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ModelTools.py
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ModelTools.py
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from __future__ import absolute_import, print_function
import os
import os.path
import re
from functools import reduce
from math import *
from sys import exit, stderr, stdout
import six
from six.moves import range
from collections import OrderedDict
import ROOT
ROOFIT_EXPR = "expr"
ROOFIT_EXPR_PDF = "EXPR"
class SafeWorkspaceImporter:
"""Class that provides the RooWorkspace::import method, but makes sure we call the proper
overload of it, since in ROOT 6 sometimes PyROOT calls the wrong one"""
def __init__(self, wsp):
self.wsp = wsp
self.imp = getattr(wsp, "import")
def __call__(self, *args):
if len(args) != 1:
self.imp(*args)
elif (
args[0].Class().InheritsFrom("RooAbsReal")
or args[0].Class().InheritsFrom("RooArgSet")
or args[0].Class().InheritsFrom("RooAbsData")
or args[0].Class().InheritsFrom("RooCategory")
):
self.imp(args[0], ROOT.RooCmdArg()) # force the proper overload to be called
else:
self.imp(*args)
class ModelBuilderBase:
"""This class defines the basic stuff for a model builder, and it's an interface on top of RooWorkspace::factory or HLF files"""
def __init__(self, options):
self.options = options
self.out = stdout
self.discrete_param_set = []
if options.bin:
if options.out == None:
options.out = re.sub(".txt$", "", options.fileName) + ".root"
options.baseDir = os.path.dirname(options.fileName)
ROOT.gSystem.Load("libHiggsAnalysisCombinedLimit")
ROOT.TH1.AddDirectory(False)
self.out = ROOT.RooWorkspace("w", "w")
# self.out.safe_import = getattr(self.out,"import") # workaround: import is a python keyword
self.out.safe_import = SafeWorkspaceImporter(self.out)
self.objstore = OrderedDict()
self.out.dont_delete = []
if options.verbose == 0:
ROOT.RooMsgService.instance().setGlobalKillBelow(ROOT.RooFit.ERROR)
elif options.verbose < 3:
ROOT.RooMsgService.instance().setGlobalKillBelow(ROOT.RooFit.WARNING)
if "ROOFITSYS" in os.environ:
ROOT.gSystem.AddIncludePath(" -I%s/include " % os.environ["ROOFITSYS"])
elif options.out != None:
# stderr.write("Will save workspace to HLF file %s" % options.out)
self.out = open(options.out, "w")
if not options.bin:
stderr.write("\nWARNING: You're not using binary mode. This is is DEPRECATED and NOT SUPPORTED anymore, and can give WRONG results.\n\n")
if options.cexpr:
global ROOFIT_EXPR
ROOFIT_EXPR = "cexpr"
def addObj(self, classtype, name, *args):
if name not in self.objstore:
self.objstore[name] = classtype(name, *args)
return self.objstore[name]
def getObj(self, name):
if name not in self.objstore:
raise RuntimeError("Requested object %s not found in store" % name)
return self.objstore[name]
def renameObj(self, currName, newName):
if currName not in self.objstore:
raise RuntimeError("Requested object %s not found in store" % name)
self.objstore[currName].SetName(newName)
self.objstore[newName] = self.objstore.pop(currName)
def factory_(self, X):
if self.options.verbose >= 7:
print("RooWorkspace::factory('%s')" % X)
if len(X) > 1000:
print(
"Executing factory with a string of length ",
len(X),
" > 1000, could trigger a bug: ",
X,
)
ret = self.out.factory(X)
if ret:
if self.options.verbose >= 7:
print(" ---> ", ret)
self.out.dont_delete.append(ret)
return ret
else:
print("ERROR parsing '%s'" % X)
self.out.Print("V")
raise RuntimeError("Error in factory statement")
def doComment(self, X):
if not self.options.bin:
self.out.write("// " + X + "\n")
def doVar(self, vardef):
if self.options.bin:
self.factory_(vardef)
else:
self.out.write(vardef + ";\n")
def doExp(self, name, expression, vars):
if self.options.bin:
self.factory_('expr::%s("%s",%s)' % (name, expression, vars))
else:
self.out.write('%s = expr::%s("%s",%s)' % (name, name, expression, vars) + ";\n")
def doSet(self, name, vars):
if self.options.bin:
self.out.defineSet(name, vars)
else:
self.out.write("%s = set(%s);\n" % (name, vars))
def doObj(self, name, type, X, ignoreExisting=False):
