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Copyright 2016 Bastian Bechtold
Redistribution and use in source and binary forms, with or without modification, are permitted provided that the following conditions are met:
1. Redistributions of source code must retain the above copyright notice, this list of conditions and the following disclaimer.
2. Redistributions in binary form must reproduce the above copyright notice, this list of conditions and the following disclaimer in the documentation and/or other materials provided with the distribution.
3. Neither the name of the copyright holder nor the names of its contributors may be used to endorse or promote products derived from this software without specific prior written permission.
THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.

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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](http://www.stat.cmu.edu/~rnugent/PCMI2016/papers/ViolinPlots.pdf)"
by J. L. Hintze and R. D. Nelson in The American Statistician, vol.
52, no. 2, pp. 181-184, 1998 (DOI: 10.2307/2685478).
For a simple call:
```matlab
load carbig MPG Origin
Origin = cellstr(Origin);
figure
vs = violinplot(MPG, Origin);
ylabel('Fuel Economy in MPG');
xlim([0.5, 7.5]);
```
![example image](./example.png)
You can also play around with the different options, and tune your violin plots to your liking.
```matlab
grouporder={'England','Sweden','Japan','Italy','Germany','France','USA'};
vs = Violin({MPG(strcmp(Origin, grouporder{pos}))},...
position,...
'HalfViolin','right',...% left, full
'QuartileStyle','shadow',... % boxplot, none
'DataStyle', 'histogram',... % scatter, none
'ShowNotches', false,...
'ShowMean', false,...
'ShowMedian', true,...
'ViolinColor', color);
```
![example image2](example2.png)
## Citation
[![DOI](https://zenodo.org/badge/60771923.svg)](https://zenodo.org/badge/latestdoi/60771923)
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

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classdef Violin < handle
% Violin creates violin plots for some data
% 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.
% It is also possible to provide two sets of data which are supposed
% to be compared by plotting each column of the two datasets together
% on each side of the violin.
%
% Additional constructor parameters include the width of the
% plot, the bandwidth of the kernel density estimation, the
% X-axis position of the violin plot, and the categories.
%
% Use <a href="matlab:help('violinplot')">violinplot</a> for a
% <a href="matlab:help('boxplot')">boxplot</a>-like wrapper for
% interactive plotting.
%
% See for more information on Violin Plots:
% J. L. Hintze and R. D. Nelson, "Violin plots: a box
% plot-density trace synergism," The American Statistician, vol.
% 52, no. 2, pp. 181-184, 1998.
%
% Violin Properties:
% ViolinColor - Fill color of the violin area and data points.
% Can be either a matrix nx3 or an array of up to two
% cells containing nx3 matrices.
% Defaults to the next default color cycle.
% ViolinAlpha - Transparency of the violin area and data points.
% Can be either a single scalar value or an array of
% up to two cells containing scalar values.
% Defaults to 0.3.
% EdgeColor - Color of the violin area outline.
% Defaults to [0.5 0.5 0.5]
% BoxColor - Color of the box, whiskers, and the outlines of
% the median point and the notch indicators.
% Defaults to [0.5 0.5 0.5]
% MedianColor - Fill color of the median and notch indicators.
% Defaults to [1 1 1]
% ShowData - Whether to show data points.
% Defaults to true
% ShowNotches - Whether to show notch indicators.
% Defaults to false
% ShowMean - Whether to show mean indicator.
% Defaults to false
% ShowBox - Whether to show the box.
% Defaults to true
% ShowMedian - Whether to show the median indicator.
% Defaults to true
% ShowWhiskers - Whether to show the whiskers
% Defaults to true
% HalfViolin - Whether to do a half violin(left, right side) or
% full. Defaults to full.
% QuartileStyle - Option on how to display quartiles, with a
% boxplot, shadow or none. Defaults to boxplot.
% DataStyle - Defines the style to show the data points. Opts:
% 'scatter', 'histogram' or 'none'. Default is 'scatter'.
