tm_shape(r) + tm_raster()

library(tmap) system.file("gpkg/nc.gpkg", package = "sf") |> read_sf() |> st_transform('EPSG:32119') -> nc.32119 tm_shape(nc.32119) + tm_polygons(c("SID74", "SID79"), title = "SIDS") + tm_layout(legend.outside = TRUE, panel.labels = c("1974-78", "1979-84")) + tm_facets(free.scales=FALSE)

A/B testing example using hypothesis testing, confidence intervals, and visualization in R.

library(ggplot2) library(stars) r <- read_stars(system.file("tif/L7_ETMs.tif", package = "stars")) ggplot() + geom_stars(data = r) + facet_wrap(~band) + coord_equal() + theme_void() + scale_x_discrete(expand = c(0,0)) + scale_y_discrete(expand = c(0,0)) + scale_fill_viridis_c()

Dashboard quarto

library(tidyverse) |> suppressPackageStartupMessages() nc.32119 <- st_transform(nc, 32119) year_labels <- c("SID74" = "1974 - 1978", "SID79" = "1979 - 1984") nc.32119 |> select(SID74, SID79) |> pivot_longer(starts_with("SID")) -> nc_longer ggplot() + geom_sf(data = nc_longer, aes(fill = value), linewidth = 0.4) + facet_wrap(~ name, ncol = 1, labeller = labeller(name = year_labels)) + scale_y_continuous(breaks = 34:36) + scale_fill_gradientn(colours = sf.colors(20)) + theme(panel.grid.major = element_line(colour = "white"))

library(stars) # Loading required package: abind system.file("tif/L7_ETMs.tif", package = "stars") |> read_stars() -> r st_bbox(r) |> st_as_sfc() |> st_sample(5) |> st_buffer(300) -> circ hook <- function() { plot(circ, col = NA, border = 'yellow', add = TRUE) } plot(r, hook = hook, key.pos = 4)

library(sf) nc <- read_sf(system.file("gpkg/nc.gpkg", package = "sf")) plot(nc["BIR74"], reset = FALSE, key.pos = 4) plot(st_buffer(nc[1,1], units::set_units(10, km)), col = 'NA', border = 'red', lwd = 2, add = TRUE)

homework

install.packages("rnaturalearthdata") library(rnaturalearth) w <- ne_countries(scale = "medium", returnclass = "sf") suppressWarnings(st_crs(w) <- st_crs('OGC:CRS84')) layout(matrix(1:2, 1, 2), c(2,1)) par(mar = rep(0, 4)) plot(st_geometry(w)) # sphere: old <- options(s2_oriented = TRUE) # don't change orientation from here on countries <- s2::s2_data_countries() |> st_as_sfc() globe <- st_as_sfc("POLYGON FULL", crs = st_crs(countries)) oceans <- st_difference(globe, st_union(countries)) visible <- st_buffer(st_as_sfc("POINT(-30 -10)", crs = st_crs(countries)), 9800000) # visible half visible_ocean <- st_intersection(visible, oceans) visible_countries <- st_intersection(visible, countries) st_transform(visible_ocean, "+proj=ortho +lat_0=-10 +lon_0=-30") |> plot(col = 'lightblue') st_transform(visible_countries, "+proj=ortho +lat_0=-10 +lon_0=-30") |> plot(col = NA, add = TRUE)