Matlab散点图和直方图

Question

我有 20 个带有 x 和 y 坐标的数字数据点。我想将它们绘制在二维图中。它们将集中在 x 和 y 坐标周围。为了更好地可视化这种行为，我想在 x 轴的 2D 散点图顶部添加直方图条，并在 y 轴的 2D 图右侧添加直方图条，这样它们不会干扰轴标签.现在，我的 20 个数字点实际上是两组 10 个，我希望两组都用不同的颜色绘制。像这样的东西： python plot

我该怎么做？

更新：

FWHM11Avg    = [3.88,3.43,3.16,3.22,3.73,2.43,2.88,3.01,3.59,2.17];
FWHM11Med    = [4.4,3.1,3,3.15,3.9,2,3.00,2.85,3.85,2.2];
FWHM12Avg    = [3.50,2.30,2.97,2.97,2.98,2.28,2.94,2.36,3.51,1.7];
FWHM12Med    = [3.3,2.1,2.9,2.8,2.9,2.1,2.8,2.30,3.5,1.7];

minx = min([FWHM11Avg; FWHM11Med]);
maxx = max([FWHM11Avg; FWHM11Med]);
miny = min([FWHM12Avg; FWHM12Med]);
maxy = max([FWHM12Avg; FWHM12Med]);

% make figure
figure(1)
clf
% first subplot -- y-data histc
ah1 = subplot(2, 2,  1);
y_bins = 1.5:.25:4.5;
n = hist(FWHM12Avg, y_bins);
bar(y_bins, n, 'vertical', 'on')
hold on
hist(FWHM12Med, y_bins)
bar(y_bins, n, 'vertical', 'on')
% x-data histc
ah2 = subplot(2, 2, 4);
x_bins = 1.5:.25:4.5;
n = hist(FWHM11Avg, x_bins);
bar(x_bins, n, 'horizontal', 'on')
hold on
n = hist(FWHM11Med, x_bins);
bar(x_bins, n, 'horizontal', 'on')
% scatterplot
ah3 = subplot(2, 2, 2);
hold on
scatter(FWHM11Avg, FWHM11Med)
scatter(FWHM12Avg, FWHM12Med)

% link axes, adjust histc orientation
linkaxes([ah1, ah3], 'y')
linkaxes([ah3, ah2], 'x')
set(ah3,'XLim',[minx, maxx]);
set(ah3,'YLim',[miny, maxy]);
ah1.Box = 'off';
ah1.View = [180, -90];
ah1.Visible = 'off';
ah2.Visible = 'off';
ah2.Box = 'off';
ah2.View = [0, -90];

此外，似乎没有可用于将数值轴添加到直方图中以查看条形图中有多少点的选项 - 至少在文档中我没有看到任何选项。是这样吗？

对上述语法应用建议的第二次更新：

FWHM11Avg    = [3.88,3.43,3.16,3.22,3.73,2.43,2.88,3.01,3.59,2.17];
FWHM11Med    = [4.4,3.1,3,3.15,3.9,2,3.00,2.85,3.85,2.2];
FWHM12Avg    = [3.50,2.30,2.97,2.97,2.98,2.28,2.94,2.36,3.51,1.7];
FWHM12Med    = [3.3,2.1,2.9,2.8,2.9,2.1,2.8,2.30,3.5,1.7];

minx = min([FWHM11Avg; FWHM11Med]);
maxx = max([FWHM11Avg; FWHM11Med]);
miny = min([FWHM12Avg; FWHM12Med]);
maxy = max([FWHM12Avg; FWHM12Med]);

% make figure
figure(1)
clf
% first subplot -- y-data histc
ah1 = subplot(2, 2,  1);
y_bins = 1.5:.25:4.5;
n = hist(FWHM12Avg, y_bins);
bar(y_bins, n, 'vertical', 'on')
hold on
hist(FWHM12Med, y_bins)
bar(y_bins, n, 'vertical', 'on')
% x-data histc
ah2 = subplot(2, 2, 4);
x_bins = 1.5:.25:4.5;
n = hist(FWHM11Avg, x_bins);
bar(x_bins, n, 'horizontal', 'on')
hold on
n = hist(FWHM11Med, x_bins);
bar(x_bins, n, 'horizontal', 'on')
% scatterplot
ah3 = subplot(2, 2, 2);
hold on
scatter(FWHM11Avg, FWHM11Med)
scatter(FWHM12Avg, FWHM12Med)