%
%
% Violin Children:
% ScatterPlot - <a href="matlab:help('scatter')">scatter</a> plot of the data points
% ScatterPlot2 - <a href="matlab:help('scatter')">scatter</a> second plot of the data points
% ViolinPlot - <a href="matlab:help('fill')">fill</a> plot of the kernel density estimate
% ViolinPlot2 - <a href="matlab:help('fill')">fill</a> second plot of the kernel density estimate
% BoxPlot - <a href="matlab:help('fill')">fill</a> plot of the box between the quartiles
% WhiskerPlot - line <a href="matlab:help('plot')">plot</a> between the whisker ends
% MedianPlot - <a href="matlab:help('scatter')">scatter</a> plot of the median (one point)
% NotchPlots - <a href="matlab:help('scatter')">scatter</a> plots for the notch indicators
% MeanPlot - line <a href="matlab:help('plot')">plot</a> at mean value
% Copyright (c) 2016, Bastian Bechtold
% This code is released under the terms of the BSD 3-clause license
properties (Access=public)
ScatterPlot % scatter plot of the data points
ScatterPlot2 % comparison scatter plot of the data points
ViolinPlot % fill plot of the kernel density estimate
ViolinPlot2 % comparison fill plot of the kernel density estimate
BoxPlot % fill plot of the box between the quartiles
WhiskerPlot % line plot between the whisker ends
MedianPlot % scatter plot of the median (one point)
NotchPlots % scatter plots for the notch indicators
MeanPlot % line plot of the mean (horizontal line)
HistogramPlot % histogram of the data
ViolinPlotQ % fill plot of the Quartiles as shadow
end
properties (Dependent=true)
ViolinColor % fill color of the violin area and data points
ViolinAlpha % transparency of the violin area and data points
MarkerSize % marker size for the data dots
MedianMarkerSize % marker size for the median dot
LineWidth % linewidth of the median plot
EdgeColor % color of the violin area outline
BoxColor % color of box, whiskers, and median/notch edges
BoxWidth % width of box between the quartiles in axis space (default 10% of Violin plot width, 0.03)
MedianColor % fill color of median and notches
ShowData % whether to show data points
ShowNotches % whether to show notch indicators
ShowMean % whether to show mean indicator
ShowBox % whether to show the box
ShowMedian % whether to show the median line
ShowWhiskers % whether to show the whiskers
HalfViolin % whether to do a half violin(left, right side) or full
end
methods
function obj = Violin(data, pos, varargin)
%Violin plots a violin plot of some data at pos
% VIOLIN(DATA, POS) plots a violin at x-position POS for
% a vector of DATA points.
%
% VIOLIN(..., 'PARAM1', val1, 'PARAM2', val2, ...)
% specifies optional name/value pairs:
% 'Width' Width of the violin in axis space.
% Defaults to 0.3
% 'Bandwidth' Bandwidth of the kernel density
% estimate. Should be between 10% and
% 40% of the data range.
% 'ViolinColor' Fill color of the violin area
% and data points.Can be either a matrix
% nx3 or an array of up to two cells
% containing nx3 matrices.
% 'ViolinAlpha' Transparency of the violin area and data
% points. Can be either a single scalar
% value or an array of up to two cells
% containing scalar values. Defaults to 0.3.
% 'MarkerSize' Size of the data points, if shown.
% Defaults to 24
% 'MedianMarkerSize' Size of the median indicator, if shown.
% Defaults to 36
% 'EdgeColor' Color of the violin area outline.
% Defaults to [0.5 0.5 0.5]
% 'BoxColor' Color of the box, whiskers, and the
% outlines of the median point and the
% notch indicators. Defaults to
% [0.5 0.5 0.5]
% 'MedianColor' Fill color of the median and notch
% indicators. Defaults to [1 1 1]
% 'ShowData' Whether to show data points.
% Defaults to true
% 'ShowNotches' Whether to show notch indicators.
% Defaults to false
% 'ShowMean' Whether to show mean indicator.
% Defaults to false
% 'ShowBox' Whether to show the box
% Defaults to true
% 'ShowMedian' Whether to show the median line
% Defaults to true
% 'ShowWhiskers' Whether to show the whiskers
% Defaults to true
% 'HalfViolin' Whether to do a half violin(left, right side) or
% full. Defaults to full.
% 'QuartileStyle' Option on how to display quartiles, with a
% boxplot or as a shadow. Defaults to boxplot.
% 'DataStyle' Defines the style to show the data points. Opts:
% 'scatter', 'histogram' or 'none'. Default is 'Scatter'.
