geojav 0.1.0

Cartographic rendering and mesh analytics powered by PyVista

Cartographic rendering and mesh analytics powered by PyVista

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🎥 Reykjanes Time-Series

Submission to the Data Visualization and Effective Communication in Volcanology: Cross-disciplinary Lessons from Research and Practice collection in the Journal of Applied Volcanology.

[!NOTE] The geojav package does not contain production grade code. It is a proof-of-concept tool to help the paper authors easily explore the plume time-series datasets and collectively decide on the final static renders for submission.

Install

Please follow these steps to install the geojav package.

Clone the Repository

Make a local clone of the geovista-jav-2026 repository:

> git clone https://github.com/bjlittle/geovista-jav-2026
> cd geovista-jav-2026

Create the Environment

Create an environment to install geojav and all its required dependencies.

pixi

We recommend using pixi for package management.

Simply:

> pixi shell --environment geojav

Alternatively, install direnv to activate/deactivate the geojav environment automatically whenever you enter/leave the geovista-jav-2026 directory:

> pixi global install direnv
> direnv allow

[!TIP] For information about the system, workspace and available pixi environments:

> pixi info

conda

Simply:

> conda env create --file requirements/geojav.yml
> conda activate geojav

[!TIP] Alternatively, for linux users only, install the fully resolved geojav environment:

> conda env create --file requirements/locks/geojav_linux-64_conda_spec.yml
> conda activate geojav

pip

Simply:

> pip install .
> pip install git+https://github.com/bjlittle/geovista.git@main

[!WARNING] The PyPI package scitools-iris has a dependency on cf-units which in turn requires the Unidata UDUNITS-2 package (C based library) for units of physical quantities to be available.

The UDUNITS-2 package is not pip installable.

Explore

If you wish to interactvely explore either of the Raikoke and Reykjanes datasets, then please click either of the images below for further instructions.

Raikoke (Russia)

Quick Start

To download, unpack, preprocess and render the Raikoke dataset, simply:

> pixi run --frozen raikoke

Reykjanes (Iceland)

Quick Start

To download, unpack, preprocess and render the Reykjanes dataset, simply:

> pixi run --frozen reykjanes

#ShowYourStripes

Graphics and Lead Scientist: Ed Hawkins, National Centre for Atmospheric Science, University of Reading.

Data: Berkeley Earth, NOAA, UK Met Office, MeteoSwiss, DWD, SMHI, UoR, Meteo France & ZAMG.

#ShowYourStripes is distributed under a Creative Commons Attribution 4.0 International License