sigClassif: Signals clustering

View source: R/sampleClustering.R

sigClassifR Documentation

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.

Details

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

Value

signals plots images in the different directories.

See Also

imgClassif

Examples

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=".")

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

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


RclusTool documentation built on May 29, 2024, 5:23 a.m.