# matlab pairplot

**Repository Path**: slandarer/matlab-pairplot

## Basic Information

- **Project Name**: matlab pairplot
- **Description**: SPairplot Create and customize pairplot (scatter plot matrix | 散点图矩阵)
- **Primary Language**: Unknown
- **License**: BSD-3-Clause
- **Default Branch**: master
- **Homepage**: None
- **GVP Project**: No

## Statistics

- **Stars**: 0
- **Forks**: 0
- **Created**: 2026-06-18
- **Last Updated**: 2026-06-18

## Categories & Tags

**Categories**: Uncategorized

**Tags**: None

## README

# pairplot (scatter plot matrix | 散点图矩阵)
SPairplot Create and customize pairplot (scatter plot matrix | 散点图矩阵)

#### mathworks fileexchange 链接(引用格式)
Zhaoxu Liu / slandarer (2026). pairplot (scatter plot matrix | 散点图矩阵) (https://www.mathworks.com/matlabcentral/fileexchange/184069-pairplot-scatter-plot-matrix), MATLAB Central File Exchange. Retrieved June 18, 2026.

## Cover
![](gallery/demo5_1.png)

## Basic usage : one matrix input
```matlab
% Load Fisher's iris dataset (150 samples, 4 features, 3 species)
% 加载鸢尾花数据集（150个样本，4个特征，3个品种）
fisher = load("fisheriris.mat");
X = fisher.meas;            % 150×4 feature matrix / 特征矩阵
group = fisher.species;     % Species labels / 品种标签
label = {'sepal-length', 'sepal-width', 'petal-length', 'petal-width'};

% Create pairplot object with customized visualization
% 创建散点图矩阵对象，自定义可视化风格
SP = SPairplot(X, 'Group', group, 'DiagType', 12, 'UpperType', 11, 'LowerType', 13);
SP.draw();

% Set X-labels and Y-labels
% 设置 X 轴标签和 Y 轴标签
SP.setXLabelString(label);
SP.setYLabelString(label);
```
![](gallery/demo1_12_11_13.png)

![](gallery/demo1_11_7_10.png)

![](gallery/demo1_6_9_6.png)

![](gallery/demo1_1_9_2.png)

## DiagType, BottomType and RightType
![](DiagType.png)

## UpperType and LowerType
![](LowerType.png)

## Basic usage : Two matrix inputs
```matlab
% Generate synthetic data with three groups (150 samples, 6 features total)
% 生成包含三个分组的合成数据(150个样本，共6个特征)
P1 = mvnrnd([0,20,0,10,8,7], eye(6).*6, 50);
P2 = mvnrnd([10,5,15,0,4,2], eye(6).*8, 50);
P3 = mvnrnd([10,15,0,0,2,3], eye(6).*[3,9,2,1,4,4], 50);
G  = [ones(50,1)*1; ones(50,1)*2; ones(50,1)*3];  % Group labels / 分组标签

% Split into X (first 4 variables) and Y (last 2 variables)
% 拆分为 X(前4个变量)和 Y(后2个变量)
XY = [P1; P2; P3];
X = XY(:, 1:4);   
Y = XY(:, 5:6);   

% Create pairplot with two variable sets (X vs Y)
% 创建双变量集的散点图矩阵（X 与 Y 的对比）
% Note: When X and Y are both provided, only LowerType (off-diagonal below)
% is effective. Upper triangle and diagonal are automatically disabled.
% 注意：当同时输入 X 和 Y 时，仅 LowerType(下三角区域)生效，
% 上三角和对角线区域自动禁用。
SP = SPairplot(X, Y, 'Group', G, 'LowerType', 9);
SP.draw();
```
![](gallery/demo2.png)