st = dbstack; % get the calling function for reporting errors
namefun = st.name;
args = obj.checkInputs(data, pos, varargin{:});
if length(data)==1
data2 = [];
data = data{1};
else
data2 = data{2};
data = data{1};
end
if isempty(args.ViolinColor)
Release= strsplit(version('-release'), {'a','b'}); %Check release
if str2num(Release{1})> 2019 || strcmp(version('-release'), '2019b')
C = colororder;
else
C = lines;
end
if pos > length(C)
C = lines;
end
args.ViolinColor = {repmat(C,ceil(size(data,2)/length(C)),1)};
end
data = data(not(isnan(data)));
data2 = data2(not(isnan(data2)));
if numel(data) == 1
obj.MedianPlot = scatter(pos, data, 'filled');
obj.MedianColor = args.MedianColor;
obj.MedianPlot.MarkerEdgeColor = args.EdgeColor;
return
end
hold('on');
%% Calculate kernel density estimation for the violin
[density, value, width] = obj.calcKernelDensity(data, args.Bandwidth, args.Width);
% also calculate the kernel density of the comparison data if
% provided
if ~isempty(data2)
[densityC, valueC, widthC] = obj.calcKernelDensity(data2, args.Bandwidth, args.Width);
end
%% Plot the data points within the violin area
if length(density) > 1
[~, unique_idx] = unique(value);
jitterstrength = interp1(value(unique_idx), density(unique_idx)*width, data, 'linear','extrap');
else % all data is identical:
jitterstrength = density*width;
end
if isempty(data2) % if no comparison data
jitter = 2*(rand(size(data))-0.5); % both sides
else
jitter = rand(size(data)); % only right side
end
switch args.HalfViolin % this is more modular
case 'left'
jitter = -1*(rand(size(data))); %left
case 'right'
jitter = 1*(rand(size(data))); %right
case 'full'
jitter = 2*(rand(size(data))-0.5);
end
% Make scatter plot
switch args.DataStyle
case 'scatter'
if ~isempty(data2)
jitter = 1*(rand(size(data))); %right
obj.ScatterPlot = ...
scatter(pos + jitter.*jitterstrength, data, args.MarkerSize, 'filled');
% plot the data points within the violin area
if length(densityC) > 1
jitterstrength = interp1(valueC, densityC*widthC, data2);
else % all data is identical:
jitterstrength = densityC*widthC;
end
jitter = -1*rand(size(data2));% left
obj.ScatterPlot2 = ...
scatter(pos + jitter.*jitterstrength, data2, args.MarkerSize, 'filled');
else
obj.ScatterPlot = ...
scatter(pos + jitter.*jitterstrength, data, args.MarkerSize, 'filled');
end
case 'histogram'
[counts,edges] = histcounts(data, size(unique(data),1));
switch args.HalfViolin
case 'right'
obj.HistogramPlot= plot([pos-((counts')/max(counts))*max(jitterstrength)*2, pos*ones(size(counts,2),1)]',...
[edges(1:end-1)+max(diff(edges))/2; edges(1:end-1)+max(diff(edges))/2],'-','LineWidth',1, 'Color', 'k');
case 'left'
obj.HistogramPlot= plot([pos*ones(size(counts,2),1), pos+((counts')/max(counts))*max(jitterstrength)*2]',...
[edges(1:end-1)+max(diff(edges))/2; edges(1:end-1)+max(diff(edges))/2],'-','LineWidth',1, 'Color', 'k');
otherwise
fprintf([namefun, ' No histogram/bar plot option available for full violins, as it would look overcrowded.\n'])
end
case 'none'
end
%% Plot the violin
halfViol= ones(1, size(density,2));
if isempty(data2) % if no comparison data
switch args.HalfViolin
case 'right'
obj.ViolinPlot = ... % plot color will be overwritten later
fill([pos+density*width halfViol*pos], ...
[value value(end:-1:1)], [1 1 1],'LineWidth',1);
case 'left'
obj.ViolinPlot = ... % plot color will be overwritten later
fill([halfViol*pos pos-density(end:-1:1)*width], ...
[value value(end:-1:1)], [1 1 1],'LineWidth',1);
case 'full'
obj.ViolinPlot = ... % plot color will be overwritten later
fill([pos+density*width pos-density(end:-1:1)*width], ...
[value value(end:-1:1)], [1 1 1],'LineWidth',1);
end
else
% plot right half of the violin
obj.ViolinPlot = ...
fill([pos+density*width pos-density(1)*width], ...
[value value(1)], [1 1 1],'LineWidth',1);
% plot left half of the violin
obj.ViolinPlot2 = ...
fill([pos-densityC(end)*widthC pos-densityC(end:-1:1)*widthC], ...
[valueC(end) valueC(end:-1:1)], [1 1 1],'LineWidth',1);
end
%% Plot the quartiles within the violin
quartiles = quantile(data, [0.25, 0.5, 0.75]);
flat= [halfViol*pos halfViol*pos];
switch args.QuartileStyle
case 'shadow'
switch args.HalfViolin
case 'right'
w = [pos+density*width halfViol*pos];
h= [value value(end:-1:1)];
case 'left'
w = [halfViol*pos pos-density(end:-1:1)*width];
h= [value value(end:-1:1)];
case 'full'
w = [pos+density*width pos-density(end:-1:1)*width];
h= [value value(end:-1:1)];
end
w(h<quartiles(1))=flat(h<quartiles(1));
w(h>quartiles(3))=flat((h>quartiles(3)));
obj.ViolinPlotQ = ... % plot color will be overwritten later
fill(w, ...
h, [1 1 1]);
case 'boxplot'
obj.BoxPlot = ... % plot color will be overwritten later
fill(pos+[-1,1,1,-1]*args.BoxWidth, ...
