remove building_type and stop reading the residential permit shapefile

convert_osm/src/lib.rs

@@ -13,7 +13,6 @@ use std::io::{BufRead, BufReader};
 use structopt::StructOpt;
 
 const MAX_DIST_BTWN_INTERSECTION_AND_SIGNAL: Distance = Distance::const_meters(50.0);
-const MAX_DIST_BTWN_BLDG_PERMIT_AND_BLDG: Distance = Distance::const_meters(10.0);
 
 #[derive(StructOpt, Debug)]
 #[structopt(name = "convert_osm")]
@@ -26,10 +25,6 @@ pub struct Flags {
     #[structopt(long = "traffic_signals", default_value = "")]
     pub traffic_signals: String,
 
-    /// KML with residential building permits. Optional.
-    #[structopt(long = "residential_buildings", default_value = "")]
-    pub residential_buildings: String,
-
     /// ExtraShapes file with blockface, produced using the kml crate. Optional.
     #[structopt(long = "parking_shapes", default_value = "")]
     pub parking_shapes: String,
@@ -67,9 +62,6 @@ pub fn convert(flags: &Flags, timer: &mut abstutil::Timer) -> raw_data::Map {
     // Do this after removing stuff.
     map.compute_gps_bounds();
 
-    if !flags.residential_buildings.is_empty() {
-        handle_residences(&mut map, &flags.residential_buildings, timer);
-    }
     if !flags.parking_shapes.is_empty() {
         use_parking_hints(&mut map, &flags.parking_shapes, timer);
     }
@@ -175,49 +167,6 @@ fn handle_traffic_signals(map: &mut raw_data::Map, path: &str, timer: &mut Timer
     timer.stop("handle traffic signals");
 }
 
-fn handle_residences(map: &mut raw_data::Map, path: &str, timer: &mut Timer) {
-    timer.start("match residential permits with buildings");
-
-    let mut closest: FindClosest<usize> = FindClosest::new(&map.gps_bounds.to_bounds());
-    for (idx, b) in map.buildings.iter().enumerate() {
-        // TODO Ew, have to massage into Pt2D.
-        closest.add_gps(idx, &b.points, &map.gps_bounds);
-    }
-
-    let shapes = kml::load(path, &map.gps_bounds, timer)
-        .expect("loading residential buildings failed")
-        .shapes;
-    timer.start_iter("handle residential permits", shapes.len());
-    for shape in shapes.into_iter() {
-        timer.next();
-        if shape.points.len() > 1 {
-            panic!(
-                "Residential building permit has multiple points: {:?}",
-                shape
-            );
-        }
-        let pt = shape.points[0];
-        if !map.gps_bounds.contains(pt) {
-            continue;
-        }
-        if let Some(num) = shape
-            .attributes
-            .get("net_units")
-            .and_then(|n| usize::from_str_radix(n, 10).ok())
-        {
-            if let Some((idx, _)) = closest.closest_pt(
-                Pt2D::from_gps(pt, &map.gps_bounds).unwrap(),
-                MAX_DIST_BTWN_BLDG_PERMIT_AND_BLDG,
-            ) {
-                // Just blindly override with the latest point. The dataset says multiple permits
-                // per building might exist.
-                map.buildings[idx].num_residential_units = Some(num);
-            }
-        }
-    }
-    timer.stop("match residential permits with buildings");
-}
-
 fn read_osmosis_polygon(path: &str) -> Vec<LonLat> {
     let mut pts: Vec<LonLat> = Vec::new();
     for (idx, maybe_line) in BufReader::new(File::open(path).unwrap())

convert_osm/src/osm.rs

@@ -63,7 +63,6 @@ pub fn osm_to_raw_roads(
                 osm_way_id: way.id,
                 points: pts,
                 osm_tags: tags,
-                num_residential_units: None,
             });
         } else if let Some(at) = get_area_type(&tags) {
             areas.push(raw_data::Area {

docs/design/notes/map_model.md

@@ -93,8 +93,6 @@ is the source of truth.
   - Neighborhood boundaries
 - http://data-seattlecitygis.opendata.arcgis.com/datasets/blockface
   - Blockfaces, used to determine where on-street parking lanes are
-- https://data-seattlecitygis.opendata.arcgis.com/datasets/residential-building-permits-issued-and-final
-  - Number of units per residential building
 
