Correct shuffling and add fit result to hepstats objects

src/zfitwrapper/BaseFitter.py

@@ -130,12 +130,11 @@ class BaseFitter(ABC):
     def _randomize_parameters(self, model: Model) -> None:
         for param in model.parameters.values():
             modelparameter = model.get_modelparameter(param.name)
-
-            if modelparameter.floating and param.shuffle:
+            if param.floating and param.shuffle:
                 modelparameter.randomize(
                     minval=param.lower, maxval=param.upper, sampler=np.random.uniform
                 )
-            elif modelparameter.floating and param.shuffle and param.extended:
+            elif param.floating and param.shuffle and param.extended:
                 modelparameter.set_value(param.value)
 
     def _single_fit(self) -> None:
@@ -158,8 +157,8 @@ class BaseFitter(ABC):
             nll = result_global.loss
 
         minimizer_local = self.minimizer
-        result = minimizer_local.minimize(nll).update_params()
-
+        result = minimizer_local.minimize(nll)
+        result = result.update_params()
         # calculate errors
         result.errors()
         try:
@@ -229,6 +228,7 @@ class BaseFitter(ABC):
         calculator = self.get_calculator(
             calculator=calculator, calculator_kwargs=calculator_kwargs
         )
+        calculator.bestfit = self.zfitresult
         poinull = POIarray(parameter, parameter_range)
         discovery_test = Discovery(calculator, poinull)
         pnull, significance = discovery_test.result()
@@ -250,6 +250,7 @@ class BaseFitter(ABC):
         calculator = self.get_calculator(
             calculator=calculator, calculator_kwargs=calculator_kwargs
         )
+        calculator.bestfit = self.zfitresult
         poinull = POIarray(parameter, parameter_range)
         poialt = POI(parameter, alt_value)
         ul = UpperLimit(calculator, poinull, poialt)