Fixes for submission

.Rbuildignore

@@ -16,3 +16,4 @@ geofacet.code-workspace
 ^pkgdown$
 ^revdep$
 ^\.github$
+^CRAN-SUBMISSION$

.github/workflows/R-CMD-check.yaml

@@ -26,4 +26,6 @@ jobs:
           extra-packages: any::rcmdcheck
           needs: check
 
+      - run: Rscript -e 'install.packages("rnaturalearthhires", repos = "https://ropensci.r-universe.dev", type = "source")'
+
       - uses: r-lib/actions/check-r-package@v2

R/grid_auto.R

@@ -215,11 +215,11 @@ plot_geo_raw <- function(x, label = "name") {
 
   ggplot2::ggplot(tmp) +
     ggplot2::geom_polygon(aes(x = long, y = lat, group = group),
-      fill = "lightgray", color = "white", size = 0.3) +
+      fill = "lightgray", color = "white", linewidth = 0.3) +
     ggrepel::geom_text_repel(aes(xcentroid, ycentroid, label = label_col),
       data = tmpl, min.segment.length = 0) +
     ggplot2::coord_equal() +
-    ggplot2::guides(fill = FALSE) +
+    ggplot2::guides(fill = "none") +
     ggplot2::theme_void()
 }
 

cran-comments.md

@@ -47,10 +47,6 @@ Found the following (possibly) invalid URLs:
           inst/doc/geofacet.html
     Status: 403
     Message: Forbidden
-  URL: https://countymapsofwashington.com/aapics/washingstate.gif
-    From: man/grids.Rd
-    Status: 403
-    Message: Forbidden
   For content that is 'Moved Permanently', please change http to https,
   add trailing slashes, or replace the old by the new URL.
 

tests/testthat/test-auto.R

@@ -5,22 +5,28 @@ test_that("auto examples work", {
   testthat::skip_if_not_installed("rnaturalearthhires")
 
   # auto grid using a name to identify the country
-  grd <- grid_auto("brazil", seed = 1234)
-  grid_preview(grd, label = "name")
-  grd$name2 <- gsub(" ", "\n", grd$name)
-  grid_preview(grd, label = "name2", label_raw = "name")
-  # open the result up in the grid designer for further refinement
-  grid_design(grd, label = "name")
+  expect_no_error({
+    grd <- grid_auto("uruguay", seed = 1234)
+    grid_preview(grd, label = "name")
+    grd$name2 <- gsub(" ", "\n", grd$name)
+    grid_preview(grd, label = "name2", label_raw = "name")
+    # open the result up in the grid designer for further refinement
+    # grid_design(grd, label = "name")
+  })
 
   # using a custom file (can be GeoJSON or shapefile)
-  ff <- system.file("extdata", "bay_counties.geojson", package = "geogrid")
-  bay_shp <- sf::st_read(ff)
-  grd <- grid_auto(bay_shp, seed = 1) # names are inferred
-  grid_preview(grd, label = "name_county")
-  grid_design(grd, label = "code_fipsstco")
+  expect_no_error({
+    ff <- system.file("extdata", "bay_counties.geojson", package = "geogrid")
+    bay_shp <- sf::st_read(ff)
+    grd <- grid_auto(bay_shp, seed = 1) # names are inferred
+    grid_preview(grd, label = "name_county")
+    # grid_design(grd, label = "code_fipsstco")
+  })
 
   # explicitly specify the names and codes variables to use
-  grd <- grid_auto(bay_shp, seed = 1, names = "county", codes = "fipsstco")
-  grid_preview(grd, label = "name_county")
-  grid_preview(grd, label = "code_fipsstco")
+  expect_no_error({
+    grd <- grid_auto(bay_shp, seed = 1, names = "county", codes = "fipsstco")
+    grid_preview(grd, label = "name_county")
+    # grid_preview(grd, label = "code_fipsstco")
+  })
 })

tests/testthat/test-break.R

@@ -59,7 +59,7 @@ test_that("things break in an expected way", {
         y = "Population density per square km") +
       theme_bw()
   },
-  "will be ignored")
+  "does not exist")
 
