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Visualize Variables Factor Map

Source: R/AllGenerics.R, R/viz_coordinates.R
viz_variables.Rd

Plots column/variable principal coordinates.

Usage

viz_variables(x, ...)

viz_columns(x, ...)

# S4 method for class 'MultivariateAnalysis'
viz_columns(
  x,
  ...,
  axes = c(1, 2),
  active = TRUE,
  sup = TRUE,
  labels = FALSE,
  extra_quali = NULL,
  extra_quanti = NULL,
  color = NULL,
  fill = FALSE,
  symbol = FALSE,
  size = c(1, 6),
  xlim = NULL,
  ylim = NULL,
  main = NULL,
  sub = NULL,
  panel.first = NULL,
  panel.last = NULL,
  legend = list(x = "topleft")
)

# S4 method for class 'MultivariateBootstrap'
viz_columns(
  x,
  ...,
  axes = c(1, 2),
  color = FALSE,
  fill = FALSE,
  symbol = FALSE
)

# S4 method for class 'PCA'
viz_variables(
  x,
  ...,
  axes = c(1, 2),
  active = TRUE,
  sup = TRUE,
  labels = list(filter = "contribution", n = 10),
  extra_quali = NULL,
  extra_quanti = NULL,
  color = NULL,
  symbol = NULL,
  size = 1,
  xlim = NULL,
  ylim = NULL,
  main = NULL,
  sub = NULL,
  panel.first = NULL,
  panel.last = NULL,
  legend = list(x = "topleft")
)

# S4 method for class 'CA'
viz_variables(
  x,
  ...,
  axes = c(1, 2),
  active = TRUE,
  sup = TRUE,
  labels = FALSE,
  extra_quali = NULL,
  extra_quanti = NULL,
  color = NULL,
  fill = FALSE,
  symbol = FALSE,
  size = c(1, 6),
  xlim = NULL,
  ylim = NULL,
  main = NULL,
  sub = NULL,
  panel.first = NULL,
  panel.last = NULL,
  legend = list(x = "topleft")
)

# S4 method for class 'BootstrapPCA'
viz_variables(
  x,
  ...,
  axes = c(1, 2),
  color = FALSE,
  fill = FALSE,
  symbol = FALSE
)

Arguments

x

A CA, MCA or PCA object.

...

Further graphical parameters.

axes

A length-two numeric vector giving the dimensions to be plotted.

active

A logical scalar: should the active observations be plotted?

sup

A logical scalar: should the supplementary observations be plotted?

labels

A logical scalar: should labels be drawn? Labeling a large number of points can be computationally expensive and make the graph difficult to read. A selection of points to label can be provided using a list of two named elements, filter (a string specifying how to filter the labels to be drawn) and n (an integer specifying the number of labels to be drawn). See examples below.

extra_quali

An optional vector of qualitative data for aesthetics mapping.

extra_quanti

An optional vector of quantitative data for aesthetics mapping. If a single character string is passed, it must be one of "observation", "mass", "sum", "contribution" or "cos2" (see augment()).

color

The colors for lines and points (will be mapped to extra_quanti or extra_quali; if both are set, the latter has priority). Ignored if set to FALSE.

fill

The background colors for points (will be mapped to extra_quanti or extra_quali; if both are set, the latter has priority). Ignored if set to FALSE.

symbol

A vector of plotting characters or symbols (will be mapped to extra_quali). This can either be a single character or an integer code for one of a set of graphics symbols. If symbol is a named a named vector, then the symbols will be associated with their name within extra_quali. Ignored if set to FALSE.

size

A length-two numeric vector giving range of possible sizes (greater than 0; will be mapped to extra_quanti). Ignored if set to FALSE.

xlim

A length-two numeric vector giving the x limits of the plot. The default value, NULL, indicates that the range of the finite values to be plotted should be used.

ylim

A length-two numeric vector giving the y limits of the plot. The default value, NULL, indicates that the range of the finite values to be plotted should be used.

main

A character string giving a main title for the plot.

sub

A character string giving a subtitle for the plot.

panel.first

An expression to be evaluated after the plot axes are set up but before any plotting takes place. This can be useful for drawing background grids.

panel.last

An expression to be evaluated after plotting has taken place but before the axes, title and box are added.

legend

A list of additional arguments to be passed to graphics::legend(); names of the list are used as argument names. If NULL, no legend is displayed.

Value

viz_*() is called for its side-effects: it results in a graphic being displayed. Invisibly returns x.

See also

Other plot methods: biplot(), plot(), screeplot(), viz_contributions(), viz_individuals(), viz_wrap, wrap

Author

N. Frerebeau

Examples

## Load data
data("iris")

## Compute principal components analysis
X <- pca(iris, scale = TRUE)
#> 1 qualitative variable was removed: Species.

## Plot individuals
viz_individuals(X, panel.last = graphics::grid())


## Labels of the 10 individuals with highest cos2
viz_individuals(X, labels = list(how = "cos2", n = 10))


## Plot variables
viz_variables(X, panel.last = graphics::grid())


## Graphical parameters
## Continuous values
viz_individuals(X, extra_quanti = iris$Petal.Length, symbol = 16, size = c(1, 2))

viz_individuals(X, extra_quanti = iris$Petal.Length, symbol = 16, size = c(1, 2),
                color = grDevices::hcl.colors(12, "RdPu"))


viz_variables(X, extra_quanti = "contribution",
              color = grDevices::hcl.colors(12, "BluGrn", rev = TRUE),
              size = c(0, 1))


## Discrete values
viz_individuals(X, extra_quali = iris$Species, symbol = 21:23)

viz_individuals(X, extra_quali = iris$Species, symbol = 21:23,
                fill = c("#004488", "#DDAA33", "#BB5566"),
                color = "black")
#> Warning: Only 1 colors were specified (3 are required).


viz_variables(X, extra_quali = c("Petal", "Petal", "Sepal", "Sepal"),
              color = c("#EE7733", "#0077BB"),
              symbol = c(1, 3))