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Violin Plots for Matlab

A violin plot is an easy to read substitute for a box plot that replaces the box shape with a kernel density estimate of the data, and optionally overlays the data points itself. The original boxplot shape is still included as a grey box/line in the center of the violin.

Violin plots are a superset of box plots, and give a much richer understanding of the data distribution, while not taking more space. You will be able to instantly spot too-sparse data, or multi-modal distributions, which could go unnoticed in boxplots.

violinplot is meant as a direct substitute for boxplot (excluding named arguments). Additional constructor parameters include the width of the plot, the bandwidth of the kernel density estimation, and the X-axis position of the violin plot.

For more information about violin plots, read "Violin plots: a box plot-density trace synergism" by J. L. Hintze and R. D. Nelson in The American Statistician, vol. 52, no. 2, pp. 181-184, 1998 (DOI: 10.2307/2685478).

load carbig MPG Origin
Origin = cellstr(Origin);
figure
vs = violinplot(MPG, Origin);
ylabel('Fuel Economy in MPG');
xlim([0.5, 7.5]);

Citation

If you want to cite this repository, use

Bechtold, Bastian, 2016. Violin Plots for Matlab, Github Project
https://github.com/bastibe/Violinplot-Matlab, DOI: 10.5281/zenodo.4559847

datacite.yml
Title	Code for: Network state changes in sensory thalamus represent learned outcomes
Authors	Hasegawa,Masashi;German Center for Neurodegenerative Diseases (DZNE), Bonn, Germany and University of Basel, Department of Biomedicine, Basel, Switzerland Huang,Ziyan;German Center for Neurodegenerative Diseases (DZNE), Bonn, Germany Paricio-Montesinos,Ricardo;German Center for Neurodegenerative Diseases (DZNE), Bonn, Germany Gründemann,Jan;German Center for Neurodegenerative Diseases (DZNE), Bonn, Germany and University of Basel, Department of Biomedicine, Basel, Switzerland
Description	Code for generation of figures of Hasegawa, Huang, Paricio-Montesinos, Gründemann, 2024. Network state changes in sensory thalamus represent learned outcome. Code can be used to perform single cell and poplulation level analyses of in vivo calcium imaging data from mice.
License	BSD 3-Clause License (https://opensource.org/license/bsd-3-clause)
References	Hasegawa M, Huang Z, Paricio-Montesinos R, Gründemann J (2024) Network state changes in sensory thalamus represent learned outcomes. tba [doi:tba] (IsSupplementTo) Hasegawa M, Huang Z, Paricio-Montesinos R, Gründemann J (2024) Data for: Network state changes in sensory thalamus represent learned outcomes. G-Node. https://doi.org/10.12751/g-node.7xxnmw [doi:10.12751/g-node.7xxnmw] (IsReferencedBy)
Funding	DFG; SFB1089, SPP2411, Walter Benjamin Programme 528405672 EU; ERC Starting Grant 803870 Swiss National Science Foundation; PP00P3_170672 Schweizerische Hirnliga; Forschungspreis The Forschungsfonds Nachwuchsforschende of the University of Basel The Department of Biomedicine at the University of Basel Deutsches Zentrum für Neurodegenerative Erkrankungen (DZNE) DZNE Innovative Minds Program
Keywords	Neuroscience Thalamus Imaging
Resource Type	Software

README.md

Violin Plots for Matlab

Citation