Provided by: montage_6.0+dfsg-6_amd64 bug


       mHistogram - None


       mHistogram  [-d]  -file  in.fits  minrange  maxrange [logpower/gaussian/gaussian-log/asinh
       [asinh-beta]] -out out.hist


       The mViewer application makes PNG/JPEG files using FITS images as  input.   Part  of  that
       processing  involves  analyzing  the  FITS  files and creating a histogram that is used to
       inform  the  transformation  from  pixel  values  to  display  colors/intensities.    This
       processing is done inside mViewer itself.

       However, there are situations where it helps to have the histogram earlier.  For instance,
       you may have several images to process into PNGs and wish to use the same  histogram-based
       stretch  for  each  one.   Or you may want to generate a set of pixel values that give the
       visual impression of a color bar (see mPad). Sometimes, you may just  want  the  histogram
       itself for display or analysis purposes.

       The  mHistogram  module contains the same histogram code as mViewer but writes the results
       out to an ASCII file which can then be read in by mHistogram, mPad or user programs.



              Turn on debugging.

       -file in.fits minrange maxrange [logpower/gaussian/gaussian-log/asinh [asinh-beta]]

              The FITS image file; stretch range; and (optionally) stretch mode.  See the mViewer
              documentation for more details.

       -out out.hist

              Output histogram (ASCII) file.


       If  successful,  the  result  is  an ASCII file containing the histogram data, color table
       lookup mapping, and some other information.


       ERROR  Too few arguments following -file flag

       ERROR  Image file badfile invalid FITS

       ERROR  Can't find HDU badHDU

       ERROR  Too few arguments following -out flag

       ERROR  No input FITS file name given

       ERROR  No output histogram file name given

       ERROR  Cannot open output histogram file.

       ERROR  Grayscale/pseudocolor mode but no gray image given

       ERROR  FITS library error

       ERROR  leading numeric term in 'string' cannot be converted to  a  finite  floating  point

       ERROR  not a valid datatype

       ERROR  negative percentile

       ERROR  percentile context larger than 100

       ERROR  extra  numeric  term  in context 'string'  cannot be converted to a finite floating
              point number

       ERROR  context 'string' contains trailing junk


       mHistogram -file SDSS_r.fits -2s max gaussian-log -out SDSS_r.hist
              [struct stat="OK"]


       The drizzle algorithm has been implemented but has not been tested in this release.

       If a header template contains  carriage  returns  (i.e.,  created/modified  on  a  Windows
       machine),  the cfitsio library will be unable to read it properly, resulting in the error:
       [struct stat="ERROR", status=207, msg="illegal character in keyword"]

       It is best for the background correction algorithms if the area described  in  the  header
       template  completely encloses all of the input images in their entirety. If parts of input
       images are "chopped off" by  the  header  template,  the  background  correction  will  be
       affected.  We  recommend  you  use  an expanded header for the reprojection and background
       modeling steps, returning to the originally desired header size for the final  coaddition.
       The default background matching assumes that there are no non-linear background variations
       in the individual images (and therefore in the  overlap  differences).  If  there  is  any
       uncertainty  in  this  regard, it is safer to turn on the "level only" background matching
       (the "-l" flag in mBgModel.


       2001-2015 California Institute of Technology, Pasadena, California

       If your research  uses  Montage,  please  include  the  following  acknowledgement:  "This
       research  made use of Montage. It is funded by the National Science Foundation under Grant
       Number ACI-1440620, and was previously  funded  by  the  National  Aeronautics  and  Space
       Administration's  Earth Science Technology Office, Computation Technologies Project, under
       Cooperative Agreement Number  NCC5-626  between  NASA  and  the  California  Institute  of

       The  Montage  distribution  includes an adaptation of the MOPEX algorithm developed at the
       Spitzer Science Center.