Awesome

MexBrewer <img src="man/figures/MexBrewer.png" align="right" width=300 />

MexBrewer is a package with color palettes inspired by the works of Mexican painters and muralists. This package was motivated and draws heavily from the code of Blake R. Mills’s {MetBrewer}, the package with color palettes form the Metropolitan Museum of Art of New York. The structure of the package and coding, like {MetBrewer}, are based on {PNWColors} and {wesanderson}.

Installation

The package is available from CRAN:

install.packages("MexBrewer")

The development version of the package can be installed like so:

if (!require("remotes")) install.packages("remotes")
remotes::install_github("paezha/MexBrewer") 

Artists

Electa Arenal

Revolución

This palette is called Revolucion.

Olga Costa

Naturaleza

This palette is called Naturaleza.

Ofrenda

This palette is called Ofrenda.

Vendedora

This palette is called Vendedora.

María Izquierdo

Alacena

This palette is called Alacena.

La Tierra

This palette is called Tierra.

Frida Khalo

La Casa Azul

These palettes are called Casita1, Casita2, and Casita3. They are inspired by the colors of Frida’s home in Coyoacán, Mexico City.

Rina Lazo

Venerable Abuelo Maiz

This palette is called Maiz.

Fanny Rabel

La Ronda del Tiempo

This palette is called Ronda.

Aurora Reyes

El atentado a las maestras rurales

This palette is called Atentado.

Aurora, Concha, y Frida

This work of Aurora Rivera inspired three palettes, called Aurora, Concha, and Frida.

Remedios Varo

La Huida

This palette is called Huida.

Taurus

This work of Remedios Varo inspired two palettes, called Taurus1 and Taurus2.

Examples

library(aRtsy) # Koen Derks' package for generative art 
library(flametree) # Danielle Navarro's package for generative art
library(MexBrewer)
library(sf)
library(tidyverse)

Invoke data sets used in the examples:

data("mx_estados") # Simple features object with the boundaries of states in Mexico
data("df_mxstate_2020") # Data from {mxmaps }with population statistics at the state level

Join population statistics to state boundaries:

mx_estados <- mx_estados |>
  left_join(df_mxstate_2020 |>
              #Percentage of population that speak an indigenous language
              mutate(pct_ind_lang = indigenous_language/pop * 100) |> 
              dplyr::transmute(pop2020 = pop,
                               am2020 = afromexican,
                               state_name, 
                               pct_ind_lang),
            by = c("nombre" = "state_name"))

Distribution of population by geographic region in Mexico:

ggplot(data = mx_estados,
       aes(x = region, y = pop2020, fill = region)) +
  geom_boxplot() +
  scale_fill_manual(values = mex.brewer("Concha", n = 5)) +
  theme_minimal()

Percentage of population who speak an indigenous language in 2020 by state:

ggplot() +
  geom_sf(data = mx_estados,
          aes(fill = pct_ind_lang),
          color = "white",
          size = 0.08) +
  scale_fill_gradientn(colors = mex.brewer("Tierra")) +
  theme_minimal()

Some Rtistry

Danielle Navarro’s {flametree}

The following three images were created using the {flametree} package.

# pick some colours
shades <- MexBrewer::mex.brewer("Vendedora") |>
  as.vector()

# data structure defining the trees
dat <- flametree_grow(seed = 3563,
                      time = 11, 
                      trees = 10)

# draw the plot
dat |> 
  flametree_plot(
    background = shades[1],
    palette = shades[2:length(shades)], 
    style = "nativeflora"
  )

# pick some colours
shades <- MexBrewer::mex.brewer("Concha") |>
  as.vector()

# data structure defining the trees
dat <- flametree_grow(seed = 3536,
                      time = 8, 
                      trees = 6)

# draw the plot
dat |> 
  flametree_plot(
    background = shades[1],
    palette = rev(shades[2:length(shades)]), 
    style = "wisp"
  )

# pick some colours
shades <- MexBrewer::mex.brewer("Maiz") |>
  as.vector()

# data structure defining the trees
dat <- flametree_grow(seed = 3653,
                      time = 8, 
                      trees = 6)

# draw the plot
dat |> 
  flametree_plot(
    background = shades[1],
    palette = shades[2:length(shades)], 
    style = "minimal"
  )

Koen Derks’s aRtsy

The following three images were created using the {aRtsy} package.

