[skip-ci][tutorials] fix legend style in roofit tutorial

Author: siliataider

tutorials/roofit/roofit/rf615_simulation_based_inference.py

@@ -33,8 +33,8 @@
 ## \date July 2024
 ## \author Robin Syring
 
-import ROOT
 import numpy as np
+import ROOT
 from sklearn.neural_network import MLPClassifier
 
 # The samples used for training the classifier in this tutorial / rescale for more accuracy
@@ -45,8 +45,7 @@
 
 
 # Morphing as a baseline
-def morphing(setting):
-
+def morphing(setting, workspace):
     # Define binning for morphing
     grid = ROOT.RooMomentMorphFuncND.Grid(ROOT.RooBinning(4, 0.0, 4.0))
     x_var.setBins(50)
@@ -199,7 +198,7 @@ def learned_likelihood_ratio(x, mu):
 ROOT.SetOwnership(nllr_learned, True)
 
 # Compute the morphed nll
-morphing(ROOT.RooMomentMorphFuncND.Linear)
+morphing(ROOT.RooMomentMorphFuncND.Linear, workspace)
 nll_morph = workspace["morph"].createNLL(obs_data)
 ROOT.SetOwnership(nll_morph, True)
 
@@ -228,8 +227,8 @@ def learned_likelihood_ratio(x, mu):
 frame1.Draw()
 
 legend1 = ROOT.TLegend(0.43, 0.63, 0.8, 0.87)
-legend1.SetFillColor("kWhite")
-legend1.SetLineColor("kWhite")
+legend1.SetFillColor(ROOT.kWhite)
+legend1.SetLineColor(ROOT.kWhite)
 legend1.SetTextSize(0.04)
 legend1.AddEntry("learned", "learned (SBI)", "L")
 legend1.AddEntry("gauss", "true NLL", "L")
@@ -247,8 +246,8 @@ def learned_likelihood_ratio(x, mu):
 frame2.Draw()
 
 legend2 = ROOT.TLegend(0.53, 0.73, 0.87, 0.87)
-legend2.SetFillColor("kWhite")
-legend2.SetLineColor("kWhite")
+legend2.SetFillColor(ROOT.kWhite)
+legend2.SetLineColor(ROOT.kWhite)
 legend2.SetTextSize(0.04)
 legend2.AddEntry("learned_ratio", "learned (SBI)", "L")
 legend2.AddEntry("exact", "true ratio", "L")