ValueError from report_numerical_issues()

[adam-a-a]

I am getting the following error when I try running report_numerical_issues() from the DiagnosticToolbox. I should note that this was working fine until I updated my WaterTAP environment--just haven't taken the time to identify potentially problematic dependencies.

Traceback (most recent call last):
  File "c:\redacted.py", line 450, in <module>
    dt.report_numerical_issues()
  File "C:\redacted\lib\site-packages\idaes\core\util\model_diagnostics.py", line 1501, in report_numerical_issues      
    warnings, next_steps = self._collect_numerical_warnings(jac=jac, nlp=nlp)
  File "C:\redacted\lib\site-packages\idaes\core\util\model_diagnostics.py", line 1246, in _collect_numerical_warnings  
    par_cons = check_parallel_jacobian(
  File "C:\redacted\lib\site-packages\idaes\core\util\model_diagnostics.py", line 3778, in check_parallel_jacobian      
    maxval = max(np.abs(vec.data))
ValueError: max() arg is an empty sequence

FYI @andrewlee94 @lbianchi-lbl

[andrewlee94]

@adam-a-a First thing, could you update your version of IDAES and see if the issue persists? From the line numbers it appears you version of IDAES is out-of-date (I suspect this will not fix the issue hwoever).

[lbianchi-lbl]

• As @andrewlee94 said, we need more info on the environment from @adam-a-a (pip list is a good starting point)
• As per @dallan-keylogic, there's a chance that More efficient method for check_parallel_jacobian #1395 might resolve this once merged

[dallan-keylogic]

@adam-a-a , do you have a file where you can replicate this? I could debug it live to figure out what the issue is.

[adam-a-a]

@dallan-keylogic I'll have to dig that up, but I think I realize why this happened. The model I was working with failed before going through initialization because of DOF > 0, and I was subsequently running report_numerical_issues on an uninitialized model, where there were likely variables without initial values.

In the interim, I wonder if you want to run any old model, and before initializing, run dt.report_numerical_issues. I know that we aren't supposed to do this in the first place and really should initialize the model first before trying to report numerical issues. That said, maybe we want a more helpful exception to pop up if a user makes the same mistake that I did; e.g., "Consider initializing your model first as it seems that variables without initial values were passed in."