Create interactive bins guide

Description

The guide is based on guide_bins(). See the documentation for that function for more details.

Usage

guide_bins_interactive(...)

Arguments

Value

An interactive guide object.

Details for scale_interactive and guide_interactive functions

For scales, the interactive parameters can be supplied as arguments in the relevant function and they can be scalar values or vectors, depending on the number of breaks (levels) and the type of the guide used. The guides do not accept any interactive parameter directly, they receive them from the scales.

• When guide of type legend or bins is used, it will be converted to a guide_legend_interactive() or guide_bins_interactive() respectively, if it's not already.

  The length of each scale interactive parameter vector should match the length of the breaks. It can also be a named vector, where each name should correspond to the same break name. It can also be defined as function that takes the breaks as input and returns a named or unnamed vector of values as output.

  The interactive parameters here, give interactivity only to the key elements of the guide.

• When guide of type colourbar or coloursteps is used, it will be converted to a guide_colourbar_interactive() or guide_coloursteps_interactive() respectively, if it's not already.

  The scale interactive parameters in this case should be scalar values and give interactivity to the colorbar only.

To provide interactivity to the rest of the elements of a guide, (title, labels, background, etc), the relevant theme elements or relevant guide arguments can be used. The guide arguments title.theme and label.theme can be defined as element_text_interactive (in fact, they will be converted to that if they are not already), either directly or via the theme. See the element_*_interactive section for more details.

See Also

interactive_parameters(), girafe()

Examples

# add interactive bins guide to a ggplot -------
library(ggplot2)
library(ggiraph)

set.seed(4393)
dsmall <- diamonds[sample(nrow(diamonds), 1000),]
p <- ggplot(dsmall, aes(x, y)) +
  stat_density_2d(aes(
    fill = stat(nlevel),
    tooltip = paste("nlevel:", stat(nlevel))
  ),
  geom = "interactive_polygon") +
  facet_grid(. ~ cut)

# add interactive binned scale and guide
p1 <- p + scale_fill_viridis_b_interactive(data_id = "nlevel",
                                           tooltip = "nlevel",
                                           guide = "bins")
x <- girafe(ggobj = p1)
if (interactive()) print(x)

# set the keys separately
p2 <- p + scale_fill_viridis_b_interactive(
  data_id = function(breaks) {
    as.character(breaks)
  },
  tooltip = function(breaks) {
    as.character(breaks)
  },
  guide = "bins"
)
x <- girafe(ggobj = p2)
if (interactive()) print(x)


# make the title and labels interactive
p3 <- p + scale_fill_viridis_c_interactive(
  data_id = function(breaks) {
    as.character(breaks)
  },
  tooltip = function(breaks) {
    as.character(breaks)
  },
  guide = "bins",
  name = label_interactive("nlevel", data_id = "nlevel",
                           tooltip = "nlevel"),
  labels = function(breaks) {
    l <- lapply(breaks, function(br) {
      label_interactive(
        as.character(br),
        data_id = as.character(br),
        onclick = paste0("alert(\"", as.character(br), "\")"),
        tooltip = as.character(br)
      )
    })
    l
  }
)
x <- girafe(ggobj = p3)
x <- girafe_options(x,
                    opts_hover_key(girafe_css("stroke:red", text="stroke:none;fill:red")))
if (interactive()) print(x)