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)