Mask out Skyttehøj and everything south of it (lat 55.628)

Add south_bound_lat to modes.yaml and a load_south_bound() helper in prepare.py. When set, the area geometry is intersected with the north half-plane above the cutoff, so all downstream clipping (lines, stops, stations) cascades automatically. Removed: 94 bus stops (including Skyttehøj), 1 station (Vestamager), and line segments south of the boundary (Metro M1 tail, buses 32-36).
Add bus whitelist, route exclusions, crow-fly shape filter, and KML export
2026-09-18 00:32:02 +02:00 · 2026-09-18 00:24:37 +02:00
5 changed files with 632 additions and 4 deletions
@@ -4,10 +4,11 @@ copenhagen/data/processed/**
 !copenhagen/data/raw/.gitkeep
 !copenhagen/data/processed/.gitkeep
-# Generated map outputs (regenerable via render.py)
+# Generated map outputs (regenerable via render.py / export_google_mymaps.py)
 copenhagen/output/*.png
 copenhagen/output/*.svg
 copenhagen/output/*.pdf
 copenhagen/output/*.kml
 # Python
 .venv/
@@ -0,0 +1,251 @@
 <?xml version='1.0' encoding='utf-8'?>
 <kml xmlns="http://www.opengis.net/kml/2.2">
  <Document>
    <name>Coastline (from Hide+Seek Copenhagen City Pass map)</name>
    <StyleMap id="line-01579B-3131-nodesc">
      <Pair>
        <key>normal</key>
        <styleUrl>#line-01579B-3131-nodesc-normal</styleUrl>
      </Pair>
      <Pair>
        <key>highlight</key>
        <styleUrl>#line-01579B-3131-nodesc-highlight</styleUrl>
      </Pair>
    </StyleMap>
    <Style id="line-01579B-3131-nodesc-highlight">
      <LineStyle>
        <color>ff9b5701</color>
        <width>4.6965</width>
      </LineStyle>
      <BalloonStyle>
        <text>&lt;h3&gt;$[name]&lt;/h3&gt;</text>
      </BalloonStyle>
    </Style>
    <Style id="line-01579B-3131-nodesc-normal">
      <LineStyle>
        <color>ff9b5701</color>
        <width>3.131</width>
      </LineStyle>
      <BalloonStyle>
        <text>&lt;h3&gt;$[name]&lt;/h3&gt;</text>
      </BalloonStyle>
    </Style>
    <Folder>
      <name>Coastline</name>
      <Placemark>
        <name>Coastline</name>
        <styleUrl>#line-01579B-3131-nodesc</styleUrl>
        <LineString>
          <tessellate>1</tessellate>
          <coordinates>
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          </coordinates>
        </LineString>
      </Placemark>
    </Folder>
  </Document>
 </kml>
@@ -13,6 +13,28 @@
 # ORDER MATTERS: the styles listed here are also the priority order when a
 # pole is served by several modes (e.g. S-tog and regional trains share
 # platforms at hub stations — the higher style wins).
 # Hard exclusions: specific routes to drop entirely, keyed by (agency,
 # short name) — the pairing rule used everywhere else in this feed.
 # 083 (Snälltåget night train, Malmö-Stockholm): its in-area shapes are
 # sparse crow-fly stubs that draw as straight cuts across the map; the
 # long-distance train is not relevant for the city game, so skip it.
 # Bus whitelist: only these buses are included — there are far more city
 # bus routes than the game scale needs. Match on bus category (per
 # styling.yaml bus_filters) or on specific refs. Remove this section to
 # include all buses; with empty lists no buses are included.
 bus_whitelist:
  categories: [A]   # all "A" city buses (1A, 2A, 4A, 6A, 9A, ...)
  refs: ["21", "30", "31", "32", "33", "34", "35", "36", "37", "38", "39", "68", "77"]
 exclude:
  - agency: Snälltåget AB
    ref: "083"
 # South bound: drop every stop/station south of this latitude (inclusive),
 # and clip transit lines at this boundary. Used to cut the map short of
 # Skyttehøj (Amager Landevej) and everything south of it on Amager.
 south_bound_lat: 55.628
 modes:
  metro:
    agencies: [Metroselskabet]
@@ -0,0 +1,257 @@
 #!/usr/bin/env python3
 """Export the master GeoPackage to a Google My Maps-importable KML.
