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.