Merge branch 'develop'

Author: WolfgangWaltenberger

ReleaseNotes

@@ -1,3 +1,10 @@
+Release v3.0.2, Thu 23 Jan 2025
+=======================================================
+
+  * Small fix in pyhf caching code (results should not change)
+  * Fixes with parallelisation of resummino cross section computer
+  * Tiny fix to allow '#' without subsequent whitespace as comment in text database
+
 Release v3.0.1, Thu 31 Oct 2024
 =======================================================
 

docs/manual/source/ReleaseUpdate.rst

@@ -33,6 +33,13 @@ What's New
 ==========
 The major novelties of all releases since v1.0 are as follows:
 
+New in Version 3.0.2:
+^^^^^^^^^^^^^^^^^^^^^
+
+  * Small fix in pyhf caching code (results should not change)
+  * Fixes with parallelisation of :ref:`resummino cross section <xsecResummino>` computer
+  * Tiny fix to allow '#' without subsequent whitespace as comment in text database
+
 New in Version 3.0.1:
 ^^^^^^^^^^^^^^^^^^^^^
 

smodels/base/runtime.py

@@ -10,10 +10,13 @@
 
 """
 
+from typing import Union
+
 ## place to keep the pointer to the model file (default = mssm)
 modelFile="smodels.share.models.mssm"
 
-_experimental = False ## turn on experimental features
+_experimental = { "truncatedgaussians": False,
+                  "spey": False } ## experimental features
 
 _deltas_rel_default = .2 ## the default relative error on the signal strength
 
@@ -51,11 +54,16 @@ def filetype ( filename ):
     return None
 
 
-def experimentalFeatures():
-    """ a simple boolean flag to turn experimental features on/off,
+def experimentalFeature( feature : str ) -> Union[None,bool]:
+    """ method to check if a certain experimental feature is enabled.
     can be turned on and off via options:experimental in parameters.ini.
+    :param feature: ask for feature
+    
+    :returns: None if feature does not exist, else boolean
     """
-    return _experimental
+    if not feature in _experimental:
+        return None
+    return _experimental[feature]
 
 def nCPUs():
     """ obtain the number of *available* CPU cores on the machine, for several

smodels/experiment/databaseObj.py

@@ -58,7 +58,7 @@ def _getSHA1(filename):
 
 # some mechanism to remove lock files if the download got interrupted
 import atexit
-lockfiles = set() 
+lockfiles = set()
 
 def removeLockFiles( lockfiles ):
     """ remove cruft lockfiles """
@@ -73,13 +73,13 @@ def removeLockFiles( lockfiles ):
 atexit.register ( removeLockFiles, lockfiles )
 
 class Database(object):
-    """ 
+    """
     Database object. Holds a list of SubDatabases and the ExpSMS map.
     Delegates all calls to SubDatabases.
     """
 
     def __init__(self, base=None, force_load=None,
-                 progressbar=False, subpickle=True, 
+                 progressbar=False, subpickle=True,
                  combinationsmatrix=None):
         """
         :param base: path to the database, or pickle file (string), or http
@@ -99,17 +99,15 @@ def __init__(self, base=None, force_load=None,
                      optionally specifying signal regions, e.g. { "anaid1:SR1":
                      ( "anaid2:SR2", "anaid3" ) }
         """
-        
         self.subs = []
-        
         if "_fastlim" in base:  # for backwards compatibility
             base = base.replace("_fastlim", "+fastlim")
         sstrings = base.split("+")
         for ss in sstrings:
             self.subs.append(SubDatabase(ss, force_load,
-                                         progressbar, subpickle, 
+                                         progressbar, subpickle,
                                          combinationsmatrix))
-        
+
 
         # Compute SMS dict with all results
         self._allExpSMSDict = ExpSMSDict(self.expResultList)
@@ -120,7 +118,7 @@ def __init__(self, base=None, force_load=None,
     @property
     def expResultList(self):
         """
-        The combined list of results, compiled from the 
+        The combined list of results, compiled from the
         the active results in each subdatabase.
         """
 
@@ -235,11 +233,11 @@ def getExpResults(self, analysisIDs=['all'], datasetIDs=['all'], txnames=['all']
         Select (filter) the results within the database satisfying the restrictions set by the arguments and returns the corresponding results.
         """
 