 Reads (from data/processed): master.gpkg (lines, stops, stations), area.gpkg
 Read (from config): coastline.kml — the coastline layer extracted verbatim
 from the reference map
 (https://www.google.com/maps/d/u/0/kml?mid=17T6ZDYbGz72h_eteL-CxdkiaXcgDLEA&forcekml=1)
 Writes: output/copenhagen-mymaps.kml
 My Maps turns each top-level KML Folder into a layer on import. We emit:
    Bus stops / Bus routes
    Train stations / Train routes   (metro + S-tog + light rail + regional)
    Ferry stops / Ferry routes
    City Pass boundary (outline + faint fill)
    Coastline (verbatim from the reference map's layer)
 Colours match the PNG map: routes use colour_final from prepare.py; stop
 icons use styling.yaml palette defaults (train stations match the reference
 map's red pin). Import manually in Google My Maps:
 Create map → Import → upload the .kml.
 """
 import re
 import sys
 import xml.etree.ElementTree as ET
 import geopandas as gpd
 import yaml
 from _common import CONFIG, OUTPUT, PROCESSED
 KML = "http://www.opengis.net/kml/2.2"
 ET.register_namespace("", KML)
 # My Maps stock pin (same as the reference map uses); tinted via IconStyle.
 ICON_HREF = "https://www.gstatic.com/mapspro/images/stock/503-wht-blank_maps.png"
 ICON_SCALE = 1.0
 TRAIN_STATION_COLOR = "#C2185B"  # reference map's station-pin red
 TRAIN_STYLES = ["metro", "s_tog", "light_rail", "regional"]
 # route line widths in pixels, per style
 LINE_WIDTH = {
    "metro": 4.5,
    "s_tog": 4.25,
    "light_rail": 4.25,
    "regional": 3.5,
    "ferry": 3.75,
    "bus": 2.75,
 }
 BOUNDARY_COLOR = "#006064"
 BOUNDARY_LINE_WIDTH = 3.0
 BOUNDARY_FILL_ALPHA = 0x54  # ~33 %
 class Styles:
    """Registry of unique (kind, color, width) -> KML <Style> ids."""
    def __init__(self):
        self._map = {}
    def get(self, kind, color_hex, width=0.0):
        key = (kind, color_hex, width)
        if key not in self._map:
            self._map[key] = f"s{len(self._map):03d}"
        return self._map[key]
    def elements(self):
        """Yield <Style> elements for everything registered so far."""
        by_id = sorted(self._map.items(), key=lambda kv: kv[1])
        for (kind, color_hex, width), sid in by_id:
            st = ET.Element(f"{{{KML}}}Style", id=sid)
            if kind == "icon":
                el = ET.SubElement(st, f"{{{KML}}}IconStyle")
                el.append(_tex("color", kml_color(color_hex)))
                el.append(_tex("scale", str(ICON_SCALE)))
                icon = ET.SubElement(el, f"{{{KML}}}Icon")
                icon.append(_tex("href", ICON_HREF))
            else:
                el = ET.SubElement(st, f"{{{KML}}}LineStyle")
                el.append(_tex("color", kml_color(color_hex)))
                el.append(_tex("width", str(width)))
                if kind == "poly":
                    poly = ET.SubElement(st, f"{{{KML}}}PolyStyle")
                    poly.append(_tex("color", kml_color(color_hex, BOUNDARY_FILL_ALPHA)))
            balloon = ET.SubElement(st, f"{{{KML}}}BalloonStyle")
            balloon.append(_tex("text", "<h3>$[name]</h3>"))
            yield st
 def _tex(tag, value):
    el = ET.Element(f"{{{KML}}}{tag}")
    el.text = value
    return el
 def kml_color(hex_color, alpha=0xFF):
    """#RRGGBB -> KML AABBGGRR."""
