Nothing
AAdescriptor <-
function(data,descriptor=151,normalize=0) {
#################################################catch missing or bad input
if(missing(data))
stop("data argument missing")
else
if(!(is.character(data)))
stop("invalid argument: data argument is required to be a vector of amino acids")
if(!is.numeric(descriptor) | descriptor > 533 | descriptor < 1)
stop("invalid argument: descriptor is required to be 1 <= n <= 533")
if(!is.numeric(normalize) | normalize > 2 | normalize < 0)
stop("invalid argument: normalization argument is required to be {1,2,3}")
if(missing(descriptor))
descriptor = 151
if(missing(normalize))
normalize = 0
################################################Encoding
#load("descriptors.RData")
data(AAindex)
indices <- AAindex[,1]
AAindex = AAindex[,-1]
descriptor = round(descriptor)
normalize = round(normalize)
max_value = max(AAindex[descriptor,])
################################################Determine normalization function to use
if(normalize==0) { norm <- function(data,max_value) { return(data) } }
if(normalize==1) { norm <- function(data,max_value) { return(data/max_value) } }
if(normalize==2) { norm <- function(data,max_value) { return((data+max_value)/(max_value*2)) } }
#data.encoded = list()
data.encoded <- vector("list", length(data))
for(n in 1:length(data)) {
data.encoded.tmp = c()
data.tmp = unlist(strsplit(data[n],""))
for(m in 1:length(data.tmp)){ data.encoded.tmp = c(data.encoded.tmp, AAindex[descriptor, data.tmp[m]]) }
data.encoded[[n]] <- norm(data.encoded.tmp, max_value)
}
names(data.encoded) <- names(data)
return(data.encoded)
}
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