Print function migration for RecoTauTag_TauTagTools

RecoTauTag/TauTagTools/python/MVASteering_cfi.py

@@ -7,6 +7,7 @@
                 - which algorithms (shrinkingConePFTauDecayModeProducer, etc)
         Define locations of train/test ROOT files
 """
+from __future__ import print_function
 
 import sys
 import six
@@ -15,7 +16,7 @@
 try:
    Project_Area = os.environ["CMSSW_BASE"]
 except KeyError:
-   print "$CMSSW_BASE enviroment variable not set!  Please run eval `scramv1 ru -[c]sh`"
+   print("$CMSSW_BASE enviroment variable not set!  Please run eval `scramv1 ru -[c]sh`")
    sys.exit(1)
 
 import FWCore.ParameterSet.Config as cms

RecoTauTag/TauTagTools/python/PFTauMVAInputDiscriminatorTranslator_cfi.py

@@ -1,3 +1,4 @@
+from __future__ import print_function
 import FWCore.ParameterSet.Config as cms
 
 produceTancMVAInputDiscriminators = cms.EDProducer(
@@ -73,7 +74,7 @@
 def loadMVAInputsIntoPatTauDiscriminants(thePatTauProducer):
     return
     " Add all of the MVA inputs discriminators to the tauID inputs of a patTau Producer "
-    print "Embedding MVA inputs into PAT Tau producer "
+    print("Embedding MVA inputs into PAT Tau producer ")
     patTauIDConfig = thePatTauProducer.tauIDSources
     for tancInputInfo in produceTancMVAInputDiscriminators.discriminants:
         name = tancInputInfo.name.value()
@@ -94,7 +95,7 @@ class Dummy:
     test = Dummy()
     test.tauIDSources = cms.PSet()
     loadMVAInputsIntoPatTauDiscriminants(test)
-    print test.tauIDSources
+    print(test.tauIDSources)
 
 
 

RecoTauTag/TauTagTools/test/database/ReblobTancDB_cfg.py

@@ -1,3 +1,4 @@
+from __future__ import print_function
 #!/usr/bin/env cmsRun
 
 import FWCore.ParameterSet.Config as cms
@@ -21,15 +22,15 @@
 mytag       = cms.string('TauNeuralClassifier_v2')
 mytimetype  = cms.untracked.string('runnumber')
 
-print ""
-print "***************************************************"
-print "******  Upload Tau Neural Classifier to DB   ******"
-print "***************************************************"
-print "*  Using the %s algorithm                         " % algorithm
-print "*  DB tag:       %s                               " % mytag.value()
-print "*  Database:     %s                               " % myconnect.value()
-print "*  Timetype:     %s                               " % mytimetype.value()
-print "* ----------------------------------------------- "
+print("")
+print("***************************************************")
+print("******  Upload Tau Neural Classifier to DB   ******")
+print("***************************************************")
+print("*  Using the %s algorithm                         " % algorithm)
+print("*  DB tag:       %s                               " % mytag.value())
+print("*  Database:     %s                               " % myconnect.value())
+print("*  Timetype:     %s                               " % mytimetype.value())
+print("* ----------------------------------------------- ")
 
 
 process = cms.Process("TaNCCondUpload")

RecoTauTag/TauTagTools/test/database/UploadTancToDB.py

@@ -5,6 +5,7 @@
 Original author: Christopher Saout
 Modifications by Evan Friis
 '''
+from __future__ import print_function
 
 import FWCore.ParameterSet.Config as cms
 import RecoTauTag.TauTagTools.TauMVAConfigurations_cfi
@@ -35,15 +36,15 @@
 myconnect   = cms.string(options.db)  #or frontier, etc
 mytag       = cms.string(options.tag)
 mytimetype  = cms.untracked.string('runnumber')
-print ""
-print "***************************************************"
-print "******  Upload Tau Neural Classifier to DB   ******"
-print "***************************************************"
-print "*  Using the %s algorithm                         " % algorithm
-print "*  DB tag:       %s                               " % mytag.value()
-print "*  Database:     %s                               " % myconnect.value()
-print "*  Timetype:     %s                               " % mytimetype.value()
-print "* ----------------------------------------------- "
+print("")
+print("***************************************************")
+print("******  Upload Tau Neural Classifier to DB   ******")
+print("***************************************************")
+print("*  Using the %s algorithm                         " % algorithm)
+print("*  DB tag:       %s                               " % mytag.value())
+print("*  Database:     %s                               " % myconnect.value())
+print("*  Timetype:     %s                               " % mytimetype.value())
+print("* ----------------------------------------------- ")
 
 # Unpack the TaNC neural nets into a parameter set
 tempPSet   = cms.PSet()
@@ -59,7 +60,7 @@
    # god bless you, python
    tempPSet.__setattr__(aNeuralNet.computerName.value(), cms.string(mvaFileLocation))
    toCopyList.append(neuralNetName)
-   print "* %-20s %-20s      " % (neuralNetName, mvaFileLocation )
+   print("* %-20s %-20s      " % (neuralNetName, mvaFileLocation ))
 
 process = cms.Process("TaNCCondUpload")
 

