analyzePlot {RclusTool} | R Documentation |
Plot for data exploration/analysis
Description
Create some specific plots for data exploration/analysis.
Usage
analyzePlot(
nb,
data.sample,
selectedVar,
type = "boxplot",
hscale = 1.2,
K.max = 20,
fontsize = 11
)
Arguments
nb |
notebook in which the analyze plot will be added. |
data.sample |
list containing features, profiles and clustering results. |
selectedVar |
character vector containing the selected variables names to analyze. |
type |
character vector specifying the analysis type. Must be 'boxplot', 'gapSE', 'histo', 'pcaCorr' or 'pcaVar'. |
hscale |
numeric value corresponding to the horizontal scale of graphic. |
K.max |
maximal number of clusters (K.Max=20 by default). |
fontsize |
size of font (fontsize=11 by default). |
Details
analyzePlot creates specific plot for data exploration/analysis.
Value
None
Examples
dat <- rbind(matrix(rnorm(100, mean = 2, sd = 0.3), ncol = 2),
matrix(rnorm(100, mean = 4, sd = 0.3), ncol = 2),
matrix(rnorm(100, mean = 6, sd = 0.3), ncol = 2))
colnames(dat) <- c("x","y")
tf <- tempfile()
write.table(dat, tf, sep=",", dec=".")
x <- importSample(file.features=tf)
mainWindow <- tktoplevel()
tktitle(mainWindow) <- "Barplot clustering"
mainWindow$env$nb <- tk2notebook(mainWindow, tabs = c())
tkpack(mainWindow$env$nb, fill="both", expand= TRUE)
analyzePlot(mainWindow$env$nb, x, selectedVar="x", type="boxplot")
[Package RclusTool version 0.91.6 Index]