    h = hex_color.lstrip("#")
    return f"{alpha:02x}{h[4:6]}{h[2:4]}{h[0:2]}"
 def placemark(folder_el, name, sid, geom_el):
    pm = ET.SubElement(folder_el, f"{{{KML}}}Placemark")
    pm.append(_tex("name", str(name)))
    pm.append(_tex("styleUrl", f"#{sid}"))
    pm.append(geom_el)
 def point_el(geom):
    pt = ET.Element(f"{{{KML}}}Point")
    pt.append(_tex("coordinates", f"{geom.x:.7f},{geom.y:.7f}"))
    return pt
 def linestring_el(geom):
    ls = ET.Element(f"{{{KML}}}LineString")
    ls.append(_tex("tessellate", "1"))
    ls.append(_tex("coordinates", " ".join(f"{x:.7f},{y:.7f}" for x, y in geom.coords)))
    return ls
 def polygon_el(geom):
    pg = ET.Element(f"{{{KML}}}Polygon")
    pg.append(_tex("tessellate", "1"))
    outer = ET.SubElement(pg, f"{{{KML}}}outerBoundaryIs")
    ring = ET.SubElement(outer, f"{{{KML}}}LinearRing")
    ring.append(_tex("coordinates", " ".join(f"{x:.7f},{y:.7f}" for x, y in geom.exterior.coords)))
    for inner in geom.interiors:
        b = ET.SubElement(pg, f"{{{KML}}}innerBoundaryIs")
        ring = ET.SubElement(b, f"{{{KML}}}LinearRing")
        ring.append(_tex("coordinates", " ".join(f"{x:.7f},{y:.7f}" for x, y in inner.coords)))
    return pg
 def multi_el(geom, single):
    """Wrap (Multi)Geometry into a KML element (MultiGeometry if needed)."""
    geoms = list(getattr(geom, "geoms", [geom]))
    if len(geoms) == 1:
        return single(geoms[0])
    mg = ET.Element(f"{{{KML}}}MultiGeometry")
    for g in geoms:
        mg.append(single(g))
    return mg
 def add_folder(document, name):
    f = ET.SubElement(document, f"{{{KML}}}Folder")
    f.append(_tex("name", name))
    return f
 def add_stops_folder(document, name, gdf, tint, styles):
    f = add_folder(document, name)
    sid = styles.get("icon", tint)
    for _, row in gdf.sort_values("name").iterrows():
        placemark(f, row["name"], sid, point_el(row.geometry))
    return len(gdf)
 def add_routes_folder(document, name, gdf, styles):
    f = add_folder(document, name)
    for _, row in gdf.iterrows():
        sid = styles.get("line", row["colour_final"], LINE_WIDTH[row["style"]])
        placemark(f, f'{row["ref"]} {row["name"]}', sid, multi_el(row.geometry, linestring_el))
    return len(gdf)
 def add_boundary_folder(document, area_geom, styles):
    f = add_folder(document, "City Pass boundary")
    sid = styles.get("poly", BOUNDARY_COLOR, BOUNDARY_LINE_WIDTH)
    placemark(f, "City Pass boundary", sid, multi_el(area_geom, polygon_el))
    return 1
 def append_coastline(document):
    """Append the verbatim coastline layer stored in config/coastline.kml."""