RecoTauTag/TauTagTools/test/training/castor.py

@@ -1,3 +1,4 @@
+from __future__ import print_function
 # @file castor.py
 # @brief A simple helper to handle simple tasks with CASTOR
 #
@@ -209,8 +210,8 @@ def getFileSize( pathToFile = None ) :
     #'nsls -l $CASTOR_DIR/$FILE | awk -F ' ' '{print $5}'
 
     if status != 0 :
-        print "** PyCastor ERROR **"
-        print output
+        print("** PyCastor ERROR **")
+        print(output)
         return []
 
     output = output.splitlines()
@@ -253,12 +254,12 @@ def stagein( fileListPattern = None, nSlices = 10, verbose = True ) :
         stageList = ' -M '.join( [''] + [ s for s in slice ] )
         cmd = 'stager_get %s' % stageList
         if verbose :
-            print ">>> cmd= ",cmd
+            print(">>> cmd= ",cmd)
         status,output = commands.getstatusoutput(cmd)
 
         if status != 0 :
-            print "** PyCastor ERROR **"
-            print output
+            print("** PyCastor ERROR **")
+            print(output)
             pass
         else :
             if verbose :
@@ -279,10 +280,10 @@ def stager_qry(inFiles):
         cmd = "stager_qry -M %s " % ( inFile, )
         sc,out = commands.getstatusoutput( cmd )
         if sc != 0:
-            print "** PyCastor ERROR **"
-            print "## Could not check status of this file [%s] !!" % inFile
-            print "## status sc=", sc
-            print "## output out=", out
+            print("** PyCastor ERROR **")
+            print("## Could not check status of this file [%s] !!" % inFile)
+            print("## status sc=", sc)
+            print("## output out=", out)
 
         #for str in out.split():
         #   print "out_str=", str
@@ -320,29 +321,29 @@ def grep_path(schema, text):
         return paths
 
     path_list = grep_path("rfio", file_text)
-    print "rfio_file list extracted from input file =", inFile
-    print "-"*77; print path_list; print "-"*77
+    print("rfio_file list extracted from input file =", inFile)
+    print("-"*77); print(path_list); print("-"*77)
 
     def _print(str):
-        print str
+        print(str)
 
     status_dict = stager_qry(path_list)
     ready_files_list = [file for file in status_dict if status_dict[file] == 1]
-    print "---STAGED (ready to be copied):";
-    p = map(_print, ready_files_list); print "-"*77
+    print("---STAGED (ready to be copied):");
+    p = map(_print, ready_files_list); print("-"*77)
 
     noready_files_list = [file for file in status_dict if status_dict[file] == 0]
-    print "---NOT STAGED (not ready to be copied):";
-    p = map(_print, noready_files_list); print "-"*77
+    print("---NOT STAGED (not ready to be copied):");
+    p = map(_print, noready_files_list); print("-"*77)
 
     def _rfcp(file): #aux func. just for reporting purpose
-        print "rfcp ", file
+        print("rfcp ", file)
         return file
     rfcp( map(_rfcp, ready_files_list), #[file for file in ready_files_list],
           outDir  )
 
     def _stager_get(file): #aux func. just for reporting purpose
-        print "stager_get -M ", file
+        print("stager_get -M ", file)
         stager_get(file)
     map(_stager_get, noready_files_list) #[stager_get(file) for file in noready_files_list if 1 print "stager_get -M ", file]
 
@@ -357,8 +358,8 @@ def stager_get(inFile):
     cmd = "stager_get -M %s" % (inFile)
     sc,out = commands.getstatusoutput( cmd )
     if sc != 0:
-        print "** PyCastor ERROR **"
-        print "## Could not stager_get this file [%s] !!" % inFile
+        print("** PyCastor ERROR **")
+        print("## Could not stager_get this file [%s] !!" % inFile)
         allGood = False
         pass
     if allGood:
@@ -376,8 +377,8 @@ def rfcp( inFiles, outDir ):
                                              os.path.basename(inFile) ) )
         sc,out = commands.getstatusoutput( cmd )
         if sc != 0:
-            print "** PyCastor ERROR **"
-            print "## Could not copy this file [%s] !!" % inFile
+            print("** PyCastor ERROR **")
+            print("## Could not copy this file [%s] !!" % inFile)
             allGood = False
             pass
         pass
@@ -395,10 +396,10 @@ def rfstat (pathname):
     cmd = 'rfstat %s' % pathname
     sc, out = commands.getstatusoutput (cmd)
     if sc != 0:
-        print "** PyCastor ERROR **"
-        print ":: command: [%s]" % cmd
-        print ":: status:  [%s]" % sc
-        print out
+        print("** PyCastor ERROR **")
+        print(":: command: [%s]" % cmd)
+        print(":: status:  [%s]" % sc)
+        print(out)
         raise RuntimeError (sc)
 
     stat = dict()

RecoTauTag/TauTagTools/test/training/computeTransform.py

@@ -12,6 +12,7 @@
 Authors: Evan K. Friis, Christian Veelken (UC Davis)
 
