"""
.. module:: summaryPrinter
:synopsis: Class for describing a summary printer in text format.
.. moduleauthor:: Andre Lessa <lessa.a.p@gmail.com>
"""
from __future__ import print_function
import os
from smodels.matching.theoryPrediction import TheoryPredictionList,TheoryPrediction,TheoryPredictionsCombiner
from smodels.tools.ioObjects import OutputStatus
from smodels.tools.coverage import Uncovered
from smodels.base.physicsUnits import fb, TeV
from smodels.base.smodelsLogging import logger
from smodels.tools.printers.txtPrinter import TxTPrinter
import numpy as np
import unum
[docs]class SummaryPrinter(TxTPrinter):
"""
Printer class to handle the printing of one single summary output.
It uses the facilities of the TxTPrinter.
"""
def __init__(self, output='stdout', filename=None, outputFormat='version3'):
TxTPrinter.__init__(self, output, filename, outputFormat)
self.name = "summary"
self.printingOrder = [
OutputStatus, TheoryPredictionList,
TheoryPredictionsCombiner,
TheoryPrediction, Uncovered]
self.toPrint = [None]*len(self.printingOrder)
[docs] def setOutPutFile(self, filename, overwrite=True, silent=False):
"""
Set the basename for the text printer. The output filename will be
filename.smodels.
:param filename: Base filename
:param overwrite: If True and the file already exists, it will be removed.
:param silent: dont comment removing old files
"""
self.filename = filename + '.smodels'
if overwrite and os.path.isfile(self.filename):
if not silent:
logger.warning("Removing old output file " + self.filename)
os.remove(self.filename)
def _formatTheoryPredictionList(self, obj):
"""
Format data of the TheoryPredictionList object.
:param obj: A TheoryPredictionList object to be printed.
"""
obj.sortTheoryPredictions()
if hasattr(self, "expandedsummary") and not self.expandedsummary:
theoPredictions = [obj._theoryPredictions[0]]
else:
theoPredictions = obj._theoryPredictions
output = ""
maxr = {"obs": -1., "exp": -1, "anaid": "?"}
maxcoll = {"CMS": {"obs": -1., "exp": -1, "anaid": "?"},
"ATLAS": {"obs": -1., "exp": -1, "anaid": "?"}}
for theoPred in obj._theoryPredictions:
r = theoPred.getRValue(evaluationType=False)
r_expected = theoPred.getRValue(evaluationType=self.getTypeOfExpected())
expResult = theoPred.expResult
coll = "ATLAS" if "ATLAS" in expResult.globalInfo.id else "CMS"
if (r_expected is not None) and (r_expected > maxcoll[coll]["exp"]):
maxcoll[coll] = {"obs": r, "exp": r_expected,
"anaid": expResult.globalInfo.id}
if (r is not None) and (r > maxr["obs"]):
maxr = {"obs": r, "exp": r_expected,
"anaid": expResult.globalInfo.id}
output += "#Analysis Sqrts Cond_Violation Theory_Value(fb) Exp_limit(fb) r r_expected"
output += "\n\n"
for theoPred in theoPredictions:
expResult = theoPred.expResult
ul = theoPred.getUpperLimit(evaluationType=False)
uls = str(ul)
if isinstance(ul, unum.Unum):
uls = f"{ul.asNumber(fb):10.3E}"
signalRegion = theoPred.dataset.getID()
if signalRegion is None:
signalRegion = '(UL)'
value = theoPred.xsection
r = theoPred.getRValue(evaluationType=False)
r_expected = theoPred.getRValue(evaluationType=self.getTypeOfExpected())
if r is not None:
rs = f"{r:10.3E}"
else:
rs = "NaN" # r = None means the calculation failed
if r_expected is not None:
rs_expected = f"{r_expected:10.3E}"
else:
rs_expected = "N/A" # r_exp could not be available
output += "%19s " % (expResult.globalInfo.id) # ana