if self.out.obj(name) and ignoreExisting:
return 1 # Still complain if not explicitly told to ignore the existing object
if self.options.bin:
return self.factory_("%s::%s(%s)" % (type, name, X))
else:
self.out.write("%s = %s(%s);\n" % (name, type, X))
def addDiscrete(self, var):
if self.options.removeMultiPdf:
return
self.discrete_param_set.append(var)
class ModelBuilder(ModelBuilderBase):
"""This class defines the actual methods to build a model"""
def __init__(self, datacard, options):
ModelBuilderBase.__init__(self, options)
self.DC = datacard
self.doModelBOnly = True
self.selfNormBins = []
self.extraNuisances = []
self.extraGlobalObservables = []
self.globalobs = []
def getSafeNormName(self, n):
# need to be careful in case user has _norm name and wants to auto-create flatPrior
if self.options.flatParamPrior:
if n in self.DC.pdfnorms.keys():
return self.DC.pdfnorms[n]
return n
def setPhysics(self, physicsModel):
self.physics = physicsModel
self.physics.setModelBuilder(self)
def doModel(self, justCheckPhysicsModel=False):
if not justCheckPhysicsModel:
self.doObservables()
self.physics.doParametersOfInterest()
# set a group attribute on POI variables
poiIter = self.out.set("POI").createIterator()
poi = poiIter.Next()
while poi:
self.out.var(poi.GetName()).setAttribute("group_POI", True)
poi = poiIter.Next()
self.physics.preProcessNuisances(self.DC.systs)
self.doNuisances()
self.doExtArgs()
self.doRateParams()
self.doAutoFlatNuisancePriors()
self.doFillNuisPdfsAndSets()
self.doExpectedEvents()
if justCheckPhysicsModel:
self.physics.done()
print("Model is OK")
exit(0)
self.doIndividualModels()
self.doNuisancesGroups() # this needs to be called after both doNuisances and doIndividualModels
self.doCombination()
self.runPostProcesses()
self.physics.done()
if self.options.bin:
self.doModelConfigs()
if self.options.verbose > 1:
self.out.Print("tv")
if self.options.verbose > 2:
self.out.pdf("model_s").graphVizTree(self.options.out + ".dot", "\\n")
print("Wrote GraphVizTree of model_s to ", self.options.out + ".dot")
def getRenamingParameters(self):
toFreeze = []
renameParamString = []
paramString = []
for n in self.DC.systematicsParamMap.keys():
paramString.append(n)
renameParamString.append(self.DC.systematicsParamMap[n])
if n != self.DC.systematicsParamMap[n]:
toFreeze.append(n)
if len(renameParamString):
renameParamString = ",".join(renameParamString)
paramString = ",".join(paramString)
return paramString, renameParamString, toFreeze
def runPostProcesses(self):
for n in self.DC.frozenNuisances:
self.out.arg(n).setConstant(True)
def doExtArgs(self):
open_files = OrderedDict()
for rp in self.DC.extArgs.keys():
if self.out.arg(rp):
continue
argv = self.DC.extArgs[rp][-1]
if ":" in argv:
split = argv.split(":")
importargs = []
if "RecycleConflictNodes" in split:
split.remove("RecycleConflictNodes")
importargs.append(ROOT.RooFit.RecycleConflictNodes())
fin, wsn = split
if (fin, wsn) in open_files:
wstmp = open_files[(fin, wsn)]
if not wstmp.arg(rp):
raise RuntimeError("No parameter '%s' found for extArg in workspace %s from file %s" % (rp, wsn, fin))
self.out.safe_import(wstmp.arg(rp), *importargs)
else:
fitmp = ROOT.TFile.Open(fin)
if not fitmp:
raise RuntimeError("No File '%s' found for extArg" % fin)
wstmp = fitmp.Get(wsn)
if not wstmp:
raise RuntimeError("Workspace '%s' not in file %s" % (wsn, fin))
if not wstmp.arg(rp):
raise RuntimeError("No parameter '%s' found for extArg in workspace %s from file %s" % (rp, wsn, fin))
self.out.safe_import(wstmp.arg(rp), *importargs)
open_files[(fin, wsn)] = wstmp
else:
param_range = ""
param_val = self.DC.extArgs[rp][-1]
if len(self.DC.extArgs[rp]) > 3: # range is included:
param_range = self.DC.extArgs[rp][-1]
param_val = self.DC.extArgs[rp][-2]
if "[" not in param_range:
raise RuntimeError("Expected range arguments [min,max] or [const] for extArg %s " % (rp))
param_range = param_range.strip("[]")
removeRange = False
setConst = param_range == "const"
if param_range in ["", "const"]:
