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For the first question, the values are stored in the members of the minimo object. Explicitly print(minimo.success) print(minimo.x) For the second part of the question as to how to setup bounds, import scipy.optimize as so from scipy.optimize import Bounds import numpy as np my_bounds = Bounds(0,np.inf) def func_AC(r): return 1/((r[0]**2)+1) guess ...


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This is probably too late to help you, but here is a compact code that will do points, weights and first derivatives for Gauss, Lobatto or either Radau. function [x,w,A] = OCnonsymGLReig(n,meth) % code for nonsymmetric orthogonal collocation applications on 0 < x < 1 % n - interior points % meth = 1,2,3,4 for Gauss, Lobatto, Radau (right), ...


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The paper you linked to describes an algorithm similar to the Kabsch algorithm from what I see. It's used to find the least squares rotation between two sets of points. For your case you need something else entirely. Suppose sensor 1 has matrix $M_1$ at time t and sensor 2 has matrix $M_2$ at time t. That means that a vector, whose coordinates in the local ...


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