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VapoRwave Themes

License: MIT

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Overview

vapoRwave is an R package that provides ggplot2 themes inspired by the vaporwave movement, a genre of electronic music and art characterized by nostalgic and satirical takes on consumer capitalism, glitch art, anime, 3D-rendered objects, and cyberpunk tropes.

Explore the aesthetics of vaporwave through themes that mimic iconic album covers and visual styles.

Installation

Use the devtools package to install it.

devtools::install_github("moldach/vapoRwave")

# To include the vignette
devtools::install_github("moldach/vapoRwave", build_vignettes=TRUE)

Load packages:

library(vapoRwave)
library(ggplot2)
library(extrafont)

Windows Font Installation

While Ubuntu users can effortlessly install fonts, Windows users are required to take an additional step to utilize the fonts provided.

The fonts from the vapoRwave package will be locally installed in C:\Windows\Users\<username>\MyFonts\. To use them, move/copy the fonts to Control Panel -> Appearance and Personalization -> Fonts.

After each new R session, execute the following commands to make the fonts available:

library(extrafont)
# Import the TrueType fonts
font_import(paths = "C:/Windows/Fonts/", recursive = TRUE)

Select Y to continue:

Themes

Floral Shoppe

ggplot(mpg, aes(displ)) + 
        geom_histogram(aes(fill=class), 
                   binwidth = .1, 
                   col="black", 
                   size=.1) +  # change binwidth
        labs(title="Floral Shoppe", 
        subtitle="Engine Displacement across Vehicle Classes") + floral_shoppe() + scale_fill_floralShoppe()

New Retro Wave

options(scipen=999)  # turn-off scientific notation like 1e+48
data("midwest", package = "ggplot2")
ggplot(midwest, aes(x=area, y=poptotal)) + 
  geom_point(aes(col=state, size=popdensity)) + 
  geom_smooth(method="loess", se=F, color = "#FA5F70FF") + 
  xlim(c(0, 0.1)) + 
  ylim(c(0, 500000)) + 
  labs(subtitle="Area Vs Population", 
       y="Population", 
       x="Area", 
       title="New Retro Theme", 
       caption = "Source: midwest") + 
        new_retro() + 
        scale_colour_newRetro() +
        guides(size = guide_legend(override.aes = list(colour = "#FA5F70FF")))

JWZ

ggplot(mpg, aes(class, cty)) +
        geom_boxplot(aes(fill=factor(cyl))) + 
        theme(axis.text.x = element_text(angle=65, vjust=0.6)) + 
        labs(title="Box plot", 
             subtitle="City Mileage grouped by Class of vehicle",
             caption="Source: mpg",
             x="Class of Vehicle",
             y="City Mileage") + 
        jwz() +
        scale_fill_jwz()

Vignettes

For more advanced and complex use-cases, as well as detailed examples and customization options, refer to the vapoRwave vignette. The vignette explore diverse demos that include information on various palletes, fonts, changing parameters, and integrating with extensions. For a comprehensive guide, consult the vignette for the full potential of the vapoRwave package.

When users install the package and want to access the vignettes, they can use the following command to open them:

library(vapoRwave)
browseVignettes("vapoRwave")

Docker

Dive into the world of vapoRwave v0.2.0 and experience the perfect blend of retro aesthetics and modern data visualization within the Synthwave85 RStudio IDE, now more accessible than ever!

The v0.2.0 release streamlines the installation process across various operating systems. Get the New Retro theme in your IDE coupled with a pre-configured Python environment via the reticulate package. Python aficionados can now indulge in retro-flavored coding while leveraging R’s simple syntax and powerful graphics.

Python and R in a Retro IDE

For your convenience, we offer two ways to get vapoRwave running in a Docker container:

Pull the Pre-Built Docker Image

The easiest way to get started is to pull the pre-built image from Docker Hub, which was optimized for size and security using Slim:

docker pull moldach686/vaporwave:latest
docker run -p 8787:8787 -e PASSWORD=vaporwave moldach686/vaporwave

Build from the Dockerfile

Alternatively, if you prefer to build the Docker image yourself from the Dockerfile:

docker build -t vaporwave .
docker run -p 8787:8787 -e PASSWORD=vaporwave vaporwave

Either of these options will start vapoRwave and you can access the IDE by navigating to http://localhost:8787`` in your web browser. Log in with the usernamerstudioand the passwordvaporwave`.

For instance, you can leverage Pandas for data wrangling and then visualize your results with R’s ggplot2, all within this unique environment.

Once inside the IDE, feel free to install additional R packages through the console. Alternatively, in the terminal you can install Python packages using pip3 within a Poetry virtual environment, and any system dependencies using apt-get.

Please note that when building from the Dockerfile, you may pull the latest dependencies, which provides the most up-to-date environment, while using the pre-built image ensures a consistent, tested setup.

Enjoy the blend of the past and present in data science with vapoRwave v0.2.0 Retro Player One!🕹️📼🎵

Contributing

Please read CONTRIBUTING.md for details on our code of conduct, and the process for submitting pull requests to us.

License

This code is released under the MIT License - see the LICENSE.md file for details.