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optimtool-2.5.1

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@linjing-lab linjing-lab released this 09 Oct 02:41
· 74 commits to master since this release

Fixed Bug:

  • step size of Lasso in example should conform to lipschitz continuity condition, same as tk in any module of hybrid file.
  • test lagrange_augmented algorithm and correct the name of inner gradient normalized epsilon with default parameter.
import optimtool.constrain as oc
from optimtool.base import sp
f, x1, x2 = sp.symbols("f x1 x2")
f = (x1 - 2)**2 + (x2 - 1)**2
c1 = x1 - x2 - 1
c2 = 0.25*x1**2 - x2 - 1
oc.mixequal.lagrange_augmentedm(f, (x1, x2), c1, c2, (1., 0.), verbose=True)

see tests and examples for a full ecology of optimization.