format & re-enalbe the test with FrequentisCalculator

ostap/fitting/roostats.py

@@ -1183,7 +1183,7 @@ def __del__ ( self ) :
 
     @property
     def cloned_dataset ( self ) :
-        """'cloned_dataset' : get the CLONED dataset (actually used in calcualtor)"""
+        """'cloned_dataset' : get the CLONED dataset (actually used in calculator)"""
         return self.__cloned_dataset
 
     # ==============================================================================================
@@ -1487,15 +1487,12 @@ def scan_with_progress ( self , *values ) :
              2 <= values                                 and \
              isinstance ( values [ 1 ] , num_types     ) and \
              isinstance ( values [ 2 ] , num_types     ) :            
-            return self.scan_with_progress ( vrange ( values[1] , vales[2] , values[0] ) ) 
+            return self.scan_with_progress ( vrange ( values[1] , values [2] , values[0] ) ) 
 
         elif  1 == len ( values ) and isinstance ( values [ 0 ] , sequence_types  ) :
-
             for v in progress_bar ( values [ 0 ] , description = 'Scan:' ) :
-                self.__inverter.RunOnePoint ( v )
-
-        else :
-
+                self.__inverter.RunOnePoint ( v )                
+        else :            
             for v in progress_bar ( values , description = 'Scan:' ) :
                 self.__inverter.RunOnePoint ( v )
 
@@ -1553,7 +1550,7 @@ def plot ( self ) :
     # ========================================================================= 
     ## Reset/clear current interval & plot
     def reset  ( self ) :
-        """Reset/clear current interval & plot
+        """ Reset/clear current interval & plot
         """
         if self.__interval : self.__interval = None
         if self.__plot     : self.__plot = None 
@@ -1577,7 +1574,7 @@ def reset  ( self ) :
 #  p.draw('a')
 #  @endcode 
 class BrasilBand(object) :
-    """Helper class to create and keep the 'Brasil-band' plot
+    """ Helper class to create and keep the 'Brasil-band' plot
     >>> bp = BrasilBand( sigmas = (1,2,3) )  ## draw 1,2&3-sigma bands 
     >>> for value  in [ ... ] :
     >>>     ...
@@ -1621,7 +1618,7 @@ def __init__  ( self               ,
     # =========================================================================
     ## Add the point to the Brasil-plot
     def fill ( self , x , observed , hti_result ) : 
-        """Add the point to the Brasil-plot
+        """ Add the point to the Brasil-plot
         """
         expected = tuple ( hti_result.GetExpectedUpperLimit ( s ) for s in self.__nsigmas )
         self.__data [ x ] = observed, expected
@@ -1740,7 +1737,7 @@ def legend ( self )  :
     # ===========================================================================
     ## number of points in the graph 
     def __len__ ( self ) :
-        """Number of points in the graph
+        """ Number of points in the graph
         """
         return len ( self.__data ) 
 
@@ -1763,7 +1760,7 @@ def __len__ ( self ) :
 #  @endcode
 #  @thanks Dima Golubkov 
 class P0Plot(object) :
-    """Helper class to create graphs(s) for p0-scan plot
+    """ Helper class to create graphs(s) for p0-scan plot
     >>> plot = P0Plot() 
     >>> for ,,, :
     ...    value       = ...
@@ -1774,7 +1771,7 @@ class P0Plot(object) :
     >>> plot.p0         .draw ( 'ac') ## plot p-values 
     >>> plot.p0_expected.draw ( 'c' ) ## plot expected p-values 
     >>> plot.sigmas     .draw ( 'ac') ## plot #sigmas  
-    - thanks to Dima Golubkov 
+    - thanks to Dima Golubkov! 
     """
     def __init__ ( self ) :
 
@@ -1809,7 +1806,7 @@ def __init__ ( self ) :
     #     plot.fill ( value , calculator ) 
     #  @endcode
     def fill ( self , value , *what ) :
-        """Add the point to TGraph(s
+        """ Add the point to TGraph(s
         
         - Full version 
         >>> plot = P0Plot() 

ostap/fitting/tests/test_fitting_roostats1.py

@@ -34,10 +34,6 @@
 else : 
     logger = getLogger ( __name__ )
 # =============================================================================
-
-
-
-# ============================================================================
 ## Test the confidence intervals for the width of low-statistic gaussian ssignal
 #  
 #  - Profile likelihood confidence interval 

ostap/fitting/tests/test_fitting_roostats3.py

@@ -61,11 +61,11 @@
 
 graphs = [] 
 # ============================================================================-
-## Scan the positon of the peak and get the limit for each peak posiiton peak
+## Scan the position of the peak and get the limit for each peak posiiton peak
 #  - resolution is known with some finite precision 
 #  - efficiency is known with some finite precision 
 def test_scan_limit1 () :
-    """Scan the positon of the peak and get the limit for each peak posiiton peak
+    """Scan the position of the peak and get the limit for each peak posiiton peak
     - resolution is known with some finite precision 
     - efficiency is known with some finite precision 
     """
@@ -169,7 +169,7 @@ def test_scan_limit1 () :
 
