Difference between revisions of "User:Zeracles/Starmap/Minimal Spanning Tree"
< User:Zeracles | Starmap
Jump to navigation
Jump to search
(Boruvka's algorithm is faster, at least the way I've done it) |
m (link) |
||
Line 1: | Line 1: | ||
− | I originally coded up [[wikipedia:Prim's_algorithm|Jarnik/Prim's algorithm]]. In the process of optimising it, I unwittingly reinvented [[wikipedia:Bor%C5%AFvka%27s_algorithm|Boruvka's algorithm]], which handles large numbers of input points better, at least the way I've done it. | + | I originally coded up [[wikipedia:Prim's_algorithm|Jarnik/Prim's algorithm]]. In the process of optimising it, I unwittingly reinvented [[wikipedia:Bor%C5%AFvka%27s_algorithm|Boruvka's algorithm]], which handles large numbers of input points better, at least the way I've done it. Demonstration [http://www.star-control.com/forum/index.php/topic,1660.msg35209.html#msg35209 here]. |
==Boruvka's Algorithm== | ==Boruvka's Algorithm== | ||
Also downloadable [http://www.physics.usyd.edu.au/~asmith/files/sc1/MST_Boruvka.m here] | Also downloadable [http://www.physics.usyd.edu.au/~asmith/files/sc1/MST_Boruvka.m here] |
Revision as of 16:52, 19 February 2010
I originally coded up Jarnik/Prim's algorithm. In the process of optimising it, I unwittingly reinvented Boruvka's algorithm, which handles large numbers of input points better, at least the way I've done it. Demonstration here.
Boruvka's Algorithm
Also downloadable here
% minimal spannng tree in matlab % Boruvka's algorithm (independently invented by yours truly) % see http://www.star-control.com/forum/index.php/topic,1660 % by Anthony Smith (Zeracles) % astroant@hotmail.com % if only after an MST, leave separation=pruning=0 load('inputpositions') localcount=8; separation=0; separationlength=0.03; pruning=0; prunesteps=1; % how many times to have a go at the tree prunelevel=10; % length of branch to cut each time % detect input properties and set up index sizeinputpositions=size(inputpositions); lengthinputpositions=sizeinputpositions(1); dimensions=sizeinputpositions(2); index=transpose(linspace(1,lengthinputpositions,lengthinputpositions)); inputpositionxs=inputpositions(:,1); inputpositionys=inputpositions(:,2); if dimensions>2 inputpositionzs=inputpositions(:,3); end % initialise search parameters minx=min(inputpositionxs); maxx=max(inputpositionxs); xextent=minx*maxx; miny=min(inputpositionys); maxy=max(inputpositionys); yextent=miny*maxy; if dimensions>2 minz=min(inputpositionzs); maxz=max(inputpositionzs); zextent=minz*maxz; end if dimensions==2 measure=xextent*yextent; localmeasure=measure/lengthinputpositions; searchincrement=((localcount*localmeasure)/pi)^(1/2); end if dimensions==3 measure=xextent*yextent*zextent; localmeasure=measure/lengthinputpositions; searchincrement=((localcount*localmeasure)/(4/3)/pi)^(1/3); end treenumber=index; numbertrees=length(unique(treenumber)); branches=[]; searchfactor=1; % setting this to zero can lead to infinite loop if this is scaled multiplicatively searchfactors=zeros(lengthinputpositions,1); while numbertrees>1 % each input point is treated as a separate tree, and we join them together until we only have one tree searchfactor=2*searchfactor; % calculate interpoint distances for ``close" points, with ``close" defined by this variable while min(searchfactors)<searchfactor % searchfactors stores the searchfactors searched for each existing tree tree=treenumber(min(find(searchfactors<(searchfactor)))); % choose a tree to search which has been searched with the smallest distance so far treesearched=0; while treesearched==0 % while we're not yet done looking around the nodes of this tree for links