https://github.com/ShixiangWang/polar

polar: Dots and Their Connections in Polar Coordinate System
https://github.com/ShixiangWang/polar

ggplot2-enhancements

Last synced: 2 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 (about 3 years ago)
• Default Branch: main
• Last Pushed: 2022-10-10T10:39:10.000Z (over 2 years ago)
• Last Synced: 2024-10-28T17:27:32.893Z (3 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

[![ggpolar status badge](https://shixiangwang.r-universe.dev/badges/ggpolar)](https://shixiangwang.r-universe.dev)

[![CRAN

status](https://www.r-pkg.org/badges/version/ggpolar)](https://CRAN.R-project.org/package=ggpolar)

[![](https://cranlogs.r-pkg.org/badges/grand-total/ggpolar?color=blue)](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.