doc/SmallTools/mrcImageNormalizing.html

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   3 <TITLE>mrcImageNormalizing</TITLE>
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   6 <H1>mrcImageNormalizing</H1>
   7 <H2>Usage</H2>
   8 <PRE>
   9 Usage: mrcImageNormalizing
  10 Options:
  11     [-i[nput]            In                  (NULL      )] :Essential :InputDataFile
  12     [-o[utput]           Out                 (NULL      )] :Essential :OutputDataFile
  13     [-A                  A                   (1.0       )] :Optional  :A
  14     [-B                  B                   (0.0       )] :Optional  :B
  15     [-ContourMin         ContourMin          (0.0       )] :Optional  :ContourMin
  16     [-ContourMax         ContourMax          (1.0       )] :Optional  :ContourMax
  17     [-ContourSolvent     ContourSolvent      (0.0       )] :Optional  :ContourSolvent
  18     [-c[onfig]           configFile          (NULL      )] :Optional  :ConfigurationFile
  19     [-m[ode]             mode                (0         )] :Optional  :Mode
  20 ----- mode -----
  21 ----- Mode for lmrcImageNormalizing -----
  22   0: Double Exponential: Solvent and Object
  23          Fitting histgram to double exponentials as Solvent and Object
  24                    data = A*(data-MeanOfSolvent)/(MeanOfObject-MeanOfSolvent) + B
  25   1: Min-Max: Background and Object
  26                    data = A*(data-Min)/(Max-Min) + B
  27   2: Contour
  28                    data = A*(data-ContourMin)/(ContourMax-ContourMin) + B
  29   3: Contour and Solvent
  30                    if data < ContourSolvent, data = ContourSolvent.  After this, calculate the below.
  31                    data = A*(data-ContourMin)/(ContourMax-ContourMin) + B
  32   4: No Estimation
  33                    data = A*data + B
  34   5: Assume the density as gaussion.
  35                    data = A*Normalized(data) + B , where normalized means (average=0, SD=1)
  36 </PRE>
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