diff --git a/ostap/core/ostap_types.py b/ostap/core/ostap_types.py
index 33215c68..ca17cc95 100644
--- a/ostap/core/ostap_types.py
+++ b/ostap/core/ostap_types.py
@@ -26,7 +26,8 @@
'sequence_types' , ## sequence types
'iterable_types' , ## iterable
'sized_types' , ## sized types
- 'path_types' , ## path-like types
+ 'path_types' , ## path-like types
+ 'ordered_dict' , ## normal/ordered dict
##
'is_integer' , ## is a value of int-like type?
'is_number' , ## is a value of numeric type?
@@ -76,11 +77,9 @@
# =============================================================================
logger.debug ( 'Core objects/classes/functions for Ostap')
# =============================================================================
-
iterable_types = Iterable,
num_types = integer_types + ( float , )
str_types = str,
-
list_types = list , tuple
import array
listlike_types = list_types + ( set , C.Sequence , array.array )
@@ -99,7 +98,13 @@
if (3,6) <= python_version :
path_types = string_types + ( os.PathLike , )
# =============================================================================
-
+## sometimewe we need to ensure that dictionary is ordered
+ordered_dict = dict
+if python_version < ( 3 , 7 ) :
+ from collections import OrderedDict as ordered_dict
+ dictlike_types += ( ordered_dict, )
+ dict_types += ( ordered_dict, )
+
# =============================================================================
## Is this number of a proper integer?
def is_integer ( v ) :
diff --git a/ostap/fitting/dataset.py b/ostap/fitting/dataset.py
index 00d6f527..84d8abf4 100644
--- a/ostap/fitting/dataset.py
+++ b/ostap/fitting/dataset.py
@@ -763,10 +763,6 @@ def _rds_make_unique_ ( dataset ,
ROOT.RooAbsData . sample = _rad_sample_
ROOT.RooAbsData . shuffle = _rad_shuffle_
-from ostap.trees.trees import _stat_covs_
-
-ROOT.RooAbsData . statCovs = _stat_covs_
-
from ostap.stats.statvars import data_the_moment
ROOT.RooAbsData. the_moment = data_the_moment
@@ -802,7 +798,6 @@ def _rds_make_unique_ ( dataset ,
ROOT.RooAbsData . sample ,
ROOT.RooAbsData . shuffle ,
#
- ROOT.RooAbsData . statCovs ,
]
diff --git a/ostap/frames/frames.py b/ostap/frames/frames.py
index 399fadc2..8a5f71f8 100644
--- a/ostap/frames/frames.py
+++ b/ostap/frames/frames.py
@@ -51,10 +51,11 @@
# =============================================================================
from ostap.core.core import ( cpp , Ostap ,
strings , split_string , var_separators )
-from ostap.math.base import isequal, iszero
+from ostap.math.base import isequal, iszero
from ostap.core.meta_info import root_info
from ostap.core.ostap_types import ( integer_types , num_types ,
- string_types , sequence_types )
+ string_types , sequence_types ,
+ ordered_dict )
from ostap.logger.utils import multicolumn
from ostap.utils.progress_conf import progress_conf
from ostap.utils.basic import isatty, loop_items
@@ -268,8 +269,7 @@ def frame_progress2 ( frame , length = -1 ) :
return frame
__all__ = __all__ + ( 'frame_progress2', )
-
-
+
# =============================================================================
## Get the effective entries in data frame
# @code
@@ -359,8 +359,10 @@ def _fr_helper_ ( frame , expressions , cuts = '' ) :
exprs, cuts, input_string = SV.vars_and_cuts ( expressions , cuts )
## Frame/Tree ?
- if isinstance ( frame , ROOT.TTree ) : frame = DataFrame ( frame )
- node = as_rnode ( frame )
+ if isinstance ( frame , ROOT.TTree ) : node = DataFrame ( frame )
+ elif isinstance ( frame , DataFrame ) : node = frame
+ elif isinstance ( frame , FrameNode ) : node = frame
+ else : node = as_rnode ( frame )
## get the list of currently known names
vars = frame_columns ( node )
@@ -368,17 +370,22 @@ def _fr_helper_ ( frame , expressions , cuts = '' ) :
current = node
- vnames = {}
- for i,expr in enumerate ( exprs ) :
+ vnames = ordered_dict()
+ for i , expr in enumerate ( exprs , start = 1 ) :
vname = expr
if not expr in all_vars :
used = tuple ( all_vars | set ( frame_columns ( current ) ) )
- vn = var_name ( 'var_' , used , expr , *vars )
+ vn = var_name ( 'var%d_' % i , used , expr , *vars )
all_vars.add ( vn )
current = current.Define ( vn , expr )
vname = vn
vnames [ expr ] = vname
-
+
+ ## Filter frame, if needed!
+ ## if cuts :
+ ## ## add named filter
+ ## current = current.Filter ( '(bool) (%s)' % cuts, 'FILTER: %s' % cuts )
+
cname = cuts
if cuts and not cuts in all_vars :
used = tuple ( all_vars | set ( frame_columns ( current ) ) )
@@ -387,8 +394,8 @@ def _fr_helper_ ( frame , expressions , cuts = '' ) :
ncuts = '1.0*(%s)' % cuts
current = current.Define ( cn , ncuts )
cname = cn
-
- return current, vnames , cname, input_string
+
+ return current, vnames, cname, input_string
# ==================================================================================
## the second helper method to implement "statistics"-related actions
@@ -414,7 +421,6 @@ def _fr_helper2_ ( frame , creator , expressions , cuts = '' , lazy = True ) :
return results
-
# ============================================================================
_types_1D = Ostap.Math.LegendreSum , Ostap.Math.Bernstein , Ostap.Math.ChebyshevSum ,
_types_2D = Ostap.Math.LegendreSum2 , Ostap.Math.Bernstein2D ,
@@ -422,7 +428,7 @@ def _fr_helper2_ ( frame , creator , expressions , cuts = '' , lazy = True ) :
_types_4D = Ostap.Math.LegendreSum4 ,
_types_nD = _types_1D + _types_2D + _types_3D + _types_4D
# =============================================================================
-## "project/parameterise" frame into polynomial structures
+## "project/parameterise" frame into polynomial structures (lazy action)
# @code
# frame = ...
#
@@ -439,111 +445,87 @@ def _fr_helper2_ ( frame , creator , expressions , cuts = '' , lazy = True ) :
# res = frame_param ( frame , ls2 , 'y' , 'x' , 'z>0' )
#
# bs2 = Ostap.Math.Bernstein2D ( ... )
-# res = frame_param ( frame , bs2 , 'y' , 'x' , 'z>0' )
+# res = frame_param ( frame , bs2 , ( 'y' , 'x' ) , 'z>0' )
#
# ls3 = Ostap.Math.LegendreSum3 ( ... )
-# res = frame_param ( frame , ls3 , 'z' , 'y' , 'x' , 'z>0' )
+# res = frame_param ( frame , ls3 , ( 'z' , 'y' , 'x' ) , 'z>0' )
#
# bs2 = Ostap.Math.Bernstein2D ( ... )
-# res = frame_param ( frame , bs2 , 'y' , 'x' , 'z>0' )
-#
+# res = frame_param ( frame , bs2 , ( 'y' , 'x' ) , 'z>0' )
# @endcode
-def _fr_param_ ( frame , poly , *expressions ) :
+def _fr_param_ ( frame , poly , expressions , cuts = '' , lazy = True ) :
""" `project/parameterise` frame into polynomial structures
+
>>> frame = ...
