- #1
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I am trying to fit a transformation from one set of coordiantes to another.
x' = R + Px + Qy
y' = S - Qx + Py
Where P,Q,R,S are constants, P = scale*cos(rotation). Q=scale*sin(rotation)
There is a well known 'by hand' formula for fitting P,Q,R,S to a set of corresponding points.
But I need to have an error estimate on the fit - so I need a least squares solution.
I'm having trouble working out how to do this for first principles for data sets with x and y in them.
Can anyone point to an example/tutorial/code sample of how to do this ?
x' = R + Px + Qy
y' = S - Qx + Py
Where P,Q,R,S are constants, P = scale*cos(rotation). Q=scale*sin(rotation)
There is a well known 'by hand' formula for fitting P,Q,R,S to a set of corresponding points.
But I need to have an error estimate on the fit - so I need a least squares solution.
I'm having trouble working out how to do this for first principles for data sets with x and y in them.
Can anyone point to an example/tutorial/code sample of how to do this ?