Hello,
I try to use minimization function of sage but I didn't understand how
minimize with a function.
I want construct a hermite curve and I have p array of 4 control points. I
would try to find alpha and beta scalar value so that the curve
have the minimimun curvature in some points.
I would like find the alpha and beta value but I don't know how use
minimize function in this case.
p=[vector([9,4,0]),vector([9,1,0]),vector([3,3,0]),vector([2,1,0])]
def minimumHermite(alpha,beta):
# varing tangent 1
p[2]=p[2]*alpha
# varing tangent 2
p[3]=p[3]*beta
# build the hermite curve from contro point p
curveHermite=HermiteCurve(p)
curvatureH=curvature(curveHermite)
best=0
# calculate curvature value at some points and minimize this value
rispect to alpha and beta
for i in range(1,11):
square=curvatureH.substitute(t==0.1*i).norm()
best=best+square*square
return best
Thanks in advance
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