added schoolmaps_PDFs.Rmd

.gitignore

@@ -1,9 +1,3 @@
-data/TOPS/*
-basemaps/*
-figures/school_maps/*
-figures/municipalities/*
-api_keys/*
-basemaps/*
 .Rproj.user
 .Rhistory
-other/districts_done.csv
+districts_done.csv

Makefile

@@ -0,0 +1,18 @@
+osrm: osrm-data osrm-containers
+
+TOPS_data_process: R/TOPS_data_process.Rmd
+	R -e 'library("rmarkdown"); old_path <- Sys.getenv("PATH"); Sys.setenv(PATH = paste(old_path, "/usr/local/bin", sep = ":")); rmarkdown::render(knit_root_dir = "../", output_dir = "./html", input = "./R/TOPS_data_process.Rmd", output_file = "./html/TOPS_data_process.html")'
+
+schoolmaps_PDFs: R/schoolmaps_PDFs.Rmd
+	R -e 'library("rmarkdown"); old_path <- Sys.getenv("PATH"); Sys.setenv(PATH = paste(old_path, "/usr/local/bin", sep = ":")); rmarkdown::render(knit_root_dir = "../", output_dir = "./html", input = "./R/schoolmaps_PDFs.Rmd", output_file = "./html/schoolmaps_PDFs.html")'
+
+crashmaps_dynamic:
+
+osrm-data:
+	cd ./docker/osrm/; wget https://download.geofabrik.de/north-america/us/wisconsin-latest.osm.pbf -O ./data-raw/wisconsin-latest.osm.pbf
+	cd ./docker/osrm/; docker run --rm -t -v "./data-foot:/data" -v "./data-raw/wisconsin-latest.osm.pbf:/data/wisconsin-latest.osm.pbf" osrm/osrm-backend osrm-extract -p /opt/foot.lua /data/wisconsin-latest.osm.pbf
+	cd ./docker/osrm/; docker run --rm -t -v "./data-foot:/data" -v "./data-raw/wisconsin-latest.osm.pbf:/data/wisconsin-latest.osm.pbf" osrm/osrm-backend osrm-partition /data/wisconsin-latest.osrm
+	cd ./docker/osrm/; docker run --rm -t -v "./data-foot:/data" -v "./data-raw/wisconsin-latest.osm.pbf:/data/wisconsin-latest.osm.pbf" osrm/osrm-backend osrm-customize /data/wisconsin-latest.osrm
+
+osrm-containers: ./docker/osrm/docker-compose.yml
+	cd ./docker/osrm/; docker compose up -d

