Example costing_options? about valhallr HOT 6 CLOSED

library(tidyverse)
library(valhallr)
library(leaflet)

# set up start/stop points (university of ottawa and a sports arena)
ottawa_points <- valhallr::test_data() %>%
  filter(lat > 45, lon > -78)

# set up polygons (one blocking major artery, another blocking downtown major street)
poly1 <- tibble::tribble(~lat, ~lon,
                         45.406729, -75.703046,
                         45.402346, -75.700519,
                         45.407185, -75.686590,
                         45.410834, -75.692833)

poly2 <- tibble::tribble(~lat, ~lon,
                         45.424620, -75.696708,
                         45.419283, -75.709161,
                         45.416166, -75.701505,
                         45.420895, -75.692013)

# put them in a list to pass multiple at once
e_polys <- list(poly1, poly2)

########### route()
# no exclusion
route_0 <- route(from = ottawa_points[1,],
                to = ottawa_points[3,],
                hostname = "192.168.2.39")

# 1 polygon passed as tibble
route_1 <- route(from = ottawa_points[1,],
                to = ottawa_points[3,],
                hostname = "192.168.2.39",
                exclude_polygons = exclude_poly_small)

# 2 polygons passed as list
route_2 <- route(from = ottawa_points[1,],
                to = ottawa_points[3,],
                hostname = "192.168.2.39",
                exclude_polygons = e_polys)

# inspect results
map_trip(route_0)

map_trip(route_1) %>%
  addPolygons(data = exclude_poly_small, lat = ~lat, lng = ~lon)

map_trip(route_2) %>%
  addPolygons(data = exclude_poly_small, lat = ~lat, lng = ~lon) %>%
  addPolygons(data = poly_small_2, lat = ~lat, lng = ~lon)

########### Also testing with sources_to_targets

st_0 <- sources_to_targets(froms = ottawa_points[1,],
                   tos = ottawa_points[3,],
                   hostname = "192.168.2.39")

st_1 <- sources_to_targets(froms = ottawa_points[1,],
                                   tos = ottawa_points[3,],
                                   hostname = "192.168.2.39",
                                   exclude_polygons = poly1)

st_2 <- sources_to_targets(froms = ottawa_points[1,],
                                    tos = ottawa_points[3,],
                                    hostname = "192.168.2.39",
                                   exclude_polygons = e_polys)

####### Testing with od_table
# no polygons
od_0 <- od_table(froms = ottawa_points[1,],
         from_id_col = "name",
         tos = ottawa_points[3,],
         to_id_col= "name",
         hostname = "192.168.2.39")

# 1 polygon passed as tibble
od_1 <- od_table(froms = ottawa_points[1,],
         from_id_col = "name",
         tos = ottawa_points[3,],
         to_id_col= "name",
         exclude_polygons = poly1,
         hostname = "192.168.2.39")

# 2 polygons passed as list
od_2 <- od_table(froms = ottawa_points[1,],
         from_id_col = "name",
         tos = ottawa_points[3,],
         to_id_col= "name",
         exclude_polygons = e_polys,
         hostname = "192.168.2.39")

### Make summary table
results <- tibble(polygons = 0:2, 
                  route = c(route_0$summary$length, route_1$summary$length, route_2$summary$length),
                  od_matrix = c(od_0$distance, od_1$distance, od_2$distance),
                  sources_to_targets = c(st_0$distance, st_1$distance, st_2$distance)
)

inundation_dists <- sources_to_targets(froms = orig,
                                       tos = dest,
                                       minimum_reachability = 50,
                                       hostname = host,
                                       port = port,
                                       costing_options = list('avoid_polygons' = '[[[-122.443993,47.220645],[-122.443993,47.289334],[-122.318552,47.289334],[-122.318552,47.220645],[-122.443993,47.220645]]]'))