It provides materials (i.e. serialaxes objects) to visualize high dimensional data in ggplot
.
Documentation: https://great-northern-diver.github.io/ggmulti/
Package ggmulti
extends the ggplot2
package to provide some high dimensional visualization functionality, such as
Serialaxes coordinates (i.e., parallel or radial axis systems)
General glyphs (e.g., polygons, images) to appear a scatterplot.
"More general" geom_histogram
and geom_density
to allow them to appear on serial axes.
Parallel coordinates
library(ggmulti)
p <- ggplot(iris,
mapping = aes(Sepal.Length = Sepal.Length,
Sepal.Width = Sepal.Width,
Petal.Length = Petal.Length,
Petal.Width = Petal.Width,
colour = Species)) +
geom_path(alpha = 0.2) +
coord_serialaxes()
p
We can also construct a radar plot by setting axes.layout = "radial"
in coord_serialaxes
. In addition, we can add histogram layer on top
p +
geom_histogram(mapping = aes(fill = Species), alpha = 0.5)
The flag of Canada
canada <- data.frame(
xmin = c(-2, -1, 1),
xmax = c(-1, 1, 2),
ymin = rep(-1.2, 3),
ymax = rep(1.2, 3),
fill = factor(c(1,2,1))
)
p <- ggplot() +
geom_rect(data = canada,
mapping = aes(xmin = xmin, xmax = xmax,
ymin = ymin, ymax = ymax,
fill = fill),
colour = "black") +
geom_polygon_glyph(data = data.frame(x = 0, y = 0),
mapping = aes(x = x, y = y),
polygon_x = x_maple,
polygon_y = y_maple,
fill = "red",
size = 12) +
scale_fill_manual(values = c("red", "white")) +
theme_void() +
theme(legend.position = "none")
p
We can save it as a png
object, then call geom_image_glyph
to display the image glyph
ggsave("canada.png", type = "cairo", bg = "white")
images <- png::readPNG("canada.png")
ggplot(data = data.frame(x = c(1,2,1.5,2,1), y = c(1,1,1.5,2,2)),
mapping = aes(x = x, y = y)) +
geom_image_glyph(images = rep(list(images), 5)) +
coord_cartesian(xlim = extendrange(c(1,2)),
ylim = extendrange(c(1,2)))
geom_histogram
and geom_density
Functions geom_histogram_
and geom_density_
are more general geom_histogram
and geom_density
since these two functions can accommodate both x
and y
simutaniously. If only one is provided, geom_histogram
or geom_density
will be executed.
The following figure displays the back to back plot (histogram and density)
iris %>%
tidyr::pivot_longer(cols = -Species,
names_to = "Outer sterile whorls",
values_to = "values") %>%
ggplot(mapping = aes(x = `Outer sterile whorls`,
y = values,
fill = Species)) +
geom_histogram_(scale.y = "group",
alpha = 0.5,
prop = 0.6) +
geom_density_(scale.y = "group",
prop = 0.6,
alpha = 0.5,
colour = NA,
positive = FALSE)
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