R/TOPS_data_process.Rmd

@@ -0,0 +1,108 @@
+---
+title: "TOPS data process"
+output:
+  html_document:
+    toc: true
+    toc_depth: 5
+    toc_float:
+      collapsed: false
+      smooth_scroll: true
+editor_options:
+  chunk_output_type: console
+---
+
+
+# Input Data & Configuration
+
+## Libraries
+```{r libs, eval = TRUE, echo = TRUE, results = "show", warning = FALSE, error = TRUE, message = FALSE}
+date()
+rm(list=ls())
+library(tidyverse)
+```
+
+## Compile TOPS data from multiple years
+```{r topsdata, eval = TRUE, echo = TRUE, results = "show", warning = FALSE, error = TRUE, message = FALSE}
+## add data from WiscTransPortal Crash Data Retrieval Facility ----
+## query:  SELECT * 
+## FROM DTCRPRD.SUMMARY_COMBINED C 
+## WHERE C.CRSHDATE BETWEEN TO_DATE('2022-JAN','YYYY-MM') AND 
+## LAST_DAY(TO_DATE('2022-DEC','YYYY-MM')) AND 
+## (C.BIKEFLAG = 'Y' OR C.PEDFLAG = 'Y') 
+## ORDER BY C.DOCTNMBR
+
+## Load TOPS data ----
+## load TOPS data for the whole state (crashes involving bikes and pedestrians),
+TOPS_data <- as.list(NULL)
+for (file in list.files(path = "data/TOPS/", pattern = "crash-data-download")) {
+  message(paste("importing data from file: ", file))
+  year <- substr(file, 21, 24)
+  csv_run <- read_csv(file = paste0("data/TOPS/",file), col_types = cols(.default = "c"))
+  csv_run["retreive_date"] <- file.info(file = paste0("data/TOPS/",file))$mtime
+  TOPS_data[[file]] <- csv_run
+}
+rm(csv_run, file, year)
+TOPS_data <- bind_rows(TOPS_data)
+```
+
+## Clean up data
+```{r cleandata, eval = TRUE, echo = TRUE, results = "show", warning = FALSE, error = TRUE, message = FALSE}
+TOPS_data <- TOPS_data %>% 
+  mutate(date = ymd(CRSHDATE), 
+         age1 = as.double(AGE1),
+         age2 = as.double(AGE2),
+         latitude  = as.double(LATDECDG),
+         longitude = as.double(LONDECDG)) %>% 
+  mutate(month = month(date, label = TRUE),
+         year = as.factor(year(date)))
+
+retrieve_date <- max(TOPS_data %>% filter(year %in% max(year(TOPS_data$date), na.rm = TRUE)) %>% pull(retreive_date))
+```
+
+## Add injury severity index and assign bike/ped roles
+```{r injuryseverity, eval = TRUE, echo = TRUE, results = "show", warning = FALSE, error = TRUE, message = FALSE}
+# Injury Severity Index and Color -------------------------------------------
+# injury severity index
+injury_severity <- data.frame(InjSevName = c("Injury severity unknown", "No apparent injury", "Possible Injury", "Suspected Minor Injury","Suspected Serious Injury","Fatality"), 
+                              code = c(NA, "O", "C", "B", "A", "K"),
+                              color = c("grey", "#fafa6e", "#edc346", "#d88d2d", "#bd5721", "#9b1c1c"))
+
+#injury_severity_pal <- colorFactor(palette = injury_severity$color, levels = injury_severity$InjSevName)
+
+TOPS_data <- left_join(TOPS_data, injury_severity %>% select(InjSevName, code), join_by(INJSVR1 == code)) %>% 
+  mutate(InjSevName = factor(InjSevName, levels = injury_severity$InjSevName)) %>%
+  rename(InjSevName1 = InjSevName)
+TOPS_data <- left_join(TOPS_data, injury_severity %>% select(InjSevName, code), join_by(INJSVR2 == code)) %>% 
+  mutate(InjSevName = factor(InjSevName, levels = injury_severity$InjSevName)) %>%
+  rename(InjSevName2 = InjSevName)
+# add bike or pedestrian roles ----
+
+bike_roles <- c("BIKE", "O BIKE")
+ped_roles <- c("PED", "O PED", "PED NO")
+vuln_roles <- c(bike_roles, ped_roles)
+
+TOPS_data <- TOPS_data %>% mutate(ped_inj = ifelse(ROLE1 %in% vuln_roles, 
+                                                   INJSVR1, 
+                                                   ifelse(ROLE2 %in% vuln_roles, 
+                                                          INJSVR2,
+                                                          NA)))
+
+TOPS_data <- left_join(TOPS_data, injury_severity %>% select(InjSevName, code), join_by(ped_inj == code)) %>% 
+  mutate(InjSevName = factor(InjSevName, levels = injury_severity$InjSevName)) %>%
+  rename(ped_inj_name = InjSevName)
+
+# bike or ped
+TOPS_data <- TOPS_data %>% mutate(vulnerable_role = ifelse(ROLE1 %in% bike_roles | ROLE2 %in% bike_roles, 
+                                                           "Bicyclist", 
+                                                           ifelse(ROLE1 %in% ped_roles | ROLE2 %in% ped_roles, 
+                                                                  "Pedestrian",
+                                                                  NA)))
+```
+
+## Save resulting data table as an Rda file for use in other documents
+```{r savecleaneddata, eval = TRUE, echo = TRUE, results = "show", warning = FALSE, error = TRUE, message = FALSE}
+save(TOPS_data, file = "data/TOPS/TOPS_data.Rda")
+save(vuln_roles, file = "data/TOPS/vuln_roles.Rda")
+save(retrieve_date, file = "data/TOPS/retrieve_date.Rda")
+save(injury_severity, file = "data/TOPS/injury_severity.Rda")
+```

