小编给大家分享一下Matlab怎么绘制散点密度图，相信大部分人都还不怎么了解，因此分享这篇文章给大家参考一下，希望大家阅读完这篇文章后大有收获，下面让我们一起去了解一下吧！
效果
原理也很简单，通过matlab自带的ksdensity获得网格每一点密度，通过密度拟合曲面，再计算每个数据点对应的概率，并将概率映射到颜色即可
为了怕大家找不到函数这次工具函数放到最前面
1工具函数完整代码
function [CData,h,XMesh,YMesh,ZMesh,colorList]=density2C(X,Y,XList,YList,colorList) [XMesh,YMesh]=meshgrid(XList,YList); XYi=[XMesh(:) YMesh(:)]; F=ksdensity([X,Y],XYi); ZMesh=zeros(size(XMesh)); ZMesh(1:length(F))=F; h=interp2(XMesh,YMesh,ZMesh,X,Y); if nargin<5 colorList=[0.2700 0 0.3300 0.2700 0.2300 0.5100 0.1900 0.4100 0.5600 0.1200 0.5600 0.5500 0.2100 0.7200 0.4700 0.5600 0.8400 0.2700 0.9900 0.9100 0.1300]; end colorFunc=colorFuncFactory(colorList); CData=colorFunc((h-min(h))./(max(h)-min(h))); colorList=colorFunc(linspace(0,1,100)'); function colorFunc=colorFuncFactory(colorList) x=(0:size(colorList,1)-1)./(size(colorList,1)-1); y1=colorList(:,1);y2=colorList(:,2);y3=colorList(:,3); colorFunc=@(X)[interp1(x,y1,X,'pchip'),interp1(x,y2,X,'pchip'),interp1(x,y3,X,'pchip')]; end end
2参数说明
输入：
-
X,Y 散点坐标
-
XList,YList 用来构造密度曲面网格的序列，其实就是把XLim，YLim分成小份，例如XList=0:0.1:10
-
colorList 颜色表mx3数组，用来构造将高度映射到颜色函数的数据表
输出：
-
CData各个点对应颜色
-
h 各个点对应核密度
-
XMesh,YMesh,ZMesh 核密度曲面数据
-
colorList 插值后更细密的颜色表
3使用方式
假如编写了如下程序：
PntSet1=mvnrnd([2 3],[1 0;0 2],800); PntSet2=mvnrnd([6 7],[1 0;0 2],800); PntSet3=mvnrnd([8 9],[1 0;0 1],800); PntSet=[PntSet1;PntSet2;PntSet3]; scatter(PntSet(:,1),PntSet(:,2),'filled');
结果：
3.1散点赋色
将上面那段代码改写
PntSet1=mvnrnd([2 3],[1 0;0 2],800); PntSet2=mvnrnd([6 7],[1 0;0 2],800); PntSet3=mvnrnd([8 9],[1 0;0 1],800); PntSet=[PntSet1;PntSet2;PntSet3]; CData=density2C(PntSet(:,1),PntSet(:,2),-2:0.1:15,-2:0.1:15); scatter(PntSet(:,1),PntSet(:,2),'filled','CData',CData);
3.2等高线图
PntSet1=mvnrnd([2 3],[1 0;0 2],800); PntSet2=mvnrnd([6 7],[1 0;0 2],800); PntSet3=mvnrnd([8 9],[1 0;0 1],800); PntSet=[PntSet1;PntSet2;PntSet3]; [~,~,XMesh,YMesh,ZMesh,colorList]=density2C(PntSet(:,1),PntSet(:,2),-2:0.1:12,-2:0.1:12); colormap(colorList) contourf(XMesh,YMesh,ZMesh,10)
3.3带直方图的散点图
PntSet1=mvnrnd([2 3],[1 0;0 2],800);
PntSet2=mvnrnd([6 7],[1 0;0 2],800);
PntSet3=mvnrnd([8 9],[1 0;0 1],800);
PntSet=[PntSet1;PntSet2;PntSet3];
colorList=[0.9400 0.9700 0.9600
0.8900 0.9300 0.9200
0.8200 0.9100 0.8800
0.6900 0.8500 0.7700
0.5900 0.7800 0.6900
0.5500 0.7500 0.6500
0.4500 0.6500 0.5600
0.4000 0.5800 0.4900
0.3500 0.5100 0.4200
0.2500 0.3600 0.3100
0.1300 0.1700 0.1400];
CData=density2C(PntSet(:,1),PntSet(:,2),-2:0.1:15,-2:0.1:15,colorList);
set(gcf,'Color',[1 1 1]);
% 主分布图
ax1=axes('Parent',gcf);hold(ax1,'on')
scatter(ax1,PntSet(:,1),PntSet(:,2),'filled','CData',CData);
ax1.Position=[0.1,0.1,0.6,0.6];
% X轴直方图
ax2=axes('Parent',gcf);hold(ax2,'on')
histogram(ax2,PntSet(:,1),'FaceColor',[0.78 0.88 0.82],...