   my_grid <- us_state_grid1
 

tests/testthat/test-examples.R

@@ -3,154 +3,185 @@ context("examples")
 library(ggplot2)
 
 test_that("examples work", {
-
   # barchart of state rankings in various categories
-  p <- ggplot(state_ranks, aes(variable, rank, fill = variable)) +
-    geom_col() +
-    coord_flip() +
-    facet_geo(~ state) +
-    theme_bw()
-  print(p)
+  expect_no_error({
+    p <- ggplot(state_ranks, aes(variable, rank, fill = variable)) +
+      geom_col() +
+      coord_flip() +
+      facet_geo(~ state) +
+      theme_bw()
+    print(p)
+  })
 
   # use an alternative US state grid and place
-  p <- ggplot(state_ranks, aes(variable, rank, fill = variable)) +
-    geom_col() +
-    coord_flip() +
-    facet_geo(~ state, grid = "us_state_grid2") +
-    theme(panel.spacing = unit(0.1, "lines"))
-  print(p)
-
-  grid_preview(us_state_grid2)
-  grid_preview(eu_grid1, label = "name")
+  expect_no_error({
+    p <- ggplot(state_ranks, aes(variable, rank, fill = variable)) +
+      geom_col() +
+      coord_flip() +
+      facet_geo(~ state, grid = "us_state_grid2") +
+      theme(panel.spacing = unit(0.1, "lines"))
+    print(p)
+  })
+
+  expect_no_error(grid_preview(us_state_grid2))
+  expect_no_error(grid_preview(eu_grid1, label = "name"))
 
   # custom grid (move Hawaii over more)
-  my_grid <- us_state_grid2
-  my_grid$col <- my_grid$col + 2
-  my_grid$col[my_grid$code == "HI"] <- 1
-  grid_preview(my_grid)
+  expect_no_error({
+    my_grid <- us_state_grid2
+    my_grid$col <- my_grid$col + 2
+    my_grid$col[my_grid$code == "HI"] <- 1
+    grid_preview(my_grid)
+  })
 
   # test to make sure we can have empty columns (since Hawaii is moved over)
-  p <- ggplot(state_ranks, aes(variable, rank, fill = variable)) +
-    geom_col() +
-    coord_flip() +
-    facet_geo(~ state, grid = my_grid)
-  print(p)
+  expect_no_error({
+    p <- ggplot(state_ranks, aes(variable, rank, fill = variable)) +
+      geom_col() +
+      coord_flip() +
+      facet_geo(~ state, grid = my_grid)
+    print(p)
+  })
 
   # use a free x-axis (not a good idea but just to show it works)
-  p <- ggplot(state_ranks, aes(variable, rank, fill = variable)) +
-    geom_col() +
-    coord_flip() +
-    facet_geo(~ state, scales = "free_x") +
-    theme_bw()
-  print(p)
+  expect_no_error({
+    p <- ggplot(state_ranks, aes(variable, rank, fill = variable)) +
+      geom_col() +
+      coord_flip() +
+      facet_geo(~ state, scales = "free_x") +
+      theme_bw()
+    print(p)
+  })
 
   # plot unemployment rate time series for each state
-  p <- ggplot(state_unemp, aes(year, rate)) +
-    geom_line() +
-    facet_geo(~ state) +
-    scale_x_continuous(labels = function(x) paste0("'", substr(x, 3, 4))) +
-    ylab("Unemployment Rate (%)")
-  print(p)
+  expect_no_error({
+    p <- ggplot(state_unemp, aes(year, rate)) +
+      geom_line() +
+      facet_geo(~ state) +
+      scale_x_continuous(labels = function(x) paste0("'", substr(x, 3, 4))) +
+      ylab("Unemployment Rate (%)")
+    print(p)
+  })
 
