RclusTool (version 0.91)

abdPlot: Abundances barplot

Description

Display the abundances barplot of a clustering.

Usage

abdPlot(label, title, point.param = c("grey", "black", "red", "blue",
  "green", "cyan", "yellow", "orange", "rosybrown", "palevioletred",
  "darkblue", "deeppink", "blueviolet", "darkgoldenrod1", "chartreuse",
  "darkorchid1", "deeppink", "coral", "darkolivegreen1", "#66C2A5",
  "#9DAE8C", "#D49A73", "#F08F6D", "#C79693", "#9E9DBA", "#9F9BC9",
  "#C193C6", "#E28BC3", "#D2A29F", "#BABF77", "#AAD852", "#CBD844",
  "#ECD836", "#FAD53E", "#F1CD64", "#E7C689", "#D7BF9C", "#C5B9A7",
  "#B3B3B3", "#D53E4F", "#E04F4A", "#EB6046", "#F47346", "#F88B51",     
  "#FBA35C", "#FDB869", "#FDCA79", "#FDDD88", "#F6E68F", "#EDEE93",
  "#E2F398", "#CDEA9D", "#B7E2A1", "#A0D8A4", "#86CEA4", "#6DC4A4",
  "#58B2AB", "#459DB4", "#3288BD"))

Arguments

label

factor describing the clustering.

title

naming the graph.

point.param

specifying the colors and the symbols to use for clusters display.

Details

abdPlot displays the abundances barplot of a clustering.

Examples

# NOT RUN {
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, dir.save=tempdir())

x <- computeUnSupervised(x, K=3, method.name='K-means')

abdPlot(x[["clustering"]][["K-means_preprocessed"]][["label"]], 'K-means_preprocessed')
 

# }