VapoRwave Themes

Matthew J. Oldach

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)

Introduction

This package provides a number of ggplot2 themes inspired by vaporwave, both a subgenre of electronic music and an art movement. Here’s a nice sampling here: link.

On the musical side it’s known for it’s appropriation of 1980’s and 1990’s elevator/lounge music along with the application of slowed-down chopped and screwed techniques, looping and other effects.

On the visual side it’s know for A E S T H E T I C S with fullwidth characters it’s satrical takes on consumer capitalism (.e.g the use wih Greco-Roman statues to signify the fall of capitalism), and other nostalgic or surrealist engagement with glitch art, anime, 3D-rendered objects and cyberpunk trope in it’s cover art and music videos.

Aesthetic, often stylized as a e s t h e t i c, refers to retro-inspired visual art and music associated with the vaporwave subculture, which typically include Japanese lettering and nostalgic themes from 1980s and 1990s computer operating systems and video game consoles. Additionally, the term is widely associated with the 2012 vaporwave song “リサフランク420 / 現代のコンピュー” by Macintosh Plus…

Setup theme and scales

There are three theme-generating functions:

floral_shoppe()

sets the plot theme to match the most recognized album cover in vaporwave, Vektroid’s Floral Shoppe released under the one-time pseudonym of Macintosh Plus.

new_retro()

sets the plot theme to match the A E S T H E T I C of the New Retro Wave record label.

jwz()

The jwz() function sets the plot theme to match the personal blog of the American programmer jwz.

James Werner Zawinski known as jwz was a programmer known for contributions to your parents browser (netscape yo!), Mozilla (firefox, etc.) and XEmacs. In 2000, Zawinski starred in the 60-minute-long PBS documentary “Code Rush”. The footage was taken during 1998 while Zawinski was still working for Netscape in which he is portrayed as a pivotal person in the company. In addition, he underlined his preference for the night scene which led him to buy a nightclub.

Color Palette’s

The colors for this theme were drawn from many vaporwave images; I selected those that worked well together for color and fill scales.

Floral Shoppe Palette

scales::show_col(vapoRwave:::floralShoppe_palette)

New Retro Palette

scales::show_col(vapoRwave:::newRetro_palette)

jwz Palette

scales::show_col(vapoRwave:::jwz_palette)

Hotline Bling Palette

scales::show_col(vapoRwave:::hotlineBling_palette)

Hyper Bubble Palette

scales::show_col(vapoRwave:::hyperBubble_palette)

dantaki/vapeplot

There was a matplotlib extension for python with a couple of vaporwave palettes I incorportaed as well

Demos

library(tidyverse)
#> -- Attaching packages ------------------------------------------------ tidyverse 1.2.1 --
#> v ggplot2 3.1.0       v purrr   0.3.0  
#> v tibble  2.0.1       v dplyr   0.8.0.1
#> v tidyr   0.8.2       v stringr 1.4.0  
#> v readr   1.3.1       v forcats 0.4.0
#> -- Conflicts --------------------------------------------------- tidyverse_conflicts() --
#> x dplyr::filter() masks stats::filter()
#> x dplyr::lag()    masks stats::lag()
library(vapoRwave)
library(extrafont)
#> Registering fonts with R

Floral Shoppe

# use palette_03
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

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 Style

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()

Fonts

You will need to download the following ttf fonts to use this package. You can import them with the extrafont package.

• Alien Encounters the font used by the Dream Catalogue Vaporwave record label. This typeface invokes the forward learning, horizontally sliced fonts of Blade Runner and Tron.
• VCR OSD Mono Pixel art is a mainstay of Vaporwave art, it evokes a child-like nostalgia associated with 8-bit consoles and runs with the movements Japanese leanings. Fittingly, VCR OSD Mono’s glitch-y, pixelated form plays on video game culture and compliments the warbled, pitched down vocals of Vaporwave that often mimic malfunctioning VHS tapes.
• Windows Command Prompt
• Blade Runner a font from the motion picture Blade Runner.
• Streamster a font that can be used with vintage textures, 80’s iconography and neon-lit colour palettes.