[quartiles(1) quartiles(1) quartiles(3) quartiles(3)], ...
[1 1 1]);
case 'none'
end
%% Plot the data mean
meanValue = mean(data);
if length(density) > 1
[~, unique_idx] = unique(value);
meanDensityWidth = interp1(value(unique_idx), density(unique_idx), meanValue, 'linear','extrap')*width;
else % all data is identical:
meanDensityWidth = density*width;
end
if meanDensityWidth<args.BoxWidth/2
meanDensityWidth=args.BoxWidth/2;
end
switch args.HalfViolin
case 'right'
obj.MeanPlot = plot(pos+[0,1].*meanDensityWidth, ...
[meanValue, meanValue]);
case 'left'
obj.MeanPlot = plot(pos+[-1,0].*meanDensityWidth, ...
[meanValue, meanValue]);
case 'full'
obj.MeanPlot = plot(pos+[-1,1].*meanDensityWidth, ...
[meanValue, meanValue]);
end
obj.MeanPlot.LineWidth = 1;
%% Plot the median, notch, and whiskers
IQR = quartiles(3) - quartiles(1);
lowhisker = quartiles(1) - 1.5*IQR;
lowhisker = max(lowhisker, min(data(data > lowhisker)));
hiwhisker = quartiles(3) + 1.5*IQR;
hiwhisker = min(hiwhisker, max(data(data < hiwhisker)));
if ~isempty(lowhisker) && ~isempty(hiwhisker)
obj.WhiskerPlot = plot([pos pos], [lowhisker hiwhisker]);
end
% Median
obj.MedianPlot = scatter(pos, quartiles(2), args.MedianMarkerSize, [1 1 1], 'filled');
% Notches
obj.NotchPlots = ...
scatter(pos, quartiles(2)-1.57*IQR/sqrt(length(data)), ...
[], [1 1 1], 'filled', '^');
obj.NotchPlots(2) = ...
scatter(pos, quartiles(2)+1.57*IQR/sqrt(length(data)), ...
[], [1 1 1], 'filled', 'v');
%% Set graphical preferences
obj.EdgeColor = args.EdgeColor;
obj.MedianPlot.LineWidth = args.LineWidth;
obj.BoxColor = args.BoxColor;
obj.BoxWidth = args.BoxWidth;
obj.MedianColor = args.MedianColor;
obj.ShowData = args.ShowData;
obj.ShowNotches = args.ShowNotches;
obj.ShowMean = args.ShowMean;
obj.ShowBox = args.ShowBox;
obj.ShowMedian = args.ShowMedian;
obj.ShowWhiskers = args.ShowWhiskers;
if not(isempty(args.ViolinColor))
if size(args.ViolinColor{1},1) > 1
ViolinColor{1} = args.ViolinColor{1}(pos,:);
else
ViolinColor{1} = args.ViolinColor{1};
end
if length(args.ViolinColor)==2
if size(args.ViolinColor{2},1) > 1
ViolinColor{2} = args.ViolinColor{2}(pos,:);
else
ViolinColor{2} = args.ViolinColor{2};
end
else
ViolinColor{2} = ViolinColor{1};
end
else
% defaults
if args.scpltBool
ViolinColor{1} = obj.ScatterPlot.CData;
else
ViolinColor{1} = [0 0 0];
end
ViolinColor{2} = [0 0 0];
end
obj.ViolinColor = ViolinColor;
if not(isempty(args.ViolinAlpha))
if length(args.ViolinAlpha{1})>1
error('Only scalar values are accepted for the alpha color channel');
else
ViolinAlpha{1} = args.ViolinAlpha{1};
end
if length(args.ViolinAlpha)==2
if length(args.ViolinAlpha{2})>1
error('Only scalar values are accepted for the alpha color channel');
else
ViolinAlpha{2} = args.ViolinAlpha{2};
end
else
ViolinAlpha{2} = ViolinAlpha{1}/2; % default unless specified
end
else
% default
ViolinAlpha = {1,1};
end
obj.ViolinAlpha = ViolinAlpha;
end
%% SET METHODS
function set.EdgeColor(obj, color)
if ~isempty(obj.ViolinPlot)
obj.ViolinPlot.EdgeColor = color;
obj.ViolinPlotQ.EdgeColor = color;
if ~isempty(obj.ViolinPlot2)
obj.ViolinPlot2.EdgeColor = color;
end
end
end
function color = get.EdgeColor(obj)
if ~isempty(obj.ViolinPlot)
color = obj.ViolinPlot.EdgeColor;
end
end
function set.MedianColor(obj, color)
obj.MedianPlot.MarkerFaceColor = color;
if ~isempty(obj.NotchPlots)
obj.NotchPlots(1).MarkerFaceColor = color;
obj.NotchPlots(2).MarkerFaceColor = color;
end
end
function color = get.MedianColor(obj)
color = obj.MedianPlot.MarkerFaceColor;
end
function set.BoxColor(obj, color)
if ~isempty(obj.BoxPlot)
obj.BoxPlot.FaceColor = color;
obj.BoxPlot.EdgeColor = color;
obj.WhiskerPlot.Color = color;
obj.MedianPlot.MarkerEdgeColor = color;
obj.NotchPlots(1).MarkerFaceColor = color;
