fingerprint: sim – R documentation

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sim

Calculates a Similarity Matrix for a Set of Fingerprints

Description

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

Usage

fp.sim.matrix(fplist, fplist2=NULL, method='tanimoto')

Arguments

`fplist`	A list structure with each element being an object of class `fingerprint` or `featvec`. These can be constructed by hand or read from disk via `fp.read`
`fplist2`	A list structure with each element being an object of class `fingerprint` or `featvec`. if `NULL` then traditional pairwise similarity is calculated with each member in `fplist`, otherwise the resultant N x M matrix is derived from the similarity between each member of `fplist` and `fplist2`
`method`	The type of distance metric to use. The default is `tanimoto`. Partial matching is supported.

Value

A matrix with dimensions equal to (length(fplist), length(fplist)) if fplist2 is NULL, otherwise (length(fplist), length(fplist2))

Author(s)

Rajarshi Guha rajarshi.guha@gmail.com

Examples

# 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) )

fingerprint

Functions to Operate on Binary Fingerprint Data

v3.5.7

GPL

Authors

Rajarshi Guha <rajarshi.guha@gmail.com>

Initial release

2018-01-06

sim