v = float(param_val)
param_range = "%g,%g" % (-2.0 * abs(v), 2.0 * abs(v))
removeRange = True
self.doVar("%s[%s,%s]" % (rp, float(param_val), param_range))
if removeRange:
self.out.var(rp).removeRange()
self.out.var(rp).setConstant(False)
if setConst:
self.out.var(rp).setConstant(True)
self.out.var(rp).setAttribute("flatParam")
def doRateParams(self):
# First support external functions/parameters
# keep a map of open files/workspaces
open_files = OrderedDict()
for rp in self.DC.rateParams.keys():
for rk in range(len(self.DC.rateParams[rp])):
type = self.DC.rateParams[rp][rk][0][-1]
if type != 2:
continue
argu, argv = (
self.DC.rateParams[rp][rk][0][0],
self.DC.rateParams[rp][rk][0][1],
)
if self.out.arg(argu):
continue
fin, wsn = argv.split(":")
if (fin, wsn) in open_files:
wstmp = open_files[(fin, wsn)]
if not wstmp.arg(argu):
raise RuntimeError("No parameter '%s' found for rateParam in workspace %s from file %s" % (argu, wsn, fin))
self.out.safe_import(wstmp.arg(argu), ROOT.RooFit.RecycleConflictNodes())
else:
fitmp = ROOT.TFile.Open(fin)
if not fitmp:
raise RuntimeError("No File '%s' found for rateParam" % fin)
wstmp = fitmp.Get(wsn)
if not wstmp:
raise RuntimeError("Workspace '%s' not in file %s" % (wsn, fin))
if not wstmp.arg(argu):
raise RuntimeError("No parameter '%s' found for rateParam in workspace %s from file %s" % (argu, wsn, fin))
self.out.safe_import(wstmp.arg(argu), ROOT.RooFit.RecycleConflictNodes())
open_files[(fin, wsn)] = wstmp
# fitmp.Close()
# First do independant parameters, then expressions
for rp in self.DC.rateParams.keys():
for rk in range(len(self.DC.rateParams[rp])):
type = self.DC.rateParams[rp][rk][0][-1]
if type != 0:
continue
param_range = (self.DC.rateParams[rp][rk][1]).strip("[]")
argu, argv = (
self.DC.rateParams[rp][rk][0][0],
self.DC.rateParams[rp][rk][0][1],
)
if self.out.arg(argu):
continue
v = float(argv)
removeRange = len(param_range) == 0
if param_range == "":
if self.options.flatParamPrior:
raise ValueError(
"Cannot create flat Prior for rateParam nuisance parameter '"
+ argu
+ "' without specifying a range [a,b]. Please fix in the datacard"
)
## check range. The parameter needs to be created in range. Then we will remove it
param_range = "%g,%g" % (-2.0 * abs(v), 2.0 * abs(v))
# additional check for range requested
lo_r, hi_r = map(float, param_range.split(","))
if v < lo_r or v > hi_r:
raise ValueError("Parameter: " + argu + " asked to be created out-of-range (it will lead to an error): " + argv + ":" + param_range)
self.doVar("%s[%s,%s]" % (argu, argv, param_range))
if removeRange:
self.out.var(argu).removeRange()
self.out.var(argu).setConstant(False)
self.out.var(argu).setAttribute("flatParam")
# functions are tricky (functions of functions?)
toBeCreated = []
for rp in self.DC.rateParams.keys():
for rk in range(len(self.DC.rateParams[rp])):
type = self.DC.rateParams[rp][rk][0][-1]
if type != 1:
continue
argu, arge, argv = (
self.DC.rateParams[rp][rk][0][0],
self.DC.rateParams[rp][rk][0][1],
self.DC.rateParams[rp][rk][0][2],
)
if self.out.arg(argu):
continue
if not reduce(
lambda x, y: x * y,
[self.out.arg(a) != None for a in argv.split(",")],
1,
):
toBeCreated.append([argu, arge, argv])
else:
self.doExp(argu, arge, argv)
# by now we 've probably picked up the majority of the, repeat through list until we get them all
tbc = toBeCreated[:]
while True:
toBeCreated = tbc[:]
if len(toBeCreated) == 0:
break
for rp in toBeCreated:
argu, arge, argv = rp[0], rp[1], rp[2]
if reduce(
lambda x, y: x * y,
[self.out.arg(a) != None for a in argv.split(",")],
1,
):
self.doExp(argu, arge, argv)
tbc.remove([argu, arge, argv])
if len(tbc) == len(toBeCreated):
print(tbc, " -> ", toBeCreated)
raise RuntimeError("Cannot produce following rateParams (dependent parameters not found!) %s" % (",".join([t[0] for t in toBeCreated])))
def doObservables(self):
"""create pdf_bin<X> and pdf_bin<X>_bonly for each bin"""
raise RuntimeError("Not implemented in ModelBuilder")
def doNuisances(self):
for cpar in self.DC.discretes:
self.addDiscrete(cpar)
if len(self.DC.systs) == 0:
return
self.doComment(" ----- nuisances -----")
# globalobs = []
for n, nofloat, pdf, args, errline in self.DC.systs:
is_func_scaled = False
func_scaler = None
for pn, pf in self.options.nuisanceFunctions:
if re.match(pn, n):
is_func_scaled = True
func_scaler = pf
if self.options.verbose > 1:
print("Rescaling %s constraint as %s" % (n, pf))
for pn, pf in self.options.nuisanceGroupFunctions:
if pn in self.DC.groups and n in self.DC.groups[pn]:
is_func_scaled = True
func_scaler = pf
if self.options.verbose > 1:
print("Rescaling %s constraint (in group %s) as %s" % (n, pn, pf))
if pdf == "lnN" or (pdf.startswith("shape") and pdf != "shapeU"):
r = "-4,4" if pdf == "shape" else "-7,7"
sig = 1.0
for pn, pf in self.options.nuisancesToRescale:
if re.match(pn, n):
sig = float(pf)
sigscale = sig * (4 if pdf == "shape" else 7)
r = "-%g,%g" % (sigscale, sigscale)
sig = "%g" % sig
if is_func_scaled:
sig = func_scaler
r_exp = "" if self.out.var(n) else "[%s]" % r # Specify range to invoke factory to produce a RooRealVar only if it doesn't already exist
if self.options.noOptimizePdf or is_func_scaled:
self.doObj(
"%s_Pdf" % n,
"Gaussian",
"%s%s, %s_In[0,%s], %s" % (n, r_exp, n, r, sig),
True,
)
# Use existing constraint since it could be a param
if is_func_scaled:
boundHi = self.doObj("%s_BoundHi" % n, "prod", "5, %s" % sig)
boundLo = self.doObj("%s_BoundLo" % n, "prod", "-5, %s" % sig)
self.out.var(n).setRange(boundLo, boundHi)
else:
self.doObj(
"%s_Pdf" % n,
"SimpleGaussianConstraint",
"%s%s, %s_In[0,%s], %s" % (n, r_exp, n, r, sig),
True,
)
# Use existing constraint since it could be a param
self.out.var(n).setVal(0)
self.out.var(n).setError(1)
self.globalobs.append("%s_In" % n)
if self.options.bin:
self.out.var("%s_In" % n).setConstant(True)
if self.options.optimizeBoundNuisances and not is_func_scaled:
self.out.var(n).setAttribute("optimizeBounds")
elif pdf == "gmM":
val = 0
for c in errline.values(): # list channels
for v in c.values(): # list effects in each channel
if v != 0:
if val != 0 and v != val:
raise RuntimeError("Error: line %s contains two different uncertainties %g, %g, which is not supported for gmM" % (n, v, val))
val = v
if val == 0:
raise RuntimeError("Error: line %s contains all zeroes")
theta = val * val
kappa = 1 / theta
self.doObj(
"%s_Pdf" % n,
"Gamma",
"%s[1,%f,%f], %s_In[%g,%g,%g], %s_scaling[%g], 0"
% (
n,
max(0.01, 1 - 5 * val),
1 + 5 * val,
n,
kappa,
1,
2 * kappa + 4,
n,
theta,
),
)
self.globalobs.append("%s_In" % n)
if self.options.bin:
self.out.var("%s_In" % n).setConstant(True)
elif pdf == "gmN":
if False:
# old version, that creates a poisson with a very large range
self.doObj(
"%s_Pdf" % n,
"Poisson",
"%s_In[%d,0,%d], %s[0,%d], 1" % (n, args[0], 2 * args[0] + 5, n, 2 * args[0] + 5),
)
else:
# new version, that creates a poisson with a narrower range (but still +/- 7 sigmas)
# print "Searching for bounds for",n,"poisson with obs",args[0]
minExp = args[0] + 1 if args[0] > 0 else 0
while (ROOT.TMath.Poisson(args[0], minExp) > 1e-12) and minExp > 0:
# print "Poisson(%d, minExp = %f) = %g > 1e-12" % (args[0], minExp, ROOT.TMath.Poisson(args[0], minExp))
minExp *= 0.8
maxExp = args[0] + 1
while ROOT.TMath.Poisson(args[0], maxExp) > 1e-12:
# print "Poisson(%d, maxExp = %f) = %g > 1e-12" % (args[0], maxExp, ROOT.TMath.Poisson(args[0], maxExp))
maxExp *= 1.2
minObs = args[0]
while minObs > 0 and (ROOT.TMath.Poisson(minObs, args[0] + 1) > 1e-12):
# print "Poisson(minObs = %d, %f) = %g > 1e-12" % (minObs, args[0]+1, ROOT.TMath.Poisson(minObs, args[0]+1))
minObs -= sqrt(args[0]) if args[0] > 10 else 1
maxObs = args[0] + 2
while ROOT.TMath.Poisson(maxObs, args[0] + 1) > 1e-12:
# print "Poisson(maxObs = %d, %f) = %g > 1e-12" % (maxObs, args[0]+1, ROOT.TMath.Poisson(maxObs, args[0]+1))
maxObs += sqrt(args[0]) if args[0] > 10 else 2
self.doObj(
"%s_Pdf" % n,
"Poisson",
"%s_In[%d,%f,%f], %s[%f,%f,%f], 1" % (n, args[0], minObs, maxObs, n, args[0] + 1, minExp, maxExp),
)
self.globalobs.append("%s_In" % n)