R/schoolmaps_PDFs.Rmd

@@ -0,0 +1,441 @@
+---
+title: "School Maps PDFs"
+output:
+  html_document:
+    toc: true
+    toc_depth: 5
+    toc_float:
+      collapsed: false
+      smooth_scroll: true
+editor_options:
+  chunk_output_type: console
+---
+
+
+# Input Data & Configuration
+
+## Libraries
+```{r libs, eval = TRUE, echo = TRUE, results = "show", warning = FALSE, error = TRUE, message = FALSE}
+date()
+rm(list=ls())
+library(tidyverse)
+library(ggmap)
+library(sf)
+library(osrm)
+library(smoothr)
+library(ggnewscale)
+library(RColorBrewer)
+library(magick)
+library(rsvg)
+library(parallel)
+```
+
+## Load TOPS data
+```{r cleandata, eval = TRUE, echo = TRUE, results = "show", warning = FALSE, error = TRUE, message = FALSE}
+load(file = "data/TOPS/TOPS_data.Rda")
+load(file = "data/TOPS/vuln_roles.Rda")
+load(file = "data/TOPS/retrieve_date.Rda")
+load(file = "data/TOPS/injury_severity.Rda")
+```
+
+## Load school data
+```{r schooldata, eval = TRUE, echo = TRUE, results = "show", warning = FALSE, error = TRUE, message = FALSE}
+## add school enrollment data
+enrollment <- read_csv(file = "data/Schools/Enrollement_2022-2023/enrollment_by_gradelevel_certified_2022-23.csv",
+                       col_types = "ccccccccccccciid")
+enrollment_wide <- 
+  enrollment %>% 
+  mutate(district_school = paste0(DISTRICT_CODE, SCHOOL_CODE),
+         variable_name = paste0(GROUP_BY, "__", GROUP_BY_VALUE)) %>%
+  mutate(variable_name = str_replace_all(variable_name, "[ ]", "_")) %>%
+  pivot_wider(id_cols = c(district_school, GRADE_LEVEL, SCHOOL_NAME, DISTRICT_NAME, GRADE_GROUP, CHARTER_IND), names_from = variable_name, values_from = PERCENT_OF_GROUP) %>%
+  group_by(district_school, SCHOOL_NAME, DISTRICT_NAME, GRADE_GROUP, CHARTER_IND) %>%
+  summarise_at(vars("Disability__Autism":"Migrant_Status__[Data_Suppressed]"), mean, na.rm = TRUE)
+
+district_info <- data.frame(name = c("Madison Metropolitan", "Milwaukee"),
+                            code = c("3269","3619"),
+                            walk_boundary_hs = c(1.5, 2),
+                            walk_boundary_ms = c(1.5, 2),
+                            walk_boundary_es = c(1.5, 1))
+
+## load school locations
+WI_schools <- st_read(dsn = "data/Schools/Wisconsin_Public_Schools_-5986231931870160084.gpkg")
+
+WI_schools <- left_join(WI_schools %>% mutate(district_school = paste0(SDID, SCH_CODE)), 
+                        enrollment_wide, 
+                        join_by(district_school))
+```
+
+
+## Load bike LTS networks
+```{r bikeLTS, eval = TRUE, echo = TRUE, results = "show", warning = FALSE, error = TRUE, message = FALSE}
+bike_lts <- as.list(NULL)
+for(file in list.files("data/bike_lts")) {
+  county <- str_sub(file, 10, -9)
+  lts_run <- st_read(paste0("data/bike_lts/", file))
+  lts_run[["lts"]] <- as.factor(lts_run$LTS_F)
+  bike_lts[[county]] <- lts_run
+}
+bike_lts_scale <- data.frame(code = c(1, 2, 3, 4, 9),
+                             color = c("#1a9641",
+                                       "#a6d96a",
+                                       "#fdae61",
+                                       "#d7191c",
+                                       "#d7191c"))
+
+```
+
+## Load API keys from StadiaMaps and the census
+```{r APIkeys, eval = TRUE, echo = TRUE, results = "show", warning = FALSE, error = TRUE, message = FALSE}
+# register stadia API key ----
+register_stadiamaps(key = substr(read_file(file = "api_keys/stadia_api_key"), 1, 36))
+#options(ggmap.file_drawer = "basemaps")
+# dir.create(file_drawer(), recursive = TRUE, showWarnings = FALSE)
+# saveRDS(list(), file_drawer("index.rds"))
+#readRDS(file_drawer("index.rds"))
+#file_drawer("index.rds")
+
+# load census api key ----
+#census_api_key(key = substr(read_file(file = "api_keys/census_api_key"), 1, 40))
+```
+
+## Load logos
+```{r logos, eval = TRUE, echo = TRUE, results = "show", warning = FALSE, error = TRUE, message = FALSE}
+logo <- image_read(path = "icons/BFW_Logo_180_x_200_transparent_background.png")
