analyzePlot: Plot for data exploration/analysis

In RclusTool: Graphical Toolbox for Clustering and Classification of Data Frames

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")

RclusTool documentation built on Aug. 29, 2022, 9:07 a.m.