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Ozzy is a data visualization and data wrangling Python package geared towards particle-in-cell (PIC) simulations and the plasma physics community.

Ozzy's philosophy is to make the analysis of simulation data originating from multiple simulation codes and often contained in large files as easy as possible by building on the powerful features of the xarray package.

Why ozzy?

  • Any simulation code

    Read and plot simulation data written by any PIC simulation code. Write the backend to parse the data once and move on. Currently available: openPMD, OSIRIS, and LCODE.

  • Labeled dimensions (thanks to xarray)

    Think like a physicist, not like a software engineer. You'll never have to wonder which numerical index corresponds to the $x$ dimension of that array again.

  • No file size too large (thanks to Dask)

    Chunking and lazy-loading of large data files are handled automatically by xarray and Dask.

  • Flexible

    We embrace xarray and Dask data objects, but you don't have to. Easily manipulate your data as trusty NumPy arrays whenever convenient.

  • Beautiful plots with one line of code

    Ozzy lays the groundwork using the dataset's metadata.

Installation

[!IMPORTANT] Ozzy requires Python >= 3.10.

A detailed guide is available in the "Installation" page of the documentation.

We highly recommend installing ozzy in its own virtual environment.

conda (recommended)

conda install --channel=conda-forge ozzy-pic

pip

python3 -m pip install ozzy-pic

Head to the documentation page to see some examples of how to get started.

Documentation

All the documentation can be found at https://mtrocadomoreira.github.io/ozzy.

Acknowledgment

Please consider acknowledging ozzy if you use it to produce images or results published in a scientific publication, for example by including the following text in the acknowledgments and/or citing ozzy's Zenodo reference1:

The data and plots in this publication were processed with ozzy1, a freely available data visualization and analysis package.

In addition, please note that ozzy.plot uses two color maps developed by Fabio Crameri (licensed under an MIT license) by default: vik (diverging) and lipari (sequential). These color maps should be acknowledged if used in a published image, for example with:

The Scientific colour map lipari2 is used in this study to prevent visual distortion of the data and exclusion of readers with colour-vision deficiencies3.

More information about the colour libraries used by ozzy can be found in the "Plotting" section of the User Guide.

License

Copyright © 2024 Mariana Moreira - All Rights Reserved

You may use, distribute and modify this code under the terms of the MIT License.

The plotting submodule of ozzy (ozzy.plot) also bundles a few different fonts under the SIL Open Font License (OFL), which is a free and open-source license. The full text of these licenses is included for each font in the fonts directory (src/ozzy/fonts/). See more details about the bundled fonts and their copyright notices in the "License" section of the documentation.

ozzy icon

  1. M. Moreira, “Ozzy: A flexible Python package for PIC simulation data analysis and visualization”. Zenodo, Jul. 16, 2024. doi: 10.5281/zenodo.12752995. ↩ ↩2

  2. F. Crameri, "Scientific colour maps". Zenodo, Oct. 05, 2023. doi: 10.5281/zenodo.8409685. ↩

  3. F. Crameri, G.E. Shephard, and P.J. Heron, "The misuse of colour in science communication". Nat. Commun. 11, 5444 (2020). doi: 10.1038/s41467-020-19160-7. ↩

Project links

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  • Released:
Newer release available (2.1.7)

1 maintainer

PyPI data
Data sourced directly from PyPI's database.
Avatar for marianam from gravatar.com marianam

Credits

Author: Mariana Moreira

License expression

MIT
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Requires

Python <3.15, >=3.11

Provides Extra

interactive

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