Exeter example

.Rbuildignore

@@ -10,3 +10,4 @@
 ^README\.Rmd$
 ^ab_scenario\.json$
 ^cran-comments\.md$
+^CRAN-RELEASE$

CRAN-RELEASE

@@ -0,0 +1,2 @@
+This package was submitted to CRAN on 2021-08-18.
+Once it is accepted, delete this file and tag the release (commit 6543bdc).

DESCRIPTION

@@ -1,7 +1,7 @@
 Type: Package
 Package: abstr
 Title: R Interface to the A/B Street Transport System Simulation Software
-Version: 0.3.0
+Version: 0.3.0.9000
 Authors@R: 
     c(person(given = "Nathanael",
              family = "Sheehan",

NEWS.md

@@ -1,3 +1,5 @@
+# abstr (development version)
+
 # abstr 0.3.0
 
 * New Vignette to reproduce the datasets based on the Montlake area in Seattle

data-raw/exeter.r

@@ -0,0 +1,178 @@
+####
+####
+#### AIM: Use PCT data to create scenario of change where commuting cycling levels increase and car journeys decrease which can be imported
+####      into A/B Street city simulation software. This method should be fully reproducible for all other pct_regions.
+####
+####
+
+####  LIBRARYS ####
+library(pct)
+library(sf)
+library(tidyverse)
+library(abstr)
+
+# for plotting
+# library(tmap)
+# library (mapview)
+
+####    READ DATA ####
+devon_zones = pct::get_pct_zones(region = "devon", geography = "msoa") # get zone data
+exeter_zones = devon_zones %>% filter(lad_name == "Exeter") %>% select(geo_code) # filter for exeter
+
+exeter_commute_od = pct::get_pct_lines(region = "devon", geography = "msoa") %>% # get commute od data
+  filter(lad_name1 == "Exeter" &
+           lad_name2 == "Exeter") # filter for exeter
+
+
+####    CLEAN DATA , CALCULATE EUCLIDEAN DISTANCE  & GENERATE SCENARIOS OF CHANGE ####
+exeter_commute_od = exeter_commute_od %>%
+  mutate(cycle_base = bicycle) %>%
+  mutate(walk_base = foot) %>%
+  mutate(transit_base = bus + train_tube) %>% # bunch of renaming -_-
+  mutate(drive_base = car_driver + car_passenger + motorbike + taxi_other) %>%
+  mutate(all_base = all) %>%
+  mutate(
+    # create new columns
+    pcycle_godutch_uptake = pct::uptake_pct_godutch_2020(distance = rf_dist_km, gradient = rf_avslope_perc),
+    cycle_godutch_additional = pcycle_godutch_uptake * drive_base,
+    cycle_godutch = cycle_base + cycle_godutch_additional,
+    pcycle_godutch = cycle_godutch / all_base,
+    drive__godutch = drive_base - cycle_godutch_additional,
+    across(c(drive__godutch, cycle_godutch), round, 0),
+    all_go_dutch = drive__godutch + cycle_godutch + transit_base + walk_base
+  ) %>%
+  select(
+    # select variables for new df
+    geo_code1,
+    geo_code2,
+    cycle_base,
+    drive_base,
+    walk_base,
+    transit_base,
+    all_base,
+    all_go_dutch,
+    drive__godutch,
+    cycle_godutch,
+    cycle_godutch_additional,
+    pcycle_godutch
+  )
+
+identical(exeter_commute_od$all_base, exeter_commute_od$all_go_dutch) # sanity check: make sure total remains the same (not a dynamic model where population change is factored in)
+
+####    DOWNLOAD OSM BUILDING DATA ####
+osm_polygons = osmextract::oe_read(
+  "https://download.geofabrik.de/europe/great-britain/england/devon-latest.osm.pbf",
+  # download osm buildings for region using geofabrik