>>> ls = Ostap.Math.LegendreSum ( ... )
- >>> res = frame_param ( frame , ls , 'x' , 'y>0' )
+ >>> res = frame_param_lazy ( frame , ls , 'x' , 'y>0' )
>>> bs = Ostap.Math.Bernstein ( ... )
- >>> res = frame_param ( frame , bs , 'x' , 'y>0' )
+ >>> res = frame_param_lazy ( frame , bs , 'x' , 'y>0' )
>>> cs = Ostap.Math.ChebyshevSum ( ... )
- >>> res = frame_param ( frame , cs , 'x' , 'y>0' )
+ >>> res = frame_param_lazy( frame , cs , 'x' , 'y>0' )
>>> ls2 = Ostap.Math.LegendreSum2 ( ... )
- >>> res = frame_param ( frame , ls2 , 'y' , 'x' , 'z>0' )
+ >>> res = frame_param_lazy ( frame , ls2 , 'y,x' , 'z>0' )
>>> bs2 = Ostap.Math.Bernstein2D ( ... )
- >>> res = frame_param ( frame , bs2 , 'y' , 'x' , 'z>0' )
+ >>> res = frame_param_lazy ( frame , bs2 , 'y,x' , 'z>0' )
>>> ls3 = Ostap.Math.LegendreSum3 ( ... )
- >>> res = frame_param ( frame , ls3 , 'z' , 'y' , 'x' , 'z>0' )
+ >>> res = frame_param_lazy ( frame , ls3 , 'z,y;z' , 'z>0' )
>>> bs2 = Ostap.Math.Bernstein2D ( ... )
- >>> res = frame_param ( frame , bs2 , 'y' , 'x' , 'z>0' )
+ >>> res = frame_param_lazy ( frame , bs2 , 'y,x' , 'z>0' )
"""
-
- if isinstance ( frame , ROOT.TTree ) : frame = DataFrame ( frame )
-
- node = as_rnode ( frame )
-
- items = []
- for e in expressions :
- items += split_string ( e , ',:;' , strip = True , respect_groups = True )
-
- ## get the list of currently known names
- vars = frame_columns ( node )
- all_vars = set ( vars )
+ ## the histogram ?
+ if isinstance ( poly , ROOT.TH1 ) :
+ return _fr_project_ ( frame , poly , expressions , cuts = cuts , lazy = lazy )
- assert ( isinstance ( poly , _types_1D ) and 1 <= len ( items ) <= 2 ) or \
- ( isinstance ( poly , _types_2D ) and 2 <= len ( items ) <= 3 ) or \
- ( isinstance ( poly , _types_3D ) and 3 <= len ( items ) <= 4 ) or \
- ( isinstance ( poly , _types_4D ) and 4 <= len ( items ) <= 5 ) , \
- "Invalid structure of polynomial and variables/cuts!"
+ ##
+ current , items, cname , _ = _fr_helper_ ( frame , expressions , cuts )
- current = node
+ nvars = len ( items )
- ## actual variables
- uvars = []
- for e in items :
- if e in all_vars :
- uvars.append ( e )
- continue
- else :
- used = tuple ( all_vars | set ( frame_columns ( current ) ) )
- vn = var_name ( 'var_' , used , e , *vars )
- all_vars.add ( vn )
- current = current.Define ( vn , e )
- uvars.append ( vn )
-
- if ( isinstance ( poly , _types_1D ) and 2 == len ( uvars ) ) or \
- ( isinstance ( poly , _types_2D ) and 3 == len ( uvars ) ) or \
- ( isinstance ( poly , _types_3D ) and 4 == len ( uvars ) ) or \
- ( isinstance ( poly , _types_4D ) and 5 == len ( uvars ) ) :
-
- cuts = uvars [ -1]
- current = current.Filter ( cuts )
-
- wn = var_name ( 'weight_' , used , cuts , *vars )
- all_vars.add ( wn )
- current = current.Define ( wn , '1.0*(%s)' % cuts )
-
- uvars = [ u for u in reversed ( uvars [:-1] ) ] + [ wn ] ## ATTENTION !! RESERSED HERE!
-
- else :
- uvars = [ u for u in reversed ( uvars ) ] ## ATTENTION !! RESERSED HERE!
+ assert \
+ ( 1 == nvars and isinstance ( poly , _types_1D ) ) or \
+ ( 2 == nvars and isinstance ( poly , _types_2D ) ) or \
+ ( 3 == nvars and isinstance ( poly , _types_3D ) ) or \
+ ( 4 == nvars and isinstance ( poly , _types_4D ) ) , \
+ "Invalid structure of polynomial and variables/cuts!"
+ ## variables
+ uvars = [ k for k in items.values() ]
+ if cuts : uvars.append ( cname )
+ uvars = CNT ( uvars )
