fp.distance {fingerprint} | R Documentation |
A number of distance metrics can be calculated for binary fingerprints. These metrics can be used to evaluate similarity/dissimilarity between fingerprints and hence are useful for clustering purposes. The function currently allows the evaluation of 4 distance metrics
fp.distance(fp1, fp2, size=1024, type='tanimoto', ...)
fp1 |
A fingerprint vector |
fp2 |
A fingerprint vector |
size |
The length of the fingerprints being considered |
type |
The type of distance metric desired. Alternative values are
euclidean and dice and mt
|
... |
Currently not used, but will be used to supply arguments to the Tversky metric (a generalization of the Tanimoto and Dice metrics) |
Numeric representing the distance in the specified metric between the supplied fingerprint vectors
Rajarshi Guha rguha@indiana.edu
Fligner, M.A.; Verducci, J.S.; Blower, P.E.; A Modification of the Jaccard-Tanimoto Similarity Index for Diverse Selection of Chemical Compounds Using Binary Strings, Technometrics, 2002, 44(2), 110-119
# make a 2 fingerprint vectors fp1 <- fp.from.bstring("110011") fp2 <- fp.from.bstring("110011") # calculate the tanimoto coefficient fp.distance(fp1,fp2,6) # should be 1 # Invert the second fingerprint fp3 <- fp.not(fp2, 6) fp.distance(fp1,fp3,6) # should be 0