prepare v1.9.6.2

CMakeLists.txt

@@ -21,7 +21,7 @@ include(CTest)
 set(OSTAP_VERSION_MAJOR 1)
 set(OSTAP_VERSION_MINOR 9)
 set(OSTAP_VERSION_PATCH 6)
-set(OSTAP_VERSION_TWEAK 1)
+set(OSTAP_VERSION_TWEAK 2)
 
 set(OSTAP_VERSION ${OSTAP_VERSION_MAJOR}.${OSTAP_VERSION_MINOR}.${OSTAP_VERSION_PATCH}.${OSTAP_VERSION_TWEAK})
 

ReleaseNotes/release_notes.md

@@ -1,3 +1,5 @@
+# v1.9.6.2
+
 ## New features:
 
   1. add `ROOT.TTree.fproject` method for projection of the trees using `DataFrame` (the same as `frame_project`)

ReleaseNotes/v1.9.6.2.md

@@ -0,0 +1,45 @@
+# v1.9.6.2
+
+## New features:
+
+  1. add `ROOT.TTree.fproject` method for projection of the trees using `DataFrame` (the same as `frame_project`)
+  1. add `Ostap::Math::IrwinHall`, `Ostap::Math::Bates` and `Ostap::Math::BAresShape`
+  1. add `Ostap::Models::BatesShape`
+  1. add `ostap.fitting.signals.BatesShape_pdf`
+  1. add `ostap.fitting.resolution.ResoBatesShape`
+  1. update tests 
+  1. add  'TH1(F,D).bezier_sum_fill', 'TH1(F,D).bernstein_sum_fill', 'TH1(F,D).legendre_sum_fill', 'TH1(F,D).chebyshev_sum_fill' methods  for 1D-historgam parameterisations based on `Bernstein::fill`, `LegendreSum::fill` and 
+`ChebyshevSum::fill` methods. Extend the corresponding test
+  1. add `TH(2,3)(F,D).bezier`, `TH(2,3)(F,D).bezier_fast`, `TH(2,3)(F,D).bezier_fill` methods for 2&3D-histogram parameterisations based on `Bernstein2D::fill` and `Bernstein3D::fill` methods 
+  1. add `TH(2,3)(F,D).bernstein`, `TH(2,3)(F,D).bernstein_fasr`, `TH(2,3)(F,D).bernstein_fill` methods for 2&3D-histogram parameterisations based on `Bernstein2D::fill` and `Bernstein3D::fill` methods 
+  1. add `ostap.utils.utils.slow`  method for `slow`-iteration with delaye at each step
+  1. add `Ostap::Math::agm` for complex numbers 
+  1. add `Ostap::Math::agm` for `ValueWithError` objects 
+  1. histogram parameterisations: add warnings for `fill`-based methods if polynomial degree is too large for such number of bins  
+  1. extend `test_histos_parameterisation` for 2D and 3D cases 
+  1. add `tag` method to several C+ classes 
+  1. add ``SimFit.sPlot` method (background-subtraction for simultaneous fits) & extend the test 
+  1. slight update in `ds_var_minmax` : try to deduce minmax when result is empty....
+  1. add proper pickling for `ROOT.RooLinearVar`
+  1. introduce `ConfigReducer` base class for better pickling/deserialisation 
+  1. add Karlin-Shapley & Karlin-Studen positive polynomials (functions&pdfs)
+  1. more polishing for Karlin-Shapley & Karlin-Studden stuff   
+  1. remove `conf_interval`, `upper_limit` and `lower_limit` methods for `PDF`, based on `RooStats::ProfileLikelihoodCalculator`
+  1. remove `poi` method from `funbasic`
+  1. rewrite `ostap.fitting.roostats`
+  1. add new test `test_fitting_roostats.py`
+  1. largely rewrite  "Breit-Wigner with interference" model
+  1. unify the variable separators for trees, datastes and frames 
+  1. further imporvements 
+  1. make a try to fix morphing 
+  1. fix for 3D-reweighting, add 3D-reweighting test/example for  Paula Garcia 
+  1. add (self)addition/subtraction operators for polynomial classes (`Polynomial`, `ChebyshevSum`, `LegendreSum`, `LegendreSum2`, `LegendreSum3` and `LegendreSum4`) with the same domain. 
+  1. few steps towards better polinomial parameterrisatios
+  1. Add polynomial parameterisation to frames (and trees) 
+  1. disable some frame functionality when `ROOT.std.move` is not available
+  1. add `ROOT.TTree.fparam` method for projection of the trees using `DataFrame` (the same as `frame_param`)
+
+
+## Backward incompatible:  
+
+## Bug fixes:

ostap/fitting/pdfbasic.py

@@ -488,17 +488,13 @@ def fit_to ( self , model , data , *options ) :
         assert all ( isinstance ( o , ROOT.RooCmdArg ) for o in options  ), \
                "fit_to: invalid argument types: %s" % list ( options  ) 
 
-        print ( 'I AM HERE/1', options  )
-
-        ## ## for "small" number of arguments use the standard function 
-        ## if len ( options ) <= NARGS :
-        ##     return model.fitTo ( data , *options )
+        ##  for "small" number of arguments use the standard function 
+        if len ( options ) <= NARGS :
+            return model.fitTo ( data , *options )
 
         from ostap.fitting.roocmdarg import command 
         cmd = command ( *options )
 
-        print ( 'I AM HERE/2', cmd  , type( cmd ) )
-
         return model.fitTo ( data , cmd  )