db.close()
else:
logger.info('Existing weights DBASE will be used')
# =============================================================================
## make reweighting iterations
from ostap.tools.reweight import Weight, makeWeights, WeightingPlot, W2Data
from ostap.fitting.selectors import SelectorWithVars, Variable
import ostap.parallel.parallel_fill
# =============================================================================
## configuration of reweighting
weightings = (
## variable address in DB
Weight.Var('x', 'x-reweight'),
Weight.Var('y', 'y-reweight'),
Weight.Var(('x', 'y'), '2D-reweight'),
)
# =============================================================================
## variables to be used in MC-dataset
variables = [
Variable('x', 'x-var', 0, 20),
Variable('y', 'y-var', 0, 15),
]
selector = SelectorWithVars(variables,
'0<x && x<20 && 0<y && y<20',
silence=True)
mctree.process(selector, silent=True)
mcds_ = selector.data ## dataset
db.close()
else :
logger.info('Existing weights DBASE will be used')
#
## make reweighting iterations
#
from ostap.tools.reweight import Weight, makeWeights, WeightingPlot
from ostap.fitting.selectors import SelectorWithVars, Variable
## start iterations:
for iter in range ( 0 , maxIter ) :
weighting = (
## variable address in DB
Weight.Var( accessor = lambda s : s.x , address = 'x-reweight' ) ,
)
weighter = Weight( dbname , weighting )
## variables to be used in MC-dataset
variables = [
Variable ( 'pt_x' , 'pt_x' , 0 , 100 , lambda s : s.x ) ,
Variable ( 'weight' , 'weight' , accessor = weighter )
]
#
## create new "weighted" mcdataset
#
selector = SelectorWithVars (
variables ,
'0<x && x<100 '
db.close()
else :
logger.info('Existing weights DBASE will be used')
#
## make reweigthing iterations
#
from ostap.tools.reweight import Weight, makeWeights, WeightingPlot
from ostap.fitting.selectors import SelectorWithVars, Variable
## start iterations:
for iter in range ( 0 , maxIter ) :
weightings = (
## variable address in DB
Weight.Var ( lambda s : s.x , 'x-reweight' ) ,
Weight.Var ( lambda s : s.y , 'y-reweight' ) ,
Weight.Var ( lambda s : (s.x,s.y) , '2D-reweight' ) ,
)
weighter = Weight( dbname , weightings )
## variables to be used in MC-dataset
variables = [
Variable( 'x' , 'x-var' , 0 , 20 , lambda s : s.x ) ,
Variable( 'y' , 'y-var' , 0 , 15 , lambda s : s.y ) ,
Variable( 'weight' , 'weight' , accessor = weighter )
]
#
## create new "weighted" mcdataset
#
db.close()
else:
logger.info('Existing weights DBASE will be used')
#
## make reweighting iterations
#
from ostap.tools.reweight import Weight, makeWeights, WeightingPlot
from ostap.fitting.selectors import SelectorWithVars, Variable
## start iterations:
for iter in range(0, maxIter):
weighting = (
## variable address in DB
Weight.Var('x', address='x-reweight'), )
weighter = Weight(dbname, weighting)
## variables to be used in MC-dataset
variables = [
## Variable ( 'x' , 'x-variable' , 0 , 100 , lambda s : s.x ) ,
Variable('x', 'x-variable', 0, 100),
Variable('weight', 'weight', accessor=weighter)
]
#
## create new "weighted" mcdataset
#
selector = SelectorWithVars(variables, '0<x && x<100 ')
mctree.pprocess(selector, chunk_size=len(mctree) // 20)