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Interactive 3D Plot for Principal Component Analyses (plotly::)

Source: R/pca-3d.R
ggpca_3d.Rd

Interactive 3D Plot for Principal Component Analyses (plotly::)

Usage

ggpca_3d(
  res.pca,
  axes = c(1, 2, 3),
  princ_axes_print = -3:3,
  base_axe_n_breaks = 10,
  ind.size = 4,
  ind_name.size = 3,
  title,
  center = TRUE,
  var_names_on = "var",
  base_zoom = 1,
  remove_buttons = FALSE,
  cone_size = 0.33,
  view = "All",
  type = c("var", "ind", "main_plan", "projections"),
  camera_view,
  aspectratio_from_eig = FALSE,
  always_make_ind_tooltips = FALSE,
  var_color = "#4D4D4D",
  max_ind = 500,
  max_ind_seed
)

Arguments

res.pca

The result of FactoMineR::PCA.

axes

The axes to print, as a numeric vector of length 3 (or 2).

princ_axes_print

The breaks of the principal axes.

base_axe_n_breaks

The number of breaks in initial variables axes.

ind.size

The size of the points of individuals.

ind_name.size

The size of the names of individuals.

title

Plot title.

center

By default the plot is centered on the central point. Set to `FALSE` to center on the origin of all variables (zero coordinates).

var_names_on

By default `"var"` the names of variables are drawn upon the initial axes. Set to `"cor"` to draw them upon correlation vectors instead.

base_zoom

The base level of zoom.

remove_buttons

Set to TRUE to remove buttons to change view.

cone_size

The size of the conic arrow at the end of each axe.

view

The starting point of view (in 3D) :

  • "Plane 1-2" : Axes 1 and 2.

  • "Plane 1-3" : Axes 1 and 3.

  • "Plane 2-3" : Axes 2 and 3.

  • "All" : A 3D perspective with Axes 1, 2, 3.

type

Which elements of the graph to print, among : #'

  • "var" : initial variables axes, with breaks

  • "cor" : normalized correlation vectors (length = 1)

  • "cor_sphere" : a 3D sphere of standard deviation 1

  • "ind" : points of individuals

  • "ind_name" : names of individuals

  • "main_plan" : the plan 1-2.

  • "projections" : projections of mean point on initial variables

  • "V" : vectors of the V transition matrix

  • "vs" : vectors of the matrix of singular values

camera_view

Possibility to add a (replace `view`)

aspectratio_from_eig

Set to `TRUE` to modify axes length based on eigenvalues.

always_make_ind_tooltips

Set to `TRUE` to add interactive toolips for individuals.

var_color

The color of the initial variables/dimensions

max_ind

The maximun number of individuals to print.

max_ind_seed

The random seed used to sample individuals.

Value

A plotly html interactive 2d or 3d graph.

Examples

# \donttest{
data(mtcars, package = "datasets")
mtcars <- mtcars[1:7] |> dplyr::rename(weight = wt)
res.pca <- FactoMineR::PCA(mtcars, graph = FALSE)

# Variables and individuals
ggpca_3d(res.pca)



# Circle of correlation 3D
ggpca_3d(res.pca, type = c("cor", "cor_sphere"),
         var_names_on = "cor", base_zoom = 0.6,
         princ_axes_print = -1:1, view = "All"
)


# }