+school_symbol <- image_read_svg(path = "icons/school_FILL0_wght400_GRAD0_opsz24.svg")
+```
+
+## Set parameters of run
+```{r runparameters, eval = TRUE, echo = TRUE, results = "show", warning = FALSE, error = TRUE, message = FALSE}
+
+run_parameters <- read_csv(file = "parameters/run_parameters.csv")
+# set which counties to generate figures for
+county_focus <- run_parameters$county_focus
+if(str_to_lower(county_focus) == "all") {
+  county_focus <- str_to_upper(unique(WI_schools %>% pull(CTY_DIST)))
+}
+
+# set which school types to generate figures for
+school_type_focus <- run_parameters$school_type_focus
+if(str_to_lower(school_type_focus) == "all") {
+  school_type_focus <- unique(WI_schools %>% filter(CTY_DIST %in% str_to_title(county_focus)) %>% pull(SCHOOLTYPE))
+}
+
+# set which school types to generate figures for
+district_focus <- run_parameters$district_focus
+if(str_to_lower(district_focus) == "all") {
+  district_focus <- unique(WI_schools %>%   filter(CTY_DIST %in% str_to_title(county_focus),  SCHOOLTYPE %in% school_type_focus, !is.na(DISTRICT_NAME)) %>%  pull(DISTRICT_NAME))
+}
+
+school_number <- length(unique(WI_schools %>% filter(CTY_DIST %in% str_to_title(county_focus),  
+                                              SCHOOLTYPE %in% school_type_focus, 
+                                              DISTRICT_NAME %in% district_focus) %>%  
+                          pull(district_school)))
+```
+
+## generate county charts
+```{r countyfigures, eval = TRUE, echo = TRUE, results = "show", warning = FALSE, error = TRUE, message = FALSE}
+
+for(county in county_focus) {
+  message(county)
+  TOPS_data %>% 
+    filter(CNTYNAME %in% county) %>% 
+    filter(ROLE1 %in% vuln_roles & age1 < 18 | ROLE2 %in% vuln_roles & age2 < 18) %>% 
+    group_by(year) %>% summarise(count = n_distinct(DOCTNMBR)) %>%
+    ggplot() +
+    geom_col(aes(x = year,
+                 y = count),
+             fill = "darkred") +
+    scale_y_continuous(expand = expansion(mult = c(0,0.07))) +
+    labs(title = paste0("Pedestrians/bicyclists under 18 years old hit by cars in ",
+                        str_to_title(county), 
+                        " County"),
+         x = "Year",
+         y = "Number of crashes",
+         caption = paste0("crash data from UW TOPS lab - retrieved ",
+                          strftime(retrieve_date, format = "%m/%Y"),
+                          " per direction of the WisDOT Bureau of Transportation Safety",
+                          "\nbasemap from StadiaMaps and OpenStreetMap Contributers"))
+  ggsave(file = paste0("figures/school_maps/Crash Maps/", 
+                       str_to_title(county), 
+                       " County/_",
+                       str_to_title(county), 
+                       " County_year.pdf"), 
+         title = paste0(county, " County Youth Pedestrian/Bike crashes"),
+         device = pdf,
+         height = 8.5,
+         width = 11,
+         units = "in",
+         create.dir = TRUE)
+  
+  # #  generate map for county
+  # county_data <- WI_schools %>% filter(CTY_DIST %in% str_to_title(county))
+  # bbox <- st_bbox(st_transform(st_buffer(county_data %>% pull(SHAPE), dist = 4000), crs = 4326))
+  # bbox <- c(left = as.double(bbox[1]), bottom = as.double(bbox[2]), right = as.double(bbox[3]), top = as.double(bbox[4]))
+  # 
+  # #get basemap
+  # basemap <- get_stadiamap(bbox = bbox, zoom = 12, maptype = "stamen_toner_lite")
+  # 
+  # # generate map
+  # ggmap(basemap) +
+  #   labs(title = paste0("Crashes between cars and youth (under 18) pedestrians/bicyclists in ", 
+  #                       str_to_title(county),
+  #                       " County"),
+  #        subtitle = paste0(min(year(TOPS_data$date), na.rm = TRUE), " - ", max(year(TOPS_data$date), na.rm = TRUE)),
+  #        caption = "data from Wisconsin DOT, UW TOPS Laboratory, Wisconsin DPI, and OpenStreetMap",
+  #        x = NULL,
+  #        y = NULL) +
+  #   theme(axis.text=element_blank(),
+  #         axis.ticks=element_blank()) +
