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https://paezha.github.io/MexBrewer/
Color Palettes Inspired by Works Mexican Muralists
https://paezha.github.io/MexBrewer/
colors dataviz mexico rstats rstats-package rtistry
Last synced: 2 days ago
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Color Palettes Inspired by Works Mexican Muralists
- Host: GitHub
- URL: https://paezha.github.io/MexBrewer/
- Owner: paezha
- License: other
- Created: 2021-12-30T03:30:11.000Z (almost 3 years ago)
- Default Branch: master
- Last Pushed: 2023-02-24T13:35:03.000Z (over 1 year ago)
- Last Synced: 2024-08-03T23:24:49.408Z (3 months ago)
- Topics: colors, dataviz, mexico, rstats, rstats-package, rtistry
- Language: R
- Homepage: https://paezha.github.io/MexBrewer/
- Size: 13.9 MB
- Stars: 21
- Watchers: 1
- Forks: 1
- Open Issues: 0
-
Metadata Files:
- Readme: README.Rmd
- License: LICENSE
Awesome Lists containing this project
README
---
output: github_document
---
```{r, include = FALSE}
knitr::opts_chunk$set(
collapse = TRUE,
comment = "#>",
fig.path = "man/figures/README-",
out.width = "100%"
)
```
# MexBrewer [
](https://paezha.github.io/MexBrewer/)
[](https://CRAN.R-project.org/package=MexBrewer)
[](https://lifecycle.r-lib.org/articles/stages.html#stable)
[](https://github.com/paezha/MexBrewer/stargazers)
[](https://cran.r-project.org/package=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](https://github.com/BlakeRMills/)'s
[{MetBrewer}](https://github.com/BlakeRMills/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}](https://github.com/jakelawlor/PNWColors) and [{wesanderson}](https://github.com/karthik/wesanderson).
## Installation
The package is available from CRAN:
```r
install.packages("MexBrewer")
```
The development version of the package can be installed like so:
``` r
if (!require("remotes")) install.packages("remotes")
remotes::install_github("paezha/MexBrewer")
```
## Artists
### Electa Arenal
#### Revolución
This palette is called `Revolucion`.
```{r revolucion, echo=FALSE, out.width="400px", fig.cap="Revolucion"}
knitr::include_graphics("man/figures/electa_arenal_revolucion.jpg")
```
```{r revolucion-palette, echo=FALSE, out.width="185px", fig.cap="Revolucion"}
knitr::include_graphics("man/figures/revolucion.png")
```
***
### Olga Costa
#### Naturaleza
This palette is called `Naturaleza`.
```{r naturaleza, echo=FALSE, out.width="400px", fig.cap="Naturaleza"}
knitr::include_graphics("man/figures/olga_costa_naturaleza.jpg")
```
```{r naturaleza-palette, echo=FALSE, out.width="185px", fig.cap="Naturaleza"}
knitr::include_graphics("man/figures/naturaleza.png")
```
#### Ofrenda
This palette is called `Ofrenda`.
```{r ofrenda, echo=FALSE, out.width="400px", fig.cap="Ofrenda"}
knitr::include_graphics("man/figures/olga_costa_ofrenda.jpg")
```
```{r ofrenda-palette, echo=FALSE, out.width="185px", fig.cap="Ofrenda"}
knitr::include_graphics("man/figures/ofrenda.png")
```
#### Vendedora
This palette is called `Vendedora`.
```{r vendedora, echo=FALSE, out.width="400px", fig.cap="Vendedora"}
knitr::include_graphics("man/figures/olga_costa_vendedora.jpg")
```
```{r vendedora-palette, echo=FALSE, out.width="185px", fig.cap="Vendedora"}
knitr::include_graphics("man/figures/vendedora.png")
```
***
### María Izquierdo
#### Alacena
This palette is called `Alacena`.
```{r alacena, echo=FALSE, out.width="400px", fig.cap="Alacena"}
knitr::include_graphics("man/figures/maria_izquierdo_alacena.jpg")
```
```{r alacena-palette, echo=FALSE, out.width="185px", fig.cap="Alacena"}
knitr::include_graphics("man/figures/alacena.png")
```
#### La Tierra
This palette is called `Tierra`.
```{r tierra, echo=FALSE, out.width="400px", fig.cap="Tierra"}
knitr::include_graphics("man/figures/maria_izquierdo_tierra.jpg")
```
```{r tierra-palette, echo=FALSE, out.width="185px", fig.cap="Tierra"}
knitr::include_graphics("man/figures/tierra.png")
```
***
### Frida Khalo
#### La Casa Azul
These palettes are called `Casita1`, `Casita2`, and `Casita3`. They are inspired by the colors of [Frida's home](https://www.museofridakahlo.org.mx/museo/) in Coyoacán, Mexico City.
