[RF] Pythonize RooAbsReal::setEvalErrorLogging mode with string to enum

root-project · Oct 13, 2024 · 77da806 · 77da806
1 parent 2957adf
commit 77da806
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Showing 3 changed files with 25 additions and 5 deletions.
diff --git a/bindings/pyroot/pythonizations/python/ROOT/_pythonization/_roofit/_rooabsreal.py b/bindings/pyroot/pythonizations/python/ROOT/_pythonization/_roofit/_rooabsreal.py
@@ -29,7 +29,7 @@ class RooAbsReal(object):
     \endcode
     """
 
-    __cpp_name__ = 'RooAbsReal'
+    __cpp_name__ = "RooAbsReal"
 
     @cpp_signature(
         "RooPlot* RooAbsReal::plotOn(RooPlot* frame,"
@@ -131,3 +131,23 @@ def getVal(self, normalizationSet=None):
         if normalizationSet:
             self._getVal_normSet = normalizationSet
         return self._getVal(normalizationSet) if normalizationSet else self._getVal()
+
+    def setEvalErrorLoggingMode(m):
+
+        import ROOT
+
+        if isinstance(m, str):
+            # Hardcode enum integer values here, because enum lookups cause
+            # some memory fiasco at the end.
+            # TODO: fix this in cppyy / PyROOT!
+            lut = {"PrintErrors": 0, "CollectErrors": 1, "CountErrors": 2, "Ignore": 3}
+            if m not in lut:
+                raise ValueError(
+                    "Unsupported value passed. The value has to be the name or enum value of an RooAbsReal ErrorLogging mode: {}".format(
+                        lut
+                    )
+                )
+
+            m = lut[m]
+
+        ROOT.RooAbsReal._setEvalErrorLoggingMode(m)
diff --git a/tutorials/roofit/rf615_simulation_based_inference.py b/tutorials/roofit/rf615_simulation_based_inference.py
@@ -196,9 +196,9 @@ def learned_likelihood_ratio(x, mu):
 frame1 = mu_var.frame(Title="NLL of SBI vs. Morphing", Range=(1.5, 2.5))
 nll_gauss.plotOn(frame1, LineColor="g", ShiftToZero=True, Name="gauss")
 nllr_learned.plotOn(frame1, LineColor="r", LineStyle="--", ShiftToZero=True, Name="learned")
-ROOT.RooAbsReal.setEvalErrorLoggingMode(ROOT.RooAbsReal.Ignore)  # Silence some warnings
+ROOT.RooAbsReal.setEvalErrorLoggingMode("Ignore")  # Silence some warnings
 nll_morph.plotOn(frame1, LineColor="c", ShiftToZero=True, Name="morphed")
-ROOT.RooAbsReal.setEvalErrorLoggingMode(ROOT.RooAbsReal.PrintErrors)
+ROOT.RooAbsReal.setEvalErrorLoggingMode("PrintErrors")
 
 # Plot the likelihood functions
 frame2 = x_var.frame(Title="Learned vs analytical likelihhood function")

diff --git a/tutorials/roofit/rf617_simulation_based_inference_multidimensional.py b/tutorials/roofit/rf617_simulation_based_inference_multidimensional.py
@@ -255,9 +255,9 @@ def learned_likelihood_ratio(*args):
     Range=(mu_observed[0] - 1, mu_observed[0] + 1),
 )
 nll_gauss.plotOn(frame1, ShiftToZero=True, LineColor="g", Name="gauss")
-ROOT.RooAbsReal.setEvalErrorLoggingMode(ROOT.RooAbsReal.Ignore)  # Silence some warnings
+ROOT.RooAbsReal.setEvalErrorLoggingMode("Ignore")  # Silence some warnings
 nll_morph.plotOn(frame1, ShiftToZero=True, LineColor="c", Name="morph")
-ROOT.RooAbsReal.setEvalErrorLoggingMode(ROOT.RooAbsReal.PrintErrors)
+ROOT.RooAbsReal.setEvalErrorLoggingMode("PrintErrors")
 nllr_learned.plotOn(frame1, LineColor="r", ShiftToZero=True, LineStyle="--", Name="learned")