+  #   
+  #   # add crash heatmap
+  #   # stat_density_2d(data = TOPS_data %>% 
+  #   #                   filter(ROLE1 %in% c("BIKE", "PED") & age1 < 18 | ROLE2 %in% c("BIKE", "PED") & age2 < 18),
+  #   #                 inherit.aes = FALSE,
+  #   #                 geom = "polygon", 
+  #   #                 aes(fill = after_stat(level),
+  #   #                     x = longitude,
+  #   #                     y = latitude),
+  #   #                 alpha = 0.2,
+  #   #                 color = NA,
+  #   #                 na.rm = TRUE,
+  #   #                 bins = 12,
+  #   #                 n = 300) +
+  #   # scale_fill_distiller(type = "div", palette = "YlOrRd", guide = "none", direction = 1) +
+  #   
+  #   # add crashes
+  #   new_scale_color() +
+  #   geom_point(data = TOPS_data %>% 
+  #                filter(ROLE1 %in% c("BIKE", "PED") & age1 < 18 | ROLE2 %in% c("BIKE", "PED") & age2 < 18) %>%
+  #                filter(longitude >= as.double(bbox[1]), 
+  #                       latitude >= as.double(bbox[2]), 
+  #                       longitude <= as.double(bbox[3]), 
+  #                       latitude <= as.double(bbox[4])), 
+  #              aes(x = longitude,
+  #                  y = latitude,
+  #                  color = InjSevName),
+  #              shape = 18,
+  #              size = 1) +
+  #   scale_color_manual(values = injury_severity$color, name = "Crash Severity")
+  #   
+  #   # add school location
+  #   # new_scale_color() +
+  #   # geom_sf(data = st_transform(WI_schools, crs = 4326),
+  #   #         inherit.aes = FALSE,
+  #   #         aes(color = "school"),
+  #   #         size = 2,
+  #   #         shape = 0) +
+  #   # scale_color_manual(values = "black", name = NULL)
+  # 
+  # ggsave(file = paste0("figures/school_maps/Crash Maps/", 
+  #                                      str_to_title(county), " County/_", 
+  #                                      str_to_title(county), " County.pdf"), 
+  #        title = paste0(str_to_title(county), " County Youth Pedestrian/Bike crashes"),
+  #        device = pdf,
+  #        height = 8.5,
+  #        width = 11,
+  #        units = "in",
+  #        create.dir = TRUE)
+}
+```
+
+# Generate school maps
+
+## Set OpenStreetMap Routing Machine parameters
+```{r OSRM, eval = TRUE, echo = TRUE, results = "show", warning = FALSE, error = TRUE, message = FALSE}
+
+options(osrm.server = "http://127.0.0.1:5000/")
+options(osrm.profile = "walk")
+```
+
+## Function to generate maps
+```{r schoolmaps, eval = TRUE, echo = TRUE, results = "show", warning = FALSE, error = TRUE, message = FALSE}
+generate_school_maps <- function(district) {
+  
+  message(paste("***", district, "School District |"))
+  options(ggmap.file_drawer = paste0("basemaps/districts/", district))
+  dir.create(file_drawer(), recursive = TRUE, showWarnings = FALSE)
+  saveRDS(list(), file_drawer("index.rds"))
+  readRDS(file_drawer("index.rds"))
+  file_drawer("index.rds")
+  for(school in WI_schools %>%
+      filter(DISTRICT_NAME %in% district,
+             SCHOOLTYPE %in% school_type_focus,
+             !st_is_empty(SHAPE)) %>%
+      pull(district_school)) {
+    school_data <- WI_schools %>% filter(district_school == school)
+    i <- i + 1
+    message(paste(school_data %>% pull(SCHOOL_NAME), "-", district, "School District", "-", school_data %>% pull(CTY_DIST), "County |", i, "/", school_number, "|", round(i/school_number*100, 2), "%"))
+
+    #find walk boundary distance for school
+    if(length(which(district_info$name == district)) > 0) {
+      ifelse((school_data %>% pull(SCHOOLTYPE)) %in% "High School",
+             walk_boundary_mi <- district_info$walk_boundary_hs[district_info$name == district],
+             ifelse((school_data %>% pull(SCHOOLTYPE)) %in% c("Junior High School", "Middle School"),
+                    walk_boundary_mi <- district_info$walk_boundary_ms[district_info$name == district],
+                    ifelse((school_data %>% pull(SCHOOLTYPE)) %in% c("Combined Elementary/Secondary School", "Elementary School"),
