Determine positions of projected points onto an ellipse
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Hi,
I have a set of data points (blue dots below) and I woule like to project them onto an ellipse (with known a, b, x0, y0, and radian or tilt).
I wonder how I can determine the position of each projected points on the ellipse. Any advices/code/peudo code would be lovely. Thank you.
![](https://www.mathworks.com/matlabcentral/answers/uploaded_files/1232877/image.png)
Réponse acceptée
Matt J
le 16 Déc 2022
Modifié(e) : Matt J
le 16 Déc 2022
Use the ellipseprj function below. It requires the download of trustregprob from the file exchange
ab = [2 1]; %ellipse radii
xy0 = [1 1]; %ellipse center
rad=5; R = [cos(rad), -sin(rad); sin(rad),cos(rad)]; %ellipse tilt
xysamp = randn(2,5); %random points to be projected onto the ellipse
xyproj = ellipseprj( R'*diag(1./ab.^2)*R , xy0, xysamp); %the projected points
%%%Visualize
t = linspace(0,2*pi,50)';
xyc = xy0 + ab.*[cos(t), sin(t)]*R; %points for plotting the ellipse
plot(xyc(:,1),xyc(:,2),'b-')
axis equal
grid on
hold on
plot(xysamp(1,:),xysamp(2,:),'ro') %plot random points
plot(xyproj(1,:),xyproj(2,:),'ks') %plot their projections
line([xysamp(1,:);xyproj(1,:)],[xysamp(2,:);xyproj(2,:)],'color','g')
hold off
function Xp=ellipseprj(Q,xc,X0)
%Projects given 2D points onto 2D ellipse
%
% Xp=ellipseprj(Q,xc,X0)
%
%IN:
%
% Q,xc: Ellipse equation matrices. Q is 2x2 and xc is 2x1 such that
% ellipse equation is (y-xc).'*Q*(y-xc)=1
% X0: 2xN matrix of points to be projected
%
%OUT:
%
% Xp: 2xN matrix of projected points
N=size(X0,2);
xc=xc(:);
[Rt,D]=eig(Q);
Rt=real(Rt); D=real(D);
iD=diag(1./diag(D));
iDsqrt=sqrt(iD);
b=-iDsqrt*Rt.'*bsxfun(@minus,xc,X0);
Yp=nan(size(X0));
for i=1:N
Yp(:,i)=trustregprob(iD,b(:,i),1);
end
Xp=bsxfun(@plus, Rt*iDsqrt*Yp,xc);
end
5 commentaires
Matt J
le 20 Déc 2022
@Salad Box, In addition to what John said, it is a pretty basic calculus exercise to compute the tangent to the ellipse at B, and to verify numerically that the tangent is orthogonal to (A-B). I encourage doing that in addition to any visual tests.
Plus de réponses (2)
John D'Errico
le 16 Déc 2022
Modifié(e) : John D'Errico
le 16 Déc 2022
Simple. Just download my distance2curve utility, found on the file exchange.
For some example data, I'm not sure what you meant by radian as a variable.
t = linspace(0,2*pi,50)';
ab = [2 1];
xy0 = [1 1];
rotmat = @(R) [cos(R), -sin(R);sin(R),cos(R)];
xyc = xy0 + ab.*[cos(t), sin(t)]*rotmat(5);
plot(xyc(:,1),xyc(:,2),'b-')
axis equal
grid on
Now for a given set of points,
xy0 = randn(10,2);
xyproj = distance2curve(xyc,xy0);
hold on
plot(xy0(:,1),xy0(:,2),'ro')
plot(xyproj(:,1),xyproj(:,2),'rs')
line([xy0(:,1),xyproj(:,1)]',[xy0(:,2),xyproj(:,2)]','color','g')
Each point is projected to the nearest point on the ellipse.
distance2curve is found for free download from the file exchange, here:
Torsten
le 16 Déc 2022
Modifié(e) : Torsten
le 16 Déc 2022
a = 2;
b = 1; % main axes
x0 = 1;
y0 = 1; % translation
alpha = 5; % rotation angle of ellipse in degrees
px = randn(1,10);
py = randn(1,10); % Sample points to be projected
syms theta xp yp xp_given yp_given
% Generate ellipse equation dependent on theta
x = a*cos(theta);
y = b*sin(theta);
% Solve for theta that minimizes the distance
f = (x-xp)^2 + (y-yp)^2;
df = diff(f,theta);
sol_theta = solve(df==0,theta,'MaxDegree',4)
% Transform given points (xp_given,yp_given) to coordinate system of the centered ellipse
% and project on it
P_slash = [cosd(-alpha) -sind(-alpha);sind(-alpha) cosd(-alpha)]*[xp_given - x0 ; yp_given - y0];
sol_theta = subs(sol_theta,[xp yp],[P_slash(1) P_slash(2)])
% Transform projected points back to given ellipse
Px_proj = cosd(alpha)*subs(x,theta,sol_theta) - sind(alpha)*subs(y,theta,sol_theta) + x0;
Py_proj = sind(alpha)*subs(x,theta,sol_theta) + cosd(alpha)*subs(y,theta,sol_theta) + y0;
% Numerical example
for i = 1:numel(px)
px_proj = double(subs(Px_proj,[xp_given yp_given],[px(i) py(i)]));
py_proj = double(subs(Py_proj,[xp_given yp_given],[px(i) py(i)]));
idx = abs(imag(px_proj))<1e-6 & abs(imag(py_proj))<1e-6;
px_proj = px_proj(idx);
py_proj = py_proj(idx);
d = sqrt((px(i)-px_proj).^2 + (py(i)-py_proj).^2);
[dist(i),index] = min(d);
pxp(i) = px_proj(index);
pyp(i) = py_proj(index);
end
%Graphical presentation
thetanum = 0:2*pi/100:2*pi;
xx = a*cos(thetanum);
yy = b*sin(thetanum);
xxx = xx*cosd(alpha) - yy*sind(alpha);
yyy = xx*sind(alpha) + yy*cosd(alpha);
xxx = xxx + x0;
yyy = yyy + y0;
plot(xxx,yyy)
hold on
arrayfun(@(i)plot([px(i), real(pxp(i))],[py(i), real(pyp(i))]),1:numel(px))
axis equal
grid on
2 commentaires
Torsten
le 16 Déc 2022
Modifié(e) : Torsten
le 16 Déc 2022
px and py should be your data points.
You must admit 0 <= theta < 2*pi to determine the optimal projection point on the ellipse, but the graphical part is only for illustration - it's not a necessary part of the code.
Inputs are - as said -
a = 2;
b = 1; % main axes
x0 = 1;
y0 = 1; % translation
alpha = 5; % rotation angle of ellipse in degrees
px = randn(1,10);
py = randn(1,10); % Sample points to be projected
and outputs are pxp and pyp - the x-and y-coordinates of the points on the ellipse nearest to the (px /py) - and maybe (if it's of interest) the array "dist" which contains the Euclidean distance between the given data points and their counterparts on the ellipse.
Voir également
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