Plot method for BRIL.Filtering objects

Source: R/filter_outliers.R

Plot method for BRIL.Filtering objects

# S3 method for BRIL.Filtering
plot(
  x,
  contents = c("p.values", "scatterplot", "dist", "hist"),
  showCenter = TRUE,
  showSelection = TRUE,
  col = "black",
  colSelection = "red",
  colCenter = "orange",
  mtextTitles = TRUE,
  mfrow,
  ...
)

Arguments

x

An object of class BRIL.Filtering (see filter_outliers())
contents

Contents to be displayed, options are "p.values", "scatterplot", "dist", "hist" and "all"
showCenter

Logical value, to show the center used in the filtering
showSelection

Logical value, to highlight the samples selected by the filtering process
col

Default color for non-selected samples (default: "black")
colSelection

Color of the selected samples (default: "red")
colCenter

Color for the center in "scatterplot" (default: "orange")
mtextTitles

Logical value, TRUE to set smaller titles/subtitles on top, FALSE to use the default plot title options.
mfrow

Number of rows and columns of the figure (example: c(4,1))
...

Other arguments passed to or from other methods (such as pch for the symbols, main and sub for title and subtitle, xlab, xmin, ...)

Details

Red intercept lines correspond to the selection based on the p.values exceeding the given threshold.
To display all the p.values, rerun the function filter_outliers() with the parameter debug = TRUE

contents options:

  • "p.values" provides a plot of the test p.values (in function of the subset size)

  • "scatterplot" displays the data in cartesian coordinates. Selected samples are displayed in red, and the center used to compute distances as an orange cross

  • "dist" shows the distances of each sample to the center provided in filter_outliers() (in function of sample index)

  • "hist" draws an histogram of the distances of the samples to the center provided in filter_outliers()

  • "all" displays a figure with all of the options above

See also

filter_outliers(), print.BRIL.Filtering(), bril(), median_rec(), median_mv(), depth_values()

Examples


# Illustrative data
XY <- rbind(
  mvtnorm::rmvnorm(300, c(0, 0), diag(2) * 3 - 1),
  mvtnorm::rmvnorm(100, c(15, 20), diag(2)),
  mvtnorm::rmvnorm(150, c(-10, 15), diag(2) * 2 - 0.5),
  mvtnorm::rmvnorm(200, c(5, 5), diag(2) * 200)
)

# Process the data
filtering <- filter_outliers(XY, median_rec(XY)$median, test = "DIP", debug = TRUE)

# Plot all default figures
plot(filtering)


# Plot P.Values and Scatterplot only
plot(filtering, contents = c("pvalues", "scatterplot"))


# Change the layout to vertical
plot(filtering, contents = c("pvalues", "scatterplot"), mfrow = c(2, 1))


# Remove title, subtitle, and axis labels
plot(filtering, contents = "scatterplot", main = "", sub = "",
  ylab = "", xlab = "")


# Other graphical options
plot(filtering, contents = "scatterplot", asp = 1,
  xlim = c(-30, 30), ylim = c(-30, 30))


plot(filtering,
  contents = "scatterplot", asp = 1, pch = 4, lwd = 2, col = "blue",
  colSelection = "green", showCenter = FALSE
)


plot(filtering, contents = "hist", main = "My Histogram",
  showSelection = FALSE, breaks = 50)