if self.options.bin:
self.out.var("%s_In" % n).setConstant(True)
elif pdf == "trG":
trG_min = -7
trG_max = +7
for b in errline.keys():
for v in errline[b].values():
if v > 0 and 1.0 + trG_min * v < 0:
trG_min = -1.0 / v
if v < 0 and 1.0 + trG_max * v < 0:
trG_max = -1.0 / v
r = "%f,%f" % (trG_min, trG_max)
self.doObj("%s_Pdf" % n, "Gaussian", "%s[0,%s], %s_In[0,%s], 1" % (n, r, n, r))
self.globalobs.append("%s_In" % n)
if self.options.bin:
self.out.var("%s_In" % n).setConstant(True)
elif pdf == "lnU" or pdf == "shapeU":
self.doObj("%s_Pdf" % n, "Uniform", "%s[-1,1]" % n)
elif pdf == "unif":
self.doObj("%s_Pdf" % n, "Uniform", "%s[%f,%f]" % (n, args[0], args[1]))
elif pdf == "flatParam" and self.options.flatParamPrior:
c_param_name = self.getSafeNormName(n)
if self.out.var(c_param_name):
v, x1, x2 = self.out.var(c_param_name).getVal(), self.out.var(c_param_name).getMin(), self.out.var(c_param_name).getMax()
self.DC.toCreateFlatParam[c_param_name] = [v, x1, x2]
else:
self.DC.toCreateFlatParam[c_param_name] = []
elif pdf == "dFD" or pdf == "dFD2":
dFD_min = -(1 + 8 / args[0])
dFD_max = +(1 + 8 / args[0])
for b in errline.keys():
for v in errline[b].values():
if v > 0 and 1.0 + dFD_min * v < 0:
dFD_min = -1.0 / v
if v < 0 and 1.0 + dFD_max * v < 0:
dFD_max = -1.0 / v
r = "%f,%f" % (dFD_min, dFD_max)
# r = "%f,%f" % (-(1+8/args[0]), +(1+8/args[0]));
# r = "-1,1"
if pdf == "dFD":
self.doObj(
"%s_Pdf" % n,
ROOFIT_EXPR_PDF,
"'1/(2*(1+exp(%f*((@0-@1)-1)))*(1+exp(-%f*((@0-@1)+1))))', %s[0,%s], %s_In[0,%s]" % (args[0], args[0], n, r, n, r),
)
else:
self.doObj(
"%s_Pdf" % n,
ROOFIT_EXPR_PDF,
"'1/(2*(1+exp(%f*(@0-1)))*(1+exp(-%f*(@0+1))))', %s[0,%s], %s_In[0,%s]" % (args[0], args[0], n, r, n, r),
)
self.globalobs.append("%s_In" % n)
if self.options.bin:
self.out.var("%s_In" % n).setConstant(True)
elif pdf == "constr":
print("-------------- WARNING, constraint found --> make sure that you know what you are doing!")
## I want to construct this line
## constr1_In[0.],RooFormulaVar::fconstr1("r_Bin0+r_Bin2-2*r_Bin1",{r_Bin0,r_Bin1,r_Bin2}),constr1_S[0.001000]
## Assuming args=
## r_Bin0+r_Bin2-2*r_Bin1 0.001
## or r_Bin0+r_Bin2-2*r_Bin1 {r_Bin0,r_Bin1,r_Bin2} 0.001000
## the parameter can be a number or a variable
d = {
"pdf": "%s_Pdf" % n,
"name": n,
"function": "%s_Func" % n,
"in": "%s_In" % n,
"sigma": "%s_S" % n,
"formula": args[0],
"param": args[-1],
}
if len(args) > 2:
d["depend"] = args[1] if args[1][0] == "{" else "{" + args[1] + "}"
else:
remove = set(["TMath", "Exp", "::", ""])
l = list(set(re.split("\\+|-|\\*|/|\\(|\\)", d["formula"])) - remove)
l2 = [] ## remove all the non-float expressions
for x in l:
try:
float(x)
except ValueError:
l2.append(x)
d["depend"] = "{" + ",".join(l2) + "}"
## derve the constrain strength
try:
float(d["param"]) # raise exception
if self.options.verbose > 2:
print("DEBUG constr", "param is a number")
d["fullsigma"] = "%(sigma)s[%(param)s]" % d
except ValueError:
if self.options.verbose > 2:
print("DEBUG constr", "param is a variable")
d["fullsigma"] = d["param"]
if self.options.verbose > 2:
print("DEBUG constr", "args", args)
if self.options.verbose > 2:
print("DEBUG constr", "Dictionary", d)
full = '%(in)s[0.],RooFormulaVar::%(function)s("%(formula)s",%(depend)s),%(fullsigma)s' % d
# self.doObj("%s_Pdf"%n, "Gaussian"," ".join(args),True)
v = self.options.verbose
self.options.verbose = 10 # force debug this line
self.doObj("%s_Pdf" % n, "Gaussian", full, True)
self.options.verbose = v
elif pdf == "param":
mean = float(args[0])
if "/" in args[1]:
sigmaL, sigmaR = args[1].split("/")
if sigmaL[0] != "-" or sigmaR[0] != "+":
raise RuntimeError("Asymmetric parameter uncertainties should be entered as -x/+y")
sigmaL = sigmaL[1:]
sigmaR = sigmaR[1:]
if len(args) == 3: # mean, sigma, range
if self.out.var(n):
bounds = [float(x) for x in args[2][1:-1].split(",")]
self.out.var(n).setConstant(False)
if self.out.var(n).getMin() != bounds[0] or self.out.var(n).getMax() != bounds[1]:
print(
