fix?

ostap/fitting/dataset.py

@@ -25,7 +25,8 @@
     )
 # =============================================================================
 from   builtins                  import range
-from   collections               import defaultdict 
+from   collections               import defaultdict
+from   ostap.core.meta_info      import root_info
 from   ostap.core.core           import ( Ostap, VE, SE ,
                                           hID  , dsID , strings , 
                                           valid_pointer , split_string   ,
@@ -2272,7 +2273,7 @@ def _ds_symmetrize_ ( ds , var1 , var2 , *vars ) :
 
 
 # =============================================================================
-## get the name of weigth variable in dataset
+## get the name of weight variable in dataset
 #  @code
 #  dataset = ...
 #  wname   = dataset.wname() 
@@ -2288,8 +2289,12 @@ def _ds_wname_ ( dataset ) :
 
     attr = '_weight_var_name'
     if not hasattr ( dataset , attr ) :
-
-        wn = Ostap.Utils.getWeight (  dataset )
+
+        if ( 6 , 26 ) <= root_info :
+            wv = dataset.weightVar()
+            wn = wv.name if wv else Ostap.Utils.getWeight ( dataset )
+        else : wn = Ostap.Utils.getWeight ( dataset )
+
         setattr ( dataset , attr , wn ) 
 
     return getattr ( dataset , attr , '' )

ostap/fitting/ds2numpy.py

@@ -46,36 +46,6 @@
 
 
 
-# input: 
-# dataset - initial dataset
-# var_lst - name of variables to add in numpy array 
-# weight - Bool value, which work with weights vars in dataset
-#ds = DS_to_Numpy(data, ['evt', 'run'], weight)
-#ds = DS_to_Numpy_for_old_version(data, ['evt', 'run']) - for old ROOT package version
-# output: 
-# data - numpy array with values of the required variables
-
-#Check the list of variables for duplicates
-def find_dublicates_in_var_list(var_lst):
-    return len(var_lst) != len(set(var_lst))
-
-#add weight variable in numpy array
-def add_weight ( ds , data ):
-
-    if not ds.isWeighted() : return data
-
-    weight  = ds.weightVar().GetName()
-
-    ## creathe the weight array 
-    weights = np.zeros( len ( ds ) , dtype=np.float64)
-
-    ## fill it 
-    for i in ds : weight_array[i] = ds.weight()
-
-    data [ weight ] = weights 
-
-    return data
-
 # =============================================================================
 if   np and ( 6 , 26 ) <= root_info  :  ## 6.26 <= ROOT 
 # =============================================================================
@@ -142,7 +112,7 @@ def ds2numpy ( dataset , var_lst , silent = True ) :
         categories = [ v.name for v in vars if isinstance ( v , ROOT.RooAbsCategory ) ]
 
         ## name of weight variable 
-        weight = '' if not dataset.isWeighted() else dataset.weightVar().GetName () 
+        weight = '' if not dataset.isWeighted() else dataset.wname () 
 
         dtypes = [] 
         for v in vnames :
@@ -247,7 +217,7 @@ def ds2numpy ( dataset , var_lst , silent = False ) :
         categories = [ v.name for v in vars if isinstance ( v , ROOT.RooAbsCategory ) ]
 
         ## name of weight variable 
-        weight = '' if not dataset.isWeighted() else dataset.weightVar().GetName () 
+        weight = '' if not dataset.isWeighted() else dataset.wname () 
 
         dtypes = [] 
         for v in vnames :