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


       mConvert - Convert FITS data to a different data type (ie, integer to floating-point)


       mConvert  [-d  level]  [-s  statusfile]  [-b  bitpix]  [-min minval] [-max maxval] [-blank
       blankval] in.fits out.fits


       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.


       -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.


              Input image filename

              Output image filename.


       Output image with the datatype as specified by the user (BITPIX).


       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


       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"]


       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.