"Resetting range for %s to be [%s,%s] from param statement (was [%s,%s])"
% (
n,
bounds[0],
bounds[1],
self.out.var(n).getMin(),
self.out.var(n).getMax(),
)
)
self.out.var(n).setRange(bounds[0], bounds[1])
else:
self.doVar("%s%s" % (n, args[2]))
else:
if self.out.var(n):
self.out.var(n).setConstant(False)
self.out.var(n).setRange(mean - 4 * float(sigmaL), mean + 4 * float(sigmaR))
else:
self.doVar(
"%s[%g,%g]"
% (
n,
mean - 4 * float(sigmaL),
mean + 4 * float(sigmaR),
)
)
self.out.var(n).setVal(mean)
self.out.var(n).setError(0.5 * (float(sigmaL) + float(sigmaR)))
sigmaStrL = sigmaL
sigmaStrR = sigmaR
if is_func_scaled:
sigmaStrL = "%s_WidthScaledL" % n
sigmaStrR = "%s_WidthScaledR" % n
self.doObj(sigmaStrL, "prod", "%g, %s" % (float(sigmaL), func_scaler))
self.doObj(sigmaStrR, "prod", "%g, %s" % (float(sigmaR), func_scaler))
self.doObj(
"%s_Pdf" % n,
"BifurGauss",
"%s, %s_In[%s,%g,%g], %s, %s"
% (
n,
n,
args[0],
self.out.var(n).getMin(),
self.out.var(n).getMax(),
sigmaStrL,
sigmaStrR,
),
True,
)
self.out.var("%s_In" % n).setConstant(True)
if is_func_scaled:
self.doExp(
"%s_BoundHi" % n,
"%g+%g*@0" % (mean, self.out.var(n).getMax() - mean),
"%s" % (func_scaler),
)
self.doExp(
"%s_BoundLo" % n,
"%g-%g*@0" % (mean, mean - self.out.var(n).getMin()),
"%s" % (func_scaler),
)
self.out.var(n).setRange(
self.out.function("%s_BoundLo" % n),
self.out.function("%s_BoundHi" % n),
)
else:
if len(args) == 3: # mean, sigma, range
sigma = float(args[1])
if self.out.var(n):
bounds = [float(x) for x in args[2][1:-1].split(",")]
self.out.var(n).setConstant(False)
if self.out.var(n).getMin() != bounds[0] or self.out.var(n).getMax() != bounds[1]:
print(
"Resetting range for %s to be [%s,%s] from param statement (was [%s,%s])"
% (
n,
bounds[0],
bounds[1],
self.out.var(n).getMin(),
self.out.var(n).getMax(),
)
)
self.out.var(n).setRange(bounds[0], bounds[1])
else:
self.doVar("%s%s" % (n, args[2]))
else:
sigma = float(args[1])
if self.out.var(n):
self.out.var(n).setConstant(False)
self.out.var(n).setRange(mean - 4 * sigma, mean + 4 * sigma)
else:
self.doVar("%s[%g,%g]" % (n, mean - 4 * sigma, mean + 4 * sigma))
self.out.var(n).setVal(mean)
self.out.var(n).setError(sigma)
sigmaStr = args[1]
if is_func_scaled:
sigmaStr = "%s_WidthScaled" % n
self.doObj(sigmaStr, "prod", "%g, %s" % (float(args[1]), func_scaler))
if self.options.noOptimizePdf or is_func_scaled:
self.doObj(
"%s_Pdf" % n,
"Gaussian",
"%s, %s_In[%s,%g,%g], %s"
% (
n,
n,
args[0],
self.out.var(n).getMin(),
self.out.var(n).getMax(),
sigmaStr,
),
True,
)
else:
self.doObj(
"%s_Pdf" % n,
"SimpleGaussianConstraint",
"%s, %s_In[%s,%g,%g], %s"
% (
n,
n,
args[0],
self.out.var(n).getMin(),
self.out.var(n).getMax(),
sigmaStr,
),
True,
)
self.out.var("%s_In" % n).setConstant(True)
if is_func_scaled:
boundHi = self.doExp(
"%s_BoundHi" % n,
"%g+%g*@0" % (mean, self.out.var(n).getMax() - mean),
"%s" % (func_scaler),
)
boundLo = self.doExp(
"%s_BoundLo" % n,
"%g-%g*@0" % (mean, mean - self.out.var(n).getMin()),
"%s" % (func_scaler),
)
self.out.var(n).setRange(
self.out.function("%s_BoundLo" % n),
self.out.function("%s_BoundHi" % n),
)
self.globalobs.append("%s_In" % n)
# if self.options.optimizeBoundNuisances: self.out.var(n).setAttribute("optimizeBounds")
elif pdf == "extArg":
continue
else:
raise RuntimeError("Unsupported pdf %s" % pdf)
if nofloat:
self.out.var(n).setAttribute("globalConstrained", True)
# self.out.var(n).Print('V')
if n in self.DC.frozenNuisances:
self.out.var(n).setConstant(True)
def doFillNuisPdfsAndSets(self):
if self.options.bin:
# avoid duplicating _Pdf in list
setNuisPdf = []
nuisPdfs = ROOT.RooArgList()
nuisVars = ROOT.RooArgSet()
for n, nf, p, a, e in self.DC.systs:
c_param_name = self.getSafeNormName(n)
if p != "constr":
nuisVars.add(self.out.var(c_param_name))
setNuisPdf.append(c_param_name)
setNuisPdf = list(dict.fromkeys((setNuisPdf)))
for n in setNuisPdf:
nuisPdfs.add(self.out.pdf(n + "_Pdf"))
self.out.defineSet("nuisances", nuisVars)
self.out.nuisPdf = ROOT.RooProdPdf("nuisancePdf", "nuisancePdf", nuisPdfs)