    src = ET.parse(CONFIG / "coastline.kml").getroot().find(f"{{{KML}}}Document")
    n = 0
    for el in src:
        if el.tag == f"{{{KML}}}Folder":
            document.append(el)
            n = len(el.findall(f"{{{KML}}}Placemark"))
        elif el.tag in (f"{{{KML}}}Style", f"{{{KML}}}StyleMap"):
            document.append(el)
    return n
 def natural_key(ref):
    return tuple(int(t) if t.isdigit() else t for t in re.split(r"(\d+)", str(ref)))
 def main():
    lines = gpd.read_file(PROCESSED / "master.gpkg", layer="lines")
    stops = gpd.read_file(PROCESSED / "master.gpkg", layer="stops")
    stations = gpd.read_file(PROCESSED / "master.gpkg", layer="stations")
    area = gpd.read_file(PROCESSED / "area.gpkg").geometry.union_all()
    styling = yaml.safe_load((CONFIG / "styling.yaml").read_text())
    palette = styling["palette"]
    kml = ET.Element(f"{{{KML}}}kml")
    document = ET.SubElement(kml, f"{{{KML}}}Document")
    document.append(_tex("name", "Kurragömma Köpenhamn"))
    styles = Styles()
    counts = {}
    counts["Bus stops"] = add_stops_folder(
        document, "Bus stops", stops[stops["style"] == "bus"],
        palette["bus"]["default"], styles,
    )
    bus_lines = lines[lines["style"] == "bus"].copy()
    bus_lines["_k"] = bus_lines["ref"].map(natural_key)
    counts["Bus routes"] = add_routes_folder(
        document, "Bus routes", bus_lines.sort_values("_k"), styles
    )
    counts["Train stations"] = add_stops_folder(
        document, "Train stations", stations, TRAIN_STATION_COLOR, styles
    )
    train = lines[lines["style"].isin(TRAIN_STYLES)].copy()
    train["_order"] = train["style"].map(TRAIN_STYLES.index)
    train["_k"] = train["ref"].map(natural_key)
    counts["Train routes"] = add_routes_folder(
        document, "Train routes", train.sort_values(["_order", "_k"]), styles
    )
    counts["Ferry stops"] = add_stops_folder(
        document, "Ferry stops", stops[stops["style"] == "ferry"],
        palette["ferry"]["default"], styles,
    )
    ferry_lines = lines[lines["style"] == "ferry"].sort_values("ref")
    counts["Ferry routes"] = add_routes_folder(document, "Ferry routes", ferry_lines, styles)
    counts["City Pass boundary"] = add_boundary_folder(document, area, styles)
    counts["Coastline"] = append_coastline(document)
    # <Style> elements belong before the first <Folder> (KML resolves style
    # ids regardless of order; this is conventional + nicer on the eyes).
    insert_at = list(document).index(document.find(f"{{{KML}}}name")) + 1
    for offset, st in enumerate(styles.elements()):
        document.insert(insert_at + offset, st)
    out = OUTPUT / "copenhagen-mymaps.kml"
    tree = ET.ElementTree(kml)
    ET.indent(tree, space="  ")
    tree.write(out, encoding="utf-8", xml_declaration=True)
    print(f"wrote {out}")
    for n, c in counts.items():
        print(f"  {n}: {c} placemarks")
 if __name__ == "__main__":
    main()
@@ -30,6 +30,7 @@ import sys
 import geopandas as gpd
 import pandas as pd
 import yaml
 from shapely.geometry import box
 from _common import CONFIG, GTFS_RAW, PROCESSED
@@ -39,10 +40,47 @@ STATION_STYLES = {"metro", "s_tog", "light_rail", "regional"}
 # within this distance. Routes have variants; without this check a stop can
 # end up further from the map than the variant we chose not to draw.
 STOP_LINE_MARGIN_M = 300
 # Shapes sparser than this (points per km) are "crow-fly" placeholders from
 # the feed (a handful of points for a several-hundred-km line) — they render
 # as straight cuts across the map. Real rail/bus geometry is >= 0.5 pts/km.
 MIN_SHAPE_POINTS_PER_KM = 0.05
 def load_modes():
-    return yaml.safe_load((CONFIG / "modes.yaml").read_text())["modes"]
+    return _load_modes_yaml().get("modes", {})
 def load_exclude():
    """Hard route blacklist from modes.yaml: list of (agency, ref)."""
    return [(e["agency"], str(e["ref"]))
            for e in _load_modes_yaml().get("exclude", [])]
 def load_bus_whitelist():
    """Bus whitelist from modes.yaml: dict with categories/refs sets.
    Returns None when the section is absent (= include all buses).
    """
    wl = _load_modes_yaml().get("bus_whitelist")
    if wl is None:
        return None
    return {
        "categories": set(wl.get("categories") or []),
        "refs": {str(r) for r in (wl.get("refs") or [])},
    }
 def load_south_bound():
    """South latitude cutoff from modes.yaml, or None.
    When set, stops/stations south of (and transit lines below) this
    latitude are dropped. Used to trim the map at a boundary.
