NAME

       mFixNaN - Replace a particular set of values in a FITS image with NaNs (or vice-versa)

SYNOPSIS

       mFixNaN [-d level] [-v NaN-value] in.fits out.fits [minblank maxblank]

DESCRIPTION

       Converts  NaNs  found  in the image to some other value (given by the user), or converts a
       range of supplied values into NaNs.

OPTIONS

       -d level
              Turn on debugging to the specified level (1-3)

       -b     Check for non-physical boundary area (e.g. the corners  of  an  Aitoff  image)  and
              correct them.

       -v NaN-value
              Value to use in place of any NaNs

ARGUMENTS

       in.fits
              Input FITS image file

       out.fits
              Path  of output FITS file.  To run in "count" mode without creating an output file,
              use a dash ("-") for this argument.

       minblank maxblank
              If the "-v" switch is not used, mFixNaN  will  replace  all  pixel  values  between
              minblank and maxblank with NaN.

RESULT

       [struct stat="OK", rangeCount=rangeCount, nanCount=nanCount]

       rangeCount  is the number of pixels that were found between minblank and maxblank, if they
       were specified.  If not (i.e., NaNs were removed and replaced with value), nanCount is the
       number of NaNs removed.

MESSAGES

       OK     [struct stat="OK", rangeCount=rangeCount, nanCount=nanCount"]

       ERROR  No debug level given

       ERROR  Debug level string is invalid: level

       ERROR  Debug level string is invalid: level

       ERROR  Debug level string cannot be negative

       ERROR  No value given for NaN conversion

       ERROR  NaN conversion value string is invalid: 'NaN-value'

       ERROR  Invalid input file 'in.fits']

       ERROR  min blank value string is not a number

       ERROR  max blank value string is not a number

       ERROR  Image file in.fits missing or invalid FITS

       ERROR  FITS library error

EXAMPLES

       A FITS image with BITPIX -64 (double-precision floating point) was generated without using
       NaNs; all "blank" pixels are represented by very small negative numbers.  This  can  throw
       off  initial  attempts to display the image with a proper stretch, and does not conform to
       the FITS standard.  To replace all those "blank" pixels with NaNs:

       mFixNaN original.fits NaN.fits -4.61169e32 -4.61169e10
              [struct stat="OK", rangeCount=1321, nanCount=0]

       To convert those NaNs back into a single pixel value:

       mFixNaN -v -4.6e32 NaN.fits blankval.fits
              [struct stat="OK", rangeCount=0, nanCount=1321]

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.