self.out.safe_import(self.out.nuisPdf)
self.out.nuisPdfs = nuisPdfs
gobsVars = ROOT.RooArgSet()
for g in self.globalobs:
gobsVars.add(self.out.var(g))
self.out.defineSet("globalObservables", gobsVars)
else: # doesn't work for too many nuisances :-(
# avoid duplicating _Pdf in list
setNuisPdf = list(dict.fromkeys(keywords([self.getSafeNormName(n) for (n, nf, p, a, e) in self.DC.systs])))
self.doSet("nuisances", ",".join(["%s" % self.getSafeNormName(n) for (n, nf, p, a, e) in self.DC.systs]))
self.doObj("nuisancePdf", "PROD", ",".join(["%s_Pdf" % n for n in setNuisPdf]))
self.doSet("globalObservables", ",".join(self.globalobs))
def doAutoFlatNuisancePriors(self):
if len(self.DC.toCreateFlatParam.keys()) > 0:
for flatNP in self.DC.toCreateFlatParam.items():
c_param_name = flatNP[0]
c_param_details = flatNP[1]
if len(c_param_details):
v, x1, x2 = c_param_details
else:
v, x1, x2 = self.out.var(c_param_name).getVal(), self.out.var(c_param_name).getMin(), self.out.var(c_param_name).getMax()
if self.options.verbose > 2:
print("Will create flat prior for parameter ", c_param_name, " with range [", x1, x2, "]")
self.doExp(
"%s_diff_expr" % c_param_name, "%s-%s_In" % (c_param_name, c_param_name), "%s,%s_In[%g,%g,%g]" % (c_param_name, c_param_name, v, x1, x2)
)
self.doObj("%s_Pdf" % c_param_name, "Uniform", "%s_diff_expr" % c_param_name)
self.out.var("%s_In" % c_param_name).setConstant(True)
self.globalobs.append("%s_In" % c_param_name)
def doNuisancesGroups(self):
# Prepare a dictionary of which group a certain nuisance belongs to
groupsFor = OrderedDict()
# existingNuisanceNames = tuple(set([syst[0] for syst in self.DC.systs]+self.DC.flatParamNuisances.keys()+self.DC.rateParams.keys()+self.DC.extArgs.keys()+self.DC.discretes))
existingNuisanceNames = self.DC.getAllVariables()
for groupName, nuisanceNames in six.iteritems(self.DC.groups):
for nuisanceName in nuisanceNames:
if nuisanceName not in existingNuisanceNames:
raise RuntimeError(
'Nuisance group "%(groupName)s" refers to nuisance "%(nuisanceName)s" but it does not exist. Perhaps you misspelled it.' % locals()
)
if nuisanceName in groupsFor:
groupsFor[nuisanceName].append(groupName)
else:
groupsFor[nuisanceName] = [groupName]
# print self.DC.groups
# print groupsFor
for n in existingNuisanceNames:
# set an attribute related to the group(s) this nuisance belongs to
if n in groupsFor:
groupNames = groupsFor[n]
if self.options.verbose > 1:
print('Nuisance "%(n)s" is assigned to the following nuisance groups: %(groupNames)s' % locals())
for groupName in groupNames:
var = self.out.var(n)
if not var:
var = self.out.cat(n)
if not var:
raise RuntimeError('Nuisance group "%(groupName)s" refers to nuisance but it is not an independent parameter.' % locals())
var.setAttribute("group_" + groupName, True)
for groupName, nuisanceNames in six.iteritems(self.DC.groups):
nuisanceargset = ROOT.RooArgSet()
for nuisanceName in nuisanceNames:
nuisanceargset.add(self.out.var(nuisanceName))
self.out.defineSet("group_%s" % groupName, nuisanceargset)
def doExpectedEvents(self):
self.doComment(" --- Expected events in each bin, for each process ----")
for b in self.DC.bins:
for p in self.DC.exp[b].keys(): # so that we get only self.DC.processes contributing to this bin
# if it's a zero background, write a zero and move on
if self.DC.exp[b][p] == 0:
self.doVar("n_exp_bin%s_proc_%s[%g]" % (b, p, self.DC.exp[b][p]))
continue
# get model-dependent scale factor
scale = self.physics.getYieldScale(b, p)
if scale == 0:
self.doVar("n_exp_bin%s_proc_%s[%g]" % (b, p, 0))
continue
# collect multiplicative corrections
nominal = self.DC.exp[b][p]
gamma = None
# gamma normalization (if present, DC.exp[b][p] is ignored)
factors = [] # RooAbsReal multiplicative factors (including gmN)
logNorms = [] # (kappa, RooAbsReal) lnN (or lnN)
alogNorms = [] # (kappaLo, kappaHi, RooAbsReal) asymm lnN
if scale == 1:
pass
elif type(scale) == str:
factors.append(scale)
else:
raise RuntimeError("Physics model returned something that is neither a name, nor 0, nor 1.")
