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improved error message. #1412

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merged 3 commits into from
May 30, 2024
Merged

improved error message. #1412

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cc018bf
improved error message.
k1nshuk May 28, 2024
df9b4b7
run black.
k1nshuk May 28, 2024
b30dd99
Merge branch 'main' into better_err_msg
ksbeattie May 30, 2024
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4 changes: 3 additions & 1 deletion watertap/core/plugins/solvers.py
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Expand Up @@ -158,7 +158,9 @@ def _scale_constraints(self, blk):
self._cleanup()
raise RuntimeError(
"Error in AMPL evaluation.\n"
"Run ipopt with halt_on_ampl_error=yes and symbolic_solver_labels=True to see the affected function."
"Re-run ipopt with:\n"
'1. solver options = {"halt_on_ampl_error" : "yes", "nlp_scaling_method" : "gradient-based"\n'
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I am forgetting- should nlp_scaling_method be what you have here or user-scaling? What happens if you don't specify gradient -based scaling?

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This option ensures watertap's own scaling gets skipped and the model gets handed directly to Ipopt. This is what we want to see the problematic constraint / expression.

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I just thought I remembered this working regardless of that option so maybe I'm not recalling correctly.

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It certainly does in IDAES or if you just use SolverFactory("ipopt").

"2. set keyword argument symbolic_solver_labels=True in the pyomo solve function call to see the affected function.\n"
)
else:
print("Error in constraint_autoscale_large_jac")
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