I have a series of discrete point on a plane, However, their order is scattered. Here is an instance:
To connect them with a smooth curve, I wrote a findSmoothBoundary()
to achieve the smooth boundary.
function findSmoothBoundary(boundaryPointSet)
%initialize the current point
currentP = boundaryPointSet(1,:);
%Create a space smoothPointsSet to store the point
smoothPointsSet = NaN*ones(length(boundaryPointSet),2);
%delete the current point from the boundaryPointSet
boundaryPointSet(1,:) = [];
ptsNum = 1; %record the number of smoothPointsSet
smoothPointsSet(ptsNum,:) = currentP;
while ~isempty(boundaryPointSet)
%ultilize the built-in knnsearch() to
%achieve the nearest point of current point
nearestPidx = knnsearch(boundaryPointSet,currentP);
currentP = boundaryPointSet(nearestPidx,:);
ptsNum = ptsNum + 1;
smoothPointsSet(ptsNum,:) = currentP;
%delete the nearest point from boundaryPointSet
boundaryPointSet(nearestPidx,:) = [];
end
%visualize the smooth boundary
plot(smoothPointsSet(:,1),smoothPointsSet(:,2))
axis equal
end
Although findSmoothBoundary()
can find the smooth boundary rightly, but its efficiency is much lower ( About the data, please see here)
So I would like to know:
theta = linspace(0,2*pi,1000)';
boundaryPointSet= [2*sin(theta),cos(theta)];
tic;
findSmoothBoundary(boundaryPointSet)
toc;
%Elapsed time is 4.570719 seconds.
This answer is not perfect because I'll have to make a few hypothesis in order for it to work. However, for a vast majority of cases, it should works as intended. Moreover, from the link you gave in the comments, I think these hypothesis are at least weak, if not verified by definition :
1. The point form a single connected region
2. The center of mass of your points lies in the convex hull of those points
If these hypothesis are respected, you can do the following (Full code available at the end):
Step 1 : Calculate the center of mass of your points
Means=mean(boundaryPointSet);
Step 2 : Change variables to set the origin to the center of mass
boundaryPointSet(:,1)=boundaryPointSet(:,1)-Means(1);
boundaryPointSet(:,2)=boundaryPointSet(:,2)-Means(2);
Step3 : Convert coordinates to polar
[Angles,Radius]=cart2pol(boundaryPointSet(:,1),boundaryPointSet(:,2));
Step4 : Sort the Angle
and use this sorting to sort the Radius
[newAngles,ids]=sort(Angles);
newRadius=Radius(ids);
Step5 : Go back to cartesian coordinates and re-add the coordinates of the center of mass:
[X,Y]=pol2cart(newAngles,newRadius);
X=X+Means(1);
Y=Y+means(2);
%%% Find smooth boundary
fid=fopen('SmoothBoundary.txt');
A=textscan(fid,'%f %f','delimiter',',');
boundaryPointSet=cell2mat(A);
boundaryPointSet(any(isnan(boundaryPointSet),2),:)=[];
idx=randperm(size(boundaryPointSet,1));
boundaryPointSet=boundaryPointSet(idx,:);
tic
plot(boundaryPointSet(:,1),boundaryPointSet(:,2))
%% Find mean value of all parameters
Means=mean(boundaryPointSet);
%% Center values around Mean point
boundaryPointSet(:,1)=boundaryPointSet(:,1)-Means(1);
boundaryPointSet(:,2)=boundaryPointSet(:,2)-Means(2);
%% Get polar coordinates of your points
[Angles,Radius]=cart2pol(boundaryPointSet(:,1),boundaryPointSet(:,2));
[newAngles,ids]=sort(Angles);
newRadius=Radius(ids);
[X,Y]=pol2cart(newAngles,newRadius);
X=X+Means(1);
Y=Y+means(2);
toc
figure
plot(X,Y);
Note : As your values are already sorted in your input file, I had to mess it up a bit by permutating them
Boundary
Elapsed time is 0.131808 seconds.
Messed Input :
Output :
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