-        self.selectExpResults(analysisIDs=analysisIDs, datasetIDs=datasetIDs, 
-                             txnames=txnames, dataTypes=dataTypes, 
+        self.selectExpResults(analysisIDs=analysisIDs, datasetIDs=datasetIDs,
+                             txnames=txnames, dataTypes=dataTypes,
                              useNonValidated=useNonValidated,
                              onlyWithExpected=onlyWithExpected)
-        
+
         return self.expResultList[:]
 
     def selectExpResults(self, analysisIDs=['all'], datasetIDs=['all'], txnames=['all'],
@@ -420,8 +418,8 @@ def __init__(self, base=None, force_load=None,
             self._setParticles()
             self.txt_meta.printFastlimBanner()
             return
-        logger.error("when initialising database: force_load=%s is not "
-                     "recognized. Valid values are: pcl, txt, None." % force_load)
+        logger.error( f"when initialising database: force_load={force_load} is not "
+                     "recognized. Valid values are: pcl, txt, None." )
         raise SModelSError()
 
     def __eq__(self, other):
@@ -462,16 +460,21 @@ def loadDatabase(self):
             it needs update, create new binary file, in
             case it does need an update.
         """
-        if not os.path.exists(self.pcl_meta.pathname):
-            logger.info("Creating binary database ")
-            logger.info("(this may take a few minutes, but it's done only once!)")
-            self.loadTextDatabase()
-            self.createBinaryFile()
-        else:
-            if self.needsUpdate():
+        try:
+            if not os.path.exists(self.pcl_meta.pathname):
+                logger.info("Creating binary database ")
+                logger.info("(this may take a few minutes, but it's done only once!)")
+                self.loadTextDatabase()
                 self.createBinaryFile()
             else:
-                self.loadBinaryFile(lastm_only=False)
+                if self.needsUpdate():
+                    self.createBinaryFile()
+                else:
+                    self.loadBinaryFile(lastm_only=False)
+        except Exception as e:
+            import traceback
+            logger.error ( "when loading database: {e}, {traceback.format_exc()}" )
+            sys.exit(-1)
 
     def loadTextDatabase(self):
         """ simply loads the textdabase """
@@ -557,7 +560,7 @@ def loadBinaryFile(self, lastm_only=False):
                     t1 = time.time()-t0
                     logger.info("Loaded database from %s in %.1f secs." %
                             (self.pcl_meta.pathname, t1))
-                    self.databaseParticles = None                    
+                    self.databaseParticles = None
                     try:
                         self.databaseParticles = serializer.load(f)
                     except EOFError as e:
@@ -669,7 +672,7 @@ def base(self):
     def lockFile ( self, filename : os.PathLike ):
         """ lock the file <filename>
         """
-        lockfile = os.path.join ( os.path.dirname ( filename ), 
+        lockfile = os.path.join ( os.path.dirname ( filename ),
                                   ".lock_"+ os.path.basename ( filename ) )
         ctr = 0
         while ( ctr < 5 ):
@@ -700,7 +703,7 @@ def lockFile ( self, filename : os.PathLike ):
     def unlockFile ( self, filename : os.PathLike ):
         """ unlock the file <filename>
         """
-        lockfile = os.path.join ( os.path.dirname ( filename ), 
+        lockfile = os.path.join ( os.path.dirname ( filename ),
                                   ".lock_"+ os.path.basename ( filename ) )
         if lockfile in lockfiles:
             lockfiles.remove( lockfile )
@@ -1079,7 +1082,7 @@ def setActiveExpResults(self, analysisIDs=['all'], datasetIDs=['all'], txnames=[
         """
 
         self._activeResults = self.getExpResults(analysisIDs, datasetIDs, txnames,
-                                                dataTypes, useNonValidated, 
+                                                dataTypes, useNonValidated,
                                                 onlyWithExpected)
 
     def getExpResults(self, analysisIDs=['all'], datasetIDs=['all'], txnames=['all'],

smodels/experiment/infoObj.py

@@ -45,7 +45,7 @@ def __init__(self, path=None):
             for i, tag in enumerate(tags):
                 if not tag:
                     continue
-                if tag.startswith("# "):  # a comment!
+                if tag.startswith("#"):  # a comment!
                     continue
                 line = content[i]
                 value = line.split(':', 1)[1].strip()

smodels/matching/modelTester.py

@@ -178,11 +178,10 @@ def testPoint(inputFile, outputDir, parser, database):
             useBest = False
     except (NoSectionError, NoOptionError):
         pass
-    try:
-        expFeatures = parser.getboolean("options", "experimentalFeatures")
-        runtime._experimental = expFeatures
-    except (NoSectionError, NoOptionError):
-        pass
+
+    if parser.has_section ( "experimentalFeatures" ):
+        featuresDict = dict(parser.items("experimentalFeatures"))
+        setExperimentalFeatures( featuresDict )
 
     allPredictions = theoryPredictionsFor(database, smstoplist,
                                           useBestDataset=useBest,
@@ -530,7 +529,11 @@ def getParameters(parameterFile):
     if ret == []:
         logger.error("No such file or directory: '%s'" % parameterFile)
         sys.exit()
-    setExperimentalFlag(parser)
+
+    if parser.has_section ( "experimentalFeatures" ):
+        featuresDict = dict(parser.items("experimentalFeatures"))
+        setExperimentalFeatures(featuresDict)
+    
     try:
         runtime.modelFile = parser.get("particles", "model")
     except:
@@ -544,12 +547,15 @@ def getParameters(parameterFile):
     return parser
 
