MATLAB实例：二维高斯分布图

clear
clc
% Author:  凯鲁嘎吉 - 博客园 http://www.cnblogs.com/kailugaji/
%% 加载数据
data_load=dlmread(\'./gauss_data.txt\');
% 每一类
data_1=data_load(data_load(:, end)==1, :);
data_2=data_load(data_load(:, end)==2, :);
data_3=data_load(data_load(:, end)==3, :);
data_4=data_load(data_load(:, end)==4, :);
data_5=data_load(data_load(:, end)==5, :);
%% 空间坐标范围
x1=-8:0.1:8;
x2=-10:0.1:8;
[X1, X2]=meshgrid(x1, x2);
X=[X1(:) X2(:)];

%第一类数据
mu1=[0 0]; % 均值
S1=[1 0;0 1]; % 协方差
%第二类数据
mu2=[4 4];
S2=[2 -1;-1 2];
%第三类数据
mu3=[-4 4];
S3=[2 1;1 2];
%第四类数据
mu4=[-4 -4];
S4=[2 -1;-1 2];
%第五类数据
mu5=[4 -4];
S5=[2 1;1 2];

%% 高斯概率密度函数
% 分量1
y_1=mvnpdf(X, mu1, S1);
y_1=reshape(y_1, length(x2), length(x1));
% 分量2
y_2=mvnpdf(X, mu2, S2);
y_2=reshape(y_2, length(x2), length(x1));
% 分量3
y_3=mvnpdf(X, mu3, S3);
y_3=reshape(y_3, length(x2), length(x1));
% 分量4
y_4=mvnpdf(X, mu4, S4);
y_4=reshape(y_4, length(x2), length(x1));
% 分量5
y_5=mvnpdf(X, mu5, S5);
y_5=reshape(y_5, length(x2), length(x1));
%% 作图
figure(1)
contour(x1, x2, y_1);
hold on
contour(x1, x2, y_2);
contour(x1, x2, y_3);
contour(x1, x2, y_4);
contour(x1, x2, y_5);
xlabel(\'X\');
ylabel(\'Y\');
plot(data_1(:, 1), data_1(:, 2), \'b.\', \'MarkerSize\',10 );
hold on
plot(data_2(:, 1), data_2(:, 2), \'r^\', \'MarkerSize\',4, \'MarkerFaceColor\',\'r\');
plot(data_3(:, 1), data_3(:, 2), \'ko\', \'MarkerSize\',4, \'MarkerFaceColor\',\'g\');
plot(data_4(:, 1), data_4(:, 2), \'rp\', \'MarkerSize\',4, \'MarkerFaceColor\',\'y\');
plot(data_5(:, 1), data_5(:, 2), \'mh\', \'MarkerSize\',4, \'MarkerFaceColor\',\'m\');
saveas(gcf,sprintf(\'2D_Gauss_PDF.jpg\'),\'bmp\'); %保存图片