         graphs.append ( bplot ) 
 # ============================================================================-
-## Scan the positon of the peak and get the limit for each peak posiiton peak
+## Scan the position of the peak and get the limit for each peak posiiton peak
 #  - mass-dependent resolution is known with some finite precision
 #  - mass-dependent efficiency is known with some finite precision 
 def test_scan_limit2 () :
@@ -314,19 +314,19 @@ def test_scan_limit2 () :
         bplot.plot  .draw ( 'a' )
         bplot.legend.draw (     )
 
-        title = '90% Upper limits'
+        title = '90% Upper limit'
         table = T.table ( rows , title = title , prefix = '# ' , alignment = 'lr' )
         logger.info ( '%s:\n%s' % ( title , table ) )
 
         graphs.append ( bplot ) 
 
 # ============================================================================-
-## Scan the positon of the peak and get the p0 
+## Scan the position of the peak and get the p0 
 #  - resolution is known with some finite precision 
 #  - efficiency is known with some finite precision
 #  @thanks to Dima Golubkov 
 def test_scan_p0_1 () :
-    """Scan the positon of the peak and get p0 for each peak position peak
+    """ Scan the position of the peak and get p0 for each peak position peak
     - resolution is known with some finite precision 
     - efficiency is known with some finite precision 
     - thanks to Dima Golubkov 
@@ -444,10 +444,10 @@ def test_scan_p0_1 () :
 
     with rooSilent ( ) : 
 
-        ## test_scan_limit1    ()
-        ## test_scan_limit2    ()
+        test_scan_limit1    ()
+        test_scan_limit2    ()
 
-        test_scan_p0_1      ()
+        ## test_scan_p0_1      ()
 
 # =============================================================================
 ##                                                                      The END 

ostap/fitting/tests/test_fitting_roostats4.py

@@ -131,7 +131,7 @@
 ## Get the upper limit limit for small signal at fixed mass
 #  - Asymptotic Calculator is used 
 def test_limit_ac_1 () :
-    """Get the upper limit at given point for small signal at fixed mass
+    """ Get the upper limit at given point for small signal at fixed mass
     - Asymptotic Calculator is used 
     """
 
@@ -278,7 +278,7 @@ def test_limit_ac_2 () :
 ## Get the upper limit limit for small signal at fixed mass
 #  - Frequentists Calculator is used 
 def test_limit_fc_1 () :
-    """Get the upper limit at given point for small signal at fixed mass
+    """ Get the upper limit at given point for small signal at fixed mass
     - Friquentists Calculator is used 
     """
 
@@ -297,7 +297,7 @@ def test_limit_fc_1 () :
     constraints = constraint , eff_constraint 
 
     logger.info ( 'Dataset is\n%s' % the_data.table ( prefix = '# ' ) ) 
-    rr , frame = the_model.fitTo ( the_data , nbins = 100 , constraints = constraints )
+    rr , frame = the_model.fitTo ( the_data , nbins = 100 , constraints = constraints , silent = True )
     with use_canvas ( 'test_limit_ac_2:data' ) : the_model.draw ( the_data , nbins = 100 )
     title = 'Results of the fit'
     logger.info ( '%s\n%s' % ( title , rr.table ( title = title , prefix = '# ' ) ) )
@@ -335,14 +335,13 @@ def test_limit_fc_1 () :
                                       model_sb              ,
                                       dataset    = the_data ,
                                       ntoys_null = 100      ,
-                                      ntoys_alt  = 100      ,
-                                      ) 
+                                      ntoys_alt  = 100      ) 
 
         ## create Hypo Test inverter 
         hti = HypoTestInverter ( fc ,  0.90 , use_CLs = True , verbose = False )
 
         ## make a scan 
-        hti .scan_with_progress ( vrange ( 1.e-3 , 0.5 , 25 )  ) ## scan it!
+        hti .scan_with_progress ( vrange ( 1.e-3 , 0.4 , 20 )  ) ## scan it!
 
     ## visualize the scan results 
     with use_canvas ( 'test_limit_fc_1: HypoTestInverter plot (frequentist)' , wait = 2 ) :
@@ -355,7 +354,7 @@ def test_limit_fc_1 () :
 
     test_limit_ac_1 () 
     test_limit_ac_2 ()    
-    ## test_limit_fc_1 () 
+    test_limit_fc_1 () 
 
 # =============================================================================
 ##                                                                      The END