+                           walk_boundary_mi <- district_info$walk_boundary_es[district_info$name == district],
+                           walk_boundary <- 2)))
+    } else {
+      walk_boundary_mi <- 2
+    }
+    walk_boundary_m <- walk_boundary_mi * 1609
+    
+    walk_boundary_poly <- fill_holes(st_make_valid(osrmIsodistance(
+      loc = st_transform(school_data %>% pull(SHAPE), crs = 4326),
+      breaks = c(walk_boundary_m),
+      res = 80)
+    ), units::set_units(1, km^2))
+    
+    # create bounding box from school, 5km away.
+    bbox <- st_bbox(st_transform(st_buffer(school_data %>% pull(SHAPE), dist = walk_boundary_m + 500), crs = 4326))
+    bbox <- c(left = as.double(bbox[1]), 
+              bottom = as.double(bbox[2]), 
+              right = as.double(bbox[3]), 
+              top = as.double(bbox[4]))
+    
+    #get basemap
+    basemap <- get_stadiamap(bbox = bbox, zoom = 15, maptype = "stamen_toner_lite")
+    
+    # generate map
+    ggmap(basemap) +
+      labs(title = paste0(
+        "Crashes between cars and youth (<18) pedestrians/bicyclists near ",
+#        "Crashes between cars and all pedestrians/bicyclists near ",
+        school_data %>% pull(SCHOOL_NAME),
+        " School"),
+           subtitle = paste0(school_data %>% pull(DISTRICT_NAME),
+                             " School District | ",
+                             min(year(TOPS_data$date), na.rm = TRUE), 
+                             " - ", 
+                             max(year(TOPS_data$date), na.rm = TRUE)),
+           caption = paste0("crash data from UW TOPS lab - retrieved ",
+                                   strftime(retrieve_date, format = "%m/%Y"),
+                                   " per direction of the WisDOT Bureau of Transportation Safety",
+                                   "\nbasemap from StadiaMaps and OpenStreetMap Contributers"),
+           x = NULL,
+           y = NULL) +
+      theme(axis.text=element_blank(),
+            axis.ticks=element_blank(),
+            plot.caption = element_text(color = "grey")) +
+      
+      ## add bike lts
+#      geom_sf(data = bike_lts[[county]],
+#             inherit.aes = FALSE,
+#             aes(color = lts)) +
+#      scale_color_manual(values = bike_lts_scale$color, name = "Bike Level of Traffic Stress") +
+      
+
+      # add walk boundary
+      new_scale_color() +
+      new_scale_fill() +
+      geom_sf(data = walk_boundary_poly,
+              inherit.aes = FALSE,
+              aes(color = paste0(walk_boundary_mi, " mile walking boundary")),
+              fill = NA,
+              linewidth = 1) +
+      scale_color_manual(values = "black", name = NULL) +
+      # add school location
+      # geom_sf(data = st_transform(school_data, crs = 4326), inherit.aes = FALSE) +
+      annotation_raster(school_symbol,
+                        # Position adjustments here using plot_box$max/min/range
+                        ymin = as.double((st_transform(school_data, crs = 4326) %>% pull(SHAPE))[[1]])[2] - 0.001,
+                        ymax = as.double((st_transform(school_data, crs = 4326) %>% pull(SHAPE))[[1]])[2] + 0.001,
+                        xmin = as.double((st_transform(school_data, crs = 4326) %>% pull(SHAPE))[[1]])[1] - 0.0015,
+                        xmax = as.double((st_transform(school_data, crs = 4326) %>% pull(SHAPE))[[1]])[1] + 0.0015) +
+      geom_sf_label(data = st_transform(school_data, crs = 4326),
+                    inherit.aes = FALSE,
+                    mapping = aes(label = paste(SCHOOL_NAME, "School")),
+                    nudge_y = 0.0015,
+                    label.size = 0.04,
+                    size = 2) +
+      annotation_raster(logo,
+                        # Position adjustments here using plot_box$max/min/range
+                        ymin = bbox['top'] - (bbox['top']-bbox['bottom']) * 0.16,
+                        ymax = bbox['top'],
+                        xmin = bbox['right'] + (bbox['right']-bbox['left']) * 0.05,
