made draft hexsticker

.pre-commit-config.yaml

@@ -43,7 +43,7 @@ repos:
     rev: v3.4.0
     hooks: 
     -   id: check-added-large-files
-        args: ['--maxkb=200']
+        args: ['--maxkb=800']
     -   id: end-of-file-fixer
         exclude: '\.Rd'
 -   repo: local

README.Rmd

@@ -11,6 +11,21 @@ knitr::opts_chunk$set(
 )
 ```
 
+
+# Hexsticker designs
+
+### Design 1
+![Design 1](man/figures/logo1.png)
+
+### Design 2
+![design 2](man/figures/logo2.png)
+
+### Design 3
+![design 3](man/figures/logo3.png)
+
+### Design 5
+![design 5](man/figures/logo5.png)
+
 # Subnational data for the COVID-19 outbreak
 
 [![Lifecycle: maturing](https://img.shields.io/badge/lifecycle-maturing-blue.svg)](https://lifecycle.r-lib.org/articles/stages.html) [![R-CMD-check](https://github.com/epiforecasts/covidregionaldata/workflows/R-CMD-check/badge.svg)](https://github.com/epiforecasts/covidregionaldata/actions) [![Codecov test coverage](https://codecov.io/gh/epiforecasts/covidregionaldata/branch/master/graph/badge.svg)](https://codecov.io/gh/epiforecasts/covidregionaldata?branch=master) [![Data status](https://img.shields.io/badge/Data-status-lightblue.svg?style=flat)](https://epiforecasts.io/covidregionaldata/articles/supported-countries.html) [![metacran downloads](http://cranlogs.r-pkg.org/badges/grand-total/covidregionaldata?color=ff69b4)](https://cran.r-project.org/package=covidregionaldata)

README.md

@@ -1,4 +1,22 @@
 
+# Hexsticker designs
+
+### Design 1
+
+![Design 1](man/figures/logo1.png)
+
+### Design 2
+
+![design 2](man/figures/logo2.png)
+
+### Design 3
+
+![design 3](man/figures/logo3.png)
+
+### Design 5
+
+![design 5](man/figures/logo5.png)
+
 # Subnational data for the COVID-19 outbreak
 
 [![Lifecycle:
@@ -27,11 +45,11 @@ both official sources, such as Public Health England in the UK, and from
 other Covid-19 data collections, including the World Health Organisation
 (WHO), European Centre for Disease Prevention and Control (ECDC), John
 Hopkins University (JHU), Google Open Data and others. This package is
-designed to streamline Covid-19 data extraction, cleaning, and processing
-from a range of data sources in an open and transparent way. This allows
-users to inspect and scrutinise the data, and tools used to process it,
-at every step. For all countries supported, data includes a daily
-time-series of cases and, wherever available, data on deaths,
+designed to streamline Covid-19 data extraction, cleaning, and
+processing from a range of data sources in an open and transparent way.
+This allows users to inspect and scrutinise the data, and tools used to
+process it, at every step. For all countries supported, data includes a
+daily time-series of cases and, wherever available, data on deaths,
 hospitalisations, and tests. National level data is also supported using
 a range of data sources as well as line list data and links to
 intervention data sets.
@@ -78,7 +96,7 @@ the temporary directory by default),
 
