NAME

       mHistogram - None

SYNOPSIS

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

DESCRIPTION

       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.

OPTIONS

       -d

              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.

RESULT

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

MESSAGES

       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 number

       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

EXAMPLES

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

BUGS

       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.

COPYRIGHT

       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 Technology."

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

Montage 5                                           Dec 2016                                       MHISTOGRAM(1)