fp.sim.matrix | R Documentation |
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
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
distance
, fp.read
# make fingerprint objects fp1 <- new("fingerprint", nbit=6, bits=c(1,2,5,6)) fp2 <- new("fingerprint", nbit=6, bits=c(1,4,5,6)) fp3 <- new("fingerprint", nbit=6, bits=c(2,3,4,5,6)) fp.sim.matrix( list(fp1,fp2,fp3) )
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