Jan Grundemann e4a757e601 Upload files to '' | 3 meses atrás | |
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test_cases | 3 meses atrás | |
README.md | 3 meses atrás | |
Violin.m | 3 meses atrás | |
example.png | 3 meses atrás | |
violinplot.m | 3 meses atrás |
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]);
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 | |
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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 |