maskvector=treenumber==tree; treeindices=find(maskvector); lengthtreepositions=sum(maskvector); remainingpositionxs=inputpositionxs(find(maskvector==0)); remainingpositionys=inputpositionys(find(maskvector==0)); if dimensions>2 remainingpositionzs=inputpositionzs(find(maskvector==0)); end remainingpositionindices=index(find(maskvector==0)); mindistances=[]; for i=linspace(1,lengthtreepositions,lengthtreepositions) % search around each of the tree positions for remainingpositions % retrieve coordinates of a tree position treepositionx=inputpositions(treeindices(i),1); treepositiony=inputpositions(treeindices(i),2); if dimensions>2 treepositionz=inputpositions(treeindices(i),3); end treeindex=treeindices(i); % search for remainingpositions boxradius=searchfactor*searchincrement; boxminx=treepositionx-boxradius; boxmaxx=treepositionx+boxradius; boxminy=treepositiony-boxradius; boxmaxy=treepositiony+boxradius; if dimensions>2 boxminz=treepositionz-boxradius; boxmaxz=treepositionz+boxradius; end if dimensions==2 closerremainingmask=(boxminx<=remainingpositionxs).*(remainingpositionxs<=boxmaxx).*(boxminy<=remainingpositionys).*(remainingpositionys<=boxmaxy); end if dimensions==3 closerremainingmask=(boxminx<=remainingpositionxs).*(remainingpositionxs<=boxmaxx).*(boxminy<=remainingpositionys).*(remainingpositionys<=boxmaxy).*(boxminz<=remainingpositionzs).*(remainingpositionzs<=boxmaxz); end mindistancecandidates=[]; mindistancecandidateindices=[]; if sum(closerremainingmask)>0 % if there are remainingpositions inside the box, calculate the actual distances to them for k=transpose(find(closerremainingmask==1)); branchcandidatex=remainingpositionxs(k); branchcandidatey=remainingpositionys(k); if dimensions>2 branchcandidatez=remainingpositionzs(k); end branchcandidateindex=remainingpositionindices(k); % set up to remember the index of each prospective link destination if dimensions==2 mindistancecandidate=((branchcandidatex-treepositionx).^2+(branchcandidatey-treepositiony).^2).^(1/2); end if dimensions==3 mindistancecandidate=((branchcandidatex-treepositionx).^2+(branchcandidatey-treepositiony).^2+(branchcandidatez-treepositionz).^2).^(1/2); end if mindistancecandidate<=boxradius mindistancecandidates=[mindistancecandidates;mindistancecandidate]; mindistancecandidateindices=[mindistancecandidateindices;branchcandidateindex]; end end end if numel(mindistancecandidates)>0 % minimum distance from this position on the tree mindistance=[min(mindistancecandidates),treeindex,mindistancecandidateindices(find(mindistancecandidates==min(mindistancecandidates)))]; % minimum distances carry the indices of the prospective link destination mindistances=[mindistances;mindistance]; end end if numel(mindistances)==0 searchfactors(maskvector)=searchfactor; treesearched=1; end if numel(mindistances)>0 branchdistance=min(mindistances(:,1)); branchindex=find(branchdistance==mindistances(:,1)); numberbranchcandidates=numel(branchindex); if numberbranchcandidates>1 % if there's a tie for minimum length branchindex=branchindex(ceil(numberbranchcandidates*rand(1))); end % add this branch to the tree branch=mindistances(branchindex,:); branches=[branches;branch]; % join the two trees together targettree=treenumber(branch(3)); % need to update the treenumber variable, which remembers which points belong to which trees treenumber(find(treenumber==targettree))=tree; numbertrees=numbertrees-1; % so that we are one step closer to finishing end end end end % do custom stuff with this tree % separation - remove all branches above a certain length if separation==1 separationmask=(branches(:,1))<=separationlength; branches=branches(find(separationmask),:); end % pruning - remove wandering branches if pruning==1 degrees=[]; for i=linspace(1,lengthinputpositions,lengthinputpositions) degree=(sum((branches(:,2))==i))+(sum((branches(:,3))==i)); degrees=[degrees;degree]; end