Using the hessian matrix in optimization about pyhf HOT 2 OPEN

One thought at the moment is you can subclass the scipy_optimizer via something like this for now:

class scipy_optimizer_hess(pyhf.optimize.scipy_optimizer):
    def _get_minimizer(self, *args, hess=None, **kwargs):
        return lambda *a, **k: scipy.optimize.minimize(*a, **k, hess=hess)

and then you can use it like so:

pyhf.set_backend(pyhf.tensorlib, scipy_optimizer_hess())

just to get a quick way of having it working for right now. This is probably something that needs a bit more thought as minuit doesn't support the hess, so we'd need a way to handle it seamlessly.

from pyhf.

Thanks, yes, that can work. It's trickier than I first thought, though, because of how it must interact with fixed_params.

from pyhf.