Qfyilyi

For the problem formulation

import pyomo.environ as pe



model = pe.AbstractModel()

model.I = pe.Set()

model.p = model.Param(model.I)

model.create_instance("input.dat")

and the input.dat

set I := 1 2 3 ;

param p :=

1 0.1

2 0.2

3 0.3

;

param q :=

1 1.1

2 2.2

3 3.3

;

The following error is shown

AttributeError: 'AbstractModel' object has no attribute 'q'

How to silence create_instance in this case? The model is fully specified. The "excess" data (parameter q in this case) is needed for another model and the models share this input.dat. I could go with a try/except for the AttributeError and just carry on I guess, but then I would need to guard each create_instance call. I looked for a "skip_undefined" kwarg or similar in the documentation. Is there another preferred way to handle this situation?

According to the documentation, if you load your data using the method load from the class DataPortal, the parameters not used by the model are omitted.

Therefore you may try:

from pyomo.environ import *





data = DataPortal()

model = AbstractModel()



data.load(filename='./input.dat')



model.I = Set()

model.p = model.Param(model.I)



instance = model.create_instance(data)