1. add pos_error/neg_error/errors properteis to `Ostap::Math::Valu…

…eWithError` object `

   1. add column `@limit?` for printput of `RooFitResult` object to shwo the distance to the limits (if any). Distanc eof <3sigma, an d<5 sigma ar ecolored. Distances > 10sigma are omitted.

ReleaseNotes/release_notes.md

@@ -4,7 +4,10 @@
    1. add `pretty_array` function for nice print of arrays/sequences
    1. add some auxillary methods for matrices: `(min/max/minabs/maxabs)_element` and `(min/max)_diagonal` and `(min/max/minabs/maxabs)_element_index`
    1. improve printout of `SVectorwithError`
+   1. add `pos_error/neg_error/errors` properteis to `Ostap::Math::ValueWithError` object `
+   1. add column `@limit?` for printput of `RooFitResult` object to shwo the distance to the limits (if any). Distanc eof <3sigma, an d<5 sigma ar ecolored. Distances > 10sigma are omitted.
 
+    `   
 ## Backward incompatible
 
 ## Bug fixes

ostap/fitting/roofitresult.py

@@ -21,10 +21,11 @@
 from   ostap.core.meta_info     import root_info 
 from   ostap.core.core          import Ostap, VE, valid_pointer, iszero, isequal
 from   ostap.core.ostap_types   import string_types , integer_types
+from   ostap.utils.valerrors    import ValWithErrors, AsymErrors   
 import ostap.fitting.variables     
 import ostap.fitting.printable
 import ostap.math.linalg        as     LA 
-from   ostap.logger.colorized   import allright, attention
+from   ostap.logger.colorized   import allright, attention, attstr 
 from   ostap.logger.pretty      import pretty_float, pretty_ve, pretty_err2 
 import ROOT, math, sys, ctypes  
 # =============================================================================
@@ -593,7 +594,7 @@ def _rfr_evaluate_ ( self , func , args , partial = () ) :
 #  result.table() 
 #  @endcode 
 def _rfr_table_ ( rr , title = '' , prefix = '' , more_vars = {} ) :
-    """ print RooFitResult  as a table
+    """ Print RooFitResult  as a table
     >>> result = ...
     >>> result.table() 
     """
@@ -653,18 +654,63 @@ def _rfr_table_ ( rr , title = '' , prefix = '' , more_vars = {} ) :
         rows.append ( ( 'Invalid FCN/NLL evaluations' , '' , '  %d' % nbadnll , '' ) )
 
 
-    with_globcorr = not ( (6,24) <= root_info < (6,28) )
-    with_globcorr = True or not ( (6,24) <= root_info < (6,28) )
-    with_globcorr = not ( (6,24) <= root_info < (6,26) )
+    with_globcorr =         not ( ( 6 , 24 ) <= root_info < ( 6 , 28 ) )
+    with_globcorr = True or not ( ( 6 , 24 ) <= root_info < ( 6 , 28 ) )
+    with_globcorr =         not ( ( 6 , 24 ) <= root_info < ( 6 , 26 ) )
 
     with_globcorr = True 
 
-    if with_globcorr : rows = [ ( '', 'Unit', 'Value' , 'Global/max correlation [%]') ] + rows
-    else             : rows = [ ( '', 'Unit', 'Value' , 'Max correlation [%]') ] + rows
-
     pars_all   = r.params ( float_only = False )
     pars_float = r.params ( float_only = True  )
 