   # plot the 2016 unemployment rate
-  p <- ggplot(subset(state_unemp, year == 2016), aes(factor(year), rate)) +
-    geom_col(fill = "steelblue") +
-    facet_geo(~ state) +
-    theme(
-      axis.title.x = element_blank(),
-      axis.text.x = element_blank(),
-      axis.ticks.x = element_blank()) +
-    ylab("Unemployment Rate (%)")
-  print(p)
+  expect_no_error({
+    p <- ggplot(subset(state_unemp, year == 2016), aes(factor(year), rate)) +
+      geom_col(fill = "steelblue") +
+      facet_geo(~ state) +
+      theme(
+        axis.title.x = element_blank(),
+        axis.text.x = element_blank(),
+        axis.ticks.x = element_blank()) +
+      ylab("Unemployment Rate (%)")
+    print(p)
+  })
 
   # plot European Union GDP
-  p <- ggplot(eu_gdp, aes(year, gdp_pc)) +
-    geom_line(color = "steelblue") +
-    geom_hline(yintercept = 100, linetype = 2) +
-    facet_geo(~ name, grid = "eu_grid1") +
-    scale_x_continuous(labels = function(x) paste0("'", substr(x, 3, 4))) +
-    ylab("GDP Per Capita") +
-    theme_bw()
-  print(p)
+  expect_no_error({
+    p <- ggplot(eu_gdp, aes(year, gdp_pc)) +
+      geom_line(color = "steelblue") +
+      geom_hline(yintercept = 100, linetype = 2) +
+      facet_geo(~ name, grid = "eu_grid1") +
+      scale_x_continuous(labels = function(x) paste0("'", substr(x, 3, 4))) +
+      ylab("GDP Per Capita") +
+      theme_bw()
+    print(p)
+  })
 
   # use a free y-axis to look at just change
-  p <- ggplot(eu_gdp, aes(year, gdp_pc)) +
-    geom_line(color = "steelblue") +
-    facet_geo(~ name, grid = "eu_grid1", scales = "free_y") +
-    scale_x_continuous(labels = function(x) paste0("'", substr(x, 3, 4))) +
-    ylab("GDP Per Capita in Relation to EU Index (100)") +
-    theme_bw()
-  print(p)
+  expect_no_error({
+    p <- ggplot(eu_gdp, aes(year, gdp_pc)) +
+      geom_line(color = "steelblue") +
+      facet_geo(~ name, grid = "eu_grid1", scales = "free_y") +
+      scale_x_continuous(labels = function(x) paste0("'", substr(x, 3, 4))) +
+      ylab("GDP Per Capita in Relation to EU Index (100)") +
+      theme_bw()
+    print(p)
+  })
 
   # plot European Union annual # of resettled persons
-  p <- ggplot(eu_imm, aes(year, persons)) +
-    geom_line() +
-    facet_geo(~ name, grid = "eu_grid1") +
-    scale_x_continuous(labels = function(x) paste0("'", substr(x, 3, 4))) +
-    scale_y_sqrt(minor_breaks = NULL) +
-    ylab("# Resettled Persons") +
-    theme_bw()
-  print(p)
+  expect_no_error({
+    p <- ggplot(eu_imm, aes(year, persons)) +
+      geom_line() +
+      facet_geo(~ name, grid = "eu_grid1") +
+      scale_x_continuous(labels = function(x) paste0("'", substr(x, 3, 4))) +
+      scale_y_sqrt(minor_breaks = NULL) +
+      ylab("# Resettled Persons") +
+      theme_bw()
+    print(p)
+  })
 
   # plot just for 2016
-  p <- ggplot(subset(eu_imm, year == 2016), aes(factor(year), persons)) +
-    geom_col(fill = "steelblue") +
-    geom_text(aes(factor(year), 3000, label = persons), color = "gray") +
-    facet_geo(~ name, grid = "eu_grid1") +
-    theme(
-      axis.title.x = element_blank(),
-      axis.text.x = element_blank(),
-      axis.ticks.x = element_blank()) +
-    ylab("# Resettled Persons in 2016") +
-    xlab("Year") +
-    theme_bw()
-  print(p)
+  expect_no_error({
+    p <- ggplot(subset(eu_imm, year == 2016), aes(factor(year), persons)) +
+      geom_col(fill = "steelblue") +
+      geom_text(aes(factor(year), 3000, label = persons), color = "gray") +
+      facet_geo(~ name, grid = "eu_grid1") +
+      theme(
+        axis.title.x = element_blank(),
+        axis.text.x = element_blank(),
+        axis.ticks.x = element_blank()) +
+      ylab("# Resettled Persons in 2016") +
+      xlab("Year") +
+      theme_bw()
+    print(p)
+  })
 