obj.NotchPlots(2).MarkerFaceColor = color;
elseif ~isempty(obj.ViolinPlotQ)
obj.WhiskerPlot.Color = color;
obj.MedianPlot.MarkerEdgeColor = color;
obj.NotchPlots(1).MarkerFaceColor = color;
obj.NotchPlots(2).MarkerFaceColor = color;
end
end
function color = get.BoxColor(obj)
if ~isempty(obj.BoxPlot)
color = obj.BoxPlot.FaceColor;
end
end
function set.BoxWidth(obj,width)
if ~isempty(obj.BoxPlot)
pos=mean(obj.BoxPlot.XData);
obj.BoxPlot.XData=pos+[-1,1,1,-1]*width;
end
end
function width = get.BoxWidth(obj)
width=max(obj.BoxPlot.XData)-min(obj.BoxPlot.XData);
end
function set.ViolinColor(obj, color)
obj.ViolinPlot.FaceColor = color{1};
obj.ScatterPlot.MarkerFaceColor = color{1};
obj.MeanPlot.Color = color{1};
if ~isempty(obj.ViolinPlot2)
obj.ViolinPlot2.FaceColor = color{2};
obj.ScatterPlot2.MarkerFaceColor = color{2};
end
if ~isempty(obj.ViolinPlotQ)
obj.ViolinPlotQ.FaceColor = color{1};
end
for idx = 1: size(obj.HistogramPlot,1)
obj.HistogramPlot(idx).Color = color{1};
end
end
function color = get.ViolinColor(obj)
color{1} = obj.ViolinPlot.FaceColor;
if ~isempty(obj.ViolinPlot2)
color{2} = obj.ViolinPlot2.FaceColor;
end
end
function set.ViolinAlpha(obj, alpha)
obj.ViolinPlotQ.FaceAlpha = .65;
obj.ViolinPlot.FaceAlpha = alpha{1};
obj.ScatterPlot.MarkerFaceAlpha = 1;
if ~isempty(obj.ViolinPlot2)
obj.ViolinPlot2.FaceAlpha = alpha{2};
obj.ScatterPlot2.MarkerFaceAlpha = 1;
end
end
function alpha = get.ViolinAlpha(obj)
alpha{1} = obj.ViolinPlot.FaceAlpha;
if ~isempty(obj.ViolinPlot2)
alpha{2} = obj.ViolinPlot2.FaceAlpha;
end
end
function set.ShowData(obj, yesno)
if yesno
obj.ScatterPlot.Visible = 'on';
for idx = 1: size(obj.HistogramPlot,1)
obj.HistogramPlot(idx).Visible = 'on';
end
else
obj.ScatterPlot.Visible = 'off';
for idx = 1: size(obj.HistogramPlot,1)
obj.HistogramPlot(idx).Visible = 'off';
end
end
if ~isempty(obj.ScatterPlot2)
obj.ScatterPlot2.Visible = obj.ScatterPlot.Visible;
end
end
function yesno = get.ShowData(obj)
if ~isempty(obj.ScatterPlot)
yesno = strcmp(obj.ScatterPlot.Visible, 'on');
end
end
function set.ShowNotches(obj, yesno)
if ~isempty(obj.NotchPlots)
if yesno
obj.NotchPlots(1).Visible = 'on';
obj.NotchPlots(2).Visible = 'on';
else
obj.NotchPlots(1).Visible = 'off';
obj.NotchPlots(2).Visible = 'off';
end
end
end
function yesno = get.ShowNotches(obj)
if ~isempty(obj.NotchPlots)
yesno = strcmp(obj.NotchPlots(1).Visible, 'on');
end
end
function set.ShowMean(obj, yesno)
if ~isempty(obj.MeanPlot)
if yesno
obj.MeanPlot.Visible = 'on';
else
obj.MeanPlot.Visible = 'off';
end
end
end
function yesno = get.ShowMean(obj)
if ~isempty(obj.BoxPlot)
yesno = strcmp(obj.BoxPlot.Visible, 'on');
end
end
function set.ShowBox(obj, yesno)
if ~isempty(obj.BoxPlot)
if yesno
obj.BoxPlot.Visible = 'on';
else
obj.BoxPlot.Visible = 'off';
end
end
end
function yesno = get.ShowBox(obj)
if ~isempty(obj.BoxPlot)
yesno = strcmp(obj.BoxPlot.Visible, 'on');
end
end
function set.ShowMedian(obj, yesno)
if ~isempty(obj.MedianPlot)
if yesno
obj.MedianPlot.Visible = 'on';
else
obj.MedianPlot.Visible = 'off';
end
end
end
function yesno = get.ShowMedian(obj)
if ~isempty(obj.MedianPlot)
yesno = strcmp(obj.MedianPlot.Visible, 'on');
end
end
function set.ShowWhiskers(obj, yesno)
if ~isempty(obj.WhiskerPlot)
if yesno
obj.WhiskerPlot.Visible = 'on';
else
obj.WhiskerPlot.Visible = 'off';
end
end
end
function yesno = get.ShowWhiskers(obj)
if ~isempty(obj.WhiskerPlot)
yesno = strcmp(obj.WhiskerPlot.Visible, 'on');
end
end
end
methods (Access=private)
function results = checkInputs(~, data, pos, varargin)
isscalarnumber = @(x) (isnumeric(x) & isscalar(x));
p = inputParser();
p.addRequired('Data', @(x)isnumeric(vertcat(x{:})));
p.addRequired('Pos', isscalarnumber);
p.addParameter('Width', 0.3, isscalarnumber);
