspect, analyse and manipulate field constructs and their data;
• Edit, delete and create field metadata and properties;
• Output the underlying cf-python and cf-plot code;
• View and produce plots such as map, contour, zonal means, vector, line and trajectory plots;
• Change plotting properties such as map, colour scale, contour levels and vector properties; and
• Change interface colour scheme, fonts and font sizes.

Future releases will add support for data:

• with 2D dimensions;
• defined on rotated pole grids;
• defined on unstructured grids i.e. UGRID data.

See the cf-view homepage (https://ncas-cms.github.io/cf-view/build/) for the full online documentation.

After installing (see below), start cf-view through the command line via running:

cfview

or if you wish to start working with a specific file, add a positional argument:

cfview <file>

where <file> is the path to the netCDF, Met Office PP or fields file.

Note: when starting cf-view for the first time, it might take twenty or so seconds to start while matplotlib does some initialisation work.

There are two main ways to install cf-view: through a package manager, or by downloading and running a dedicated installation script.

You can use pip with conda (or similar package managers such as mamba) as follows.

To use pip, run:

pip install cf-python cf-plot cf-view

In future you will be able to install cf-view and all of its dependencies fully with conda, but for now only the dependencies are installable this way, like so:

conda install -c ncas -c conda-forge cf-python cf-plot udunits2

and you must use e.g. pip to install the cf-view library itself.

Alternatively, to install cf-view with its required dependencies, you can download from source. For Linux, run:

wget http://gws-access.jasmin.ac.uk/public/ncas_climate/ajh/cfview_install/cfview_install.sh

or for Mac, instead run:

curl -O -L http://gws-access.jasmin.ac.uk/public/ncas_climate/ajh/cfview_install/cfview_install.sh

and then install by running the cfview_install.sh script, for example with:

bash cfview_install.sh

More detail about installation is provided on the installation page (https://ajheaps.github.io/cf-view/download.html) of the documentation.

Everyone is welcome to contribute to cf-view in the form of bug reports, documentation, code, design proposals, and more.

Contributing guidelines will be added to the repository shortly.

For any queries, see the guidance page (https://ajheaps.github.io/cf-view/issues.html).