Given a set of data points, this function calculates the center and radius of the data in a least squared sense. The least squared equations are used to reduce the matrix that is inverted to a 3x3, opposed to doing it directly on the data set. Does not require a large arc or many data points. Assumes points are not singular (co-planar) and real...
Created on R2010b, but should work on all versions.
Dear Alan, could you please, explain more about the two vectors A and B. I don't understand the rationality of Error function you defined as sum((x-xc)^2+(y-yc)^2+(z-zc)^2-r^2)^2,. Is the initial sphere center is taken for partial of the error of each parameter for example xc= mean(x), yc=mean (y) and zc= mean (z) and the function E = sum((xi-mean(x))^2+(y-mean(y))^2+(z-mean(z))^2-r^2)^2 and then, minimze the function E. many thanks
Dear Alan, can you send me the related papers? You know, I don't understand the rationality of Error function you defined as sum((x-xc)^2+(y-yc)^2+(z-zc)^2-r^2)^2, since I thought it was supposed to be sum(sqrt((x-xc)^2+(y-yc)^2+(z-zc)^2)-r)^2. My email: email@example.com. many thanks