2021-11-03_baltimore-mixup-map.R

# inspirational example https://gist.github.com/ryanpeek/99c6935ae51429761f5f73cf3b027da2
# libraries
library(ggplot2)
library(dplyr)
library(purrr)
library(sf)
library(ggplot2)
library(mapbaltimore)
library(patchwork)

# areas <- neighborhoods
areas <- council_districts

# Set parameters for mixed-up map
scale_min <- 0.3 # Scale down by scale_min percent
scale_max <- 0.3 # Scale up by scale_max percent
rotate_deg <- 40 # Rotate up to rotate_deg degrees left or right

# Make scale/rotate function
scale_rotate <- function(x, scale = 1, rotate = 0) {
  # rotate function (see here: https://r-spatial.github.io/sf/articles/sf3.html#affine-transformations
  rot <- function(a) matrix(c(cos(a), sin(a), -sin(a), cos(a)), 2, 2)
  
  crs <- st_crs(x)
  geom <- st_geometry(x)
  center <- st_centroid(geom)
  
  y <- (geom - center) * rot(pi / (360 / (rotate * 2)))
  y <- y * scale + center
  
  st_geometry(x) <- y
  st_crs(x) <- crs
  x
}

area_list <- areas |>
  st_transform(4326) |>
  nest_by(name, .keep = TRUE)

city_layer <-
  list(
    geom_sf(data = baltimore_city_detailed, fill = NA, color = "gray40", size = 0.3),
    pilot::scale_fill_pilot(),
    theme_void()
  )

area_map <-
  ggplot() +
  geom_sf(data = areas, aes(fill = name), alpha = 0.4, show.legend = FALSE, size = 0.2) +
  city_layer

area_mixup_map <-
  ggplot() +
  map(
    area_list$data,
    ~ geom_sf(
      data = scale_rotate(
        .x,
        runif(1, min = 1 - scale_min, max = 1 + scale_max),
        runif(1, min = -1 * rotate_deg, max = rotate_deg)
      ), 
      aes(fill = name), alpha = 0.4, show.legend = FALSE, size = 0.2
    )
  ) +
  city_layer

area_map + area_mixup_map +
  plot_layout(
    ncol = 2,
    nrow = 1,
    widths = c(0.5, 0.5)
  )