You can achieve the above 3 implementations using the scatter, imagesc and contourf functions respectively. You can have a look at each of the implementation below:
- Colour spots using scatter
% Example data
X = randi(100, [100, 1]);
Y = randi(50, [100, 1]);
Z = linspace(100, 1, 100);
% Create the scatter plot
figure;
scatter(X, Y, 100, Z, 'filled'); % Use Z for color
% Set colormap from red to green
colormap(jet); % Or use other colormaps like 'hot', 'cool', etc.
colorbar; % Show color scale
- Using imagesc for heatmap: This approach bins your data into a grid.
% Define grid size
x_edges = linspace(min(X), max(X), 50);
y_edges = linspace(min(Y), max(Y), 25);
% Create a 2D histogram
heatmap_data = zeros(length(y_edges)-1, length(x_edges)-1);
for i = 1:length(X)
x_idx = find(X(i) >= x_edges, 1, 'last');
y_idx = find(Y(i) >= y_edges, 1, 'last');
if x_idx < length(x_edges) && y_idx < length(y_edges)
heatmap_data(y_idx, x_idx) = heatmap_data(y_idx, x_idx) + Z(i);
end
end
% Plot the heatmap
figure;
imagesc(x_edges, y_edges, heatmap_data);
set(gca, 'YDir', 'normal'); % Correct the y-axis direction
colormap(jet); % Or any other colormap
colorbar;
- Segmentation for contourf
% Create a grid for contour
[X_grid, Y_grid] = meshgrid(linspace(min(X), max(X), 100), linspace(min(Y), max(Y), 100));
% Interpolate Z values on the grid
Z_grid = griddata(X, Y, Z, X_grid, Y_grid, 'cubic');
% Plot the contour map
figure;
contourf(X_grid, Y_grid, Z_grid, 10, 'LineColor', 'none'); % 10 levels
colormap(jet);
colorbar;
You can adjust the number of levels in contourf to change how many segments are displayed.
I hope it helps.
Thanks
