README

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MexBrewer

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

Currently, there is only a development version of {MexBrewer}, which can be installed like so:

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

Artists

Electa Arenal

Revolución

Olga Costa

Naturaleza

Ofrenda

Vendedora

María Izquierdo

Alacena

La 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

Fanny Rabel

La Ronda del Tiempo

Aurora Reyes

El atentado a las maestras rurales

Aurora, Concha, y Frida

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

Remedios Varo

La 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)

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

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"))

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

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}

# 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

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)

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

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))
}

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

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")

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")

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
Health stats visible at Monitor.