 ``` r
 start_using_memoise()
-#> Using a cache at: /tmp/RtmpJAeC7J
+#> Using a cache at: /tmp/Rtmp22YZr9
 ```
 
 To stop using `memoise` use,
@@ -103,7 +121,7 @@ the Google COVID-19 open data project), use:
 ``` r
 nots <- get_national_data()
 #> Downloading data from https://covid19.who.int/WHO-COVID-19-global-data.csv
-#> Rows: 124,425
+#> Rows: 126,084
 #> Columns: 8
 #> Delimiter: ","
 #> chr  [3]: Country_code, Country, WHO_region
@@ -115,7 +133,7 @@ nots <- get_national_data()
 #> Cleaning data
 #> Processing data
 nots
-#> # A tibble: 124,425 x 15
+#> # A tibble: 126,084 x 15
 #>    date       un_region who_region country        iso_code cases_new cases_total
 #>    <date>     <chr>     <chr>      <chr>          <chr>        <dbl>       <dbl>
 #>  1 2020-01-03 Asia      EMRO       Afghanistan    AF               0           0
@@ -128,7 +146,7 @@ nots
 #>  8 2020-01-03 Americas  AMRO       Antigua & Bar… AG               0           0
 #>  9 2020-01-03 Americas  AMRO       Argentina      AR               0           0
 #> 10 2020-01-03 Asia      EURO       Armenia        AM               0           0
-#> # … with 124,415 more rows, and 8 more variables: deaths_new <dbl>,
+#> # … with 126,074 more rows, and 8 more variables: deaths_new <dbl>,
 #> #   deaths_total <dbl>, recovered_new <dbl>, recovered_total <dbl>,
 #> #   hosp_new <dbl>, hosp_total <dbl>, tested_new <dbl>, tested_total <dbl>
 ```
@@ -169,7 +187,7 @@ for example by level 1 region in the UK, use:
 ``` r
 uk_nots <- get_regional_data(country = "UK", verbose = FALSE)
 uk_nots
-#> # A tibble: 6,474 x 26
+#> # A tibble: 6,565 x 26
 #>    date       region   region_code cases_new cases_total deaths_new deaths_total
 #>    <date>     <chr>    <chr>           <dbl>       <dbl>      <dbl>        <dbl>
 #>  1 2020-01-30 East Mi… E12000004          NA          NA         NA           NA
@@ -182,7 +200,7 @@ uk_nots
 #>  8 2020-01-30 Scotland S92000003          NA          NA         NA           NA
 #>  9 2020-01-30 South E… E12000008          NA          NA         NA           NA
 #> 10 2020-01-30 South W… E12000009          NA          NA         NA           NA
-#> # … with 6,464 more rows, and 19 more variables: recovered_new <dbl>,
+#> # … with 6,555 more rows, and 19 more variables: recovered_new <dbl>,
 #> #   recovered_total <dbl>, hosp_new <dbl>, hosp_total <dbl>, tested_new <dbl>,
 #> #   tested_total <dbl>, areaType <chr>, cumCasesByPublishDate <dbl>,
 #> #   cumCasesBySpecimenDate <dbl>, newCasesByPublishDate <dbl>,
@@ -256,10 +274,10 @@ using the following,
 
 [![Development](https://img.shields.io/badge/Wiki-lightblue.svg?style=flat)](https://github.com/epiforecasts/covidregionaldata/wiki/)
 
-This package is the result of work from a number of contributors
-(see contributors list in the
-[here](https://epiforecasts.io/covidregionaldata/authors.html)).
-We would like to thank the [CMMID COVID-19 working
+This package is the result of work from a number of contributors (see
+contributors list
+[here](https://epiforecasts.io/covidregionaldata/authors.html)). We
+would like to thank the [CMMID COVID-19 working
 group](https://cmmid.github.io/groups/ncov-group.html) for inciteful
 comments and feedback.
 

inst/WORDLIST

@@ -190,6 +190,7 @@ HDTRA
 Healy
 hellewell
 Hellewell
+Hexsticker
 Hiroaki
 hl
 Hongru

