function batch_3_Spiral_3D%% Clustering Through Ranking On Manifolds% Version 0.2%% Copyright by Markus Breitenbach and Gregory Z. Grudic% This code is for your personal and research use only.%% http://www.cs.colorado.edu/~grudic/% http://ucsu.colorado.edu/~breitenm/%% This software is provided "as is," without warranty of any kind, express% or implied.  In no event shall the authors be held liable% for any direct, indirect, incidental, special or consequential damages% arising out of the use of or inability to use this software.%% Generate some Dataclose alldeg = 0:0.05:2*pi;rad_min = 0.95;rad_max = 1.0;X1 = zeros(length(deg),3);for i=1:length(deg)    r = rad_min + rand(1,1)*(rad_max-rad_min);    X1(i,1) = r * cos(deg(i));    X1(i,2) = r * sin(deg(i));    X1(i,3) = (i/length(deg));endX2 = zeros(length(deg),3);for i=1:length(deg)    r = rad_min + rand(1,1)*(rad_max-rad_min);    X2(i,1) = r * cos(deg(i) + (2 * pi/3));    X2(i,2) = r * sin(deg(i) + (2 * pi/3));    X2(i,3) = (i/length(deg));endX3 = zeros(length(deg),3);for i=1:length(deg)    r = rad_min + rand(1,1)*(rad_max-rad_min);    X3(i,1) = r * cos(deg(i) + (4 * pi/3));    X3(i,2) = r * sin(deg(i) + (4 * pi/3));    X3(i,3) = (i/length(deg));end% plot the original datafigure;plot3(X1(:,1),X1(:,2),X1(:,3),'r+');hold onplot3(X2(:,1),X2(:,2),X2(:,3),'g*');plot3(X3(:,1),X3(:,2),X3(:,3),'bs');hold offpause(1); % give matlab a chance to plotX = [X1;X2;X3];% Now lets cluster the data[num_ex,dim] = size(X);lrn_par = Set_Default_Learning_Paramters;% distance paramterslrn_par.DST_TYPE = 1; % 1 for Euclidean, 2 for dot% Optimization for both ALPHA and SIGMA togetherlrn_par.OPT_S_A = 1; % set to 1 to optimize for both alpha and sigma%lrn_par.my_alpha = 0.99;%lrn_par.my_sigma= 0.039;%lrn_par.Cluster_Search = 3;lrn_par.Cluster_Search = [2,3,4,5]; % This defines the clusters to be evaluated%Clustering Examplemodel_cluster = LG_Cluster(X,lrn_par);%[un_class] = Classify_New_Data(X,model_cluster);colors=['r+';'go';'b^';'y*';'cs'];figurehold on;for i=1:num_ex    ii = find(model_cluster.Y(i,:)>0);    plot3(X(i,1),X(i,2),X(i,3), colors(ii(1),:) );end;return;figure;ind_1 = model_cluster.Class_Outlier(1).ind;plot3(X(ind_1,1),X(ind_1,2),X(ind_1,3),'r+');hold onind_2 = model_cluster.Class_Outlier(2).ind;plot3(X(ind_2,1),X(ind_2,2),X(ind_2,3),'go');ind_3 = model_cluster.Class_Outlier(3).ind;plot3(X(ind_3,1),X(ind_3,2),X(ind_3,3),'b^');xlabel('x');ylabel('y');zlabel('z');hold offt99 = 0;t0 = 0;