## Properties setting for subplots
```matlab
fisher = load("fisheriris.mat");
X = fisher.meas;            
group = fisher.species;     
label = {'sepal-length', 'sepal-width', 'petal-length', 'petal-width'};

SP = SPairplot(X, 'Group', group, 'DiagType', 1, 'UpperType', 9, 'LowerType', 2);

% set CData
SP.CData = [119,69,133; 56,108,155; 33,160,122] ./ 255;
SP.draw();

% Set X-labels and Y-labels
SP.setXLabelString(label);
SP.setYLabelString(label);


% Customize subplot appearance
% 自定义子图外观
SP.setAxes('Box','off', 'LineWidth',1.5, 'XGrid','on', 'YGrid','on')
SP.setXLabel('FontWeight','bold', 'Color',[0,0,.8])
SP.setYLabel('FontWeight','bold', 'Color',[.8,0,0])
```
![](gallery/demo3.png)

## Display legend
```matlab
fisher = load("fisheriris.mat");
X = fisher.meas;            
group = fisher.species; 
label = {'sepal-length', 'sepal-width', 'petal-length', 'petal-width'};

SP = SPairplot(X, 'Group', group, 'DiagType', 10, 'UpperType', 9, 'LowerType', 2);
% set CData
SP.CData = [211, 43, 43;  61, 96,137; 249,206, 61;  76,103, 86;  80, 80, 80]./255;

SP.Padding = [.08, .08, .2, .04];
SP.draw();

% Set X-labels and Y-labels
SP.setXLabelString(label);
SP.setYLabelString(label);

legend(SP.axMat{4, 4}, SP.GroupLabel, 'FontSize',17, 'Position',[.82, .88, .12, .08])
```
![](gallery/demo4.png)

## Marginal plot : one matrix input
```matlab
% Load Fisher's iris dataset (150 samples, 4 features, 3 species)
% 加载鸢尾花数据集（150个样本，4个特征，3个品种）
fisher = load("fisheriris.mat");
X = fisher.meas;            % 150×4 feature matrix / 特征矩阵
group = fisher.species;     % Species labels / 品种标签
label = {'sepal-length', 'sepal-width', 'petal-length', 'petal-width'};

% Create pairplot object with customized visualization
% 创建散点图矩阵对象，自定义可视化风格
SP = SPairplot(X, 'Group', group);
SP.DiagType = 14;
SP.UpperType = 11;
SP.LowerType = 14;
SP.BottomType = 12;
SP.RightType = 11;
SP.CornerType = 1;
SP.draw();

% Set X-labels and Y-labels
% 设置 X 轴标签和 Y 轴标签
SP.setXLabelString(label);
SP.setYLabelString(label);
```
![](gallery/demo5_1.png)
![](gallery/demo5_2.png)

## Marginal plot : Two matrix inputs
```matlab
% Generate synthetic data with three groups (150 samples, 6 features total)
% 生成包含三个分组的合成数据(150个样本，共6个特征)
P1 = mvnrnd([0,20,0,10,8,7], eye(6).*6, 50);
P2 = mvnrnd([10,5,15,0,4,2], eye(6).*8, 50);
P3 = mvnrnd([10,15,0,0,2,3], eye(6).*[3,9,2,1,4,4], 50);
G  = [ones(50,1)*1; ones(50,1)*2; ones(50,1)*3];  % Group labels / 分组标签

% Split into X (first 4 variables) and Y (last 2 variables)
% 拆分为 X(前4个变量)和 Y(后2个变量)
XY = [P1; P2; P3];
X = XY(:, 1:4);   
Y = XY(:, 5:6);   

% Create pairplot with two variable sets (X vs Y)
% 创建双变量集的散点图矩阵（X 与 Y 的对比）
% Note: When X and Y are both provided, only LowerType (off-diagonal below)
% is effective. Upper triangle and diagonal are automatically disabled.
% 注意：当同时输入 X 和 Y 时，仅 LowerType(下三角区域)生效，
% 上三角和对角线区域自动禁用。
fig = figure('Units','normalized', 'Position',[.1,.2,.7,.65]);
SP = SPairplot(fig, X, Y, 'Group', G);
SP.GroupLabel = {'G1','G2','G3'};
SP.LowerType = 7;
SP.BottomType = 12;
SP.RightType = 14;
SP.CornerType = 1;
SP.draw();


SP.setXLabelString({'X1', 'X2', 'X3', 'X4'});
SP.setYLabelString({'Y1', 'Y2'});
```
![](gallery/demo6_1.png)