while prunesteps>0 protectednodes=index(find(degrees>2)); tempprunelevel=prunelevel; while tempprunelevel>0 ends=index(find(degrees==1)); % find branch end nodes for i=transpose(ends) if sum(i==protectednodes)==0 if (degrees(i))>0 deletemask=((branches(:,2))==i)+((branches(:,3))==i); cutbranch=branches(find(deletemask),:); branches=branches(find(deletemask==0),:); degrees(cutbranch(2))=(degrees(cutbranch(2)))-1; degrees(cutbranch(3))=(degrees(cutbranch(3)))-1; end end end tempprunelevel=tempprunelevel-1; end prunesteps=prunesteps-1; end end save('branches','branches') % for plotting sizebranches=size(branches); numberofbranches=sizebranches(1); figure hold on box on if dimensions==2 plot(inputpositions(:,1),inputpositions(:,2),'k.') end if dimensions==3 plot3(inputpositions(:,1),inputpositions(:,2),inputpositions(:,3),'k.') end for i=linspace(1,numberofbranches,numberofbranches) if dimensions==2 startindex=branches(i,2); finishindex=branches(i,3); startx=inputpositions(startindex,1); starty=inputpositions(startindex,2); finishx=inputpositions(finishindex,1); finishy=inputpositions(finishindex,2); line([startx;finishx],[starty;finishy],'Color','k') end if dimensions==3 startindex=branches(i,2); finishindex=branches(i,3); startx=inputpositions(startindex,1); starty=inputpositions(startindex,2); startz=inputpositions(startindex,3); finishx=inputpositions(finishindex,1); finishy=inputpositions(finishindex,2); finishz=inputpositions(finishindex,3); line([startx;finishx],[starty;finishy],[startz;finishz],'Color','k') end end
Jarnik/Prim's Algorithm
Also downloadable here
% minimal spannng tree in matlab % Jarnik/Prim's algorithm - runs pretty slowly for any more than 50 input points % see http://www.star-control.com/forum/index.php/topic,1660.msg33938.html#msg33938 % by Anthony Smith (Zeracles) % astroant@hotmail.com load('inputpositions') remainingpositions=inputpositions; % detect input properties and set up index sizeremainingpositions=size(remainingpositions); lengthremainingpositions=sizeremainingpositions(1); dimensions=sizeremainingpositions(2); index=transpose(linspace(1,lengthremainingpositions,lengthremainingpositions)); remainingpositionxs=remainingpositions(:,1); remainingpositionys=remainingpositions(:,2); if dimensions>2 remainingpositionzs=remainingpositions(:,3); end % initialise search parameters minx=min(remainingpositionxs); maxx=max(remainingpositionxs); xextent=minx*maxx; miny=min(remainingpositionys); maxy=max(remainingpositionys); yextent=miny*maxy; if dimensions>2 minz=min(remainingpositionzs); maxz=max(remainingpositionzs); zextent=minz*maxz; end if dimensions==2 measure=xextent*yextent; localmeasure=measure/lengthremainingpositions; searchincrement=((10*localmeasure)/pi)^(1/2); end if dimensions==3 measure=xextent*yextent*zextent; localmeasure=measure/lengthremainingpositions; searchincrement=((10*localmeasure)/(4/3)/pi)^(1/3); end % initialise with a seed point seedindex=1; maskvector=zeros(lengthremainingpositions,1); maskvector(seedindex)=1; remainingpositionxs=remainingpositionxs(find(maskvector==0)); remainingpositionys=remainingpositionys(find(maskvector==0)); if dimensions>2 remainingpositionzs=remainingpositionzs(find(maskvector==0)); end remainingpositionindices=index(find(maskvector==0)); lengthremainingpositions=lengthremainingpositions-1; treeindices=index(seedindex,:); lengthtreepositions=1; branches=[]; while lengthremainingpositions>0 % keep going until nothing remains unlinked to the tree (the ``remainingpositions") mindistances=[]; for i=linspace(1,lengthtreepositions,lengthtreepositions) % search around each of the tree positions for remainingpositions % retrieve coordinates of a tree position