## finally book the actions!
if isinstance ( poly , Ostap.Math.LegendreSum ) :
- result = current.Book ( ROOT.std.move ( Ostap.Actions.LegendrePoly ( poly ) ) , CNT ( uvars ) )
+ result = current.Book ( ROOT.std.move ( Ostap.Actions.LegendrePoly ( poly ) ) , uvars )
elif isinstance ( poly , Ostap.Math.LegendreSum2 ) :
- result = current.Book ( ROOT.std.move ( Ostap.Actions.LegendrePoly2 ( poly ) ) , CNT ( uvars ) )
+ result = current.Book ( ROOT.std.move ( Ostap.Actions.LegendrePoly2 ( poly ) ) , uvars )
elif isinstance ( poly , Ostap.Math.LegendreSum3 ) :
- result = current.Book ( ROOT.std.move ( Ostap.Actions.LegendrePoly3 ( poly ) ) , CNT ( uvars ) )
+ result = current.Book ( ROOT.std.move ( Ostap.Actions.LegendrePoly3 ( poly ) ) , uvars )
elif isinstance ( poly , Ostap.Math.LegendreSum4 ) :
- result = current.Book ( ROOT.std.move ( Ostap.Actions.LegendrePoly4 ( poly ) ) , CNT ( uvars ) )
+ result = current.Book ( ROOT.std.move ( Ostap.Actions.LegendrePoly4 ( poly ) ) , uvars )
elif isinstance ( poly , Ostap.Math.ChebyshevSum ) :
- result = current.Book ( ROOT.std.move ( Ostap.Actions.ChebyshevPoly ( poly ) ) , CNT ( uvars ) )
+ result = current.Book ( ROOT.std.move ( Ostap.Actions.ChebyshevPoly ( poly ) ) , uvars )
elif isinstance ( poly , Ostap.Math.Bernstein ) :
- result = current.Book ( ROOT.std.move ( Ostap.Actions.BernsteinPoly ( poly ) ) , CNT ( uvars ) )
+ result = current.Book ( ROOT.std.move ( Ostap.Actions.BernsteinPoly ( poly ) ) , uvars )
elif isinstance ( poly , Ostap.Math.Bernstein2D ) :
- result = current.Book ( ROOT.std.move ( Ostap.Actions.BernsteinPoly2 ( poly ) ) , CNT ( uvars ) )
+ result = current.Book ( ROOT.std.move ( Ostap.Actions.BernsteinPoly2 ( poly ) ) , uvars )
elif isinstance ( poly , Ostap.Math.Bernstein3D ) :
- result = current.Book ( ROOT.std.move ( Ostap.Actions.BernsteinPoly3 ( poly ) ) , CNT ( uvars ) )
+ result = current.Book ( ROOT.std.move ( Ostap.Actions.BernsteinPoly3 ( poly ) ) , uvars )
+
+ print ( 'I AM HERE/1' )
+ if not lazy :
+ result = result.GetValue()
+ poly = result
+ print ( 'I AM HERE/2' )
+ print ( 'I AM HERE/3', result )
return result
@@ -617,8 +599,8 @@ def col_type ( var ) :
vcols = tuple ( [ v for v in vcols if cpat.match ( v ) ] )
svars = vcols + tuple ( more_vars )
- stats = frame_statVars ( frame , svars , cuts = cuts , lazy = False )
-
+ stats = _fr_statVar_ ( frame , svars , cuts = cuts , lazy = False )
+
if len ( vcols ) < 10 : ifmt = '%1d.'
elif len ( vcols ) < 100 : ifmt = '%2d.'
elif len ( vcols ) < 1000 : ifmt = '%3d.'
@@ -852,15 +834,15 @@ def _p2_model_ ( histo ) :
# ==============================================================================
-## 'Lazy' project of the frame
+## Project of the frame
# @code
# frame = ...
# h1_model = ...
# h1 = frame_project ( frame , h1_model , 'pt' )
# h2_model = ...
-# h2 = frame_project ( frame , h2_model , 'pt' , 'x' )
+# h2 = frame_project ( frame , h2_model , ( 'pt' , 'x' ) )
# h3_model = ...
-# h3 = frame_project ( frame , h3_model , 'pt' , 'x' , 'y' )
+# h3 = frame_project ( frame , h3_model , ( 'pt' , 'x' , 'y' ) )
# ...
# @endcode
# Cuts/weigth are also can be specified
@@ -869,9 +851,9 @@ def _p2_model_ ( histo ) :
# h1_model = ...
# h1 = frame_project ( frame , h1_model , 'pt' , 'w')
# h2_model = ...
-# h2 = frame_project ( frame , h2_model , 'pt' , 'x' , 'w')
+# h2 = frame_project ( frame , h2_model , 'pt,x' , 'w')
# h3_model = ...
-# h3 = frame_project ( frame , h3_model , 'pt' , 'x' , 'y' , 'w' )
+# h3 = frame_project ( frame , h3_model , 'pt,x:y' , 'w' )
# ...
# @endcode
#
@@ -883,16 +865,19 @@ def _p2_model_ ( histo ) :
# - ROOT::RDF::TH3DModel
# - anything that can be converted to ROOT::RDF::TH1DModel,
# ROOT::RDF::TH2DModel or ROOT::RDF::TH3DModel objects
-#
-def frame_project ( frame , model , *what ) :
- """ 'Lazy' project of the frame
+# @attention: variables should be listed in reverse order!
+def frame_project ( frame , model , expressions , cuts = '' , lazy = True ) :
+ """ Project of the frame into histigram
+
+ - attention: variables should be listed in reverse order!
+
>>> frame = ...
>>> h1_model = ...
>>> h1 = frame_project ( frame , h1_model , 'pt' )
>>> h2_model = ...
- >>> h2 = frame_project ( frame , h2_model , 'pt' , 'x' )
+ >>> h2 = frame_project ( frame , h2_model , 'pt,x' )
>>> h3_model = ...
- >>> h3 = frame_project ( frame , h3_model , 'pt' , 'x' , 'y' )
+ >>> h3 = frame_project ( frame , h3_model , ( 'pt' , 'x' , 'y' ) )
>>> ...
- Cuts/weigth are also can be specified
@@ -901,107 +886,59 @@ def frame_project ( frame , model , *what ) :
>>> h1_model = ...
>>> h1 = frame_project ( frame , h1_model , 'pt' , 'w')
>>> h2_model = ...
- >>> h2 = frame_project ( frame , h2_model , 'pt' , 'x' , 'w')
+ >>> h2 = frame_project ( frame , h2_model , ( 'pt' , 'x' ) , 'w')
>>> h3_model = ...
- >>> h3 = frame_project ( frame , h3_model , 'pt' , 'x' , 'y' , 'w' )
+ >>> h3 = frame_project ( frame , h3_model , 'pt' , 'x,y,z' , 'w' )
>>>...
