Description of the program: xc2

Cross-correlation integral of two data sets (i.e. two columns in a ssingle file) in 2 to M embedding dimensions. Together with the (auto-)correlation intergrals of each of the two sets, this gives an impression of their similarity or dissimilarity. If the minimal number of centers n is small, the program is fast but the results suffer from large statistical fluctuations on the large length scales. Apart from statistical fluctuations, the results are invariant under the exchange of the sequence of the two files.

As a special case, it is possible (but somewhat inefficient) to compute an ordinary correlation integral by taking the two sets to be the same. This can be done by selecting the same column twice, for example -c1,1 .

Usage:

xc2 -M# -n# -t# [other options] file

Everything not being a valid option will be interpreted as a potential datafile name.

Possible options are:

Option Description Default
-M# maximal embedding dimension to be specified!
-n# minimal number of centers to be specified!
-t# minimal time separation to be specified!
-d# delay for the embedding 1
-N# maximal number of pairs 1000
-## number of length scale values 2 per octave
-r# minimal length scale smallest distance of points in 2 dimensions
-R# maximal length scale MAX(xmax-xmin,ymax-ymin)
-l# maximal number of values to read from files read whole file
-x# number of lines to be skipped at the beginning 0
-c#[,#] columns to be read 1,2
-o# output file name file_xc2
where mm is the embedding dimension.
-V# verbosity level 0 (= report only fatal errors)
-h show these options none

Description of the Output:

Output: files outfile_mm for each embedding dimension between mm=2 and mm=M, containing in the second column the fraction of pairs of points with distance smaller than the value reportet in the first column.
View the FORTRAN source.
See also c2 and d2
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