There is pypesto.problem.base.Problem.x_guesses which is used to pre-select startpoints for optimization. By default, Problem.startpoint_method will return points from x_guesses if that's set. Repeated calls will always return the same points. While this may be convenient in a few situations, it's a bit of a footgun elsewhere.
Are there any uses cases for x_guesses outside multi-start optimization (pypesto.optimize.optimize.minimize)? If not, I would propose removing Problem.x_guesses and instead adding an x0 argument to minimize().
There is
pypesto.problem.base.Problem.x_guesseswhich is used to pre-select startpoints for optimization. By default,Problem.startpoint_methodwill return points fromx_guessesif that's set. Repeated calls will always return the same points. While this may be convenient in a few situations, it's a bit of a footgun elsewhere.Are there any uses cases for
x_guessesoutside multi-start optimization (pypesto.optimize.optimize.minimize)? If not, I would propose removingProblem.x_guessesand instead adding anx0argument tominimize().