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included more bike and ped roles for school maps, fixed colors

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This commit is contained in:
Ben Varick 2024-04-09 09:17:26 -05:00
parent ff64e72a65
commit 1116722a98
Signed by: ben
SSH Key Fingerprint: SHA256:758jG979jvr5HnQJl1AQ/NYTyzXRgnuoVM/yCR024sE
2 changed files with 42 additions and 12 deletions
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2
scripts/school_maps.R
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@ -134,7 +134,7 @@ for(county in county_focus) {
message(county) message(county)
TOPS_data %>% TOPS_data %>%
filter(CNTYNAME %in% county) %>% filter(CNTYNAME %in% county) %>%
filter(ROLE1 %in% c("BIKE", "PED") & age1 < 18 | ROLE2 %in% c("BIKE", "PED") & age2 < 18) %>% filter(ROLE1 %in% vuln_roles & age1 < 18 | ROLE2 %in% vuln_roles & age2 < 18) %>%
group_by(year) %>% summarise(count = n_distinct(DOCTNMBR)) %>% group_by(year) %>% summarise(count = n_distinct(DOCTNMBR)) %>%
ggplot() + ggplot() +
geom_col(aes(x = year, geom_col(aes(x = year,

52
scripts/school_maps_parallel.R
View File

@ -48,11 +48,41 @@ counties <- data.frame(name = c("Dane", "Milwaukee"),
COUNTY = c("DANE", "MILWAUKEE")) COUNTY = c("DANE", "MILWAUKEE"))
# Injury Severy Index and Color ------------------------------------------- # Injury Severy Index and Color -------------------------------------------
# injury severity index # injury severity index
injury_severity <- data.frame(InjSevName = c("No apparent injury", "Possible Injury", "Suspected Minor Injury","Suspected Serious Injury","Fatality"), injury_severity <- data.frame(InjSevName = c("Injury severity unknown", "No apparent injury", "Possible Injury", "Suspected Minor Injury","Suspected Serious Injury","Fatality"),
code = c("O", "C", "B", "A", "K"), code = c(NA, "O", "C", "B", "A", "K"),
color = c("#fafa6e", "#edc346", "#d88d2d", "#bd5721", "#9b1c1c")) color = c("grey", "#fafa6e", "#edc346", "#d88d2d", "#bd5721", "#9b1c1c"))
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$InjSevName)) %>%
rename(ped_inj_name = InjSevName)
# bike or ped
TOPS_data <- TOPS_data %>% mutate(vulnerable_role = ifelse(ROLE1 %in% bike_roles | ROLE2 %in% bike_roles,
"Bicyclist",
ifelse(ROLE1 %in% ped_roles | ROLE2 %in% ped_roles,
"Pedestrian",
NA)))
TOPS_data <- left_join(TOPS_data, injury_severity %>% select(InjSevName, code), join_by(INJSVR == code)) %>% mutate(InjSevName = factor(InjSevName, levels = injury_severity$InjSevName))
# ---- add additional data # ---- add additional data
@ -97,7 +127,7 @@ WI_schools <- left_join(WI_schools %>% mutate(district_school = paste0(SDID, SCH
# "#d7191c")) # "#d7191c"))
# register stadia API key ---- # register stadia API key ----
register_stadiamaps(key = substr(read_file(file = "api_keys/stadia_api_key"), 1, 36)) register_stadiamaps(key = read_file(file = "api_keys/stadia_api_key"))
#options(ggmap.file_drawer = "data/basemaps") #options(ggmap.file_drawer = "data/basemaps")
# dir.create(file_drawer(), recursive = TRUE, showWarnings = FALSE) # dir.create(file_drawer(), recursive = TRUE, showWarnings = FALSE)
# saveRDS(list(), file_drawer("index.rds")) # saveRDS(list(), file_drawer("index.rds"))
@ -140,7 +170,7 @@ for(county in county_focus) {
message(county) message(county)
TOPS_data %>% TOPS_data %>%
filter(CNTYNAME %in% county) %>% filter(CNTYNAME %in% county) %>%
filter(ROLE1 %in% c("BIKE", "PED") & age1 < 18 | ROLE2 %in% c("BIKE", "PED") & age2 < 18) %>% filter(ROLE1 %in% vuln_roles & age1 < 18 | ROLE2 %in% vuln_roles & age2 < 18) %>%
group_by(year) %>% summarise(count = n_distinct(DOCTNMBR)) %>% group_by(year) %>% summarise(count = n_distinct(DOCTNMBR)) %>%
ggplot() + ggplot() +
geom_col(aes(x = year, geom_col(aes(x = year,
@ -320,9 +350,9 @@ generate_school_maps <- function(district) {
# add crash locations # add crash locations
new_scale_fill() + new_scale_fill() +
geom_point(data = TOPS_data %>% geom_point(data = TOPS_data %>%
filter(ROLE1 %in% c("BIKE", "PED") filter(ROLE1 %in% vuln_roles
& age1 < 18 & age1 < 18
| ROLE2 %in% c("BIKE", "PED") | ROLE2 %in% vuln_roles
& age2 < 18 & age2 < 18
) %>% ) %>%
filter(longitude >= as.double(bbox[1]), filter(longitude >= as.double(bbox[1]),
@ -331,10 +361,10 @@ generate_school_maps <- function(district) {
latitude <= as.double(bbox[4])), latitude <= as.double(bbox[4])),
aes(x = longitude, aes(x = longitude,
y = latitude, y = latitude,
fill = InjSevName), fill = ped_inj_name),
shape = 23, shape = 23,
size = 3) + size = 3) +
scale_fill_manual(values = injury_severity$color, name = "Crash Severity") + scale_fill_manual(values = setNames(as.character(injury_severity$color), injury_severity$InjSevName), name = "Crash Severity") +
# add walk boundary # add walk boundary
new_scale_color() + new_scale_color() +
new_scale_fill() + new_scale_fill() +
@ -389,7 +419,7 @@ generate_school_maps <- function(district) {
## generate maps in parallel ---- ## generate maps in parallel ----
mclapply(district_focus, mclapply(district_focus,
generate_school_maps, generate_school_maps,
mc.cores = 12, mc.cores = 10,
mc.cleanup = TRUE, mc.cleanup = TRUE,
mc.preschedule = TRUE, mc.preschedule = TRUE,
mc.silent = FALSE) mc.silent = FALSE)