   # plot Australian population
-  p <- ggplot(aus_pop, aes(age_group, pop / 1e6, fill = age_group)) +
-    geom_col() +
-    facet_geo(~ code, grid = "aus_grid1") +
-    coord_flip() +
-    labs(
-      title = "Australian Population Breakdown",
-      caption = "Data Source: ABS Labour Force Survey, 12 month average",
-      y = "Population [Millions]") +
-    theme_bw()
-  print(p)
+  expect_no_error({
+    p <- ggplot(aus_pop, aes(age_group, pop / 1e6, fill = age_group)) +
+      geom_col() +
+      facet_geo(~ code, grid = "aus_grid1") +
+      coord_flip() +
+      labs(
+        title = "Australian Population Breakdown",
+        caption = "Data Source: ABS Labour Force Survey, 12 month average",
+        y = "Population [Millions]") +
+      theme_bw()
+    print(p)
+  })
 
   # South Africa population density by province
-  p <- ggplot(sa_pop_dens, aes(factor(year), density, fill = factor(year))) +
-    geom_col() +
-    facet_geo(~ code, grid = "sa_prov_grid1") +
-    labs(title = "South Africa population density by province",
-      caption = "Data Source: Statistics SA Census",
-      y = "Population density per square km") +
-    theme_bw()
-  print(p)
+  expect_no_error({
+    p <- ggplot(sa_pop_dens, aes(factor(year), density, fill = factor(year))) +
+      geom_col() +
+      facet_geo(~ code, grid = "sa_prov_grid1") +
+      labs(title = "South Africa population density by province",
+        caption = "Data Source: Statistics SA Census",
+        y = "Population density per square km") +
+      theme_bw()
+    print(p)
+  })
 
   # Use the Afrikaans name stored in the grid, "name_af", as facet labels
-  p <- ggplot(sa_pop_dens, aes(factor(year), density, fill = factor(year))) +
-    geom_col() +
-    facet_geo(~ code, grid = "sa_prov_grid1", label = "name_af") +
-    labs(title = "South Africa population density by province",
-      caption = "Data Source: Statistics SA Census",
-      y = "Population density per square km") +
-    theme_bw()
-  print(p)
+  expect_no_error({
+    p <- ggplot(sa_pop_dens, aes(factor(year), density, fill = factor(year))) +
+      geom_col() +
+      facet_geo(~ code, grid = "sa_prov_grid1", label = "name_af") +
+      labs(title = "South Africa population density by province",
+        caption = "Data Source: Statistics SA Census",
+        y = "Population density per square km") +
+      theme_bw()
+    print(p)
+  })
 
   Sys.setenv(GEOFACET_PKG_TESTING = "TRUE")
-  my_grid <- us_state_grid1
-  my_grid$col[my_grid$code == "WI"] <- 7
-  grid_submit(my_grid, name = "us_grid_tweak_wi",
-    desc = "Modified us_state_grid1 to move WI over")
-
-  # edit aus_grid1
-  grid_design(data = aus_grid1,
-    img = "http://www.john.chapman.name/Austral4.gif")
-  # start with a clean slate
-  grid_design()
-  # arrange the alphabet
-  grid_design(data.frame(code = letters))
+  expect_no_error({
+    my_grid <- us_state_grid1
+    my_grid$col[my_grid$code == "WI"] <- 7
+    grid_submit(my_grid, name = "us_grid_tweak_wi",
+      desc = "Modified us_state_grid1 to move WI over")
+  })
+
+  expect_no_error({
+    # edit aus_grid1
+    grid_design(data = aus_grid1,
+      img = "http://www.john.chapman.name/Austral4.gif")
+    # start with a clean slate
+    grid_design()
+    # arrange the alphabet
+    grid_design(data.frame(code = letters))
+  })
 
   Sys.setenv(GEOFACET_PKG_TESTING = "")