To verify the installation of these font’s on your OS you can look for them with:

extrafont::fonts()

The above installations wil give you the following fonts

• SF Alien Encounters
• SF Alien Encounters Solid
• VCR OSD Mono
• OCR A Extended
• Windows Command Prompt
• Blade Runner Movie Font
• Streamster

That being said you can use any ttf font with the vapoRwave package.

var <- mpg$class  # the categorical data 

## Prep data (nothing to change here)
nrows <- 10
df <- expand.grid(y = 1:nrows, x = 1:nrows)
categ_table <- round(table(var) * ((nrows*nrows)/(length(var))))
categ_table
#> var
#>    2seater    compact    midsize    minivan     pickup subcompact 
#>          2         20         18          5         14         15 
#>        suv 
#>         26
#>   2seater    compact    midsize    minivan     pickup subcompact        suv 
#>         2         20         18          5         14         15         26 

df$category <- factor(rep(names(categ_table), categ_table))  
# NOTE: if sum(categ_table) is not 100 (i.e. nrows^2), it will need adjustment to make the sum to 100.

## Plot
ggplot(df, aes(x = x, y = y, fill = category)) + 
    geom_tile(color = "black", size = 0.5) +
    scale_x_continuous(expand = c(0, 0)) +
    scale_y_continuous(expand = c(0, 0), trans = 'reverse') +
    scale_fill_newRetro() +
    labs(title="Waffle Chart", subtitle="'Class' of vehicles",
         caption="Source: mpg") + new_retro(font = "SF Alien Encounters Solid", main.text.color = "pink")

library(gapminder)
ggplot(filter(gapminder, year == 2007), aes(x = gdpPercap, y = lifeExp)) +
    scale_x_log10(labels = scales::dollar) +
    geom_point(aes(size = pop, fill = continent), shape = 21, colour = "white", alpha = 0.6) +
    scale_size_continuous(range = c(1, 20)) +
    labs(title = "",
         subtitle = "Relationship between life expectancy and income, 2007",
         caption = "Source: Gapminder.org  |  @traffordDataLab",
         x = "GDP per capita ($)",
         y = "Age (years)") +
    guides(size = FALSE) +
    jwz(font = "Streamster", main.text.color = "#FFCCFF", sub.text.color = "#CCFFFF", subtitle.size = 16) + scale_fill_hyperBubble()

Changing parameters

You are able to change most ggplot2::theme() elements from new_retro(), floral_shoppe() and jwz() themes.

df <- gapminder %>% 
  filter(country %in% c("France", "Germany", "Ireland", "Italy")) %>% 
  mutate(year = as.Date(paste(year, "-01-01", sep = "", format='%Y-%b-%d')))

ggplot(df, aes(x = year, y = gdpPercap, fill = country)) +
  geom_area(alpha = 0.4) +
  scale_x_date(breaks = df$year, date_labels = "%Y") +
  scale_y_continuous(expand = c(0, 0), labels = scales::dollar) +
  labs(title = "",
       subtitle = "GDP per capita by country, 1952-2007",
       caption = "Source: Gapminder.org  |  @traffordDataLab",
       x = NULL,
       y = "GDP per capita ($)",
       fill = NULL) +
  floral_shoppe(main.text.color = "black", font = "OCR A Extended", legend.position = "bottom") +
  scale_fill_newRetro()

library(forecast)

# Subset data
nottem_small <- window(nottem, start=c(1920, 1), end=c(1925, 12))  # subset a smaller timewindow

# Plot (capital "B" is the Blade Runner guy)
ggseasonplot(nottem_small) + labs(title="Seasonal B plot:", subtitle = "Air temperatures at Nottingham Castle") + scale_colour_jwz() + new_retro(font = "Blade Runner Movie Font")

vapoRwave also works with ggplot2 extensions.

library(ggcorrplot)
mydata <- mtcars[, c(1,3,4,5,6,7)]
corr <- round(cor(mydata),1)
ggcorrplot(corr, hc.order = T, 
           type = 'lower',
           outline.color = 'white',
           ggtheme = ggplot2::theme_bw,
           colors = c('#79ADDC', 'white', '#CC7E85'),
           lab = T) + floral_shoppe()

library(WVPlots) 

PairPlot(iris, 
         colnames(iris)[1:4], 
         "Anderson's Iris Data -- 3 species", 
         group_var = "Species") +
        labs(caption = "Source: https://bit.ly/2N7tudH") + 
                jwz() + 
                scale_colour_hotlineBling()
#> Scale for 'colour' is already present. Adding another scale for
#> 'colour', which will replace the existing scale.

If you need to use a color gradient take a look at the html color codes for the palette in the Readme_files folder and insert your choice in low and high.

ggplot(faithful, aes(x = eruptions, y = waiting)) +
        geom_point() + stat_density_2d(aes(fill = ..level..), geom = "polygon") +
        jwz() + 
        scale_fill_gradient(low = "#55FFFF", high = "#8B2E8B")

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.