+  layer = "multipolygons"
+)
+
+building_types = c(
+  "yes",
+  "house",
+  "detached",
+  "residential",
+  "apartments",
+  "commercial",
+  "retail",
+  "school",
+  "industrial",
+  "semidetached_house",
+  "church",
+  "hangar",
+  "mobile_home",
+  "warehouse",
+  "office",
+  "college",
+  "university",
+  "public",
+  "garages",
+  "cabin",
+  "hospital",
+  "dormitory",
+  "hotel",
+  "service",
+  "parking",
+  "manufactured",
+  "civic",
+  "farm",
+  "manufacturing",
+  "floating_home",
+  "government",
+  "bungalow",
+  "transportation",
+  "motel",
+  "manufacture",
+  "kindergarten",
+  "house_boat",
+  "sports_centre"
+)
+osm_buildings  = osm_polygons %>%
+  dplyr::filter(building %in% building_types) %>%
+  dplyr::select(osm_way_id, name, building)
+
+osm_buildings_valid = osm_buildings[sf::st_is_valid(osm_buildings), ]
+
+exeter_osm_buildings_all = osm_buildings_valid[exeter_zones, ]
+
+#mapview(exeter_osm_buildings_all)
+
+# Filter down large objects for package -----------------------------------
+exeter_osm_buildings_all_joined = exeter_osm_buildings_all %>%
+  sf::st_join(exeter_zones)
+
+set.seed(2021)
+exeter_osm_buildings_sample = exeter_osm_buildings_all_joined %>%
+  dplyr::filter(!is.na(osm_way_id))
+
+exeter_osm_buildings_tbl = exeter_osm_buildings_all %>%
+  dplyr::filter(osm_way_id %in% exeter_osm_buildings_sample$osm_way_id)
+
+
+####  LOGIC GATE ####
+# Logic gate for go_dutch scenario of change, where cycling levels increase to a proportion reflecting the Netherlands.
+#Switch to FALSE if you want census commuting OD
+go_dutch = TRUE
+if (go_dutch == TRUE) {
+  exeter_od = exeter_commute_od %>%
+    mutate(All = all_go_dutch) %>%
+    mutate(Bike = cycle_godutch) %>%
+    mutate(Transit = transit_base) %>%
+    mutate(Drive = drive_base) %>%
+    mutate(Walk = walk_base) %>%
+    select(geo_code1, geo_code2, All, Bike, Transit, Drive, Walk,geometry)
+} else {
+  exeter_od = exeter_commute_od %>%
+    mutate(All = all_base) %>%
+    mutate(Bike = cycle_base) %>%
+    mutate(Drive = drive_base) %>%
+    mutate(Transit = transit_base) %>%
+    mutate(Walk = walk_base) %>%
+    select(geo_code1, geo_code2, All, Bike, Transit, Drive, Walk, geometry)
+}
+
+####  GENERATE A/B STREET SCENARIO ####
+output_sf = ab_scenario(
+  od = exeter_od,
+  zones = exeter_zones,
+  zones_d = NULL,
+  origin_buildings = exeter_osm_buildings_tbl,
+  destination_buildings = exeter_osm_buildings_tbl,
+  pop_var = 3,
+  time_fun = ab_time_normal,
+  output = "sf",
+  modes = c("Walk", "Bike", "Drive", "Transit")
+)
+
+# make map using tmap
+# tm_shape(output_sf) + tmap::tm_lines(col = "mode", lwd = .8, lwd.legeld.col = "black") +
+#   tm_shape(exeter_zones) + tmap::tm_borders(lwd = 1.2, col = "gray") +
+#   tm_text("geo_code", size = 0.6, col = "black") +
+#   tm_style("cobalt")
+
+#### SAVE JSON FILE ####
+output_json = ab_json(output_sf, time_fun = ab_time_normal, scenario_name = "Exeter Example")
+ab_save(output_json, f = "../../Desktop/exeter.json")
+
+#### COMMANDS FOR AB STREET
+# $ cargo run
+# $ cargo run --bin import_traffic -- --map=PATH/TO/MAP --input=/PATH/TO/JSON.json