 ## Conversion process
 

editor/src/helpers.rs

@@ -154,9 +154,6 @@ impl ID {
                     "Dist along sidewalk: {}",
                     b.front_path.sidewalk.dist_along()
                 ));
-                if let Some(units) = b.num_residential_units {
-                    txt.add_line(format!("{} residential units", units));
-                }
                 styled_kv(&mut txt, &b.osm_tags);
             }
             ID::Car(id) => {

import.sh

@@ -35,13 +35,6 @@ if [ ! -f data/input/neighborhoods.geojson ]; then
 		data/input/neighborhoods.geojson;
 fi
 
-if [ ! -f data/input/residential_buildings.kml ]; then
-	# From https://data-seattlecitygis.opendata.arcgis.com/datasets/residential-building-permits-issued-and-final
-	get_if_needed \
-		https://opendata.arcgis.com/datasets/cb8c492055a44f2f9de427e0518f9246_0.kml \
-		data/input/residential_buildings.kml;
-fi
-
 if [ ! -f data/input/Seattle.osm ]; then
 	get_if_needed \
 		http://download.bbbike.org/osm/bbbike/Seattle/Seattle.osm.gz \
@@ -95,7 +88,6 @@ for poly in `ls ../data/polygons/`; do
 	RUST_BACKTRACE=1 cargo run --release -- \
 		--osm=../data/input/$name.osm \
 		--traffic_signals=../data/input/traffic_signals.kml \
-		--residential_buildings=../data/input/residential_buildings.kml \
 		--parking_shapes=../data/shapes/blockface.bin \
 		--gtfs=../data/input/google_transit_2018_18_08 \
 		--neighborhoods=../data/input/neighborhoods.geojson \
@@ -103,4 +95,4 @@ for poly in `ls ../data/polygons/`; do
 		--output=../data/raw_maps/$name.bin
 done
 
-# To run manually: cargo run -- --osm=../data/input/montlake.osm --traffic_signals=../data/input/traffic_signals.kml --residential_buildings=../data/input/residential_buildings.kml --parking_shapes=../data/shapes/blockface.bin --gtfs=../data/input/google_transit_2018_18_08 --neighborhoods=../data/input/neighborhoods.geojson --clip=../data/polygons/montlake.poly --output=../data/raw_maps/montlake.bin --fast_dev
+# To run manually: cargo run -- --osm=../data/input/montlake.osm --traffic_signals=../data/input/traffic_signals.kml --parking_shapes=../data/shapes/blockface.bin --gtfs=../data/input/google_transit_2018_18_08 --neighborhoods=../data/input/neighborhoods.geojson --clip=../data/polygons/montlake.poly --output=../data/raw_maps/montlake.bin --fast_dev

map_model/src/building.rs

@@ -23,21 +23,12 @@ pub struct FrontPath {
     pub line: Line,
 }
 
-#[derive(Clone, Copy, Debug, Eq, Hash, PartialEq, Serialize, Deserialize)]
-pub enum BuildingType {
-    Residence,
-    Business,
-    Unknown,
-}
-
 #[derive(Serialize, Deserialize, Debug)]
 pub struct Building {
     pub id: BuildingID,
-    pub building_type: BuildingType,
     pub polygon: Polygon,
     pub osm_tags: BTreeMap<String, String>,
     pub osm_way_id: i64,
-    pub num_residential_units: Option<usize>,
 
     pub front_path: FrontPath,
 }

map_model/src/lib.rs

@@ -16,7 +16,7 @@ mod traversable;
 mod turn;
 
