Plot compact PVD tmp function using list of extract_figs_from_pickle

Usage

plot_compact_pvd(
  figs,
  tile_height = 1,
  y_text_size = 9,
  x_text_size = y_text_size,
  x_title_size = x_text_size,
  facet_label_prefix = names(figs),
  legend.position = "right",
  legend.direction = "vertical",
  legend.box = "vertical",
  legend.key.height = grid::unit(1, "lines"),
  colorbar_label_type = "level",
  scale_colors = c("red", "blue", "magenta", "darkgreen", "purple4"),
  rel_heights = c(1, 0.025),
  ncol_legend = 2,
  nrow_colors = dplyr::if_else(legend.position == "none", 2, 1),
  guide_rel_widths = c(0.7, 0.3),
  legend_text_size = grid::unit(8, "pt"),
  show_group_color_legend = TRUE,
  strip_text_size = grid::unit(8, "points"),
  ...
)

Arguments

figs

todo

tile_height

todo

y_text_size

integer: size of y-axis text

x_text_size

integer: size of x-axis tick labels

x_title_size

integer: size of x-axis title

facet_label_prefix

todo

legend.position

the default position of legends ("none", "left", "right", "bottom", "top", "inside")

legend.direction

layout of items in legends ("horizontal" or "vertical")

legend.box

arrangement of multiple legends ("horizontal" or "vertical")

legend.key.height

size of legend keys (unit); key background height & width inherit from legend.key.size or can be specified separately. In turn legend.key.size inherits from spacing.

colorbar_label_type

what kind of label to use? Current options are "level" and "subscript"

scale_colors

todo

rel_heights

(optional) Numerical vector of relative rows heights. Works just as rel_widths does, but for rows rather than columns.

ncol_legend

how many columns to use for legend

nrow_colors

now many rows to use for color guide

guide_rel_widths

relative widths of guides

legend_text_size

grid::unit: legend text size

show_group_color_legend

logical: whether to show group col legend

strip_text_size

passed to ggtext::element_markdown()

...

Arguments passed on to compact_pvd_data_prep

biomarker_order: a character vector specifying the order of biomarkers to use
biomarker_var: either "biomarker" or "biomarker_label"

Value

a ggplot2::ggplot

Examples

output_path <-
  fs::path_package("extdata/sim_data", package = "fxtas")

figs <- extract_figs_from_pickle(
  output_folder = output_path,
  n = 3
)

figs |> plot_compact_pvd(scale_colors = c("red", "blue", "purple4"))