p.addParameter('Bandwidth', [], isscalarnumber);
iscolor = @(x) (isnumeric(x) & size(x,2) == 3);
p.addParameter('ViolinColor', [], @(x)iscolor(vertcat(x{:})));
p.addParameter('MarkerSize', 24, @isnumeric);
p.addParameter('MedianMarkerSize', 36, @isnumeric);
p.addParameter('LineWidth', 0.75, @isnumeric);
p.addParameter('BoxColor', [0.5 0.5 0.5], iscolor);
p.addParameter('BoxWidth', 0.01, isscalarnumber);
p.addParameter('EdgeColor', [0.5 0.5 0.5], iscolor);
p.addParameter('MedianColor', [1 1 1], iscolor);
p.addParameter('ViolinAlpha', {0.3,0.15}, @(x)isnumeric(vertcat(x{:})));
isscalarlogical = @(x) (islogical(x) & isscalar(x));
p.addParameter('ShowData', true, isscalarlogical);
p.addParameter('ShowNotches', false, isscalarlogical);
p.addParameter('ShowMean', false, isscalarlogical);
p.addParameter('ShowBox', true, isscalarlogical);
p.addParameter('ShowMedian', true, isscalarlogical);
p.addParameter('ShowWhiskers', true, isscalarlogical);
validSides={'full', 'right', 'left'};
checkSide = @(x) any(validatestring(x, validSides));
p.addParameter('HalfViolin', 'full', checkSide);
validQuartileStyles={'boxplot', 'shadow', 'none'};
checkQuartile = @(x)any(validatestring(x, validQuartileStyles));
p.addParameter('QuartileStyle', 'boxplot', checkQuartile);
validDataStyles = {'scatter', 'histogram', 'none'};
checkStyle = @(x)any(validatestring(x, validDataStyles));
p.addParameter('DataStyle', 'scatter', checkStyle);
p.parse(data, pos, varargin{:});
results = p.Results;
end
end
methods (Static)
function [density, value, width] = calcKernelDensity(data, bandwidth, width)
if isempty(data)
error('Empty input data');
end
[density, value] = ksdensity(data, 'bandwidth', bandwidth);
density = density(value >= min(data) & value <= max(data));
value = value(value >= min(data) & value <= max(data));
value(1) = min(data);
value(end) = max(data);
value = [value(1)*(1-1E-5), value, value(end)*(1+1E-5)];
density = [0, density, 0];
% all data is identical
if min(data) == max(data)
density = 1;
value= mean(value);
end
width = width/max(density);
end
end
end

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function testviolinplot()
figure();
% One could use tiled layout for better plotting them but it would be
% incompatible with older versions
subplot(2,4,1);
% TEST CASE 1
disp('Test 1: Violin plot default options');
load carbig MPG Origin
Origin = cellstr(Origin);
vs = violinplot(MPG, Origin);
plotdetails(1);
% TEST CASE 2
disp('Test 2: Test the plot ordering option');
grouporder={'USA','Sweden','Japan','Italy','Germany','France','England'};
subplot(2,4,2);
vs2 = violinplot(MPG,Origin,'GroupOrder',grouporder);
plotdetails(2);
% TEST CASE 3
disp('Test 3: Test the numeric input construction mode');
subplot(2,4,3);
cats = categorical(Origin);
catnames = (unique(cats)); % this ignores categories without any data
catnames_labels = {};
thisData = NaN(length(MPG),length(catnames));
for n = 1:length(catnames)
thisCat = catnames(n);
catnames_labels{n} = char(thisCat);
thisData(1:length(MPG(cats == thisCat)),n) = MPG(cats == thisCat);
end
vs3 = violinplot(thisData,catnames_labels);
plotdetails(3);
% TEST CASE 4
disp('Test 4: Test two sided violin plots. Japan is being compared.');
subplot(2,4,4);
C = colororder;
vs4 = violinplot({thisData,repmat(thisData(:,5),1,7)},catnames_labels,'ViolinColor',{C,C(5,:)},'ViolinAlpha',{0.3 0.3}, 'ShowMean', true, 'MarkerSize',8);
plotdetails(4);
% TEST CASE 5
disp('Test 5: Test shadow for quartiles.');
subplot(2,4,5);
vs5 = violinplot(MPG, Origin, 'QuartileStyle','shadow');
plotdetails(5);
% TEST CASE 6
disp('Test 6: Test plotting only right side & histogram plot, with quartiles as boxplot.');
subplot(2,4,6);
vs5 = violinplot(MPG, Origin, 'QuartileStyle','boxplot', 'HalfViolin','right',...