+                        xmax = bbox['right'] + (bbox['right']-bbox['left']) * 0.20) +
+      coord_sf(clip = "off") +
+      # add crash locations
+      new_scale_fill() +
+      geom_point(data = TOPS_data %>%
+                   filter(ROLE1 %in% c("BIKE", "PED") 
+                          & age1 < 18 
+                          | ROLE2 %in% c("BIKE", "PED") 
+                          & age2 < 18
+                          ) %>%
+                   filter(longitude >= as.double(bbox[1]),
+                          latitude >= as.double(bbox[2]),
+                          longitude <= as.double(bbox[3]),
+                          latitude <= as.double(bbox[4])) %>%
+                   arrange(ped_inj_name),
+                 aes(x = longitude,
+                     y = latitude,
+                     fill = ped_inj_name),
+                 shape = 23,
+                 size = 3) +
+      scale_fill_manual(values = setNames(injury_severity$color, injury_severity$InjSevName), name = "Crash Severity")
+        
+    ggsave(file = paste0("figures/school_maps/Crash Maps/",
+                         str_to_title(school_data %>% pull(CTY_DIST)), 
+                         " County/",
+                         school_data %>% pull(DISTRICT_NAME), 
+                         " School District/",
+                         str_replace_all(school_data %>% pull(SCHOOLTYPE), "/","-"), 
+                         "s/",
+                         str_replace_all(school_data %>% pull(SCHOOL_NAME), "/", "-"), 
+                        # " School_all.pdf"),
+                        " School.pdf"),
+           title = paste0(school_data %>% pull(SCHOOL), " Youth Pedestrian/Bike crashes"),
+           #title = paste0(school_data %>% pull(SCHOOL), " All Pedestrian/Bike crashes"),
+           device = pdf,
+           height = 8.5,
+           width = 11,
+           units = "in",
+           create.dir = TRUE)
+  }
+}
+```
+
+## Generate the school maps
+```{r generatemaps, eval = TRUE, echo = TRUE, results = "show", warning = FALSE, error = TRUE, message = FALSE}
+i <- 0
+if (run_parameters$parallel) {
+  mclapply(district_focus,
+           generate_school_maps,
+           mc.cores = 10,
+           mc.cleanup = TRUE,
+           mc.preschedule = TRUE,
+           mc.silent = FALSE)
+} else {
+  lapply(district_focus,
+         generate_school_maps)
+}
+
+
+# double check that all schools have a map ----
+double_check <- list(NULL)
+for(school in WI_schools$district_school) {
+  school_data <- WI_schools %>% filter(district_school %in% school)
+  school_check <- data.frame(district_school = c(school),
+                             exists = c(file.exists(paste0("figures/school_maps/Crash Maps/",
+                                                           str_to_title(school_data %>% pull(CTY_DIST)), 
+                                                           " County/",
+                                                           school_data %>% pull(DISTRICT_NAME), 
+                                                           " School District/",
+                                                           str_replace_all(school_data %>% pull(SCHOOLTYPE), "/","-"), 
+                                                           "s/",
+                                                           str_replace_all(school_data %>% pull(SCHOOL_NAME), "/", "-"), 
+                                                           #" School.pdf"))))
+                                                           " School.pdf"))))
+  double_check[[school]] <- school_check
+}
+double_check <- bind_rows(double_check)
+unique(WI_schools %>% 
+         filter(district_school %in% (double_check %>% 
+                                        filter(exists == FALSE) %>% 
+                                        pull(district_school)),
+                !st_is_empty(SHAPE)) %>% 
+         pull(DISTRICT_NAME))
+write_csv(double_check, file = "parameters/double_check.csv")
+```