# look for rate param for this bin
if "%sAND%s" % (b, p) in list(self.DC.rateParams.keys()):
for rk in range(len(self.DC.rateParams["%sAND%s" % (b, p)])):
argu = self.DC.rateParams["%sAND%s" % (b, p)][rk][0][0]
if self.out.arg(argu):
factors.append(argu)
else:
raise RuntimeError("No rate parameter found %s, are you sure you defined it correctly in the datacard?" % (argu))
selfNormRate = 1.0
for n, nofloat, pdf, args, errline in self.DC.systs:
if pdf == "param":
continue
if pdf == "constr":
continue
if pdf == "rateParam" or pdf == "flatParam":
continue
if p not in errline[b]:
continue
if errline[b][p] == 0.0:
continue
if pdf.startswith("shape") and pdf.endswith("?"): # might be a lnN in disguise
if not self.isShapeSystematic(b, p, n):
pdf = "lnN"
if pdf.startswith("shape"):
continue
if pdf == "lnN" and errline[b][p] == 1.0:
continue
if pdf == "lnN" or pdf == "lnU":
if type(errline[b][p]) == list:
elow, ehigh = errline[b][p]
alogNorms.append((elow, ehigh, n))
else:
logNorms.append((errline[b][p], n))
elif pdf == "gmM":
factors.append(n)
# elif pdf == "trG" or pdf == "unif" or pdf == "flatParam" or pdf == "dFD" or pdf == "dFD2":
elif pdf == "trG" or pdf == "unif" or pdf == "dFD" or pdf == "dFD2":
myname = "n_exp_shift_bin%s_proc_%s_%s" % (b, p, n)
self.doObj(myname, ROOFIT_EXPR, "'1+%f*@0', %s" % (errline[b][p], n))
factors.append(myname)
elif pdf == "gmN":
factors.append(n)
if abs(errline[b][p] * args[0] - self.DC.exp[b][p]) > max(0.05 * max(self.DC.exp[b][p], 1), errline[b][p]):
raise RuntimeError(
"Values of N = %d, alpha = %g don't match with expected rate %g for systematics %s "
% (args[0], errline[b][p], self.DC.exp[b][p], n)
)
if gamma != None:
raise RuntimeError("More than one gmN uncertainty for the same bin and process (second one is %s)" % n)
gamma = n
nominal = errline[b][p]
# The case with N=0 isn't relevant if the process provides its own normalisation,
# so we don't need to do anything special to handle it here.
if args[0] > 0:
selfNormRate = selfNormRate / args[0]
else:
raise RuntimeError("Unsupported pdf %s" % pdf)
# optimize constants
if len(factors) + len(logNorms) + len(alogNorms) == 0:
norm = selfNormRate if b in self.selfNormBins else self.DC.exp[b][p]
self.doVar("n_exp_bin%s_proc_%s[%g]" % (b, p, norm))
else:
norm = selfNormRate if b in self.selfNormBins else nominal
# print "Process %s of bin %s depends on:\n\tlog-normals: %s\n\tasymm log-normals: %s\n\tother factors: %s\n" % (p,b,logNorms, alogNorms, factors)
procNorm = ROOT.ProcessNormalization("n_exp_bin%s_proc_%s" % (b, p), "", norm)
for kappa, thetaName in logNorms:
procNorm.addLogNormal(kappa, self.out.function(thetaName))
for kappaLo, kappaHi, thetaName in alogNorms:
procNorm.addAsymmLogNormal(kappaLo, kappaHi, self.out.function(thetaName))
for factorName in factors:
if self.out.function(factorName):
procNorm.addOtherFactor(self.out.function(factorName))
elif self.out.var(factorName):
procNorm.addOtherFactor(self.out.var(factorName))
elif self.out.arg(factorName):
raise RuntimeError(
"Factor %s for process %s, bin %s is a %s (not supported)"
% (
factorName,
p,
b,
self.out.arg(factorName).ClassName(),
)
)
else:
raise RuntimeError("Cannot add nonexistent factor %s for process %s, bin %s" % (factorName, p, b))