# output += "%4s " % (expResult.globalInfo.sqrts/ TeV) # sqrts
# sqrts
output += f"{expResult.globalInfo.sqrts.asNumber(TeV):2.2E} "
output += "%5s " % theoPred.getmaxCondition() # condition violation
# theory cross section , expt upper limit
output += f"{value.asNumber(fb):10.3E} {uls} "
output += f"{rs} {rs_expected}"
output += "\n"
output += " Signal Region: "+signalRegion+"\n"
txWeightsDict = theoPred.getTxNamesWeights(sort=True)
txnameStr_list = list(dict.fromkeys([tx.txName for tx in txWeightsDict]))
txnameStr = ', '.join(txnameStr_list)
txnameStr = txnameStr.replace(
"'", "").replace("[", "").replace("]", "")
output += " Txnames: " + txnameStr + "\n"
# Get TxNames final states:
fStates = []
for txname in txWeightsDict:
for sms in txname.smsMap:
fs = sms.getFinalStateStr()
if fs not in fStates:
fStates.append(fs)
max_length = 3
fStates_str = ', '.join(fStates[:max_length])
if len(fStates) > max_length:
fStates_str += f',...({len(fStates)-max_length:d} more)'
if self.outputFormat != 'version2':
output += " Final States: " + fStates_str + "\n"
nll = theoPred.nll ( )
if nll is not None:
nllmin = theoPred.nll_min( )
nllsm = theoPred.nllsm( )
lvals = [nll, nllmin, nllsm]
for i, lv in enumerate(lvals):
if isinstance(lv, (float, np.floating)):
lv = f"{lv:10.3E}"
else:
lv = str(lv)
lvals[i] = lv
nll, nllmin, nllsm = lvals[:]
if nll == nllmin == nllsm == "None":
output += " Likelihoods: nll, nll_min, nll_SM = N/A\n"
else:
output += f" Likelihoods: nll, nll_min, nll_SM = {nll}, {nllmin}, {nllsm}\n"
if not (theoPred is obj[-1]):
output += 80 * "-" + "\n"
output += "\n \n"
output += 80 * "=" + "\n"
output += f"The highest r value is = {maxr['obs']:.5f} from {maxr['anaid']}"
if maxr["exp"] is not None and maxr["exp"] >= 0.0:
output += f" (r_expected={maxr['exp']:.5f})"
else:
output += " (r_expected not available)"
output += "\n"
for coll, values in maxcoll.items():
if values["obs"] == None or values["obs"] < 0.0:
continue
output += "%s analysis with highest available r_expected: %s, r_expected=%.5f, r_obs=%.5f\n" % \
(coll, values["anaid"], values["exp"], values["obs"])
return output
def _formatTheoryPrediction(self,obj):
return self._formatTheoryPredictionsCombiner(obj)
def _formatTheoryPredictionsCombiner(self, obj):
"""
Format data of the TheoryPredictionsCombiner object.
:param obj: A TheoryPredictionsCombiner object to be printed.
"""
output = "===================================================== \n"
# Get list of analyses used in combination:
expIDs = obj.analysisId()
# Get r-value:
r = obj.getRValue()
r_expected = obj.getRValue(evaluationType=self.getTypeOfExpected())
# Get likelihoods:
nllsm = obj.nllsm( )
nll = obj.nll( )
nllmin = obj.nll_min( )
# Get sorted txnames
txnames = []
for tx in obj.getTxNamesWeights(sort=True):
if tx.txName not in txnames:
txnames.append(tx.txName)
output += f"Combined Analyses: {expIDs}\n"
output += f"Txnames: {', '.join(txnames)}\n"
output += f"Likelihoods: nll, nll_min, nll_SM = {nll:.3f}, {nllmin:.3f}, {nllsm:.3f}\n"
if r is not None:
output += f"combined r-value: {r:10.3E}\n"
else:
output += f"combined r-value: NaN (failed to compute r-value)\n"
if r_expected is not None:
output += f"combined r-value (expected): {r_expected:10.3E}\n"
else:
output += f"combined r-value (expected): NaN (failed to compute r-value)\n"
output += "\n===================================================== \n"
output += "\n"
return output