- If model is a real 1D/2D/3D-hstogram, action is *not* lazy, otherwise action *is* lazy
-
+
Model can be a real histogram or
- - `ROOT.ROOT.RDF.TH1DModel`
- - `ROOT.ROOT.RDF.TH2DModel`
- - `ROOT.ROOT.RDF.TH3DModel`
- - anything that can be converted to `ROOT.ROOT.RDF.TH1DModel`,
- `ROOT.ROOT.RDF.TH2DModel` or `ROOT.ROOT.RDF.TH3DModel` objects
+ - `ROOT.ROOT.RDF.TH1DModel`
+ - `ROOT.ROOT.RDF.TH2DModel`
+ - `ROOT.ROOT.RDF.TH3DModel`
+ - anything that can be converted to :
+ -- `ROOT.ROOT.RDF.TH1DModel`,
+ -- `ROOT.ROOT.RDF.TH2DModel` or
+ -- `ROOT.ROOT.RDF.TH3DModel` objects
+
"""
-
- if isinstance ( frame , ROOT.TTree ) : frame = DataFrame ( frame )
- frame = as_rnode ( frame )
+ if isinstance ( model , _types_nD ) :
+ return _fr_param_ ( frame , model , expression, cuts = cuts , laszy = lazy )
- if ( 6 , 16 ) <= root_info and isinstance ( model , _types_nD ) :
- return _fr_param_ ( frame , model , *what )
-
- if 1 <= len ( what ) <= 2 :
- if isinstance ( what [ 0 ] , string_types ) :
- ww = split_string ( what [ 0 ] , var_separators , strip = True, respect_groups = True )
- if 1 < len ( ww ) : ww.reverse() ## ATTENTION HERE: REVERSE!!
- what = tuple ( ww ) + what [1:]
- elif isinstance ( what [ 0 ] , sequence_types ) :
- what = tuple ( w for w in what [ 0 ] ) + what [1:]
-
- ## strip blanks
- what = tuple ( w.strip() for w in what )
+ current , items, cname , _ = _fr_helper_ ( frame , expressions , cuts )
- ## cuts are empty
- if 1 < len ( what ) and not what [ -1 ] : what = what [ :-1 ]
+ ## convert histogram-like objects into 'models'
histo = None
-
- #
- ## convert histogram-like objects into 'models'
- #
-
- if isinstance ( model , ROOT.TProfile2D ) :
- histo = model
- model = model.model ()
- elif isinstance ( model , ROOT.TProfile ) :
- histo = model
- model = model.model ()
- elif isinstance ( model , ROOT.TH3 ) and 3 == model.dim () :
- histo = model
- model = model.model ()
- elif isinstance ( model , ROOT.TH2 ) and 2 == model.dim () :
- histo = model
- model = model.model ()
- elif isinstance ( model , ROOT.TH1 ) and 1 == model.dim () :
- histo = model
- model = model.model ()
+ if isinstance ( model , ROOT.TProfile2D ) : histo, model = model, model.model ()
+ elif isinstance ( model , ROOT.TProfile ) : histo, model = model, model.model ()
+ elif isinstance ( model , ROOT.TH3 ) and 3 == model.dim () : histo, model = model, model.model ()
+ elif isinstance ( model , ROOT.TH2 ) and 2 == model.dim () : histo, model = model, model.model ()
+ elif isinstance ( model , ROOT.TH1 ) and 1 == model.dim () : histo, model = model, model.model ()
if histo : histo.Reset()
- ## get the list of currently known names
- vars = frame_columns ( frame )
+ nvars = len ( items )
+ pvars = [ v for v in items.values() ]
+ if cname : pvars.append ( cname )
- pvars = []
- current = frame
- all_vars = set ( vars )
- for ww in what :
-
- w = ww
- if isinstance ( ww , ROOT.TCut ) : w = str ( ww )
-
- if not w : continue
-
- if w in vars : pvars.append ( w )
- elif w in pvars : pvars.append ( w )
- else :
- used = tuple ( all_vars | set ( frame_columns ( current ) ) )
- vname = var_name ( 'var_' , used , *what )
- current = current.Define ( vname , w )
- all_vars.add ( vname )
- pvars.append ( vname )
-
-
- numvars = len ( pvars )
-
- if isinstance ( model , DF_P2Model ) and 3 <= numvars <= 4 : action = current.Profile2D ( model , *pvars )
- elif isinstance ( model , DF_P1Model ) and 2 <= numvars <= 3 : action = current.Profiel1D ( model , *pvars )
- elif isinstance ( model , DF_H3Model ) and 3 <= numvars <= 4 : action = current.Histo3D ( model , *pvars )
- elif isinstance ( model , DF_H2Model ) and 2 <= numvars <= 3 : action = current.Histo2D ( model , *pvars )
- elif isinstance ( model , DF_H1Model ) and 1 <= numvars <= 2 : action = current.Histo1D ( model , *pvars )
+ if 3 == nvars and isinstance ( model , DF_P2Model ) : action = current.Profile2D ( model , *pvars )
+ elif 2 == nvars and isinstance ( model , DF_P1Model ) : action = current.Profiel1D ( model , *pvars )
+ elif 3 == nvars and isinstance ( model , DF_H3Model ) : action = current.Histo3D ( model , *pvars )
+ elif 2 == nvars and isinstance ( model , DF_H2Model ) : action = current.Histo2D ( model , *pvars )
+ elif 1 == nvars and isinstance ( model , DF_H1Model ) : action = current.Histo1D ( model , *pvars )
else :
- raise TypeError ('Invalid model/what objects %s %s ' % ( type ( model ) , what ) )
-
- ## ATTENTION! lazy action!
- if not histo :
- return action
+ raise TypeError ('Invalid model/what objects %s %s ' % ( type ( model ) , str ( pvars ) ) )
- ## make a loop!
- histo += action.GetValue()
- return histo
+ ## if true histo is specified, the aciton is NOT lazy!
+ if histo :
+ histo += action.GetValue()
+ return histo
+
+ return action if lazy else action.GetValue()
# ==============================================================================
## Prescale the frame
@@ -1245,8 +1182,6 @@ def frame_deciles ( frame , expression , cuts = '' , exact = True ) :
"""
return frame_quantiles ( frame , quantiles = 10 , expression = expression , cuts = cuts , exact = exact )
-
-
# ==============================================================================
## Get the mean for the frame object
# @code
@@ -1329,7 +1264,6 @@ def frame_kurtosis ( frame , expression , cuts = '' ) :
node = as_rnode ( frame )
return SV.data_kurtosis ( node , expression = expression , cuts = cuts )
-
from ostap.fitting.dataset import ds_draw as _ds_draw
# ==============================================================================
## draw for frame
@@ -1340,6 +1274,10 @@ def frame_draw ( frame , *args , **kwargs ) :
return _ds_draw ( node , *args , **kwargs )
+# ==================================================================================
+## Action-based methods
+# ==================================================================================
+
# ==================================================================================
## get statistics of variable(s)
# @code
@@ -1347,7 +1285,7 @@ def frame_draw ( frame , *args , **kwargs ) :
# stat = frame.statVar ( 'pt' , lazy = True )
# stat = frame.statVar ( 'pt' , 'eta>0' , lazy = True )
# @endcode
-def _fr_statVar_new_ ( frame , expressions , cuts = '' , lazy = False ) :
+def _fr_statVar_ ( frame , expressions , cuts = '' , lazy = True) :
"""Get statistics of variable(s)
>>> frame = ....