+    #
+    ## parameter close to the limits? 
+    # 
+    limits     = {}
+    threshold  = 10
+    for p in pars_float :
+
+        v , a = pars_float [ p ]
+
+        has_min = hasattr ( a , 'hasMin' ) and a.hasMin()
+        has_max = hasattr ( a , 'hasMax' ) and a.hasMax()
+
+        if has_min or has_max :
+
+            value = v.value()
+
+            if a.hasAsymError () : 
+                v = ValWithErrors ( a.getVal() , AsymErrors ( negative = a.getAsymErrorLo() , positive = a.getAsymErrorHi() ) )            
+
+            dmin , dmax  = -1, -1
+            if has_min and hasattr ( a , 'getMin' ) :
+                vmin = a.getMin()
+                verr = abs ( v.neg_error )
+                if   isequal ( vmin , value )  : dmin = 0   
+                elif vmin < value and 0 < verr : dmin = abs ( value - vmin ) / verr 
+
+            if has_max and hasattr ( a , 'getMax' ) :
+                vmax = a.getMax()
+                verr = abs ( v.pos_error )
+                if   isequal ( vmax , value )  : dmax = 0   
+                elif value < vmax and 0 < verr : dmax = abs ( value - vmax ) / verr 
+
+            dmn = ( 0 <= dmin < threshold ) 
+            dmx = ( 0 <= dmax < threshold ) 
+
+            if   dmn and dmx : limits [ a.name ] = min ( dmin , dmax ) 
+            elif dmn         : limits [ a.name ] = dmin
+            elif dmx         : limits [ a.name ] = dmax
+
+
+    if with_globcorr : header = ( '', 'Unit', 'Value' , 'Global/max correlation [%]') 
+    else             : header = ( '', 'Unit', 'Value' , 'Max correlation [%]') 
+
+    if limits : header   +=  ( '@limit?', ) 
+
+    rows = [ header ] + rows
+
+
     ## constant/fix parameters 
     crows = [] 
     for p in pars_all :
@@ -686,7 +732,7 @@ def _rfr_table_ ( rr , title = '' , prefix = '' , more_vars = {} ) :
 
         v , a = pars_float [ p ]
 
-        if not a.hasAsymError() :
+        if not a.hasAsymError () :
             s , n = pretty_ve   ( v ) 
         else :
             s , n = pretty_err2 (  a.getVal() , a.getAsymErrorHi() , a.getAsymErrorLo() )
@@ -720,6 +766,13 @@ def _rfr_table_ ( rr , title = '' , prefix = '' , more_vars = {} ) :
         else :
 
             row = p , n , s
+
+        dist = limits.get ( a.name , None )
+        if not dist is None :
+            item = '%.1fs' % dist 
+            if   dist <= 3 : item = attention ( item )
+            elif dist <= 5 : item = attstr    ( item )
+            row += ( item , )
 
         frows.append ( row ) 
 
@@ -747,7 +800,7 @@ def _rfr_table_ ( rr , title = '' , prefix = '' , more_vars = {} ) :
 
     import ostap.logger.table as T
 
-    return T.table ( all , title = title if title else r.GetTitle() , prefix = prefix , alignment = 'llll' )
+    return T.table ( all , title = title if title else r.GetTitle() , prefix = prefix , alignment = 'llllc' )
 
 # =============================================================================
 ## 'easy' print of RooFitResult

ostap/fitting/tests/test_fitting_models.py

@@ -191,6 +191,11 @@ def test_gauss() :
 
     models.add     ( model   )
     results.append ( result  )
+
+    with rooSilent() : 
+        result, frame = model. fitTo ( dataset0 , silent = True , minos = ( signal.mean.name, ) ) 
+
+    make_print ( model , result , 'Simple Gaussian model' , logger )
 
 # =============================================================================
 ## CrystalBall PDF
@@ -2000,10 +2005,11 @@ def dump_models () :
     ## simple Gaussian PDF                       + background
     with timing ('test_gauss'          , logger ) :
         test_gauss          () 
-        
+
     ## Crystal Ball                              + background
     with timing ('test_crystalball'    , logger ) :
         test_crystalball    () 
+
 
