import ROOT

# From the root prompt, you can see the full list of functions by using tab-completion
# ~~~{.bash}
# root [0] RooStats::NumberCountingUtils::  <tab>
# BinomialExpZ
# BinomialWithTauExpZ
# BinomialObsZ
# BinomialWithTauObsZ
# BinomialExpP
# BinomialWithTauExpP
# BinomialObsP
# BinomialWithTauObsP
# ~~~

# For each of the utilities you can inspect the arguments by tab completion
# ~~~{.bash}
# root [1] NumberCountingUtils::BinomialExpZ( <tab>
# Double_t BinomialExpZ(Double_t sExp, Double_t bExp, Double_t fractionalBUncertainty)
# ~~~

# -------------------------------------------------
# Here we see common usages where the experimenter
# has a relative background uncertainty, without
# explicit reference to the auxiliary or sideband
# measurement

# -------------------------------------------------------------
# Expected p-values and significance with background uncertainty
sExpected = 50
bExpected = 100
relativeBkgUncert = 0.1

pExp = ROOT.RooStats.NumberCountingUtils.BinomialExpP(sExpected, bExpected, relativeBkgUncert)
zExp = ROOT.RooStats.NumberCountingUtils.BinomialExpZ(sExpected, bExpected, relativeBkgUncert)
print("expected p-value = {}  Z value (Gaussian sigma) = {}".format(pExp, zExp))

# -------------------------------------------------
# Expected p-values and significance with background uncertainty
observed = 150
pObs = ROOT.RooStats.NumberCountingUtils.BinomialObsP(observed, bExpected, relativeBkgUncert)
zObs = ROOT.RooStats.NumberCountingUtils.BinomialObsZ(observed, bExpected, relativeBkgUncert)
print("observed p-value = {}  Z value (Gaussian sigma) = {}".format(pObs, zObs))

# ---------------------------------------------------------
# Here we see usages where the experimenter has knowledge
# about the properties of the auxiliary or sideband
# measurement.  In particular, the ratio tau of background
# in the auxiliary measurement to the main measurement.
# Large values of tau mean small background uncertainty
# because the sideband is very constraining.

# Usage:
# ~~~{.bash}
# root [0] RooStats::NumberCountingUtils::BinomialWithTauExpP(
# Double_t BinomialWithTauExpP(Double_t sExp, Double_t bExp, Double_t tau)
# ~~~

# --------------------------------------------------------------
# Expected p-values and significance with background uncertainty
tau = 1

pExpWithTau = ROOT.RooStats.NumberCountingUtils.BinomialWithTauExpP(sExpected, bExpected, tau)
zExpWithTau = ROOT.RooStats.NumberCountingUtils.BinomialWithTauExpZ(sExpected, bExpected, tau)
print("observed p-value = {}  Z value (Gaussian sigma) = {}".format(pExpWithTau, zExpWithTau))

# ---------------------------------------------------------------
# Expected p-values and significance with background uncertainty
pObsWithTau = ROOT.RooStats.NumberCountingUtils.BinomialWithTauObsP(observed, bExpected, tau)
zObsWithTau = ROOT.RooStats.NumberCountingUtils.BinomialWithTauObsZ(observed, bExpected, tau)
print("observed p-value = {}  Z value (Gaussian sigma) = {}".format(pObsWithTau, zObsWithTau))