Create interactive rectangles
Source:R/geom_rect_interactive.R
, R/geom_tile_interactive.R
geom_rect_interactive.Rd
These geometries are based on ggplot2::geom_rect()
and ggplot2::geom_tile()
.
See the documentation for those functions for more details.
Arguments
- ...
arguments passed to base function, plus any of the interactive_parameters.
Note
Converting a raster to svg elements could inflate dramatically the size of the
svg and make it unreadable in a browser.
Function geom_tile_interactive
should be used with caution, total number of
rectangles should be small.
Details for interactive geom functions
The interactive parameters can be supplied with two ways:
As aesthetics with the mapping argument (via
ggplot2::aes()
). In this way they can be mapped to data columns and apply to a set of geometries.As plain arguments into the geom_*_interactive function. In this way they can be set to a scalar value.
Examples
# add interactive polygons to a ggplot -------
library(ggplot2)
library(ggiraph)
dataset = data.frame( x1 = c(1, 3, 1, 5, 4),
x2 = c(2, 4, 3, 6, 6),
y1 = c( 1, 1, 4, 1, 3),
y2 = c( 2, 2, 5, 3, 5),
t = c( 'a', 'a', 'a', 'b', 'b'),
r = c( 1, 2, 3, 4, 5),
tooltip = c("ID 1", "ID 2", "ID 3", "ID 4", "ID 5"),
uid = c("ID 1", "ID 2", "ID 3", "ID 4", "ID 5"),
oc = rep("alert(this.getAttribute(\"data-id\"))", 5)
)
gg_rect = ggplot() +
scale_x_continuous(name="x") +
scale_y_continuous(name="y") +
geom_rect_interactive(data=dataset,
mapping = aes(xmin = x1, xmax = x2,
ymin = y1, ymax = y2, fill = t,
tooltip = tooltip, onclick = oc, data_id = uid ),
color="black", alpha=0.5, linejoin = "bevel", lineend = "round") +
geom_text(data=dataset,
aes(x = x1 + ( x2 - x1 ) / 2, y = y1 + ( y2 - y1 ) / 2,
label = r ),
size = 4 )
x <- girafe(ggobj = gg_rect)
if( interactive() ) print(x)
# add interactive tiles to a ggplot -------
library(ggplot2)
library(ggiraph)
df <- data.frame(
id = rep(c("a", "b", "c", "d", "e"), 2),
x = rep(c(2, 5, 7, 9, 12), 2),
y = rep(c(1, 2), each = 5),
z = factor(rep(1:5, each = 2)),
w = rep(diff(c(0, 4, 6, 8, 10, 14)), 2)
)
p <- ggplot(df, aes(x, y, tooltip = id)) + geom_tile_interactive(aes(fill = z))
x <- girafe(ggobj = p)
if( interactive() ) print(x)
# correlation dataset ----
cor_mat <- cor(mtcars)
diag( cor_mat ) <- NA
var1 <- rep( row.names(cor_mat), ncol(cor_mat) )
var2 <- rep( colnames(cor_mat), each = nrow(cor_mat) )
cor <- as.numeric(cor_mat)
cor_mat <- data.frame( var1 = var1, var2 = var2,
cor = cor, stringsAsFactors = FALSE )
cor_mat[["tooltip"]] <-
sprintf("<i>`%s`</i> vs <i>`%s`</i>:</br><code>%.03f</code>",
var1, var2, cor)
p <- ggplot(data = cor_mat, aes(x = var1, y = var2) ) +
geom_tile_interactive(aes(fill = cor, tooltip = tooltip), colour = "white") +
scale_fill_gradient2_interactive(low = "#BC120A", mid = "white", high = "#BC120A",
limits = c(-1, 1), data_id = "cormat", tooltip = "cormat") +
coord_equal()
x <- girafe(ggobj = p)
if( interactive() ) print(x)