     ## right-side Crystal Ball                   + background
     with timing ('test_crystalball_RS' , logger ) :
@@ -2184,7 +2190,7 @@ def dump_models () :
     ## Hypatia                                     + background 
     with timing ('test_hypatia'           , logger ) :
         test_hypatia           ()
-
+    
     ## check finally that everything is serializeable:
     with timing ('test_db'             , logger ) :
         test_db ()

ostap/math/ve.py

@@ -60,7 +60,6 @@ def _ve_sum_ ( s ) :
     """
     return Ostap.Math.sum ( s )
 
-
 # ============================================================================= 
 ## Sum the contents of the vector
 def _ve_asum_ ( s ) :
@@ -269,7 +268,7 @@ def _ve_ne_ ( self , other ) :
 #  print ve.minmax(2)
 #  @endcode 
 def _ve_minmax_ ( s , n = 1 ) :
-    """Get an easy and coherent way to access ``min/max'' for
+    """ Get an easy and coherent way to access `min/max' for
     the value with error object:  (value-n*error,value+n*error)
     >>> ve = VE(2,2) 
     >>> print ve.minmax()
@@ -300,6 +299,52 @@ def _ve_hash_ ( v ) :
 
 VE.__hash__ = _ve_hash_
 
+# =============================================================================
+## Get the "positive" error
+#  @code
+#  ve = ...
+#  pos_error = ve.pos_error
+#  @endcode 
+def _ve_pos_error_ ( v ) :
+    """ Get the "positive" error
+    >>> ve = ...
+    >>> pos_error = ve.pos_error
+    """
+    err = v.error()
+    return err if 0 <= err else 0 
+
+# =============================================================================
+## Get the "negative" error
+#  @code
+#  ve = ...
+#  neg_error = ve.neg_error
+#  @endcode 
+def _ve_neg_error_ ( v ) :
+    """ Get the "negative" error
+    >>> ve = ...
+    >>> neg_error = ve.neg_error
+    """
+    err = v.error()
+    return -err if 0 <= err else 0 
+
+# =============================================================================
+## Get "negative&positive" errors
+#  @code
+#  ve = ...
+#  neg, pos = ve.errors () 
+#  @endcode  
+def _ve_errors_  ( v ) :
+    """ Get `negative&positive' errors
+    >>> ve = ...
+    >>> neg, pos = ve.errors () 
+    """
+    err = v.error()
+    return (-err,err) if 0 <= err else (0,0)
+
+VE.pos_error = property ( _ve_pos_error_ , None , None , _ve_pos_error_ .__doc__ ) 
+VE.neg_error = property ( _ve_neg_error_ , None , None , _ve_neg_error_ .__doc__ ) 
+VE.errors    = property ( _ve_errors_    , None , None , _ve_errors_    .__doc__ ) 
+
 # =============================================================================
 from random import gauss as _gauss     
 # =============================================================================

ostap/utils/valerrors.py

@@ -624,7 +624,7 @@ def __setstate__ ( self , state ) :
     # ==========================================================================
     ## conversion to string 
     def toString ( self , format = '( %+.5g -/%.5g +/%-.5g ) ' ) :
-        """Conversion to string
+        """ Conversion to string
         """
         return format % ( self.value , abs ( self.neg_error ) , self.pos_error )
 

source/include/Ostap/ValueWithError.h

@@ -48,8 +48,9 @@ namespace Ostap
     public:
       // ======================================================================
       /// constructor from the value and covariance 
-      ValueWithError ( const double value      = 0 , 
-                       const double covariance = 0 ) ;
+      ValueWithError
+      ( const double value      = 0 , 
+        const double covariance = 0 ) ;
       // ======================================================================
       /** constructor from the (value,error)-pair 
        *   - first  element is "value" 
@@ -331,9 +332,9 @@ namespace Ostap
     private:
       // ======================================================================
       /// the actual value 
-      double m_value ;                             //          the actual value 
+      double m_value { 0 } ;                       //          the actual value 
       /// the associated covariance
-      double m_cov2 ;                              // the associated covariance
+      double m_cov2  { 0 } ;                       // the associated covariance
       // ======================================================================
     } ;
     // ========================================================================