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https://github.com/fkeck/editheme
Palettes and graphics matching your RStudio editor
https://github.com/fkeck/editheme
Last synced: 3 months ago
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Palettes and graphics matching your RStudio editor
- Host: GitHub
- URL: https://github.com/fkeck/editheme
- Owner: fkeck
- Created: 2017-11-27T17:53:23.000Z (almost 7 years ago)
- Default Branch: master
- Last Pushed: 2018-05-11T08:07:33.000Z (over 6 years ago)
- Last Synced: 2024-05-21T02:53:33.199Z (6 months ago)
- Language: R
- Homepage:
- Size: 2.95 MB
- Stars: 41
- Watchers: 2
- Forks: 11
- Open Issues: 0
-
Metadata Files:
- Readme: README.Rmd
Awesome Lists containing this project
README
---
output: github_document
---
```{r, echo = FALSE}
knitr::opts_chunk$set(
collapse = TRUE,
comment = "#>",
fig.path = "man/figures/README-"
)
```
# editheme
### Palettes and graphics matching your RStudio editor
The package editheme provides a collection of color palettes designed to match the different themes available in RStudio. It also includes functions to customize 'base' and 'ggplot2' graphs styles in order to harmonize the look of your favorite IDE.
### Install
To install the package from Gihub you can use devtools:
```{r, eval = FALSE}
#editheme use the package styles to customize base plots
devtools::install_github("fkeck/editheme")
```
```{r}
library(default)
library(editheme)
```
### Palettes
Print the list of available palettes with `list_pal`:
```{r}
list_pal()
```
Get one specific palette with `get_pal` and visualize it with `viz_pal`:
```{r, fig.height = 3, fig.width = 5}
my_pal <- get_pal(theme = "Twilight")
viz_pal(my_pal, print.hex = TRUE)
```
`get_pal` is smart, if you are using RStudio, it can find automatically the palette matching your current theme using rstudioapi, just type:
```{r, eval = FALSE}
get_pal()
```
```{r, include = FALSE}
png(filename = "man/figures/viz_all_pal.png", width = 1000, height = 750, pointsize = 20)
par(mfrow = c(7, 5))
for(i in list_pal()) {viz_pal(get_pal(i))}
dev.off()
```
[All available palettes](man/figures/viz_all_pal.png)
### Customizing base graphics
To change the look of base graphics editheme uses the styles package.
The function `set_base_sty` modifies the graphical parameters and the behavior of different
plotting functions according to the selected theme.
```{r, fig.width = 8}
set_base_sty("Clouds Midnight")
par(mfrow = c(2, 3))
hist(rnorm(100))
plot(iris$Sepal.Length, iris$Petal.Length)
barplot(1:9, names.arg = LETTERS[1:9])
boxplot(iris$Sepal.Length ~ iris$Species)
image(volcano)
```
Tip: Just like `get_pal`, `set_base_sty` is smart. If you are using RStudio, it can find automatically your current theme. Just type: `set_base_sty()`
### Customizing ggplot2 graphics
The package provides a ggplot2 theme function `theme_editor` and scales functions
(`scale_color_editor`, `scale_fill_editor`) to control the appearance of the plot.
```{r}
library(ggplot2)
pal <- get_pal(theme = "Clouds Midnight")
ggplot(iris, aes(Sepal.Length, Petal.Length)) +
geom_point(color = col_fg(pal, fade = 0.2)) +
geom_smooth(color = pal[1], fill = pal[2]) +
labs(title = "Edgar Anderson's Iris Data",
subtitle = "This is a demo", caption = "This is a caption") +
theme_editor("Clouds Midnight")
ggplot(iris, aes(Sepal.Length, Petal.Length, color = Species)) +
geom_point() +
labs(title = "Edgar Anderson's Iris Data",
subtitle = "This is a demo", caption = "This is a caption") +
theme_editor("Clouds Midnight") +
scale_color_editor("Clouds Midnight")
```
Tip: ggplot2 theme functions can find automatically your current theme. Just type: `theme_editor()`, `scale_color_editor()`, etc...
=======
---
output: github_document
---
```{r, echo = FALSE}
knitr::opts_chunk$set(
collapse = TRUE,
comment = "#>",
fig.path = "man/figures/README-"
)
```
# editheme
### Palettes and graphics matching your RStudio editor
The package editheme provides a collection of color palettes designed to match the different themes available in RStudio. It also includes functions to customize 'base' and 'ggplot2' graphs styles in order to harmonize the look of your favorite IDE.
### Install
To install the package from Github you can use devtools:
```{r, eval = FALSE}
#editheme use the package styles to customize base plots
devtools::install_github("ropenscilabs/styles")
devtools::install_github("fkeck/editheme")
```
```{r}
library(default)
library(editheme)
```
### Palettes
Print the list of available palettes with `list_pal`:
```{r}
list_pal()
```
Get one specific palette with `get_pal` and visualize it with `viz_pal`:
```{r, fig.height = 3, fig.width = 5}
my_pal <- get_pal(theme = "Twilight")
viz_pal(my_pal, print.hex = TRUE)
```
`get_pal` is smart, if you are using RStudio, it can find automatically the palette matching your current theme using rstudioapi, just type:
```{r, eval = FALSE}
get_pal()
```
```{r, include = FALSE}
png(filename = "man/figures/viz_all_pal.png", width = 1000, height = 750, pointsize = 20)
par(mfrow = c(7, 5))
for(i in list_pal()) {viz_pal(get_pal(i))}
dev.off()
```
[All available palettes](man/figures/viz_all_pal.png)
### Customizing base graphics
To change the look of base graphics editheme uses the styles package.
The function `set_base_sty` modifies the graphical parameters and the behavior of different
plotting functions according to the selected theme.
```{r, fig.width = 8}
set_base_sty("Clouds Midnight")
par(mfrow = c(2, 3))
hist(rnorm(100))
plot(iris$Sepal.Length, iris$Petal.Length)
barplot(1:9, names.arg = LETTERS[1:9])
boxplot(iris$Sepal.Length ~ iris$Species)
image(volcano)
```
Tip: Just like `get_pal`, `set_base_sty` is smart. If you are using RStudio, it can find automatically your current theme. Just type: `set_base_sty()`
### Customizing ggplot2 graphics
The package provides a ggplot2 theme function `theme_editor` and scales functions
(`scale_color_editor`, `scale_fill_editor`) to control the appearance of the plot.
```{r}
library(ggplot2)
pal <- get_pal(theme = "Clouds Midnight")
ggplot(iris, aes(Sepal.Length, Petal.Length)) +
geom_point(color = col_fg(pal, fade = 0.2)) +
geom_smooth(color = pal[1], fill = pal[2]) +
labs(title = "Edgar Anderson's Iris Data",
subtitle = "This is a demo", caption = "This is a caption") +
theme_editor("Clouds Midnight")
ggplot(iris, aes(Sepal.Length, Petal.Length, color = Species)) +
geom_point() +
labs(title = "Edgar Anderson's Iris Data",
subtitle = "This is a demo", caption = "This is a caption") +
theme_editor("Clouds Midnight") +
scale_color_editor("Clouds Midnight")
```
Tip: ggplot2 theme functions can find automatically your current theme. Just type: `theme_editor()`, `scale_color_editor()`, etc...