cycling_route_analysis_brouter.Rmd

@@ -71,16 +71,15 @@ bike_lts_scale <- data.frame(code = c(1, 2, 3, 4, 9),
 ## Open Source Routing Machine (OSRM)
 
 ```{r osrm, eval = TRUE, echo = TRUE, results = "show", warning = FALSE, error = TRUE, message = FALSE}
-# Set url and profile of OSRM server
 options(osrm.server = "http://127.0.0.1:5001/")
 options(osrm.profile = "bike")
 ```
 
 ## Brouter options
 ```{r brouter, eval = TRUE, echo = TRUE, results = "show", warning = FALSE, error = TRUE, message = FALSE}
-# Set url and profile of brouter server
-brouter_url <- "http://127.0.0.1:17777/brouter"
-brouter_profile <- "trekking"
+# Prepare the URL query
+url <- "http://127.0.0.1:17777/brouter"
+profile <- "trekking"  # choose appropriate profile
 ```
 
 ## Stadia Maps API Key
@@ -137,18 +136,16 @@ routes <- list(NULL)
 school_focus_location <- WI_schools %>% filter(NCES_CODE %in% school_focus$NCES_CODE) %>% select(LAT, LON)
 for(i in addresses_near %>% arrange(number) %>% pull(number)) {
   query <- paste0(
-    brouter_url, 
+  url, 
   "?lonlats=",
   (addresses_near %>% filter(number == i) %>% pull(point) %>% str_split(., ","))[[1]][1], ",", 
   (addresses_near %>% filter(number == i) %>% pull(point) %>% str_split(., ","))[[1]][2], "|", 
   school_focus_location$LON, ",", school_focus_location$LAT,
-    "&profile=", brouter_profile,
+  "&profile=", profile,
   "&alternativeidx=0&format=geojson"
 )
   response <- GET(query)
-  route_run <- st_read(content <- content(response, as = "text"), quiet = TRUE)
-  route_run[["student_number"]] <- i
-  routes[[i]] <- route_run
+ routes[[i]] <- st_read(content <- content(response, as = "text"), quiet = TRUE)
  
  
   message(paste0("done - ", i, " of ", max(addresses_near$number)))