[Jboost-cvs] jboost/scripts VisualizeScores.py,1.5,1.6

[Yoav F. <yf...@us...>]

Update of /cvsroot/jboost/jboost/scripts
In directory sc8-pr-cvs17.sourceforge.net:/tmp/cvs-serv2628/scripts

Modified Files:
	VisualizeScores.py 
Log Message:
Visualizing fluctuations.

Index: VisualizeScores.py
===================================================================
RCS file: /cvsroot/jboost/jboost/scripts/VisualizeScores.py,v
retrieving revision 1.5
retrieving revision 1.6
diff -C2 -d -r1.5 -r1.6
*** VisualizeScores.py	11 Sep 2008 04:14:40 -0000	1.5
--- VisualizeScores.py	11 Sep 2008 21:25:45 -0000	1.6
***************
*** 82,87 ****
  highestScore = d.getMax()
  print "lowestScore=%f, highestScore=%f\n" % (lowestScore,highestScore)
- v=HistogramFrame(d)
- v.show()
  
  print len(exampleData)
--- 82,85 ----
***************
*** 111,157 ****
  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]
-     
  
--- 109,150 ----
  iterList.sort()
  
! fluctBins=20
! percentage=0.05
! barHeight=6
! binWidth = (highestScore-lowestScore)/fluctBins
  fluct = {}
  for iter in iterList:
!     fluct[iter] = [ {"trainScores":[]} for i in range(fluctBins)]
  
! for iterNo in range(len(iterList)):
!     iter = iterList[iterNo]
!     print "iteration %d\n" % iter
!     for index in exampleData.keys():
          testScore=exampleData[index]["scores"][iter]["test"]
!         bin = int((testScore-lowestScore)/binWidth)
          bin = min(bin,fluctBins-1)
!         for trainScore in  exampleData[index]["scores"][iter]["train"]:
!             fluct[iter][bin]["trainScores"].append(trainScore)
  
!     y=0
      for bin in range(fluctBins):
!         fluct[iter][bin]["trainScores"].sort()
!         n=len(fluct[iter][bin]["trainScores"])
!         if n>10:
!             bottom = fluct[iter][bin]["trainScores"][int(n*percentage)]
!             top = fluct[iter][bin]["trainScores"][int(n*(1-percentage))]
!             yMax = y
!             yMin = y-barHeight
!             y=y-1.1*barHeight
!             fluct[iter][bin]["bottom"] = bottom
!             fluct[iter][bin]["top"]=top
!             fluct[iter][bin]["yMin"]=yMin
!             fluct[iter][bin]["yMax"]=yMax
!             
!             print "[%f,%f] -> [%f,%f] X [%f,%f]\n" % (lowestScore+bin*binWidth,lowestScore+(bin+1)*binWidth,bottom,top,yMin,yMax)
!             d.addFluctItems(iterNo, lowestScore+bin*binWidth, lowestScore+(bin+1)*binWidth, bottom, top, yMin, yMax)
!             fluct[iter][bin]["trainScores"] = []
  
  
+ v=HistogramFrame(d)
+ v.show()