Momocs (version 1.4.1)

plot_PCA: PCA plot using grindr layers

Description

Quickly vizualise PCA objects and friends and build customs plots using the layers. See examples.

Usage

plot_PCA(
  x,
  f = NULL,
  axes = c(1, 2),
  palette = NULL,
  points = TRUE,
  points_transp = 1/4,
  morphospace = TRUE,
  morphospace_position = "range",
  chull = TRUE,
  chullfilled = FALSE,
  labelpoints = FALSE,
  labelgroups = FALSE,
  legend = TRUE,
  title = "",
  center_origin = TRUE,
  zoom = 0.9,
  eigen = TRUE,
  box = TRUE,
  axesnames = TRUE,
  axesvar = TRUE
)

Value

a plot

Arguments

x

a PCA object

f

factor specification to feed fac_dispatcher

axes

numeric of length two to select PCs to use (c(1, 2) by default)

palette

color palette to use col_summer by default

points

logical whether to draw this with layer_points

points_transp

numeric to feed layer_points (default:0.25)

morphospace

logical whether to draw this using layer_morphospace_PCA

morphospace_position

to feed layer_morphospace_PCA (default: "range")

chull

logical whether to draw this with layer_chull

chullfilled

logical whether to draw this with layer_chullfilled

labelpoints

logical whether to draw this with layer_labelpoints

labelgroups

logical whether to draw this with layer_labelgroups

legend

logical whether to draw this with layer_legend

title

character if specified, fee layer_title (default to "")

center_origin

logical whether to center origin

zoom

numeric zoom level for the frame (default: 0.9)

eigen

logical whether to draw this using layer_eigen

box

logical whether to draw this using layer_box

axesnames

logical whether to draw this using layer_axesnames

axesvar

logical whether to draw this using layer_axesvar

See Also

Other grindr: drawers, layers_morphospace, layers, mosaic_engine(), papers, pile(), plot_LDA(), plot_NMDS()

Examples

### First prepare two PCA objects.

# Some outlines with bot
bp <- bot %>% mutate(fake=sample(letters[1:5], 40, replace=TRUE)) %>%
efourier(6) %>% PCA
plot_PCA(bp)
plot_PCA(bp, ~type)
plot_PCA(bp, ~fake)

# Some curves with olea
op <- olea %>%
mutate(s=coo_area(.)) %>%
filter(var != "Cypre") %>%
chop(~view) %>% opoly(5, nb.pts=90) %>%
combine %>% PCA
op$fac$s %<>% as.character() %>% as.numeric()

op %>% plot_PCA(title="hi there!")

### Now we can play with layers
# and for instance build a custom plot
# it should start with plot_PCA()

my_plot <- function(x, ...){

x %>%
    plot_PCA(...) %>%
    layer_points %>%
    layer_ellipsesaxes %>%
    layer_rug
}

# and even continue after this function
op %>% my_plot(~var, axes=c(1, 3)) %>%
    layer_title("hi there!")

# grindr allows (almost nice) tricks like highlighting:

# bp %>% .layerize_PCA(~fake) %>%
#   layer_frame %>% layer_axes() %>%
#   layer_morphospace_PCA() -> x

# highlight <- function(x, ..., col_F="#CCCCCC", col_T="#FC8D62FF"){
#  args <- list(...)
#  x$colors_groups <- c(col_F, col_T)
#  x$colors_rows <- c(col_F, col_T)[(x$f %in% args)+1]
#  x
#  }
# x %>% highlight("a", "b") %>% layer_points()

# You get the idea.