{ggpolar}
provides a very flexible way to create dots in
coordinate system for event list and connect the dots with segments
based on {ggplot2}
.
You can install the released version of {ggpolar}
from
CRAN with:
install.packages("ggpolar")
You can install the development version of {ggpolar}
from GitHub with:
::install_github("ShixiangWang/polar") remotes
library(ggpolar)
#> Loading required package: ggplot2
<- data.frame(x = LETTERS[1:7])
data
<- polar_init(data, x = x)
p1 p1
# Set aes value
<- polar_init(data, x = x, size = 3, color = "red", alpha = 0.5)
p2 p2
# Set aes mapping
set.seed(123L)
<- data.frame(
data1 x = LETTERS[1:7],
shape = c("r", "r", "r", "b", "b", "b", "b"),
color = c("r", "r", "r", "b", "b", "b", "b"),
size = abs(rnorm(7))
)# Check https://ggplot2.tidyverse.org/reference/geom_point.html
# for how to use both stroke and color
<- polar_init(data1, x = x, aes(size = size, color = color, shape = shape), alpha = 0.5)
p3 p3
<- data.frame(
data2 x1 = LETTERS[1:7],
x2 = c("B", "C", "D", "E", "C", "A", "C"),
color = c("r", "r", "r", "b", "b", "b", "b")
)<- p3 + polar_connect(data2, x1, x2)
p4 p4
# Unlike polar_init, mappings don't need to be included in aes()
<- p3 + polar_connect(data2, x1, x2, color = color, alpha = 0.8, linetype = 2)
p5 p5
# Use two different color scales
if (requireNamespace("ggnewscale")) {
library(ggnewscale)
= p3 +
p6 new_scale("color") +
polar_connect(data2, x1, x2, color = color, alpha = 0.8, linetype = 2)
print(p6 + scale_color_brewer())
print(p6 + scale_color_manual(values = c("darkgreen", "magenta")))
}#> Loading required namespace: ggnewscale
If you use {ggpolar}
in academic research, please cite
the following paper along with the GitHub repo.
Antigen presentation and tumor immunogenicity in cancer immunotherapy response prediction, eLife. https://doi.org/10.7554/eLife.49020.