'DataStyle', 'histogram');
plotdetails(6);
% TEST CASE 7
disp('Test 7: Test plotting only left side & histogram plot, and quartiles as shadow.');
subplot(2,4,7);
vs5 = violinplot(MPG, Origin, 'QuartileStyle','shadow', 'HalfViolin','left',...
'DataStyle', 'histogram', 'ShowMean', true);
plotdetails(7);
% TEST CASE 8
disp('Test 8: Same as previous one, just removing the data of half of the violins afterwards.');
subplot(2,4,8);
vs5 = violinplot([MPG; 5;5;5;5;5], [Origin; 'test';'test';'test';'test';'test'], 'QuartileStyle','shadow', 'HalfViolin','full',...
'DataStyle', 'scatter', 'ShowMean', false);
plotdetails(8);
for n= 1:round(length(vs5)/2)
vs5(1,n).ShowData = 0;
end
xlim([0, 9]);
%other test cases could be added here
end
function plotdetails(n)
title(sprintf('Test %02.0f \n',n));
ylabel('Fuel Economy in MPG ');
xlim([0, 8]); grid minor;
set(gca, 'color', 'none');
xtickangle(-30);
fprintf('Test %02.0f passed ok! \n ',n);
end

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function violins = violinplot(data, cats, varargin)
%Violinplots plots violin plots of some data and categories
% VIOLINPLOT(DATA) plots a violin of a double vector DATA
%
% VIOLINPLOT(DATAMATRIX) plots violins for each column in
% DATAMATRIX.
%
% VIOLINPLOT(DATAMATRIX, CATEGORYNAMES) plots violins for each
% column in DATAMATRIX and labels them according to the names in the
% cell-of-strings CATEGORYNAMES.
%
% In the cases above DATA and DATAMATRIX can be a vector or a matrix,
% respectively, either as is or wrapped in a cell.
% To produce violins which have one distribution on one half and another
% one on the other half, DATA and DATAMATRIX have to be cell arrays
% with two elements, each containing a vector or a matrix. The number of
% columns of the two data sets has to be the same.
%
% VIOLINPLOT(DATA, CATEGORIES) where double vector DATA and vector
% CATEGORIES are of equal length; plots violins for each category in
% DATA.
%
% VIOLINPLOT(TABLE), VIOLINPLOT(STRUCT), VIOLINPLOT(DATASET)
% plots violins for each column in TABLE, each field in STRUCT, and
% each variable in DATASET. The violins are labeled according to
% the table/dataset variable name or the struct field name.
%
% violins = VIOLINPLOT(...) returns an object array of
% <a href="matlab:help('Violin')">Violin</a> objects.
%
% VIOLINPLOT(..., 'PARAM1', val1, 'PARAM2', val2, ...)
% specifies optional name/value pairs for all violins:
% 'Width' Width of the violin in axis space.
% Defaults to 0.3
% 'Bandwidth' Bandwidth of the kernel density estimate.
% Should be between 10% and 40% of the data range.
% 'ViolinColor' Fill color of the violin area and data points. Accepts
% 1x3 color vector or nx3 color vector where n = num
% groups. In case of two data sets being compared it can
% be an array of up to two cells containing nx3
% matrices.
% Defaults to the next default color cycle.
% 'ViolinAlpha' Transparency of the violin area and data points.
% Can be either a single scalar value or an array of
% up to two cells containing scalar values.
% Defaults to 0.3.
% 'MarkerSize' Size of the data points, if shown.
% Defaults to 24
% 'MedianMarkerSize' Size of the median indicator, if shown.
% Defaults to 36
% 'EdgeColor' Color of the violin area outline.