>>> stat = frame.statVar ( 'pt' , lazy = True )
@@ -1371,7 +1309,7 @@ def _fr_nEff_ ( frame , expressions , cuts = '' , lazy = False ) :
>>> frame = ...
>>> nEff = data_get_nEff ( 'x*x' , 'y>0' )
"""
- return _fr_statVar_new_ ( frame , expressions , cuts = cuts , lazy = lazy )
+ return _fr_statVar_ ( frame , expressions , cuts = cuts , lazy = lazy )
# ==================================================================================
## get statistics of variable(s)
@@ -1412,7 +1350,7 @@ def mcreator ( node , var_name , cut_name ) :
# stat = frame.the_mean ( 'x'x' , 'y<0' )
# mean = stat.mean()
# @ndcode
-def _fr_the_mean_ ( frame , expressions , cuts , errors = True , lazy = True ) :
+def _fr_the_mean_ ( frame , expressions , cuts = '' , errors = True , lazy = True ) :
""" Get a mean via moment
>>> frame = ...
>>> stat = frame.the_mean ( 'x'x' , 'y<0' )
@@ -1427,7 +1365,7 @@ def _fr_the_mean_ ( frame , expressions , cuts , errors = True , lazy = True ) :
# stat = frame.the_rms ( 'x'x' , 'y<0' )
# value = stat.rms()
# @ndcode
-def _fr_the_rms_ ( frame , expressions , cuts , errors = True , lazy = True ) :
+def _fr_the_rms_ ( frame , expressions , cuts = '' , errors = True , lazy = True ) :
"""Get a rms via moment
>>> frame = ...
>>> stat = frame.the_rms ( 'x'x' , 'y<0' )
@@ -1442,7 +1380,7 @@ def _fr_the_rms_ ( frame , expressions , cuts , errors = True , lazy = True ) :
# stat = frame.the_variance ( 'x'x' , 'y<0' )
# value = stat.variance ()
# @ndcode
-def _fr_the_variance_ ( frame , expressions , cuts , errors = True , lazy = True ) :
+def _fr_the_variance_ ( frame , expressions , cuts = '' , errors = True , lazy = True ) :
"""Get a variance via moment
>>> frame = ...
>>> stat = frame.the_variance( 'x'x' , 'y<0' )
@@ -1457,7 +1395,7 @@ def _fr_the_variance_ ( frame , expressions , cuts , errors = True , lazy = True
# stat = frame.the_skewness ( 'x'x' , 'y<0' )
# mean = stat.skewness ()
# @ndcode
-def _fr_the_skewness_ ( frame , expressions , cuts , errors = True , lazy = True ) :
+def _fr_the_skewness_ ( frame , expressions , cuts = '' , errors = True , lazy = True ) :
"""Get a variance via moment
>>> frame = ...
>>> stat = frame.the_skewness ( 'x'x' , 'y<0' )
@@ -1472,7 +1410,7 @@ def _fr_the_skewness_ ( frame , expressions , cuts , errors = True , lazy = True
# stat = frame.the_kurtosis ( 'x'x' , 'y<0' )
# value = stat.kurtosis ()
# @ndcode
-def _fr_the_kurtosis_ ( frame , expressions , cuts , errors = True , lazy = True ) :
+def _fr_the_kurtosis_ ( frame , expressions , cuts = '' , errors = True , lazy = True ) :
"""Get a kurtosis via moment
>>> frame = ...
>>> stat = frame.the_kurtosis ( 'x'x' , 'y<0' )
@@ -1480,7 +1418,6 @@ def _fr_the_kurtosis_ ( frame , expressions , cuts , errors = True , lazy = True
"""
return _fr_the_moment_ ( frame , 8 if errors else 4 , expressions , cuts = cuts , lazy = lazy )
-
# ============================================================================
## Get an arithmetic mean
# @see Ostap::Math::ArithmeticMean
@@ -1695,14 +1632,18 @@ def frame_rms ( frame , expression , cuts = '' ) :
# ================================================================================
if Frames_OK :
- frame_statVar = _fr_statVar_new_
- frame_statVars = _fr_statVar_new_
+
frame_table = _fr_table_
+
+ frame_the_statVar = _fr_statVar_
+ frame_the_statVars = _fr_statVar_
frame_the_moment = _fr_the_moment_
-
+
+ frame_the_nEff = _fr_nEff_
frame_the_mean = _fr_the_mean_
frame_the_rms = _fr_the_rms_
frame_the_variance = _fr_the_variance_
+ frame_the_dispersion = _fr_the_variance_
frame_the_skewness = _fr_the_skewness_
frame_the_kurtosis = _fr_the_kurtosis_
@@ -1711,8 +1652,9 @@ def frame_rms ( frame , expression , cuts = '' ) :
frame_harmonic_mean = _fr_harmonic_mean_
frame_power_mean = _fr_power_mean_
frame_lehmer_mean = _fr_lehmer_mean_
- for f in frames :
- f.statVars = frame_statVars
+
+ for f in frames :
+ f.statVars = frame_the_statVars
_new_methods_ .append ( f.statVars )
f.table = frame_table
_new_methods_ .append ( f.table )
@@ -1739,11 +1681,11 @@ def frame_rms ( frame , expression , cuts = '' ) :
f.lehmer_mean = frame_lehmer_mean
_new_methods_ .append ( f.lehmer_mean )
- _new_methods_ .append ( frame_statVars )
- _new_methods_ .append ( frame_table )
- _new_methods_ .append ( frame_the_moment )
+ _new_methods_ .append ( frame_table )
+ _new_methods_ .append ( frame_the_statVar )
+ _new_methods_ .append ( frame_the_moment )
_new_methods_ .append ( frame_arithmetic_mean )
- __all__ = __all__ + ( 'frame_statVars' ,
+ __all__ = __all__ + ( 'frame_the_statVar' ,
'frame_table' ,
'frame_the_moment' ,
'frame_the_mean' ,
@@ -1757,8 +1699,8 @@ def frame_rms ( frame , expression , cuts = '' ) :
'frame_power_mean' ,
'frame_lehmer_mean' )
- ROOT.TTree. fstatVars = frame_statVars
- ROOT.TTree. fthe_moment = frame_statVars
+ ROOT.TTree. fstatVars = frame_the_statVar
+ ROOT.TTree. fthe_moment = frame_the_statVar
_new_methods_ .append ( ROOT.TTree. fstatVars )
_new_methods_ .append ( ROOT.TTree. fthe_moment )
diff --git a/ostap/frames/tests/test_frames_frames.py b/ostap/frames/tests/test_frames_frames.py
index c4581cfe..fe1a0a3b 100644
--- a/ostap/frames/tests/test_frames_frames.py
+++ b/ostap/frames/tests/test_frames_frames.py
@@ -462,7 +462,7 @@ def test_frame7 () :
poll = rl.GetValue()
polb = rb.GetValue()
- with use_canvas ( 'test_frame5: b4,b5.b6 as polynomials' , wait = 2 ) :
+ with use_canvas ( 'test_frame7: b4,b5,b6 as polynomials' , wait = 2 ) :
poll.draw ( linecolor = 2 )
polc.draw ( 'same' , linecolor = 4 )
polb.draw ( 'same' , linecolor = 8 )
diff --git a/ostap/parallel/parallel_statvar.py b/ostap/parallel/parallel_statvar.py
index 61be02a3..2e07ae56 100644
--- a/ostap/parallel/parallel_statvar.py
+++ b/ostap/parallel/parallel_statvar.py
@@ -77,26 +77,25 @@ def process ( self , jobid , item ) :
with logWarning() :
import ostap.core.pyrouts
import ostap.trees.trees
-
chain = item.chain
first = item.first
last = min ( n_large , first + item.nevents if 0 < item.nevents else n_large )
- from ostap.trees.trees import _stat_vars_
-
- self.__output = _stat_vars_ ( chain , self.what , self.cuts , first , last )
+ from ostap.stats.starvrs import data_statistics
+ self.__output = data_statistics ( chain , self.what , self.cuts , first , last )
return self.__output
## merge results
def merge_results ( self , result , jobid = -1 ) :
- from ostap.stats.counters import WSE
+ from ostap.stats.counters import WSE
+ from ostap.core.ostap_types import dictlike_types
if not self.__output : self.__output = result
else :
assert type( self.__output ) == type ( result ) , 'Invalid types for merging!'
