How to color each cluster with different color ?

function cluster_dp(filename, percent)
shapeset = load(filename);
showShapeSet(shapeset);
distset = shapeset2distset(shapeset);
%dc = computeDc(distset, percent);
dc = 0.048;
fprintf('average percentage of neighbours (hard coded): %5.6f\n', percent);
fprintf('Computing Rho with gaussian kernel of radius: %12.6f\n', dc);
rhos = getLocalDensity(distset, dc);

%rho_delta = load('vc/rho_delta.txt');
%rhos = rho_delta(:, 1)';
[deltas, nneigh] = getDistanceToHigherDensity(distset, rhos);
%deltas = rho_delta(:, 2)';

showDeltas(rhos, deltas);
[min_rho, min_delta] = selectRect();
filter = (rhos > min_rho) & (deltas > min_delta);
cluster_num = sum(filter);
fprintf('rho: %f, delta: %f, number of clusters: %i \n', min_rho, min_delta, cluster_num);
ords = find(filter);
cluster = zeros(size(rhos));
color = 1;
for i = 1:size(ords, 2)
    cluster(ords(i)) = color;
    color = color + 1;
end
[sorted_rhos, rords] = sort(rhos, 'descend');
for i = 1:size(rords, 2)
    if cluster(rords(i)) == 0
        neigh_cluster = cluster(nneigh(rords(i)));
        assert(neigh_cluster ~= 0, 'neigh_cluster has not assign!');
        cluster(rords(i)) = neigh_cluster;
    end
end
showColorShape(shapeset, cluster, cluster_num, ords);

halo = cluster;
dc_filter = (distset ~= 0) & (distset < dc);
elnum = size(distset, 1);
rhos_matrix = repmat(rhos', 1, elnum);
rhos_items = repmat(rhos, elnum, 1);
rho_filter = rhos_matrix > rhos_items;
cluster_filter = repmat(cluster', 1, elnum) ~= repmat(cluster, elnum, 1);
halo_filter = dc_filter & rho_filter & cluster_filter;
bord_rhos = zeros(size(halo_filter));
bord_rhos(halo_filter) = (rhos_matrix(halo_filter) + rhos_items(halo_filter)) / 2;
r = max(bord_rhos, [], 1);
c = max(bord_rhos, [], 2);
d = [r; c'];
e = max(d, [], 1);
[row, col, v] = find(e);
cluster_rho = zeros(cluster_num);
for i = col
    if e(i) > cluster_rho(cluster(i))
        cluster_rho(cluster(i)) = e(i);
    end
end
for i = 1:elnum
    if rhos(i) < cluster_rho(cluster(i))
        halo(i) = 0;
    end
end
showElementCount(cluster, halo, cluster_num);
showHaloShape(shapeset, cluster, halo, cluster_num, ords);
end
function showElementCount(cluster, halo, cluster_num)
faa = fopen("assign.txt","w")
for i = 0:cluster_num
    halo_filter = (halo == i);
    cluster_filter = (cluster == i);
    nc = length(find(cluster_filter));
    nh = length(find(halo_filter));
    fprintf('CLUSTER: %i, ELEMENTS: %i, CORE: %i, HALO: %i\n', i, nc, nh, nc-nh);
    fprintf(faa, '%i %i %i\n',i,cl(i),halo(i));
    
end
end


function [min_rho, min_delta] = selectRect()
subplot(2,2,2);
rect = getrect
%fprintf('rect(x:%i y:%i width:%i height:%i)\n', rectangle(1), rectangle(2), rectangle(3), rectangle(4));
min_rho   = rect(1);
min_delta = rect(2);
end

function showHaloShape(shapeset, cluster, halo, cluster_num, ords)
subplot(2,2,4); 
hold on;    
cmap = colormap;
for i = 0:cluster_num
    filter = (halo == i);
    x = shapeset(:, 1)';
    y = shapeset(:, 2)';
    xx = x(filter);
    yy = y(filter);
    ic = int8(i * 32.0 / cluster_num) + 1;
    %fprintf('i: %d, cluster_element: %d\n', i, size(xx, 2));
    tt=plot(xx, yy, 'o', 'MarkerSize', 2, 'MarkerFaceColor', cmap(ic,:), 'MarkerEdgeColor', cmap(ic,:));
end
for i = 1:size(ords, 2)
    color = cluster(ords(i));
    x = shapeset(ords(i), 1);
    y = shapeset(ords(i), 2);
    ic = int8(color * 64.0 / cluster_num);
    tt=plot([x], [y], 'o', 'MarkerSize', 10, 'MarkerFaceColor', cmap(ic,:), 'MarkerEdgeColor', cmap(ic,:));
end    
text = strcat('HaloShape: ', num2str(cluster_num));
title (text, 'FontSize', 15.0);
xlabel ('x');
ylabel ('y');    
end

