LHCbMath:

LHCbMath:

• Bernstein3D*: add missing methods

this MR for 2018-patches and master

Kernel/LHCbMath/tests/test_B2D.py

@@ -31,7 +31,7 @@ print 'Check for constant 2D-polynomial      is OK'
 # 2) create & evaluate  symmetric 
 BP2DS = ROOT.Gaudi.Math.Bernstein2DSym
 
-b = BP2DS ( 5 , 0. , 2. ) ## 5x2th order for x,y in [0,2] 
+b = BP2DS ( 2 , 0. , 2. ) ## 2x2th order for x,y in [0,2] 
 for i in  range ( b.npars() ) : b.setPar(i,1)
 
 sc = (b.xmax()-b.xmin())*(b.ymax()-b.ymin())/((b.nX()+1)*(b.nY()+1))
@@ -54,8 +54,8 @@ print 'Check for symmetric 2D-polynomial(x2) is OK'
 
 # 3) check integrals
 
-b = BP2D ( 5 , 5 , 0. ,  1 , 0 , 2 ) ## 5x2th order for x,y in [0,2] 
-for i in  range ( b.npars() ) : b.setPar(i,   random.uniform(-10,10) )
+b = BP2D ( 2 , 2 , 0. ,  1 , 0 , 2 ) ## 2x2th order for x,y in [0,2] 
+for i in  range ( b.npars() ) : b.setPar(i,   random.uniform(-1,1) )
 
 tiny = 1.e-7
 i  = b.integral()
@@ -73,11 +73,14 @@ check_equality ( i , fi , 'Invalid integrals[1]' , 1.e-4 )
 
 print 'Check for integrals[1]                is OK'
 
-for i in  range(100) :
-    x1  = random.uniform ( b.xmin() , b.xmax() )
-    x2  = random.uniform ( x1       , b.xmax() )
-    y1  = random.uniform ( b.ymin() , b.ymax() )
-    y2  = random.uniform ( y1       , b.ymax() )
+xmid = 0.5*(b.xmin()+b.xmax())
+ymid = 0.5*(b.ymin()+b.ymax())
+
+for i in  range(20) :
+    x1  = random.uniform ( b.xmin() ,   xmid   )
+    x2  = random.uniform (   xmid   , b.xmax() )
+    y1  = random.uniform ( b.ymin() ,   ymid   )
+    y2  = random.uniform (   ymid   , b.ymax() )
     z1  =  b (x1,y1)
     z2  =  b (x2,y2)
     v1  =  f1(x1,y1)
@@ -93,8 +96,8 @@ del f1, _f1
 print 'Check for integrals[2]                is OK'
 
 
-b = BP2DS ( 5 , 0. , 2. ) ## 5x2th order for x,y in [0,2] 
-for i in  range ( b.npars() ) : b.setPar(i,   random.uniform(-10,10) )
+b = BP2DS ( 2 , 0. , 2. ) ## 5x2th order for x,y in [0,2] 
+for i in  range ( b.npars() ) : b.setPar(i,   random.uniform(-1,1) )
 
 i  = b.integral() 
 ii = b.integral( b.xmin() + tiny , b.xmax() - tiny ,
@@ -105,7 +108,7 @@ def _f2 ( x , pars = [] ) :
     return b( x[0] , x[1] )
 f2 = ROOT.TF2('f2',_f2, b.xmin() ,b.xmax() ,  b.ymin(),  b.ymax() )
 fi = f2.Integral( b.xmin() ,b.xmax() ,  b.ymin(),  b.ymax() )
-check_equality ( i , fi , 'Invalid integrals[4]' , 1.e-4 ) 
+check_equality ( i , fi , 'Invalid integrals[3]' , 1.e-4 ) 
 
 print 'Check for integrals[3]                is OK'
 
@@ -124,7 +127,7 @@ for i in  range(10) :
     check_equality ( z2 , v2       , 'Invalid values' , 1.e-6 )     
     i   = b.integral  ( x1 , x2 ,  y1 ,  y2 )
     fi  = f2.Integral ( x1 , x2 ,  y1 ,  y2 )
-    check_equality ( i , fi , 'Invalid integrals[2]' , 1.e-4 ) 
+    check_equality ( i , fi , 'Invalid integrals[4]' , 1.e-4 ) 
     
 del f2, _f2     
 print 'Check for integrals[4]                is OK'
@@ -132,7 +135,7 @@ print 'Check for integrals[4]                is OK'
 ## positive polynomials 
 
 BP2DP = ROOT.Gaudi.Math.Positive2D
-b     = BP2DP ( 5 , 5 ,  0 , 2 , 0 , 2 ) 
+b     = BP2DP ( 2 , 2 ,  0 , 2 , 0 , 2 ) 
 
 for i in  range(100) :    
     x1  = random.uniform ( b.xmin() , b.xmax() )
@@ -167,7 +170,7 @@ print 'Check for integrals[5]                is OK'
 ## positive symmetric polynomials 
 
 BP2DPS = ROOT.Gaudi.Math.Positive2DSym
-b     = BP2DPS ( 5 , 0 , 2 ) 
+b     = BP2DPS ( 2 , 0 , 2 ) 
 
 for i in  range(100) :    
     x1  = random.uniform ( b.xmin() , b.xmax() )
@@ -198,11 +201,13 @@ ii = b.integral( b.xmin() + tiny , b.xmax() - tiny ,
 fi = f4.Integral( b.xmin() ,b.xmax() ,  b.ymin(),  b.ymax() )
 check_equality ( i , fi , 'Invalid integrals[7]' , 1.e-4 ) 
 
+xmid = 0.5*(b.xmin()+b.xmax())
+ymid = 0.5*(b.ymin()+b.ymax())
 for i in  range(100) :    
-    x1  = random.uniform ( b.xmin() , b.xmax() )
-    y1  = random.uniform ( b.ymin() , b.ymax() )
-    x2  = random.uniform ( x1       , b.xmax() )
-    y2  = random.uniform ( y1       , b.ymax() )
+    x1  = random.uniform ( b.xmin() ,   xmid   )
+    y1  = random.uniform ( b.ymin() ,   ymid   )
+    x2  = random.uniform (   xmid   , b.xmax() )
+    y2  = random.uniform (   ymid   , b.ymax() )
     
     i  = b .integral ( x1 , x2 ,  y1  ,  y2 )
     fi = f4.Integral ( x1 , x2 ,  y1  ,  y2 )