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      Cross-correlate two N-dimensional images or autocorrelate an image
     
acrosscorr  infile1 infile2 outfile [crop] [pad] [center] [clobber]
[verbose] [kernel] 
      
         Compute the correlation of two
         N-dimensional images or compute the
         autocorrelation of a single N-D image (when infile2 is set to "NONE").
       
         `acrosscorr' uses the FFT method of computing the cross-correlation, which
         assumes that the edges wrap around. The cross-correlation of two arrays
         is computed as:
          C = inverseFFT( FFT(A) * FFT(B)' )
         which differs from FFT convolution only in the complex conjugation of
         the FFT of the 2nd array.  
       
acrosscorr infile1=sig1.fits infile2=sig2.fits outfile=my_out.fits
            
               Correlate the arrays (stored as images) in files sig1.fits and
               sig2.fits and store the results in my_out.fits 
             
acrosscorr infile1=my_evts.fits[STDEVT][bin time=0:10000:1]
infile2=none outfile=/tmp/time.fits center=yes
            
               Creates a 1-D "image" from the STDEVT table in the file my_evts.fits,
               binned on the time column from 0 to 10000 in 1 [unit] bins, then
               calculates the autocorrelation of this image. The output is centered
               such that 0 offset is in the center of the array. 
             
acrosscorr infile1=sig1.fits infile2=bigger_sig2.fits
outfile=/tmp/my_out.fits crop=yes
            
               The output is cropped to the size of sig1.fits
             
            First input image file.
          
            
               The input image can
               have the following data types:  "short" (BITPIX=16), "long"
               (BITPIX=32), "float" (BITPIX=-32), and "double" (BITPIX=-64).  Complex
               inputs are not currently supported. Alternatively a FITS binary table
               can be binned using the datamodel syntax to specify the image (see
               example). 
             
            Second input image file. If infile2 is "NONE" (or 'none'), then the autocorrelation of infile1 is
            computed.  Otherwise, the syntax is the same as for infile1.
          
Parameter=outfile (file required filetype=output autoname=yes)
            Output image file.
          
            
               The output image is an image of type FLOAT (32bit IEEE floating point
               number). The pad and crop parameters determine the output
               size. By default, the output image is the maximum size in each direction
               from both input files.  Thus if infile1 is 5x2 and infile2 is 3x3, the
               output will be 5x3.  The autoname filename suffix is "_corr".
             
            If crop = yes, the output is cropped to the size of infile1.
          
            
               If crop = yes, the output is cropped to the size of infile1.  Cropping
               is done after the correlation is performed, so if both crop and pad
               are set to "yes", the final output will be cropped.
             
            If pad = yes, the data are padded to the size of infile1 + infile2.
          
            
               If pad = yes, the data are padded to the size of infile1 +
               infile2. Padding is done before the correlation is performed. 
             
            If center=yes, the zero-offset point will be in the center of the
            output data array. Otherwise, it will be at the 1 pixel location.
          
            Clobber existing output files?
          
            Processing verbosity; 0 is no output, 5 is high verbosity.
          
            Output format.  Can be "fits", "iraf", or "default", where 'default' uses
            the format of the input files.
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