https://github.com/ShixiangWang/polar
polar: Dots and Their Connections in Polar Coordinate System
https://github.com/ShixiangWang/polar
ggplot2-enhancements
Last synced: 6 months ago
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polar: Dots and Their Connections in Polar Coordinate System
- Host: GitHub
- URL: https://github.com/ShixiangWang/polar
- Owner: ShixiangWang
- License: gpl-3.0
- Created: 2021-11-09T12:57:54.000Z (almost 4 years ago)
- Default Branch: main
- Last Pushed: 2022-10-10T10:39:10.000Z (about 3 years ago)
- Last Synced: 2024-10-28T17:27:32.893Z (12 months ago)
- Topics: ggplot2-enhancements
- Language: R
- Homepage: https://shixiangwang.github.io/polar/
- Size: 1.09 MB
- Stars: 9
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.Rmd
- License: LICENSE.md
Awesome Lists containing this project
README
---
output: github_document
---
```{r, include = FALSE}
knitr::opts_chunk$set(
collapse = TRUE,
comment = "#>",
fig.path = "man/figures/README-",
out.width = "100%"
)
```
# ggpolar: Dots and Their Connections in Polar Coordinate System
[](https://shixiangwang.r-universe.dev)
[](https://CRAN.R-project.org/package=ggpolar)
[](https://cran.r-project.org/package=ggpolar)
`{ggpolar}` provides a very flexible way to create dots in coordinate system
for event list and connect the dots with segments based on [`{ggplot2}`](https://ggplot2.tidyverse.org/).
## Installation
You can install the released version of `{ggpolar}` from CRAN with:
``` r
install.packages("ggpolar")
```
You can install the development version of `{ggpolar}` from GitHub with:
``` r
remotes::install_github("ShixiangWang/polar")
```
## Example
### Init a polar plot
```{r example}
library(ggpolar)
data <- data.frame(x = LETTERS[1:7])
p1 <- polar_init(data, x = x)
p1
# Set aes value
p2 <- polar_init(data, x = x, size = 3, color = "red", alpha = 0.5)
p2
# Set aes mapping
set.seed(123L)
data1 <- data.frame(
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
p3 <- polar_init(data1, x = x, aes(size = size, color = color, shape = shape), alpha = 0.5)
p3
```
### Connect polar dots
```{r}
data2 <- data.frame(
x1 = LETTERS[1:7],
x2 = c("B", "C", "D", "E", "C", "A", "C"),
color = c("r", "r", "r", "b", "b", "b", "b")
)
p4 <- p3 + polar_connect(data2, x1, x2)
p4
# Unlike polar_init, mappings don't need to be included in aes()
p5 <- p3 + polar_connect(data2, x1, x2, color = color, alpha = 0.8, linetype = 2)
p5
# Use two different color scales
if (requireNamespace("ggnewscale")) {
library(ggnewscale)
p6 = p3 +
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")))
}
```
## Citation
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.