.gitignore

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

Makefile

@@ -1,18 +0,0 @@
-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

@@ -1,108 +0,0 @@
----
-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

@@ -1,441 +0,0 @@
----
-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

crash_data.Rproj

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

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

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