function showColorShape(shapeset, cluster, cluster_num, ords)
subplot(2,2,3); 
hold on;    
cmap = colormap;
color = lines(6); % Generate color values
for i = 0:cluster_num
    filter = (cluster == i);
    x = shapeset(:, 1)';
    y = shapeset(:, 2)';
    xx = x(filter);
    yy = y(filter);
    ic = int8(i * 32.0 / cluster_num) + 1;
    %fprintf('i: %d, cluster_element: %d\n', i, size(xx, 2));
    tt=plot(xx, yy, 'o', 'MarkerSize', 2, 'MarkerFaceColor', cmap(ic,:), 'MarkerEdgeColor', cmap(ic,:));
    %C = hsv(6);
    %gscatter(xx,yy,color(1:3,:))
end
for i = 1:size(ords, 2)
    color = cluster(ords(i));
    x = shapeset(ords(i), 1);
    y = shapeset(ords(i), 2);
    ic = int8(color * 64.0 / cluster_num);
    tt=plot([x], [y], 'o', 'MarkerSize', 10, 'MarkerFaceColor', cmap(ic,:), 'MarkerEdgeColor', cmap(ic,:));
    
end    
text = strcat('ColorShape: ', num2str(cluster_num));
title (text, 'FontSize', 15.0);
xlabel ('x');
ylabel ('y');    
end

function showShapeSet(shapeset)
scrsz = get(0,'ScreenSize');
figure('Position', [6 72 scrsz(3)/2. scrsz(4)/1.3]);
subplot(2,2,1); 
tt = plot(shapeset(:, 1), shapeset(:, 2), 'o', 'MarkerSize', 2, 'MarkerFaceColor', 'k', 'MarkerEdgeColor', 'k');
text = 'LoadShape';
title (text, 'FontSize', 15.0);
xlabel ('x');
ylabel ('y');       
end

function showDeltas(rhos, deltas)
subplot(2,2,2);
tt = plot(rhos(:), deltas(:), 'o', 'MarkerSize', 3, 'MarkerFaceColor', 'k', 'MarkerEdgeColor', 'k');
text = strcat('max rho: ', num2str(max(rhos)), ', delta: ', num2str(max(deltas)));
title (text, 'FontSize', 15.0);
xlabel ('rho');
ylabel ('delta');
end

Answer 1

[Image Analyst]

Very simple. Just use the function made for that. It's called gscatter().

[sam mohel]

thanks for replying , excuse me did you mean i need to add this line in the first for loop ?

C = hsv(6);
gscatter(xx,yy,Origin,C)

[Image Analyst]

I was thinking that gscatter() could replace your function entirely.

For example, see this demo:

% Clusters points at a constant radius but different angles and has kmeans find clusters.
% Clean up / initialization
clc;    % Clear the command window.
close all;  % Close all figures (except those of imtool.)
clear;  % Erase all existing variables. Or clearvars if you want.
workspace;  % Make sure the workspace panel is showing.
format long g;
format compact;
fontSize = 20;
% Make 5 groups.
numGroups = 5
pointsPerGroup = 10;
radius = 1
% Define angles where the groups will be centered at.
centerAngles = linspace(0, 330, numGroups+1)'
allAngles = [];
subplot(1, 2, 1);
% Add and plot each group to the allAngles complete data set.
for g = 1 : numGroups
    % Get angles for this one group.
    theseAngles = centerAngles(g) + 30 * rand(pointsPerGroup, 1);
    % Add these angles to the complete set.
    allAngles = [allAngles; theseAngles];	
    % Plot this one group.
    xg = cosd(theseAngles);
    yg = sind(theseAngles);
    plot(xg, yg, '.', 'MarkerSize', 20);
    hold on
end
grid on;
axis square
title('Ground Truth - The Actual Groups', 'FontSize', fontSize);
xlim([-1.1, 1.1]);
ylim([-1.1, 1.1]);
% Enlarge figure to full screen.
set(gcf, 'Units', 'Normalized', 'OuterPosition', [0, 0.04, 1, 0.96]);
drawnow;
% Now we have our data and we can begin.
% Now assume there are numGroups and figure out what group they belong to
% Cluster via kmeans() of the Statistics and Machine Learning Toolbox.
% Use 5 replicates otherwise you'll get wrong clusters for the very first run after launching MATLAB.
groupLabels = kmeans(allAngles, numGroups, 'Replicates', 5);
% Identification of clusters/groups is done.  Now plot.
x = cosd(allAngles);  % Get (x,y) coordinates of each angle.
y = sind(allAngles);
subplot(1, 2, 2);
gscatter(x, y, groupLabels);
grid on;
axis square
title('Groups Determined by kmeans()', 'FontSize', fontSize);
xlim([-1.1, 1.1]);
ylim([-1.1, 1.1]);

See how each cluster is colored with its own color using gscatter once the clusters have been determined?

[sam mohel]

thanks a lot for replying but excuse me i'm confused in kmeans and the algorithm i'm using which is dentisty peak clustering. the full code that i'm following i edited the post with it. can you please guide me where exaclty i should make the gscatter , please ?

[Image Analyst]

Attach all needed m-files with the paperclip icon. then tell us which m-file needs to be run to run your code, and if any input arguments need to be assigned in advance.

[sam mohel]

i attached all the files needed to run the code . you should run main.m file to run the code. inside in this file you will speicify the text file location which contains the points need to be cluster .. Thanks a lot for helping