Description Usage Arguments Value Author(s) See Also Examples
Given a set of fingerprints, a pairwise similarity can be calculated using the
various distance metrics defined for binary strings. This function calculates
the pairwise similarity matrix for a set of fingerprint
or
featvec
objects supplied in a list
structure. Any of the distance metrics provided by distance
can be used and the
default is the Tanimoto metric.
Note that if the the Euclidean distance is specified then the resultant matrix is a distance matrix and not a similarity matrix
1  fp.sim.matrix(fplist, fplist2=NULL, method='tanimoto')

fplist 
A list structure with each element being an object of class

fplist2 
A list structure with each element being an object of class

method 
The type of distance metric to use. The default is 
A matrix with dimensions equal to (length(fplist), length(fplist))
if
fplist2
is NULL, otherwise (length(fplist), length(fplist2))
Rajarshi Guha rajarshi.guha@gmail.com
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