 
-def setExperimentalFlag(parser):
-    """ set the experimental flag, if options:experimental = True """
-    if parser.has_option("options", "experimental"):
-        if parser.getboolean("options", "experimental"):
-            runtime._experimental = True
+def setExperimentalFeatures(featuresDict):
+    """ set the experimental features flats, if experimentalFeatures:* = True """
 
+    for feature in featuresDict.keys():
+        if not feature in runtime._experimental:
+            logger.warning ( f"'{feature}' is not a known experimental feature. will ignore." )
+            continue
+        flag = bool(featuresDict[feature])
+        runtime._experimental[feature]=flag
 
 def getAllInputFiles(inFile):
     """

smodels/matching/theoryPrediction.py

@@ -12,7 +12,6 @@
 from smodels.matching.exceptions import SModelSMatcherError as SModelSError
 from smodels.matching import clusterTools
 from smodels.base.smodelsLogging import logger
-from smodels.statistics.statsTools import StatsComputer
 from typing import Union, Text, Dict
 import numpy as np
 
@@ -144,10 +143,12 @@ def setStatsComputer(self):
         to define a statistical computer (upper limit result or no expected
         upper limits), set the computer to 'N/A'.
         """
+        from smodels.statistics.statsTools import getStatsComputerModule
+        StatsComputer = getStatsComputerModule()
 
         if self.dataType() == "upperLimit":
-            from smodels.base.runtime import experimentalFeatures
-            if not experimentalFeatures():
+            from smodels.base.runtime import experimentalFeature
+            if not experimentalFeature( "truncatedGaussians" ):
                 computer = 'N/A'
             else:
                 computer = StatsComputer.forTruncatedGaussian(self)
@@ -373,7 +374,8 @@ def computeStatistics(self, expected=False):
             self.cachedObjs[expected]["nll_sm"] = llhdDict["lsm"]
             self.cachedObjs[expected]["nllmax"] = llhdDict["lmax"]
             self.cachedObjs[expected]["muhat"] = llhdDict["muhat"]
-            self.cachedObjs[expected]["sigma_mu"] = llhdDict["sigma_mu"]
+            if "sigma_mu" in llhdDict:
+                self.cachedObjs[expected]["sigma_mu"] = llhdDict["sigma_mu"]
 
 
 class TheoryPredictionsCombiner(TheoryPrediction):
@@ -522,6 +524,8 @@ def setStatsComputer(self):
         if any(tp.statsComputer == 'N/A' for tp in self.theoryPredictions):
             computer = 'N/A'
         else:
+            from smodels.statistics.statsTools import getStatsComputerModule
+            StatsComputer = getStatsComputerModule()
             computer = StatsComputer.forAnalysesComb(self.theoryPredictions, self.deltas_rel)
 
         self._statsComputer = computer

smodels/share/BANNER

@@ -8,7 +8,7 @@
 SModelS -- A tool for interpreting simplified-model results from the LHC,
 see https://smodels.github.io/.
 
-Copyright (C) 2012-2024 The SModelS collaboration, smodels-users@lists.oeaw.ac.at
-Current members: Mohammad Mahdi Altakach, Sabine Kraml, Andre Lessa, Sahana Narashima, Timothee Pascal, Camila Ramos, Humberto Reyes-Gonzalez, Yoxara Villamizar, Wolfgang Waltenberger
+Copyright (C) 2012-2025 The SModelS collaboration, smodels-users@lists.oeaw.ac.at
+Current members: Mohammad Mahdi Altakach, Sabine Kraml, Andre Lessa, Sahana Narashima, Timothee Pascal, Camila Ramos, Humberto Reyes-Gonzalez, Theo Reymermier, Yoxara Villamizar, Wolfgang Waltenberger
 
 Previously involved in SModelS: Gael Alguero, Federico Ambrogi, Juhi Dutta, Jan Heisig, Charanjit K. Khosa, Suchita Kulkarni, Ursula Laa, Veronika Magerl, Wolfgang Magerl, Philipp Neuhuber, Doris Proschofsky, Jory Sonneveld, Michael Traub, Matthias Wolf, Alicia Wongel

smodels/statistics/basicStats.py

@@ -23,10 +23,10 @@ def CLsfromNLL(
     compute the CLs - alpha from the NLLs
     TODO: following needs explanation
 
-    :param nllA:
-    :param nll0A:
-    :param nll:
-    :param nll0:
+    :param nllA: negative log likelihood for Asimov data
+    :param nll0A: negative log likelihood at muhat for Asimov data
+    :param nll: negative log likelihood
+    :param nll0: negative log likelihood at muhat
     :param return_type: (Text) can be "CLs-alpha", "1-CLs", "CLs" \
                         CLs-alpha: returns CLs - 0.05 \
                         1-CLs: returns 1-CLs value \