More Initializer Testing #1170
More Initializer Testing #1170
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andrewlee94
added
enhancement
| "in models that involve ExternalFunctions. We suggest you try " | ||
| "setting calculate_variable_options=\u007b'diff_mode': " | ||
| "pyomo.core.expr.calculus.differentiate.Modes.reverse_numeric\u007d. " | ||
| ) |
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Not for this, but is this because you are using sympy for derivatives? Could you use pynumero?
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This is a Pyomo tool so that is a question for them, but yes it is because they are using sympy by default for the derivatives.
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@jsiirola I don't want to put in the effort to trace this back and file a pyomo issue. Is it possible to fall back on pynumero (or maybe more of a stretch make sympy understand AMPL functions? Or just have a pynumero derivative option?
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@eslickj, this is orthogonal to pynumero. But yes, it is possible to automatically fall back on numeric differentiation (or just always use numeric differentiation). I just pushed up Pyomo/pyomo#2812 to have calculate_variable_from_constraint() automatically fall back on numeric differentiation if symbolic fails (and the user didn't care what differentiation engine to use).
Codecov ReportPatch coverage:
Additional details and impacted files@@ Coverage Diff @@
## main #1170 +/- ##
==========================================
- Coverage 76.67% 76.32% -0.36%
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Files 369 369
Lines 60306 60613 +307
Branches 11087 11187 +100
==========================================
+ Hits 46237 46260 +23
- Misses 11665 11966 +301
+ Partials 2404 2387 -17
... and 3 files with indirect coverage changes Help us with your feedback. Take ten seconds to tell us how you rate us. Have a feature suggestion? Share it here. ☔ View full report in Codecov by Sentry. |
Fixes None
Summary/Motivation:
This PR adds more testing and refinement of Initializers for core unit models.
Changes proposed in this PR:
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