% Defaults to [0.5 0.5 0.5]
% 'BoxColor' Color of the box, whiskers, and the outlines of
% the median point and the notch indicators.
% Defaults to [0.5 0.5 0.5]
% 'MedianColor' Fill color of the median and notch indicators.
% Defaults to [1 1 1]
% 'ShowData' Whether to show data points.
% Defaults to true
% 'ShowNotches' Whether to show notch indicators.
% Defaults to false
% 'ShowMean' Whether to show mean indicator
% Defaults to false
% 'ShowBox' Whether to show the box.
% Defaults to true
% 'ShowMedian' Whether to show the median indicator.
% Defaults to true
% 'ShowWhiskers' Whether to show the whiskers
% Defaults to true
% 'GroupOrder' Cell of category names in order to be plotted.
% Defaults to alphabetical ordering
% Copyright (c) 2016, Bastian Bechtold
% This code is released under the terms of the BSD 3-clause license
hascategories = exist('cats','var') && not(isempty(cats));
%parse the optional grouporder argument
%if it exists parse the categories order
% but also delete it from the arguments passed to Violin
grouporder = {};
idx=find(strcmp(varargin, 'GroupOrder'));
if ~isempty(idx) && numel(varargin)>idx
if iscell(varargin{idx+1})
grouporder = varargin{idx+1};
varargin(idx:idx+1)=[];
else
error('Second argument of ''GroupOrder'' optional arg must be a cell of category names')
end
end
% check and correct the structure of ViolinColor input
idx=find(strcmp(varargin, 'ViolinColor'));
if ~isempty(idx) && iscell(varargin{idx+1})
if length(varargin{idx+1}(:))>2
error('ViolinColor input can be at most a two element cell array');
end
elseif ~isempty(idx) && isnumeric(varargin{idx+1})
varargin{idx+1} = varargin(idx+1);
end
% check and correct the structure of ViolinAlpha input
idx=find(strcmp(varargin, 'ViolinAlpha'));
if ~isempty(idx) && iscell(varargin{idx+1})
if length(varargin{idx+1}(:))>2
error('ViolinAlpha input can be at most a two element cell array');
end
elseif ~isempty(idx) && isnumeric(varargin{idx+1})
varargin{idx+1} = varargin(idx+1);
end
% tabular data
if isa(data, 'dataset') || isstruct(data) || istable(data)
if isa(data, 'dataset')
colnames = data.Properties.VarNames;
elseif istable(data)
colnames = data.Properties.VariableNames;
elseif isstruct(data)
colnames = fieldnames(data);
end
catnames = {};
if isempty(grouporder)
for n=1:length(colnames)
if isnumeric(data.(colnames{n}))
catnames = [catnames colnames{n}]; %#ok<*AGROW>
end
end
catnames = sort(catnames);
else
for n=1:length(grouporder)
if isnumeric(data.(grouporder{n}))
catnames = [catnames grouporder{n}];
end
end
end
for n=1:length(catnames)
thisData = data.(catnames{n});
violins(n) = Violin({thisData}, n, varargin{:});
end
set(gca, 'XTick', 1:length(catnames), 'XTickLabels', catnames);
set(gca,'Box','on');
return
elseif iscell(data) && length(data(:))==2 % cell input
if not(size(data{1},2)==size(data{2},2))
error('The two input data matrices have to have the same number of columns');
end
elseif iscell(data) && length(data(:))>2 % cell input
error('Up to two datasets can be compared');
elseif isnumeric(data) % numeric input
% 1D data, one category for each data point
if hascategories && numel(data) == numel(cats)
if isempty(grouporder)
cats = categorical(cats);
else
cats = categorical(cats, grouporder);
end
catnames = (unique(cats)); % this ignores categories without any data
catnames_labels = {};
for n = 1:length(catnames)
thisCat = catnames(n);
catnames_labels{n} = char(thisCat);
thisData = data(cats == thisCat);
violins(n) = Violin({thisData}, n, varargin{:});
end
set(gca, 'XTick', 1:length(catnames), 'XTickLabels', catnames_labels);
set(gca,'Box','on');
return
else
data = {data};
end
end
% 1D data, no categories
if not(hascategories) && isvector(data{1})
violins = Violin(data, 1, varargin{:});
set(gca, 'XTick', 1);
% 2D data with or without categories
elseif ismatrix(data{1})
for n=1:size(data{1}, 2)
thisData = cellfun(@(x)x(:,n),data,'UniformOutput',false);
violins(n) = Violin(thisData, n, varargin{:});
end
set(gca, 'XTick', 1:size(data{1}, 2));
if hascategories && length(cats) == size(data{1}, 2)
set(gca, 'XTickLabels', cats);
end
end
set(gca,'Box','on');
end