So I want to solve the equation z= a + b*y +c*x
,. getting a,b,c
.
ie: making a (plane) surface fit to a load of scatter points in 3D space.
But I can't seem to find anything! I thought there would be a simple module for such a simple problem.
I have tried, where x,y,z are arrays;
ys=zip(x,y)
(coeffs, residuals, rank, sing_vals) = np.linalg.lstsq(ys,z)
am I right in thinking coeffs = b,c? Or am I going completely in the wrong direction. I just can't seem to find anything else that will work in 3d...
I think you're on the right track. You could still try following the example of the scipy.linalg
documentation, in particular the Solving least-squares...` section
A = np.column_stack((np.ones(x.size), x, y))
c, resid,rank,sigma = np.linalg.lstsq(A,zi)
(we added a column of 1 for the constant).