本文将为大家详细讲解Matlab中小提琴图的绘制函数及ggtheme主题修饰函数
写了个matlab绘制小提琴图的函数：
1.图中小提琴状区域为核密度曲线。
2.白色方块为25%，75%分位数。
3.中间横线为中位数。
4.白色点为离群值点。
5.竖着的黑线是去掉离群值点后点的上下限。
X=1:5; Y=randn(100,5); violinChart(gca,X,Y,[0 0.447 0.741],0.6);
X=[1.*ones(1,50),2.*ones(1,30),3.*ones(1,20),4.*ones(1,50),5.*ones(1,50)]; Y=randn(1,200)+sin(X); violinChart(gca,X,Y,[0 0.447 0.741]);
X1=[1:2:7,13];
Y1=randn(100,5)+sin(X1);
X2=2:2:10;
Y2=randn(100,5)+cos(X2);
figure
Hdl1=violinChart(gca,X1,Y1,[0 0.447 0.741]);
Hdl2=violinChart(gca,X2,Y2,[0.850 0.325 0.098]);
legend([Hdl1.F_legend,Hdl2.F_legend],{'randn+sin(x)','randn+cos(x)'});
若函数有更新则会将更新版本放入文末所示压缩文件内。
function Hdl=violinChart(ax,X,Y,FaceColor,width)
% @author slandarer
% Hdl: 返回的图形对象句柄结构体
% - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
% Hdl.F_density(i) | patch | 核密度分布
% Hdl.F_outlier(i) | scatter | 离群值点
% Hdl.F_range95(i) | line | 去除离群值点后最大值及最小值
% Hdl.F_quantile(i) | patch | 四分位数框
% Hdl.F_medianLine(i)| line | 中位数
%
% Hdl.F_legend | patch | 用于生成legend图例的图形对象
% - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
% 请使用如下方式生成图例：
% Hdl1=violinChart(ax,X,Y,... ...)
% Hdl2=violinChart(ax,X,Y,... ...)
% ... ...
% legend([Hdl1,Hdl2,... ...],{Name1,Name2,...})
% ===========================================================
% 以下为使用实例代码：
% - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
% X1=[1:2:7,13];
% Y1=randn(100,5)+sin(X1);
% X2=2:2:10;
% Y2=randn(100,5)+cos(X2);
%
% Hdl1=violinChart(gca,X1,Y1,[0 0.447 0.741],0.5);
% Hdl2=violinChart(gca,X2,Y2,[0.850 0.325 0.098],0.5);
% legend([Hdl1.F_legend,Hdl2.F_legend],{'randn+sin(x)','randn+cos(x)'});
if nargin<5
width=0.4;
end
if ~isempty(ax)
else
ax=gca;
end
hold(ax,'on');
oriX=X;
X=unique(X);
sep=min(diff(X));
if isempty(sep)
sep=1;
end
for i=1:length(X)
if length(oriX)==numel(Y)
tY=Y(oriX==X(i));
else
tY=Y(:,i);
end
[f,yi]=ksdensity(tY);
Hdl.F_density(i)=fill([f,-f(end:-1:1)].*sep.*width+X(i),[yi,yi(end:-1:1)],FaceColor);
outliBool=isoutlier(tY,'quartiles');
outli=tY(outliBool);
Hdl.F_outlier(i)=scatter(repmat(X(i),[length(outli),1]),outli,20,'filled',...
'CData',[1 1 1],'MarkerEdgeColor','none');
nY=tY(~outliBool);
Hdl.F_range95(i)=plot([X(i),X(i)],[min(nY),max(nY)],'k','lineWidth',1);
qt25=quantile(tY,0.25);
qt75=quantile(tY,0.75);
Hdl.F_quantile(i)=fill(X(i)+0.6.*sep.*width.*[-1 1 1 -1].*max(f),...
[qt25,qt25,qt75,qt75],[1 1 1],...
'EdgeColor',[0 0 0]);
med=median(tY);
Hdl.F_medianLine(i)=plot(X(i)+0.6.*sep.*width.*[-1 1].*max(f),[med,med],'LineWidth',3,...
