cals-methods {msbase}R Documentation

Similarity by user defined function

Description

Compute similarity between two Massvectors using a similarity function passed to argument msim

Arguments

obx see below in Methods section
oby see above in Methods section
error measurement error
ppm if TRUE then error in parts per million, in arbitrary units otherwise
msim similarity function
p argument to similarity function
uniq if TRUE compute optimal aligmnent

Value

Scalar, Vector or object of class dist

Methods

obx = "numeric", oby = "numeric"
given two vectors computes alignement and similarity using function passed to arguement mdist
obx = "Massvector", oby = "Massvector"
same for Massvectors
obx = "Massvectorlist", oby = "Massvector"
compute similarities between Massvector and Massvectorlist
obx = "Massvectorlist", oby = "NULL"
computes object of class dist casting the similarities into distances

Author(s)

Witold E. Wolski witek96@users.sourceforge.net

See Also

calssim,calsrange

Examples

data(pldata)
pl1 <- pldata[[1]]
pl2 <- pldata[[2]]
cals(pl1,pl2,error=400,ppm=TRUE,msim=calssim,p=3)
cals(pl1,pl2,error=400,ppm=TRUE,msim=calsrange)
tmp <- cals(pldata,NULL,error=400,ppm=TRUE,msim=calssim,p=3)
plot(hclust(tmp,method="average"))

[Package msbase version 1.4.0 Index]