Kurzfassungen der Meteorologentagung DACH
DACH2022-280, 2022
https://doi.org/10.5194/dach2022-280
DACH2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.

Interactive visualization of climate model data via Python or GUI with psyplot

Philipp S. Sommer
Philipp S. Sommer
  • Helmholtz-Zentrum hereon GmbH, Institute of Coastal Systems - Analysis and Modeling, Geesthacht, Germany (philipp.sommer@hereon.de)

psyplot (https://psyplot.github.io) is an open-source data visualization framework that integrates rich computational and mathematical software packages (such as xarray and matplotlib) into a flexible framework for visualization. It differs from most of the visual analytic software such that it focuses on extensibility in order to flexibly tackle the different types of analysis questions that arise in pioneering research. The design of the high-level API of the framework enables a simple and standardized usage from the command-line, python scripts or Jupyter notebooks. A modular plugin framework enables a flexible development of the framework that can potentially go into many different directions. The additional enhancement with a graphical user interface (GUI) makes it the only visualization framework that can be handled from the convenient command-line or scripts, as well as via point-click handling. It additionally allows to build further desktop applications on top of the existing framework. 

In this presentation, I will show the main functionalities of psyplot, with a special focus on the visualization of unstructured grids (such as the ICON model by the German Weather Service (DWD)), and the usage of psyplot on the HPC facilities of the DKRZ (mistral, jupyterhub, remote desktop, etc.). My demonstration will cover the basic structure of the psyplot framework and how to use psyplot in python scripts (and Jupyter notebooks). I will demonstrate a quick demo of to the psyplot GUI and psy-view, a ncview-like interface built upon psyplot, and talk about different features such as reusing plot configurations and exporting figures.

How to cite: Sommer, P. S.: Interactive visualization of climate model data via Python or GUI with psyplot, DACH2022, Leipzig, Deutschland, 21–25 Mar 2022, DACH2022-280, https://doi.org/10.5194/dach2022-280, 2022.