- if isinstance ( self.__output , dict ) :
+ if isinstance ( self.__output , dictlike_types ) :
for key in result :
if key in self.output : self.__output [ key ] += result [ key ]
else : self.__output [ key ] = result [ key ]
@@ -127,7 +126,7 @@ def pStatVar ( chain ,
"""
## few special/trivial cases
- from ostap.trees.trees import _stat_vars_
+ import ostap.trees.trees
last = min ( n_large , first + nevents if 0 < nevents else n_large )
if 0 <= first and 0 < nevents < chunk_size :
diff --git a/ostap/stats/statvars.py b/ostap/stats/statvars.py
index f795cca4..c0500e1f 100644
--- a/ostap/stats/statvars.py
+++ b/ostap/stats/statvars.py
@@ -50,6 +50,10 @@
'data_central_moment' , ## get the central moment (with uncertainty)
'data_nEff' , ## get the effective number of entries
'data_sum' , ## get the (weigted) sum
+ 'data_statistics' , ## get the statistics
+ 'data_covariance' , ## get the covariance
+ 'data_covariances' , ## get the covariances
+ 'data_statvector' , ## get the stat-vector
'data_mean' , ## get the mean (with uncertainty)
'data_variance' , ## get the variance (with uncertainty)
'data_dispersion' , ## get the dispersion (with uncertainty)
@@ -81,7 +85,7 @@
# =============================================================================
from builtins import range
from ostap.math.base import isequal, iszero
-from ostap.core.core import Ostap, rootException, WSE
+from ostap.core.core import Ostap, rootException, WSE, VE, std
from ostap.core.ostap_types import ( string_types , integer_types ,
num_types , dictlike_types )
from ostap.trees.cuts import expression_types, vars_and_cuts
@@ -299,7 +303,7 @@ def data_covariance ( data , expression1 , expression2 , cuts = '' , *args ) :
expression1 = str ( expression1 )
expression2 = str ( expression2 )
cuts = str ( cuts ).strip()
-
+
with rootException() :
if isinstance ( data , ROOT.TTree ) and not cuts :
return StatVar.statCov ( data , expression1 , expression2 , *args )
@@ -307,6 +311,86 @@ def data_covariance ( data , expression1 , expression2 , cuts = '' , *args ) :
return StatVar.statCov ( data , expression1 , expression2 , cuts , *args )
+# =============================================================================
+## get the covariances for many varibales
+# @code
+# tree = ...
+# stats , cov2 , len = data_covarinces ( ['x' , 'y'] )
+# # apply some cuts
+# stats , cov2 , len = data_covariances ( [ 'x' , 'y' , 'z'] , 'z>0' )
+# @endcode
+# @author Vanya BELYAEV Ivan.Belyaev@itep.ru
+# @date 2017-02-19
+def data_covariances ( tree ,
+ expressions ,
+ cuts = '' , *args ) :
+ """Get the statistic for the list of expressions
+ >>> tree = ...
+ >>> stats , cov2 , len = data_covariances ( data , ['x' , 'y'] )
+ Apply some cuts
+ >>> stats , cov2 , len = data_covariances ( data , [ 'x' , 'y' , 'z'] , 'z>0' )
+ Use only subset of events
+ >>> stats , cov2 , len = data_covariances ( data , [ 'x' , 'y' , 'z' ], 'z>0' , 100 , 10000 )
+ """
+
+ ## decode expressions & cuts
+ var_lst, cuts, input_string = vars_and_cuts ( expressions , cuts )
+
+ assert 2 <= len ( var_lst ) , 'Invalid number of varibales!'
