Hello! I would like to extend NREL’s progressive hedging package to include a scaled penalty parameter, i.e. one which is proportional to the coefficients of the variable being penalised in the objective function.

Long story short: if I have a JuMP model, is there a way of querying the scalar coefficient of that variable in the objective? Something like this:

```
using JuMP
m = Model()
x = @variable(m, lower_bound=0.0)
con = @constraint(m, x >= 1)
obj = @objective(m, Min, 2*x)
get_scalar_coefficient(obj, x) # Would return 2.0
```

I was thinking that there must be a a way of doing this through `MathOptInterface`

, though I wasn’t able to find it in the documentation. If it makes it easier, for my particular use case the problem would be a QP (linear constraints with linear + quadratic objective terms).