RclusTool (version 0.91)

sigClassif: Signals clustering

Description

Sort signals (if available) in different directories according to a clustering result.

Usage

sigClassif(data.sample, method, user.name = "")

Arguments

data.sample

list containing features, profiles and clustering results.

method

character vector specifying the clustering method (already performed) to use.

user.name

character vector specifying the user name.

Value

signals plots images in the different directories.

Details

sigClassif sorts signals (if available) in different directories according to a clustering result

See Also

imgClassif

Examples

# NOT RUN {
dat <- rbind(matrix(rnorm(100, mean = 0, sd = 0.3), ncol = 2), 
             matrix(rnorm(100, mean = 2, sd = 0.3), ncol = 2), 
             matrix(rnorm(100, mean = 4, sd = 0.3), ncol = 2))
tf1 <- tempfile()
write.table(dat, tf1, sep=",", dec=".")

sig <- data.frame(ID=rep(1:150, each=30), SIGNAL=rep(dnorm(seq(-2,2,length=30)),150))
tf2 <- tempfile()
write.table(sig, tf2, sep=",", dec=".")

x <- importSample(file.features=tf1,file.profiles = tf2, dir.save=tempdir())
x <- computeUnSupervised(x, K=3, method.name="K-means")

sigClassif(x, method = "K-means_preprocessed")
 

# }