+
+ from ostap.core.core import strings
+ vars = strings ( var_lst )
+
+ WSE = Ostap.WStatEntity
+ WV = std.vector( WSE )
+ stats = WV ()
+
+ import ostap.math.linalg
+ import ostap.math.linalgt
+
+ N = len ( var_lst )
+ cov2 = Ostap.TMatrixSymD ( N )
+
+ with rootException() :
+ length = Ostap.StatVar.statCov ( tree ,
+ vars ,
+ cuts ,
+ stats ,
+ cov2 , *args )
+
+ assert N == len ( stats ) , "Invalid size 'stats' from 'Ostap.StatVar.statCov'"
+ assert cov2.IsValid() , "Invalid 'cov2' from 'Ostap.StatVar.statCov'"
+ assert N == cov2.GetNrows() , "Invalid size of 'cov2' from 'Ostap.StatVar.statCov'"
+ assert N == cov2.GetNcols() , "Invalid size of 'cov2' from 'Ostap.StatVar.statCov'"
+
+ ## covert to tuple
+ stats = tuple ( WSE ( s ) for s in stats )
+
+ ## convert to S-matrix
+ cov2 = cov2.smatrix()
+
+ return stats, cov2 , length
+
+# ============================================================================
+## get the effective vector of mean-values with covarinaces for the dataset
+# @code
+# vct = data_statvct ( data , 'a,b,c' )
+# @endcode
+def data_statvector ( data ,
+ expressions ,
+ cuts = '' ) :
+ """Get the effective vector of mean-values with covariances for the dataset
+ >>> vct = data_statvct ( data , 'a,y,z' ,'w' )
+ """
+
+ stats , cov2, _ = data_covariances ( data , expressions , cuts = cuts )
+
+ N = len ( stats )
+ v = Ostap.Vector ( N ) ()
+ for i in range ( N ) : v[i] = stats[i].mean()
+
+ return Ostap.VectorE ( N ) ( v , cov2 )
+
# ==============================================================================
## Get the (weighted) sum over the variable(s)
# @code
@@ -325,7 +409,7 @@ def data_sum ( data , expressions , cuts = '' , *args ) :
result = data_statistics ( data , expressions , cuts , *args )
- if isinstance ( result , dictlike_type ) :
+ if isinstance ( result , dictlike_types ) :
for k , r in loop_items ( result ) :
result [ key ] = VE ( r.sum() , r.sum2() )
else :
@@ -334,7 +418,8 @@ def data_sum ( data , expressions , cuts = '' , *args ) :
return result
# ==============================================================================
-## Get the effewctoevnumebr of etries in data
+## Get the effective number of entries in data
+# \f$ \frac{ (\sum w)^2}{\sum w^2} \f$
# @code
# data = ...
# result = data_nEff ( data , 'x+y' )
@@ -350,7 +435,7 @@ def data_nEff ( data , expression = '' , *args ) :
assert isinstance ( expression , expression_types ) , 'Invalid type of expression!'
expression = str ( expression ).strip()
- return StatVar.nEff ( expression )
+ return StatVar.nEff ( data , expression )
# =============================================================================
## Get harmonic mean over the data
@@ -1023,12 +1108,16 @@ def data_decorate ( klass ) :
if hasattr ( klass , 'sumVar' ) : klass.orig_sumVar = klass.sumVar
if hasattr ( klass , 'sumVars' ) : klass.orig_sumVars = klass.sumVars
if hasattr ( klass , 'statCov' ) : klass.orig_statCov = klass.statCov
+ if hasattr ( klass , 'statCovs' ) : klass.orig_statCovs = klass.statCovs
+ if hasattr ( klass , 'statVct' ) : klass.orig_statVct = klass.statVct
klass.statVar = data_statistics
klass.statVars = data_statistics
klass.sumVar = data_sum
klass.sumVars = data_sum
klass.statCov = data_covariance
+ klass.statCovs = data_covariances
+ klass.statVct = data_statvector
if hasattr ( klass , 'the_moment' ) : klass.orig_the_moment = klass.the_moment
if hasattr ( klass , 'the_mean' ) : klass.orig_the_mean = klass.the_mean
@@ -1081,6 +1170,7 @@ def data_decorate ( klass ) :
klass.sumVar ,
klass.sumVars ,
klass.statCov ,
+ klass.statCovs ,
klass.the_moment ,
klass.the_mean ,
klass.the_rms ,
diff --git a/ostap/tools/tests/test_tools_reweight2.py b/ostap/tools/tests/test_tools_reweight2.py
index b6b5c402..adeff98a 100755
--- a/ostap/tools/tests/test_tools_reweight2.py
+++ b/ostap/tools/tests/test_tools_reweight2.py
@@ -235,7 +235,7 @@ def prepare_data ( ) :
datatree = ROOT.TChain ( 'DATA_tree' ) ; datatree.Add ( testdata )
mctree = ROOT.TChain ( tag_mc ) ; mctree.Add ( testdata )
-datastat = datatree.statCov('x','y')
+datastat = datatree.statCov ( 'x' , 'y' )
# =============================================================================
## prebook MC histograms
# =============================================================================
@@ -405,8 +405,8 @@ def prepare_data ( ) :
title = tag + ': DATA(x,y) vs MC(x,y) difference'
logger.info ( '%s:\n%s' % ( title , hdata .cmp_diff_prnt ( hmc , density = True , title = title , prefix = '# ' ) ) )
- ## 4e) 2D-statistics
- mcstat = mcds.statCov('x','y','weight')
+ ## 4e) 2D-statistics
+ mcstat = mcds .statCov ( 'x' , 'y' , 'weight' )
logger.info ( tag + ': x/y correlation DATA (unbinned): %+.2f' % datastat.correlation () )
logger.info ( tag + ': x/y correlation MC (unbinned): %+.2f' % mcstat.correlation () )
diff --git a/ostap/trees/trees.py b/ostap/trees/trees.py
index dbf73be2..facb7a3b 100755
--- a/ostap/trees/trees.py
+++ b/ostap/trees/trees.py
@@ -716,133 +716,6 @@ def _rt_contains_ ( tree , obj ) :
ROOT.TTree .__contains__ = _rt_contains_
ROOT.TChain.__contains__ = _rt_contains_
-# =============================================================================
-## get the statistic for pair of expressions in Tree/Dataset
-# @code
-# tree = ...
-# stat1 , stat2 , cov2 , len = tree.statCov ( 'x' , 'y' )
-# # apply some cuts
-# stat1 , stat2 , cov2 , len = tree.statCov ( 'x' , 'y' , 'z>0' )
-# # use only subset of events
-# stat1 , stat2 , cov2 , len = tree.statCov ( 'x' , 'y' , 'z>0' , 100 , 10000 )
-# @endcode
-# @author Vanya BELYAEV Ivan.Belyaev@itep.ru
-# @date 2013-09-15
-def _stat_cov_ ( tree ,
- expression1 ,
- expression2 ,
- cuts = '' , *args ) :
- """Get the statistic for pair of expressions in Tree/Dataset
-
- >>> tree = ...
- >>> stat1 , stat2 , cov2 , len = tree.statCov( 'x' , 'y' )
-
- Apply some cuts:
- >>> stat1 , stat2 , cov2 , len = tree.statCov( 'x' , 'y' , 'z>0' )
-
- Use only subset of events
- >>> stat1 , stat2 , cov2 , len = tree.statCov( 'x' , 'y' , 'z>0' , 100 , 10000 )
- """
-
-
- """
- import ostap.math.linalg
- stat1 = Ostap.WStatEntity ()
- stat2 = Ostap.WStatEntity ()
- cov2 = Ostap.Math.SymMatrix(2) ()
-
- with rootException() :
- if cuts : length = Ostap.StatVar.statCov ( tree ,
- expression1 ,
- expression2 ,
- cuts ,
- stat1 ,
- stat2 ,
- cov2 ,
- *args )
- else : length = Ostap.StatVar.statCov ( tree ,
- expression1 ,
- expression2 ,
- stat1 ,
- stat2 ,
- cov2 ,
- *args )
-
- return stat1 , stat2 , cov2, length
- """
-
-
-
-ROOT.TTree . statCov = _stat_cov_
-ROOT.TChain . statCov = _stat_cov_
-
-# =============================================================================
-## get the statistic for the list of expressions
-# @code
-# tree = ...