inst/make_hexsticker.R

@@ -0,0 +1,202 @@
+library(covidregionaldata)
+library(hexSticker)
+library(showtext)
+library(ggplot2)
+library(dplyr)
+library(maps)
+library(countrycode)
+library(sf)
+library(rnaturalearth)
+library(rmapshaper)
+
+# font setup
+font_add_google("Zilla Slab Highlight", "useme")
+
+# get countries we have data for
+regional_countries <- get_available_datasets() %>%
+  filter(.data$type == "regional")
+
+regional_countries_l2 <- regional_countries %>%
+  filter(!(is.na(.data$level_2_region)))
+
+regional_countries_l1 <- regional_countries %>%
+  filter(is.na(.data$level_2_region))
+
+# get world data
+world <- spData::world %>%
+  st_as_sf()
+
+
+# mark supported countries from the world data
+supported_countries <- world %>%
+  mutate(
+    fill = case_when(
+      name_long %in% countryname(regional_countries_l2[["origin"]], destination = "country.name.en") ~ "Level 2",
+      name_long %in% countryname(regional_countries[["origin"]], destination = "country.name.en") ~ "Level 1",
+      TRUE ~ "Unsupported"
+    )
+  )
+
+# make covid map
+covid_map_1 <- ggplot() +
+  ggspatial::layer_spatial(data = supported_countries, aes(fill = fill, color = fill, size = fill)) +
+  coord_sf(crs = "ESRI:54010") +
+  scale_fill_manual(
+    name = "",
+    values = c("#0072b2", "#cc79a7", "grey80")
+  ) +
+  scale_color_manual(
+    name = "",
+    values = c("black", "black", "#666666")
+  ) +
+  scale_size_manual(
+    name = "",
+    values = c(0.1, 0.1, 0.018)
+  ) +
+  cowplot::theme_minimal_grid(color = "white", line_size = 0.05) +
+  theme(legend.position = "none", axis.text.x = element_blank())
+
+logo1 <- sticker(
+  covid_map_1,
+  package = "covidregionaldata",
+  p_size = 48, s_x = 1, s_y = 0.8, s_width = 1.98, s_height = 1.98,
+  p_y = 1.45,
+  p_color = "white",
+  p_family = "useme",
+  h_color = "#646770",
+  h_fill = "#24A7DF",
+  filename = "man/figures/logo1.png",
+  u_size = 3.5,
+  dpi = 1000
+)
+
+# make logo 2
+supported_countries <- supported_countries %>%
+  filter(name_long != "Antarctica")
+
+covid_map_2 <- ggplot() +
+  ggspatial::layer_spatial(data = supported_countries, aes(fill = fill, size = fill, color = fill)) +
+  coord_sf(crs = "ESRI:54016") +
+  scale_fill_manual(
+    name = "",
+    values = c("#0072b2", "#cc79a7", "grey80")
+  ) +
+  scale_color_manual(
+    name = "",
+    values = c("black", "black", "#666666")
+  ) +
+  scale_size_manual(
+    name = "",
+    values = c(0.1, 0.1, 0.018)
+  ) +
+  theme_void() +
+  theme(legend.position = "none", axis.text.x = element_blank())
+
+print(covid_map_2)
+
+# Approach using Natural Earth data
+
+world_without_regions <- ne_countries(returnclass = "sf") %>%
+  filter(sovereignt != "Antarctica")
+
+# numberOfLevels should be less than half the number of colours in the
+# divergent palette used (usually 7)
+numberOfLevels <- 3
+
+regional_maps_l1 <- ms_simplify(
+  ne_states(gsub(" \\(.*\\)", "",
+    regional_countries_l1$origin,
+    perl = TRUE
+  ), returnclass = "sf") %>%
+    mutate(region_code = woe_id %% numberOfLevels),
+  keep = 0.04
+)
+
+regional_maps_l2 <- ms_simplify(
+  ne_states(gsub(" \\(.*\\)", "",
+    regional_countries_l2$origin,
+    perl = TRUE
+  ), returnclass = "sf") %>%
+    mutate(region_code = woe_id %% numberOfLevels + numberOfLevels + 1),
+  keep = 0.04
+)
+
+regional_maps <- bind_rows(regional_maps_l1, regional_maps_l2)
+
+# We keep 50% of the points of the country outlines because it's a
+# finer scale map
+# We add the US and the UK to the list because otherwise we don't
+# successfully include them.
+regional_outlines <- ms_lines(
+  ms_simplify(
+    ne_countries(
+      country = c(
+        gsub(" \\(.*\\)", "", regional_countries$origin, perl = TRUE),
+        "United States", "United Kingdom"
+      ),
+      returnclass = "sf"
+    ),
+    keep = 0.5
+  )
+)
+
+
+covid_map_3 <- ggplot() +
+  ggspatial::layer_spatial(data = world_without_regions, size = 0.01) +
+  ggspatial::layer_spatial(
+    data = regional_maps,
+    aes(fill = region_code), size = 0.02
+  ) +
+  ggspatial::layer_spatial(
+    data = regional_outlines,
+    aes(colour = 1), size = 0.1
+  ) +
+  coord_sf(crs = "ESRI:54016") +
+  scale_fill_fermenter(palette = "RdBu") +
+  theme_void() +
+  theme(legend.position = "none", axis.text.x = element_blank())
+
+print(covid_map_3)
+
+logo2 <- sticker(
+  covid_map_2,
+  package = "covidregionaldata",
+  p_size = 48, s_x = 0.96, s_y = 0.8, s_width = 1.7, s_height = 1.7,
+  p_y = 1.45,
+  p_color = "white",
+  p_family = "useme",
+  h_color = "#646770",
+  h_fill = "#24A7DF",
+  filename = "man/figures/logo2.png",
+  u_size = 3.5,
+  dpi = 1000
+)
+
+logo3 <- sticker(
+  covid_map_2,
+  package = "covidregionaldata",
+  p_size = 48, s_x = 1, s_y = 0.8, s_width = 1.7, s_height = 1.7,
+  p_y = 1.45,
+  p_color = "white",
+  p_family = "useme",
+  h_color = "#646770",
+  h_fill = "#24A7DF",
+  filename = "man/figures/logo3.png",
+  u_size = 3.5,
+  dpi = 1000
+)
+
+logo4 <- sticker(
+  covid_map_3,
+  package = "covidregionaldata",
+  p_size = 48, s_x = 1, s_y = 0.8, s_width = 1.7, s_height = 1.7,
+  p_y = 1.45,
+  p_color = "white",
+  p_family = "useme",
+  h_color = "#646770",
+  h_fill = "#24A7DF",
+  filename = "man/figures/logo5.png",
+  u_size = 3.5,
+  dpi = 1000
+)
+