display_pca: Display tour path with principal component scores with...

In tourr: Tour Methods for Multivariate Data Visualisation

Display tour path with principal component scores with original axes

Description

Animate a 2D tour path on data that has been transformed into principal components, and also show the original variable axes.

Usage

display_pca(
  center = TRUE,
  axes = "center",
  half_range = NULL,
  col = "black",
  pch = 20,
  cex = 1,
  pc_coefs = NULL,
  edges = NULL,
  edges.col = "black",
  palette = "Zissou 1",
  ...
)

animate_pca(data, tour_path = grand_tour(), rescale = FALSE, ...)

Arguments

center	if TRUE, centers projected data to (0,0). This pins the center of data cloud and make it easier to focus on the changing shape rather than position.
axes	position of the axes: center, bottomleft or off
half_range	half range to use when calculating limits of projected. If not set, defaults to maximum distance from origin to each row of data.
col	color to use for points, can be a vector or hexcolors or a factor. Defaults to "black".
pch	shape of the point to be plotted. Defaults to 20.
cex	size of the point to be plotted. Defaults to 1.
pc_coefs	coefficients relating the original variables to principal components. This is required.
edges	A two column integer matrix giving indices of ends of lines.
edges.col	colour of edges to be plotted, Defaults to "black.
palette	name of color palette for point colour, used by hcl.colors, default "Zissou 1"
...	other arguments passed on to animate and display_slice
data	matrix, or data frame containing numeric columns
tour_path	tour path generator, defaults to 2d grand tour
rescale	Default FALSE. If TRUE, rescale all variables to range [0,1].

Examples

flea_std <- apply(flea[,1:6], 2, function(x) (x-mean(x))/sd(x))
flea_pca <- prcomp(flea_std, center = FALSE, )
flea_coefs <- flea_pca$rotation[, 1:3]
flea_scores <- flea_pca$x[, 1:3]
animate_pca(flea_scores, pc_coefs = flea_coefs)

tourr documentation built on Aug. 25, 2023, 1:08 a.m.