'EdgeColor','none','FaceAlpha',0.7)
ax2.Position=[0.1,0.75,0.6,0.15];
ax2.YColor='none';
ax2.XTickLabel='';
ax2.TickDir='out';
ax2.XLim=ax1.XLim;
% Y轴直方图
ax3=axes('Parent',gcf);hold(ax3,'on')
histogram(ax3,PntSet(:,2),'FaceColor',[0.78 0.88 0.82],...
'EdgeColor','none','FaceAlpha',0.7,'Orientation','horizontal')
ax3.Position=[0.75,0.1,0.15,0.6];
ax3.XColor='none';
ax3.YTickLabel='';
ax3.TickDir='out';
ax3.YLim=ax1.YLim;
3.4带直方图的等高线图
PntSet1=mvnrnd([2 3],[1 0;0 2],800);
PntSet2=mvnrnd([6 7],[1 0;0 2],800);
PntSet3=mvnrnd([8 9],[1 0;0 1],800);
PntSet=[PntSet1;PntSet2;PntSet3];
colorList=[0.9300 0.9500 0.9700
0.7900 0.8400 0.9100
0.6500 0.7300 0.8500
0.5100 0.6200 0.7900
0.3700 0.5100 0.7300
0.2700 0.4100 0.6300
0.2100 0.3200 0.4900
0.1500 0.2200 0.3500
0.0900 0.1300 0.2100
0.0300 0.0400 0.0700];
[~,~,XMesh,YMesh,ZMesh,colorList]=density2C(PntSet(:,1),PntSet(:,2),-2:0.1:13,-2:0.1:13,colorList);
set(gcf,'Color',[1 1 1]);
% 主分布图
ax1=axes('Parent',gcf);hold(ax1,'on')
colormap(colorList)
contourf(XMesh,YMesh,ZMesh,10,'EdgeColor','none')
ax1.Position=[0.1,0.1,0.6,0.6];
ax1.TickDir='out';
% X轴直方图
ax2=axes('Parent',gcf);hold(ax2,'on')
[f,xi]=ksdensity(PntSet(:,1));
fill([xi,xi(1)],[f,0],[0.34 0.47 0.71],'FaceAlpha',...
0.3,'EdgeColor',[0.34 0.47 0.71],'LineWidth',1.2)
ax2.Position=[0.1,0.75,0.6,0.15];
ax2.YColor='none';
ax2.XTickLabel='';
ax2.TickDir='out';
ax2.XLim=ax1.XLim;
% Y轴直方图
ax3=axes('Parent',gcf);hold(ax3,'on')
[f,yi]=ksdensity(PntSet(:,2));
fill([f,0],[yi,yi(1)],[0.34 0.47 0.71],'FaceAlpha',...
0.3,'EdgeColor',[0.34 0.47 0.71],'LineWidth',1.2)
ax3.Position=[0.75,0.1,0.15,0.6];
ax3.XColor='none';
ax3.YTickLabel='';
ax3.TickDir='out';
ax3.YLim=ax1.YLim;
4使用方式扩展–与ggplot修饰器联动
ggplot风格修饰器：(点击图片跳转链接)
示例1
PntSet1=mvnrnd([2 3],[1 0;0 2],800); PntSet2=mvnrnd([6 7],[1 0;0 2],800); PntSet3=mvnrnd([8 9],[1 0;0 1],800); PntSet=[PntSet1;PntSet2;PntSet3]; ax=gca; ax.XLim=[-1 13]; ax.YLim=[-1 13]; ax=ggplotAxes2D(ax); CData=density2C(PntSet(:,1),PntSet(:,2),0:0.1:15,0:0.1:15); scatter(PntSet(:,1),PntSet(:,2),'filled','CData',CData);
是不是瞬间有那味了：
示例2
PntSet1=mvnrnd([2 3],[1 0;0 2],800); PntSet2=mvnrnd([6 7],[1 0;0 2],800); PntSet3=mvnrnd([8 9],[1 0;0 1],800); PntSet=[PntSet1;PntSet2;PntSet3]; ax=gca; ax.XLim=[-3 13]; ax.YLim=[-3 13]; ax=ggplotAxes2D(ax); [~,~,XMesh,YMesh,ZMesh,colorList]=density2C(PntSet(:,1),PntSet(:,2),-2:0.1:12,-2:0.1:12); colormap(colorList) contourf(XMesh,YMesh,ZMesh,10)
以上是“Matlab怎么绘制散点密度图”这篇文章的所有内容，感谢各位的阅读！相信大家都有了一定的了解，希望分享的内容对大家有所帮助，如果还想学习更多知识，欢迎关注云搜网行业资讯频道！
