inst/unitTests/runit.getSeqKernel.R

In krm: Kernel Based Regression Models

library("RUnit")
library("krm")

test.getSeqKernel <- function() {


tolerance=1e-3
# more stringent tolerance for one system to ensure algorithm accuracy
if (R.Version()$system %in% c("x86_64, mingw32")) {
    tolerance=1e-6
} 
RNGkind("Mersenne-Twister", "Inversion")


fileName=paste(system.file(package="krm")[1],'/misc/SETpfamseed_aligned_for_testing.fasta', sep="")

K=getSeqKernel (fileName, kern.type="mi", tau=.01, call.C=T)
checkEqualsNumeric(
    c(K[1:2, 1:2])
    , 
    c(1.0000000, 0.1038921, 0.1038921, 1.0000000)
    , tolerance = tolerance
)

## compare R and C implementation, commented out b/c it takes a while to run
#K.1=getSeqKernel (fileName, kern.type="mi", tau=.01, call.C=FALSE)
#checkEqualsNumeric(K, K.1, tolerance = tolerance)

# test K^0.01 and tau=1
K=getSeqKernel (fileName, kern.type="mi", tau=1, call.C=T)
checkEqualsNumeric(
    c((K^0.01)[1:2, 1:2])
    , 
    c(1.0000000, 0.1038921, 0.1038921, 1.0000000)
    , tolerance = tolerance
)

# test seq.alignment
seq.alignment <- readFastaFile(fileName)
K=getSeqKernel (seq.alignment[1:2], kern.type="mi", tau=.01)
checkEqualsNumeric(
    c(K[1:2, 1:2])
    , 
    c(1.0000000, 0.1038921, 0.1038921, 1.0000000)
    , tolerance = tolerance
)

# test subsequence and call.C
seq.alignment <- readFastaFile(fileName)
K=getSeqKernel (seq.alignment[1:2], kern.type="mi", tau=.01, seq.start=100, seq.end=200)
K.1=getSeqKernel (seq.alignment[1:2], kern.type="mi", tau=.01, seq.start=100, seq.end=200, call.C=FALSE)
checkEqualsNumeric(
    c(K[1:2, 1:2])
    , 
    c(K.1[1:2, 1:2])
    , tolerance = tolerance
)





#aaList=c("A","C","D","E","F","G","H","I","K","L","M","N","P","Q","R","S","T","V","W","Y","-")
#sequences=as.list(aaList[-21])
#names(sequences)=aaList[-21]
#K.aa=getSeqKernel (sequences, kern.type="mi", tau=1)


}