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154b9f9fb5cd35185a204104b3f58c2b71f7b9a4
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5 Commits
Author SHA1 Message Date
marvin 154b9f9fb5 Make station labels opt-in; add station markers (symbols without text) 
- labels: off by default (was on). Enable via --labels flag or
  styling.yaml labels.show: true. Previously --no-labels opted out.
- stations: new markers layer -- small white-filled circles with dark
  border at each station, sized by mode (metro 3.5pt, s_tog 3.0pt,
  regional 2.5pt). On by default; disable via --no-stops.
- markers respect --modes filter (only mark stations for drawn layers)
- styling.yaml: add stations section (shape/fill/edge/size/linewidth)
- classify_station() helper deduplicates the metro/s_tog/regional logic
- fix attribution to Esri (was CARTO)
 2026-09-13 22:37:50 +02:00
marvin 0ec288bfd0 Switch basemap to ESRI WorldGrayCanvas (OSM tiles blocked) 
OSM's tile server blocks apps without a valid identifying User-Agent
(contextily's default is a random UUID, which OSM rejects with an
'Access blocked' error tile). Switched to ESRI WorldGrayCanvas, a free
no-key light-gray basemap comparable to CartoDB Positron, and set a
proper User-Agent header (jetlag-maps/0.1) on contextily requests per
OSM tile usage policy.
 2026-09-13 22:32:16 +02:00
marvin 4b85e93e6c Copenhagen Phase 3: render.py -> PNG/SVG/PDF map 
- render.py: parameterized CLI (--modes, --no-buses, --bus-subset,
  --max-bus-routes, --dpi, --size, --format, --out, --no-basemap, --no-labels)
- basemap: OSM standard tiles via contextily (EPSG:3857)
- two-tone lines: dark casing + colour body per route, z-order
  bus->s_tog->light_rail->regional->metro
- shapeburst fade mask outside City Pass area (distance-transform alpha)
- station labels for metro + S-tog via adjustText
- title + attribution
- styling.yaml: switch basemap to OpenStreetMap.Mapnik (CartoDB now needs API key)
- .gitignore: exclude generated outputs (regenerable via render.py)
- verified: full map, --no-buses, --bus-subset, --modes, SVG all work
 2026-09-13 01:27:55 +02:00
marvin 0086d8a308 Copenhagen Phase 2: prepare.py merges + clips + colours -> master.gpkg 
- prepare.py: merge per-mode OSM lines, resolve colours
  (GTFS route_color -> OSM colour tag -> keyed palette, robust to pd.NA),
  categorise buses (A/C/S/regular via regex), clip lines+stops to area,
  write master.gpkg layers (lines/stops/stations)
- download_osm.py: add stations query (public_transport=station /
  railway=station nodes+areas, out center) -> stations.gpkg with proper
  human-readable names + subway/light_rail mode tags for labelling
- verified: 135 lines (8 metro/16 s-tog/28 regional/83 bus), 90 named
  stations, zero NaN colours
 2026-09-13 01:19:34 +02:00
marvin ac02320f1d Copenhagen Phase 1: scaffolding + area + OSM download 
- pyproject.toml with all deps (geopandas, contextily, partridge, etc.)
- config/: area.json (3 OSM boundary relations), modes.yaml (subway/s_tog/
  light_rail/regional/bus, S-tog scoped to route=light_rail network=Takst),
  styling.yaml (zorder/widths/colours/palette/mask/labels)
- build_area.py: fetch 3 relations via OSM API, stitch rings, dissolve to
  area.gpkg/area.geojson (City Pass approximation)
- download_osm.py: per-mode Overpass (mirror+backoff, out geom + recurse for
  stops), writes {mode}.gpkg (lines+stops) + query text
- download_gtfs.py / gtfs_to_geopackage.py: stubs (blocked on Rejseplanen)
- data/ gitignored (regenerable); output/ tracked
 2026-09-13 01:15:25 +02:00