[Jboost-cvs] jboost/scripts VisualizeScores.py,1.4,1.5

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Update of /cvsroot/jboost/jboost/scripts
In directory sc8-pr-cvs17.sourceforge.net:/tmp/cvs-serv24863/scripts

Modified Files:
	VisualizeScores.py 
Log Message:
First version of visualizeScores.py that computes fluctuations in scores between folds.

Index: VisualizeScores.py
===================================================================
RCS file: /cvsroot/jboost/jboost/scripts/VisualizeScores.py,v
retrieving revision 1.4
retrieving revision 1.5
diff -C2 -d -r1.4 -r1.5
*** VisualizeScores.py	10 Sep 2008 00:19:25 -0000	1.4
--- VisualizeScores.py	11 Sep 2008 04:14:40 -0000	1.5
***************
*** 4,33 ****

  args = sys.argv[1:]
! if len(args) != 1:
!     sys.exit("""
!     Usage: VisualizeScore <info-files-path>
!     info-file-path is a directory containing files with names like trial0.test.boosting.info, trial2.train.boosting.info ...
!     Example: perform the following commands from the jboost root directory
!     <setup classpath to point to jython>
!     source scripts/setClassPath.sh
!     cd demo
!     cat spambase.test spambase.train > spambase.data
!     ../scripts/nfold.py --folds=3 --data=spambase.data --spec=spambase.spec --rounds=43 --tree=ADD_ALL --generate --booster=LogLossBoost
!     jython ../scripts/VisualizeScores.py cvdata-09-09-17-00-55/ADD_ALL/
!     """)
! info_path = args[0]

  header_p = re.compile('iteration=(\d+): elements=(\d+):')
  scoreline_p = re.compile('([-+\d.]+):\s+') #([+-1]+):')

  testfiles = glob.glob(info_path+"trial*.test.boosting.info")

  #testfiles = glob.glob("/Users/yoavfreund/Downloads/dc_boost_active_output/iter?/*.test.boosting.info")

  #testfiles = glob.glob("/Users/yoavfreund/projects/jboost/demo/cvdata-09-09-17-00-55/ADD_ALL/trial*.test.boosting.info")
  print testfiles
! indexes={}
! scores={}
! labels={}

  #find the iteration indices
--- 4,35 ----

  args = sys.argv[1:]
! #if len(args) != 1:
! #    sys.exit("""
! #    Usage: VisualizeScore <info-files-path>
! #    info-file-path is a directory containing files with names like trial0.test.boosting.info, trial2.train.boosting.info ...
! #    Example: perform the following commands from the jboost root directory
! #    <setup classpath to point to jython>
! #    source scripts/setClassPath.sh
! #    cd demo
! #    cat spambase.test spambase.train > spambase.data
! #    ../scripts/nfold.py --folds=3 --data=spambase.data --spec=spambase.spec --rounds=43 --tree=ADD_ALL --generate --booster=LogLossBoost
! #    jython ../scripts/VisualizeScores.py cvdata-09-09-17-00-55/ADD_ALL/
! #    """)
! #info_path = args[0]

  header_p = re.compile('iteration=(\d+): elements=(\d+):')
  scoreline_p = re.compile('([-+\d.]+):\s+') #([+-1]+):')

+ info_path = "/Users/yoavfreund/projects/jboost/demo/cvdata-09-10-13-54-55/ADD_ALL/"
+ 
  testfiles = glob.glob(info_path+"trial*.test.boosting.info")
+ trainfiles = glob.glob(info_path+"trial*.train.boosting.info")

  #testfiles = glob.glob("/Users/yoavfreund/Downloads/dc_boost_active_output/iter?/*.test.boosting.info")

  #testfiles = glob.glob("/Users/yoavfreund/projects/jboost/demo/cvdata-09-09-17-00-55/ADD_ALL/trial*.test.boosting.info")
+ 
  print testfiles
! exampleData={}

