plotSampleFeatures: 2D-features scatter-plot

View source: R/sampleView.R

plotSampleFeaturesR Documentation

2D-features scatter-plot

Description

Plot 2D-features scatter-plot of all particles. Grey color (label=0) is for data to cleaned or to remove in classification process.

Usage

plotSampleFeatures(
  data,
  label,
  parH = NULL,
  parV = NULL,
  figure.title = "Scatter plot",
  logscale = "",
  cex = 0.8,
  point.param = expand.grid(col = 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"), pch = c(20, 0:18),
    stringsAsFactors = FALSE),
  env.plot = NULL
)

Arguments

data

matrix or data.frame of raw data (points by line).

label

vector of labels.

parH

character vector specifying the name of the feature to use as x-axis.

parV

character vector specifying the name of the feature to use as y-axis.

figure.title

character vector specifying the title of the scatter-plot.

logscale

character vector containing "x" if the x-axis is to be logarithmic, "y" if the y-axis is to be logarithmic and "xy" or "yx" if both axes are to be logarithmic.

cex

numeric value specifying the size of the graphical labels.

point.param

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

env.plot

environment where to store graphical parameters used by function PlotScatter to select points.

Details

plotSampleFeatures plots 2D-features scatter-plot of all particles

Value

None

See Also

plotProfile, visualizeSampleClustering

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")
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=".")

x <- importSample(file.features=tf1, file.profiles=tf2)

res <- KmeansQuick(x$features$initial$x, K=3)
new.labels <- formatLabelSample(res$cluster, x)

plotSampleFeatures(x$features$initial$x, label = new.labels, parH="x", parV="y")



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