% link axes, adjust histc orientation
linkaxes([ah1, ah3], 'y')
linkaxes([ah3, ah2], 'x')
set(ah3,'XLim',[minx, maxx]);
set(ah3,'YLim',[miny, maxy]);
set(ah1,'Box','off');
set(ah1,'View',[180, -90]);
set(ah1,'Visible','off');
set(ah2,'Visible','off');
set(ah2,'Box','off');
set(ah2,'View',[0, -90]);

Answer 1

请在询问之前进行研究。 Matlab scatterhist 中有一个函数可以做到这一点

x0 = 6.1;
y0 = 3.2;
n = 50;
r = rand(n ,1 );
theta = 2*pi*rand(n, 1);
x = x0 + r.*cos(theta);
y = y0 + r.*sin(theta);
scatterhist(x,y, 'Direction','out', 'Location', 'NorthEast')

编辑：使用您提供的数据。这是你想要的吗？

FWHM11Avg    = [3.88,3.43,3.16,3.22,3.73,2.43,2.88,3.01,3.59,2.17];
FWHM11Med    = [4.4,3.1,3,3.15,3.9,2,3.00,2.85,3.85,2.2];
FWHM12Avg    = [3.50,2.30,2.97,2.97,2.98,2.28,2.94,2.36,3.51,1.7];
FWHM12Med    = [3.3,2.1,2.9,2.8,2.9,2.1,2.8,2.30,3.5,1.7];

% make figure
figure(1)
clf

FWHM11Avg = FWHM11Avg(:);
FWHM11Med = FWHM11Med(:);
FWHM12Avg = FWHM12Avg(:);
FWHM12Med = FWHM12Med(:);

minX = min([FWHM11Avg; FWHM12Avg]);
maxX = max([FWHM11Avg; FWHM12Avg]);
minY = min([FWHM11Med; FWHM12Med]);
maxY = max([FWHM11Med; FWHM12Med]);

resX = 0.25;
resY = 0.25;

nBinsX = ceil((maxX - minX) / resX);
nBinsY = ceil((maxY - minY) / resY);

label = vertcat( ...
            num2cell(repmat('FWHM11', size(FWHM11Avg)),2), ...
            num2cell(repmat('FWHM12', size(FWHM11Avg)),2));

Avg = vertcat(FWHM11Avg, FWHM12Avg);
Med = vertcat(FWHM11Med, FWHM12Med);

% scatterplot
scatterhist(Avg, Med, 'Group', label, 'Direction','out', ...
    'Location', 'NorthEast', 'NBins', [nBinsX, nBinsY])

Answer 2

这是我最近一直在使用的东西：

% generate some random data
mu = [1 2];
sigma = [1 0.5; 0.5 2];
R = chol(sigma);
my_data1 = repmat(mu,100,1) + randn(100,2)*R;
mu = [2 1];
sigma = [3 -0.5; -0.5 2];
R = chol(sigma);
my_data2 = repmat(mu,100,1) + randn(100,2)*R;

% find limits
minx = min([my_data1(:, 1); my_data2(:, 1)]);
maxx = max([my_data1(:, 1); my_data2(:, 1)]);
miny = min([my_data1(:, 2); my_data2(:, 2)]);
maxy = max([my_data1(:, 2); my_data2(:, 2)]);

% make figure
figure(1)
clf
% first subplot -- y-data histogram
ah1 = subplot(2, 2,  1);
histogram(my_data1(:, 2), 'Orientation','horizontal', 'Normalization', 'probability', 'BinWidth', 0.5)
hold on
histogram(my_data2(:, 2), 'Orientation','horizontal', 'Normalization', 'probability', 'BinWidth', 0.5)
% x-data histogram
ah2 = subplot(2, 2, 4);
histogram(my_data1(:, 1), 'Normalization', 'probability', 'BinWidth', 0.5)
hold on
histogram(my_data2(:, 1), 'Normalization', 'probability', 'BinWidth', 0.5)
% scatterplot
ah3 = subplot(2, 2, 2);
hold on
scatter(my_data1(:, 1), my_data1(:, 2))
scatter(my_data2(:, 1), my_data2(:, 2))

% link axes, adjust histogram orientation
linkaxes([ah1, ah3], 'y')
linkaxes([ah3, ah2], 'x')
ah3.XLim = [minx, maxx];
ah3.YLim = [miny, maxy];
ah1.Box = 'off';
ah1.View = [180, -90];
ah1.Visible = 'off';
ah2.Visible = 'off';
ah2.Box = 'off';
ah2.View = [0, -90];

制作这个情节 此代码假定使用最新版本的 MATLAB（我使用 2014b），但可以使用旧的直方图函数（hist、histc）和图形对象的 set(..) 语法轻松调整。