  #find the iteration indices
***************
*** 56,68 ****
  # read the data into the Dataset data structures.
  for filename in testfiles:
-     print filename
      infile = open(filename,'r')
      iterList=[];
      for line in infile:
-         print line
          [(iter,elements)] = header_p.findall(line)
          iterationIndex=iterDict[iter]
          elements = int(elements)
-         print "iter=%s iterationIndex=%d elements=%d\n" % (iter,iterationIndex, elements)

          for count in range(elements):
--- 58,67 ----
***************
*** 70,86 ****
              #print line
              a = scoreline_p.findall(line)
!             index=int(a[0])
!             score=float(a[2])
              label=int(a[-1])
              e=DataElement(score,index,label)
              d.addDataElement(e,iterationIndex)

- print "going to preprocess\n"
  d.preProcessDataset()
! print "finisehd preprocessing\n"

! print "min= %f, max=%f\n" % (d.getMin(),d.getMax())

! v=HistogramFrame(d)

- v.show()
--- 69,157 ----
              #print line
              a = scoreline_p.findall(line)
!             index=int(a[1])
!             score=float(a[3])
              label=int(a[-1])
+             if not exampleData.has_key(index):
+                 exampleData[index]={"label":label, "scores":{} }
+             exampleData[index]["scores"][int(iter)] = {"test":score, "train":[]}
              e=DataElement(score,index,label)
              d.addDataElement(e,iterationIndex)

  d.preProcessDataset()
! lowestScore = d.getMin()
! highestScore = d.getMax()
! print "lowestScore=%f, highestScore=%f\n" % (lowestScore,highestScore)
! v=HistogramFrame(d)
! v.show()

! print len(exampleData)

! for filename in trainfiles:
!     print filename
!     infile = open(filename,'r')
!     for line in infile:
!         [(iter,elements)] = header_p.findall(line)
!         iterationIndex=iterDict[iter]
!         elements = int(elements)
! 
!         for count in range(elements):
!             line=infile.readline()
!             #print line
!             a = scoreline_p.findall(line)
!             index=int(a[1])
!             score=float(a[3])
!             label=int(a[-1])
!             if exampleData.has_key(index):
!                 exampleData[index]["scores"][int(iter)]["train"].append(score)
!             #else:
!                 #print "missing index=%d\n" % index
! 
!   
! iterList = exampleData[0]["scores"].keys()
! iterList.sort()
! 
! fluctBins=10
! fluct = {}
! for iter in iterList:
!     fluct[iter] = [{"sum":0.0, "sumSquare":0.0, "count":0} for i in range(fluctBins)]
! 
! for index in exampleData.keys():
!     for iter in iterList:
!         testScore=exampleData[index]["scores"][iter]["test"]
!         maxDiff=0
!         for trainScore in  exampleData[index]["scores"][iter]["train"]:
!             maxDiff = max(maxDiff,abs(trainScore-testScore))
!         exampleData[index]["scores"][iter]["maxDiff"]=maxDiff
!         bin = int((testScore-lowestScore)/(highestScore-lowestScore)*fluctBins)
!         bin = min(bin,fluctBins-1)
!         fluct[iter][bin]["count"] += 1
!         fluct[iter][bin]["sum"] += maxDiff
!         fluct[iter][bin]["sumSquare"] += maxDiff*maxDiff
!          
! from math import sqrt
! 
! step = (highestScore-lowestScore)/fluctBins
! for iter in iterList:
!     print "iteration %d\n" % iter
!     for bin in range(fluctBins):
!         count = fluct[iter][bin]["count"]
!         if count>0:
!             mean = fluct[iter][bin]["sum"] / count
!             meanSquare = fluct[iter][bin]["sumSquare"] / count
!             std = sqrt(meanSquare-mean*mean)
!         else:
!             mean=0
!             std=0
!         fluct[iter][bin]["mean"]=mean
!         fluct[iter][bin]["std"]=std
!         fl=fluct[iter][bin]
!         r=lowestScore + bin*step
!         print "\t[%f,%f] count=%d, mean=%f, std=%f\n" % (r,r+step,count,mean,std)
! 
! #for index in range(5):
! #    print "%d: label=%d\n" % (index,exampleData[index]["label"])
! #    for iterNo in iterList:
! #        print ("%d: " % iterNo)
! #        print exampleData[index]["scores"][iterNo]
!     