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.