'Color',[0 0 0]);
end
Hdl.F_legend=Hdl.F_density(1);
end
假设你已经编写了上述绘图代码，只需要将最后增添一行变为
X1=[1:2:7,13];
Y1=randn(100,5)+sin(X1);
X2=2:2:10;
Y2=randn(100,5)+cos(X2);
figure
Hdl1=violinChart(gca,X1,Y1,[0 0.447 0.741]);
Hdl2=violinChart(gca,X2,Y2,[0.850 0.325 0.098]);
legend([Hdl1.F_legend,Hdl2.F_legend],{'randn+sin(x)','randn+cos(x)'});
ggThemeViolin(gca,[Hdl1,Hdl2],'dust');
则图像会被修饰：
而将函数最后加入‘LP’参数则变为：
ggThemeViolin(gca,[Hdl1,Hdl2],'dust','LP');
主题有如下选择：
'flat'/'flat_dark'/'camouflage'/'chalk'/
'copper'/'dust'/'earth'/'fresh'/'grape'/
'grass'/'greyscale'/'light'/'lilac'/'pale'/
'sea'/'sky'/'solarized'
'flat'
'flat_dark'
'camouflage'
'chalk'
'copper'
'dust'
'earth'
'fresh'
'grape'
'grass'
'greyscale'
'light'
'lilac'
'pale'
'sea'
'sky'
'solarized'
注意，要使用ggThemeViolin修饰器函数，需要保证当前文件夹有themeCSS.mat文件，该文件将会一同在压缩包内给出。
function ax=ggThemeViolin(varargin)
% @author:slandarer
%
% 参数说明：
% -----------------------------------------------------
% AxesTheme | 坐标区域风格 | 'flat'/'flat_dark'/'camouflage'/'chalk'/
% 'copper'/'dust'/'earth'/'fresh'/'grape'/
% 'grass'/'greyscale'/'light'/'lilac'/'pale'
% 'sea'/'sky'/'solarized'
%
% HDLset | 句柄集合
% 获取要处理的坐标区域=====================================================
if strcmp(get(varargin{1},'type'),'axes' )
ax=varargin{1};
else
ax=gca;
end
hold(ax,'on')
% 获取要处理的图像句柄=====================================================
HDLset=varargin{2};
% 获取风格名称=============================================================
theme.AxesTheme='flat';
if length(varargin)>2
theme.AxesTheme=varargin{3};
end
% 开始风格化===============================================================
ax.Box='off';
ax.YGrid='on';
ax.XGrid='on';
ax.GridLineStyle='--';
ax.LineWidth=1.2;
% 主题风格化
Tm=load('themeCSS.mat');
Tm=Tm.theme;
ax.Color=Tm.(theme.AxesTheme).Color;
ax.TickLength=Tm.(theme.AxesTheme).TickLength;
ax.GridColorMode=Tm.(theme.AxesTheme).GridColorMode;
ax.GridColor=Tm.(theme.AxesTheme).GridColor;
ax.GridAlpha=Tm.(theme.AxesTheme).GridAlpha;
ax.XColor=Tm.(theme.AxesTheme).XColor;
ax.YColor=Tm.(theme.AxesTheme).YColor;
ax.TickDir=Tm.(theme.AxesTheme).TickDir;
ax.ColorOrder=Tm.(theme.AxesTheme).ColorOrder;
for i=1:length(HDLset)
for j=1:length(HDLset(i).F_density)
HDLset(i).F_density(j).FaceColor=ax.ColorOrder(mod(i-1,size(ax.ColorOrder,1))+1,:);
HDLset(i).F_density(j).EdgeColor=[.1,.1,.1];
f_max=(max(HDLset(i).F_density(j).XData)-min(HDLset(i).F_density(j).XData))/2;
x_mid=(max(HDLset(i).F_density(j).XData)+min(HDLset(i).F_density(j).XData))/2;
HDLset(i).F_quantile(j).XData=x_mid+0.4.*f_max.*[-1 1 1 -1];
HDLset(i).F_quantile(j).FaceColor=[1 1 1].*0.95;
HDLset(i).F_medianLine(j).XData=x_mid+0.4.*f_max.*[-1 1];
HDLset(i).F_medianLine(j).LineWidth=2;
HDLset(i).F_medianLine(j).Color=[0.3,0.3,0.3];
HDLset(i).F_outlier(j).CData=Tm.(theme.AxesTheme).EdgeColor;
end
end
if ~isempty(ax.Legend)
ax.Legend.Box='off';
ax.Legend.FontSize=12;
if mean(ax.Color)>0.6
ax.Legend.TextColor=ax.XColor;
else
ax.Legend.TextColor=[0.9 0.9 0.9];
end
if ~isempty(regexpi(ax.Legend.Location,'out', 'once'))
ax.Legend.TextColor=ax.XColor;
ax.Legend.Title.FontSize=14;
end
ax.Legend.AutoUpdate='off';
end
end 
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