mFixNaN(1)


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)

   -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.





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