 '''
+from __future__ import print_function
 
 from RecoLuminosity.LumiDB import argparse
 
@@ -29,7 +30,7 @@
 import ROOT
 import sys
 
-print "Building transformation:", options.o
+print("Building transformation:", options.o)
 
 ROOT.gROOT.SetBatch(True)
 
@@ -41,10 +42,10 @@
 signal_histo = signal_file.Get("cleanTauPlots/hpsTancTausDiscriminationByTancRaw")
 background_histo = background_file.Get("cleanTauPlots/hpsTancTausDiscriminationByTancRaw")
 
-print "Signal has %i entries in clean, %i in total" % (
-    signal_histo.Integral(), signal_denominator_histo.Integral())
-print "Background has %i entries in clean, %i in total" % (
-    background_histo.Integral(), background_denominator_histo.Integral())
+print("Signal has %i entries in clean, %i in total" % (
+    signal_histo.Integral(), signal_denominator_histo.Integral()))
+print("Background has %i entries in clean, %i in total" % (
+    background_histo.Integral(), background_denominator_histo.Integral()))
 
 # Determine the probability for a given jet to end up in this decay mode stream
 signal_scale = signal_histo.Integral()/signal_denominator_histo.Integral()
@@ -105,9 +106,9 @@ def compute_transform(raw_cut, signal_cdf, signal_scale,
     return output
 
 # Build the cumulative distribution functions
-print "Building signal c.d.f"
+print("Building signal c.d.f")
 signal_cdf = make_cdf(signal_histo)
-print "Building background c.d.f"
+print("Building background c.d.f")
 background_cdf = make_cdf(background_histo)
 transform = lambda x: compute_transform(x, signal_cdf, signal_scale,
                                         background_cdf, background_scale)
@@ -118,8 +119,8 @@ def compute_transform(raw_cut, signal_cdf, signal_scale,
     transform_values.append(transform_result['transform'])
     # Check if this is one of our cuts
     if thresholds and transform_result['signal_passing'] < thresholds[0]:
-        print "***********"
-        print x, transform_result
+        print("***********")
+        print(x, transform_result)
         thresholds.pop(0)
         threshold_values.append((x, transform_result['transform']))
 
@@ -128,7 +129,7 @@ def compute_transform(raw_cut, signal_cdf, signal_scale,
 output_object.signalDecayModeWeight = cms.double(signal_scale)
 output_object.backgroundDecayModeWeight = cms.double(background_scale)
 
-print threshold_values
+print(threshold_values)
 
 # On the chance that a decay mode has nothing in it
 if not threshold_values:
@@ -147,6 +148,6 @@ def compute_transform(raw_cut, signal_cdf, signal_scale,
 
 output_file.close()
 
-print "Transform file %s created" % options.o
+print("Transform file %s created" % options.o)
 
 sys.exit(0)

RecoTauTag/TauTagTools/test/training/dump_db.py

@@ -7,12 +7,13 @@
 Author: Evan K. Friis (UC Davis)
 
 '''
+from __future__ import print_function
 
 import FWCore.ParameterSet.Config as cms
 import sys
 import os
 
-print sys.argv
+print(sys.argv)
 
 db_file = sys.argv[2]
 mva_file = db_file.replace('.db', '.mva')

RecoTauTag/TauTagTools/test/training/evaluateMode_cfg.py

@@ -10,6 +10,7 @@
 Author: Evan K. Friis (UC Davis)
 
 '''
+from __future__ import print_function
 
 import FWCore.ParameterSet.Config as cms
 import FWCore.ParameterSet.VarParsing as VarParsing
@@ -48,7 +49,7 @@
 
 
 if options.tracks < 0 or options.pizeros < 0:
-    print "You must specify the [tracks] and [pizeros] arguments."
+    print("You must specify the [tracks] and [pizeros] arguments.")
     sys.exit(1)
 # Make a nice tuple of the decay mode
 _decay_mode = (options.tracks, options.pizeros)
@@ -75,7 +76,7 @@
     fileName = cms.string(options.outputFile)
 )
 
-print "WARNING: input branch workaround!"
+print("WARNING: input branch workaround!")
 # Input files
 process.source = cms.Source(
     "PoolSource",

RecoTauTag/TauTagTools/test/training/evaluate_cfg.py

@@ -9,6 +9,7 @@
 Author: Evan K. Friis (UC Davis)
 
 '''
+from __future__ import print_function
 
 import FWCore.ParameterSet.Config as cms
 import FWCore.ParameterSet.VarParsing as VarParsing
@@ -130,7 +131,7 @@
 # Remove the lepton discrimination
 lepton_discriminants = [name for name in process.PFTau.moduleNames()
                         if 'Muon' in name or 'Electron' in name]
-print "Removing lepton discriminants: %s" % " ".join(lepton_discriminants)
+print("Removing lepton discriminants: %s" % " ".join(lepton_discriminants))
 for lepton_discriminant in lepton_discriminants:
     module = getattr(process, lepton_discriminant)
     process.PFTau.remove(module)