api_keys/.gitignore

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+# Ignore everything in this directory
+*
+# Except this file
+!.gitignore

basemaps/.gitignore

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+# Ignore everything in this directory
+*
+# Except this file
+!.gitignore

data/.gitignore

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+# Ignore everything in this directory
+*
+# Except this file
+!.gitignore

data_summaries/.gitignore

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+# Ignore everything in this directory
+*
+# Except this file
+!.gitignore

docker/.gitignore

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+# Ignore everything in this directory
+*
+# Except this file
+!.gitignore
+!docker-compose.yml
+!data-raw/
+!data-foot/

figures/.gitignore

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+# Ignore everything in this directory
+*
+# Except this file
+!.gitignore

html/.gitignore

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+# Ignore everything in this directory
+*
+# Except this file
+!.gitignore

parameters/.gitignore

@@ -0,0 +1,4 @@
+# Ignore everything in this directory
+*
+# Except this file
+!.gitignore

wisconsin_crashes.Rproj

@@ -1,4 +1,5 @@
 Version: 1.0
+ProjectId: 0da73295-ef24-454f-bd60-31bef147eca9
 
 RestoreWorkspace: Default
 SaveWorkspace: Default
@@ -11,3 +12,5 @@ Encoding: UTF-8
 
 RnwWeave: Sweave
 LaTeX: pdfLaTeX
+
+BuildType: Makefile