Provided by: montage_6.1+dfsg-1build1_amd64 
      
    
NAME
       mConvert - Convert FITS data to a different data type (ie, integer to floating-point)
SYNOPSIS
       mConvert  [-d  level]  [-s  statusfile] [-b bitpix] [-min minval] [-max maxval] [-blank blankval] in.fits
       out.fits
DESCRIPTION
       mConvert changes the datatype of an image.  When converting to floating point, no additional  information
       is  needed.   However,  when converting from higher precision (e.g. 64-bit floating point) to lower (e.g.
       16-bit integer), scaling information is necessary.  This can be given explicitly by the user  or  guessed
       by the program.
OPTIONS
       -d level
              Turns on debugging to the specified level (1-3).
       -s statusfile
              mBgModel output and errors are written to statusfile instead of to stdout.
       -b bitpix
              BITPIX value for the output FITS file (default is -64).  Possible values are:
              8  (character  or  unsigned  binary  integer)  16 (16-bit integer) 32 (32-bit integer) -32 (single
              precision floating point) -64 (double precision floating point).
       -min minval
              Pixel data value in the input image which should be treated as a  minimum  (value  of  0)  in  the
              output image when converting from floating point to integer.  (default for BITPIX 8: 0; BITPIX 16:
              -32767; BITPIX 32: -2147483647
       -max maxval
              Pixel  data  value in the input image which should be treated as a maximum (value of 255 or 32768)
              in the output image when converting from floating point to integer. (Default for  BITPIX  8:  255;
              BITPIX 16: 32768; BITPIX 32: 2147483648)
       -blank blankval
              If  converting  down  to an integer scale: value to be used in the output image to represent blank
              pixels (NaN) from the input image. Default value is minval.
ARGUMENTS
       in.fits
              Input image filename
       out.fits
              Output image filename.
RESULT
       Output image with the datatype as specified by the user (BITPIX).
MESSAGES
       OK     [struct stat="OK"]
       ERROR  No status file name given
       ERROR  Cannot open status file: statusfile
       ERROR  No debug level given
       ERROR  Debug level string is invalid: 'debug-level'
       ERROR  Debug level value cannot be negative
       ERROR  No bitpix value given
       ERROR  Bitpix string is invalid: 'bitpix'
       ERROR  Bitpix must be one of (8, 16, 32, -32, -64)
       ERROR  No range min value given
       ERROR  Range min string is invalid: 'min'
       ERROR  No range max value given
       ERROR  Range max string is invalid: 'max'
       ERROR  No blank value given
       ERROR  Blank string is invalid: 'blank'
       ERROR  Invalid input file 'in.fits'
       ERROR  Invalid output file 'out.fits'
       ERROR  general error message
       ERROR  FITS library error message
EXAMPLES
       Converting a single-precision image down to a 16-bit integer BITPIX, when the data is  clustered  between
       values of -0.01 and 0.1:
       $ mConvert -b 16 -min -0.01 -max 0.1 -blank -32767 acs.fits acs_bitpix16.fits
              [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                                         MCONVERT(1)