    """
    return _load_modes_yaml().get("south_bound_lat")
 def _load_modes_yaml():
    return yaml.safe_load((CONFIG / "modes.yaml").read_text())
 def load_styling():
@@ -66,7 +104,7 @@ def classify(agency, route_type, modes):
    return None
-def load_routes(modes):
+def load_routes(modes, exclude=()):
    """route_colors.csv joined with agency names and classified by style."""
    agencies = pd.read_csv(GTFS_RAW / "agency.txt", dtype=str)
    agency_names = dict(zip(agencies["agency_id"], agencies["agency_name"]))
@@ -77,6 +115,17 @@ def load_routes(modes):
        classify(a, t, modes)
        for a, t in zip(routes["agency_name"], routes["route_type"])
    ]
    if exclude:
        mask = [
            (a, str(r)) in set(exclude)
            for a, r in zip(routes["agency_name"], routes["route_short_name"])
        ]
        n = sum(mask)
        if n:
            routes.loc[mask, "style"] = None
            print(f"excluded by modes.yaml: {n} route(s) "
                  f"({sorted(set(zip(routes.loc[mask, 'agency_name'], routes.loc[mask, 'route_short_name'])) )})",
                  flush=True)
    return routes
@@ -99,6 +148,15 @@ def resolve_colour(style, ref, bus_category, gtfs_colour, palette):
    return p.get(ref) or p.get("default")
 def shape_points_per_km(shapes_25832):
    """Point density per shape. Geometries are projected (metres)."""
    def n_pts(geom):
        geoms = getattr(geom, "geoms", [geom])
        return sum(len(g.coords) for g in geoms)
    pts = shapes_25832.geometry.map(n_pts)
    return pts / (shapes_25832.geometry.length / 1000.0).clip(lower=1e-6)
 def build_lines(routes, styling, area_geom, trips, st, area_stop_ids):
    """One feature per (style, ref, direction).
@@ -108,6 +166,20 @@ def build_lines(routes, styling, area_geom, trips, st, area_stop_ids):
    """
    shapes = gpd.read_file(PROCESSED / "gtfs_shapes.gpkg")
    # The feed contains a few "crow-fly" placeholder shapes for long-distance
    # trains (e.g. Snälltåget, 6-8 points for ~700 km). Those draw as
    # straight lines across the map and can shadow the proper rail-geometry
    # shape in coverage comparison. Drop below a point-density floor;
    # real shapes are >= 0.5 pts/km, placeholders are ~0.01 pts/km, and even
    # the 0.44 km ferry 993 (a handful of points over 440 m) stays well above.
    shapes = shapes.to_crs(LENGTH_CRS)
    pts_km = shape_points_per_km(shapes)
    degenerate = pts_km < MIN_SHAPE_POINTS_PER_KM
    if degenerate.any():
        print(f"dropping {int(degenerate.sum())} degenerate (crow-fly) "
              f"shapes (<{MIN_SHAPE_POINTS_PER_KM:g} pts/km)", flush=True)
    shapes = shapes[~degenerate].to_crs("EPSG:4326")
    shape_rows = trips.dropna(subset=["shape_id"]).drop_duplicates("shape_id")
    shape_direction = dict(zip(shape_rows["shape_id"], shape_rows["direction_id"]))
@@ -269,7 +341,32 @@ def main():
    styling = load_styling()
    area_geom = load_area()
-    routes = load_routes(modes)
+    south_bound = load_south_bound()
    if south_bound is not None:
        north = box(-180, south_bound, 180, 90)
        area_geom = area_geom.intersection(north)
        print(f"south bound: clipping area at lat {south_bound}", flush=True)
    routes = load_routes(modes, load_exclude())
    bus_wl = load_bus_whitelist()
    if bus_wl is not None:
        patterns = styling["bus_filters"]["categories"]
        is_bus = routes["style"] == "bus"
        keep = routes["route_short_name"].map(
            lambda r: str(r) in bus_wl["refs"]
                      or categorise_bus(r, patterns) in bus_wl["categories"]
        )
        routes.loc[is_bus & ~keep, "style"] = None
        kept = sorted(
            routes.loc[is_bus & keep, "route_short_name"].unique(),
            key=lambda s: [int(t) if t.isdigit() else t
                           for t in re.split(r"(\d+)", str(s))],
        )
        print(f"bus whitelist: kept {len(kept)} of "
              f"{int(is_bus.sum())} bus refs: {', '.join(kept)}",
              flush=True)
    print(f"routes classified: {routes['style'].notna().sum()} of "
          f"{len(routes)} map to a style", flush=True)