adding stale linking variables explicitly to pyomoNLP #43
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Thanks for this!
Unfortunately, the stale attribute on variables is only updated/checked when the model goes to a solver. Initially, all variables are marked as stale.
Do we even need to check for staleness? I think we can just put all of the linking variables in the export_nonlinear_variables list.
| @@ -197,7 +197,9 @@ def _setup(self, start_t: float, end_t: float): | |||
| start_t=_start_t, | |||
| end_t=_end_t, | |||
| add_init_conditions=add_init_conditions) | |||
| self._nlps[ndx] = nlp = InteriorPointInterface(pyomo_model=pyomo_model) | |||
| start_stale_names = [v.name for v in start_states if v.stale] | |||
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You can use a ComponentSet here to avoid using names:
from pyomo.common.collections import ComponentSet
start_stale_vars = ComponentSet(v for v in start_states if v.stale)
stale_vars = [v for v in start_states if v.stale] + [v for v in end_states if v.stale and v not in start_stale_vars]
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Ok, makes sense. Yes I think you're right, we probably can put all linking variables in the list, since they would be written anyway if they're not stale. Do you think checking for duplicates between start_states and end_states is necessary? I don't know how the writer behaves if the same variable occurs multiple times in export_nonlinear_variables.
…sing ComponentSet
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Looks like some of the tests are failing. I'll take a look, but probably not until next week. |
This addresses the bug where an error is thrown when a linking variable is stale within a time block. The stale linking variables are passed explicitly to the .nl file writer in pyomoNLP, so that they can be found in the _vardata_to_idx map later. In the dynamic Schur interface class, the stale linking variables are selected from the start and end states. There might be a more 'pyomo' way to avoid duplicates when passing the variables, here I did this based on variable name.