% 生成示例数据(替换为你的数据)
rng(42); % 固定随机种子
X = randn(1500, 1);
Y = 0.6*X + randn(size(X));
% 计算每个数据点的概率密度
data_points = [X, Y];
bandwidth = 0.4; % 带宽参数
density = ksdensity(data_points, data_points, 'Bandwidth', bandwidth);
% 执行密度归一化(核心修改部分)
density_normalized = (density - min(density)) / (max(density) - min(density));
% 创建带密度编码的散点图
figure;
scatter(X, Y, 25, density_normalized, 'filled'); % 25控制点大小
% 图形修饰
colormap(jet(256)); % 使用彩虹色系
c = colorbar;
c.Label.String = '归一化密度'; % 设置颜色条标签
caxis([0 1]); % 强制设置色带范围为[0,1]
axis tight;
grid on;
xlabel('X坐标');
ylabel('Y坐标');
title('归一化密度编码散点图');
% 验证归一化结果(可选)
disp(['原始密度范围: [', num2str(min(density)), ', ', num2str(max(density)), ']'])
disp(['归一化后范围: [', num2str(min(density_normalized)), ', ', num2str(max(density_normalized)), ']'])