Display tour path with principal component scores with original axes

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",
  axislablong = FALSE,
  ...
)

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"
axislablong: text labels only for the long axes in a projection, default FALSE
...: 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)
#> Using half_range 4.4