Evaluation of constraints in the "trust-constr" minimize algorithm.

Hello List,

I am reading the source of the "trust-constr" minimize algorithm and I
am confused about what fun_and_constr() does on line 147 of
equality_constrained_sqp.py i.e.
https://github.com/scipy/scipy/blob/main/scipy/optimize/_trustregion_constr/equality_constrained_sqp.py#L147.

 From what I understand of the theory, I expected the fun_and_constr()
to simply evaluate the function and the constraints but it doesn't do
that. Rather the function does a lot more -- Hessians and Jacobian
computation and returns some sort of difference. What is the reason for
this?

Regards,

- Olumide

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