Functions:

my_formula <- list(
  x = quote(runif(1, -1, 1) * x_i^2 - sin(y_i^2)),
  y = quote(runif(1, -1, 1) * y_i^3 - cos(x_i^2))
)

canvas_function(colors = mex.brewer("Atentado"), 
                polar = FALSE,
                by = 0.005,
                formula = my_formula)

Mosaic:

canvas_squares(colors = mex.brewer("Alacena"), 
               cuts = 20,
               ratio = 1.5,
               resolution = 200,
               noise = TRUE)

Mandelbrot’s set:

canvas_mandelbrot(colors = mex.brewer("Naturaleza"), 
                  zoom = 8,
                  iterations = 200,
                  resolution = 500)

Meghan S. Harris’s waves

These plots are adaptations of Meghan Harris’s artsy waves. Create data frames with wave functions:

##Set up the "range" on the x axis for horizontal waves=====
wave_theta <- seq(from = -pi,
                  to = -0, 
                  by = 0.01) 

# Create waves using functions
wave_1 <- data.frame(x = wave_theta) |> 
  mutate(y = (sin(x) * cos(2 * wave_theta) + exp(x * 2)))

wave_2 <- data.frame(x = wave_theta) |>
  mutate(y = (0.5 * sin(x) * cos(2.0 * wave_theta) + exp(x)) - 0.5)

Define a function to convert a single wave into a set of n waves. The function takes a data frame with a wave function and returns a data frame with n waves:

# Creating a function for iterations====

wave_maker <- function(wave_df, n, shift){
  
  #Create an empty list to store our multiple dataframes(waves)#
  wave_list<- list()
  
  #Create a for loop to iteratively make "n" waves shifted a distance `shift` from each other #
  for(i in seq_along(1:n)){
    
    wave_list[[i]] <- wave_df |>
      mutate(y = y - (shift * i),
             group = i)  
  }
  
  #return the completed data frame to the environment#
  return(bind_rows(wave_list))
}

Create layered waves using the data frames with the wave functions above:

wave_layers <- rbind(wave_1 |>
                       wave_maker(n = 5, 
                                  shift = 0.075),
                     wave_2 |>
                       wave_maker(n = 5, 
                                  shift = 0.075) |>
                       mutate(group = group + 5)) # adjust the group counter to identify waves uniquely

Plot layered waves using cartesian coordinates and palette Ofrenda:

ggplot(wave_layers) +
  geom_rect(aes(xmin = -pi, 
                xmax = -0.0, 
                ymin = min(y) - 0.50,
                ymax = max(y) + 0.30 ),
            size = 2.5,
            color = mex.brewer("Ofrenda")[6],
            fill = mex.brewer("Ofrenda")[4]) +
  geom_rect(aes(xmin = -pi, 
                xmax = -0.0, 
                ymin = min(y) - 0.50,
                ymax = max(y) + 0.30 ),
            size = 1,
            color = "black",
            fill = NA) +
  geom_ribbon(aes(x, 
                  ymin = y - 0.025 * 4 * x,
                  ymax = y + 0.015 * 10 * x, 
                  group = group, 
                  fill = group),
              color = "black",
              size = 0.5) + 
  scale_fill_gradientn(colors = mex.brewer("Ofrenda"))+
  theme_void() +
  theme(legend.position = "none")
#> Warning: Using `size` aesthetic for lines was deprecated in ggplot2 3.4.0.
#> ℹ Please use `linewidth` instead.

Plot layered waves using polar coordinates and palette Atentado:

ggplot(wave_layers) +
  geom_rect(aes(xmin = -pi, 
                xmax = -0.0, 
                ymin = min(y) - 0.45,
                ymax = max(y) + 0.30 ),
            size = 2.5,
            color = mex.brewer("Atentado")[6],
            fill = mex.brewer("Atentado")[3]) +
  geom_rect(aes(xmin = -pi, 
                xmax = -0.0, 
                ymin = min(y) - 0.45,
                ymax = max(y) + 0.30 ),
            size = 1,
            color = "black",
            fill = NA) +
  geom_ribbon(aes(x, 
                  ymin = y - 0.025 * 4 * x,
                  ymax = y + 0.015 * 10 * x, 
                  group = group, 
                  fill = group),
              color = "black",
              size = 0.5) + 
  scale_fill_gradientn(colors = mex.brewer("Atentado")) +
  coord_polar(theta = "x",  
              start = 0, 
              direction = 1, 
              clip = "on") +
  theme_void() +
  theme(legend.position = "none")