-# stats , cov2 , len = tree.statCovs( ['x' , 'y'] )
-# # apply some cuts
-# stats , cov2 , len = tree.statCovs( [ 'x' , 'y' , 'z'] , 'z>0' )
-# # use only subset of events
-# stats , cov2 , len = tree.statCovs( [ 'x' , 'y' , 'z' ], 'z>0' , 100 , 10000 )
-# @endcode
-# @author Vanya BELYAEV Ivan.Belyaev@itep.ru
-# @date 2017-02-19
-def _stat_covs_ ( tree ,
- expressions ,
- cuts = '' , *args ) :
- """Get the statistic for the list of expressions
- >>> tree = ...
- >>> stats , cov2 , len = tree.statCovs( ['x' , 'y'] )
- Apply some cuts
- >>> stats , cov2 , len = tree.statCovs( [ 'x' , 'y' , 'z'] , 'z>0' )
- Use only subset of events
- >>> stats , cov2 , len = tree.statCovs( [ 'x' , 'y' , 'z' ], 'z>0' , 100 , 10000 )
- """
- ##
- if isinstance ( expressions , string_types ) :
- expressions = split_string ( expressions , strip = True , respect_groups = True )
- ##
-
- vars = strings ( expressions )
- N = len ( vars )
-
- assert N , "Invalid 'expressions' %s" % str ( expressions )
-
-
- WSE = Ostap.WStatEntity
- WV = std.vector( WSE )
- stats = WV ()
-
- import ostap.math.linalg
- import ostap.math.linalgt
-
- cov2 = Ostap.TMatrixSymD ( N )
-
- with rootException() :
- length = Ostap.StatVar.statCov ( tree ,
- vars ,
- cuts ,
- stats ,
- cov2 , *args )
-
- assert N == len ( stats ) , "Invalid size 'stats' from 'Ostap.StatVar.statCov'"
- assert cov2.IsValid() , "Invalid 'cov2' from 'Ostap.StatVar.statCov'"
- assert N == cov2.GetNrows() , "Invalid size of 'cov2' from 'Ostap.StatVar.statCov'"
- assert N == cov2.GetNcols() , "Invalid size of 'cov2' from 'Ostap.StatVar.statCov'"
-
- ## covert to tuple
- stats = tuple ( WSE ( s ) for s in stats )
-
- ## convert to S-matrix
- cov2 = cov2.smatrix()
-
- return stats, cov2 , length
-
-ROOT.TTree . statCovs = _stat_covs_
-ROOT.TChain . statCovs = _stat_covs_
-
-
# =============================================================================
from ostap.stats.statvars import data_the_moment
diff --git a/source/src/StatVar.cpp b/source/src/StatVar.cpp
index ba7eca2b..2f2626f8 100644
--- a/source/src/StatVar.cpp
+++ b/source/src/StatVar.cpp
@@ -1570,6 +1570,11 @@ Ostap::StatVar::statVar
const unsigned long first ,
const unsigned long last )
{
+ // ==========================================================================
+ Ostap::Assert ( nullptr != data ,
+ "Invalid RotAbsData" ,
+ "Ostap::StatVar::statVar" ) ;
+ // ==========================================================================
Statistic result ;
if ( 0 == data || last <= first ) { return result ; } // RETURN
//
@@ -1686,6 +1691,72 @@ Ostap::StatVar::statVars
return result.empty() ? 0 : result[0].nEntries() ;
}
// ============================================================================
+/* calculate the covariance of two expressions
+ * @param tree (INPUT) the input tree
+ * @param exp1 (INPUT) the first expresiion
+ * @param exp2 (INPUT) the second expresiion
+ * @param cuts (INPUT) selection/weight expression
+ * @return number of processed events
+ * @author Vanya BELYAEV Ivan.Belyaev@itep.ru
+ * @date 2014-03-27
+ */
+// ============================================================================
+Ostap::StatVar::WCovariance
+Ostap::StatVar::statCov
+( const RooAbsData* data ,
+ const std::string& exp1 ,
+ const std::string& exp2 ,
+ const std::string& cuts ,
+ const std::string& cut_range ,
+ const unsigned long first ,
+ const unsigned long last )
+{
+ // ===========================================================================
+ Ostap::Assert ( nullptr != data ,
+ "Invalid RotAbsData" ,
+ "Ostap::StatVar::statCov" ) ;
+ //
+ // prepare the result
+ Ostap::StatVar::WCovariance result {} ;
+ //
+ if ( last <= first ) { return result ; } // RETURN
+ //
+ const std::unique_ptr formula1 { make_formula ( exp1 , *data ) } ;
+ const std::unique_ptr formula2 { make_formula ( exp2 , *data ) } ;
+ const std::unique_ptr selection { make_formula ( cuts , *data , true ) } ;
+ //
+ const bool weighted = data->isWeighted() ;
+ const char* cutrange = cut_range.empty() ? nullptr : cut_range.c_str() ;
+ //
+ const unsigned long the_last = std::min ( last , (unsigned long) data->numEntries() ) ;
+ //
+ // start the loop
+ for ( unsigned long entry = first ; entry < the_last ; ++entry )
+ {
+ //
+ const RooArgSet* vars = data->get( entry ) ;
+ if ( nullptr == vars ) { break ; } // RETURN
+ if ( cutrange && !vars->allInRange ( cutrange ) ) { continue ; } // CONTINUE
+ //
+ // apply cuts:
+ const long double wc = selection ? selection -> getVal() : 1.0L ;
+ if ( !wc ) { continue ; } // CONTINUE
+ // apply weight:
+ const long double wd = weighted ? data->weight() : 1.0L ;
+ if ( !wd ) { continue ; } // CONTINUE
+ // cuts & weight:
+ const long double w = wd * wc ;
+ if ( !w ) { continue ; } // CONTINUE
+ //
+ const double v1 = formula1->getVal () ;
+ const double v2 = formula2->getVal () ;
+ //
+ result.add ( v1 , v2 , w ) ;
+ }
+ //
+ return result ;
+}
+// ============================================================================
/* calculate the covariance of several expressions
* @param tree (INPUT) the inpout tree
* @param vars (INPUT) expressions