xenial (1) mConvert.1.gz

Provided by: montage_4.0+dfsg-3_amd64 bug

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.

       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.