matthiasm@8: % Consider matching sources to detections
matthiasm@8: 
matthiasm@8: %  s1 d2  
matthiasm@8: %         s2 d3
matthiasm@8: %  d1
matthiasm@8: 
matthiasm@8: %a  = bipartiteMatchingHungarian([52;0.01])
matthiasm@8: 
matthiasm@8: % sources(:,i) = [x y] coords
matthiasm@8: sources = [0.1 0.7; 0.6 0.4]';
matthiasm@8: detections = [0.2 0.2; 0.2 0.8; 0.7 0.1]';
matthiasm@8: dst = sqdist(sources, detections);
matthiasm@8: 
matthiasm@8: % a = [2 3] which means s1-d2, s2-d3
matthiasm@8: a = bipartiteMatchingHungarian(dst);
matthiasm@8: a2 = bipartiteMatchingIntProg(dst);
matthiasm@8: assert(isequal(a(:),a2(:)))
matthiasm@8: 
matthiasm@8: 
matthiasm@8: figure(1); clf
matthiasm@8: bipartiteMatchingDemoPlot(sources, detections, a)
matthiasm@8: 
matthiasm@8: 
matthiasm@8: 
matthiasm@8: 
matthiasm@8: %%%% Flip roles of sources and detections
matthiasm@8: 
matthiasm@8: %dst  = dst';
matthiasm@8: dst = sqdist(detections, sources);
matthiasm@8: % a = [0 1 2] which means d1-0, d2-s1, d3-s2
matthiasm@8: a = bipartiteMatchingHungarian(dst);
matthiasm@8: 
matthiasm@8: a2 = bipartiteMatchingIntProg(dst);
matthiasm@8: assert(isequal(a(:),a2(:)))
matthiasm@8: 
matthiasm@8: figure(2); clf
matthiasm@8: bipartiteMatchingDemoPlot(detections, sources, a) % swapped args
matthiasm@8: 
matthiasm@8: 
matthiasm@8: 
matthiasm@8: 
matthiasm@8: %%%%%%%%%% Move s1 nearer to d1
matthiasm@8: %  d2  
matthiasm@8: %         s2 d3
matthiasm@8: %  s1 d1
matthiasm@8: 
matthiasm@8: sources = [0.1 0.3; 0.6 0.4]';
matthiasm@8: detections = [0.2 0.2; 0.2 0.8; 0.7 0.1]';
matthiasm@8: dst = sqdist(sources, detections);
matthiasm@8: 
matthiasm@8: % a = [2 3] which means s1-d2, s2-d3
matthiasm@8: a = bipartiteMatchingHungarian(dst);
matthiasm@8: [a2, ass] = bipartiteMatchingIntProg(dst);
matthiasm@8: assert(isequal(a(:),a2(:)))
matthiasm@8: 
matthiasm@8: 
matthiasm@8: figure(3); clf
matthiasm@8: bipartiteMatchingDemoPlot(sources, detections, a)
matthiasm@8: 
matthiasm@8: 
matthiasm@8: 
matthiasm@8: %%%%%%%%%%
matthiasm@8: 
matthiasm@8: % Use random points
matthiasm@8: 
matthiasm@8: % Generate 2D data from a mixture of 2 Gaussians (from netlab demgmm1)
matthiasm@8: randn('state', 0); rand('state', 0);
matthiasm@8: gmix = gmm(2, 2, 'spherical');
matthiasm@8: ndat1 = 10; ndat2 = 10; ndata = ndat1+ndat2;
matthiasm@8: %gmix.centres =  [0.3 0.3; 0.7 0.7]; 
matthiasm@8: %gmix.covars = [0.01 0.01];
matthiasm@8: gmix.centres =  [0.5 0.5; 0.5 0.5];
matthiasm@8: gmix.covars = [0.1 0.01];
matthiasm@8: [x, label] = gmmsamp(gmix, ndata);
matthiasm@8: 
matthiasm@8: ndx = find(label==1);
matthiasm@8: sources = x(ndx,:)';
matthiasm@8: ndx = find(label==2);
matthiasm@8: detections = x(ndx,:)';
matthiasm@8: dst = sqdist(sources, detections);
matthiasm@8: 
matthiasm@8: [a, ass] = bipartiteMatchingIntProg(dst);
matthiasm@8: [a2] = bipartiteMatchingHungarian(dst);
matthiasm@8: assert(isequal(a(:), a2(:)))
matthiasm@8: 
matthiasm@8: figure(4); clf
matthiasm@8: bipartiteMatchingDemoPlot(sources, detections, a)
matthiasm@8: 
matthiasm@8: % only match 80% of points
matthiasm@8: p1 = size(sources, 2);
matthiasm@8: p2 = size(detections, 2);
matthiasm@8: nmatch = ceil(0.8*min(p1,p2));
matthiasm@8: a2 = bipartiteMatchingIntProg(dst, nmatch);
matthiasm@8: figure(5); clf
matthiasm@8: bipartiteMatchingDemoPlot(sources, detections, a2)
matthiasm@8: 
matthiasm@8: 
matthiasm@8: %%% swap roles
matthiasm@8: 
matthiasm@8: ndx = find(label==2);
matthiasm@8: sources = x(ndx,:)';
matthiasm@8: ndx = find(label==1);
matthiasm@8: detections = x(ndx,:)';
matthiasm@8: dst = sqdist(sources, detections);
matthiasm@8: 
matthiasm@8: % only match 80% of points
matthiasm@8: p1 = size(sources, 2);
matthiasm@8: p2 = size(detections, 2);
matthiasm@8: nmatch = ceil(0.8*min(p1,p2));
matthiasm@8: a2 = bipartiteMatchingIntProg(dst, nmatch);
matthiasm@8: figure(6); clf
matthiasm@8: bipartiteMatchingDemoPlot(sources, detections, a2)