treepositionx=inputpositions(treeindices(i),1); treepositiony=inputpositions(treeindices(i),2); if dimensions>2 treepositionz=inputpositions(treeindices(i),3); end treeindex=treeindices(i); occupiedbox=0; searchfactor=1; while occupiedbox==0 % search for remainingpositions inside a box that grows until some are found boxradius=searchfactor*searchincrement; boxminx=treepositionx-boxradius; boxmaxx=treepositionx+boxradius; boxminy=treepositiony-boxradius; boxmaxy=treepositiony+boxradius; if dimensions>2 boxminz=treepositionz-boxradius; boxmaxz=treepositionz+boxradius; end if dimensions==2 closerremainingmask=(boxminx<=remainingpositionxs).*(remainingpositionxs<=boxmaxx).*(boxminy<=remainingpositionys).*(remainingpositionys<=boxmaxy); end if dimensions==3 closerremainingmask=(boxminx<=remainingpositionxs).*(remainingpositionxs<=boxmaxx).*(boxminy<=remainingpositionys).*(remainingpositionys<=boxmaxy).*(boxminz<=remainingpositionzs).*(remainingpositionzs<=boxmaxz); end mindistancecandidates=[]; mindistancecandidateindices=[]; if sum(closerremainingmask)>0 % if there are remainingpositions inside the box, calculate the actual distances to them for k=find(closerremainingmask==1) branchcandidatex=remainingpositionxs(k); branchcandidatey=remainingpositionys(k); if dimensions>2 branchcandidatez=remainingpositionzs(k); end branchcandidateindex=remainingpositionindices(k); % set up to remember the index of each prospective link destination if dimensions==2 mindistancecandidate=((branchcandidatex-treepositionx).^2+(branchcandidatey-treepositiony).^2).^(1/2); end if dimensions==3 mindistancecandidate=((branchcandidatex-treepositionx).^2+(branchcandidatey-treepositiony).^2+(branchcandidatez-treepositionz).^2).^(1/2); end if mindistancecandidate<=boxradius mindistancecandidates=[mindistancecandidates;mindistancecandidate]; mindistancecandidateindices=[mindistancecandidateindices;branchcandidateindex]; end end end if numel(mindistancecandidates)>0 mindistance=[min(mindistancecandidates),treeindex,mindistancecandidateindices(find(mindistancecandidates==min(mindistancecandidates)))]; % minimum distances carry the indices of the prospective link destination mindistances=[mindistances;mindistance]; occupiedbox=1; end searchfactor=searchfactor+1; % make the search box bigger end end branchdistance=min(mindistances(:,1)); branchindex=find(branchdistance==mindistances(:,1)); numberbranchcandidates=numel(branchindex); if numberbranchcandidates>1 % if there's a tie for minimum length branchindex=branchindex(ceil(numberbranchcandidates*rand(1))); end % add this branch to the tree branch=mindistances(branchindex,:); branches=[branches;branch]; % add that location to the tree treeindices=[treeindices;branch(3)]; lengthtreepositions=lengthtreepositions+1; % remove that location from the remainingpositions remainingmask=ones(lengthremainingpositions,1); removed=find(remainingpositionindices==branch(3)); remainingmask(removed)=0; remainingpositionindices=remainingpositionindices(find(remainingmask)); remainingpositionxs=remainingpositionxs(find(remainingmask)); remainingpositionys=remainingpositionys(find(remainingmask)); if dimensions>2 remainingpositionzs=remainingpositionzs(find(remainingmask)); end lengthremainingpositions=lengthremainingpositions-1; end save('branches','branches') % for plotting sizebranches=size(branches); numberofbranches=sizebranches(1); figure hold on box on plot(inputpositions(:,1),inputpositions(:,2),'k.') for i=linspace(1,numberofbranches,numberofbranches) startindex=branches(i,2); finishindex=branches(i,3); startx=inputpositions(startindex,1); starty=inputpositions(startindex,2); finishx=inputpositions(finishindex,1); finishy=inputpositions(finishindex,2); line([startx;finishx],[starty;finishy],'Color','k') end