dataset2.project ( h3 , x . GetName () )
dataset2.project ( h4 , x . GetName () )
dataset2.project ( h5 , x . GetName () )
h1s = h1.rescale_bins ( 1 )
h2s = h2.rescale_bins ( 1 )
h3s = h3.rescale_bins ( 1 )
h4s = h4.rescale_bins ( 1 )
h5s = h5.rescale_bins ( 1 )
# =============================================================================
logger.info('Test Gamma-Distribution')
# =============================================================================
m_gamma = Models.GammaDist_pdf( 'GD1' , x )
with rooSilent() :
result,f = m_gamma.fitTo ( dataset2 )
result,f = m_gamma.fitTo ( dataset2 )
if 0 != result.status() or 3 != result.covQual() :
logger.warning('Fit is not perfect MIGRAD=%d QUAL=%d ' % ( result.status() , result.covQual() ) )
print result
else :
print "\tGamma: k = %s " % result( m_gamma.k.GetName() )[0]
print "\tGamma: theta= %s " % result( m_gamma.theta.GetName() )[0]
# =============================================================================
logger.info("Test 2-expo-distribution")
# =============================================================================
m_2expo = Models.TwoExpos_pdf( '2exp' , x )
increasing = Models.Monothonic_pdf('PI', mass4, power=3, increasing=True)
decreasing = Models.Monothonic_pdf('PD', mass4, power=3, increasing=False)
inc_convex = Models.Convex_pdf('PIX',
mass4,
power=3,
increasing=True,
convex=True)
dec_convex = Models.Convex_pdf('PDX',
mass4,
power=3,
increasing=False,
convex=True)
convex = Models.ConvexOnly_pdf('PX', mass4, power=3, convex=True)
concave = Models.ConvexOnly_pdf('PX', mass4, power=3, convex=False)
with timing('Positive 5'), rooSilent():
r5, f = positive.fitTo(dataset5)
with timing('Increasing 5'), rooSilent():
i5, f = increasing.fitTo(dataset5)
with timing('Convex 5'), rooSilent():
x4, f = inc_convex.fitTo(dataset5)
with timing('ConvexOnly 5'), rooSilent():
c4, f = convex.fitTo(dataset5)
## logger.info ( 'Positive pars: %s' % positive .pdf.function().pars() )
## logger.info ( 'Increasing pars: %s' % increasing.pdf.function().pars() )
## logger.info ( 'Convex pars: %s' % inc_convex.pdf.function().pars() )
for i in (positive, increasing, inc_convex, convex):
pars = i.pdf.function().bernstein().pars()
pars = list(pars)