View source: R/sampleClustering.R
sigClassif | R Documentation |
Sort signals (if available) in different directories according to a clustering result.
sigClassif(data.sample, method, user.name = "")
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. |
sigClassif sorts signals (if available) in different directories according to a clustering result
signals plots images in the different directories.
imgClassif
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")
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