```{r casa-azul-1, echo=FALSE, out.width="400px", fig.cap="Casa Azul"}
knitr::include_graphics("man/figures/casa-azul-1.jpg")
```
```{r casa-azul-2, echo=FALSE, out.width="400px", fig.cap="Casa Azul"}
knitr::include_graphics("man/figures/casa-azul-2.jpg")
```
```{r casa-azul-3, echo=FALSE, out.width="400px", fig.cap="Casa Azul"}
knitr::include_graphics("man/figures/casa-azul-3.jpg")
```
```{r casa-azul-4, echo=FALSE, out.width="400px", fig.cap="Casa Azul"}
knitr::include_graphics("man/figures/casa-azul-4.jpg")
```
```{r casa-azul-5, echo=FALSE, out.width="400px", fig.cap="Casa Azul"}
knitr::include_graphics("man/figures/casa-azul-5.jpg")
```
```{r casa-azul-6, echo=FALSE, out.width="400px", fig.cap="Casa Azul"}
knitr::include_graphics("man/figures/casa-azul-6.jpg")
```
```{r casita-1-palette, echo=FALSE, out.width="185px", fig.cap="Casita1"}
knitr::include_graphics("man/figures/casita-1.png")
```
```{r casita-2-palette, echo=FALSE, out.width="185px", fig.cap="Casita2"}
knitr::include_graphics("man/figures/casita-2.png")
```
```{r casita-3-palette, echo=FALSE, out.width="185px", fig.cap="Casita3"}
knitr::include_graphics("man/figures/casita-3.png")
```
***
### Rina Lazo
#### Venerable Abuelo Maiz
This palette is called `Maiz`.
```{r maiz, echo=FALSE, out.width="400px", fig.cap="Maiz"}
knitr::include_graphics("man/figures/rina_lazo_maiz.jpg")
```
```{r maiz-palette, echo=FALSE, out.width="185px", fig.cap="Maiz"}
knitr::include_graphics("man/figures/maiz.png")
```
***
### Fanny Rabel
#### La Ronda del Tiempo
This palette is called `Ronda`.
```{r ronda, echo=FALSE, out.width="400px", fig.cap="Ronda"}
knitr::include_graphics("man/figures/fanny_rabel_ronda.jpg")
```
```{r ronda-palette, echo=FALSE, out.width="185px", fig.cap="Ronda"}
knitr::include_graphics("man/figures/ronda.png")
```
***
### Aurora Reyes
#### El atentado a las maestras rurales
This palette is called `Atentado`.
```{r echo=FALSE, out.width="400px", fig.cap="Aurora, Concha, y Frida"}
knitr::include_graphics("man/figures/aurora_reyes_atentado.jpeg")
```
```{r echo=FALSE, out.width="185px", fig.cap="Aurora"}
knitr::include_graphics("man/figures/atentado.png")
```
#### Aurora, Concha, y Frida
This work of Aurora Rivera inspired three palettes, called `Aurora`, `Concha`, and `Frida`.
```{r auroa-concha-frida, echo=FALSE, out.width="400px", fig.cap="Aurora, Concha, y Frida"}
knitr::include_graphics("man/figures/aurora_concha_frida.jpg")
```
```{r aurora-palette, echo=FALSE, out.width="185px", fig.cap="Aurora"}
knitr::include_graphics("man/figures/aurora.png")
```
```{r concha-palette, echo=FALSE, out.width="185px", fig.cap="Concha"}
knitr::include_graphics("man/figures/concha.png")
```
```{r frida-palette, echo=FALSE, out.width="185px", fig.cap="Frida"}
knitr::include_graphics("man/figures/frida.png")
```
***
### Remedios Varo
#### La Huida
This palette is called `Huida`.
```{r echo=FALSE, out.width="400px", fig.cap="La Huida"}
knitr::include_graphics("man/figures/remedios_varo_huida.jpg")
```
```{r echo=FALSE, out.width="185px", fig.cap="Huida"}
knitr::include_graphics("man/figures/huida.png")
```
#### Taurus
This work of Remedios Varo inspired two palettes, called `Taurus1` and `Taurus2`.
```{r Taurus, echo=FALSE, out.width="400px", fig.cap="Taurus"}
knitr::include_graphics("man/figures/remedios_varo_taurus.jpg")
```
```{r taurus1-palette, echo=FALSE, out.width="185px", fig.cap="Taurus1"}
knitr::include_graphics("man/figures/taurus1.png")
```
```{r taurus2-palette, echo=FALSE, out.width="185px", fig.cap="Taurus2"}
knitr::include_graphics("man/figures/taurus2.png")
```
***
## Examples
```{r load-packges, message=FALSE, warning=FALSE}
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:
```{r load-data}
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:
```{r prepare-data}
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:
```{r population-distribution}
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:
```{r indigenous-languages}
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}](https://github.com/djnavarro/flametree)
The following three images were created using the {flametree} package.
```{r flametree-1, cache=TRUE}
# 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"
)
```
```{r flametree-2, cache=TRUE}
# 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"
)
```
```{r flametree-3, cache=TRUE}
# 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](https://github.com/koenderks/aRtsy)
The following three images were created using the {aRtsy} package.
Functions:
```{r aRtsy-1, cache=TRUE}
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:
```{r aRtsy-2, cache=TRUE}
canvas_squares(colors = mex.brewer("Alacena"),
cuts = 20,
ratio = 1.5,
resolution = 200,
noise = TRUE)
```
Mandelbrot's set:
```{r aRtsy-3, cache=TRUE}
canvas_mandelbrot(colors = mex.brewer("Naturaleza"),
zoom = 8,
iterations = 200,
resolution = 500)
```
### Meghan S. Harris's [waves](https://thetidytrekker.com/rtistry.html)
These plots are adaptations of Meghan Harris's artsy waves. Create data frames with wave functions:
```{r}
##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:
```{r}
# 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:
```{r}
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`:
```{r}
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")
```
Plot layered waves using polar coordinates and palette `Atentado`:
```{r}
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")
```