 pub use crate::area::{Area, AreaID, AreaType};
-pub use crate::building::{Building, BuildingID, BuildingType, FrontPath};
+pub use crate::building::{Building, BuildingID, FrontPath};
 pub use crate::bus_stop::{BusRoute, BusRouteID, BusStop, BusStopID};
 pub use crate::edits::MapEdits;
 pub use crate::intersection::{Intersection, IntersectionID, IntersectionType};

map_model/src/make/buildings.rs

@@ -1,8 +1,8 @@
 use crate::make::sidewalk_finder::find_sidewalk_points;
-use crate::{raw_data, Building, BuildingID, BuildingType, FrontPath, Lane};
+use crate::{raw_data, Building, BuildingID, FrontPath, Lane};
 use abstutil::Timer;
 use geom::{Bounds, Distance, GPSBounds, HashablePt2D, Line, Polygon, Pt2D};
-use std::collections::{BTreeMap, HashSet};
+use std::collections::HashSet;
 
 pub fn make_all_buildings(
     results: &mut Vec<Building>,
@@ -46,7 +46,6 @@ pub fn make_all_buildings(
             let id = BuildingID(results.len());
             results.push(Building {
                 id,
-                building_type: classify(input[idx].num_residential_units, &input[idx].osm_tags),
                 polygon: Polygon::new(&points),
                 osm_tags: input[idx].osm_tags.clone(),
                 osm_way_id: input[idx].osm_way_id,
@@ -55,7 +54,6 @@ pub fn make_all_buildings(
                     sidewalk: *sidewalk_pos,
                     line,
                 },
-                num_residential_units: input[idx].num_residential_units,
             });
         }
     }
@@ -83,30 +81,3 @@ fn trim_front_path(bldg_points: &Vec<Pt2D>, path: Line) -> Line {
     // Just give up
     path
 }
-
-fn classify(num_residential_units: Option<usize>, tags: &BTreeMap<String, String>) -> BuildingType {
-    if num_residential_units.is_some() {
-        return BuildingType::Residence;
-    }
-    if tags.get("building") == Some(&"apartments".to_string()) {
-        return BuildingType::Residence;
-    }
-    if tags.get("building") == Some(&"residential".to_string()) {
-        return BuildingType::Residence;
-    }
-    if tags.get("building") == Some(&"house".to_string()) {
-        return BuildingType::Residence;
-    }
-
-    if tags.contains_key(&"shop".to_string()) || tags.contains_key(&"amenity".to_string()) {
-        return BuildingType::Business;
-    }
-    if tags.get("building") == Some(&"commercial".to_string()) {
-        return BuildingType::Business;
-    }
-    if tags.get("building") == Some(&"retail".to_string()) {
-        return BuildingType::Business;
-    }
-
-    BuildingType::Unknown
-}

map_model/src/raw_data.rs

@@ -162,7 +162,6 @@ pub struct Building {
     pub points: Vec<LonLat>,
     pub osm_tags: BTreeMap<String, String>,
     pub osm_way_id: i64,
-    pub num_residential_units: Option<usize>,
 }
 
 #[derive(Clone, PartialEq, Debug, Serialize, Deserialize)]

synthetic/src/lib.rs

@@ -365,7 +365,6 @@ impl Model {
                 points: b.polygon().points().iter().map(|p| pt(*p)).collect(),
                 osm_tags,
                 osm_way_id: idx as i64,
-                num_residential_units: None,
             });
         }
 

tests/src/map_conversion.rs

@@ -8,7 +8,6 @@ pub fn run(t: &mut TestRunner) {
         let flags = convert_osm::Flags {
             osm: "../data/input/montlake.osm".to_string(),
             traffic_signals: "../data/input/traffic_signals.kml".to_string(),
-            residential_buildings: "../data/input/residential_buildings.kml".to_string(),
             parking_shapes: "../data/shapes/blockface.bin".to_string(),
             gtfs: "../data/input/google_transit_2018_18_08".to_string(),
             neighborhoods: "../data/input/neighborhoods.geojson".to_string(),